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Martin, Robert C. G.

Mayo Clinic

University of Louisville

Citations 2

Development and testing of an ex vivo, live tumor fragment platform for the prediction of immune checkpoint inhibitor response and relationship to approved biomarkers.
Braun, David A., Gierman, Hinco J., Sood, Chetan , Hrycyniak, Laura, Hernan, Hilary, Dana, Nicholas, Caenepeel, Sean, Vedder, Lindsey, Mukhopadhyay, Debabrata, Martin, Robert C. G., Broome, Barbara , Kokabi, Nima, Chen, Ruqin, Lou, Yanyan, Majeed, Umair, Ramos, Hilario J., Taube, Janis M., Petal, Premal, Advani, Pooja , Braun, David A. , Gierman, Hinco J. , Hrycyniak, Laura , Caenepeel, Sean , Sahni, Shalini, Mukhopadhyay, Debabrata , Martin, Robert C.G. , Kokabi, Nima , Majeed, Umair , Ramos, Hilario J. , Taube, Janis M

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 2646-2646

10.1200/jco.2026.44.16_suppl.2646 Get It

2646 Background: Immune checkpoint inhibitors (ICIs) have transformed the management of many advanced cancers but identifying patients who are likely or unlikely to benefit from ICI treatment remains a critical challenge. Biomarkers, such as PD-L1, mismatch repair deficiency, and tumor mutational burden, capture only static, unidimensional features of the complex tumor microenvironment, and therefore inadequately predict response to immunotherapy in patients. In contrast, live tumor fragments (LTFs) preserve the full complexity of the tumor microenvironment and enable functional ex vivo assessments of ICI activity. Previous efforts have had limited clinical applicability because they required larger resection specimens often collected at a single academic center. Here, the predictive capability of an ex vivo platform using core needle and forceps biopsies from multiple clinical sites was assessed and compared to approved biomarkers. Methods: Patients with eligible solid tumors (where ICI has an indication, including renal, non-small cell lung, bladder, colorectal, and triple-negative breast cancer, and others) were enrolled in ongoing, prospective observational trials (NCT05478538, NCT05520099, NCT06349642). Biopsies were cut into LTFs, encapsulated in hydrogel, and treated sequentially with IgG antibody followed by ICI (αPD-[L]1 with or without αCTLA-4). Cytokine production was assessed by a multiplexed bead-based immunoassay at multiple time points during ex vivo treatment. Using receiver operating characteristic and precision recall analyses, we identified 9 predictive cytokines (including IFN-γ, granzyme B, and CXCL9/10), which were used to develop the Elephas score (ELP-score) to assess cytokine response to ex vivo ICI treatment. Results: Of 167 eligible patient specimens, 85% (n = 142) passed quality control metrics and 130 were used for model development. Hierarchical clustering of cytokine production revealed that 27% (n = 35) of patient specimens exhibited a cytokine response to ICI. In a validation set of 20 tumors, collected from patients who were subsequently treated with ICI, ELP-score positivity correctly identified 9 of 11 patients (82%) who had an objective response (PR/CR) to ICI, including 2 patients who were negative for FDA-approved standard-of-care ICI biomarkers. Furthermore, 5 of 5 patients (100%) with clinical progressive disease were correctly characterized as ELP-score negative. Conclusions: Using routine biopsy specimens, the ex vivo live tumor platform accurately identifies patients with clinical response to ICI therapy, including those incorrectly identified by conventional biomarkers. Ongoing efforts will test these findings in an additional validation set. If confirmed, the ex vivo LTF platform could enable the identification of patients likely to benefit from ICI therapy. Clinical trial information: NCT05478538 , NCT05520099 , NCT06349642 .
Prognostic value of circulating tumor DNA (ctDNA) for recurrence detection across solid tumors: A real-world meta-analysis.
Kopetz, Scott, Laliotis, George, Abdelrahim, Maen, Malla, Midhun, Martin, Robert C. G., Basu, Arnab, Bardia, Aditya, Jacobsen, Luke D., Sharma, Shruti, Toboni, Michael, Schwartz, Gary, Eroglu, Zeynep, Klempner, Samuel J., Lipsyc-Sharf, Marla, Jurdi, Adham A., Liu, Minetta C., Aleshin, Alexey, Galsky, Matthew D., Kopetz, Scott , Laliotis, George, Malla, Midhun , Kim, Richard D. , Martin, Robert C.G. , Bardia, Aditya , Sharma, Shruti , Toboni, Michael Driscoll , Schwartz, Gary , Eroglu, Zeynep , Botta, Gregory P. , Lipsyc-Sharf, Marla , Jurdi, Adham Adel , Liu, Minetta C. , Aleshin, Alexey , Galsky, Matthew D.

Journal of Clinical Oncology | May 27, 2026 | Volume: 44 | Issue: 16_suppl | Pages: 11177-11177

10.1200/jco.2026.44.16_suppl.11177 Get It

11177 Background: Early detection of recurrence after curative-intent treatment is a critical priority, traditional imaging often detects relapse when disease burden is high, potentially limiting treatment efficacy. ctDNA has emerged as an established prognostic biomarker for molecular residual disease (MRD) detection and early relapse. We performed a real-world meta-analysis on published datasets that utilized personalized, tumor-informed ctDNA testing to assess its performance across tumor types and clinical management approaches. Methods: Real-world studies published from December 2022 to December 2025 using the personalized, tumor-informed Signatera ctDNA assay (Natera, Inc.) were included. Eligibility required ctDNA assessment in the MRD (2–16 weeks post-surgery (histology dependent)/pre adjuvant therapy (ACT)) and/or surveillance (post-ACT/end of the MRD window if no ACT was given) settings, with outcomes stratified by ctDNA status and hazard ratios (HR) reported from univariable or time-dependent Cox regression analysis. Exclusions included: clinical trials, biobanks, metastatic disease treated with palliative intent, case reports, reviews, editorials, or commentaries. Clinical outcomes were harmonized into a composite event-free survival (EFS) endpoint (time to recurrence, progression, or death). Pooled HRs and 95% CIs were estimated using random and fixed effects models and heterogeneity between studies was assessed using the I 2 and Cochran’s Q test. Median lead time from ctDNA-positivity to radiographic or clinical recurrence was summarized when available. Results: We identified 18 eligible publications comprising 3,004 unique patients across 15 solid tumor types. During the MRD window, ctDNA positivity was associated with a significantly increased risk of an EFS event compared with ctDNA negativity (pooled HR: 8.15; 95% CI: 6.12–10.85, I 2 = 0.00%, P = 0.844, n = 13). During the surveillance window, inclusive of post-definitive treatment, ctDNA positivity conferred an even greater EFS risk (pooled HR: 18.30; 95% CI: 14.17–23.65, I 2 = 0%, P = 0.911 for heterogeneity, n = 16). Across studies, ctDNA detection during surveillance preceded radiographic or clinical recurrence by a median of 3.20 months (95% CI: 2.50-4.10, P < 0.0001, n = 10), although this varied substantially by study/tumor type (I 2 = 80.9%). Conclusions: In this pan-cancer real-world meta-analysis, ctDNA positivity assessed using a tumor-informed assay was highly prognostic following curative-intent therapy at all timepoints evaluated with low heterogeneity between studies. These findings support the broad clinical utility of tumor-informed ctDNA testing for post-treatment risk stratification and longitudinal disease monitoring across solid tumors.