Kohli, Manish

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.

Purpose This trial assessed the efficacy and safety of docetaxel monotherapy or docetaxel in combination with ramucirumab (vascular endothelial growth factor receptor 2 antibody) or icrucumab (vascular endothelial growth factor receptor 1 antibody) after progression during or within 12 months of platinum-based regimens for patients with locally advanced or metastatic urothelial carcinoma. Patients and Methods Patients were randomly assigned (1:1:1) to receive docetaxel 75 mg/m2 intravenously (IV) on day 1 of a 3-week cycle (arm A), docetaxel 75 mg/m2 IV plus ramucirumab 10 mg/kg IV on day 1 of a 3-week cycle (arm B), or docetaxel 75 mg/m2 IV on day 1 plus icrucumab 12 mg/kg IV on days 1 and 8 of a 3-week cycle (arm C). Treatment continued until disease progression or unacceptable toxicity. The primary end point was investigator-assessed progression-free survival (PFS). Results A total of 140 patients were randomly assigned and treated in arms A (n = 45), B (n = 46), or C (n = 49). PFS was significantly longer in arm B compared with arm A (median, 5.4 months; 95% CI, 3.1 to 6.9 months v 2.8 months; 95% CI, 1.9 to 3.6 months; stratified hazard ratio, 0.389; 95% CI, 0.235 to 0.643; P = .0002). Arm C did not experience improved PFS compared with arm A (1.6 months; 95% CI, 1.4 to 2.9; stratified hazard ratio, 0.863; 95% CI, 0.550 to 1.357; P = .5053). The most common grade 3 or worse adverse events (arms A, B, and C) were neutropenia (36%, 33%, and 39%), fatigue (13%, 30%, and 20%), febrile neutropenia (13%, 17%, and 6.1%), and anemia (6.7%, 13%, and 14%, respectively). Conclusion The addition of ramucirumab to docetaxel met the prespecified efficacy end point for prolonging PFS in patients with locally advanced or metastatic urothelial carcinoma receiving second-line treatment and warrants further investigation in the phase III setting.

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 Androgen deprivation therapy (ADT) for hormone-sensitive prostate cancer (HSPC) and chemotherapy for castration-resistant prostate cancer (CRPC) are considered standard of care. However, there are no clinical tests or factors that can reliably predict treatment responses for the advanced prostate cancer patients. Examination of tumor component in circulation, also known as liquid biopsy, has shown promise for predicting treatment outcomes and survival. To capture the tumor-derived genomic alterations and decrease the surrogacy of using PSA measurements as is currently performed, we propose a Plasma Genomic Abnormality (PGA) score and Treatment Efficacy (TEff) index based on copy number variations as estimated by cell free DNA (cfDNA) in plasma. We first performed whole genome and targeted sequencing (NimbleGen comprehensive cancer panel) to examine plasma cfDNA for tumor-associated genetic and genomic aberrations in 10 HSPC patients receiving ADT and 10 CRPC patients receiving chemotherapy. For each patient, we tested plasma from two time points: pre-treatment and 4 months post-treatment. We then calculated the PGA score by summing the most significant genomic abnormalities with higher PGA score indicating greater tumor DNA content in cfDNA. TEff index was derived from comparison of PGA score difference between treatments with higher TEff index reflecting a better treatment response. The sequencing-based copy number analysis revealed locus-specific gains or losses including those previously reported in prostate cancers, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. We found that overall PGA score was significantly higher in CRPC patients than in HSPC patients (p&lt;0.0005), possibly reflecting increased tumor burden during the disease progression. Patients with low TEff index often demonstrated poor response to treatments, and patients with high initial PGA score or low TEff index tended to have poor overall survival. As examples of the PGA-based TEff associations with outcome we presented three CRPC patients including two with neuro-endocrine origin (small cell carcinoma). Comparison of mutational profiles between pre- and post-treatments showed that treatments caused more diverse gene mutations, in particular, in the genes involving androgen biosynthesis, AR activation, DNA repair and chemotherapy resistance, suggesting subclonal evolution of heterogeneous tumor genomes in response to these treatments. Our results strongly support the feasibility of using non-invasive liquid biopsy as a potential powerful tool to study biological mechanisms underlying therapy-specific resistance and monitor disease progression in the advanced prostate cancer. Further studies are needed to develop and validate the genomics-based PGA score and TEff index for clinical applications. Citation Format: Liang Wang, Shu Xia, Meijun Du, Rachel Ditmar, Tiezheng Yuan, Yongchen Guo, Yuan Wang, Adam Lee, Michael Tschannen, Elizabeth Worthey, Howard Jacobs, Chiang-Ching Huang, Manish Kohli. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5231. doi:10.1158/1538-7445.AM2015-5231