JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-23DOI: 10.1200/PO-26-00046
Alisa Posner, Carol Rosenberg, Katharine M Esselen, Andrew Kelly, Bruno Bockorny
{"title":"Acquired <i>TSC1</i> Mutation as a Mechanism of Alectinib Resistance in <i>ALK</i>-Fused Leiomyosarcoma: Response to Combined ALK and Mammalian Target of Rapamycin Inhibition.","authors":"Alisa Posner, Carol Rosenberg, Katharine M Esselen, Andrew Kelly, Bruno Bockorny","doi":"10.1200/PO-26-00046","DOIUrl":"https://doi.org/10.1200/PO-26-00046","url":null,"abstract":"","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600046"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148578771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of Prior Systemic Chemotherapy on Response to <i>ROS1</i> Tyrosine Kinase Inhibitors in <i>ROS1</i>-Rearranged Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.","authors":"Fumihiro Kashizaki, Shohei Watanabe, Ryusuke Orii, Hanming Lin, Junki Takeda, Takumi Takagishi, Kentaro Yumoto, Harumi Koizumi","doi":"10.1200/PO-26-00347","DOIUrl":"10.1200/PO-26-00347","url":null,"abstract":"<p><strong>Purpose: </strong><i>ROS1</i> rearrangements occur in approximately 1%-2% of non-small cell lung cancer and define a molecular subset characterized by marked sensitivity to tyrosine kinase inhibitors (TKIs). Although ROS1 inhibitors demonstrate high response rates, the potential impact of prior systemic chemotherapy exposure before ROS1 inhibition on subsequent ROS1-TKI efficacy has not been systematically evaluated.</p><p><strong>Methods: </strong>We conducted a systematic review and meta-analysis of prospective ROS1-TKI trials published through December 30, 2025. Outcomes were analyzed separately for TKI-naïve and post-crizotinib cohorts using random-effects models. Study-level meta-regression was performed to evaluate associations between the proportion of patients exposed to prior systemic chemotherapy and treatment response.</p><p><strong>Results: </strong>Eleven TKI-naïve cohorts (N = 706) and four post-crizotinib cohorts (N = 186) were included in the primary analysis. The pooled objective response rate (ORR) was 79% (95% CI, 72 to 84) in TKI-naïve cohorts compared with 42% (95% CI, 32 to 51) in post-crizotinib cohorts. Among 11 TKI-naïve cohorts, prior systemic chemotherapy exposure was significantly and inversely associated with ORR (<i>β</i> = -1.12; OR, 0.33; <i>P</i> = .004). A similar directional association was observed in four post-crizotinib cohorts (<i>β</i> = -1.08; OR, 0.34; <i>P</i> = .077). No significant association was identified between prior systemic chemotherapy exposure and median progression-free survival.</p><p><strong>Conclusion: </strong>Beyond the expected difference between TKI-naïve and post-crizotinib cohorts, prior systemic chemotherapy exposure was associated with lower response rates to ROS1-TKIs in this study-level analysis. Although exploratory and limited by aggregate data, these findings suggest that treatment sequencing and cumulative treatment exposure may influence responsiveness to ROS1 inhibition and support early use of ROS1-directed therapy when clinically feasible.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600347"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148421394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-15DOI: 10.1200/PO-26-00021
Martin W Schoen, Jiannong Li, Sihang Zeng, Heena Desai, Ryan Hausler, Candace L Haroldsen, Lukas Owens, Luca F Valle, Ruth B Etzoni, Timothy R Rebbeck, Brent S Rose, Michael J Kelley, R Bruce Montgomery, Nicholas G Nickols, Matthew B Rettig, Kosj Yamoah, Kara N Maxwell, Isla P Garraway
