Biomarkers and methods for determining sensitivity to microtubule-stabilizing agents

Abstract

Biomarkers that are useful for identifying a mammal that will respond therapeutically or is responding therapeutically to a method of treating cancer that comprises administering a microtubule-stabilizing agent. In one aspect, the cancer is breast cancer, and the microtubule-stabilizing agent is an epothilone or analog or derivative thereof, or ixabepilone.

Description

SEQUENCE LISTING

A compact disc labeled “Copy 1” contains the Sequence Listing as 10338 NP.ST25.txt. The Sequence Listing is 1686 KB in size and was recorded Nov. 29, 2005. The compact disk is 1 of 2 compact disks. A duplicate copy of the compact disc is labeled “Copy 2” and is 2 of 2 compact discs.

The compact disc and duplicate copy are identical and are hereby incorporated by reference into the present application.

FIELD OF THE INVENTION

The present invention relates generally to the field of pharmacogenomics, and more specifically to methods and procedures to determine drug sensitivity in patients to allow the identification of individualized genetic profiles which will aid in treating diseases and disorders.

BACKGROUND OF THE INVENTION

Cancer is a disease with extensive histoclinical heterogeneity. Although conventional histological and clinical features have been correlated to prognosis, the same apparent prognostic type of tumors varies widely in its responsiveness to therapy and consequent survival of the patient.

New prognostic and predictive markers, which would facilitate an individualization of therapy for each patient, are needed to accurately predict patient response to treatments, such as small molecule or biological molecule drugs, in the clinic. The problem may be solved by the identification of new parameters that could better predict the patient's sensitivity to treatment. The classification of patient samples is a crucial aspect of cancer diagnosis and treatment. The association of a patient's response to a treatment with molecular and genetic markers can open up new opportunities for treatment development in non-responding patients, or distinguish a treatment's indication among other treatment choices because of higher confidence in the efficacy. Further, the pre-selection of patients who are likely to respond well to a medicine, drug, or combination therapy may reduce the number of patients needed in a clinical study or accelerate the time needed to complete a clinical development program (M. Cockett et al., Current Opinion in Biotechnology, 11:602-609 (2000)).

The ability to predict drug sensitivity in patients is particularly challenging because drug responses reflect not only properties intrinsic to the target cells, but also a host's metabolic properties. Efforts to use genetic information to predict drug sensitivity have primarily focused on individual genes that have broad effects, such as the multidrug resistance genes, mdr1 and mrp1 (P. Sonneveld, J. Intern. Med., 247:521-534 (2000)).

The development of microarray technologies for large scale characterization of gene mRNA expression pattern has made it possible to systematically search for molecular markers and to categorize cancers into distinct subgroups not evident by traditional histopathological methods (J. Khan et al., Cancer Res., 58:5009-5013 (1998); A. A. Alizadeh et al., Nature, 403:503-511 (2000); M. Bittner et al., Nature, 406:536-540 (2000); J. Khan et al., Nature Medicine, 7(6):673-679 (2001); T. R. Golub et al., Science, 286:531-537 (1999); U. Alon et al., P. N. A. S. USA, 96:6745-6750 (1999)). Such technologies and molecular tools have made it possible to monitor the expression level of a large number of transcripts within a cell population at any given time (see, e.g., Schena et al., Science, 270:467-470 (1995); Lockhart et al., Nature Biotechnology, 14:1675-1680 (1996); Blanchard et al., Nature Biotechnology, 14:1649 (1996); U.S. Pat. No. 5,569,588 to Ashby et al.).

Recent studies demonstrate that gene expression information generated by microarray analysis of human tumors can predict clinical outcome (L. J. van't Veer et al., Nature, 415:530-536 (2002); T. Sorlie et al., P. N. A. S. USA, 98:10869-10874 (2001); M. Shipp et al., Nature Medicine, 8(1):68-74 (2002); G. Glinsky et al., The Journal of Clin. Invest., 113(6):913-923 (2004)). These findings bring hope that cancer treatment will be vastly improved by better predicting the response of individual tumors to therapy.

Needed are new and alternative methods and procedures to determine drug sensitivity in patients to allow the development of individualized genetic profiles which are necessary to treat diseases and disorders based on patient response at a molecular level.

SUMMARY OF THE INVENTION

The invention provides methods and procedures for determining patient sensitivity to one or more microtubule-stabilizing agents. The invention also provides methods of determining or predicting whether an individual requiring therapy for a disease state such as cancer will or will not respond to treatment, prior to administration of the treatment, wherein the treatment comprises administration of one or more microtubule-stabilizing agents.

In one aspect, the invention provides a method for identifying a mammal that will respond therapeutically to a method of treating cancer comprising administering a microtubule-stabilizing agent, wherein the method comprises: (a) measuring in the mammal the level of at least one biomarker selected from the biomarkers of Table 1 and Table 2; (b) exposing a biological sample from the mammal to the agent; (c) following the exposing in step (b), measuring in said biological sample the level of the at least one biomarker, wherein an increase in the level of the at least one biomarker measured in step (c) compared to the level of the at least one biomarker measured in step (a), predicts that the mammal will respond therapeutically to said method of treating cancer when said biomarker is from Table 1, and predicts that the mammal will not respond therapeutically to said method of treating cancer when said biomarker is from Table 2.

In another aspect, the invention provides a method for determining whether a mammal is responding therapeutically to a microtubule-stabilizing agent, comprising (a) exposing the mammal to the agent; and (b) following the exposing of step (a), measuring in the mammal the level of at least one biomarker selected from the biomarkers of Table 1 and Table 2, wherein an increase in the level of the at least one biomarker measured in step (b), compared to the level of the at least one biomarker in a mammal that has not been exposed to said agent, indicates that the mammal is responding to said agent when said biomarker is from Table 1, and indicates that the mammal is not responding to said agent when said biomarker is from Table 2.

In another aspect, the invention provides a method for predicting whether a mammal will respond therapeutically to a method of treating cancer comprising administering a microtubule-stabilizing agent, wherein the method comprises: (a) exposing a biological sample from the mammal to the microtubule-stabilizing agent; (b) following the exposing of step (a), measuring in said biological sample the level of at least one biomarker selected from the biomarkers of Table 1 or Table 2, wherein an increase in the level of the at least one biomarker measured in step (b), compared to the level of the at least one biomarker in a mammal that has not been exposed to said agent, predicts that the mammal will respond therapeutically to said method of treating cancer when said biomarker is from Table 1, and predicts that the mammal will not respond therapeutically to said method of treating cancer when said biomarker is from Table 2.

In another aspect, the invention provides a method for determining whether an agent stabilizes microtubules and has cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease in a mammal, comprising: (a) exposing the mammal to the agent; and (b) following the exposing of step (a), measuring in the mammal the level of at least one biomarker selected from the biomarkers of Table 1 and Table 2, wherein an increase in the level of said at least one biomarker measured in step (b), compared to the level of the biomarker in a mammal that has not been exposed to said agent, indicates that the agent stabilizes microtubules and has cytotoxic activity against rapidly proliferating cells when said biomarker is from Table 1, and indicates that the agent does not stabilize microtubules and does not have cytotoxic activity against rapidly proliferating cells when said biomarker is from Table 2.

As used herein, respond therapeutically refers to the alleviation or abrogation of the cancer. This means that the life expectancy of an individual affected with the cancer will be increased or that one or more of the symptoms of the cancer will be reduced or ameliorated. The term encompasses a reduction in cancerous cell growth or tumor volume. Whether a mammal responds therapeutically can be measured by many methods well known in the art, such as PET imaging.

The amount of increase in the level of the at least one biomarker measured in the practice of the invention can be readily determined by one skilled in the art. In one aspect, the increase in the level of a biomarker is at least a two-fold difference, at least a three-fold difference, or at least a four-fold difference in the level of the biomarker.

The mammal can be, for example, a human, rat, mouse, dog, rabbit, pig sheep, cow, horse, cat, primate, or monkey.

The method of the invention can be, for example, an in vitro method wherein the step of measuring in the mammal the level of at least one biomarker comprises taking a biological sample from the mammal and then measuring the level of the biomarker(s) in the biological sample. The biological sample can comprise, for example, at least one of whole fresh blood, peripheral blood mononuclear cells, frozen whole blood, fresh plasma, frozen plasma, urine, saliva, skin, hair follicle, bone marrow, or tumor tissue.

The level of the at least one biomarker can be, for example, the level of protein and/or mRNA transcript of the biomarker(s).

The invention also provides an isolated biomarker selected from the biomarkers of Table 1 and Table 2. The biomarkers of the invention comprise sequences selected from the nucleotide and amino acid sequences provided in Table 1 and Table 2 and the Sequence Listing, as well as fragments and variants thereof.

The invention also provides a biomarker set comprising two or more biomarkers selected from the biomarkers of Table 1 and Table 2.

The invention also provides kits for determining or predicting whether a patient would be susceptible or resistant to a treatment that comprises one or more microtubule-stabilizing agents. The patient may have a cancer or tumor such as, for example, a breast cancer or tumor.

In one aspect, the kit comprises a suitable container that comprises one or more specialized microarrays of the invention, one or more microtubule-stabilizing agents for use in testing cells from patient tissue specimens or patient samples, and instructions for use. The kit may further comprise reagents or materials for monitoring the expression of a biomarker set at the level of mRNA or protein.

In another aspect, the invention provides a kit comprising two or more biomarkers selected from the biomarkers of Table 1 and Table 2.

In yet another aspect, the invention provides a kit comprising at least one of an antibody and a nucleic acid for detecting the presence of at least one of the biomarkers selected from the biomarkers of Table 1 and Table 2. In one aspect, the kit further comprises instructions for determining whether or not a mammal will respond therapeutically to a method of treating cancer comprising administering a microtubule-stabilizing agent. In another aspect, the instructions comprise the steps of (a) measuring in the mammal the level of at least one biomarker selected from the biomarkers of Table 1 and Table 2, (b) exposing the mammal to the microtubule-stabilizing agent, (c) following the exposing of step (b), measuring in the mammal the level of the at least one biomarker, wherein a difference in the level of the at least one biomarker measured in step (c) compared to the level of the at least one biomarker measured in step (a) predicts that the mammal will respond therapeutically to said method of treating cancer when said biomarker is from Table 1, and predicts that the mammal will not respond therapeutically to said method of treating cancer when said biomarker is from Table 2.

The invention also provides screening assays for determining if a patient will be susceptible or resistant to treatment with one or more microtubule-stabilizing agents.

The invention also provides a method of monitoring the treatment of a patient having a disease, wherein said disease is treated by a method comprising administering one or more microtubule-stabilizing agents.

The invention also provides individualized genetic profiles which are necessary to treat diseases and disorders based on patient response at a molecular level.

The invention also provides specialized microarrays, e.g., oligonucleotide microarrays or cDNA microarrays, comprising one or more biomarkers having expression profiles that correlate with either sensitivity or resistance to one or more microtubule-stabilizing agents.

The invention also provides antibodies, including polyclonal or monoclonal, directed against one or more biomarkers of the invention.

The invention will be better understood upon a reading of the detailed description of the invention when considered in connection with the accompanying figures.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates classification of breast cancer cell lines based on IC₅₀ values measured against ixabepilone treatment. The cell lines were normalized based on a mean of the log(IC₅₀) values (a dotted line) and divided into two groups defined as sensitive or resistant. The cell lines on the left are defined as sensitive since they are below the mean of the log(IC₅₀)s, and those on the right are defined as resistant since they are above the mean.

FIG. 2 illustrates the error rates generated from each classifier identified. From the GeneCluster analysis, classifiers containing up to 250 genes were determined. Each predictor identified was evaluated with the error rate calculated through the leave-one out cross validation. As shown in FIG. 2, error rates for classifiers (8-250 genes) remain to be the minimum at zero.

FIG. 3 illustrates the error rate calculation on random permutation. Error rates generated from several examples of random classification (random 1-11) using the software GeneCluster are plotted against the predictor sets containing up to 250 genes. As shown in the plot, the error rate calculated based on the IC₅₀-based classification is significantly lower than the error rates based on the random classification.

FIG. 4 illustrates the top 50 genes correlated with sensitivity for ixabepilone. The red and blue matrix represents the normalized expression patterns for each gene across the cell lines (brightest red indicates highest relative expression, darkest blue indicates lowest relative expression).

FIG. 5 illustrates gene expression level of microtubule associated protein, tau and estrogen receptor (also referred to herein as estrogen receptor 1, ER, and ER1). In order to explore the relationship between Tau and ER, gene expression levels of the two are plotted for each cell line. Tau expression levels are shown as a bar, and ER as a line.

FIG. 6 illustrates gene expression patterns of top 50 genes in 175 primary breast tumors. The red and green matrix represents the normalized expression patterns for each gene across the 175 primary breast tumors (brightest red indicates highest relative expression, green indicates lowest relative expression). A subset of tumors in a blue box shows relative high expression of the top 25 markers which expressed highly in the sensitive cell lines. On the other hand, the tumors in a magenta box show relatively high expression of the 25 genes expressed at elevated levels in the resistant cell lines.

FIG. 7 illustrates MAP tau and ER expression in breast tumors. In order to see the expression patterns of Tau and ER within tumors, their expression levels are plotted together. Tau is shown as a line, and ER as a bar. Tumors are arranged in an increasing order of Tau expression level. There seems to be a subset of tumors that express these genes highly, which suggest these are non-responders for ixabepilone.

FIG. 8 illustrates the biological networks implied in the mechanism of resistance to ixabepilone as determined by Ingenuity® pathway analysis using 200 preclinical candidate markers. There are nine major networks indicated above with their significance scores. As shown, ER pathway is the most implicated network.

FIG. 9 illustrates the most implicated ER network and shows the functional connectivity between ER and Tau.

FIG. 10 illustrates molecular intrinsic profiles of 134 patient tumors. A hierarchical clustering analysis was performed using about 9800 genes after eliminating low expressed and low variance genes. Row, gene; column, tumor. The tumors were classified into two major clusters and, interestingly, the majority of the samples from three Russian sites were clustered in the first cluster.

DETAILED DESCRIPTION OF THE INVENTION

The invention provides biomarkers that correlate with microtubule-stabilization agent sensitivity or resistance. These biomarkers can be employed for predicting response to one or more microtubule-stabilization agents. In one aspect, the biomarkers of the invention are those provided in Table 1, Table 2, and the Sequence Listing, including both polynucleotide and polypeptide sequences.

The biomarkers provided in Table 1 include the nucleotide sequences of SEQ ID NOS:1-100 and the amino acid sequences of SEQ ID NOS:201-299.

