Patent Application
20130171647
1. Technical Field
This document relates to methods and materials involved in predicting whether a prostate cancer patient is likely to respond to an androgen deprivation therapy for a prolonged time period. For example, this document provides methods and materials for predicting whether a prostate cancer patient is likely to respond to an androgen deprivation therapy for a prolonged time period (e.g., greater than three years) based at least in part on the presence of a genetic variation in a TMRT11 nucleic acid.
This document also relates to methods and materials involved in determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment (e.g., after failing androgen deprivation therapy). For example, this document provides methods and materials for determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment after failing androgen deprivation therapy based at least in part on the presence of a genetic variation in a UGT1A3 nucleic acid, the presence of a genetic variation in a UGT1A7 nucleic acid, and/or the presence of a genetic variation in a UGT1A10 nucleic acid.
2. Background Information
Prostate cancer occurs when a malignant tumor forms in the tissue of the prostate. The prostate is a gland in the male reproductive system located below the bladder and in front of the rectum. The main function of the prostate gland, which is about the size of a walnut, is to make fluid for semen. Although there are several cell types in the prostate, nearly all prostate cancers start in the gland cells. This type of cancer is known as adenocarcinoma.
Prostate cancer is the second leading cause of cancer-related death in American men. Most of the time, prostate cancer grows slowly. Autopsy studies show that many older men who died of other diseases also had prostate cancer that neither they nor their doctor were aware of. Sometimes, however, prostate cancer can grow and spread quickly. When localized to the prostate, treatments are delivered with curative intent, either with surgical prostatectomy or radiation. Clinical follow up post treatment is performed by monitoring serum prostate specific antigen (PSA), which can become immeasurable after successful localized therapy. However, in a large case series with adequate longitudinal follow-up, between 27% and 53% of men undergoing radical prostatectomy were detected to have a PSA elevation (also labeled-biochemical failure) within 10 years following primary prostate therapy (surgery) signaling the first evidence of progressive disease prior to the appearance of clinical metastasis. An initial treatment after biochemical failure and progression to advanced disease can be continuous androgen deprivation therapy (ADT), which is usually performed in the United States by using intra-muscular or subcutaneous depots of luteinizing hormone-releasing hormone (LHRH)-analogues, every three to four months.
This document provides methods and materials for predicting whether a prostate cancer patient is likely to respond to an androgen deprivation therapy for a prolonged period of time. For example, this document provides methods and materials for predicting whether a prostate cancer patient is likely to respond to an androgen deprivation therapy for a prolonged period of time based at least in part on the presence of a genetic variation in a TMRT11 nucleic acid (e.g., rs6900796, rs1268121, rs2326215, and/or rs6569442). This document also provides methods and materials for predicting how long a prostate cancer patient is likely to respond to an androgen deprivation therapy based on the presence or absence of a genetic variation.
Having the ability to identify prostate cancer patients that are likely to respond to an androgen deprivation therapy can allow doctors and patients to proceed with appropriate treatment options. For example, a patient identified as having one or two alleles having rs6900796 or rs1268121 can be instructed to proceed with an ADT sooner than he would have been had he lacked alleles having rs6900796 or rs1268121.
This document also provides methods and materials for determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment. For example, this document provides methods and materials for determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment based at least in part on the presence of a genetic variation in a UGT1A3 nucleic acid (e.g., rs17864701, rs17862875, or rs11891311), the presence of a genetic variation in a UGT1A7 nucleic acid (e.g., rs6753320 or rs6736508), and/or the presence of a genetic variation in a UGT1A10 nucleic acid (e.g., rs10929251 or rs10929252).