{"title":"Genomic Classification to Predict Survival in Metastatic Prostate Cancer: Development of Somatic Tumor Risk Assessment for Overall Survival-Prostate.","authors":"Martin W Schoen, Jiannong Li, Sihang Zeng, Heena Desai, Ryan Hausler, Candace L Haroldsen, Lukas Owens, Luca F Valle, Ruth B Etzoni, Timothy R Rebbeck, Brent S Rose, Michael J Kelley, R Bruce Montgomery, Nicholas G Nickols, Matthew B Rettig, Kosj Yamoah, Kara N Maxwell, Isla P Garraway","doi":"10.1200/PO-26-00021","DOIUrl":"10.1200/PO-26-00021","url":null,"abstract":"<p><strong>Purpose: </strong>Tumor comprehensive genomic profiling (CGP) has revolutionized cancer care and identifies patients for biomarker-specific therapy. In metastatic hormone-sensitive prostate cancer (mHSPC), although individual genes are prognostic, no comprehensive genomic classification exists using CGP that accounts for combinations of alterations to inform prognosis. We developed a DNA-based CGP classification that is prognostic for overall survival (OS) and could inform treatment.</p><p><strong>Methods: </strong>This was a retrospective cross-sectional study using multivariable models to develop a clinicogenomic prognostic risk classification in US veterans with synchronous mHSPC. The primary outcome was OS from time of metastasis.</p><p><strong>Results: </strong>A total of 7,201 veterans with metastatic prostate cancer and CGP were identified. There were 2,484 veterans (median [IQR] age, 72 [67-77] years) with synchronous mHSPC and tissue CGP, which were divided into training and testing data sets. Sixteen genes associated with survival were identified, and favorable, intermediate, and unfavorable genomic prognostication groups were created based on the mortality risk to generate the Somatic Tumor Risk Assessment for OS-Prostate (STRATOS-P) classification. In a multivariable model, classification into intermediate and unfavorable groups was associated with increased mortality relative to the favorable group (adjusted hazard ratio [aHR], 1.54 [95% CI, 1.33 to 1.78]; aHR, 2.37 [95% CI, 1.97 to 2.485], respectively), demonstrating an average AUC of 0.83. In an external, nonveterans validation cohort, intermediate and unfavorable classifications were associated with increased mortality (aHR, 2.45 [95% CI, 1.87 to 3.21]; aHR, 4.37 [95% CI, 3.06 to 6.22], respectively) with an AUC of 0.79. The intermediate and unfavorable genomic prognostication groups were also associated with increased mortality across multiple disease states including synchronous and metachronous diagnoses, castration resistance, and analyte type.</p><p><strong>Conclusion: </strong>In metastatic prostate cancer, tumor DNA genomic alterations are prognostic for OS. The STRATOS-P classification is a validated prognostic tool that has the potential to guide decision making in mHSPC.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600021"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13378758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148455849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-06DOI: 10.1200/PO-26-00011
Janene Dalrymple, Rebecca Symons, Katrin M Sjoquist, Sally J Lord, Rachel Woodford, Michael Friedlander, R John Simes, Chee Khoon Lee
{"title":"Time to Treatment Failure as an End Point in Pragmatic Oncology Trials: Association With Progression-Free Survival Across Randomized Studies.","authors":"Janene Dalrymple, Rebecca Symons, Katrin M Sjoquist, Sally J Lord, Rachel Woodford, Michael Friedlander, R John Simes, Chee Khoon Lee","doi":"10.1200/PO-26-00011","DOIUrl":"https://doi.org/10.1200/PO-26-00011","url":null,"abstract":"<p><strong>Purpose: </strong>Time to treatment failure (TTF), defined as the time from random assignment to treatment cessation for any reason, is an end point readily obtainable from routine clinical and real-world data sources. Despite its growing use, evidence describing its relationship with progression-free survival (PFS) remains limited. We evaluated the association between TTF and PFS across tumor types and treatment modalities to assess the validity of TTF as an end point for pragmatic oncology trials.