TABLE 1
BIOMARKERS (SENSITIVE)
		Affymetrix
Unigene title and		Probe	Gene
SEQ ID NO:	Affymetrix Description	Set	Ontology
C6orf145:	“Consensus includes gb: AK024828.1	212923_s_at
chromosome 6	/DEF = Homo sapiens cDNA: FLJ21175
open reading	fis, clone CAS11071. /FEA = mRNA
frame 145	/DB_XREF = gi: 10437233
(LOC221749)	/UG = Hs.69388 hypothetical protein
SEQ ID NOS: 1	FLJ20505”
(DNA) and 201
(amino acid)
RTCD1: RNA	“gb: NM_003729.1 /DEF = Homo sapiens	203594_at	assembly
terminal phosphate	RNA 3-terminal phosphate cyclase		of
cyclase domain 1	(RPC), mRNA. /FEA = mRNA		spliceosomal
(LOC8634)	/GEN = RPC /PROD = RNA 3-terminal		tri-
SEQ ID NOS: 2	phosphate cyclase		snRNP
(DNA) and 202	/DB_XREF = gi: 4506588 /UG = Hs.27076
(amino acid)	RNA 3-terminal phosphate cyclase
	/FL = gb: NM_003729.1”
FXYD5: FXYD	“gb: NM_014164.2 /DEF = Homo sapiens	218084_x_at	negative
domain containing	FXYD domain-containing ion transport		regulation
ion transport	regulator 5 (FXYD5), mRNA.		of
regulator 5	/FEA = mRNA /GEN = FXYD5		calcium-
(LOC53827)	/PROD = related to ion channel		dependent
SEQ ID NOS: 3	/DB_XREF = gi: 11612664		cell-cell
(DNA) and 203	/UG = Hs.294135 FXYD domain-		adhesion
(amino acid)	containing ion transport regulator 5
	/FL = gb: NM_014164.2 gb: AF161462.1”
G3BP: Ras-	Consensus includes gb: BG500067	201503_at	protein-
GTPase-activating	/FEA = EST /DB_XREF = gi: 13461584		nucleus
protein SH3-	/DB_XREF = est: 602545874F1		import
domain-binding	/CLONE = IMAGE: 4668234
protein	/UG = Hs.220689 Ras-GTPase-activating
(LOC10146)	protein SH3-domain-binding protein
SEQ ID NOS: 4	/FL = gb: U32519.1 gb: NM_005754.1
(DNA) and 204
(amino acid)
FKBP1A: FK506	“gb: NM_000801.1 /DEF = Homo sapiens	200709_at	protein
binding protein	FK506-binding protein 1A (12 kD)		folding
1A, 12 kDa	(FKBP1A), mRNA. /FEA = mRNA
(LOC2280)	/GEN = FKBP1A /PROD = FK506-binding
SEQ ID NOS: 5	protein 1A (12 kD)
(DNA) and 205	/DB_XREF = gi: 4503724 /UG = Hs.752
(amino acid)	FK506-binding protein 1A (12 kD)
	/FL = gb: BC001925.1 gb: M34539.1
	gb: NM_000801.1”
VARS2: valyl-	“gb: NM_006295.1 /DEF = Homo sapiens	201797_s_at	translational
tRNA synthetase 2	valyl-tRNA synthetase 2 (VARS2),		elongation
(LOC7407)	mRNA. /FEA = mRNA /GEN = VARS2
SEQ ID NOS: 6	/PROD = valyl-tRNA synthetase 2
(DNA) and 206	/DB_XREF = gi: 5454157
(amino acid)	/UG = Hs.159637 valyl-tRNA synthetase
	2 /FL = gb: NM_006295.1”
FKBP1A: FK506	Consensus includes gb: AI936769	214119_s_at	protein
binding protein	/FEA = EST /DB_XREF = gi: 5675639		folding
1A, 12 kDa	/DB_XREF = est: wp69c11.x1
(LOC2280)	/CLONE = IMAGE: 2467028 /UG = Hs.752
SEQ ID NOS: 7	FK506-binding protein 1A (12 kD)
(DNA) and 207
(amino acid)
MTMR2:	“Consensus includes gb: AK027038.1	203211_s_at	protein
myotubularin	/DEF = Homo sapiens cDNA: FLJ23385		amino
related protein 2	fis, clone HEP16802. /FEA = mRNA		acid
(LOC8898)	/DB_XREF = gi: 10440053		dephosphorylation
SEQ ID NOS: 8	/UG = Hs.181326 KIAA1073 protein
(DNA) and 208	/FL = gb: AB028996.1 gb: NM_016156.1”
(amino acid)
PSMB8:	“gb: U17496.1 /DEF = Human proteasome	209040_s_at	proteolysis
proteasome	subunit LMP7 (allele LMP7B) mRNA,		and
(prosome,	complete cds. /FEA = mRNA		peptidolysis,
macropain)	/GEN = LMP7 /PROD = proteasome		ubiquitin-
subunit, beta type,	subunit LMP7 /DB_XREF = gi: 596139		dependent
8 (large	/UG = Hs.180062 proteasome (prosome,		protein
multifunctional	macropain) subunit, beta type, 8 (large		catabolism
protease 7)	multifunctional protease 7)
(LOC5696)	/FL = gb: U17496.1 gb: U17497.1”
SEQ ID NOS: 9
(DNA) and 209
(amino acid)
CTSC: cathepsin C	“gb: NM_001814.1 /DEF = Homo sapiens	201487_at	proteolysis
(LOC1075)	cathepsin C (CTSC), mRNA.		and
SEQ ID NOS: 10	/FEA = mRNA /GEN = CTSC		peptidolysis
(DNA) and 210	/PROD = cathepsin C
(amino acid)	/DB_XREF = gi: 4503140 /UG = Hs.10029
	cathepsin C /FL = gb: NM_001814.1”
ST5: suppression	“gb: NM_005418.1 /DEF = Homo sapiens	202440_s_at
of tumorigenicity 5	suppression of tumorigenicity 5 (ST5),
(LOC6764)	mRNA. /FEA = mRNA /GEN = ST5
SEQ ID NOS: 11	/PROD = suppression of tumorigenicity 5
(DNA) and 211	/DB_XREF = gi: 4885612 /UG = Hs.79265
(amino acid)	suppression of tumorigenicity 5
	/FL = gb: U15131.1 gb: U15779.1
	gb: NM_005418.1”
MTMR2:	“Consensus includes gb: U58033.1	214649_s_at	protein
myotubularin	/DEF = Homo sapiens myotubularin		amino
related protein 2	related protein 2 (MTMR2) mRNA,		acid
(LOC8898)	partial cds. /FEA = mRNA		dephosphorylation
SEQ ID NOS: 12	/GEN = MTMR2 /PROD = myotubularin
(DNA) and 212	related protein 2 /DB_XREF = gi: 3912941
(amino acid)	/UG = Hs.278491 myotubularin related
	protein 2 /FL = gb: NM_003912.1”
PRNP: prion	“gb: NM_000311.1 /DEF = Homo sapiens	201300_s_at
protein (p27-30)	prion protein (p27-30) (Creutzfeld-Jakob
(Creutzfeld-Jakob	disease, Gerstmann-Strausler-Scheinker
disease,	syndrome, fatal familial insomnia)
Gerstmann-	(PRNP), mRNA. /FEA = mRNA
Strausler-	/GEN = PRNP /PROD = prion protein
Scheinker	/DB_XREF = gi: 4506112 /UG = Hs.74621
syndrome, fatal	prion protein (p27-30) (Creutzfeld-Jakob
familial insomnia)	disease, Gerstmann-Strausler-Scheinker
(LOC5621)	syndrome, fatal familial insomnia)
SEQ ID NOS: 13	/FL = gb: AY008282.1 gb: M13899.1
(DNA) and 213	gb: NM_000311.1”
(amino acid)
MET: met proto-	“gb: U19348.1 /DEF = Human (tpr-met	211599_x_at	signal
oncogene	fusion) oncogene mRNA, complete cds.		transduction
(hepatocyte	/FEA = mRNA /GEN = tprmet fusion
growth factor	/PROD = tpr-met fusion protein
receptor)	/DB_XREF = gi: 625085
(LOC4233)	/FL = gb: U19348.1”
SEQ ID NOS: 14
(DNA) and 214
(amino acid)
MIRAB13:	“Cluster Incl. W46406: zc31c10.s1 Homo	55081_at	vesicle-
molecule	sapiens cDNA, 3 end /clone = IMAGE-		mediated
interacting with	323922 /clone_end = 3′ /gb = W46406		transport
Rab13	/gi = 1331036 /ug = Hs.8535 /len = 568”
(LOC85377)
SEQ ID NOS: 15
(DNA) and 215
(amino acid)
AKAP2: A kinase	Consensus includes gb: BE879367	202759_s_at
(PRKA) anchor	/FEA = EST /DB_XREF = gi: 10328143
protein 2	/DB_XREF = est: 601484628F1
(LOC11217)	/CLONE = IMAGE: 3887262
SEQ ID NOS: 16	/UG = Hs.42322 A kinase (PRKA) anchor
(DNA) and 216	protein 2 /FL = gb: AB023137.1
(amino acid)	gb: NM_007203.1
MET: met proto-	Consensus includes gb: BG170541	203510_at	signal
oncogene	/FEA = EST /DB_XREF = gi: 12677244		transduction
(hepatocyte	/DB_XREF = est: 602322942F1
growth factor	/CLONE = IMAGE: 4425947
receptor)	/UG = Hs.285754 met proto-oncogene
(LOC4233)	(hepatocyte growth factor receptor)
SEQ ID NOS: 17	/FL = gb: J02958.1 gb: NM_000245.1
(DNA) and 217
(amino acid)
STAC: SH3 and	“gb: NM_003149.1 /DEF = Homo sapiens	205743_at	intracellular
cysteine rich	src homology three (SH3) and cysteine		signaling
domain	rich domain (STAC), mRNA.		cascade
(LOC6769)	/FEA = mRNA /GEN = STAC /PROD = src
SEQ ID NOS: 18	homology three (SH3) and cysteine
(DNA) and 218	richdomain /DB_XREF = gi: 4507246
(amino acid)	/UG = Hs.56045 src homology three
	(SH3) and cysteine rich domain
	/FL = gb: D86640.1 gb: NM_003149.1”
CALU: calumenin	Consensus includes gb: BF939365	200755_s_at
(LOC813)	/FEA = EST /DB_XREF = gi: 12356685
SEQ ID NOS: 19	/DB_XREF = est: nad87h04.x1
(DNA) and 219	/CLONE = IMAGE: 3410551
(amino acid)	/UG = Hs.7753 calumenin
	/FL = gb: U67280.1 gb: AF013759.1
	gb: NM_001219.2
MSN: moesin	“gb: NM_002444.1 /DEF = Homo sapiens	200600_at	cell
(LOC4478)	moesin (MSN), mRNA. /FEA = mRNA		motility
SEQ ID NOS: 20	/GEN = MSN /PROD = moesin
(DNA) and 220	/DB_XREF = gi: 4505256
(amino acid)	/UG = Hs.170328 moesin
	/FL = gb: M69066.1 gb: NM_002444.1”
ANXA1: annexin	“gb: NM_000700.1 /DEF = Homo sapiens	201012_at	inflammatory
A1 (LOC301)	annexin A1 (ANXA1), mRNA.		response,
SEQ ID NOS: 21	/FEA = mRNA /GEN = ANXA1		cell
(DNA) and 221	/PROD = annexin I		motility
(amino acid)	/DB_XREF = gi: 4502100 /UG = Hs.78225
	annexin A1 /FL = gb: BC001275.1
	gb: NM_000700.1”
CGI-100: CGI-100	“gb: NM_016040.1 /DEF = Homo sapiens	202195_s_at	intracellular
protein	CGI-100 protein (LOC50999), mRNA.		protein
(LOC50999)	/FEA = mRNA /GEN = LOC50999		transport
SEQ ID NOS: 22	/PROD = CGI-100 protein
(DNA) and 222	/DB_XREF = gi: 7705583
(amino acid)	/UG = Hs.296155 CGI-100 protein
	/FL = gb: AF151858.1 gb: NM_016040.1”
CALU: calumenin	“gb: NM_001219.2 /DEF = Homo sapiens	200757_s_at
(LOC813)	calumenin (CALU), mRNA.
SEQ ID NOS: 23	/FEA = mRNA /GEN = CALU
(DNA) and 223	/PROD = calumenin precursor
(amino acid)	/DB_XREF = gi: 6005991 /UG = Hs.7753
	calumenin /FL = gb: U67280.1
	gb: AF013759.1 gb: NM_001219.2”
EGFR: epidermal	“gb: U95089.1 /DEF = Human truncated	210984_x_at	EGF
growth factor	epidermal growth factor receptor-like		receptor
receptor	protein precursor mRNA, complete cds.		signaling
(erythroblastic	/FEA = mRNA /PROD = truncated		pathway
leukemia viral (v-	epidermal growth factor receptor-
erb-b) oncogene	likeprotein precursor
homolog, avian)	/DB_XREF = gi: 2051984 /UG = Hs.77432
(LOC1956)	epidermal growth factor receptor (avian
SEQ ID NOS: 24	erythroblastic leukemia viral (v-erb-b)
(DNA) and 224	oncogene homolog) /FL = gb: U95089.1”
(amino acid)
CASP4: caspase 4,	“gb: U25804.1 /DEF = Human Ich-2	209310_s_at	apoptosis
apoptosis-related	cysteine protease mRNA, complete cds.
cysteine protease	/FEA = mRNA /PROD = Ich-2
(LOC837)	/DB_XREF = gi: 886049 /UG = Hs.74122
SEQ ID NOS: 25	caspase 4, apoptosis-related cysteine
(DNA) and 225	protease /FL = gb: U28976.1 gb: U28977.1
(amino acid)	gb: U28978.1 gb: NM_001225.1
	gb: U25804.1 gb: U28014.1”
DKFZP566E144:	“gb: NM_015523.1 /DEF = Homo sapiens	218194_at	nucleotide
small fragment	small fragment nuclease		metabolism
nuclease	(DKFZP566E144), mRNA.
(LOC25996)	/FEA = mRNA /GEN = DKFZP566E144
SEQ ID NOS: 26	/PROD = small fragment nuclease
(DNA) and 226	/DB_XREF = gi: 7661645 /UG = Hs.7527
(amino acid)	small fragment nuclease
	/FL = gb: AF151872.1 gb: AL110239.1
	gb: NM_015523.1”
AKR1B1: aldo-	“gb: NM_001628.1 /DEF = Homo sapiens	201272_at	carbohydrate
keto reductase	aldo-keto reductase family 1, member B1		metabolism
family 1, member	(aldose reductase) (AKR1B1), mRNA.
B1 (aldose	/FEA = mRNA /GEN = AKR1B1
reductase)	/PROD = aldo-keto reductase family 1,
(LOC231)	member B1 (aldosereductase)
	/DB_XREF = gi: 4502048 /UG = Hs.75313
SEQ ID NOS: 27	aldo-keto reductase family 1, member B1
(DNA) and 227	(aldose reductase) /FL = gb: BC000260.1
(amino acid)	gb: BC005387.1 gb: J04795.1 gb: J05017.1
	gb: J05474.1 gb: M34720.1
	gb: NM_001628.1”
CAV1: caveolin 1,	Consensus includes gb: AU147399	212097_at
caveolae protein,	/FEA = EST /DB_XREF = gi: 11008920
22 kDa (LOC857)	/DB_XREF = est: AU147399
SEQ ID NOS: 28	/CLONE = MAMMA1000563
(DNA) and 228	/UG = Hs.74034 Homo sapiens clone
(amino acid)	24651 mRNA sequence
MBNL2:	Consensus includes gb: BE328496	203640_at
muscleblind-like 2	/FEA = EST /DB_XREF = gi: 9202272
(Drosophila)	/DB_XREF = est: hs98f09.x1
(LOC10150)	/CLONE = IMAGE: 3145289
SEQ ID NOS: 29	/UG = Hs.283609 hypothetical protein
(DNA) and 229	PRO2032/FL = gb: AF116683.1
(amino acid)	gb: NM_018615.1
CRSP6: cofactor	“gb: AF105421.1 /DEF = Homo sapiens	221517_s_at	regulation
required for Sp1	vitamin D3 receptor interacting protein		of
transcriptional	(DRIP80) mRNA, complete cds.		transcription,
activation, subunit	/FEA = mRNA /GEN = DRIP80		DNA-
6, 77 kDa	/PROD = vitamin D3 receptor interacting		dependent
(LOC9440)	protein /DB_XREF = gi: 4838128
SEQ ID NOS: 30	/UG = Hs.22630 cofactor required for Sp1
(DNA) and 230	transcriptional activation, subunit 6
(amino acid)	(77 kD) /FL = gb: AF105421.1”
CALU: calumenin	”gb: U67280.1 /DEF = Homo sapiens	200756_x_at
(LOC813)	calumenin mRNA, complete cds.
SEQ ID NOS: 31	/FEA = mRNA /PROD = calumenin
(DNA) and 231	/DB_XREF = gi: 2809323 /UG = Hs.7753
(amino acid)	calumenin /FL = gb: U67280.1
	gb: AF013759.1 gb: NM_001219.2”
PTRF: polymerase	“Consensus includes gb: BC004295.1	208789_at
I and transcript	/DEF = Homo sapiens, clone
release factor	IMAGE: 3622356, mRNA, partial cds.
(LOC284119)	/FEA = mRNA /PROD = Unknown
SEQ ID NOS: 32	(protein for IMAGE: 3622356)
(DNA) and 232	/DB_XREF = gi: 13279151
(amino acid)	/UG = Hs.29759 RNA POLYMERASE I
	AND TRANSCRIPT RELEASE
	FACTOR /FL = gb: AF312393.1”
NUP155:	“gb: NM_004298.1 /DEF = Homo sapiens	206550_s_at	nucleocytoplasmic
nucleoporin	nucleoporin 155 kD (NUP155), mRNA.		transport
155 kDa	/FEA = mRNA /GEN = NUP155
(LOC9631)	/PROD = nucleoporin 155 kD
SEQ ID NOS: 33	/DB_XREF = gi: 4758843 /UG = Hs.23255
(DNA) and 233	nucleoporin 155 kD /FL = gb: AB018334.1
(amino acid)	gb: NM_004298.1”
DONSON:	“gb: AF232674.1 /DEF = Homo sapiens	221677_s_at
downstream	B17 mRNA, complete cds. /FEA = mRNA
neighbor of SON	/PROD = B17 /DB_XREF = gi: 8118230
(LOC29980)	/UG = Hs.17834 downstream neighbor of
SEQ ID NOS: 34	SON /FL = gb: AF232674.1”
(DNA) and 234
(amino acid)
CALU: calumenin	“Consensus includes gb: AF257659.1	214845_s_at
(LOC813)	/DEF = Homo sapiens crocalbin-like
SEQ ID NOS: 35	protein mRNA, partial cds.
(DNA) and 235	/FEA = mRNA /PROD = crocalbin-like
(amino acid)	protein /DB_XREF = gi: 8515717
	/UG = Hs.302073 Homo sapiens
	crocalbin-like protein mRNA, partial
	cds”
FAD104: FAD104	“gb: NM_022763.1 /DEF = Homo sapiens	218618_s_at
(LOC64778)	hypothetical protein FLJ23399
SEQ ID NOS: 36	(FLJ23399), mRNA. /FEA = mRNA
(DNA) and 236	/GEN = FLJ23399 /PROD = hypothetical
(amino acid)	protein FLJ23399
	/DB_XREF = gi: 12232434
	/UG = Hs.299883 hypothetical protein
	FLJ23399 /FL = gb: NM_022763.1”
EPHA2: EphA2	”gb: NM_004431.1 /DEF = Homo sapiens	203499_at
(LOC1969)	EphA2 (EPHA2), mRNA. /FEA = mRNA
SEQ ID NOS: 37	/GEN = EPHA2 /PROD = EphA2
(DNA) and 237	/DB_XREF = gi: 4758277
(amino acid)	/UG = Hs.171596 EphA2
	/FL = gb: M59371.1 gb: NM_004431.1”
PAK1IP1: PAK1	“gb: NM_017906.1 /DEF = Homo sapiens	218886_at
interacting protein	hypothetical protein FLJ20624
1 (LOC55003)	(FLJ20624), mRNA. /FEA = mRNA
SEQ ID NOS: 38	/GEN = FLJ20624 /PROD = hypothetical
(DNA) and 238	protein FLJ20624
(amino acid)	/DB_XREF = gi: 8923576 /UG = Hs.52256
	hypothetical protein FLJ20624
	/FL = gb: NM_017906.1”
CTPS: CTP	“gb: NM_001905.1 /DEF = Homo sapiens	202613_at	pyrimidine
synthase	CTP synthase (CTPS), mRNA.		nucleotide
(LOC1503)	/FEA = mRNA /GEN = CTPS		biosynthesis
SEQ ID NOS: 39	/PROD = CTP synthase
(DNA) and 239	/DB_XREF = gi: 4503132
(amino acid)	/UG = Hs.251871 CTP synthase
	/FL = gb: NM_001905.1”
CD44: CD44	“gb: BC004372.1 /DEF = Homo sapiens,	209835_x_at	cell-cell
antigen (homing	Similar to CD44 antigen (homing		adhesion
function and	function and Indian blood group system),
Indian blood group	clone MGC: 10468, mRNA, complete
system) (LOC960)	cds. /FEA = mRNA /PROD = Similar to
SEQ ID NOS: 40	CD44 antigen (homing function
(DNA) and 240	andIndian blood group system)
(amino acid)	/DB_XREF = gi: 13325117
	/UG = Hs.169610 CD44 antigen (homing
	function and Indian blood group system)
	/FL = gb: BC004372.1”
CD97: CD97	“gb: NM_001784.1 /DEF = Homo sapiens	202910_s_at	G-protein
antigen (LOC976)	CD97 antigen (CD97), mRNA.		coupled
SEQ ID NOS: 41	/FEA = mRNA /GEN = CD97		receptor
(DNA) and 241	/PROD = CD97 antigen		protein
(amino acid)	/DB_XREF = gi: 4502690 /UG = Hs.3107		signaling
	CD97 antigen /FL = gb: NM_001784.1”		pathway
SPTBN1: spectrin,	“Consensus includes gb: BE968833	212071_s_at
beta, non-	/FEA = EST /DB_XREF = gi: 10579538
erythrocytic 1	/DB_XREF = est: 601649861F1
(LOC6711)	/CLONE = IMAGE: 3933782
SEQ ID NOS: 42	/UG = Hs.324648 Homo sapiens cDNA
(DNA) and 242	FLJ13700 fis, clone PLACE2000216,
(amino acid)	highly similar to SPECTRIN BETA
	CHAIN, BRAIN”
SH3GLB1: SH3-	“gb: AF263293.1 /DEF = Homo sapiens	209091_s_at
domain GRB2-like	endophilin B1 mRNA, complete cds.
endophilin B1	/FEA = mRNA /PROD = endophilin B1
(LOC51100)	/DB_XREF = gi: 8118529
SEQ ID NOS: 43	/UG = Hs.136309 SH3-containing protein
(DNA) and 243	SH3GLB1 /FL = gb: AF263293.1”
(amino acid)
PGM1:	“gb: NM_002633.1 /DEF = Homo sapiens	201968_s_at	glucose
phosphoglucomutase	phosphoglucomutase 1 (PGM1), mRNA.		metabolism
1 (LOC5236)	/FEA = mRNA /GEN = PGM1
SEQ ID NOS: 44	/PROD = phosphoglucomutase 1
(DNA) and 244	/DB_XREF = gi: 4505764 /UG = Hs.1869
(amino acid)	phosphoglucomutase 1
	/FL = gb: BC001756.1 gb: M83088.1
	gb: NM_002633.1”
SH3GLB1: SH3-	“gb: AF257318.1 /DEF = Homo sapiens	210101_x_at
domain GRB2-like	SH3-containing protein SH3GLB1
endophilin B1	mRNA, complete cds. /FEA = mRNA
(LOC51100)	/PROD = SH3-containing protein
	SH3GLB1 /DB_XREF = gi: 8896091
SEQ ID NOS: 45	/UG = Hs.136309 SH3-containing protein
(DNA) and 245	SH3GLB1 /FL = gb: AF350371.1
(amino acid)	gb: AF151819.1 gb: NM_016009.1
	gb: AF257318.1”
GBP1: guanylate	“gb: BC002666.1 /DEF = Homo sapiens,	202269_x_at	immune
binding protein 1,	guanylate binding protein 1, interferon-		response
interferon-	inducible, 67 kD, clone MGC: 3949,
inducible, 67 kDa	mRNA, complete cds. /FEA = mRNA
(LOC2633)	/PROD = guanylate binding protein
SEQ ID NOS: 46	1, interferon-inducible, 67 kD
(DNA) and 246	/DB_XREF = gi: 12803662
(amino acid)	/UG = Hs.62661 guanylate binding protein
	1, interferon-inducible, 67 kD
	/FL = gb: BC002666.1 gb: M55542.1
	gb: NM_002053.1”
ADORA2B:	“gb: NM_000676.1 /DEF = Homo sapiens	205891_at	adenylate
adenosine A2b	adenosine A2b receptor (ADORA2B),		cyclase
receptor (LOC136)	mRNA. /FEA = mRNA		activation
SEQ ID NOS: 47	/GEN = ADORA2B /PROD = adenosine
(DNA) and 247	A2b receptor /DB_XREF = gi: 4501950
(amino acid)	/UG = Hs.45743 adenosine A2b receptor
	/FL = gb: M97759.1 gb: NM_000676.1”
PLS3: plastin 3 (T	“gb: NM_005032.2 /DEF = Homo sapiens	201215_at
isoform)	plastin 3 (T isoform) (PLS3), mRNA.
(LOC5358)	/FEA = mRNA /GEN = PLS3
SEQ ID NOS: 48	/PROD = plastin 3 precursor
(DNA) and 248	/DB_XREF = gi: 7549808 /UG = Hs.4114
(amino acid)	plastin 3 (T isoform) /FL = gb: M22299.1
	gb: NM_005032.2”
PDGFC: platelet	“gb: NM_016205.1 /DEF = Homo sapiens	218718_at
derived growth	platelet derived growth factor C
factor C	(PDGFC), mRNA. /FEA = mRNA
(LOC56034)	/GEN = PDGFC /PROD = secretory growth
SEQ ID NOS: 49	factor-like protein fallotein
(DNA) and 249	/DB_XREF = gi: 9994186 /UG = Hs.43080
(amino acid)	platelet derived growth factor C
	/FL = gb: AF091434.1 gb: AF244813.1
	gb: AB033831.1 gb: NM_016205.1”
MID1: midline 1	“gb: NM_000381.1 /DEF = Homo sapiens	203637_s_at	microtubule
(Opitz/BBB	midline 1 (OpitzBBB syndrome)		cytoskeleton
syndrome)	(MID1), mRNA. /FEA = mRNA		organization
(LOC4281)	/GEN = MID1 /PROD = midline 1		and
SEQ ID NOS: 50	/DB_XREF = gi: 4557752 /UG = Hs.27695		biogenesis
(DNA) and 250	midline 1 (OpitzBBB syndrome)
(amino acid)	/FL = gb: F269101.1 gb: AF230976.1
	gb: AF035360.1 gb: NM_000381.1”
MET: met proto-	Consensus includes gb: BE870509	213807_x_at	signal