As described herein, the presence of a genetic variation in a UGT1A3 nucleic acid (e.g., rs17864701, rs17862875, or rs11891311) can indicate that the cancer patient is likely to experience longer survival from prostate cancer regardless of the type of treatment as shown in
Having the ability to identify prostate cancer patients that are likely to experience short survival time (e.g., less than three years) can allow doctors and patients to proceed with appropriate treatment options. For example, a patient identified as being likely to experience short survival time can be instructed to proceed with aggressive or additional treatment options including participation in clinical trials of new medications over and beyond the standard treatment options available, while a patient identified as being likely to experience long survival time can be instructed to proceed with standard treatment options alone.
In general, one aspect of this document features a method for identifying a prostate cancer patient likely to respond to androgen deprivation therapy. The method comprises, or consists essentially of, (a) detecting the presence of a TMRT11 allele comprising rs6900796 or rs1268121 in the patient, and (b) classifying the patient as being likely to respond to the androgen deprivation therapy without failure for a time greater than 3.5 years based at least in part on the presence of the TMRT11 allele. The prostate cancer patient can be a human. The method can comprise detecting the presence of a TMRT11 allele comprising rs6900796. The method can comprise detecting the presence of a TMRT11 allele comprising rs1268121.
In another aspect, this document features a method for identifying a prostate cancer patient likely to survive death related to prostate cancer for a time longer than 3.5 years. The method comprises, or consists essentially of, (a) detecting the presence of a UGT1A3 allele comprising rs17864701, rs17862875, or rs11891311 in the patient, and (b) classifying the patient as being likely to survive death related to prostate cancer for a time longer than 3.5 years based at least in part on the presence of the UGT1A3 allele. The prostate cancer patient can be a human. The method can comprise detecting the presence of a UGT1A3 allele comprising rs17864701. The method can comprise detecting the presence of a UGT1A3 allele comprising rs17862875. The method can comprise detecting the presence of a UGT1A3 allele comprising rs11891311.
In another aspect, this document features a method for identifying a prostate cancer patient likely to survive death related to prostate cancer for a time longer than 3.5 years. The method comprises, or consists essentially of, (a) detecting the presence of a UGT1A7 allele comprising rs6753320 or rs6736508 in the patient, and (b) classifying the patient as being likely to survive death related to prostate cancer a time longer than 3.5 years based at least in part on the presence of the UGT1A7 allele. The prostate cancer patient can be a human. The method can comprise detecting the presence of a UGT1A7 allele comprising rs6753320. The method can comprise detecting the presence of a UGT1A7 allele comprising rs6736508.
In another aspect, this document features a method for identifying a prostate cancer patient likely to survive death related to prostate cancer for a time longer than 3.5 years. The method comprises, or consists essentially of, (a) detecting the presence of two UGT1A10 alleles comprising a wild-type sequence at the rs10929251 or rs10929252 SNP position in the patient, and (b) classifying the patient as being likely to survive death related to prostate cancer a time longer than 3.5 years based at least in part on the presence of the two UGT1A10 alleles. The prostate cancer patient can be a human. The method can comprise detecting the presence of two UGT1A10 alleles comprising a wild-type sequence at the rs10929251 SNP position. The method can comprise detecting the presence of two UGT1A10 alleles comprising a wild-type sequence at the rs10929252 SNP position.
In another aspect, this document features a method for identifying a prostate cancer patient likely to survive death related to prostate cancer for a time shorter than 3.0 years. The method comprises, or consists essentially of, (a) detecting the presence of a UGT1A10 allele comprising rs10929251 or rs10929252 in the patient, and (b) classifying the patient as being likely to survive death related to prostate cancer for a time shorter than 3.0 years based at least in part on the presence of the UGT1A10 allele. The prostate cancer patient can be a human. The method can comprise detecting the presence of a UGT1A10 allele comprising rs10929251. The method can comprise detecting the presence of a UGT1A10 allele comprising rs10929252.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Although methods and materials similar or equivalent to those described herein can be used to practice the invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.