</p><p><strong>Methods: </strong>A systematic search identified randomized trials of advanced solid tumors reporting TTF and PFS. Correlations between hazard ratios (HRs) for TTF and PFS were assessed using inverse variance-weighted linear regression, stratified by prognosis (median overall survival <12 <i>v</i> ≥12 months). Subgroup analyses were performed according to therapy type and line of treatment. Individual patient data (IPD) were reconstructed from published Kaplan-Meier curves to enable arm-level comparisons.</p><p><strong>Results: </strong>Fifty-eight analysis units encompassing 19,099 patients across 13 tumor types were included. TTF and PFS were strongly correlated in both poor- (r = 0.81; 95% CI, 0.59 to 0.94) and good-prognosis (r = 0.79; 95% CI, 0.60 to 0.91) groups. In the intervention arm, median TTF and PFS were comparable in poor-prognosis trials (9.6 <i>v</i> 11.0 months, <i>P</i> = .12) but diverged in good-prognosis settings (16.8 <i>v</i> 23.0 months, <i>P</i> < .001). Correlation was the highest in chemotherapy-based (r = 0.93-0.96) and first-line (r = 0.88-0.90) trials and weaker in targeted-therapy (r = 0.35-0.55) and later-line settings (r = 0.35-0.82).</p><p><strong>Conclusion: </strong>TTF offers a practical, patient-centered end point, reflecting both treatment efficacy and tolerability. Its strong correlation with PFS supports its role as a clinically meaningful end point for pragmatic oncology trials in advanced cancers.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600011"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ilias Ziakas, Amna Jamali, Michael Conroy, Katerina Karaindrou, Jaime Wehr, Dana Petry, Benjamin P Levy, Susan C Scott, Patrick Forde, Jenna V Canzoniero, Rena Xian, Ming-Tseh Lin, Valsamo Anagnostou, Jessica J Tao
{"title":"Emergence of Microsatellite Instability in an Oncogene-Driven Non-Small Cell Lung Cancer Harboring a Canonical <i>EGFR</i> Mutation: A Molecular Tumor Board Discussion.","authors":"Ilias Ziakas, Amna Jamali, Michael Conroy, Katerina Karaindrou, Jaime Wehr, Dana Petry, Benjamin P Levy, Susan C Scott, Patrick Forde, Jenna V Canzoniero, Rena Xian, Ming-Tseh Lin, Valsamo Anagnostou, Jessica J Tao","doi":"10.1200/PO-26-00067","DOIUrl":"10.1200/PO-26-00067","url":null,"abstract":"","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600067"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336690/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148368347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-08DOI: 10.1200/PO-26-00065
Peter H J Slootbeek, Yarah M Quint, Julian J R Kokke, Samhita Pamidimarri Naga, Maria Victoria Luna-Velez, Marjolijn J L Ligtenberg, Richarda M de Voer, Niven Mehra
{"title":"Shallow Whole-Genome Sequencing to Assess Genomic Instability and Predict Treatment Response in Metastatic Castration-Resistant Prostate Cancer.","authors":"Peter H J Slootbeek, Yarah M Quint, Julian J R Kokke, Samhita Pamidimarri Naga, Maria Victoria Luna-Velez, Marjolijn J L Ligtenberg, Richarda M de Voer, Niven Mehra","doi":"10.1200/PO-26-00065","DOIUrl":"10.1200/PO-26-00065","url":null,"abstract":"<p><strong>Purpose: </strong>Patients with metastatic castration-resistant prostate cancer (mCRPC) and homologous recombination deficiency (HRD) benefit from poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis) or platinum-based chemotherapy (PlCh). Pathogenic variants in homologous recombination repair genes are used as a proxy for the phenotype. Genomic Instability Score (GIS) is a metric for the effect of HRD. This study used shallow whole-genome sequencing (sWGS), a cost-effective alternative to full-depth WGS, to calculate GIS and evaluate its predictive value for PARPi or PlCh response.