Kohli, Manish

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Amplification of androgen receptor (AR) is a common genomic event in metastatic castration-resistant prostate cancer (mCRPC). To evaluate the prognostic value of the amplifications of specific loci in the AR gene in cell-free DNA, we developed a multiplex digital PCR (dPCR) assay that targeted AR enhancer (AR-En), AR exon 1 (AR-E1), AR exon 8 (AR-E8) and OPHN1 (downstream of AR). We selected three relatively stable genes, C2orf16, FAM111B, and GRIA3, as reference controls for copy number normalization. One hundred and eight mCRPC patients were recruited to test the association of specific AR loci amplification with clinical outcome. Using a normalized ratio ≥ 1.92 as cutoff, amplification of AR-En, AR-E1, AR-E8 and OPHN1 was observed in 28, 25, 24 and 19 of 108 mCRPC patients, respectively. Among the 41 patients with AR region amplification, 9 (21.9%) showed amplification at all four selected regions and 15 (36.6%) showed amplification at AR-En, AR-E1, and AR-E8. Six (14.6%) patients showed independent AR-En amplification, while the remaining 3 (7.3%) demonstrated AR-E8 amplification only. Kaplan–Meier analysis showed overall survival’s association with the amplification of AR-En (p = 0.02, HR = 1.68 (1.07–2.65)), AR-E8 (p = 0.02, HR = 1.78 (1.08–2.92)) and AR-En-E8 (the combination of AR-En and AR-E8 (p = 0.009, HR = 1.77 (1.15–2.73)). Multivariate models that included AR-En-E8 amplification and clinical factors significantly improved prognostic performance (p = 0.0001). With further validation, the multiplex dPCR assay may assist in prognostication of mCRPC patients.

Abstract The present project was undertaken to determine whether the activation of the EGFR family (EGFR/ErbB2/ErbB3/ErbB4) and its downstream signaling effector ERK1/2 plays a role in enzalutamide resistance and whether treatment with ErbB or ERK inhibitors overcome this resistance. C4-2B (enzalutamide sensitive) and 22Rv1 (partially enzalutamide resistant) cell lines cultured for prolonged periods in enzalutamide, developed resistance to this drug (C4-2B/MDVR and 22Rv1/MDVR, respectively). Whole genome comparison of enza-resistant to parental lines demonstrated that the ErbB signaling network was significantly upregulated in the enza-resistant lines. Comparison of various enza-sensitive and resistant lines demonstrated a strong correlation between phosphorylation at EGFR(Y1068) and enza resistance. Inhibition of EGFR, but not that of ErbB2 or ErbB3 prevented cell viability. The EGFR inhibitors erlotinib and dacomitinib, but not the ErbB2 inhibitor lapatinib, suppressed viability in combination with enzalutamide. We hypothesized that enza-resistant tumors expressing higher levels of EGFR would be more responsive to erlotinib. To test this hypothesis, we compared the effects of erlotinib and enzalutamide, individually or in combination, in organelles from PDX tumors expressing high or low EGFR levels. Significantly, tumors expressing high EGFR, but not those expressing low EGFR, were responsive to the combination. Finally, we investigated the cause for greater efficacy with erlotinib compared to lapatinib in PCa. Comparison of the effects of different ligands revealed that while both lapatinib and erlotinib inhibited EGFR phosphorylation, only erlotinib but not lapatinib was able to inhibit EGF-induced ERK phosphorylation. This indicated an important role for ERK in the mediation of EGFR ligand induced enzalutamide resistance. Continuous culture of enza-sensitive C4 cells in enzalutamide resulted in the development of ERK phosphorylation in these PTEN-null cells that normally do not express phosphorylated ERK, and the newly ERK phosphorylated cells also were more susceptible to erlotinib as well. In support of a role for ERK in mediating the effects of EGFR activation in enza-resistant cells, inhibition of EGFR but not ErbB2 or ErbB3 inhibited ERK phosphorylation, and the ERK inhibitor ulitertinib inhibited viability of enza-resistant lines. We conclude that enzalutamide treatment causes an increase in EGFR ligands that result in the phosphorylation of EGFR at Y1068, which further resulted in phosphorylation of ERK. EGFR inhibitors that prevent ERK phosphorylation were effective in suppressing viability of enza-resistant CRPC cells, whereas ErbB2 inhibitors that did not affect ERK phosphorylation were unable to affect cell viability. These results demonstrate why certain ErbB inhibitors failed to affect enza-resistant CRPC tumors but provide encouragement for others. Citation Format: Thomas M. Steele, Maitreyee K. Jathal, Salma Siddiqui, Sisi Qin, Clifford G. Tepper, Ralph W. deVere White, Manish Kohli, Liewei Wang, Allen C. Gao, Paramita M. Ghosh. Overcoming EGFR and ERK-mediated resistance to enzalutamide in castration-resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4842.