This document provides methods and materials for predicting whether or not a prostate cancer patient is likely to respond to an androgen deprivation therapy based at least in part on the presence of a genetic variation in a TMRT11 nucleic acid (e.g., rs6900796, rs1268121, rs2326215, or rs6569442). As described herein, a mammal (e.g., a human) that contains one or two TMRT11 alleles of rs6900796 or rs1268121 can be identified as being likely to experience prolonged response to an ADT (e.g., likely to experience greater than 2.5 years of survival prior to ADT failure). For example, a prostate cancer patient having one or two TMRT11 alleles of rs6900796 or rs1268121 can be classified as being likely to experience greater than 2.5 years (e.g., greater than 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.5, 4.0, 4.5, 5.0, or 5.5 years) of survival without ADT failure. Examples of ADT include, without limitation, chemical castrations (e.g., treatments with LHRH-analogues or gonadotrophin-releasing hormone (GnRH) antagonists) and physical castrations.
This document also provides methods and materials for determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment based at least in part on the presence of a genetic variation in a UGT1A3 nucleic acid (e.g., rs17864701, rs17862875, or rs11891311), the presence of a genetic variation in a UGT1A7 nucleic acid (e.g., rs6753320 or rs6736508), and/or the presence of a genetic variation in a UGT1A10 nucleic acid (e.g., rs10929251 or rs10929252). As described herein, a mammal (e.g., a human) that contains one or two UGT1A3 alleles of rs17864701, rs17862875, or rs11891311 and/or one or two UGT1A7 alleles of rs6753320 or rs6736508 can be identified as being likely to experience survival from prostate cancer longer than 2.5 years (e.g., longer than 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.5, 4.0, 4.5, 5.0, or 5.5 years) regardless of the type of treatment. A mammal (e.g., a human) that contains two wild-type UGT1A10 alleles at the position of the rs10929251 and/or rs10929252 SNPs can be identified as being likely to experience survival from prostate cancer longer than 2.5 years (e.g., longer than 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.5, 4.0, 4.5, 5.0, or 5.5 years) regardless of the type of treatment. In some cases, a mammal (e.g., a human) that contains one or two UGT1A10 alleles of rs10929251 and/or rs10929252 can be identified as being likely to experience survival from prostate cancer shorter than 2.5 years regardless of the type of currently available treatment.
Any appropriate method can be used to detect the presence of one or two alleles of a particular SNP provided herein. For example, mutations can be detected by sequencing cDNA, untranslated sequences, denaturing high performance liquid chromatography (DHPLC; Underhill et al., Genome Res., 7:996-1005 (1997)), allele-specific hybridization (Stoneking et al., Am. J. Hum. Genet., 48:370-382 (1991); and Prince et al., Genome Res., 11(1):152-162 (2001)), allele-specific restriction digests, mutation specific polymerase chain reactions, single-stranded conformational polymorphism detection (Schafer et al., Nat. Biotechnol., 15:33-39 (1998)), infrared matrix-assisted laser desorption/ionization mass spectrometry (WO 99/57318), and combinations of such methods.
In some cases, genomic DNA can be used to detect an allele having a SNP provided herein. Genomic DNA typically is extracted from a biological sample such as a peripheral blood sample, but can be extracted from other biological samples, including tissues (e.g., mucosal scrapings of the lining of the mouth or from prostate tissue). Any appropriate method can be used to extract genomic DNA from a blood or tissue sample, including, for example, phenol extraction. In some cases, genomic DNA can be extracted with kits such as the QIAamp® Tissue Kit (Qiagen, Chatsworth, Calif.), the Wizard® Genomic DNA purification kit (Promega, Madison, Wis.), the Puregene DNA Isolation System (Gentra Systems, Minneapolis, Minn.), or the A.S.A.P.3 Genomic DNA isolation kit (Boehringer Mannheim, Indianapolis, Ind.).
An amplification step can be performed before proceeding with the detection method. For example, TMRT11, UGT1A3, UGT1A7, and/or UGT1A10 nucleic acid can be amplified and then directly sequenced. Dye primer sequencing can be used to increase the accuracy of detecting heterozygous samples.