</p><p><strong>Patients and methods: </strong>We analyzed 288 tumor samples from 266 patients with mCRPC, consisting of 120 whole-genome samples from formalin-fixed paraffin-embedded material newly profiled at a sequencing depth of 2× and 168 from fresh frozen material downsampled in silico from 106× to 2×. The GIS was defined as the sum of large-scale transitions, telomeric-allelic imbalances, and genomic loss of heterozygosity.</p><p><strong>Results: </strong>The median GIS was 26 (IQR, 19-37). Samples with pathogenic variants in <i>BRCA1</i>, <i>BRCA2</i>, or <i>PALB2</i> (BRCA complex) had a significantly higher median GIS (38 <i>v</i> 26, <i>P</i> < .0005). The median GIS increased significantly with tumor ploidy. Patients showing ≥50% prostate-specific antigen (PSA) declines had higher GIS on both PARPi (median 40 <i>v</i> 28, <i>P</i> = .0003) and PlCh (41 <i>v</i> 26, <i>P</i> = .0113). Similarly, patients with a partial response by RECIST1.1 had higher GIS than those with progressive disease (PARPi: 39 <i>v</i> 26, <i>P</i> = .0356; PlCh: 44 <i>v</i> 25, <i>P</i> = .0046). Adding GIS to BRCA-complex status improved PSA response prediction in logistic models (AUC PARPi: 0.849 <i>v</i> 0.781, <i>P</i> = .0308; PlCh: 0.731 <i>v</i> 0.658, <i>P</i> = .1888).</p><p><strong>Conclusion: </strong>GIS assessment by sWGS is feasible and associated with response to PARPis and PlCh. The combination of BRCA-complex status and GIS is superior to BRCA-complex status alone in predicting PSA response to PARPis but not to PlCh.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600065"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13374653/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148412121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-15DOI: 10.1200/PO-26-00208
David Hui, Kristofer Jennings, Amy Ontai, Eduardo Bruera
{"title":"Hypoalbuminemia as a Predictive Biomarker of Dyspnea Response to Dexamethasone and Placebo in Patients With Cancer: Secondary Analysis of the ABCD Randomized Clinical Trial.","authors":"David Hui, Kristofer Jennings, Amy Ontai, Eduardo Bruera","doi":"10.1200/PO-26-00208","DOIUrl":"10.1200/PO-26-00208","url":null,"abstract":"<p><strong>Purpose: </strong>We previously found that baseline cytokine levels predicted dyspnea response to dexamethasone and placebo in patients with cancer. However, cytokine immunoassays are impractical for clinical applications, highlighting the need for alternative inflammatory biomarkers. We sought to examine the predictive value of albumin, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) for dyspnea response to dexamethasone or placebo in patients with cancer.</p><p><strong>Methods: </strong>This is a secondary analysis of the Alleviating Breathlessness in Cancer Patients with Dexamethasone randomized clinical trial in which patients with cancer and moderate-to-high dyspnea received either dexamethasone or matching placebo for 14 days. We used generalized additive models to examine associations between baseline albumin, NLR, and PLR and dyspnea numeric rating scale (NRS) response to dexamethasone or placebo.</p><p><strong>Results: </strong>Clinical bloodwork was available for 63 patients. Both the dexamethasone and placebo groups had a significant decrease in dyspnea by day 14 (mean change -1.8 and -1.9, respectively), with no significant between-group differences (-0.1 [95% CI, -1.1 to 1.3]). In the dexamethasone group, lower baseline albumin was significantly associated with a greater reduction in dyspnea NRS (day 14 slope: +1.2, <i>P</i> = .05); in contrast, higher baseline albumin was significantly associated with a greater reduction of dyspnea NRS in the placebo group (day 14 slope: -3.0, <i>P</i> = .004). No associations were found between baseline NLR or PLR levels and dyspnea response to either dexamethasone or placebo.</p><p><strong>Conclusion: </strong>Hypoalbuminemia may be a potential differential biomarker of dyspnea response to dexamethasone and placebo. On further validation, these findings may facilitate future personalized clinical trial design and tailoring of dyspnea interventions.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600208"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148455851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-07-01Epub Date: 2026-07-08DOI: 10.1200/PO-26-00158