oncogene	/FEA = EST /DB_XREF = gi: 10319285		transduction
(hepatocyte	/DB_XREF = est: 601447096F1
growth factor	/CLONE = IMAGE: 3851374
receptor)	/UG = Hs.285754 met proto-oncogene
(LOC4233)	(hepatocyte growth factor receptor)
SEQ ID NOS: 51
(DNA) and 251
(amino acid)
CHST6:	“gb: NM_021615.1 /DEF = Homo sapiens	221059_s_at	proteoglycan
carbohydrate (N-	carbohydrate (N-acetylglucosamine 6-O)		sulfate
acetylglucosamine	sulfotransferase 6 (CHST6), mRNA.		transfer
6-O)	/FEA = mRNA /GEN = CHST6
sulfotransferase 6	/PROD = carbohydrate (N-
(LOC4166)	acetylglucosamine 6-O)sulfotransferase 6
SEQ ID NOS: 52	/DB_XREF = gi: 11055975
(DNA) and 252	/UG = Hs.157439 carbohydrate (N-
(amino acid)	acetylglucosamine 6-O) sulfotransferase
	6 /FL = gb: AF219990.1
	gb: NM_021615.1”
MEIS2: Meis1,	“gb: NM_020149.1 /DEF = Homo sapiens	207480_s_at	negative
myeloid ecotropic	TALE homeobox protein Meis2e		regulation
viral integration	(LOC56908), mRNA. /FEA = mRNA		of
site 1 homolog 2	/GEN = LOC56908 /PROD = TALE		transcription
(mouse)	homeobox protein Meis2e		from
(LOC4212)	/DB_XREF = gi: 9910355		Pol II
SEQ ID NOS: 53	/UG = Hs.283312 TALE homeobox		promoter
(DNA) and 253	protein Meis2e /FL = gb: AF179899.1
(amino acid)	gb: NM_020149.1”
UPP1: uridine	“gb: NM_003364.1 /DEF = Homo sapiens	203234_at	nucleoside
phosphorylase 1	uridine phosphorylase (UP), mRNA.		metabolism
(LOC7378)	/FEA = mRNA /GEN = UP /PROD = uridine
SEQ ID NOS: 54	phosphorylase /DB_XREF = gi: 4507838
(DNA) and 254	/UG = Hs.77573 uridine phosphorylase
(amino acid)	/FL = gb: BC001405.1 gb: NM_003364.1”
CD44: CD44	Consensus includes gb: AI493245	212014_x_at	cell-cell
antigen (homing	/FEA = EST /DB_XREF = gi: 4394248		adhesion
function and	/DB_XREF = est: ti30d08.x1
Indian blood group	/CLONE = IMAGE: 2131983
system) (LOC960)	/UG = Hs.169610 CD44 antigen (homing
SEQ ID NOS: 55	function and Indian blood group system)
(DNA) and 255
(amino acid)
BTG3: BTG	“Consensus includes gb: AI765445	213134_x_at	regulation
family, member 3	/FEA = EST /DB_XREF = gi: 5231954		of cell
(LOC10950)	/DB_XREF = est: wi80b08.x1		cycle
SEQ ID NOS: 56	/CLONE = IMAGE: 2399607
(DNA) and 256	/UG = Hs.77311 BTG family, member 3”
(amino acid)
FKBP1A: FK506	“gb: BC005147.1 /DEF = Homo sapiens,	210186_s_at	protein
binding protein	FK506-binding protein 1A (12 kD), clone		folding
1A, 12 kDa	MGC: 2167, mRNA, complete cds.
(LOC2280)	/FEA = mRNA /PROD = FK506-binding
SEQ ID NOS: 57	protein 1A (12 kD)
(DNA) and 257	/DB_XREF = gi: 13477342 /UG = Hs.752
(amino acid)	FK506-binding protein 1A (12 kD)
	/FL = gb: BC005147.1”
IFI16: interferon,	“gb: NM_005531.1 /DEF = Homo sapiens	206332_s_at
gamma-inducible	interferon, gamma-inducible protein 16
protein 16	(IFI16), mRNA. /FEA = mRNA
(LOC3428)	/GEN = IFI16 /PROD = interferon, gamma-
SEQ ID NOS: 58	inducible protein 16
(DNA) and 258	/DB_XREF = gi: 5031778
(amino acid)	/UG = Hs.155530 interferon, gamma-
	inducible protein 16 /FL = gb: M63838.1
	gb: NM_005531.1”
CD44: CD44	Consensus includes gb: BE903880	212063_at	cell-cell
antigen (homing	/FEA = EST /DB_XREF = gi: 10395551		adhesion
function and	/DB_XREF = est: 601494678F1
Indian blood group	/CLONE = IMAGE: 3896970
system) (LOC960)	/UG = Hs.323950 zinc finger protein 6
SEQ ID NOS: 59	(CMPX1)
(DNA) and 259
(amino acid)
IFI16: interferon,	“gb: AF208043.1 /DEF = Homo sapiens	208966_x_at
gamma-inducible	IFI16b (IFI16b) mRNA, complete cds.
protein 16	/FEA = mRNA /GEN = IFI16b
(LOC3428)	/PROD = IFI16b /DB_XREF = gi: 6644296
SEQ ID NOS: 60	/UG = Hs.155530 interferon, gamma-
(DNA) and 260	inducible protein 16
(amino acid)	/FL = gb: AF208043.1”
GNG12: guanine	Consensus includes gb: BG111761	212294_at	signal
nucleotide binding	/FEA = EST /DB_XREF = gi: 12605267		transduction
protein (G	/DB_XREF = est: 602285343F1
protein), gamma	/CLONE = IMAGE: 4372619
12 (LOC55970)	/UG = Hs.8107 Homo sapiens mRNA;
SEQ ID NOS: 61	cDNA DKFZp586B0918 (from clone
(DNA) and 261	DKFZp586B0918)
(amino acid)
GSTP1:	“gb: NM_000852.2 /DEF = Homo sapiens	200824_at	metabolism
glutathione S-	glutathione S-transferase pi (GSTP1),
transferase pi	mRNA. /FEA = mRNA /GEN = GSTP1
(LOC2950)	/PROD = glutathione transferase
SEQ ID NOS: 62	/DB_XREF = gi: 6552334
(DNA) and 262	/UG = Hs.226795 glutathione S-
(amino acid)	transferase pi /FL = gb: U62589.1
	gb: U30897.1 gb: NM_000852.2”
MCAM:	“gb: BC006329.1 /DEF = Homo sapiens,	211042_x_at
melanoma cell	Similar to melanoma adhesion molecule,
adhesion molecule	clone MGC: 12808, mRNA, complete
(LOC4162)	cds. /FEA = mRNA /PROD = Similar to
SEQ ID NOS: 63	melanoma adhesion molecule
(DNA) and 263	/DB_XREF = gi: 13623456
(amino acid)	/FL = gb: BC006329.1”
MIRAB13:	“Consensus includes gb: BC001090.1	221779_at	vesicle-
molecule	/DEF = Homo sapiens, clone		mediated
interacting with	IMAGE: 3504989, mRNA, partial cds.		transport
Rab13	/FEA = mRNA /PROD = Unknown
(LOC85377)	(protein for IMAGE: 3504989)
SEQ ID NOS: 64	/DB_XREF = gi: 12654518 /UG = Hs.8535
(DNA) and 264	hypothetical protein bA395L14.2”
(amino acid)
IFI16: interferon,	“Consensus includes gb: BG256677	208965_s_at
gamma-inducible	/FEA = EST /DB_XREF = gi: 12766493
protein 16	/DB_XREF = est: 602370865F1
(LOC3428)	/CLONE = IMAGE: 4478872
SEQ ID NOS: 65	/UG = Hs.155530 interferon, gamma-
(DNA) and 265	inducible protein 16
(amino acid)	/FL = gb: AF208043.1”
DKFZp667G2110:	“Consensus includes gb: BE501352	214030_at
hypothetical	/FEA = EST /DB_XREF = gi: 9703760
protein	/DB_XREF = est: 7a41e05.x1
DKFZp667G2110	/CLONE = IMAGE: 3221312
(LOC131544)	/UG = Hs.23294 ESTs, Weakly similar to
SEQ ID NOS: 66	T15138 hypothetical protein T28F2.4-
(DNA)	Caenorhabditis elegans C. elegans”
C1GALT1: core 1	“gb: NM_020156.1 /DEF = Homo sapiens	219439_at
UDP-galactose: N-	core1 UDP-galactose: N-
acetylgalactosamine-	acetylgalactosamine-alpha-R beta 1,3-
alpha-R beta 1,3-	galactosyltransferase (C1GALT1),
galactosyltransferase	mRNA. /FEA = mRNA
(LOC56913)	/GEN = C1GALT1 /PROD = core1UDP-
SEQ ID NOS: 67	galactose: N-acetylgalactosamine-alpha-R
(DNA) and 266	beta 1,3-galactosyltransferase
(amino acid)	/DB_XREF = gi: 9910143 /UG = Hs.46744
	core1 UDP-galactose: N-
	acetylgalactosamine-alpha-R beta 1,3-
	galactosyltransferase
	/FL = gb: AF155582.1 gb: NM_020156.1”
RANGNRF: RAN	“gb: NM_014185.1 /DEF = Homo sapiens	218526_s_at
guanine nucleotide	HSPC165 protein (HSPC165), mRNA.
release factor	/FEA = mRNA /GEN = HSPC165
(LOC29098)	/PROD = HSPC165 protein
SEQ ID NOS: 68	/DB_XREF = gi: 7661825 /UG = Hs.13605
(DNA) and 267	HSPC165 protein /FL = gb: AF161514.1
(amino acid)	gb: AF151070.1 gb: NM_014185.1
	gb: NM_016492.1 gb: AF168714.1
	gb: AF265206.1”
ELL2: elongation	“Consensus includes gb: NM_012081.1	214446_at	regulation
factor, RNA	/DEF = Homo sapiens ELL-RELATED		of
polymerase II, 2	RNA POLYMERASE II,		transcription,
(LOC22936)	ELONGATION FACTOR (ELL2),		DNA-
SEQ ID NOS: 69	mRNA. /FEA = CDS /GEN = ELL2		dependent
(DNA) and 268	/PROD = ELL-RELATED RNA
(amino acid)	POLYMERASE II,
	ELONGATIONFACTOR
	/DB_XREF = gi: 6912353
	/UG = Hs.173334 ELL-RELATED RNA
	POLYMERASE II, ELONGATION
	FACTOR /FL = gb: NM_012081.1”
BIN1: bridging	“Consensus includes gb: AF043899.1	214439_x_at	synaptic
integrator 1	/DEF = Homo sapiens amphiphysin IIc1		transmission
(LOC274)	mRNA, complete cds. /FEA = CDS
SEQ ID NOS: 70	/PROD = amphiphysin IIc1
(DNA) and 269	/DB_XREF = gi: 3064256
(amino acid)	/UG = Hs.193163 bridging integrator 1
	/FL = gb: AF043899.1”
M-RIP: myosin	“Consensus includes gb: AK025604.1	214771_x_at
phosphatase-Rho	/DEF = Homo sapiens cDNA: FLJ21951
interacting protein	fis, clone HEP04968. /FEA = mRNA
(LOC23164)	/DB_XREF = gi: 10438172
SEQ ID NOS: 71	/UG = Hs.84883 KIAA0864 protein”
(DNA) and 270
(amino acid)
MGC5306:	“gb: BC001972.1 /DEF = Homo sapiens,	221580_s_at
hypothetical	clone MGC: 5306, mRNA, complete cds.
protein MGC5306	/FEA = mRNA /PROD = Unknown
(LOC79101)	(protein for MGC: 5306)
SEQ ID NOS: 72	/DB_XREF = gi: 12805036
(DNA) and 271	/UG = Hs.301732 hypothetical protein
	MGC5306 /FL = gb: BC001972.1”
(amino acid)
BTN3A3:	“gb: NM_006994.2 /DEF = Homo sapiens	204820_s_at
butyrophilin,	butyrophilin, subfamily 3, member A3
subfamily 3,	(BTN3A3), mRNA. /FEA = mRNA
member A3	/GEN = BTN3A3 /PROD = butyrophilin,
(LOC10384)	subfamily 3, member A3
SEQ ID NOS: 73	/DB_XREF = gi: 6325463
(DNA) and 272	/UG = Hs.167741 butyrophilin, subfamily
(amino acid)	3, member A3 /FL = gb: U90548.1
	gb: NM_006994.2”
CAV2: caveolin 2	“gb: NM_001233.1 /DEF = Homo sapiens	203324_s_at
(LOC858)	caveolin 2 (CAV2), mRNA.
SEQ ID NOS: 74	/FEA = mRNA /GEN = CAV2
(DNA) and 273	/PROD = caveolin 2
(amino acid)	/DB_XREF = gi: 4557412
	/UG = Hs.139851 caveolin 2
	/FL = gb: BC005256.1 gb: AF035752.1
	gb: NM_001233.1”
IFNGR1:	“gb: NM_000416.1 /DEF = Homo sapiens	202727_s_at	signal
interferon gamma	interferon gamma receptor 1 (IFNGR1),		transduction
receptor 1	mRNA. /FEA = mRNA /GEN = IFNGR1
(LOC3459)	/PROD = interferon gamma receptor 1
SEQ ID NOS: 75	/DB_XREF = gi: 4557879
(DNA) and 274	/UG = Hs.180866 interferon gamma
(amino acid)	receptor 1 /FL = gb: BC005333.1
	gb: J03143.1 gb: NM_000416.1”
MGC5297:	“gb: NM_024091.1 /DEF = Homo sapiens	219200_at
hypothetical	hypothetical protein MGC5297
protein MGC5297	(MGC5297), mRNA. /FEA = mRNA
(LOC79072)	/GEN = MGC5297 /PROD = hypothetical
SEQ ID NOS: 76	protein MGC5297
(DNA) and 275	/DB_XREF = gi: 13129089
(amino acid)	/UG = Hs.23856 hypothetical protein
	MGC5297 /FL = gb: BC001295.1
	gb: NM_024091.1”
TGFBI:	“gb: NM_000358.1 /DEF = Homo sapiens	201506_at	cell
transforming	transforming growth factor, beta-		adhesion
growth factor,	induced, 68 kD (TGFBI), mRNA.
beta-induced,	/FEA = mRNA /GEN = TGFBI
68 kDa (LOC7045)	/PROD = transforming growth factor,
SEQ ID NOS: 77	beta-induced, 68 kD
(DNA) and 276	/DB_XREF = gi: 4507466
(amino acid)	/UG = Hs.118787 transforming growth
	factor, beta-induced, 68 kD
	/FL = gb: BC000097.1 gb: BC004972.1
	gb: M77349.1 gb: NM_000358.1”
AKAP2: A kinase	“gb: NM_007203.1 /DEF = Homo sapiens	202760_s_at
(PRKA) anchor	A kinase (PRKA) anchor protein 2
protein 2	(AKAP2), mRNA. /FEA = mRNA
(LOC11217)	/GEN = AKAP2 /PROD = A kinase
SEQ ID NOS: 78	(PRKA) anchor protein 2
(DNA) and 277	/DB_XREF = gi: 6005708 /UG = Hs.42322
(amino acid)	A kinase (PRKA) anchor protein 2
	/FL = gb: AB023137.1 gb: NM_007203.1”
QKI: quaking	Consensus includes gb: AI114716	212263_at	signal
homolog, KH	/FEA = EST /DB_XREF = gi: 6360061		transduction
domain RNA	/DB_XREF = est: HA1315 /UG = Hs.15020
binding (mouse)	homolog of mouse quaking QKI (KH
(LOC9444)	domain RNA binding protein)
SEQ ID NOS: 79	/FL = gb: AF142419.1 gb: AF142422.1
(DNA) and 278
(amino acid)
PRNP: prion	“Consensus includes gb: AV725328	215707_s_at
protein (p27-30)	/FEA = EST /DB_XREF = gi: 10830606
(Creutzfeld-Jakob	/DB_XREF = est: AV725328
disease,	/CLONE = HTCAVD03 /UG = Hs.74621
Gerstmann-	prion protein (p27-30) (Creutzfeld-Jakob
Strausler-	disease, Gerstmann-Strausler-Scheinker
Scheinker	syndrome, fatal familial insomnia)”
syndrome, fatal
familial insomnia)
(LOC5621)
SEQ ID NOS: 80
(DNA) and 279
(amino acid)
HIC: I-mfa	“gb: AF054589.1 /DEF = Homo sapiens	211675_s_at
domain-containing	HIC protein isoform p40 and HIC protein
protein	isoform p32 mRNAs, complete cds.
(LOC29969)	/FEA = mRNA /PROD = HIC protein
SEQ ID NOS: 81	isoform p32; HIC protein isoform p40
(DNA) and 280	/DB_XREF = gi: 3426297
(amino acid)	/FL = gb: AF054589.1”
POPDC3: popeye	“gb: NM_022361.1 /DEF = Homo sapiens	219926_at
domain containing	popeye protein 3 (POP3), mRNA.
3 (LOC64208)	/FEA = mRNA /GEN = POP3
SEQ ID NOS: 82	/PROD = popeye protein 3
(DNA) and 281	/DB_XREF = gi: 11641280
(amino acid)	/UG = Hs.303154 popeye protein 3
	/FL = gb: AF204171.1 gb: NM_022361.1”
FLJ10315:	“gb: NM_018056.1 /DEF = Homo sapiens	218770_s_at
hypothetical	hypothetical protein FLJ10315
protein FLJ10315	(FLJ10315), mRNA. /FEA = mRNA
(LOC55116)	/GEN = FLJ10315 /PROD = hypothetical
SEQ ID NOS: 83	protein FLJ10315
(DNA) and 282	/DB_XREF = gi: 8922347 /UG = Hs.25544
(amino acid)	hypothetical protein FLJ10315
	/FL = gb: AL136695.1 gb: NM_018056.1”
PSMB9:	“gb: NM_002800.1 /DEF = Homo sapiens	204279_at	proteolysis
proteasome	proteasome (prosome, macropain)		and
(prosome,	subunit, beta type, 9 (large		peptidolysis,
macropain)	multifunctional protease 2) (PSMB9),		ubiquitin-
subunit, beta type,	mRNA. /FEA = mRNA /GEN = PSMB9		dependent
9 (large	/PROD = proteasome (prosome,		protein
multifunctional	macropain) subunit, betatype, 9 (large		catabolism
protease 2)	multifunctional protease 2)
(LOC5698)	/DB_XREF = gi: 4506204 /UG = Hs.9280
SEQ ID NOS: 84	proteasome (prosome, macropain)
(DNA) and 283	subunit, beta type, 9 (large
(amino acid)	multifunctional protease 2)
	/FL = gb: U01025.1 gb: NM_002800.1”
DEPDC1: DEP	“gb: NM_017779.1 /DEF = Homo sapiens	220295_x_at
domain containing	hypothetical protein FLJ20354
1 (LOC55635)	(FLJ20354), mRNA. /FEA = mRNA
SEQ ID NOS: 85	/GEN = FLJ20354 /PROD = hypothetical
(DNA) and 284	protein FLJ20354
(amino acid)	/DB_XREF = gi: 8923327
	/UG = Hs.133260 hypothetical protein
	FLJ20354 /FL = gb: NM_017779.1”
EGFR: epidermal	Consensus includes gb: AW157070	201983_s_at	EGF
growth factor	/FEA = EST /DB_XREF = gi: 6228471		receptor
receptor	/DB_XREF = est: au91e07.x1		signaling
(erythroblastic	/CLONE = IMAGE: 2783652		pathway
leukemia viral (v-	/UG = Hs.77432 epidermal growth factor
erb-b) oncogene	receptor (avian erythroblastic leukemia
homolog, avian)	viral (v-erb-b) oncogene homolog)
(LOC1956)	/FL = gb: NM_005228.1
SEQ ID NOS: 86
(DNA) and 285
(amino acid)
AMPD2:	Consensus includes gb: AI916249	212360_at	purine
adenosine	/FEA = EST /DB_XREF = gi: 5636104		nucleotide
monophosphate	/DB_XREF = est: wg99c01.x1		metabolism
deaminase 2	/CLONE = IMAGE: 2379360
(isoform L)	/UG = Hs.82927 adenosine
(LOC271)	monophosphate deaminase 2 (isoform L)
SEQ ID NOS: 87	/FL = gb: NM_004037.2
(DNA) and 286
(amino acid)
GLS: glutaminase	“gb: AF158555.1 /DEF = Homo sapiens	221510_s_at	glutamine
(LOC2744)	glutaminase C mRNA, complete cds.		catabolism
SEQ ID NOS: 88	/FEA = mRNA /PROD = glutaminase C
(DNA) and 287	/DB_XREF = gi: 5690371
(amino acid)	/UG = Hs.239189 glutaminase
	/FL = gb: AF158555.1 gb: AF097492.1”
EBNA1BP2:	“gb: NM_006824.1 /DEF = Homo sapiens	201323_at	ribosome
EBNA1 binding	nucleolar protein p40; homolog of yeast		biogenesis
protein 2	EBNA1-binding protein (P40), mRNA.
(LOC10969)	/FEA = mRNA /GEN = P40
SEQ ID NOS: 89	/PROD = nucleolar protein p40; homolog
(DNA) and 288	of yeastEBNA1-binding protein
(amino acid)	/DB_XREF = gi: 5803110 /UG = Hs.74407
	nucleolar protein p40; homolog of yeast
	EBNA1-binding protein
	/FL = gb: U86602.1 gb: NM_006824.1”
VIM: vimentin	Consensus includes gb: AI922599	201426_s_at
(LOC7431)	/FEA = EST /DB_XREF = gi: 5658563
SEQ ID NOS: 90	/DB_XREF = est: wm90b11.x1
(DNA) and 289	/CLONE = IMAGE: 2443197
(amino acid)	/UG = Hs.297753 vimentin
	/FL = gb: BC000163.2 gb: NM_003380.1
ZNF258: zinc	“gb: NM_007167.1 /DEF = Homo sapiens	219924_s_at	development
finger protein 258	zinc finger protein 258 (ZNF258),
(LOC9204)	mRNA. /FEA = mRNA /GEN = ZNF258
SEQ ID NOS: 91	/PROD = zinc finger protein 258
(DNA) and 290	/DB_XREF = gi: 6005977
(amino acid)	/UG = Hs.301637 zinc finger protein 258
	/FL = gb: AF055470.1 gb: NM_007167.1”
SGCE:	“gb: NM_003919.1 /DEF = Homo sapiens	204688_at	muscle
sarcoglycan,	sarcoglycan, epsilon (SGCE), mRNA.		development
epsilon	/FEA = mRNA /GEN = SGCE
(LOC8910)	/PROD = sarcoglycan, epsilon
SEQ ID NOS: 92	/DB_XREF = gi: 10835046
(DNA) and 291	/UG = Hs.110708 sarcoglycan, epsilon
(amino acid)	/FL = gb: NM_003919.1 gb: AF036364.1”
CD44: CD44	“gb: M24915.1 /DEF = Human CDw44	204490_s_at	cell-cell
antigen (homing	antigen, complete cds. /FEA = mRNA		adhesion
function and	/DB_XREF = gi: 180196 /UG = Hs.169610
Indian blood group	CD44 antigen (homing function and
system) (LOC960)	Indian blood group system)
SEQ ID NOS: 93	/FL = gb: NM_000610.1 gb: U40373.1
(DNA) and 292	gb: M59040.1 gb: M24915.1”
(amino acid)
SHCBP1: likely	“gb: NM_024745.1 /DEF = Homo sapiens	219493_at
ortholog of mouse	hypothetical protein FLJ22009
Shc SH2-domain	(FLJ22009), mRNA. /FEA = mRNA
binding protein 1	/GEN = FLJ22009 /PROD = hypothetical
(LOC79801)	protein FLJ22009
SEQ ID NOS: 94	/DB_XREF = gi: 13376069
(DNA) and 293	/UG = Hs.123253 hypothetical protein
(amino acid)	FLJ22009 /FL = gb: NM_024745.1”
IMP-3: IGF-II	“gb: NM_006547.1 /DEF = Homo sapiens	203820_s_at	protein
mRNA-binding	IGF-II mRNA-binding protein 3		biosynthesis
protein 3	(KOC1), mRNA. /FEA = mRNA
(LOC10643)	/GEN = KOC1 /PROD = IGF-II mRNA-
SEQ ID NOS: 95	binding protein 3
(DNA) and 294	/DB_XREF = gi: 5729900 /UG = Hs.79440
(amino acid)	IGF-II mRNA-binding protein 3
	/FL = gb: U97188.1 gb: U76705.1
	gb: AF117108.1 gb: NM_006547.1”
BTG3: BTG	“gb: NM_006806.1 /DEF = Homo sapiens	205548_s_at	regulation
family, member 3	BTG family, member 3 (BTG3), mRNA.		of cell
(LOC10950)	/FEA = mRNA /GEN = BTG3		cycle
SEQ ID NOS: 96	/PROD = BTG family, member 3
(DNA) and 295	/DB_XREF = gi: 5802989 /UG = Hs.77311
(amino acid)	BTG family, member 3
	/FL = gb: D64110.1 gb: NM_006806.1”
RAI14: retinoic	“gb: NM_015577.1 /DEF = Homo sapiens	202052_s_at
acid induced 14	novel retinal pigment epithelial gene
(LOC26064)	(NORPEG), mRNA. /FEA = mRNA
SEQ ID NOS: 97	/GEN = NORPEG
(DNA) and 296	/PROD = DKFZP564G013 protein
(amino acid)	/DB_XREF = gi: 13470085
	/UG = Hs.15165 novel retinal pigment
	epithelial gene /FL = gb: NM_015577.1
	gb: AF155135.1”
QKI: quaking	Consensus includes gb: AA149639	212262_at	signal
homolog, KH	/FEA = EST /DB_XREF = gi: 1720440		transduction
domain RNA	/DB_XREF = est: zl39c06.s1
binding (mouse)	/CLONE = IMAGE: 504298
(LOC9444)	/UG = Hs.15020 homolog of mouse
SEQ ID NOS: 98	quaking QKI (KH domain RNA binding
(DNA) and 297	protein) /FL = gb: AF142419.1
(amino acid)	gb: AF142422.1
CGI-100: CGI-100	“Consensus includes gb: AL117354	202194_at	intracellular
protein	/DEF = Human DNA sequence from clone		protein
(LOC50999)	RP5-976O13 on chromosome 1p21.2-22.2		transport
SEQ ID NOS: 99	Contains part of the gene for CGI-
(DNA) and 298	100 protein, 3 isoforms of the gene for
(amino acid)	M96 protein, ESTs, STSs, GSSs and a
	CpG Island /FEA = mRNA_1
	/DB_XREF = gi: 6822199
	/UG = Hs.296155 CGI-100 protein
	/FL = gb: AF151858.1 gb: NM_016040.1”
CTSZ: cathepsin Z	“gb: AF073890.1 /DEF = Homo sapiens	210042_s_at	proteolysis
(LOC1522)	cathepsin X precursor, mRNA, complete		and
SEQ ID NOS: 100	cds. /FEA = mRNA /PROD = cathepsin X		peptidolysis
(DNA) and 299	precursor /DB_XREF = gi: 3650497
(amino acid)	/UG = Hs.252549 cathepsin Z
	/FL = gb: AF032906.1 gb: AF073890.1
	gb: NM_001336.1 gb: AF136273.1”

