Kohli, Manish

Abstract Background: Abiraterone acetate/prednisone (AA/P) is used for treatment of metastatic castration-resistant prostate cancer (mCRPC), but response is variable and there are no known molecular predictive factors. Methods: We prospectively collected germline and plasma specimens from 72 mCRPC patients progressing on androgen-deprivation therapy (ADT) before initiating AA/P treatment (baseline) and serially after 12 weeks of treatment. After extracting cell-free DNA (cfDNA), we performed copy number analysis using low pass whole-genome sequencing approach. The primary endpoints were to determine association with response and survival. Cox regression and Kaplan-Meier survival analyses were used to associate the CNV with overall survival (OS) and progression-free survival (PFS) with statistical significance at p≤0.05. For determining primary resistance to AA/P, responders and nonresponders were defined as patients showing no progression or progression after 12 weeks treatment. T-test was used to evaluate the CNV with AA/P response at 12 weeks. Results: Whole-genome sequencing generated approximately 8.0 million mappable sequence reads per subject (total plasma samples sequenced, n=144). By comparing cfDNA to germline control DNA, our copy number analysis showed significant genomic abnormalities in 37 of 144 plasma samples. We observed the most frequent amplification of 1q, 8q, Xq and deletion of 2p, 6q,10q, 13q. Among these CNVs, amplification of MYC at 8q24.21, AR at Xq12, deletion of FOXP1 at 3p14, PTEN at 10q23.31, RB1 at 13q14.2, TP53 at 17P13.1, and gene fusions (TMPRSS2:ERG) were consistent with previous reports from tumor tissue-based studies. Survival analysis showed significant association of a fragment deletion at 13q14-32 with both OS and PFS (FDR= 0.0207/0.0141). The most significant fragment showing association with OS was the deletion of fragment at 2p22.1-p14 (FDR=0.00219). Genomic gains of MYC at 8q24.21 and NCOA2 at 8q13.3 were associated with PFS with FDR= 0.0085 and 0.0072, respectively. By comparing baseline CNVs between responder and nonresponders, we identified significant association of the deletion of PTEN at 10q23.31 (p= 0.0003), RB1 at 13q14.2 (p= 0.0008) and amplification of NCOA2 at 8q13.3 (p= 0.0030) with AA/P response/resistance at 12 weeks. Although statistical analysis showed the significant CNV change at AR locus between baseline and 12-week post-AA/P treatment (p=0.0002), the CNV change was not significantly different between responders and nonresponders (p=0.1697). Conclusions: cfDNA CNV may serve as a sensitive biomarker for prediction of treatment response to AA/P. Further detailed CNV and clinical association analyses are needed to fully validate the potential clinical utilities of cfDNA-based liquid biopsy for clinical management. Citation Format: Meijun Du, Manish Kohli, Chiang-Ching Huang, Liang Wang. Genomic alterations in plasma cell-free DNA predict treatment response to abiraterone acetate and prednisone and survival in metastatic castration-resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1077.

350 Background: In prostate cancer, overexpression of EZH2 is associated with disease recurrence, androgen independent growth, cell invasion, and metastases. We evaluated the prognostic significance of EZH2 gene expression in metastatic biopsies from men with CRPC. Methods: EZH2 (RNA) expression was evaluated in two serial metastatic site biopsies in patients (pts) prior to treatment with abiraterone acetate and prednisone (pre-AA/P) and after 12 weeks of treatment (post-AA/P). All pts were enrolled and prospectively followed for clinical outcomes. The primary endpoint was overall survival (OS), defined as the time from CRPC to death or last follow-up. Cox proportional hazard regression analysis was performed on EZH2 expression using normalized fragments per kilobase million (FPKM) > 1 for association with OS and time to treatment failure (TTF). Results: Of 92 enrolled pts, 59 pts had (pre-AA/P) gene expression using RNA-seq, 45 had paired pre and post-AA/P RNA-seq available for analysis. In pre-AA/P samples, the median EZH2 expression was 4.82 FPKMs (range 1.05-38.8). Elevated expression of EZH2 was associated with shorter OS [hazard ratio (HR) 2.58, p = 0.016]. Radiographic progression at 12 weeks was more frequent in high EZH2 tumors compared to low EZH2 tumors (48% vs 20%, p = 0.03, Fisher’s exact test) No statistically significant associations were identified between EZH2 expression and TTF. In paired post-AA/P biopsies, EZH2 expression increased in 13/45 tumors and decreased in 32/45 tumors. The median log2 fold change in EZH2 expression was -1.38 (range -6.7 to 3.1). In post-AA/P biopsies, no associations were identified between an increase in EZH2 expression and OS or TTF. Conclusions: EZH2 expression represents a potential novel prognostic biomarker in mCRPC and warrants further exploration. Clinical trial information: 01953640.

