Citations

Abstract Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with individual cancer risk, and polygenic risk scores (PRS) are typically derived from these cancer-specific variants. Although previous pan-cancer studies revealed shared genetic architectures across cancer types, latent factors contributing to cancer risk have not been explored. This may allow for improved prediction of cancer risk based on a latent cancer factor which leverages shared variants across cancers. Here, we conducted an integrative pan-cancer GWAS across seven solid tumors (breast, ovarian, endometrial, pancreatic, lung, colorectal, melanoma) to identify shared latent genetic factors and novel pleiotropic variants. We curated the most recent and large-scale GWAS summary statistics to maximize statistical power, comprising 398,917 cases and 1,501,715 controls of European ancestry. Shared genetic structures among 6,346,960 common variants were evaluated using Genomic Structural Equation Modeling (GenomicSEM). Three latent factors (Common Cancer Factor, Female-Specific Cancer Factor and Non-Sex Specific Cancer Factor) were constructed, and associations of individual variants with each latent factor were estimated. Genome-wide significant loci (p < 5x10-8) were functionally annotated and subjected to pathway enrichment analysis. Models capturing shared genetic risk across cancers fit the data well. A single “Common Cancer Factor” explained much of the shared risk (SRMR = 0.064 [lower is better], CFI = 0.938 [closer to 1 is better]), and a correlated two-factor model—distinguishing female-specific from other cancers—showed even stronger fit and biological relevance (SRMR = 0.055, CFI = 0.988). The one-factor (Common Cancer Factor; SRMR: 0.064, CFI: 0.938, AIC: 54.7, p_chisq: 0.021) and the two-factor (Female-Specific Cancer Factor and Non-Sex Specific Cancer Factor; SRMR: 0.055, CFI: 0.988, AIC: 45.4, p_chisq: 0.281) models demonstrated robust model fit and biological relevance. Factor-specific GWAS identified 233 genome-wide significant loci (p < 5x10-8) with 24 distinct loci showing shared susceptibility across cancers. More importantly, we identified eight novel variants that were not previously reported or related with any cancer risk, potentially regulating cancer-related genes such as PRC1, CEBPB, SMC2, KLF5 and ATXN2. Further analyses are needed to elucidate their roles in tumorigenesis. Our findings reveal a shared genetic architecture across major solid tumors and uncover novel pleiotropic variants with potential regulatory roles in oncogenesis. This study provides novel insights into the genetic basis of cancer susceptibility and supports the development of multi-cancer PRS to improve prediction in cancer prevention and prognosis. Citation Format: Xunxuan Chen, Gamaliel T. Taengwa, Brandon J. Coombes, Stacey J. Winham. Pan-cancer genome-wide study reveals shared genetic architecture and novel pleiotropic variants across seven solid cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3600.

Abstract Chimeric antigen receptor (CAR) T-cell therapy achieves high response rates in relapsed/refractory aggressive B-cell non-Hodgkin lymphoma, yet only 40% of patients achieve durable remission. Identifying biological programs linked to long-term response remains critical. As metabolic fitness underlies T-cell persistence and effector function, we profiled metabolic pathways associated with clinical outcomes following commercial CD19 CAR T-cell therapy. Single-cell RNA sequencing of peripheral blood mononuclear cells collected at baseline (BL), peak CAR-T expansion (PK), and one-month post-infusion (M1) was analyzed using CellRanger v7.0.1, immunopipe. Seurat v4.3.0 was applied for unsupervised clustering to delineate cell subsets based on top differentially expressed genes. Patients were categorized as durable complete remission (CR ≥6 months; n = 16), primary refractory (PD1; n = 4), or relapse after initial response (PD2; n = 12). Gene-set enrichment analysis defined metabolic pathway activity across T-cell, monocyte, dendritic cell (DC), and natural killer (NK) subsets. Oxidative phosphorylation (OXPHOS) emerged as the dominant metabolic program distinguishing clinical outcomes. At BL and PK, OXPHOS was consistently enriched in PD1 relative to CR across T-cell, monocyte, and DC subsets, suggesting early oxidative activation in non-responders. By M1, this pattern inverted, with higher OXPHOS activity in CR. PD2 largely paralleled PD1, but several subsets including CD8 T central memory, classical monocytes TGFβ, intermediate monocytes CD38, monocytic myeloid-derived suppressor cell (mMDSC) HIF1A, and mMDSC SIRPA, showed OXPHOS enrichment in CR at BL and/or PK that persisted through M1. In contrast, DC and NK