This document also provides methods and materials to assist medical or research professionals in determining whether or not a prostate cancer patient is likely to respond to an androgen deprivation therapy and methods and materials to assist medical or research professionals in determining whether a prostate cancer patient is likely to survive prostate cancer related death for a short or long period of time regardless of prostate cancer treatment. Medical professionals can be, for example, doctors, nurses, medical laboratory technologists, and pharmacists. Research professionals can be, for example, principle investigators, research technicians, postdoctoral trainees, and graduate students. A professional can be assisted by (1) determining the presence of one or more alleles having a SNP described herein, and (2) communicating information about that SNP to that professional.
Any method can be used to communicate information to another person (e.g., a professional). For example, information can be given directly or indirectly to a professional. In addition, any type of communication can be used to communicate the information. For example, mail, e-mail, telephone, and face-to-face interactions can be used. The information also can be communicated to a professional by making that information electronically available to the professional. For example, the information can be communicated to a professional by placing the information on a computer database such that the professional can access the information. In addition, the information can be communicated to a hospital, clinic, or research facility serving as an agent for the professional.
In some cases, a patient identified as being likely to respond to an androgen deprivation therapy based at least in part on the presence of a genetic variation in a TMRT11 nucleic acid (e.g., rs6900796, rs1268121, rs2326215, or rs6569442) can be administered or instructed to receive an alternative or adjunct therapy to ADT. For example, a patient having one or two alleles having rs6900796 or rs1268121 can be instructed to proceed with an ADT in conjunction with an additional treatment such as abiraterone acetate, MDV3100, or TAK-700 sooner than he would have been had he lacked alleles having rs6900796 or rs1268121. In some cases, a patient identified as being likely to respond to an androgen deprivation therapy based at least in part on the presence of a genetic variation in a TMRT11 nucleic acid (e.g., rs6900796, rs1268121, rs2326215, or rs6569442) can be administered or instructed to receive abiraterone acetate, MDV3100, TAK-700, or a combination thereof.
The invention will be further described in the following examples, which do not limit the scope of the invention described in the claims.
A candidate gene/SNP based association line of investigation into the variation in genes regulating hormonal pathways in a homogenous population of prostate cancer subjects receiving ADT was performed with the overall goal of identifying specific genetic markers associated with ADT response. The study included tagSNPs in candidate genes known to be involved in sex steroid synthesis and metabolism and included definitive survival endpoints for associating response or failure of ADT. The candidate genes can be divided into four biosynthetic pathways (
i) C4 Δ pathway (nucleic acids that encode enzymes that convert progesterone to androstenedione);
ii) C5 Δ pathway (nucleic acids that encode enzymes that convert cholesterol to pregnenolone to dihydro-epiandosterone);
iii) C21 CYP pathway (CYP17 17α-hydroxylates all four classes of 21-carbon steroids, and the 17,20-lyase activity for each pathway can vary); and
iv) “Backdoor pathway” for androgen synthesis (nucleic acids that encode enzymes involved in the conversion of 17-hydroxyprogesterone to 5alpha-reduced androgen precursors via a 5alpha-reductase type 1 enzyme).
The metabolism pathway nucleic acids for androgens included SRD5A1, SRD5A2, CYP19, UGT1A, UGT2B, AKR1D1, SULT1E1, CYP2B1, COMT, CYP7B1, HSD17B, SULT2A1, ARSD, ARSE, and TRMT11. The end products of several of these pathways were 2-methoxyestrone, estriol, sufate and glucouronides, estrone-3-sulphate.
For determining genomic classifiers as predictive factors for ADT responses, three different patient data sets were used:
i) A cohort of prostate cancer patients available at Mayo Clinic Clinical Core treated with ADT on whom long term clinical outcomes of treatment and follow up is available (n=258).
ii) Specimens from patients from the University of Rochester, N.Y.
iii) DNA specimens from advanced prostate cancer patients receiving or who have received androgen ablation collected at the Mayo clinic (n=42).
