Patent Application
20110165582
The present invention relates to diagnosis methods and, more particularly, to diagnosis methods for detecting colon cancer.
With 19,200 new cases in Canada in 2004, colon cancer is one of the three most prevalent cancers in Canada for both men and women (Canadian Cancer Statistics, 2004). Invasive biopsy procedures require long hospitalizations and may have numerous possible side effects. Other alternative diagnostic procedures, such as digital rectal examination, fecal occult blood procedure, double-contrast barium enema, flexible sigmoidoscopy, and total colonoscopy are mostly invasive. The fecal occult blood test, while non-invasive, requires confirmation by way of additional invasive procedures. Unfortunately, such invasive procedures can possibly lead to side effects and/or long hospitalizations.
There is therefore a need for a non-invasive and accurate testing procedure for detecting colon cancer in humans. Ideally, such a test should be able to detect cancerous colon cells even from small sample sizes.
There is therefore a need for a more accurate diagnostic method that does not require an invasive biopsy to detect or diagnose colon cancer. Ideally, such a method should be usable even with very small sample sizes and may be combined with other, pathologist-based diagnosis methods.
The present invention provides methods for diagnosing or detecting cancerous colon tissue in humans. Colon tissue samples are acquired from patients and are tested for the expression of specific marker genes. A panel of 17 specific marker human genes are provided. The overexpression of some of these marker genes compared to their expression in normal colon tissue and the underexpression of the rest of these marker genes compared to normal colon tissue are indicative of cancerous colon tissue. By using these 17 marker genes as a diagnostic tool, small tissue samples, such as those obtained by core needle biopsies and from stool samples can be used.
In a first aspect, the present invention provides a method for diagnosing whether a human patient has colon cancer, the method comprising:
a) obtaining subject colon cells from said human patient
b) assaying the level of the RNAs encoded by SEQ ID NOs. 1-17 in said subject colon cells obtained in step a)
c) diagnosing said human patient with colon cancer when the RNAs encoded by SEQ ID NOs. 1-8 in said subject colon cells are overexpressed in comparison to the level of RNAs encoded by SEQ ID Nos. 1-8 in non-cancerous human colon cells and when the level of the RNAs encoded by SEQ ID Nos. 9-17 in said subject colon cells are underexpressed in comparison to the level of the RNAs encoded by SEQ ID Nos. 9-17 in non-cancerous human colon cells.
In a second aspect, the present invention provides a method for determining if human colon cells are cancerous, the method comprising:
a) assaying the level of the RNAs encoded by SEQ ID NOs. 1-17 in said human colon cells
b) determining that said human colon cells are cancerous when the RNAs encoded by SEQ ID NOs. 1-8 in said human colon cells are overexpressed in comparison to the level of RNAs encoded by SEQ ID Nos. 1-8 in non-cancerous human colon cells and when the level of the RNAs encoded by SEQ ID Nos. 9-17 in said human colon cells are underexpressed in comparison to the level of the RNAs encoded by SEQ ID Nos. 9-17 in non-cancerous human colon cells.
A better understanding of the invention will be obtained by considering the detailed description below, with reference to the following drawings in which:
The present invention relates to the use of a panel of 17 specific human marker genes to diagnose or detect cancerous colon tissue. The panel of 17 marker genes is listed in Table 1 below. Experiments have shown that this panel of human marker genes give high accuracy in colon cancer diagnosis due to the expression levels of the marker genes in cancer tissue relative to their expression levels in normal tissue in humans.
The panel of 17 marker genes is given in Table 1. The marker genes were determined from two different microarray data sets. A portion of the genes were found to give correct classification for the data set described by Notterman D A, et al. ((2001) Transcriptional Gene Expression Profiles of Colorectal Adenoma, Adenocarcinoma and Normal Tissue Examined by Oligonucleotide Arrays. Cancer Res. 61:3124-3130). The rest of the genes in the panel were selected from the data set published by Alon, U. et al. ((1999) Broad Patterns of Gene Expression Revealed by Clustering Analysis of Tumour and Normal Colon Tissue Probed by Oligonucleotide Arrays. Proc. Natl. Acad. Sci. 96:6745-6750).
The data set from Alon, et al. consisted of 40 tumour and 22 normal samples for a total of 66 samples. Samples were obtained from colon adenocarcinoma specimens snap-frozen in liquid nitrogen within 20 min of removal/collection from patients. From some of these patients paired normal colon tissue also was obtained. The microarrays were hybridized using Affymetrix Hum600 array using standard protocol. The 2,000 highest intensity genes were selected and published on the web at http://microarray.princeton.edu/oncology/. From this subset were selected seven diagnostic genes that give 100% of correct classification (the last 6 genes in Table 1). The dataset from Alon et al. is limited in size and therefore biomarker selection was performed on another data set also found in the Notterman et al. paper. In this data set, samples of colon adenocarcinoma and paired normal tissue from the same patient were obtained from the Cooperative Human Tissue Network. The tissue was snap-frozen in liquid nitrogen within 20-30 min of harvesting and stored thereafter at −80<0>C. mRNA was extracted from the bulk tissue samples and hybridized to the array using standard procedure (see Notterman et al., 2001). This data set was also cited by Rhodes et al. in 2004 (see Rhodes, D. R. et al. (2004) Large-scale Meta-Analysis of Cancer Microarray Data Identifies Common Transcriptional Profiles of Neoplastic Transformation and Progression. Proc. Natl. Acad. Sci. 101:9309). The adenocarcinoma samples were specifically re-reviewed by a pathologist at the institution where the samples were obtained using paraffin-embedded tissue that was adjacent or in close proximity to the frozen sample from which the RNA was extracted. The publicly available data set consists of 18 adenocarcinoma and 18 normal samples. The set consists of ˜6600 genes.