subsets exhibited the opposite pattern: OXPHOS was enriched in CR at PK (conventional DC 2 (cDC2), plasmacytoid DC (pDC), NK, proliferating NK), but shifted toward enrichment in PD2 at M1 (cDC2, NK, NK CD56bright). Glycolysis (GLY) followed a similar trajectory in monocytes and NK cells, with enrichment in PD1/PD2 at BL and PK, followed by enrichment in CR at M1. In T-cells, PD1 maintained GLY enrichment from BL through PK, with no significant differences observed at M1. The inositol-phosphate metabolism pathway showed a more static pattern and was consistently enriched in multiple PD2 effector and memory T-cell subsets without reversal at M1. Taken together, these data reveal distinct, lineage-specific metabolic signatures that differentiate durable remission from early and late progression. Dynamic OXPHOS and GLY programming, characterized by lower activity early and enhanced activity at M1 in CR, may reflect adaptive metabolic programming that supports sustained antitumor immunity. Immune-metabolic profiling may therefore serve as a biomarker of response and highlight actionable metabolic pathways to enhance CAR T-cell durability. Citation Format: Melinda S.Y. Tan, Panwen Wang, Patrizia Mondello, Jacqueline Turner, Andre de Menezes Silva Corraes, Chen Wu, Zuoyi Shao, Kevin Regan, Ma Audrey, Arushi Khurana, Nora N. Benanni, Yucai Wang, Paul Hampel, Jonas Paludo, Saad J. Kenderian, Urshila Durani, Patrick B. Johnston, Jose Caetano Villasboas, Stephen M. Ansell, Ying Li, Haidong Dong, Hu Zeng, Yi Lin. Metabolic pathway signatures defining response to CD19 CAR T-Cell therapy in aggressive B-cell non-hodgkin lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3278.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy due in part to metabolic rewiring and a high rate of metastasis. Pancreatic tumors are particularly dependent upon glutamine (Gln) as a nutrient source for multiple metabolic pathways. To adapt to low levels of glutamine, PDAC cells upregulate the Rac1 dependent process of macropinocytosis, which internalizes extracellular macromolecules to scavenge them as a glutamine source. The proto oncogene Vav1 is an activator of the potent Rac/Cdc42 signaling cascades that regulate actin dynamics. While Vav1 is normally restricted to hematopoietic cells, Vav1 expression is significantly increased in PDAC, with high Vav1 correlating with worse overall survival. Here we uncover a novel Vav1 mediated regulation of glutamine metabolism in PDAC cells. While Vav1 is a potent activator of Rac1, surprisingly, Vav1 expression inhibited macropinocytosis in PDAC cells. Intriguingly, genomic and metabolomic analysis revealed that high Vav1 expression correlates with increased dependence on glutamine and glutamate (Glu) metabolism. Indeed, Vav1 dependent macropinocytosis was rescued by cell permeable glutamate, confirming disrupted Gln/Glu balance in Vav1 knockdown cells. RPPA screening indicated a Vav1 dependent effect on glutaminase 1 (GLS1, KGA isoform), which converts glutamine to glutamate. Mechanistically, we discovered that Vav1 modulates GLS1 localization to the mitochondria through regulation of GLS1 posttranslational modification. Disrupting GLS1 localization by deleting its mitochondrial targeting motif phenocopied loss of Vav1 in reducing the invasive potential of tumor cells. Investigation of Vav1 dependent metabolic consequences showed that knockdown of Vav1 alters 13C Gln derived metabolic flux into the TCA cycle, as well as a deficiency in the level of the antioxidant glutathione (GSH), which utilizes glutamate for its synthesis. Consequently, targeting Vav1 resulted in increased levels of cellular and mitochondrial reactive oxygen species (ROS) and increased sensitivity to lipid peroxidation. Notably, dual targeting of both glucose and glutamine pathways showed significant synergistic effects on cellular viability in Vav1 expressing cells. Here we established a new tumor promoting role for Vav1 via Gln/Glu regulation and uncover a novel subcellular regulation of mitochondrial glutamine metabolism. Our findings establish Vav1 as a critical regulator of metabolic rewiring in PDAC and orchestrates glutamine metabolism by controlling the KGA isoform of GLS1 mitochondrial localization. Importantly, Vav1 functions as a signaling adapter in glutamine metabolism, providing a potential therapeutic vulnerabilities for PDAC patients with high Vav1 expression. Citation Format: Mustafa Emre Gedik, Omar L. Gutierrez-Ruiz, Katherine M. Johnson, Ella Rose D. Chianis, Jing Chen, Alex Bittner, Adam Zahm, Ankit Chhoda, Taro Hitosugi, Mark A. McNiven, Gina Razidlo. Vav1 promotes pancreatic tumor cell invasion via GLS1-dependent glutamine metabolism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7322.