A total of 338 patients were identified in the above three databases that met the criteria of being treated with hormone therapy (also referred to as androgen ablation or androgen deprivation therapy or ADT). Demographic and disease characteristics of the 338 patient cohort were summarized (Table 1).
Genotypes among nearby common genetic polymorphisms tend to be correlated. Selecting and prioritizing representative ‘tag’ SNPs improved the cost-effectiveness of the genetic study. The genetic structure of 84 candidate genes, including a subset of 57 candidate genes, involved in testosterone metabolism were evaluated by interrogating publicly available genotype data for European populations from the International HapMap Phase II (http://www.hapmap.org), Seattle SNPs (http://pga.mbt.washington.edu/), and NIEHS SNPs (http://egp.gs.washington.edu/) projects. SNPs spanning 5 kilobases upstream and downstream of each gene were used for genetic characterization in the 60 unrelated HapMap CEU samples (chromosomal position of genes and SNPs were extracted from RefSeq release 29, NCBI build 36, and dbSNP build 129). SNPs from Hapmap were found in 78 of the candidate genes. Six of the candidate genes were each resequenced in NIEHS SNPs and Seattle SNPs. Two of the genes had no SNPs. To thoroughly capture the common genetic variation, a pairwise tagging approach was utilized on each gene and each genotype source separately such that all SNPs with reported and pre-determined minor allele frequency (MAF)>=5% were either directly measured or were highly correlated (R2>=0.9) with a measured SNP.
For genes with more than one genotype source, an optimal source of tagSNPs was selected based on the one with more LD bins, giving priority to HapMap in case of equal number of bins. Hapmap was selected as an optimal source for 74 of the genes, Seattle for three of the genes, and NIEHS for one of the genes. For the subset of 57 candidate genes, the HapMap was chosen as the best source for 57 genes and NIEHS for 1 gene. To pick an optimal tagSNP for each LD bin, the SNPPicker software developed in the Mayo Clinic Bioinformatics group was used. LdSelect often gives multiple choices of tagSNPs for a given bin but not all tagSNPs have the same design probability or possible functional relevance. SNPPicker picks an optimal tagSNP for each bin, optimizing constraints such as assay score, functional relevance, and the Illumina GoldenGate platform constraint of not allowing two SNPs that are 60 bp or less from each other. It also allows multiple tagSNPs for bins. To reduce the probability of failure in larger bins, three tagSNPs were selected for bins with >=30 SNPs, while two were selected for bins with size of 10 or greater. All tagSNPs met the minimum Illumina assay score of 0.4. To increase the likelihood of identifying susceptibility alleles, 149 SNPs of interest from various sources (likely to be functionally deleterious, previous experiment evidence of association, etc.) were chosen in preference to other tagSNPs or added to the final list for a total of 1056 SNPs.
A total of 755 tagSNPs in the 58 candidate genes were selected for genotyping. In addition, 69 targeted candidate SNPs were genotyped from 20 candidate genes also in sex steroid biosynthesis and metabolism genes of which 6 were already included in the tagged set, but none of the SNPs overlapped. These candidate SNPs were selected base on previous published data from single patient cohorts suggesting either a potential functionality for the SNP or a potential significant association with response to ADT.
There are several popular programs (e.g., ldselect, tagzilla, and tagger) that help a user save on genotyping costs by selecting sets of highly correlated SNPs (called bins) and only genotyping one (or a few) representative tag SNP. A tagSNP is selected if it correlates well with all the other SNPs in the bin above some correlation coefficient (r2) threshold. The output of these programs often gives multiple choices of tag SNPs for a given bin. However, not all tag SNPs have the same design probability or even the same functional importance.
