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Alumkal, Joshi J

0000-0003-1278-0166

Mayo Clinic

University of Michigan

Citations 3

Multicenter Phase II Study of Olaparib and the ATR Inhibitor Ceralasertib in Metastatic Castration-Resistant Prostate Cancer (TRAP)
Tsung, Irene , Smith, David C. , Heath, Elisabeth I. , Cackowski, Frank C. , Devitt, Michael , Braun, Thomas , Yentz, Sarah , Nguyen, Charles B. , Shah, Neel , Vaishampayan, Ulka N. , Caram, Megan E.V. , Palmbos, Phillip L. , Alumkal, Joshi J. , Reichert, Zachery R. , Cackowski, Frank C , Devitt, Michael E , Braun, Thomas M , Dean, Emma , Vaishampayan, Ulka , Caram, Megan E V , Palmbos, Phillip , Alumkal, Joshi J , Reichert, Zachery R , Chinnaiyan, Arul , Smith, Simon A.

JCO Precision Oncology | September 16, 2025 | Volume: No volume available | Issue: 9 | Pages: No page available

10.1200/po-25-00457 Get It

PURPOSE Preclinical studies suggest the combination of the poly(adenosine diphosphate[ADP]-ribose) polymerase (PARP) inhibitor olaparib and the ataxia telangiectasia–mutated and Rad3-related (ATR) inhibitor ceralasertib has synergistic antitumor activity in homologous recombination proficient (HRP) and homologous recombination repair gene mutation (HRRm) patients. This study aims to determine the efficacy of olaparib plus ceralasertib in metastatic castration-resistant prostate cancer (mCRPC) with and without HRRm. PATIENTS AND METHODS Thirty-five HRP and 12 HRRm PARP inhibitor–naïve patients with mCRPC progressing on ≥1 line of therapy or previous androgen receptor pathway inhibitor were enrolled. Patients received olaparib (300 mg twice daily) and ceralasertib (160 mg once daily, days 1-7) in 28-day cycles. HRRm was defined as biallelic inactivation of BRCA2 or BRCA1 , monoallelic inactivation of ATM , or germline inactivation of any of these genes. The primary end point was disease response rate (dRR; confirmed prostate-specific antigen decline ≥50% and/or complete/partial radiographic response by RECIST v1.1) in HRP patients. Secondary end points included dRR in HRRm patients, progression-free survival (PFS), and safety/toxicity. Two-stage designs were used. RESULTS Four of 35 (11%; 95% CI, 3.2 to 26.7) HRP and four of 12 HRRm patients responded. Median PFS was 8.2 months (95% CI, 5.3 to not reached) for HRP patients. Thirty-six percent of patients had ≥grade 3 toxicity, most commonly from anemia. Limitations include small, single-arm, nonrandomized trial design. CONCLUSION Combining ceralasertib with olaparib had limited activity in patients with HRP mCRPC. HRRm response rate was not greater than previous single-agent PARP inhibitor clinical trials.
Understanding Drug Sensitivity and Tackling Resistance in Cancer
Tyner, Jeffrey W. , Haderk, Franziska, Kumaraswamy, Anbarasu , Baughn, Linda B., Ness, Brian Van, Liu, Song, Marathe, Himangi, Alumkal, Joshi J. , Bivona, Trever G., Chan, Keith Syson, Nelson, Peter S. , Druker, Brian J , Hutson, Alan D , Nelson, Peter S , Sawyers, Charles L. , Willey, Christopher D , Tyner, Jeffrey W. , Haderk, Franziska, Kumaraswamy, Anbarasu , Baughn, Linda B., Ness, Brian Van, Liu, Song, Marathe, Himangi, Alumkal, Joshi J , Bivona, Trever G., Chan, Keith Syson

Cancer Research | April 15, 2022 | Volume: 82 | Issue: 8 | Pages: 1448-1460

10.1158/0008-5472.can-21-3695 Get It

Abstract Decades of research into the molecular mechanisms of cancer and the development of novel therapeutics have yielded a number of remarkable successes. However, our ability to broadly assign effective, rationally targeted therapies in a personalized manner remains elusive for many patients, and drug resistance persists as a major problem. This is in part due to the well-documented heterogeneity of cancer, including the diversity of tumor cell lineages and cell states, the spectrum of somatic mutations, the complexity of microenvironments, and immune-suppressive features and immune repertoires, which collectively require numerous different therapeutic approaches. Here, we describe a framework to understand the types and biological causes of resistance, providing translational opportunities to tackle drug resistance by rational therapeutic strategies.
Multigene Profiling of Circulating Tumor Cells (CTCs) for Prognostic Assessment in Treatment-Naïve Metastatic Hormone-Sensitive Prostate Cancer (mHSPC)
Reichert, Zachery R. , Kasputis, Tadas, Abusamra, Sophia M. , Kasputis, Amy , Haruray, Saloni , Wang, Yugang , Williams, Shamara , Singhal, Udit , Alva, Ajjai , Cackowski, Frank C. , Caram, Megan E.V. , Palmbos, Phillip L. , Yentz, Sarah , Smith, David C. , Alumkal, Joshi J. , Morgan, Todd M. , Abusamra, Sophia M , Haruray, Saloni , Williams, Shamara , Singhal, Udit , Cackowski, Frank C , Alumkal, Joshi J , Morgan, Todd M , Reichert, Zachery R , Nallandhighal, Srinivas , Palmbos, Phillip

International Journal of Molecular Sciences | December 21, 2021 | Volume: 23 | Issue: 1 | Pages: 4

10.3390/ijms23010004 Get It

The substantial biological heterogeneity of metastatic prostate cancer has hindered the development of personalized therapeutic approaches. Therefore, it is difficult to predict the course of metastatic hormone-sensitive prostate cancer (mHSPC), with some men remaining on first-line androgen deprivation therapy (ADT) for several years while others progress more rapidly. Improving our ability to risk-stratify patients would allow for the optimization of systemic therapies and support the development of stratified prospective clinical trials focused on patients likely to have the greatest potential benefit. Here, we applied a liquid biopsy approach to identify clinically relevant, blood-based prognostic biomarkers in patients with mHSPC. Gene expression indicating the presence of CTCs was greater in CHAARTED high-volume (HV) patients (52% CTChigh) than in low-volume (LV) patients (23% CTChigh; * p = 0.03). HV disease (p = 0.005, q = 0.033) and CTC presence at baseline prior to treatment initiation (p = 0.008, q = 0.033) were found to be independently associated with the risk of nonresponse at 7 months. The pooled gene expression from CTCs of pre-ADT samples found AR, DSG2, KLK3, MDK, and PCA3 as genes predictive of nonresponse. These observations support the utility of liquid biomarker approaches to identify patients with poor initial response. This approach could facilitate more precise treatment intensification in the highest risk patients.