Abstract Background: Aberrations in telomere length have important implications in cancer development and progression. This study aimed to determine whether leukocyte telomere length (LTL) in patients with colorectal cancer (CRC) is associated with survival outcomes. We also investigated whether genetic variants in telomere maintenance genes are associated with survival in these patients. Methods: Blood specimens were collected from 1,007 patients prior to receiving chemotherapy or radiation. Genomic DNA was extracted using the Promega Maxwell RSC instrument. LTL was measured in triplicate using monochrome multiplex PCR, where the average amplification value of telomeric repeats was termed T. Similarly, PCR amplification of a single-copy reference gene was performed, and its average amplification value was termed S. The telomere length for each sample was expressed as the T/S ratio. Genotyping of single-nucleotide polymorphisms (SNPs) in TERC, TERT, and OBFC1 genes was conducted at the institutional Genome Analysis Core facility. Kaplan-Meier survival curves were generated to evaluate patient survival outcomes. Results: Younger individuals (∼25 years) exhibited nearly a twofold longer LTL compared with older individuals (∼75 years). No significant difference in LTL was observed between stage II and stage III CRC patients. A strong inverse correlation was observed between patient age and LTL (Spearman’s r = -0.48; p = 1.13 × 10-58). Females had significantly longer LTL than males (p = 3.97 × 10-5). The TERC SNP rs1317082 was significantly associated with both overall survival (OS) and disease-free survival (DFS) in the combined stage II and stage III patient cohort (p = 0.017 and p = 0.023, respectively). Similarly, the OBFC1 SNP rs9419958 was significantly associated with OS (p = 0.016). Importantly, LTL itself was significantly associated with both OS and DFS (p = 0.008 and p = 0.044, respectively) among the combined stage II and stage III patients. Kaplan-Meier survival analyses demonstrated that age- and sex-adjusted LTL was predictive of long-term survival outcomes. Conclusions: Survival among patients with stage II and III colorectal cancer is significantly influenced by LTL. Additionally, specific allelic variants of telomere maintenance genes, including TERC and OBFC1, are independently associated with improved survival, irrespective of LTL. These findings suggest that peripheral blood LTL measurement, along with telomere-related genotyping, may serve as a valuable prognostic marker for colorectal cancer outcomes. Funding: Individualizing colorectal cancer patient care using the host and tumor telomere phenotype (RO1 CA204013), Curtiss Fund (92541775), C-SiG Core(s): Epigenomics & Spatial Biology Core, and Clinical Core of the Mayo Clinic Center for Cell Signaling in Gastroenterology (P30DK084567) Citation Format: Estela M. Cruz Garcia, Gobinda Sarkar, Jun Chen, Shubham Sood, Kim Kossick, Daniel Schupack, Rondell Graham, Brooke Druliner, Zahra Heydari, Lauren Helgeson, Richard G. Cawthon, Lisa A. Boardman. Longer leukocyte telomeres and specific alleles of telomere maintenance genes are independently associated with improved survival of colon cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1919.