Abstract Background and Aims: Progastrin is a tumor promoting peptide which is detectable in the blood of patients with different cancers. Progastrin gene is a direct target of the WNT/ß-catenin oncogenic pathway involved in tumorigenesis and possibly tumor progression/ treatment efficacy. Since WNT/ß-catenin oncogenic pathway is dysregulated in advanced prostate cancer we evaluated plasma progastrin in metastatic prostate cancer as a predictive and prognostic biomarker. Methods: Metastatic hormone sensitive prostate cancer (mHSPC) and metastatic castration resistant prostate cancer (mCRPC) states were enrolled in a cohort study of blood sample collection and follow-up for outcomes between 9/2009 and 11/2013. Patients were enrolled in mHSPC unique sub-cohorts before initiating androgen deprivation therapy (ADT); during ADT; at the time of failure of ADT and before starting chemotherapy. Plasma progastrin was measured using the ELISA cancerREAD®. Progastrin concentrations in the cancer patients (test set) was assessed against 213 samples from asymptomatic volunteers from the French blood establishment (control set) and prograstin levels were also compared for each of the above four mHSPC and mCRPC cohorts as well as for association with time to failure on AA for the mHSPC cohort and overall survival for both mHSPC and mCRPC subcohorts. We also determined progastrin levels in patients with two serial samples to evaluate if changes were predictive for overall survival. Results: Of the 523 mHSPC+mCRPC patients 96 were in mHSPC state enrolled before starting ADT; 101 mHSPC patients were enrolled while receiving ADT; 143 mHSPC patients were enrolled at the time of ADT failure and 143 were clinically progressive mCRPC. All cohorts were unique and 246/523 patients had two serial samples collected and analyzed across all subcohorts. The median time of follow up of the whole cohort was 8.34 years (IQR: 4.53-12.97) and 371/523 had died at the time of the analysis. Plasma progastrin levels was detected in 87.6% of all the patients (cut-off value 1 pM, range 0 to 311 pM, median value of 4.7 pM) compared to the control set (median value=0.61 pM; IQR 0.00-1.58). The Receiver Operating Characteristic analysis indicated an area under the curve of 0.84 (p<0.0001; 95% CI 0.81 to 0.87). Of these, 106 patients had a decrease and 140 patients an increase of progastrin levels. Patients with a serial increase of progastrin had a worst overall survival compare to the other group (p=0.019). Conclusion: Progastrin is a blood based biomarker elevated in advanced prostate cancer patients serial increases in progastrin levels during treatment are predictive of poor survival. Progastrin assay might be useful for monitoring therapeutic interventions like androgen deprivation therapy effects as well for advanced prostate cancer patients. Citation Format: Manish Kohli, Winston Tan, Lea Payen, Carole Langlois-Jacques, Pierre Liaud, Delphine Maucort-Boulch, Dominique Joubert, Alexandre Prieur. Plasma progastrin level as a predictive and prognostic biomarker in advanced prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2294.