Abstract Castration resistant prostate cancer (CRPC) is a deadly disease with a poor prognosis. Treatment options for CRPC patients involve taxanes or newly developed drugs targeting the androgen pathway or androgen synthesis, including CYP17 inhibitors. However, response to therapy varies dramatically among patients, which might be due, in part, to tumor heterogeneity. Therefore, understanding of the genomic landscape of CRPC would be important to help achieve better outcomes by developing personalized therapies. One challenge contributing to our lack of therapies for CRPC is a paucity of clinically relevant animal models predictive of response to therapy in human patients. The Prostate Cancer Medically Optimized Genome Enhanced Therapy (PROMOTE) study is a Mayo Clinic prospective trial designed for patients with metastatic CRPC who are treated with abiraterone acetate, a CYP17 inhibitor, over a 12 week period. Fresh tissue from metastatic lesions, primarily bone metastases, was obtained by needle core biopsy before and 12 weeks after initiating abiraterone acetate treatment. The samples were submitted for DNA and RNA sequencing and were also used to generate patient-derived xenograft (PDX) models. PDX models were developed by injecting biopsy samples subcutaneously or under the renal capsule in male non-obese diabetic (NOD)/severe combined immunodeficient (SCID) or NOD/SCID/IL-2γ-receptor null (NSG) mice implanted with 25mg testosterone pellets at the time of tissue implantation and 2 months later. Baseline samples from 103 unique patients as well as second samples from 61 patients post abiraterone acetate treatment were injected into approximately 600 mice. Of the samples for which pathology is currently available, 31% of the biopsies injected into mice were confirmed to include tumor tissue, which may be compared with a figure of 37.5% of samples sent for sequencing. Thus far, we have established 8 PDX models, four from baseline and four from post treatment samples. Seven models were derived from metastatic bone lesions, and one model from a liver metastasis. The tumor tissue in each model was expanded into a second of generation of mice and harvested when the tumors grew. No tumor was expanded more than four times. Genomic and transcriptomic analysis of xenograft tissue from different “generations” of xenograft expansion is ongoing and will be compared with similar data for the original biopsy. The evaluation of treatment response after exposure of these PDX models to different therapies including CYP19 inhibitors, AR blockers and taxanes is ongoing. These PDX models provide a tool for future drug testing and for studying mechanisms of resistance to therapy in CRPC. Citation Format: Fang Xie, Manish Kohli, Yin Ping, Rafael E. Jimenez, Richard M. Weinshilboum, Liewei Wang. Developing patient derived xenograft (PDX) models for metastatic castration resistant prostate cancer (CRPC) during CYP17 inhibitor therapy. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr A05.

Objectives To evaluate the prognostic significance of germline variation in candidate genes in patients with castration‐resistant prostate cancer (CRPC). Methods Germline DNA was extracted from peripheral blood mononuclear cells of patients with CRPC enrolled in a clinically annotated registry. Fourteen candidate genes implicated in either initiation or progression of prostate cancer were tagged using single nucleotide polymorphisms (SNPs) from HapMap with a minor allele frequency of >5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP‐level results the per allele hazard ratios (HRs) and 95% confidence intervals (CIs) under the additive allele model were estimated using Cox regression, adjusted for age at CRPC and Gleason score (GS). Results A total of 240 patients with CRPC were genotyped (14 genes; 84 SNPs). The median (range) age of the cohort was 69 (43–93) years. The GS distribution was 55% with GS ≥8, 32% with GS = 7 and 13% with GS <7 or unknown. The median (interquartile range) time from castration resistance to death for the cohort was 2.67 (1.6–4.07) years (144 deaths). At the gene level, a single gene, JAK2 was associated with OS ( P < 0.01), and 11 of 18 JAK2 SNPs were individually associated with OS after adjustment for age and GS. A multivariate model consisting of age, GS, rs2149556 (HR 0.67; 95% CI 0.38–1.18) and rs4372063 (HR 2.17; 95% CI 1.25–3.76) was constructed to predict survival in patients with CRPC (concordance of 0.69, P < 3.2 × 10 −9 ). Conclusions Germline variation in the JAK2 gene was associated with survival in patients with CRPC and warrants further validation as a potential prognostic biomarker.