Abstract Introduction: Therapeutic outcomes in B-cell non-Hodgkin’s lymphoma (B-NHL) have substantially improved with the introduction of chimeric antigen receptor T-cell (CAR-T) therapy. Yet, persistent immune dysfunction and underlying metabolic dysregulation remain major obstacles to achieving durable clinical responses in B-NHL. We hypothesize that mitochondrial pathways play a critical role in mediating anti-tumor immunity during CAR-T therapy. Methods: Peripheral blood mononuclear cells were collected from healthy controls (CNTRL, n=5) and patients with advanced stage lymphoma (LYM) who received FDA approved CAR-T (n=32). Samples were collected before lymphodepletion (BL), at peak CAR-T expansion (PK) and one-month post-infusion (M1). Single-cell RNA sequencing was used to interrogate differential mitochondrial gene expression. Samples were obtained from LYM patients with complete remission for >6 months (CR), primary refractory (PD1), or relapsed (PD2) disease. Results: Compared to CNTRLs, LYM patients exhibited reduced expression of cytochrome c oxidase. At BL, CR patients demonstrated broader mitochondrial differential gene expression across all T-cell subsets relative to PD1 and PD2 and showed higher expression of MT-ATP-6, MT-ATP-8, and MT-CO3. Following CAR-T infusion, global mitochondrial gene expression increased across patients corresponding with expansion of CD8 effector T cells (Tem tumor circulating) and activated peripheral memory T cells (Tpm). Certain mitochondrial genes, such as MT-CO1, were durably expressed across LYM patients at BL, PK, and M1 in peripheral and central memory T cells (Tpm, Tcm). At PK, cytochrome c oxidase and ATP synthase genes were upregulated in CR Tpm and Tcm. At M1, MT-ATP-6, MT-ATP-8, MT-CO3 were significantly upregulated in CD8 memory precursor effector T-cells (MPECs) of CR patients compared to both PD1 and PD2. While CR and PD2 patients appeared clinically responsive at M1, CR samples maintained significantly higher MT-ATP-8 expression across T cell subsets (CD8 MPECS, Tpm, Tcm) compared to PD2 (p values 0.008; <0.0001; <0.0001). Conclusions: We report a temporal shift in immunometabolism with CAR-T therapy in LYM. Clinical responders exhibited sustained mitochondrial activity characterized by persistent expression of ATP synthase in CD8 MPECs and cytochrome c oxidase in Tpm and Tcm. In sum, mitochondrial programming may distinguish effective versus dysfunctional T cells and identify targets for therapeutic development. Citation Format: Jacqueline Turner, Panwen Wang, Patrizia Mondello, Melinda Tan, Christoph Schaefers, Chen Wu, Andre de Menezes Silva Corraes, Kevin Regan, Zuoyi Shao, Ma Audrey, Arushi Khurana, Nora N. Benanni, Yucai Wang, Paul Hampel, Saad J. Kenderian, Jonas Paludo, Urshila Durani, Patrick B. Johnston, Jose Caetano Villasboas, Stephen M. Ansell, Haidong Dong, Ying Li, Zeng Hu, Yi Lin. Mitochondrial transcriptome profiles associated with clinical responses to CAR-T therapy in aggressive lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1213.