The biomarkers provided in Table 2 include the nucleotide sequences of SEQ ID NOS:101-200 and the amino acid sequences of SEQ ID NOS:300-395.

TABLE 2
BIOMARKERS (RESISTANT)
		Affymetrix
Unigene title and		Probe	Gene
SEQ ID NO:	Affymetrix Description	Set	Ontology
GATA3: GATA	“gb: BC003070.1 /DEF = Homo sapiens,	209604_s_at	proteolysis
binding protein 3	GATA-binding protein 3, clone		and
(LOC2625)	MGC: 2346, mRNA, complete cds.		peptidolysis
SEQ ID NOS: 101	/FEA = mRNA /PROD = GATA-binding
(DNA) and 300	protein 3 /DB_XREF = gi: 13111765
(amino acid)	/UG = Hs.169946 GATA-binding protein
	3 /FL = gb: BC003070.1 gb: M69106.1
	gb: NM_002051.1”
TFF1: trefoil	“gb: NM_003225.1 /DEF = Homo sapiens	205009_at	carbohydrate
factor 1 (breast	trefoil factor 1 (breast cancer, estrogen-		metabolism,
cancer, estrogen-	inducible sequence expressed in) (TFF1),		cell
inducible sequence	mRNA. /FEA = mRNA /GEN = TFF1		growth
expressed in)	/PROD = trefoil factor 1 (breast		and/or
(LOC7031)	cancer, estrogen-inducible sequence		maintenance
SEQ ID NOS: 102	expressed in) /DB_XREF = gi: 4507450
(DNA) and 301	/UG = Hs.1406 trefoil factor 1 (breast
(amino acid)	cancer, estrogen-inducible sequence
	expressed in) /FL = gb: NM_003225.1”
ZFYVE21: zinc	“gb: NM_024071.1 /DEF = Homo sapiens	219929_s_at
finger, FYVE	hypothetical protein MGC2550
domain containing	(MGC2550), mRNA. /FEA = mRNA
21 (LOC79038)	/GEN = MGC2550 /PROD = hypothetical
SEQ ID NOS: 103	protein MGC2550
(DNA) and 302	/DB_XREF = gi: 13129053
(amino acid)	/UG = Hs.318498 hypothetical protein
	MGC2550 /FL = gb: BC001130.1
	gb: NM_024071.1”
ATP5G2: ATP	“gb: D13119.1 /DEF = Homo sapiens P2	208764_s_at	proton
synthase, H+	mRNA for ATP synthase subunit c,		transport
transporting,	complete cds. /FEA = mRNA /GEN = P2
mitochondrial F0	/PROD = ATP synthase subunit c
complex, subunit c	precursor /DB_XREF = gi: 285909
(subunit 9),	/UG = Hs.89399 ATP synthase, H+
isoform 2	transporting, mitochondrial F0 complex,
(LOC517)	subunit c (subunit 9), isoform 2
SEQ ID NOS: 104	/FL = gb: D13119.1”
(DNA) and 303
(amino acid)
EGFL5: EGF-like-	“Consensus includes gb: W68084	212830_at	metabolism
domain, multiple 5	/FEA = EST /DB_XREF = gi: 1376954
(LOC1955)	/DB_XREF = est: zd42f12.s1
SEQ ID NOS: 105	/CLONE = IMAGE: 343343 /UG = Hs.5599
(DNA) and 304	EGF-like-domain, multiple 5”
(amino acid)
MCCC2:	“gb: AB050049.1 /DEF = Homo sapiens	209624_s_at	leucine
methylcrotonoyl-	mccb mRNA for non-biotin containing		catabolism
Coenzyme A	subunit of 3-methylcrotonyl-CoA
carboxylase 2	carboxylase, complete cds.
(beta)	/FEA = mRNA /GEN = mccb /PROD = non-
(LoC64087)	biotin containing subunit of3-
SEQ ID NOS: 106	methylcrotonyl-CoA carboxylase
(DNA) and 305	/DB_XREF = gi: 10934058
(amino acid)	/UG = Hs.167531 methylcrotonoyl-
	Coenzyme A carboxylase 2 (beta)
	/FL = gb: AB050049.1 gb: AF310971.1
	gb: AF301000.1 gb: NM_022132.2”
ABAT: 4-	“gb: AF237813.1 /DEF = Homo sapiens	209460_at
aminobutyrate	NPD009 mRNA, complete cds.
aminotransferase	/FEA = mRNA /PROD = NPD009
(LOC18)	/DB_XREF = gi: 9963907
SEQ ID NOS: 107	/UG = Hs.283675 NPD009 protein
(DNA) and 306	/FL = gb: NM_020686.1 gb: AF237813.1”
(amino acid)
—: Clone	“Consensus includes gb: AV700224	208774_at	signal
IMAGE: 3869896,	/FEA = EST /DB_XREF = gi: 10302195		transduction
mRNA	/DB_XREF = est: AV700224
(LOC388434)	/CLONE = GKCARG01 /UG = Hs.75852
SEQ ID NOS: 108	casein kinase 1, delta
(DNA)	/FL = gb: BC003558.1”
FEM1B: fem-1	Consensus includes gb: AI799061	212367_at	induction
homolog b (C. elegans)	/FEA = EST /DB_XREF = gi: 5364533		of
(LOC10116)	/DB_XREF = est: we98a10.x1		apoptosis
SEQ ID NOS: 109	/CLONE = IMAGE: 2349114
(DNA) and 307	/UG = Hs.6048 FEM-1 (C. elegans)
(amino acid)	homolog b /FL = gb: AF178632.1
	gb: NM_015322.1 gb: AF204883.1
SLC35A1: solute	“gb: NM_006416.1 /DEF = Homo sapiens	203306_s_at
carrier family 35	solute carrier family 35 (CMP-sialic acid
(CMP-sialic acid	transporter), member 1 (SLC35A1),
transporter),	mRNA. /FEA = mRNA /GEN = SLC35A1
member A1	/PROD = solute carrier family 35 (CMP-
(LOC10559)	sialic acidtransporter), member 1
SEQ ID NOS: 110	/DB_XREF = gi: 5453620 /UG = Hs.82921
(DNA) and 308	solute carrier family 35 (CMP-sialic acid
(amino acid)	transporter), member 1 /FL = gb: D87969.1
	gb: NM_006416.1”
ZNF607: zinc	Consensus includes gb: AL560017	200658_s_at	DNA
finger protein 607	/FEA = EST /DB_XREF = gi: 12906073		metabolism
(LOC84775)	/DB_XREF = est: AL560017
SEQ ID NOS: 111	/CLONE = CS0DG004YD08 (5 prime)
(DNA) and 309	/UG = Hs.75323 prohibitin
(amino acid)	/FL = gb: NM_002634.2
FLJ11164:	“gb: NM_018346.1 /DEF = Homo sapiens	218307_at
hypothetical	hypothetical protein FLJ11164
protein FLJ11164	(FLJ11164), mRNA. /FEA = mRNA
(LOC55316)	/GEN = FLJ11164 /PROD = hypothetical
SEQ ID NOS: 112	protein FLJ11164
(DNA) and 310	/DB_XREF = gi: 8922910 /UG = Hs.8033
(amino acid)	hypothetical protein FLJ11164
	/FL = gb: NM_018346.1”
ABAT: 4-	“gb: NM_000663.1 /DEF = Homo sapiens	206527_at	aminobutyrate
aminobutyrate	4-aminobutyrate aminotransferase		metabolism
aminotransferase	(ABAT), nuclear gene encoding
(LOC18)	mitochondrial protein, mRNA.
SEQ ID NOS: 113	/FEA = mRNA /GEN = ABAT /PROD = 4-
(DNA) and 311	aminobutyrate aminotransferase
(amino acid)	precursor /DB_XREF = gi: 4501846
	/UG = Hs.1588 4-aminobutyrate
	aminotransferase /FL = gb: NM_000663.1
	gb: L32961.1”
SLC19A2: solute	“gb: AF153330.1 /DEF = Homo sapiens	209681_at	small
carrier family 19	thiamine carrier 1 (TC1) mRNA,		molecule
(thiamine	complete cds. /FEA = mRNA /GEN = TC1		transport
transporter),	/PROD = thiamine carrier 1
member 2	/DB_XREF = gi: 5453325 /UG = Hs.30246
(LOC10560)	solute carrier family 19 (thiamine
SEQ ID NOS: 114	transporter), member 2
(DNA) and 312	/FL = gb: AF153330.1 gb: AF135488.1
(amino acid)	gb: AF160812.1”
SLC9A3R1: solute	“gb: NM_004252.1 /DEF = Homo sapiens	201349_at	intracellular
carrier family 9	solute carrier family 9 (sodiumhydrogen		signaling
(sodium/hydrogen	exchanger), isoform 3 regulatory factor 1		cascade
exchanger),	(SLC9A3R1), mRNA. /FEA = mRNA
isoform 3 regulator	/GEN = SLC9A3R1 /PROD = solute carrier
1 (LOC9368)	family 9 (sodiumhydrogenexchanger),
SEQ ID NOS: 115	isoform 3 regulatory factor 1
(DNA) and 313	/DB_XREF = gi: 4759139
(amino acid)	/UG = Hs.184276 solute carrier family 9
	(sodiumhydrogen exchanger), isoform 3
	regulatory factor 1 /FL = gb: BC001443.1
	gb: BC003361.1 gb: AF036241.1
	gb: AF015926.1 gb: NM_004252.1”
ICA1: islet cell	“gb: L21181.1 /DEF = Human autoantigen	210547_x_at
autoantigen 1,	p69 mRNA, complete cds. /FEA = mRNA
69 kDa (LOC3382)	/PROD = autoantigen p69
SEQ ID NOS: 116	/DB_XREF = gi: 437366 /UG = Hs.167927
(DNA) and 314	islet cell autoantigen 1 (69 kD)
(amino acid)	/FL = gb: L21181.1”
CIRBP: cold	“gb: NM_001280.1 /DEF = Homo sapiens	200811_at	response
inducible RNA	cold inducible RNA-binding protein		to cold
binding protein	(CIRBP), mRNA. /FEA = mRNA
(LOC1153)	/GEN = CIRBP /PROD = cold inducible
SEQ ID NOS: 117	RNA-binding protein
(DNA) and 315	/DB_XREF = gi: 4502846
(amino acid)	/UG = Hs.119475 cold inducible RNA-
	binding protein /FL = gb: D78134.1
	gb: BC000403.1 gb: BC000901.1
	gb: AF021336.1 gb: NM_001280.1”
C14orf114:	“gb: NM_018199.1 /DEF = Homo sapiens	218363_at
chromosome 14	hypothetical protein FLJ10738
open reading	(FLJ10738), mRNA. /FEA = mRNA
frame 114	/GEN = FLJ10738 /PROD = hypothetical
(LOC55218)	protein FLJ10738
SEQ ID NOS: 118	/DB_XREF = gi: 8922630 /UG = Hs.5457
(DNA) and 316	hypothetical protein FLJ10738
(amino acid)	/FL = gb: BC001962.1 gb: NM_018199.1”
GREB1: GREB1	“gb: NM_014668.1 /DEF = Homo sapiens	205862_at
protein	KIAA0575 gene product (KIAA0575),
(LOC9687)	mRNA. /FEA = mRNA /GEN = KIAA0575
SEQ ID NOS: 119	/PROD = KIAA0575 gene product
(DNA) and 317	/DB_XREF = gi: 7662187
(amino acid)	/UG = Hs.193914 KIAA0575 gene
	product /FL = gb: AB011147.1
	gb: NM_014668.1”
ESR1: estrogen	“gb: NM_000125.1 /DEF = Homo sapiens	205225_at	nuclear
receptor 1	estrogen receptor 1 (ESR1), mRNA.		hormone
(LOC2099)	/FEA = mRNA /GEN = ESR1		receptor,
SEQ ID NOS: 120	/PROD = estrogen receptor 1		cellular
(DNA) and 318	/DB_XREF = gi: 4503602 /UG = Hs.1657		proliferation
(amino acid)	estrogen receptor 1		and
	/FL = gb: NM_000125.1”		differentiation
ABAT: 4-	“gb: AF237813.1 /DEF = Homo sapiens	209459_s_at
aminobutyrate	NPD009 mRNA, complete cds.
aminotransferase	/FEA = mRNA /PROD = NPD009
(LOC18)	/DB_XREF = gi: 9963907
SEQ ID NOS: 121	/UG = Hs.283675 NPD009 protein
(DNA) and 319	/FL = gb: NM_020686.1 gb: AF237813.1”
(amino acid)
ABCG1: ATP-	“gb: NM_004915.2 /DEF = Homo sapiens	204567_s_at	small
binding cassette,	ATP-binding cassette, sub-family G		molecule
sub-family G	(WHITE), member 1 (ABCG1),		transport
(WHITE), member	transcript variant 1, mRNA.
1 (LOC9619)	/FEA = mRNA /GEN = ABCG1
SEQ ID NOS: 122	/PROD = ATP-binding cassette sub-
(DNA) and 320	family G member 1isoform a
(amino acid)	/DB_XREF = gi: 8051574 /UG = Hs.10237
	ATP-binding cassette, sub-family G
	(WHITE), member 1
	/FL = gb: NM_004915.2”
SLC35B1: solute	“gb: NM_005827.1 /DEF = Homo sapiens	202433_at	transport
carrier family 35,	UDP-galactose transporter related
member B1	(UGTREL1), mRNA. /FEA = mRNA
(LOC10237)	/GEN = UGTREL1 /PROD = UDP-
SEQ ID NOS: 123	galactose transporter related
(DNA) and 321	/DB_XREF = gi: 5032212
(amino acid)	/UG = Hs.154073 UDP-galactose
	transporter related /FL = gb: D87989.1
	gb: NM_005827.1”
TOB1: transducer	“Consensus includes gb: AA675892	202704_at	negative
of ERBB2, 1	/FEA = EST /DB_XREF = gi: 2775239		regulation
(LOC10140)	/DB_XREF = est: b03503s		of cell
SEQ ID NOS: 124	/CLONE = b03503 /UG = Hs.178137		proliferation
(DNA) and 322	transducer of ERBB2, 1
(amino acid)	/FL = gb: D38305.1 gb: NM_005749.1”
FOXA1: forkhead	“gb: NM_004496.1 /DEF = Homo sapiens	204667_at	regulation
box A1	hepatocyte nuclear factor 3, alpha		of
(LOC3169)	(HNF3A), mRNA. /FEA = mRNA		transcription,
SEQ ID NOS: 125	/GEN = HNF3A /PROD = hepatocyte		DNA-
(DNA) and 323	nuclear factor 3, alpha		dependent
(amino acid)	/DB_XREF = gi: 4758533
	/UG = Hs.299867 hepatocyte nuclear
	factor 3, alpha /FL = gb: U39840.1
	gb: NM_004496.1”
LARGE: like-	“Consensus includes gb: AB011181.2	215543_s_at	muscle
glycosyltransferase	/DEF = Homo sapiens mRNA for		maintenance,
(LOC9215)	KIAA0609 protein, partial cds.		glycosphingolipid
SEQ ID NOS: 126	/FEA = mRNA /GEN = KIAA0609		biosynthesis
(DNA) and 324	/PROD = KIAA0609 protein
(amino acid)	/DB_XREF = gi: 6683718 /UG = Hs.25220
	like-glycosyltransferase”
AKT1: v-akt	“gb: NM_005163.1 /DEF = Homo sapiens	207163_s_at	signal
murine thymoma	v-akt murine thymoma viral oncogene		transduction
viral oncogene	homolog 1 (AKT1), mRNA.
homolog 1	/FEA = mRNA /GEN = AKT1
(LOC207)	/PROD = serinethreonine protein kinase
SEQ ID NOS: 127	/DB_XREF = gi: 4885060 /UG = Hs.71816
(DNA) and 325	v-akt murine thymoma viral oncogene
(amino acid)	homolog 1 /FL = gb: M63167.1
	gb: NM_005163.1”
CTPS2: CTP	“gb: NM_019857.1 /DEF = Homo sapiens	219080_s_at
synthase II	CTP synthase II (CTPS2), mRNA.
(LOC56474)	/FEA = mRNA /GEN = CTPS2
SEQ ID NOS: 128	/PROD = CTP synthase II
(DNA) and 326	/DB_XREF = gi: 9789918 /UG = Hs.58553
(amino acid)	CTP synthase II /FL = gb: AF226667.1
	gb: NM_019857.1”
RBM8A: RNA	Consensus includes gb: AI738479	214113_s_at	nuclear
binding motif	/FEA = EST /DB_XREF = gi: 5100460		mRNA
protein 8A	/DB_XREF = est: wi32d06.x1		splicing,
(LOC9939)	/CLONE = IMAGE: 2391947		via
SEQ ID NOS: 129	/UG = Hs.65648 RNA binding motif		spliceosome
(DNA) and 327	protein 8A
(amino acid)
SIAH2: seven in	“gb: U76248.1 /DEF = Human hSIAH2	209339_at	small
absentia homolog	mRNA, complete cds. /FEA = mRNA		GTPase
2 (Drosophila)	/PROD = hSIAH2		mediated
(LOC6478)	/DB_XREF = gi: 2673967 /UG = Hs.20191		signal
SEQ ID NOS: 130	seven in absentia (Drosophila) homolog		transduction
(DNA) and 328	2 /FL = gb: U76248.1 gb: NM_005067.1”
(amino acid)
FLJ13855:	“gb: NM_023079.1 /DEF = Homo sapiens	217750_s_at	ubiquitin
hypothetical	hypothetical protein FLJ13855		cycle
protein FLJ13855	(FLJ13855), mRNA. /FEA = mRNA
(LOC65264)	/GEN = FLJ13855 /PROD = hypothetical
SEQ ID NOS: 131	protein FLJ13855
(DNA) and 329	/DB_XREF = gi: 12751494
(amino acid)	/UG = Hs.168232 hypothetical protein
	FLJ13855 /FL = gb: NM_023079.1”
ITPK1: inositol	“gb: AF279372.1 /DEF = Homo sapiens	210740_s_at	signal
1,3,4-triphosphate	inositol 1,3,4-trisphosphate 56-kinase		transduction
5/6 kinase	mRNA, complete cds. /FEA = mRNA
(LOC3705)	/PROD = inositol 1,3,4-trisphosphate 56-
SEQ ID NOS: 132	kinase /DB_XREF = gi: 12006345
(DNA) and 330	/UG = Hs.6453 inositol 1,3,4-triphosphate
(amino acid)	56 kinase /FL = gb: AF279372.1”
SEPX1:	“gb: NM_016332.1 /DEF = Homo sapiens	217977_at
selenoprotein X, 1	selenoprotein X, 1 (SEPX1), mRNA.
(LOC51734)	/FEA = mRNA /GEN = SEPX1
SEQ ID NOS: 133	/PROD = selenoprotein X, 1
(DNA) and 331	/DB_XREF = gi: 7706510
(amino acid)	/UG = Hs.279623 selenoprotein X, 1
	/FL = gb: AF187272.1 gb: BC003127.1
	gb: AF166124.1 gb: NM_016332.1”
IRX5: iroquois	“gb: U90304.1 /DEF = Human iroquois-	210239_at	regulation
homeobox protein	class homeodomain protein IRX-2a		of
5 (LOC10265)	mRNA, complete cds. /FEA = mRNA		transcription,
SEQ ID NOS: 134	/PROD = iroquois-class homeodomain		DNA-
(DNA) and 332	protein IRX-2a /DB_XREF = gi: 1899219		dependent
(amino acid)	/UG = Hs.25351 iroquois homeobox
	protein 5 /FL = gb: U90304.1
	gb: NM_005853.1”
PTEN:	“gb: BC005821.1 /DEF = Homo sapiens,	211711_s_at	regulation
phosphatase and	phosphatase and tensin homolog		of CDK
tensin homolog	(mutated in multiple advanced cancers		activity
(mutated in	1), clone MGC: 11227, mRNA, complete
multiple advanced	cds. /FEA = mRNA /PROD = phosphatase
cancers 1)	and tensin homolog (mutated inmultiple
(LOC5728)	advanced cancers 1)
SEQ ID NOS: 135	/DB_XREF = gi: 13543309
(DNA) and 333	/FL = gb: BC005821.1”
(amino acid)
DP1: polyposis	“gb: BC000232.1 /DEF = Homo sapiens,	208873_s_at
locus protein 1	Similar to deleted in polyposis 1, clone
(LOC7905)	MGC: 2267, mRNA, complete cds.
SEQ ID NOS: 136	/FEA = mRNA /PROD = Similar to deleted
(DNA) and 334	in polyposis 1 /DB_XREF = gi: 12652946
(amino acid)	/UG = Hs.178112 DNA segment, single
	copy probe LNS-CAILNS-CAII (deleted
	in polyposis /FL = gb: BC000232.1”
KIAA1002:	“gb: NM_014925.1 /DEF = Homo sapiens	203831_at
KIAA1002 protein	KIAA1002 protein (KIAA1002), mRNA.
(LOC22864)	/FEA = mRNA /GEN = KIAA1002
SEQ ID NOS: 137	/PROD = KIAA1002 protein
(DNA) and 335	/DB_XREF = gi: 7662441
(amino acid)	/UG = Hs.102483 KIAA1002 protein
	/FL = gb: AB023219.1 gb: AF113695.1
	gb: NM_014925.1”
PDCD4:	“Consensus includes gb: N92498	212593_s_at	apoptosis
programmed cell	/FEA = EST /DB_XREF = gi: 1264807
death 4 (neoplastic	/DB_XREF = est: zb28a04.s1
transformation	/CLONE = IMAGE: 304878
inhibitor)	/UG = Hs.326248 Homo sapiens cDNA:
(LOC27250)	FLJ22071 fis, clone HEP11691”
SEQ ID NOS: 138
(DNA) and 336
(amino acid)
APPBP2: amyloid	Consensus includes gb: AV681579	202629_at	intracellular
beta precursor	/FEA = EST /DB_XREF = gi: 10283442		protein
protein	/DB_XREF = est: AV681579		transport
(cytoplasmic tail)	/CLONE = GKBAFE05 /UG = Hs.84084
binding protein 2	amyloid beta precursor protein
(LOC10513)	(cytoplasmic tail)-binding protein 2
SEQ ID NOS: 139	/FL = gb: AF017782.1 gb: NM_006380.1
(DNA) and 337
(amino acid)
ACVR1B: activin	Consensus includes gb: AL117643.1	213198_at	transmembrane
A receptor, type IB	/DEF = Homo sapiens mRNA; cDNA		receptor
(LOC91)	DKFZp434M245 (from clone		protein
SEQ ID NOS: 140	DKFZp434M245). /FEA = mRNA		serine/threonine
(DNA) and 338	/DB_XREF = gi: 5912233 /UG = Hs.5288		kinase
(amino acid)	Homo sapiens mRNA; cDNA		signaling
	DKFZp434M245 (from clone		pathway
	DKFZp434M245)
TLE3: transducin-	Consensus includes gb: AW873621	212770_at	regulation
like enhancer of	/FEA = EST /DB_XREF = gi: 8007674		of
split 3 (E(sp1)	/DB_XREF = est: ho64d03.x1		transcription,
homolog,	/CLONE = IMAGE: 3042149		DNA-
Drosophila)	/UG = Hs.31305 KIAA1547 protein		dependent
(LOC7090)
SEQ ID NOS: 141
(DNA) and 339
(amino acid)
CIRBP: cold	“gb: NM_001280.1 /DEF = Homo sapiens	200810_s_at	response
inducible RNA	cold inducible RNA-binding protein		to cold
binding protein	(CIRBP), mRNA. /FEA = mRNA
(LOC1153)	/GEN = CIRBP /PROD = cold inducible
SEQ ID NOS: 142	RNA-binding protein
(DNA) and 340	/DB_XREF = gi: 4502846
(amino acid)	/UG = Hs.119475 cold inducible RNA-
	binding protein /FL = gb: D78134.1
	gb: BC000403.1 gb: BC000901.1
	gb: AF021336.1 gb: NM_001280.1”
ABCA3: ATP-	“gb: NM_001089.1 /DEF = Homo sapiens	204343_at	drug
binding cassette,	ATP-binding cassette, sub-family A		resistance
sub-family A	(ABC1), member 3 (ABCA3), mRNA.
(ABC1), member	/FEA = mRNA /GEN = ABCA3
3 (LOC21)	/PROD = ATP-binding cassette, sub-
SEQ ID NOS: 143	family A member 3
(DNA) and 341	/DB_XREF = gi: 4501848 /UG = Hs.26630
(amino acid)	ATP-binding cassette, sub-family A
	(ABC1), member 3 /FL = gb: U78735.1
	gb: NM_001089.1”
MTSS1:	“gb: NM_014751.1 /DEF = Homo sapiens	203037_s_at
metastasis	KIAA0429 gene product (KIAA0429),
suppressor 1	mRNA. /FEA = mRNA /GEN = KIAA0429
(LOC9788)	/PROD = KIAA0429 gene product
SEQ ID NOS: 144	/DB_XREF = gi: 7662113 /UG = Hs.77694
(DNA) and 342	KIAA0429 gene product
(amino acid)	/FL = gb: AB007889.1 gb: NM_014751.1”
CA12: carbonic	“gb: NM_001218.2 /DEF = Homo sapiens	203963_at	one-
anhydrase XII	carbonic anhydrase XII (CA12), mRNA.		carbon
(LOC771)	/FEA = mRNA /GEN = CA12		compound
SEQ ID NOS: 145	/PROD = carbonic anhydrase XII		metabolism
(DNA) and 343	precursor /DB_XREF = gi: 9951924
(amino acid)	/UG = Hs.5338 carbonic anhydrase XII
	/FL = gb: AF037335.1 gb: AF051882.1
	gb: NM_001218.2”
FRAT2: frequently	“gb: AB045118.1 /DEF = Homo sapiens	209864_at
rearranged in	FRAT2 mRNA, complete cds.
advanced T-cell	/FEA = mRNA /GEN = FRAT2
lymphomas 2	/PROD = FRAT2
(LOC23401)	/DB_XREF = gi: 13365650
SEQ ID NOS: 146	/UG = Hs.140720 GSK-3 binding protein
(DNA) and 344	FRAT2 /FL = gb: AB045118.1”
(amino acid)
SUPT4H1:	“gb: NM_003168.1 /DEF = Homo sapiens	201484_at	chromatin
suppressor of Ty 4	suppressor of Ty (S. cerevisiae) 4		modeling
homolog 1 (S. cerevisiae)	homolog 1 (SUPT4H1), mRNA.
(LOC6827)	/FEA = mRNA /GEN = SUPT4H1
SEQ ID NOS: 147	/PROD = suppressor of Ty (S. cerevisiae) 4
(DNA) and 345	homolog 1 /DB_XREF = gi: 4507310
(amino acid)	/UG = Hs.79058 suppressor of Ty
	(S. cerevisiae) 4 homolog 1
	/FL = gb: BC002802.1 gb: U43923.1
	gb: U38818.1 gb: U38817.1
	gb: NM_003168.1”
UBPH: similar to	“gb: NM_019116.1 /DEF = Homo sapiens	205687_at
ubiquitin binding	similar to ubiquitin binding protein
protein	(UBPH), mRNA. /FEA = mRNA
(LOC56061)	/GEN = UBPH /PROD = similar to