SNPPicker is a post-processor to these bin-based algorithms that can refine the list of tag SNPs subject to multiple realistic constraints, including the 60 base pair constraints for Illumina. Using a three step algorithm, SNPPicker rejects solutions incompatible with the constraint, rapidly finds a good solution, and then spends as much time as the user allows looking for an optimal solution. SNPPicker is able to split SNPs that are too close among multiple SNP panels (user option) and can deal with multi-population SNP selection as well as cases where the bins are from multiple overlapping sources (e.g. Hapmap and Seatle SNPs) for the same population. SNPPicker depends on input files providing some information about the SNPs. The default format is designed to work with the Illumina provided annotation files that a user can get from Illumina.
Using supplied annotation and historical data on SNP assay performance, SNPPicker starts by computing the probability of successfully designing each SNP. Using that probability, it computes the utility of the panel, namely the sum of the probabilities of successfully genotyping each bin times the number of SNPs in that bin divided by the number of tag SNPs in the panel.
To allow flexibility in optimizing functionally relevant SNPs, the probability for all the SNPs are assessed in fixed intervals, so that within a given probability interval, priority is given to SNPs with stronger functional consequence. The functional ranking is configurable, but the default rank mapping uses the annotation in Illumina files and functional ranking of ldselect. As defined, the utility function considers bins that share SNPs, so that SNPs that tag more than one bin (e.g., in multi-population tagging or with overlapping bins from neighboring regions) improve the utility of the panel (subject to the probability). The utility function favors large bins over singletons and also allows multiple tag-SNPs to be selected for one bin in order to improve the probability that these larger bins will not fail.
The first step in SNPPicker is to filter out SNPs below a certain score cutoff. The remaining SNPs are chosen according to the following scoring: Proximity constraints must be met (though tag SNPs and obligates can be split across multiple panels), then the utility function is optimized. Given two solutions with the same utility (or choice between two SNPs with same probability), the next consideration is the functional importance of a SNP, the last consideration is the score of a SNP (since two SNPs with the same probability can have different scores).
Germline DNA purified from the above specimens were used for Illumina GoldenGate assay (GGGT) with the 936 SNPs selected, including the 824 SNPs selected subset (755 tagSNPs belonging to 58 selected candidate genes plus 69 selected tagSNPs). Illumina GGGT assays used well established protocols for performing the genotyping, which typically encompass primer extension, ligation, and universal PCR in very highly-plexed reactions (384-1536 plex). For GGGT, SNPs and genes were submitted for assay design. Location within current build of the genome was required for all submissions, and a RefSeq number identified genes. Primers were designed for each multiplex panel, and each SNP was rated for its probability of yielding optimal results for the GGGT biochemistry, on a scale of 0-1.
Analyses of the Genotypes Generated on 338 Advanced Prostate Cancer Patients Treated with Androgen Ablation
Genotypes were generated on samples from 338 prostate cancer and three CEPH subjects for 936 SNPs, including the 824 SNPs selected subset. For quality assurance, eight of the 338 prostate cancer samples were duplicated twice within the same plates, while the CEPH samples were genotyped multiple times within and across plates. All pairwise replicate sample comparisons exhibited a 100% genotype call concordance rate. Duplicated samples with a lower call rate together with the CEPH samples were eliminated from the subsequent statistical analysis. Of the remaining 338 samples, eight generated no genotypes and were therefore excluded. Evaluation of paired identity by state revealed five related pairs of samples. These paired samples were independently confirmed to have came from different blood draws of the same subjects. Only the sample with the higher call rate was retained for each of the five subjects.
25 SNPs (15 SNPs from the 824 SNPs of the selected subset) were omitted due to failed assays (0% call rate). Since all the X-linked genes of this study lie outside of the pseudo-autosomal regions, males can only have homozygous genotype for the relevant SNPs. However, five X-linked loci were identified with at least one heterozygote male: 3 SNPs has one, 1 SNP has two, and the other has 127 heterozygote males (of the 824 SNPs of the selected subset, 1 X-linked SNP was identified with excessive heterozygosity). The corresponding genotypes of the first four SNPs were set to missing, and the fifth SNP was discarded. Sixty SNPs (48 SNPs from the 824 SNPs of the selected subset) were eliminated because of low MAF (<5% in this study population where only females were included in the calculation of the X-link SNPs). 16 SNPs were dropped based on a stringent call rate of 98%. Five SNPs (two SNPs from the 824 SNPs of the selected subset) deviated from the Hardy-Weinberg equilibrium (Chi-square p-value<0.0001; only females contributed to the calculation of the X-linked SNPs). Upon visual inspection of the genotype clusters, two out of the five SNPs were omitted due to poor clustering quality. After discarding two prostate cancer samples with call rates less than 98%, a final dataset of 323 samples and 747 SNPs or 746 SNPs was used for further analysis.