5047 Background: We identified plasma cell free DNA (cfDNA) based copy number variations (CNV); single nucleotide variants (SNVs) & TMPRSS-ERG fusion in four sub states of metastatic prostate cancer (mPCa) and determined the impact on survival. Two mHSPC cohorts included treatment naïve, gp-1 and mHSPC patients (pts) responding to chronic androgen ablation (AA) (gp-2). Two mCRPC cohorts included mHSPC pts with PSA relapse on chronic AA (gp-3) and a clinically progressive mCRPC cohort post AA (gp-4). Methods: Enrollment of mPCa pts was performed from 2009-14 who were followed until 2018. Plasma from collected blood was used for extracting cfDNA. NGS was performed using Illumina HiSeq X for a preselected target panel of 129 genes including DNA damage repair genes. Statistical analyses of genomic aberrations were performed in R 3.5.1 and Cox proportional-hazard models were used for survival analyses. Results: A total of 255 pts were enrolled with 215 having adequate cfDNA that passed NGS QC. Median study follow up was 90.2 (Range:73;99) months. The table highlights pts in each gp with CNV, SNV, fusion events. ARamplification was higher in mCRPC gps3&4 (20/103 pts) compared to 3/106 pts in mHSPC gps1&2 (p < 0.001) and was prognostic for poor survival in mCRPC (p < 0.001;HR:3.34; 95%CI: 1.9-5.76). 54/103 pts in gp3&4 had SNVs in TP53 compared to 34/106 pts in mHSPC gps1&2 (P < 0.01). SNVs in APC, AR, CDK12 and BRIP1 were also increased in gps3&4 (p < 0.01). Gp1 mHSPC pts with SNVs in ATM/ CHEK2 had shorter response to AA (p < 0.001; HR:3.66; 95%: CI:1.81-7.39). Conclusions: Plasma cfDNA based somatic aberrations are detected with increased prevalence in mHSPC to mCRPC states. The ease of specimen collection and the need for molecular profiling in mPCa increases its potential for clinical applications in pt care. [Table: see text]

Abstract Introduction: Survival in mCRPC stage is heterogeneous and in this stage no molecular predictors of survival are known. Elevated circulating tumor cell (CTC) counts (&gt;5/7.5 ml blood CellSearch® assay) is the only FDA cleared prognostic biomarker in mCRPC stage that predicts poor prognosis but is not routinely performed in clinical practice. We evaluated a novel plasma cfDNA based molecular algorithmic score which is based on copy number variations (CNVs) in multiple candidate genes as a prognostic predictor of survival and also compared it to CTCs. Methods: We obtained biospecimens in a prospective cohort study (NCT#01953640) conducted in mCRPC patients who demonstrated progression on androgen deprivation therapy and were candidates to initiate pre-chemotherapy abiraterone acetate/prednisone (AA/P). Biospecimen collection was performed prior to initiating AA/P and included plasma and CTCs, both obtained at the same time. All samples underwent uniform processing. Cellsearch® assay was used for enumerating CTC counts. Plasma cfDNA was extracted using Qiagen whole blood kit and low pass sequencing was performed in the extracted plasma cfDNA and germline DNA. An algorithmic score based on CNVs in 13 candidate genes was developed after calculating an Absolute Log2 Ratio (ALR) for each pre-selected gene. The sum of ALRs for these 13 genes were combined to make a “Plasma Genome Abnormality” (PGA) score which was evaluated for association with the primary endpoint of overall survival (OS) using Hazard ratio (HR) with significance set at p ≤ 0.05. Association of concurrently collected CTC counts with OS was also determined. The PGA score based survival was adjusted for CTC counts in the final analysis. Results: Plasma and CTCs were available for analysis in 72/90 enrolled patients between 05/2013 and 09/2015 with the last enrolled patient having completed 23.5 months follow-up. 45/72 patients have died of cancer progression and the median OS of the cohort is 26.5 months (IQR: 19-46). The median plasma cfDNA amount obtained was 7.2 (Range: 1.6-70.4)ng/ml plasma and the median CTC count is 1/7.5ml blood (range: 0-308). The median PGA score was 1.108 (Range: 0.56-6.96) and the CNV based PGA score was observed to be associated with OS (HR: 1.63; 95% C.I: 1.144, 2.308); p-value= 0.0066). Association of elevated CTC counts (≥ 5/7.5 ml blood) with OS showed a statistically significant trend (HR: 1.92; CI: 0.99 - 3.7; p-value 0.051). After adjusting for CTC counts, an increased PGA score remained predictive of poor survival (HR: 1.52; 95% CI: (1.04, 2.21); p-value 0.028). Conclusions: In this cohort the PGA score, a molecular algorithm predictor based on plasma cfDNA copy number variations in candidate genes was a better prognostic marker of survival than CTC counts and potentially offers a biomarker tool which could be adopted for wider clinical application. Citation Format: Manish Kohli, Meijun Du, Liang Wang, Chiang-Ching Huang. Prognostic association of plasma cell free DNA (cfDNA) copy number variation based algorithmic score with survival in metastatic castration resistant prostate cancer (mCRPC) [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 4588.