Abstract Background: Tarlatamab, a Delta-like ligand (DLL3)/CD3-targeted bispecific T-cell engager (TCE) is FDA approved in patients (pts) with extensive stage small cell lung cancer (ES-SCLC), after progression on frontline chemoimmunotherapy. We aimed to evaluate the immune cell profile in pts who received this therapy in standard-of-care (SOC) practice with progression free survival (PFS) less than and greater than two months (mo). Methods: Patients who received tarlatamab at Mayo Clinic Rochester and consented to immuno phenotyping of blood are included in the present study. Immune phenotyping was performed on whole blood by flow cytometry and analyzed by Kaluza. Data analysis was performed with Microsoft Excel and PRISM. Results: Eighteen patients with median age 64 (range 37-79) were included in the study. 66% of our cohort were women and 83% had present or past history of smoking, with an average of 40 pack years (range 26-60). With a median follow-up of 2 months, the median PFS for the cohort was 1.5 mo (range 0.33-2.76 months). 61% (13/18) of patients had PFS <2mo. 39% (5/18) had PFS>2mo and of which, three patients had partial response with one maintaining stable disease and one patient with mixed response. At baseline (BL), there were no difference in T cell, CD4 or CD8 cell count between patients in the PFS<2mo and PFS>2mo groups. Patients with PFS<2mo had higher exhausted CD8 T cells compared to those in the PFS>2mo group (CD8+PD1+TIGIT+CD57+, PFS<3mo vs >3mo, cells/mL: 7.14±4.28, 1.58±1.37, p=0.009). Additionally, when analyzing the B-cell population, the PFS<2mo group had lower percentage of B cells compared to the group with PFS>2mo at baseline (6.0±7.5, 10.4±14, p=0.02). At day 7, the group with PFS<2mo had lower Treg compared to the group with PFS>2mo (2.88±1.38, 4.60±1.47, p=0.02). Also, the PFS<2mo group had an increase of B cells compared to the group with PFS>2mo at day 7(<2mo vs >2mo: 10.0±14, 4.37±3.07, p=0.04). Finally, the group with PFS>2mo had decrease in total monocytes (mono), classical mono, and immunosuppressive cells (PFS<2mo vs >2mo, Mono: 340±347, 253±106, p=0.04. Classical mono: 305±283, 155±109, p=0.02. CD14+HLA-DRneg: 105.8±96, 12±39, p=0.03) compared to the group with PFS<2mo by day 7. While no changes were seen between BL and day 7 for intermediate mono in PFS<2mo group, PFS>2mo group had decreased post treatment intermediate monocytes (BL vs day 7, cells/mL, intermed mono: 32.5±15,17.7±6.2, p=0.03). Conclusion: In this study investigating the SOC outcomes of tarlatamab, early progression was associated with higher presence of exhausted CD8 T cells, B cells, and immunosuppressive monocytes. Analysis of additional patients will be shared at AACR meeting. Citation Format: Dhauna Karam Prasad, Andre De Menezes Silva Corraes, Malvika Gupta, Audrey Ma, Chen Wu, Zuoyi Shao, Kevin Reagan, Rayaan Kamal, Ashley Potter, Abdullah Al-Ajmi, Syeda Mina, Sykler J. Taylor, Antonious Hazim, Anastasios Dimou, Kaushal Parikh, Mohammed Shanshal, Ailsa Luce, Anna Schwecke, Julian Molina, Aaron Mansfield, Katherine Smith, Lucy Holmes, Haidong Dong, Yi Lin, Konstantinos Leventakos. Immune cell profile changes in patients treated with tarlatamab for extensive stage small cell lung cancer in real world practice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3931.

Abstract Background: Melanoma brain metastases (MBM) represent a biologically distinct and clinically aggressive subset of melanoma. Comprehensive molecular characterization focused on intracranial disease remains limited. We aimed to define the genomic landscape of MBM and compare these findings with public melanoma datasets. Methods: We retrospectively identified 166 patients with histologically confirmed MBM across Mayo Clinic tri-sites (2011-2025). Molecular testing was performed in 123 patients (74.1%). Comprehensive next-generation sequencing (NGS; ≥300-gene platforms including Tempus, FoundationOne, Caris, NeoGenomics, and MayoComplete Solid Tumor Panel) was available in 41 patients (24.7%). Intermediate-depth profiling using the MayoComplete Melanoma Panel (17 genes) was performed in 21 patients (12.7%), and a targeted 5-gene melanoma driver panel (BRAF, NRAS, KIT, GNAQ, GNA11) in 52 patients (31.3%). cfDNA-based NGS was available in 12 patients (7.2%). Genomic alterations were summarized and benchmarked against TCGA-SKCM and MSK-IMPACT datasets via cBioPortal. We considered assay heterogeneity, as Mayo panels varied in sequencing depth and CNV coverage, and hybrid-capture platforms often under-detect TERT promoter hotspots. Results: Patients had a median age of 67 years, and 63% were male. BRAF mutations occurred in 48.8% (BRAF V600E/K 41.6%; non-V600 7.2%). Additional MAPK alterations included NRAS (17.5%), KIT (5.4%), GNAQ (1.2%), and GNA11 (0.6%). In the