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The genes listed above and identified by their SEQ ID referencing the attached sequence listings were derived using a microarray gene expression experiment.
By following the procedure noted above, the expression of the above genes can be determined from sample tissue obtained from a patient. By determining the expression of the above noted genes in the sample tissue, the presence or absence of cancerous colon tissue may be determined.
It should be noted that the procedure for determining the expression of genes in tissue is well-known in the art. Furthermore, procedures for the extraction and collection of tissue, in this case colon tissue, are also well-known. As noted above, colon tissue samples may be obtained from patient stool samples or core needle biopsies or, alternatively, from blood samples. These tissue samples may then be tested for the expression of the above genes and then compared to the expression of the above genes in tissue samples known to be non-cancerous. If the first 8 genes listed above are overexpressed in the patient sample tissue relative to their expression levels in normal tissue, and if the next 9 genes listed above are underexpressed in the patient sample tissue relative to their expression levels in normal tissue, then this would indicate the presence of cancerous colon tissue in the patient sample tissue.
It should be noted that expression analysis can be carried out using any method for measuring gene expression. Such methods as microarrays, diagnostic panel mini-chip, PCR, real-time PCR, and other similar methods may be used. Similarly, methods for measuring protein expression (protein seen as products of translation of the said genes) may also be used.
As noted above, the cancerous colon cells can be obtained from a patient using minimally invasive core needle biopsy or from techniques such as from a patient's stool samples. Normal or non-cancerous colon cells against which the cancerous cells can be compared can also be obtained from the patient or from other patients. Experiments have shown that the diagnosis can be possible from just a small number of cancer cells.
Referring to
Proc Natl Acad Sci USA. 2001 Dec
Proc Natl Acad Sci USA. 2001 Dec
Proc Natl Acad Sci USA. 2001 Dec
Proc Natl Acad Sci USA. 2001 Dec
Proc Natl Acad Sci USA. 2001 Dec
For the experiments for which the results are in the boxplots of
As another example, experiment 7 for the gene PYCR1 used the sample set C with four subsample sets (see
The correspondence between the test results in the figures and the genes being tested are as follows:
It should be noted that the underexpression or the overexpression of the above noted genes in cancerous tissue relative to their expression in normal tissue is readily evident in the box plots. Specifically, the experiments which used the samples sets A, B, M, and N compare the expression levels of specific genes in both cancerous and non-cancerous tissue in a side-by-side manner. For the genes which were not tested for sample sets A, B, M, and N, their expression levels for sample set F (normal tissue) may be compared with their expression levels for sample sets H and I (cancerous tissue). For the genes for which sample set E was used, the presence of p53 mutation indicates cancerous tissue, sample subset 2 for this sample set being cancerous tissue.
While it is preferable that the complete panel of 17 marker genes be used in the diagnosis of possible colon cancer, using a subset of the 17 marker genes will also yield useful results. Using a panel of anywhere from 1 to 17 marker genes out of the 17 marker genes on suspect colon tissue will still provide a useful indication as to whether cancerous colon tissue may be present or whether further and more involved tests are required.
The diagnostic panel of 17 genes listed above was validated using human tissue samples. Total RNA was obtained from 17 sets of donor-matched colon adenocarcinoma and normal adjacent-to-tumor (NAT) tissue samples. Fourteen of these sample sets were obtained from colorectal cancer (CRC) patients in early stages of disease (Stage I or II). The RNA was extracted from snap-frozen tissue samples excised during surgical resections. Additionally, 12 RNA samples were obtained from persons with no history of colon cancer (normal) with ages and genders of the donors being comparable to that of the tumor group. Real-time quantitative PCR was used to measure the expression of each of the genes for each patient sample.
Using a panel approach, with the rationale that applying a number of markers as a panel can provide more information and/or more accuracy than any single marker as a diagnostic, prognostic or therapeutic aid, the gene expressions were tested as noted above. Analyses of the gene expression data as a panel led to the derivation of a ratio approach for sample classification. The ratio was obtained by dividing the geometric mean of the normalized expression data for each of the eight genes predicted to be over-expressed by the geometric mean of the normalized expression data for each of the nine genes predicted to be under-expressed. The ability of the ratio to distinguish tumor (N=17) from NAT (N=17) samples was assessed by Receiver Operator Characteristic (ROC) curve analyses. With an optimal cut-off ratio value of 1.54, the test was found to have 88.2% sensitivity and a specificity of 100%. The corresponding area under the curve (AUC) for this analysis was 0.912. As is known, the sensitivity of a test is a measure of the probability that a test will produce a true positive result. The specificity of a test is the probability that the test will produce a true negative result. The present invention therefore has an 88.2% chance that the test will produce a true positive result and it has a 100% probability that it will produce a true negative result.
A person understanding this invention may now conceive of alternative structures and embodiments or variations of the above all of which are intended to fall within the scope of the invention as defined in the claims that follow.
The present application is a continuation-in-part of U.S. patent application Ser. No. 11/508,244 filed Aug. 23, 2006 which is hereby incorporated by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 11508244 | Aug 2006 | US |
| Child | 12951331 | US |