SEQ ID NOS: 148	ubiquitin binding protein
(DNA) and 346	/DB_XREF = gi: 9507222
(amino acid)	/UG = Hs.288620 similar to ubiquitin
	binding protein /FL = gb: NM_019116.1”
MGC50853:	“Consensus includes gb: AL043266	212400_at
hypothetical	/FEA = EST /DB_XREF = gi: 5935844
protein	/DB_XREF = est: DKFZp434L1423_s1
MGC50853	/CLONE = DKFZp434L1423
(LOC399665)	/UG = Hs.111334 ferritin, light
SEQ ID NOS: 149	polypeptide”
(DNA) and 347
(amino acid)
TBL1X:	Consensus includes gb: AV753028	213400_s_at	signal
transducin (beta)-	/FEA = EST /DB_XREF = gi: 10910876		transduction
like 1X-linked	/DB_XREF = est: AV753028
(LOC6907)	/CLONE = NPDBCD07 /UG = Hs.76536
SEQ ID NOS: 150	transducin (beta)-like 1
(DNA) and 348
(amino acid)
FLJ11280:	Consensus includes gb: AL561943	221856_s_at
hypothetical	/FEA = EST /DB_XREF = gi: 12909874
protein FLJ11280	/DB_XREF = est: AL561943
(LOC55793)	/CLONE = CS0DB002YO04 (3 prime)
SEQ ID NOS: 151	/UG = Hs.3346 hypothetical protein
(DNA) and 349	FLJ11280
(amino acid)
RHOB: ras	“Consensus includes gb: AI263909	212099_at	Rho
homolog gene	/FEA = EST /DB_XREF = gi: 3872112		protein
family, member B	/DB_XREF = est: qi08f09.x1		signal
(LOC388)	/CLONE = IMAGE: 1855913		transduction
SEQ ID NOS: 152	/UG = Hs.204354 ras homolog gene
(DNA) and 350	family, member B
(amino acid)	/FL = gb: NM_004040.1”
LASS6: LAG1	“Consensus includes gb: BG289001	212442_s_at
longevity	/FEA = EST /DB_XREF = gi: 13044404
assurance homolog	/DB_XREF = est: 602381262F1
6 (S. cerevisiae)	/CLONE = IMAGE: 4499078
(LOC253782)	/UG = Hs.101282 Homo sapiens cDNA:
SEQ ID NOS: 153	FLJ21238 fis, clone COL01115”
(DNA) and 351
(amino acid)
KIAA0515:	“Consensus includes gb: AB011087.1	212068_s_at
KIAA0515	/DEF = Homo sapiens mRNA for
(LOC84726)	KIAA0515 protein, partial cds.
SEQ ID NOS: 154	/FEA = mRNA /GEN = KIAA0515
(DNA)	/PROD = KIAA0515 protein
	/DB_XREF = gi: 3043553
	/UG = Hs.108945 KIAA0515 protein”
MCCC2:	Consensus includes gb: AW439494	209623_at
methylcrotonoyl-	/FEA = EST /DB_XREF = gi: 6974800
Coenzyme A	/DB_XREF = est: xt19c01.x1
carboxylase 2	/CLONE = IMAGE: 2779584
(beta)	/UG = Hs.167531 methylcrotonoyl-
(LOC64087)	Coenzyme A carboxylase 2 (beta)
SEQ ID NOS: 155	/FL = gb: AB050049.1 gb: AF310971.1
(DNA) and 352	gb: AF301000.1 gb: NM_022132.2
(amino acid)
TFF3: trefoil	“gb: NM_003226.1 /DEF = Homo sapiens	204623_at	phosphoenolpyruvate-
factor 3 (intestinal)	trefoil factor 3 (intestinal) (TFF3),		dependent
(LOC7033)	mRNA. /FEA = mRNA /GEN = TFF3		sugar
SEQ ID NOS: 156	/PROD = trefoil factor 3 (intestinal)		phosphotransferase
(DNA) and 353	/DB_XREF = gi: 4507452 /UG = Hs.82961		system
(amino acid)	trefoil factor 3 (intestinal)
	/FL = gb: L08044.1 gb: L15203.1
	gb: NM_003226.1”
GATA3: GATA	Consensus includes gb: AI796169	209603_at	defense
binding protein 3	/FEA = EST /DB_XREF = gi: 5361632		response
(LOC2625)	/DB_XREF = est: wh43d10.x1
SEQ ID NOS: 157	/CLONE = IMAGE: 2383507
(DNA) and 354	/UG = Hs.169946 GATA-binding protein
(amino acid)	3 /FL = gb: BC003070.1 gb: M69106.1
	gb: NM_002051.1
CEBPA:	“gb: NM_004364.1 /DEF = Homo sapiens	204039_at
CCAAT/enhancer	CCAATenhancer binding protein
binding protein	(CEBP), alpha (CEBPA), mRNA.
(C/EBP), alpha	/FEA = mRNA /GEN = CEBPA
(LOC1050)	/PROD = CCAATenhancer binding
SEQ ID NOS: 158	protein (CEBP), alpha
(DNA) and 355	/DB_XREF = gi: 4757971 /UG = Hs.76171
(amino acid)	CCAATenhancer binding protein
	(CEBP), alpha /FL = gb: NM_004364.1”
LOC92482:	“Consensus includes gb: AK025724.1	213224_s_at
hypothetical	/DEF = Homo sapiens cDNA: FLJ22071
protein LOC92482	fis, clone HEP11691. /FEA = mRNA
(LOC92482)	/DB_XREF = gi: 10438333
SEQ ID NOS: 159	/UG = Hs.326248 Homo sapiens cDNA:
(DNA)	FLJ22071 fis, clone HEP11691”
FLJ13910:	Consensus includes gb: BF671894	212482_at
hypothetical	/FEA = EST /DB_XREF = gi: 11945789
protein FLJ13910	/DB_XREF = est: 602151796F1
(LOC64795)	/CLONE = IMAGE: 4292999
SEQ ID NOS: 160	/UG = Hs.75277 hypothetical protein
(DNA) and 356	FLJ13910
(amino acid)
C14orf130:	“gb: NM_018108.1 /DEF = Homo sapiens	218108_at
chromosome 14	hypothetical protein FLJ10483
open reading	(FLJ10483), mRNA. /FEA = mRNA
frame 130	/GEN = FLJ10483 /PROD = hypothetical
(LOC55148)	protein FLJ10483
SEQ ID NOS: 161	/DB_XREF = gi: 8922451 /UG = Hs.6877
(DNA) and 357	hypothetical protein FLJ10483
(amino acid)	/FL = gb: NM_018108.1”
CDKN1B: cyclin-	“gb: BC001971.1 /DEF = Homo sapiens,	209112_at	regulation
dependent kinase	Similar to cyclin-dependent kinase		of CDK
inhibitor 1B (p27,	inhibitor 1B (p27, Kip1), clone		activity
Kip1) (LOC1027)	MGC: 5304, mRNA, complete cds.
SEQ ID NOS: 162	/FEA = mRNA /PROD = Similar to cyclin-
(DNA) and 358	dependent kinase inhibitor 1B(p27, Kip1)
(amino acid)	/DB_XREF = gi: 12805034
	/UG = Hs.238990 cyclin-dependent kinase
	inhibitor 1B (p27, Kip1)
	/FL = gb: BC001971.1 gb: NM_004064.1
	gb: U10906.1 gb: AF247551.1
	gb: AY004255.1”
APPBP2: amyloid	“gb: NM_006380.1 /DEF = Homo sapiens	202631_s_at	intracellular
beta precursor	amyloid beta precursor protein		protein
protein	(cytoplasmic tail)-binding protein 2		transport
(cytoplasmic tail)	(APPBP2), mRNA. /FEA = mRNA
binding protein 2	/GEN = APPBP2 /PROD = amyloid beta
(LOC10513)	precursor protein (cytoplasmictail)-
SEQ ID NOS: 163	binding protein 2
(DNA) and 359	/DB_XREF = gi: 5453552 /UG = Hs.84084
(amino acid)	amyloid beta precursor protein
	(cytoplasmic tail)-binding protein 2
	/FL = gb: AF017782.1 gb: NM_006380.1”
LOC81558:	“gb: NM_030802.1 /DEF = Homo sapiens	221249_s_at
C/EBP-induced	CEBP-induced protein (LOC81558),
protein	mRNA. /FEA = mRNA /GEN = LOC81558
(LOC81558)	/PROD = CEBP-induced protein
SEQ ID NOS: 164	/DB_XREF = gi: 13540589
(DNA) and 360	/FL = gb: NM_030802.1”
(amino acid)
FLJ20274:	Consensus includes gb: AL134904	213025_at
hypothetical	/FEA = EST /DB_XREF = gi: 6603091
protein FLJ20274	/DB_XREF = est: DKFZp762M0710_s1
(LOC55623)	/CLONE = DKFZp762M0710
SEQ ID NOS: 165	/UG = Hs.268371 hypothetical protein
(DNA) and 361	FLJ20274
(amino acid)
RAB11A:	“gb: NM_004663.1 /DEF = Homo sapiens	200864_s_at	intracellular
RAB11A, member	RAB11A, member RAS oncogene family		protein
RAS oncogene	(RAB11A), mRNA. /FEA = mRNA		transport
family (LOC8766)	/GEN = RAB11A /PROD = RAB11A,
SEQ ID NOS: 166	member RAS oncogene family
(DNA) and 362	/DB_XREF = gi: 4758983 /UG = Hs.75618
(amino acid)	RAB11A, member RAS oncogene family
	/FL = gb: AF000231.1 gb: NM_004663.1”
—: MRNA; cDNA	Consensus includes gb: BE967207	212114_at
DKFZp313P052	/FEA = EST /DB_XREF = gi: 11773627
(from clone	/DB_XREF = est: 601661094R1
DKFZp313P052)	/CLONE = IMAGE: 3916174
(LOC387869)	/UG = Hs.165590 ribosomal protein S13
SEQ ID NOS: 167
(DNA) and 363
(amino acid)
NPEPPS:	“Consensus includes gb: AJ132583.1	201455_s_at	proteolysis
aminopeptidase	/DEF = Homo sapiens mRNA for		and
puromycin	puromycin sensitive aminopeptidase,		peptidolysis
sensitive	partial. /FEA = mRNA
(LOC9520)	/PROD = puromycin sensitive
SEQ ID NOS: 168	aminopeptidase /DB_XREF = gi: 4210725
(DNA) and 364	/UG = Hs.293007 aminopeptidase
(amino acid)	puromycin sensitive
	/FL = gb: NM_006310.1”
UBL3: ubiquitin-	“gb: AF044221.1 /DEF = Homo sapiens	201534_s_at
like 3 (LOC5412)	HCG-1 protein (HCG-1) mRNA,
SEQ ID NOS: 169	complete cds. /FEA = mRNA
(DNA) and 365	/GEN = HCG-1 /PROD = HCG-1 protein
(amino acid)	/DB_XREF = gi: 4105251
	/UG = Hs.173091 ubiquitin-like 3
	/FL = gb: AF044221.1 gb: AL080177.1
	gb: NM_007106.1”
BAMBI: BMP and	“gb: NM_012342.1 /DEF = Homo sapiens	203304_at
activin membrane-	putative transmembrane protein (NMA),
bound inhibitor	mRNA. /FEA = mRNA /GEN = NMA
homolog (Xenopus	/PROD = putative transmembrane protein
laevis)	/DB_XREF = gi: 6912533 /UG = Hs.78776
(LOC25805)	putative transmembrane protein
SEQ ID NOS: 170	/FL = gb: U23070.1 gb: NM_012342.1”
(DNA) and 366
(amino acid)
GABPB2: GA	“gb: NM_005254.2 /DEF = Homo sapiens	204618_s_at	regulation
binding protein	GA-binding protein transcription factor,		of
transcription	beta subunit 1 (53 kD) (GABPB1),		transcription
factor, beta subunit	transcript variant beta, mRNA.		DNA-
2, 47 kDa	/FEA = mRNA /GEN = GABPB1		dependent
(LOC2553)	/PROD = GA-binding protein
SEQ ID NOS: 171	transcription factor, betasubunit 1
(DNA) and 367	(53 kD), isoform beta 1
(amino acid)	/DB_XREF = gi: 8051592 /UG = Hs.78915
	GA-binding protein transcription factor,
	beta subunit 1 (53 kD) /FL = gb: U13045.1
	gb: NM_005254.2”
MAPT:	“gb: J03778.1 /DEF = Human microtubule-	206401_s_at	microtubule
microtubule-	associated protein tau mRNA, complete		cytoskeleton
associated protein	cds. /FEA = mRNA /GEN = MTBT1		organization
tau (LOC4137)	/DB_XREF = gi: 338684 /UG = Hs.101174		and
SEQ ID NOS: 172	microtubule-associated protein tau		biogenesis
(DNA) and 368	/FL = gb: BC000558.1 gb: J03778.1
(amino acid)	gb: NM_016841.1”
WBSCR21:	Consensus includes gb: AI923458	221927_s_at
Williams Beuren	/FEA = EST /DB_XREF = gi: 5659422
syndrome	/DB_XREF = est: wn85h04.x1
chromosome	/CLONE = IMAGE: 2452663
region 21	/UG = Hs.182476 Homo sapiens clone
(LOC83451)	PP1226 unknown mRNA
SEQ ID NOS: 173
(DNA) and 369
(amino acid)
ZNF278: zinc	“gb: AF242522.1 /DEF = Homo sapiens	211392_s_at
finger protein 278	krueppel-related zinc finger protein
(LOC23598)	SBZF5 mRNA, complete cds.
SEQ ID NOS: 174	/FEA = mRNA /PROD = krueppel-related
(DNA) and 370	zinc finger protein SBZF5
(amino acid)	/DB_XREF = gi: 9802041 /UG = Hs.27801
	zinc finger protein 278
	/FL = gb: AF242522.1”
SUPT4H1:	“gb: BC002802.1 /DEF = Homo sapiens,	201483_s_at	chromatin
suppressor of Ty 4	suppressor of Ty (S. cerevisiae) 4		modeling
homolog 1 (S. cerevisiae)	homolog 1, clone MGC: 3864, mRNA,
(LOC6827)	complete cds. /FEA = mRNA
SEQ ID NOS: 175	/PROD = suppressor of Ty (S. cerevisiae) 4
(DNA) and 371	homolog 1 /DB_XREF = gi: 12803910
(amino acid)	/UG = Hs.79058 suppressor of Ty
	(S. cerevisiae) 4 homolog 1
	/FL = gb: BC002802.1 gb: U43923.1
	gb: U38818.1 gb: U38817.1
	gb: NM_003168.1”
RAB4B: RAB4B,	“gb: NM_016154.1 /DEF = Homo sapiens	219807_x_at
member RAS	ras-related GTP-binding protein 4b
oncogene family	(RAB4B), mRNA. /FEA = mRNA
(LOC53916)	/GEN = RAB4B /PROD = ras-related GTP-
SEQ ID NOS: 176	binding protein 4b
(DNA) and 372	/DB_XREF = gi: 7706672
(amino acid)	/UG = Hs.279771 Homo sapiens
	TR00071289_m (RAB4B), mRNA
	/FL = gb: AF165522.1 gb: NM_016154.1”
PEX11B:	“gb: NM_003846.1 /DEF = Homo sapiens	202658_at	peroxisome
peroxisomal	peroxisomal biogenesis factor 11B		organization
biogenesis factor	(PEX11B), mRNA. /FEA = mRNA		and
11B (LOC8799)	/GEN = PEX11B /PROD = peroxisomal		biogenesis
SEQ ID NOS: 177	biogenesis factor 11B
(DNA) and 373	/DB_XREF = gi: 4505718 /UG = Hs.83023
(amino acid)	peroxisomal biogenesis factor 11B
	/FL = gb: AF093670.1 gb: AB018080.1
	gb: NM_003846.1”
LASS6: LAG1	“Consensus includes gb: AI658534	212446_s_at
longevity	/FEA = EST /DB_XREF = gi: 4762104
assurance homolog	/DB_XREF = est: tu17g01.x1
6 (S. cerevisiae)	/CLONE = IMAGE: 2251344
(LOC253782)	/UG = Hs.101282 Homo sapiens cDNA:
SEQ ID NOS: 178	FLJ21238 fis, clone COL01115”
(DNA) and 374
(amino acid)
C10orf86:	“gb: BC005212.1 /DEF = Homo sapiens,	211376_s_at
chromosome 10	Similar to hypothetical protein
open reading	FLJ20003, clone MGC: 12228, mRNA,
frame 86	complete cds. /FEA = mRNA
(LOC54780)	/PROD = Similar to hypothetical protein
SEQ ID NOS: 179	FLJ20003 /DB_XREF = gi: 13528824
(DNA) and 375	/UG = Hs.258798 hypothetical protein
(amino acid)	FLJ20003 /FL = gb: BC005212.1”
PLEKHF2:	“gb: NM_024613.1 /DEF = Homo sapiens	218640_s_at
pleckstrin	hypothetical protein FLJ13187
homology domain	(FLJ13187), mRNA. /FEA = mRNA
containing, family	/GEN = FLJ13187 /PROD = hypothetical
F (with FYVE	protein FLJ13187
domain) member 2	/DB_XREF = gi: 13375826
(LOC79666)	/UG = Hs.29724 hypothetical protein
SEQ ID NOS: 180	FLJ13187 /FL = gb: NM_024613.1”
(DNA) and 376
(amino acid)
KIAA0261:	“Consensus includes gb: D87450.1	212267_at
KIAA0261	/DEF = Human mRNA for KIAA0261
(LOC23063)	gene, partial cds. /FEA = mRNA
SEQ ID NOS: 181	/GEN = KIAA0261
(DNA) and 377	/DB_XREF = gi: 1665788
(amino acid)	/UG = Hs.154978 KIAA0261 protein”
TIP120A: TBP-	gb: AL136810.1 /DEF = Homo sapiens	208839_s_at
interacting protein	mRNA; cDNA DKFZp434G0222 (from
(LOC55832)	clone DKFZp434G0222); complete cds.
SEQ ID NOS: 182	/FEA = mRNA /GEN = DKFZp434G0222
(DNA) and 378	/PROD = hypothetical protein
(amino acid)	/DB_XREF = gi: 12053130
	/UG = Hs.184786 TBP-interacting protein
	/FL = gb: AL136810.1
GATA3: GATA	Consensus includes gb: AI796169	209602_s_at	defense
binding protein 3	/FEA = EST /DB_XREF = gi: 5361632		response
(LOC2625)	/DB_XREF = est: wh43d10.x1
SEQ ID NOS: 183	/CLONE = IMAGE: 2383507
(DNA) and 379	/UG = Hs.169946 GATA-binding protein
(amino acid)	3 /FL = gb: BC003070.1 gb: M69106.1
	gb: NM_002051.1
CGI-85: CGI-85	“gb: NM_017635.1 /DEF = Homo sapiens	218242_s_at
protein	hypothetical protein FLJ20039
(LOC51111)	(FLJ20039), mRNA. /FEA = mRNA
SEQ ID NOS: 184	/GEN = FLJ20039 /PROD = hypothetical
(DNA) and 380	protein FLJ20039
(amino acid)	/DB_XREF = gi: 8923045
	/UG = Hs.267448 hypothetical protein
	FLJ20039 /FL = gb: NM_017635.1”
C20orf11:	“gb: NM_017896.1 /DEF = Homo sapiens	218448_at
chromosome 20	hypothetical protein FLJ20602
open reading	(FLJ20602), mRNA. /FEA = mRNA
frame 11	/GEN = FLJ20602 /PROD = hypothetical
(LOC54994)	protein FLJ20602
SEQ ID NOS: 185	/DB_XREF = gi: 8923556
(DNA) and 381	/UG = Hs.103808 hypothetical protein
(amino acid)	FLJ20602 /FL = gb: NM_017896.1”
IGF1R: insulin-	Consensus includes gb: H05812	203628_at	signal
like growth factor	/FEA = EST /DB_XREF = gi: 869364		transduction
1 receptor	/DB_XREF = est: yl77f04.s1
(LOC3480)	/CLONE = IMAGE: 44149
SEQ ID NOS: 186	/UG = Hs.239176 insulin-like growth
(DNA) and 382	factor 1 receptor /FL = gb: NM_000875.2
(amino acid)
LOC51315:	“gb: NM_016618.1 /DEF = Homo sapiens	218303_x_at
hypothetical	hypothetical protein (LOC51315),
protein LOC51315	mRNA. /FEA = mRNA /GEN = LOC51315
(LOC51315)	/PROD = hypothetical protein
SEQ ID NOS: 187	/DB_XREF = gi: 7706155 /UG = Hs.5721
(DNA) and 383	hypothetical protein /FL = gb: AF208845.1
(amino acid)	gb: AF217520.1 gb: NM_016618.1”
PBP: prostatic	“gb: NM_002567.1 /DEF = Homo sapiens	205353_s_at
binding protein	prostatic binding protein (PBP), mRNA.
(LOC5037)	/FEA = mRNA /GEN = PBP
SEQ ID NOS: 188	/PROD = prostatic binding protein
(DNA) and 384	/DB_XREF = gi: 4505620 /UG = Hs.80423
(amino acid)	prostatic binding protein
	/FL = gb: D16111.1 gb: NM_002567.1”
KIAA0602:	“Cluster Incl. AB011174: Homo sapiens	34406_at
KIAA0602 protein	mRNA for KIAA0602 protein, partial
(LOC23241)	cds /cds = (0,2889) /gb = AB011174
SEQ ID NOS: 189	/gi = 3043727 /ug = Hs.37656 /len = 3428”
(DNA)
MYST2: MYST	“gb: NM_007067.1 /DEF = Homo sapiens	200049_at	regulation
histone	histone acetyltransferase (HBOA),		of
acetyltransferase 2	mRNA. /FEA = mRNA /GEN = HBOA		transcription
(LOC11143)	/PROD = histone acetyltransferase		DNA-
SEQ ID NOS: 190	/DB_XREF = gi: 5901961 /UG = Hs.21907		dependent
(DNA) and 385	histone acetyltransferase
(amino acid)	/FL = gb: AF074606.1 gb: AF140360.1
	gb: NM_007067.1”
C6orf211:	“gb: NM_024573.1 /DEF = Homo sapiens	218195_at
chromosome 6	hypothetical protein FLJ12910
open reading	(FLJ12910), mRNA. /FEA = mRNA
frame 211	/GEN = FLJ12910 /PROD = hypothetical
(LOC79624)	protein FLJ12910
SEQ ID NOS: 191	/DB_XREF = gi: 13375745
(DNA) and 386	/UG = Hs.15929 hypothetical protein
(amino acid)	FLJ12910 /FL = gb: NM_024573.1”
C20orf149:	“gb: NM_024299.1 /DEF = Homo sapiens	218010_x_at
chromosome 20	hypothetical protein MGC2479
open reading	(MGC2479), mRNA. /FEA = mRNA
frame 149	/GEN = MGC2479 /PROD = hypothetical
(LOC79144)	protein MGC2479
SEQ ID NOS: 192	/DB_XREF = gi: 13236523
(DNA) and 387	/UG = Hs.79625 hypothetical protein
(amino acid)	MGC2479 /FL = gb: BC002531.1
	gb: NM_024299.1”
LLGL2: lethal	“gb: NM_004524.1 /DEF = Homo sapiens	203713_s_at
giant larvae	lethal giant larvae (Drosophila) homolog
homolog 2	2 (LLGL2), mRNA. /FEA = mRNA
(Drosophila)	/GEN = LLGL2 /PROD = lethal giant
(LOC3993)	larvae (Drosophila) homolog 2
SEQ ID NOS: 193	/DB_XREF = gi: 4758679 /UG = Hs.3123
(DNA) and 388	lethal giant larvae (Drosophila) homolog
(amino acid)	2 /FL = gb: NM_004524.1”
KIAA0882:	Consensus includes gb: AI348094	212956_at
KIAA0882 protein	/FEA = EST /DB_XREF = gi: 4085300
(LOC23158)	/DB_XREF = est: qp61g12.x1
SEQ ID NOS: 194	/CLONE = IMAGE: 1927558
(DNA) and 389	/UG = Hs.90419 KIAA0882 protein
(amino acid)
CA12: carbonic	“gb: BC001012.1 /DEF = Homo sapiens,	204508_s_at
anhydrase XII	hypothetical protein FLJ20151, clone
(LOC771)	MGC: 1073, mRNA, complete cds.
SEQ ID NOS: 195	/FEA = mRNA /PROD = hypothetical
(DNA) and 390	protein FLJ20151
(amino acid)	/DB_XREF = gi: 12654376
	/UG = Hs.279916 hypothetical protein
	FLJ20151 /FL = gb: BC001012.1
	gb: NM_017689.1”
SLC2A10: solute	“gb: NM_030777.1 /DEF = Homo sapiens	221024_s_at	glucose
carrier family 2	solute carrier family 2 (facilitated		transport
(facilitated glucose	glucose transporter), member 10
transporter),	(SLC2A10), mRNA. /FEA = mRNA
member 10	/GEN = SLC2A10 /PROD = solute carrier
(LOC81031)	family 2 (facilitated glucosetransporter),
SEQ ID NOS: 196	member 10 /DB_XREF = gi: 13540546
(DNA) and 391	/FL = gb: NM_030777.1”
(amino acid)
TRIM37: tripartite	“Consensus includes gb: AK022701.1	213009_s_at
motif-containing	/DEF = Homo sapiens cDNA FLJ12639
37 (LOC4591)	fis, clone NT2RM4001938, highly
SEQ ID NOS: 197	similar to Homo sapiens mRNA for
(DNA) and 392	KIAA0898 protein. /FEA = mRNA
(amino acid)	/DB_XREF = gi: 10434250 /UG = Hs.8164
	Mulibrey nanism”
AP1G1: adaptor-	“Consensus includes gb: AL050025.1	215867_x_at	endocytosis
related protein	/DEF = Homo sapiens mRNA; cDNA
complex 1, gamma	DKFZp564D066 (from clone
1 subunit	DKFZp564D066); partial cds.
(LOC164)	/FEA = mRNA /GEN = DKFZp564D066
SEQ ID NOS: 198	/PROD = hypothetical protein
(DNA) and 393	/DB_XREF = gi: 4884095 /UG = Hs.5344
(amino acid)	adaptor-related protein complex 1,
	gamma 1 subunit”
UBL3: ubiquitin-	“gb: NM_007106.1 /DEF = Homo sapiens	201535_at
like 3 (LOC5412)	ubiquitin-like 3 (UBL3), mRNA.
SEQ ID NOS: 199	/FEA = mRNA /GEN = UBL3
(DNA) and 394	/PROD = ubiquitin-like 3
(amino acid)	/DB_XREF = gi: 6005927
	/UG = Hs.173091 ubiquitin-like 3
	/FL = gb: AF044221.1 gb: AL080177.1
	gb: NM_007106.1”
CYB561:	“Consensus includes gb: U06715.1	217200_x_at	secretory
cytochrome b-561	/DEF = Human cytochrome B561,		vesicle-
(LOC1534)	HCYTO B561, mRNA, partial cds.		specific
SEQ ID NOS: 200	/FEA = mRNA /GEN = B561		electron
(DNA) and 395	/PROD = HCYTO B561		transport
(amino acid)	/DB_XREF = gi: 476590 /UG = Hs.153028		protein
	cytochrome b-561”