comprehensive NGS subset, tumor-suppressor alterations included CDKN2A (17.5%), PTEN (7.8%), NF1 (9.0%), TP53 (8.4%), and TERT promoter mutations (22.9%). Median TMB was 11.55 mut/Mb (IQR 5.0-25.5). Co-alterations included BRAF+CDKN2A (7.2%), BRAF+PTEN (4.2%), NRAS+CDKN2A (4.2%), NRAS+PTEN (1.2%), and CDKN2A+PTEN (3.6%); overall, 18.1% harbored MAPK driver + tumor-suppressor co-alterations. Compared with TCGA and MSK cohorts, MBM showed similar MAPK driver frequencies but fewer MAPK + tumor-suppressor co-alterations and lower CDKN2A, PTEN, and TP53 disruption, alongside a more prevalent of TERT promoter mutations (22.9% vs 7% and 2.1%), which may partly reflect coverage differences. Conclusion: MBM exhibit a distinct genomic profile characterized by reduced tumor-suppressor loss, fewer MAPK-tumor-suppressor co-alterations, and higher prevalence of TERT promoter mutations. While assay heterogeneity limits direct cross-cohort comparisons, these patterns suggest potentially distinct biological features of intracranial melanoma and underscore the need for harmonized, MBM-specific molecular studies to guide therapeutic development. Citation Format: Dina Elantably, Joseph B. Parker, Jakob Hamilton, Ahmed Abdelhakeem, Oluwatayo Adeoye, Saivaishnavi Kamatham, Winston Tan, Arkadiusz Z. Dudek, Anastasios Dimou, Matthew S. Block, Robert McWilliams, Svetomir Markovic, Mahesh Seetharam, Roxana Dronca, Ruqin Chen. Genomic landscape of melanoma brain metastases: Real-world analysis and comparison with public melanoma cohorts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2107.

Abstract Ovarian endometrioid carcinoma (OEC) is the second most common histotype associated with the most favorable prognosis among ovarian carcinomas. Similar to endometrial carcinoma, OEC exhibit significant molecular diversity. We aimed to develop a practical immunohistochemical (IHC) prognosticator by integrating IHC biomarkers with clinical substage, and surgical outcomes. This multi-institutional study included participants with primary invasive OEC from the Alberta Cancer Registry (AOVT), Mayo Clinic, and Disease of the Ovary and their Evaluation Study (DOVE). Pathology review excluded misclassified high-grade serous and mesonephric carcinomas leaving 422 OEC cases (AOVT N=158; DOVE N=143; Mayo N=121) with available tumor biospecimens who did not receive neoadjuvant treatment. Clinical characteristics included age, stage, grade, residual disease and 5-year survival. Clinical risk group was defined by combining stage and residual disease: Low (FIGO stage IA/IB & no macroscopic disease), Intermediate (stage IC-II& no macroscopic disease), High (stage III/IV or macroscopic disease). Tissue microarrays were stained for TP53, PMS2, MSH6, PGR, and CTNNB1 using IHC and were scored by a single pathologist. Tumors were hierarchically categorized as TP53-abnormal (TP53abn)/PGR-loss, mismatch-repair deficient (MMRd, via PMS2 and MSH6), nuclear-CTNNB1 (nCTNNB1), or no-specific-immunohistochemical-profile (NSIP). Overall survival (OS) at 5 years was compared across clinical risk and biomarker groups using Cox regression, adjusted for age and site to generate hazard ratios (HR), and 5-year survival rates (5-YSR). High clinical risk group was associated with worse 5-year OS compared to low & intermediate risk (p<0.0001). Hierarchical IHC biomarker groups were also associated with 5-year OS, adjusted for age and study site (p<0.0001), with consistently worse survival for combined TP53abn/PGR-loss (n=17, HR=6.07, 95% CI 2.78-13.26), PGR-loss only (n=55, HR=4.17, 95% CI 2.19-7.94), TP53abn only (n=29, HR=2.04, 95% CI 0.85-4.90), and better survival for nuclear-CTNNB1 (n=146, HR=0.22, 95% CI 0.07-0.65) compared to NSIP (n=132). Within the low-risk group, MMRd, nCTNNB1, or NSIP had greater than 97% 5-YSR, while OEC with TP53abn/PGR-loss or PR-loss only had less than 75% 5-YSR. Within the intermediate group, only nCTNNB1 exceeded a 5-YSR of greater than 97%. Within the high-risk group, 5YSR for nCTNNB1 OEC was 90.9%, compared to only 16.7% for TP53abn/PGR-loss. This IHC-based algorithm refines prognosis beyond clinical substage. It identifies low-risk patients with unfavorable prognosis (TP53abn/PGRloss, PGR loss only) who may benefit from adjuvant therapy, and also patients with favorable prognosis within the intermediate group for whom adjuvant therapy could be de-escalated. Further patient selection for chemo vs. hormone therapy in the high-risk group may be improved by biomarkers. Citation Format: Gamaliel Taengwa, Hunter J. Atkinson, Bryan M. McCauley, Sebastian M. Armasu, Chen Wang, Jennifer A. Doherty, Holly R. Harris, Ellen L. Goode, Martin Koebel, Stacey J. Winham. IHC-based prognostic sub-stratification of ovarian endometrioid carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1184.