Treatment with abiraterone acetate and prednisone (AA/P) prolongs survival in metastatic castration-resistant prostate cancer (mCRPC) patients. We evaluated the genetic variation in CYP17A1 as predictive of response to AA/P. A prospective collection of germline DNA prior to AA/P initiation and follow-up of a mCRPC cohort was performed. Five common single-nucleotide polymorphisms (SNPs) in CYP17A1 identified using a haplotype-based tagging algorithm were genotyped. Clinical outcomes included biochemical response and time to biochemical progression on AA/P. Logistic regression was used to assess the association between tag SNPs and biochemical response. Proportional hazards regression was used to assess the association between tag SNPs and time to biochemical progression. Odds or hazard ratio per minor allele were estimated and p-values below 0.05 were considered statistically significant. Germline DNA was successfully genotyped for four tag SNPs in 87 patients. The median age was 73 years (54–90); the median prostate-specific antigen was 66 ng/dL (0.1–99.9). A single SNP, rs2486758, was associated with lower odds of experiencing a biochemical response (Odds ratio 0.22, 95% confidence interval 0.07–0.63, p = 0.005) and a shorter time to biochemical progression (Hazard ratio 2.23, 95% confidence interval 1.39–3.56, p < 0.001). This tag SNP located in the promoter region of CYP17A1 will need further validation as a predictive biomarker for AA/P therapy.

BACKGROUNDProstate cancer (PCa) is a leading cause of cancer death of men worldwide. In hormone‐sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration‐resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients.METHODSA mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate‐specific antigen; PSA) as affected by ADT. Following fine‐tuning by a dataset of ADT‐treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in‐treatment.RESULTSThe mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT‐resistance mechanism, successfully retrieved individual time‐courses of PSA (R2 = 0.783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R2 = 0.98).CONCLUSIONSThe algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short‐lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision‐making. Prostate 76:48–57, 2016. © 2015 Wiley Periodicals, Inc.

Abstract Background: We investigated the association of germline genetic variation in hormone biosynthesis and metabolism genes with prostate cancer specific mortality in a cohort of advanced prostate cancer patients. Methods: We genotyped 852 single nucleotide polymorphisms (SNPs) from 97 genes in a cohort of 267 advanced prostate cancer patients at the time of progression to castration recurrence (CRPC) during on-going androgen ablation. Tagging SNPs with minor allele frequency (MAF) of &gt;5% and r2 ≥0.8 were selected from HapMap, NIEHS and Seattle SNP databases. Medical records were queried for cause of death. The primary endpoint of time to prostate cancer specific mortality (PCSM), was pre-defined as time from development of CRPC to death from prostate cancer progression. Principle components analysis was used for gene-levels tests, and to account for multiple testing, we calculated the false discovery rate (FDR). For SNP level results, Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using cox regression. Results: The median age of the cohort was 72 years at CRPC. 43% had a Gleason score (GS)=8-10, 33% a GS=7, and 24% a GS&lt;7. After a median follow up of 1.8 years (IQ range: 0.8-3.3 years), 139 patients died, of which 107 were due to prostate cancer progression. In unadjusted gene level analyses, UGT1A7 (p=0.0059; FDR=0.19), UGT1A10 (p=0.0017; FDR=0.17) and UGT1A3 (p=0.0037; FDR=0.18) were associated with PCSM. After adjusting for age and GS, SNPs strongly associated with PCSM are listed in the Table. Conclusions: Variation in UGT genes involved in hormone metabolism yield prognostic information in CRPC. Further validation is needed to develop these as prognostic biomarkers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4174. doi:10.1158/1538-7445.AM2011-4174