Sophia C Kamran, Monica Borges, Jeff Michalski, W Robert Lee, Howard M Sandler, Juanita Crook, Alan Pollack, Mark D Hurwitz, Richard K Valicenti, Deborah Watkins Bruner, Himanshu Lukka, Christopher U Jones, Mack Roach, Colleen Lawton, Seth A Rosenthal, Thomas M Pisansky, Daniel Spratt, Neha Vapiwala, Jason Efstathiou, David Miyamoto, Kent Mouw, Melissa Vyfhuis, Quynh-Thu Le, Henning Willers, Eliezer Van Allen, Franklin Huang, Jean-Paul Bahary, Joelle Helou, Stephanie L Pugh, Jennifer Wenzel, Phuoc Tran
{"title":"Participant Heterogeneity in the Prostate Cancer Biobank of the NRG: An Obstacle to Broadening the Reach of Precision Oncology.","authors":"Sophia C Kamran, Monica Borges, Jeff Michalski, W Robert Lee, Howard M Sandler, Juanita Crook, Alan Pollack, Mark D Hurwitz, Richard K Valicenti, Deborah Watkins Bruner, Himanshu Lukka, Christopher U Jones, Mack Roach, Colleen Lawton, Seth A Rosenthal, Thomas M Pisansky, Daniel Spratt, Neha Vapiwala, Jason Efstathiou, David Miyamoto, Kent Mouw, Melissa Vyfhuis, Quynh-Thu Le, Henning Willers, Eliezer Van Allen, Franklin Huang, Jean-Paul Bahary, Joelle Helou, Stephanie L Pugh, Jennifer Wenzel, Phuoc Tran","doi":"10.1200/PO-26-00158","DOIUrl":"10.1200/PO-26-00158","url":null,"abstract":"<p><strong>Purpose: </strong>Precision medicine has revolutionized oncology; however, tumor biomarkers are not reflective of the heterogeneous cancer population. We evaluated NRG Oncology prostate cancer (PCa) clinical trials for demographic differences among patients with optional biospecimen collection (BC) consent and biospecimen submission (BSub).</p><p><strong>Methods: </strong>Data from 19 NRG PCa clinical trials closed before 2015 were analyzed. Patients who consented to BC and completed BSub were evaluated by race, ethnicity, median income, area deprivation index (ADI; categorized as highest <i>v</i> lowest three quartiles), age at enrollment, site, and year of enrollment. T/chi-square tests were used for continuous/categorical variables, respectively, followed by logistic regression.</p><p><strong>Results: </strong>Of the 15,648 randomized patients eligible for BC, 11,796 (75%) had specimens submitted. In all, 4,598 (82.2%) of 5,597 eligible patients consented for optional BC in nine clinical trials with a separate BC consent process (consent rates by race/ethnicity: 74.1% Black, 72.8% Hispanic/Latino, 83.8% White). A smaller proportion of Black and Hispanic/Latino patients consented to optional BC compared with those who did not (12.1% <i>v</i> 19.5% Black, <i>P</i> < .0001; 3.5% <i>v</i> 5.8% Hispanic, <i>P</i> = .0006). In univariable logistic regression models, high ADI (more socioeconomic disadvantage) was associated with a decreased likelihood for optional BC consent (odds ratio [OR], 0.67 [95% CI, 0.55 to 0.82]; <i>P</i> = .02), but not a decreased likelihood for BSub (OR, 0.74 [95% CI, 0.53 to 1.04]; <i>P</i> = .08). Multivariable models demonstrated that Black/Hispanic/Latino patients were less likely to consent to optional BC, and Black patients were less likely to have BSub (<i>P</i> < .05 for all).</p><p><strong>Conclusion: </strong>White/non-Hispanic patients and those with less socioeconomic disadvantage were more likely to consent to optional BC, whereas Black patients were less likely to have BSub. Targeted solutions are needed to improve biorepository representation so that precision medicine approaches better reflect the cancer population.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 7","pages":"e2600158"},"PeriodicalIF":4.7,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13537434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148412085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JCO precision oncologyPub Date : 2026-06-01Epub Date: 2026-06-12DOI: 10.1200/PO-26-00138