Certain biomarkers were of particular interest. Microtubule-associated protein tau was identified as one of the resistance markers, and has been shown to bind at the close site of microtubule where Taxol® binds to. It is believed that Taxol® interferes microtubule and Tau interaction, but Tau's interaction seems more resistant than Taxol® (R. Dye et al., J. Biological Chem., 268, 6847-6850 (1993)). Therefore, this further validates the observation that Tau expressing cells are more resistant to ixabepilone treatment as ixabepilone binds at the same site of Taxol® in tubulin. Another interesting resistance biomarker is estrogen receptor. In general, estrogen-receptor status is predictive of response to hormonal treatments. (J. C. Chang et al., Lancet, 362, 362-369 (2003)). However, it was interesting to observe estrogen receptor as a strong marker for the resistance to ixabepilone. ER has not been previously suggested as a predictive marker of a patient's response to chemotherapy. More interestingly, microtubule associated protein tau is estrogen induced (M. West et al., P. N. A. S. USA, 98, 11462-11467 (2001)). ER and Tau were also found as resistance markers in an analysis of Taxol® (data not provided), and this suggests that Tau and ER both are likely to be the resistance markers for microtubule-stabilizing agents such as ixabepilone and Taxol®.

Several other genes appear promising as potential markers including transporter genes (ATP-binding cassette, sub-family G (WHITE), member 1 and ATP-binding cassette, sub-family A (ABC 1), member 3), Midline 1 (C. Berti et al., BMC Cell Biol., Feb 29; 5(1):9 (2004)), LMP7 and etc. The differential expression patterns of these biomarkers were distinct between the two phenotypes of the cell lines (sensitive and resistant). In addition, their biological functions are involved in drug resistance mechanism or related with microtubule functions. Furthermore, their differential expression patterns observed within tumors support their potential as response markers.