Clinical data was incomplete for another 19 patients. A final total of 304 patients were identified for the statistical analyses with response to ADT (hormonal therapy).
Of the 84 hormone metabolizing genes analyzed for association with duration of response to ADT, variation in TRMT11 (tRNA methyltransferase 11 homologue; synonyms: TRM11, MDS024, C6orf75, and TRMT11-1) was strongly associated with ADT response (p<0.0008; adjusted p-value for FDR-0.068). TRMT11 nucleic acid encodes a polypeptide that is implicated in breaking down testosterone (indirectly) and estrogen (directly) into sulphone and glucouronide by-products. When evaluating the TRMT11 nucleic acid in the patient population without adjustments for age and Gleason score as discussed, the p-value for the TRMT11 gene was 0.001264 with and FDR=0.014045.
At the gene-level analysis, statistical significance (P<0.05) was observed for three genes (TRMT11, HSD17B12, and PRMT3) with time to ADT failure after adjusting for Gleason Score (Table 2), with a suggestive trend (p-value ≦0.07, and a corresponding FDR of 0.80) for an additional gene, WBSCR22—listed in Table 3). Of these, TRMT11 (tRNA methyltransferase 11 homologue) was the most significant gene (p=0.1×10−3; FDR=0.008).
Four SNPs (rs6900796, which flanks 3′ UTR; rs2326215 and rs6569442, which are in the coding region; and rs1268121, which is in an intron) in TMRT11 nucleic acid were further analyzed for time to progression on ADT. rs1268121 (A>G) exhibited an MAF of 15%; rs2326215 (A>G) exhibited an MAF of 37%; rs6569442 (A>C) exhibited an MAF of 33%; and rs6900796 (A>G) exhibited an MAF of 49%.
Of the four TRMT11 SNPs (rs1268121, rs2326215, rs6569442, and rs6900796) further analyzed for time to progression on ADT, two (rs1268121 and rs6900796) were found to be highly significant for duration of response to ADT. An overall protective effect was observed in the presence of 1 or 2 alleles for these SNPs (Table 4 and
Among the non-tagged candidate SNPs, four showed a significant association (p<0.05) with ADT response (Table 5). Two of the SNPs (rs10478424, rs11749784) were from HSD17B4 while the other SNPs were from CYP19A1 (rs2124872) and SREBF2 (rs11702960). However, none of these associations were confirmed with a FDR<0.10.
These results demonstrate that knowledge about the presence of variation in these hormone metabolizing genes can be used to predict the efficacy of ADT in individuals.
SNPs within UGT1A10, UGT1A7, and UGT1A3 nucleic acid were identified as being genetic markers capable of differentiating between prostate cancer patients likely to survive prostate cancer related death for a short period from those likely to survive prostate cancer related death for a long period, regardless of prostate cancer treatment (Table 2 and
These results demonstrate that information about these variations of these SNPs belonging to these genes in individual patients will allow to prognosticate patient survival in the advanced stage of prostate cancer.
It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.
This application claims priority to U.S. Provisional Application Ser. No. 61/380,786, filed on Sep. 8, 2010. The disclosure of the prior application is considered part of (and are incorporated by reference in) the disclosure of this application.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US2011/050836 | 9/8/2011 | WO | 00 | 3/8/2013 |
| Number | Date | Country | |
|---|---|---|---|
| 61380786 | Sep 2010 | US |