Brian W Labadie, Aleksandar Obradovic, Alexander G Raufi, Urszula N Wasko, Lorenzo Tomassoni, Liner Ge, Michael May, Manan Vij, Li Li, Isabelle Ross, Sarah S Sedycius, Naomi Sender, Nickolas Dreher, Linda Wu, Sinan Abuzaid, Alina Iuga, Parin Shah, Julia D Wulfkuhle, Susan Bates, Winston Wong, Ilenia Pellicciotta, Alex K Lyashchenko, Howard Safran, Benjamin Izar, Emanuel F Petricoin, Serge Cremers, Aik Choon Tan, Shing Lee, Andrea Califano, Kenneth P Olive, Gulam A Manji
{"title":"Targeting of MEK and Autophagy in Pancreatic Adenocarcinoma and Analysis of Treatment Sensitivity in Preclinical and Clinical Models: MEKiAUTO.","authors":"Brian W Labadie, Aleksandar Obradovic, Alexander G Raufi, Urszula N Wasko, Lorenzo Tomassoni, Liner Ge, Michael May, Manan Vij, Li Li, Isabelle Ross, Sarah S Sedycius, Naomi Sender, Nickolas Dreher, Linda Wu, Sinan Abuzaid, Alina Iuga, Parin Shah, Julia D Wulfkuhle, Susan Bates, Winston Wong, Ilenia Pellicciotta, Alex K Lyashchenko, Howard Safran, Benjamin Izar, Emanuel F Petricoin, Serge Cremers, Aik Choon Tan, Shing Lee, Andrea Califano, Kenneth P Olive, Gulam A Manji","doi":"10.1200/PO-26-00138","DOIUrl":"10.1200/PO-26-00138","url":null,"abstract":"<p><strong>Purpose: </strong>Combined mitogen-activated protein kinase kinase (MEK) and autophagy inhibition has shown antitumor efficacy in preclinical pancreatic ductal adenocarcinoma (PDAC) models. We evaluated this therapeutic strategy in the autochthonous K-ras<sup>LSL.G12D/+</sup>; Trp53<sup>R172H/+</sup>; Pdx-1-Cre (KPC) mouse model and in the MEKiAUTO phase I trial of patients with metastatic <i>KRAS</i>-mutant PDAC, with or without anti-PD-L1 antibody atezolizumab.</p><p><strong>Methods: </strong>Short-term intervention studies in KPC mice and a phase I clinical trial based on a time-to-event continual reassessment method design were performed. Tumor response was assessed through multiplex immunofluorescence, reverse-phase protein array, and single-nucleus RNA sequencing of serial tumor specimens.</p><p><strong>Results: </strong>MEK and autophagy inhibition suppressed tumor growth in KPC mice. In the clinical trial, 14 patients were treated and four experienced a dose-limiting toxicity. The median progression-free survival (PFS) and overall survival were 7.7 weeks (95% CI, 6 to 15.6) and 20.7 weeks (95% CI, 15.6 to 46.1), respectively. snRNA-seq on paired tumor biopsies identified substantial malignant cell heterogeneity, including an epithelial subtype enriched for autophagy and mitogen-activated protein kinase (MAPK) signaling that decreased after treatment. Higher baseline abundance of this subtype correlated with longer PFS but was rare in TCGA PDAC tumors. By contrast, KPC tumors and PDAC cell lines exhibited reduced heterogeneity and uniform enrichment of this MAPK/autophagy-high state, consistent with their stronger preclinical responses.</p><p><strong>Conclusion: </strong>Combined MEK and autophagy inhibition showed limited tolerability in human PDAC. Divergent efficacy between preclinical and clinical settings likely reflects differences in tumor cell state heterogeneity between models. Integration of diverse, representative preclinical models is critical to guide development of effective therapies in PDAC.</p>","PeriodicalId":14797,"journal":{"name":"JCO precision oncology","volume":"10 6","pages":"e2600138"},"PeriodicalIF":4.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148239415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}