Microtubule-Stabilizing Agents

Agents that affect microtubule-stabilization are well known in the art. These agents have cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease.

In one aspect, the microtubule-stabilizing agent is an epothilone, or analog or derivative thereof. The epothilones, including analogs and derivatives thereof, may be found to exert microtubule-stabilizing effects similar to paclitaxel (Taxol®) and, hence, cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease.

Suitable microtubule-stabilizing agents are disclosed, for example, in the following PCT publications hereby incorporated by reference: WO93/10121; WO98/22461; WO99/02514; WO99/58534; WO00/39276; WO02/14323; WO02/72085; WO02/98868; WO03/07170; WO03/77903; WO03/78411; WO04/80458; WO04/56832; WO04/14919; WO03/92683; WO03/74053; WO03/57217; WO03/22844; WO03/103712; WO03/07924; WO02/74042; WO02/67941; WO01/81342; WO00/66589; WO00/58254; WO99/43320; WO99/42602; WO99/39694; WO99/16416; WO 99/07692; WO99/03848; WO99/01124; and WO 98/25929.

In another aspect, the microtubule-stabilizing agent is ixabepilone. Ixabepilone is a semi-synthetic analog of the natural product epothilone B that binds to tubulin in the same binding site as paclitaxel, but interacts with tubulin differently. (P. Giannakakou et al., P. N. A. S. USA, 97, 2904-2909 (2000)).

In another aspect, the microtubule-stabilizing agent is a taxane. The taxanes are well known in the art and include, for example, paclitaxel (Taxol®) and docetaxel (Taxotere®).

Biomarkers and Biomarker Sets

The invention includes individual biomarkers and biomarker sets having both diagnostic and prognostic value in disease areas in which microtubule-stabilization and/or cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease is of importance, e.g., in cancers or tumors. The biomarker sets comprise a plurality of biomarkers such as, for example, a plurality of the biomarkers provided in Table 1 and Table 2, that highly correlate with resistance or sensitivity to one or more microtubule-stabilizing agents.

The biomarker sets of the invention enable one to predict or reasonably foretell the likely effect of one or more microtubule-stabilizing agents in different biological systems or for cellular responses. The biomarker sets can be used in in vitro assays of microtubule-stabilizing agent response by test cells to predict in vivo outcome. In accordance with the invention, the various biomarker sets described herein, or the combination of these biomarker sets with other biomarkers or markers, can be used, for example, to predict how patients with cancer might respond to therapeutic intervention with one or more microtubule-stabilizing agents.

A biomarker set of cellular gene expression patterns correlating with sensitivity or resistance of cells following exposure of the cells to one or more microtubule-stabilizing agents provides a useful tool for screening one or more tumor samples before treatment with the microtubule-stabilizing agent. The screening allows a prediction of cells of a tumor sample exposed to one or more microtubule-stabilizing agents, based on the expression results of the biomarker set, as to whether or not the tumor, and hence a patient harboring the tumor, will or will not respond to treatment with the microtubule-stabilizing agent.

The biomarker or biomarker set can also be used as described herein for monitoring the progress of disease treatment or therapy in those patients undergoing treatment for a disease involving a microtubule-stabilizing agent.

The biomarkers also serve as targets for the development of therapies for disease treatment. Such targets may be particularly applicable to treatment of breast cancers or tumors. Indeed, because these biomarkers are differentially expressed in sensitive and resistant cells, their expression patterns are correlated with relative intrinsic sensitivity of cells to treatment with microtubule-stabilizing agents. Accordingly, the biomarkers highly expressed in resistant cells may serve as targets for the development of new therapies for the tumors which are resistant to microtubule-stabilizing agents.

The level of biomarker protein and/or mRNA can be determined using methods well known to those skilled in the art. For example, quantification of protein can be carried out using methods such as ELISA, 2-dimensional SDS PAGE, Western blot, immunopreciptation, immunohistochemistry, fluorescence activated cell sorting (FACS), or flow cytometry. Quantification of mRNA can be carried out using methods such as PCR, array hybridization, Northern blot, in-situ hybridization, dot-blot, Taqman, or RNAse protection assay.

Microarrays

The invention also includes specialized microarrays, e.g., oligonucleotide microarrays or cDNA microarrays, comprising one or more biomarkers, showing expression profiles that correlate with either sensitivity or resistance to one or more microtubule-stabilizing agents. Such microarrays can be employed in in vitro assays for assessing the expression level of the biomarkers in the test cells from tumor biopsies, and determining whether these test cells are likely to be resistant or sensitive to microtubule-stabilizing agents. For example, a specialized microarray can be prepared using all the biomarkers, or subsets thereof, as described herein and shown in Table 1 and Table 2. Cells from a tissue or organ biopsy can be isolated and exposed to one or more of the microtubule-stabilizing agents. Following application of nucleic acids isolated from both untreated and treated cells to one or more of the specialized microarrays, the pattern of gene expression of the tested cells can be determined and compared with that of the biomarker pattern from the control panel of cells used to create the biomarker set on the microarray. Based upon the gene expression pattern results from the cells that underwent testing, it can be determined if the cells show a resistant or a sensitive profile of gene expression. Whether or not the tested cells from a tissue or organ biopsy will respond to one or more of the microtubule-stabilizing agents and the course of treatment or therapy can then be determined or evaluated based on the information gleaned from the results of the specialized microarray analysis.

Antibodies

The invention also includes antibodies, including polyclonal or monoclonal, directed against one or more of the polypeptide biomarkers. Such antibodies can be used in a variety of ways, for example, to purify, detect, and target the biomarkers of the invention, including both in vitro and in vivo diagnostic, detection, screening, and/or therapeutic methods.

Kits

The invention also includes kits for determining or predicting whether a patient would be susceptible or resistant to a treatment that comprises one or more microtubule-stabilizing agents. The patient may have a cancer or tumor such as, for example, a breast cancer or tumor. Such kits would be useful in a clinical setting for use in testing a patient's biopsied tumor or other cancer samples, for example, to determine or predict if the patient's tumor or cancer will be resistant or sensitive to a given treatment or therapy with a microtubule-stabilizing agent. The kit comprises a suitable container that comprises: one or more microarrays, e.g., oligonucleotide microarrays or cDNA microarrays, that comprise those biomarkers that correlate with resistance and sensitivity to microtubule-stabilizing agents; one or more microtubule-stabilizing agents for use in testing cells from patient tissue specimens or patient samples; and instructions for use. In addition, kits contemplated by the invention can further include, for example, reagents or materials for monitoring the expression of biomarkers of the invention at the level of mRNA or protein, using other techniques and systems practiced in the art such as, for example, RT-PCR assays, which employ primers designed on the basis of one or more of the biomarkers described herein, immunoassays, such as enzyme linked immunosorbent assays (ELISAs), immunoblotting, e.g., Western blots, or in situ hybridization, and the like, as further described herein.

Application of Biomarkers and Biomarker Sets

The biomarkers and biomarker sets may be used in different applications. Biomarker sets can be built from any combination of biomarkers listed in Table 1 and Table 2 to make predictions about the likely effect of any microtubule-stabilizing agent in different biological systems. The various biomarkers and biomarkers sets described herein can be used, for example, as diagnostic or prognostic indicators in disease management, to predict how patients with cancer might respond to therapeutic intervention with a microtubule-stabilizing agent, and to predict how patients might respond to therapeutic intervention that affects microtubule-stabilization and/or cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease.

The biomarkers have both diagnostic and prognostic value in diseases areas in which microtubule-stabilization and/or cytotoxic activity against rapidly proliferating cells, such as, tumor cells or other hyperproliferative cellular disease is of importance.

In accordance with the invention, cells from a patient tissue sample, e.g., a tumor or cancer biopsy, can be assayed to determine the expression pattern of one or more biomarkers prior to treatment with one or more microtubule-stabilizing agents. In one aspect, the tumor or cancer is breast cancer. Success or failure of a treatment can be determined based on the biomarker expression pattern of the cells from the test tissue (test cells), e.g., tumor or cancer biopsy, as being relatively similar or different from the expression pattern of a control set of the one or more biomarkers. Thus, if the test cells show a biomarker expression profile which corresponds to that of the biomarkers in the control panel of cells which are sensitive to the microtubule-stabilizing agent, it is highly likely or predicted that the individual's cancer or tumor will respond favorably to treatment with the microtubule-stabilizing agent. By contrast, if the test cells show a biomarker expression pattern corresponding to that of the biomarkers of the control panel of cells which are resistant to the microtubule-stabilizing agent, it is highly likely or predicted that the individual's cancer or tumor will not respond to treatment with the microtubule-stabilizing agent.

The invention also provides a method of monitoring the treatment of a patient having a disease treatable by one or more microtubule-stabilizing agents. The isolated test cells from the patient's tissue sample, e.g., a tumor biopsy or tumor sample, can be assayed to determine the expression pattern of one or more biomarkers before and after exposure to a microtubule-stabilizing agent. The resulting biomarker expression profile of the test cells before and after treatment is compared with that of one or more biomarkers as described and shown herein to be highly expressed in the control panel of cells that are either resistant or sensitive to a microtubule-stabilizing agent. Thus, if a patient's response is sensitive to treatment by a microtubule-stabilizing agent, based on correlation of the expression profile of the one or biomarkers, the patient's treatment prognosis can be qualified as favorable and treatment can continue. Also, if, after treatment with a microtubule-stabilizing agent, the test cells don't show a change in the biomarker expression profile corresponding to the control panel of cells that are sensitive to the microtubule-stabilizing agent, it can serve as an indicator that the current treatment should be modified, changed, or even discontinued. This monitoring process can indicate success or failure of a patient's treatment with a microtubule-stabilizing agent and such monitoring processes can be repeated as necessary or desired.

The biomarkers of the invention can be used to predict an outcome prior to having any knowledge about a biological system. Essentially, a biomarker can be considered to be a statistical tool. Biomarkers are useful in predicting the phenotype that is used to classify the biological system.

Although the complete function of all of the biomarkers are not currently known, some of the biomarkers are likely to be directly or indirectly involved in microtubule-stabilization and/or cytotoxic activity against rapidly proliferating cells. In addition, some of the biomarkers may function in metabolic or other resistance pathways specific to the microtubule-stabilizing agents tested. Notwithstanding, knowledge about the function of the biomarkers is not a requisite for determining the accuracy of a biomarker according to the practice of the invention.

EXAMPLES

Example 1

Identification of Biomarkers

Methods

Cell Lines and Cytotoxicity Assay

23 breast cancer cell lines were assayed for their sensitivity to ixabepilone. Each cell line was exposed to ixabepilone for 72 hours, and growth inhibition was assessed by the CellTiter 96® Aqueous Non-Radioactive Cell proliferation Assay (Promega) for IC₅₀ measurements. Then, the concentration of the ixabepilone required for 50% growth inhibition was calculated as the IC₅₀. For each experimental condition, at least triplicate measurements were carried out for each cell line. The 23 cell lines were assayed for their IC₅₀ measurements twice, and these two separate IC₅₀ data sets were used for the following analysis.

Training Set Selection

For analysis, training cell lines were chosen in the following manner. The 23 cell lines were assigned into the classes “sensitive” or “resistant” using IC₅₀ values; log(IC₅₀) values were normalized based on the mean and the standard deviation (SD) across the 23 cell lines for each IC₅₀ data set. (J. E. Staunton et al., P.N.A.S. USA. 98, 10787-10792 (2001)) The cell lines with the normalized log(IC₅₀) below the mean of log(IC₅₀)s were classified as sensitive and above as resistant. Subsequently, classification of the cell lines were compared in two separate experiments and 18 cell lines that exhibited consistent IC₅₀ and classification were chosen as a training set for subsequent marker analysis. Five cell lines with inconsistent IC₅₀ and classification were considered to be intermediate and were eliminated from the analysis.

RNA Extraction and Gene Expression Data

The 23 breast cancer cell lines were grown to 50-70% confluent in RPMI media with FBS 10% at 37° C. and 5% CO₂. RNA was isolated using the RNeasy Mini kit (Qiagen) according to the manufacturer's instructions. 10 ug of total RNA was used to prepare biotinylated cRNA targets as described in Affymetrix protocol. Targets were hybridized to Affymetrix high-density HU133 A and B set that consist of 44,000 probe sets containing ˜32,000 genes. The chips were washed and stained using recommended procedures for GeneChip®. Expression values were calculated and scaled to 1500 by using Affymetrix GeneChip® software.

k-Nearest Neighbors (KNN) Analysis

GeneCluster software was used to find a set of marker genes. First, genes with greater than 100 average difference were filtered. Then, genes were excluded if they varied by less than 2-fold and 1000 average difference change across 18 training cell lines. Subsequently, intensity units across the cell lines for each gene were normalized to the mean and variance. The genes were ranked according to the correlation between their expression level, and the sensitivity and resistance profile of the training cell lines. A marker gene selection process was carried out by KNN algorithm which fed only the genes with higher correlation with the target class. The KNN algorithm sets the class of the data point to the majority class appearing in the k closest training set samples. This marker selection is done by sorting the genes according to the signal-to-noise statistics, [μ1(g)−μ2(g)]/[σ1(g)+σ2(g)], described as the correlation function where [μ1(g), μ2(g)] and [σ1(g), σ2(g)] denote the means and SDs of the expression levels of gene g for the samples in class 1 and class 2, respectively. The magnitude of correlation values indicates the strength of the correlation between gene expression and class distinction.

Leave-One-Out Cross-Validation Analysis and Random Classification

Predictors with 1-250 genes were used for cross-validation of the training set. For each predictor, cross-validation was performed with the entire training set; one cell line was removed, the classifier was trained on the remaining cell lines and then tested for its ability to classify the withheld cell line. This procedure was repeated for each cell line in the training set. For random classification analysis, GeneCluster was used to generate random class vectors and calculate error rates.

Clustering and Tree View

Gene Expression Data were Analyzed by the Software Cluster and Treeview.

Breast Tumors and Gene Expression Data

RNAs extracted from 175 breast tumors resected at the surgery were obtained from the Karolinska Institute (Stockholm, Sweden). These RNA samples were profiled using Aftymetrix Human U133 sets and their gene expression data were used for the analysis.

Results

Drug sensitivity data (IC₅₀) was used as a template for determining the phenotype of the cell lines as resistant or sensitive. Initially, two separate IC₅₀ data sets were generated for 23 breast cancer cell lines. As a first step for the analysis, the log(IC₅₀) value for each cell line was calculated and normalized using the mean of log(IC₅₀)s and SD across the cell lines (J. E. Staunton et al., P. N. A. S. USA. 98, 10787-10792 (2001)) in each IC₅₀ data panel. Then the cell lines were divided into two classes using the following method; the normalized log(IC₅₀)s above the mean are defined as resistant and below as sensitive (FIG. 1). After comparing the classification of the cell lines in the two data sets, 18 cell lines that displayed the consistent classification and IC₅₀ values in two separate experiments were selected and utilized for marker selection.

Subsequently, the gene expression data of the 18 cell lines were analyzed to identify genes that were highly correlated with observed phenotype defined as sensitive or resistant. From the GeneCluster analysis, classifiers that consisted of up to 250 correlated genes were selected and tested through leave-one out cross validation; by holding back one cell line, training on the remaining cell lines, predicting the class of the withheld cell line, and repeating this cycle for each cell line in the training set. Each gene was ranked according to the correlation in the training set between its expression level and the sensitivity-resistance class distinction. Each classifier identified from the analysis was evaluated with the error rate as shown in the FIG. 2. In order to assess whether or not the classifiers can be observed by chance, the error rates calculated from random classification were examined. Shown as an example in FIG. 3, error rates generated from random classifications were significantly higher than that from IC₅₀-based classification.

From the GeneCluster analysis, 200 genes (Tables 1 and 2) were identified whose expression levels were highly correlated with the sensitivity-resistance class distinction based on the KNN analysis and the T-test. Among these genes, the 50 marker candidates most closely correlated with sensitivity-resistance class distinction (first 25 sensitive markers of Table 1 and first 25 resistant markers of Table 2) were selected for further analysis.

As shown in FIG. 4, these 50 genes showed distinct expression patterns between sensitive and resistant cell lines. For example, the top 25 markers correlated with sensitivity (one of which was Proteasome subunit, beta type 8 (LMP7)) as shown in FIG. 4 were highly expressed (shown in red) in sensitive cell lines, but at a lower level (shown in blue) in the resistant cell lines. In contrast, the top 25 markers correlated with resistance showed the opposite expression pattern as these genes were highly expressed in the resistant cell lines, but at a lower level in the sensitive cell lines.

Among 200 genes identified, it is interesting to find estrogen receptor (ER) as one of the resistance markers. As shown in FIG. 4, ER expression levels were highly correlated with the resistance to ixabepilone. ER was highly expressed in the resistant cell lines, but its expression was very low in the sensitive cell lines. Although the resistance mechanism of ER is not obvious, the data suggests that ER might be involved in drug resistance associated with microtubule stabilizing agents. In fact, ER was also found as a resistance marker in our analysis of paclitaxel (data not shown). In addition to ER, a microtubule-associated protein, tau (Tau), was also identified as one of the resistance markers. This protein has been proposed to bind close to the Taxol® binding site on β-tubulin and stabilize microtubules in a similar way to Taxol® (S. Kar et al., EMBO J., 22, 70-77. (2003)). Therefore, Tau is likely to affect the Taxol® bound to microtubules and, presumably, ixabepilone in a similar way since ixabepilone binds at the same site as paclitaxel on β-tubulin. Interestingly, Tau is estrogen induced (M. West et al., P. N. A. S. USA, 98, 11462-11467 (2001)). Evidently, they seem to be co-regulated as shown in a plot of Tau expression level against ER (FIG. 5). Their correlation coefficient value is 0.7.

Among the sensitivity markers identified, LMP7 is particularly interesting because it appears to be connected to Tau's function. In general, the proteasome is a multicatalytic proteinase complex responsible for the degradation of most intracellular proteins, including proteins crucial to cell cycle regulation and programmed cell death, or apoptosis (P. Voorhees et al., Clin. Cancer Res., 9, 6316-6325 (2003)). Among many proteins processed by the proteasome, Tau is degraded by the 20S proteasome in vitro in an ubiquitin-independent manner (D. David et al., J. of Neurochemistry, 83, 176-185 (2002)). This supports LMP7 as one of the sensitivity markers because LMP7 presumably facilitates interaction between ixabepilone and microtubules by degrading Tau and making ixabepilone more accessible to the microtubules.

One type of drug resistance mechanism is based on the function of a group of transporter proteins, able to prevent the intracellular accumulation of anticancer drugs by an efflux mechanisms (F. Leonessa et al., Endocr. Relat. Cancer., 10, 43-73 (2003)). Several transporter genes were identified as potential resistance markers as they were highly expressed in the resistant cell lines. These genes include ATP-binding cassette, sub-family G (WHITE), member 1 and ATP-binding cassette, sub-family A (ABC 1), member 3. They are ATP dependent transporters which may be involved in lipid transport, and act as an efflux pump for chemotherapeutics drugs respectively (M. Gottesman et al., Nat. Rev. Cancer., Jan; 2(1):48-58 (2002)).

In addition, genes implied in microtubule functions are particularly interesting since ixabepilone is a microtubule-stabilizing agents. Microtubules are essential components of the cytoskeleton and involved in cell motility and transport, and maintenance of cell shape. The dynamic nature of a microtubule whose ability to polymerize and depolymerize, is essential for the segregation of chromosomes during mitosis (C. Bode et al., Biochemistry, 41, 3870-3874 (2002)). Therefore, marker genes such as midline 1 (C. Berti et al., BMC Cell Biol., Feb 29; 5(1):9 (2004)) and annexin A1 (L. C. Alldridge et al., Exp. Cell Res., Oct 15; 290(1):93-107 (2003)) that are implied in those functions can be involved in the mechanism of drug resistance. The biomarkers are categorized by their biological functions in Tables 1 and 2.

To study the use of these genes as response prediction markers in vivo, the expression pattern of these 50 genes in 175 breast cancer biopsies obtained from the Karolinska Institute was examined. The 50 genes were used to cluster the expression patterns of tumors. As shown in FIG. 6, these tumors were found to show patterns of expression that allowed sub-classification of these tumors into distinct groups as seen in the cell line study. Among many genes, Tau and ER were examined in tumors which were identified as resistance markers from cell lines. As shown in the FIG. 7, there is a trend in which Tau and ER seem to correlate as seen in the cell line study. In fact, both genes are highly expressed in a subset of tumors. These tumors are presumed to be non-responders for ixabepilone treatment.

Example 2

Further Evaluation of ER and Tau Biomarkers

Estrogen receptor (ER) and tau (Tau) were identified as biomarkers since their expression patterns were highly correlated with resistance to ixabepilone. In addition, it was found that the ER pathway was the most implicated biological network for resistance to ixabepilone based on the pathway analysis using preclinical candidate markers (FIGS. 9 and 10). Interestingly, Tau was recently identified as the gene most correlated with pathological complete response for T/FAC neoadjuvant treatment in breast cancer patients (M. Ayers et al, J. Clin. Oncol., 22(12):2284-93 (2004); R. Rouzier et al., P.N.A.S., Jun 7; 102(23):8315-20 (2005)). Following this report, our preclinical study on paclitaxel supported the clinical findings of Tau as a novel mediator of paclitaxel sensitivity (P. Wagner et al., Cell Cycle, Sep; 4(9):1149-52 (2005)). ER and Tau were evaluated for their predictability of response to ixabepilone in CA163-080 trial.

Methods

CA163-080 Study

CA613-080 is an exploratory genomic phase II study that was conducted in breast cancer patients who received ixabepilone as a neoadjuvant treatment. The primary objective of this study was to identify predictive markers of response to ixabepilone through gene expression profiling of pre-treatment breast cancer biopsies. Patients with invasive stage IIA-IIIB breast adenocarcinoma (tumor size≧3 cm diameter) received 40 mg/m² ixabepilone as a 3-hour infusion on Day 1 for up to four 21-day cycles, followed by surgery within 3-4 weeks of completion of chemotherapy. A total of 164 patients were enrolled in this study. Biopsies for gene expression analysis were obtained both pre- and post-treatment. Upon isolation of biopsies from the patients, samples were either snap frozen in liquid nitrogen or placed into RNAlater solution overnight, followed by removal from the RNAlater solution. All samples were kept at −70° C. until use.

Evaluation of Pathological Response

Pathological response was assessed using the Sataloff classification system (D. Sataloff et al., J. Am. Coll. Surg., 180(3):297-306 (1995)) and used as an end point for the pharmacogenomic analysis. The pathologic response was evaluated in the primary tumor site at the end of treatment and prior to surgery by assessing histologic changes compared with baseline as following: At the primary tumor site, cellular modifications were evaluated in both the infiltrating tumoral component and in the possible ductal component, to determine viable residual infiltrating component (% of total tumoral mass); residual ductal component (% of total tumoral mass); the mitotic index. Pathologic Complete Response (pCR) in the breast only was defined as T-A, Total or near total therapeutic effect in primary site. Based on this criteria, responders included patients with pCR while non-responders included patients who failed to demonstrate pCR. The response rate was defined as the number of responders divided by the number of treated patients.

Gene Expression Profiling

Total RNA was isolated using the RNeasy Mini kit (Qiagen) according to the manufacturer's instructions by Karolinska Institute (Stockholm, Sweden). A total of 134 patients with more than 1 μg of total RNA with good quality were included in the data set for the final genomic analysis. Samples were profiled in a randomized order by batches to minimize the experimental bias. Each batch consisted of about 15 subject samples and 2 experimental controls using RNA extracted from HeLa cells. The expression profiling was done following a complete randomization with an effort to balance the number of samples from two tissue collection procedures (RNAlater and liquid nitrogen), two mRNA preparation methods (standard and DNA supernatants), tissue collection sites, and time of RNA sample preparation within in each batch. The mRNA samples from each subject was processed with HG-U133A 2.0 GeneChip® arrays on the Affymetrix platform and quantitated with GeneChip® Operating Software (GCOS) V1.0 (Affymetrix). The HG-U133A 2.0 GeneChip® array consists of about 22,276 probe sets, each containing about 15 perfect match and corresponding mismatch 25mer oligonucleotide probes from specific gene sequences.

Gene Expression Data Processing

The gene expression data were transformed using base two logarithm. The Robust Multichip Average (RMA) method (C. Clopper et al., Biometrika, 26:404-13 (1934)) was used to normalize the raw expression data. The gene expression measures of each gene were centered at zero and rescaled to have a 1-unit standard deviation.

Stromal Effects in Tumor Biopsies

A hierarchical clustering analysis was performed in order to examine molecular profiles of tumor biopsies (FIG. 10). Among the two highest level clusters, the tumor samples from three Russian sites (site numbers 16, 24 and 25) were mostly clustered in the first cluster (Fisher's exact test, p-value <0.01). It appeared that genes implied in lymphocyte functions such as MHC, CD antigen, and IgG were enriched in this cluster. Therefore, this led to the concern that the tumors from the three Russian sites contained more stroma in the biopsies than other sites, thus contaminating the RNA samples with respect to gene expression for tumor tissue alone. In addition, the mean tumor size from the three Russian sites (16, 24 and 25) was larger than that for the other sites (mean 5.43 vs. mean 4.55, t-test p-value=0.022). Moreover, the pCR response rate was lower than that of the other sites (pCR 19.8% v.s. 17.2%, chi-squared p-value=0.73). This suggested that tumors from the three Russian sites were distinct from the others. Thus, a subgroup analysis excluding the three Russian sites was also performed.

Statistical Analysis

Logistic regression (F. Hsieh et al., Stat. Med., 17(14):1623-34 (1998)) was used to explore the relationships between the expression of genes and response to ixabepilone. The following model was fitted for each gene separately: $\log \left(\frac{\mathrm{Pr}\left(Y=1❘X\right)}{1-\mathrm{Pr}\left(Y=1❘X\right)}\right)=b_0+b_{1}X$ where Y=1 represents a responder and X is the gene expression measure. For each gene, the probability from a two-tailed Score test of whether the estimate of b₁=0 was used to rank the most interesting genes for further investigation. e^b1 is the odds ratio of being a non-responder for a one unit increase in gene expression relative to the average expression for the sample of subjects. Odds ratios and 95% confidence limits were reported.

Subjects were randomly assigned to the equal sized training set (n=67) or the test set (n=67), for responders and non-responders groups separately. The gene expression of ER and Tau were considered as potential predictors for response. Single logistic regression (SLR) was used to build the predictive model based on the training set, and the model performance was assessed on the test set. The prediction error, sensitivity, specificity, PPV (positive predictive value), and NPV (negative predictive value) as well as their 95% confidence intervals of the SLR model were estimated.

Results

Estrogen Receptor (ER) and Tau

For ER, patients whose predicted probability of being responders was greater than 0.3 were classified as responders. The ER prognostic sensitivity, specificity, PPV, NPV, and their 95% confidence intervals of the SLR model are 0.64 (0.35,0.85), 0.79 (0.66, 0.87), 0.37 (0.19,0.59), and 0.92 (0.80,0.97), respectively. For Tau, patients whose predicted probability of being responders was greater than 0.25 were classified as responders. The Tau prognostic sensitivity, specificity, PPV, NPV, and their 95% confidence intervals of the SLR model are 0.55 (0.28,0.79), 0.73 (0.60, 0.83), 0.29 (0.14, 0.50), and 0.89 (0.77, 0.95), respectively.

Estrogen Receptor (ER) and Tau Without Russian Sites 16, 24 and 25

For ER and Tau separately as SLR predictors, patients whose predicted probability of being responders was greater than 0.5 were classified as responders. The estrogen receptor 1 prognostic sensitivity, specificity, PPV, NPV and their 95% confidence intervals of the SLR model are 0.67 (0.35,0.88), 0.83 (0.69,0.92), 0.46 (0.23,0.71), and 0.92 (0.79,0.97), respectively. The Tau prognostic sensitivity, specificity, PPV, NPV, and their 95% confidence intervals of the SLR model are 0.44 (0.19, 0.73), 0.88 (0.75,0.95), 0.44 (0.19, 0.73), and 0.88 (0.75,0.95), respectively.

Conclusion/Discussion

A total of 164 patients were enrolled in CA163-080 study. The quality and quantity of RNA samples obtained from pre-treatment biopsies was fairly good as 134 patients (85%) had RNA samples with >1 μg good quality which did not require additional amplification for gene expression profiling. Stromal contamination in the tumor biopsies was raised as a potential problem for the analysis. It appeared that the three Russian sites 16, 24 and 25 might have more stromal tissues in the samples compared to others based on the hierarchical clustering analysis. In addition, the tumors from these three Russian sites were larger than others at baseline. Although further analysis is needed to confirm this hypothesis, it raised an important issue for analyzing clinical samples that are inherently heterogeneous.

Among preclinical candidate markers, ER and Tau were examined in CA163-080 for their predictability. In our preclinical work, ER and Tau had been identified as biomarkers since their expression patterns were highly correlated with resistance to ixabepilone. In CA163-080, ER predicted well for pCR whether or not the three Russian sites were included in the analysis. However, the highest PPV was obtained when these sites were excluded. In another study finding predictive markers of response to combination chemotherapy with paclitaxel, 5-Fluorouracil, adriamycin and cyclophosphamide, the ER regulated gene Tau was identified as the best predictor of response (M. Ayers et al., J. Clin. Oncol., 22(12):2284-93 (2004)). Work done by this group has also demonstrated in vitro that knocking down Tau levels using small interfering RNA (siRNA) increases the sensitivity of breast cancer cell lines to paclitaxel treatment (R. Rouzier et al., P.N.A.S., Jun 7; 102(23):8315-20 (2005)). The proposed mechanism is that high levels of Tau inhibit binding of paclitaxel to the taxane binding site on β-tubulin. Tau gene expression was therefore also examined for ability to predict response to ixabepilone. The PPV (0.44) with this gene was similar to that for ER (0.46) in the subset excluding the 3 Russian sites.

Thus, ER and Tau demonstrated their utility as a predictors for response to ixabepilone and can be used as biomarkers for identifying the pCR responders to ixabepilone.

Example 3

Production of Antibodies Against the Biomarkers

Antibodies against the biomarkers can be prepared by a variety of methods. For example, cells expressing a biomarker polypeptide can be administered to an animal to induce the production of sera containing polyclonal antibodies directed to the expressed polypeptides. In one aspect, the biomarker protein is prepared and isolated or otherwise purified to render it substantially free of natural contaminants, using techniques commonly practiced in the art. Such a preparation is then introduced into an animal in order to produce polyclonal antisera of greater specific activity for the expressed and isolated polypeptide.

In one aspect, the antibodies of the invention are monoclonal antibodies (or protein binding fragments thereof). Cells expressing the biomarker polypeptide can be cultured in any suitable tissue culture medium, however, it is preferable to culture cells in Earle's modified Eagle's medium supplemented to contain 10% fetal bovine serum (inactivated at about 56° C.), and supplemented to contain about 10 g/l nonessential amino acids, about 1.00 U/ml penicillin, and about 100 μg/ml streptomycin.

The splenocytes of immunized (and boosted) mice can be extracted and fused with a suitable myeloma cell line. Any suitable myeloma cell line can be employed in accordance with the invention, however, it is preferable to employ the parent myeloma cell line (SP2/0), available from the ATCC (Manassas, Va.). After fusion, the resulting hybridoma cells are selectively maintained in HAT medium, and then cloned by limiting dilution as described by Wands et al. (1981, Gastroenterology, 80:225-232). The hybridoma cells obtained through such a selection are then assayed to identify those cell clones that secrete antibodies capable of binding to the polypeptide immunogen, or a portion thereof.

Alternatively, additional antibodies capable of binding to the biomarker polypeptide can be produced in a two-step procedure using anti-idiotypic antibodies. Such a method makes use of the fact that antibodies are themselves antigens and, therefore, it is possible to obtain an antibody that binds to a second antibody. In accordance with this method, protein specific antibodies can be used to immunize an animal, preferably a mouse. The splenocytes of such an immunized animal are then used to produce hybridoma cells, and the hybridoma cells are screened to identify clones that produce an antibody whose ability to bind to the protein-specific antibody can be blocked by the polypeptide. Such antibodies comprise anti-idiotypic antibodies to the protein-specific antibody and can be used to immunize an animal to induce the formation of further protein-specific antibodies.

Example 4

Immunofluorescence Assays

The following immunofluorescence protocol may be used, for example, to verify biomarker protein expression on cells or, for example, to check for the presence of one or more antibodies that bind biomarkers expressed on the surface of cells. Briefly, Lab-Tek II chamber slides are coated overnight at 4° C. with 10 micrograms/milliliter (μg/ml) of bovine collagen Type II in DPBS containing calcium and magnesium (DPBS++). The slides are then washed twice with cold DPBS++ and seeded with 8000 CHO-CCR5 or CHO pC4 transfected cells in a total volume of 125 μl and incubated at 37° C. in the presence of 95% oxygen/5% carbon dioxide.

The culture medium is gently removed by aspiration and the adherent cells are washed twice with DPBS++ at ambient temperature. The slides are blocked with DPBS++ containing 0.2% BSA (blocker) at 0-4° C. for one hour. The blocking solution is gently removed by aspiration, and 125 μl of antibody containing solution (an antibody containing solution may be, for example, a hybridoma culture supernatant which is usually used undiluted, or serum/plasma which is usually diluted, e.g., a dilution of about 1/100 dilution). The slides are incubated for 1 hour at 0-4° C. Antibody solutions are then gently removed by aspiration and the cells are washed five times with 400 μl of ice cold blocking solution. Next, 125 μl of 1 μg/ml rhodamine labeled secondary antibody (e.g., anti-human IgG) in blocker solution is added to the cells. Again, cells are incubated for 1 hour at 0-4° C.

The secondary antibody solution is then gently removed by aspiration and the cells are washed three times with 400 μl of ice cold blocking solution, and five times with cold DPBS++. The cells are then fixed with 125 μl of 3.7% formaldehyde in DPBS++ for 15 minutes at ambient temperature. Thereafter, the cells are washed five times with 400 μl of DPBS++ at ambient temperature. Finally, the cells are mounted in 50% aqueous glycerol and viewed in a fluorescence microscope using rhodamine filters.

Although the invention has been described in some detail by way of illustration and example for purposes of clarity and understanding, it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims.

Claims

1. A method for predicting whether a mammal will respond therapeutically to a method of treating cancer comprising administering a microtubule-stabilizing agent, wherein the method comprises: (a) measuring in the mammal the level of at least one biomarker selected from the biomarkers of Table 1 and Table 2; (b) exposing a biological sample from said mammal to said agent; (c) following the exposing of step (b), measuring in said biological sample the level of the at least one biomarker, wherein an increase in the level of the at least one biomarker measured in step (c) compared to the level of the at least one biomarker measured in step (a), predicts that the mammal will respond therapeutically to said method of treating cancer when said at least one biomarker is from Table 1, and predicts that the mammal will not respond therapeutically to said method of treating cancer when said at least one biomarker is from Table 2.

2. The method of claim 1 wherein said agent is an epothilone or analog or derivative thereof.

3. The method of claim 1 wherein said agent is ixabepilone.

4. The method of claim 1 wherein said agent is a taxane.

5. A method for predicting whether a mammal will respond therapeutically to a method of treating cancer comprising administering a microtubule-stabilizing agent, wherein the method comprises: (a) exposing a biological sample from the mammal to said agent; (b) following the exposing of step (a), measuring in said biological sample the level of the at least one biomarker selected from the biomarkers of Table 1 and Table 2, wherein an increase in the level of the at least one biomarker measured in step (b), compared to the level of the at least one biomarker in a mammal that has not been exposed to said agent, predicts that the mammal will respond therapeutically to said method of treating cancer when said at least one biomarker is from Table 1, and predicts that the mammal will not respond therapeutically to said method of treating cancer when said at least one biomarker is from Table 2.

6. The method of claim 5 wherein said agent is an epothilone or analog or derivative thereof.

7. The method of claim 5 wherein said agent is ixabepilone.

8. The method of claim 5 wherein said agent is a taxane.