Abstract Background: Combination immune checkpoint inhibitor (ICI) therapy represents a standard-of-care for patients with metastatic melanoma. However, >40% of patients do not respond to treatment and severe immune-related toxicity affects up to 60% of patients. Accordingly, we need more precise ways to select patients for combination ICIs. To address this, we developed LiquidTME, a liquid biopsy method based on Spatial EcoTyper (Cancer Res (2025) 85 (8_Supplement_1): 153) that leverages a deep learning approach to noninvasively assess the tumor microenvironment from cell-free DNA (cfDNA) methylation data. LiquidTME was previously trained to predict ICI response using 78 patients with advanced melanoma treated at Yale University. Here we performed a blinded validation of LiquidTME in coordination with clinicians at Washington University (WashU). Methods: The WashU cohort consisted of pre-ICI plasma from 34 patients with advanced melanoma, each treated with ipilimumab and nivolumab (n=27) or relatlimab and nivolumab (n=7). ICI response was classified as durable clinical benefit (DCB) or no durable benefit (NDB) by a board-certified oncologist. Tumor mutational burden (TMB) was determined for 27 patients using commercial CLIA assays and analyzed as nonsynonymous mutations (mt) per megabase (Mb), using the FDA-approved 10 mt/Mb cutpoint for TMB-high and -low groups. The WashU cohort was sent to a scientific team that was blinded to all clinical and TMB data. Cell-free DNA was extracted from 2 mL plasma per patient and subjected to enzymatic methyl-seq (EM-seq) at a median depth of 15x. LiquidTME was performed on the resulting profiles, yielding a binary response prediction and a continuous response score for each sample. Test results were locked down and returned. Both assays were compared by AUC and two-sided Wilcoxon rank-sum tests for response classification, and Kaplan-Meier analysis for progression-free survival (PFS). Results: Median follow-up time of the cohort was 21.6 months. LiquidTME performed on cycle 1 day 1 pre-ICI plasma significantly stratified PFS with a hazard ratio (HR) of 0.27 (P = 0.005), with LiquidTME(+) patients achieving a median PFS of 1.7 years longer than LiquidTME(-) patients. LiquidTME distinguished DCB from NDB with an AUC of 0.77 (P = 0.007). Similar performance was seen across distinct combination ICI regimens. In patients with TMB data, LiquidTME maintained whole-cohort performance with a PFS HR of 0.30 (P < 0.03; AUC = 0.77). In contrast, TMB high vs. low subsets failed to stratify PFS (HR = 0.49; P = 0.17) or response (AUC = 0.53; P = 0.8). Conclusion: LiquidTME identified durable responders to combination ICI from pretreatment plasma in this blinded validation cohort of melanoma patients. Given its favorable performance, LiquidTME shows promise as a clinical tool to guide personalized immunotherapy decision-making. Citation Format: Aadel A. Chaudhuri, David Y. Chen, Tucker Hansen, Mirna Jarosz, Vincent A. Miller, Aaron M. Newman. Blinded clinical validation of LiquidTME, a cell-free DNA assay for predicting response to immunotherapy by noninvasively profiling the tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1040.

Abstract Background: Spatial cellular ecosystems in the tumor microenvironment (TME) form dynamic signaling hubs that critically influence cancer disease progression and response to therapy, including response to immune checkpoint inhibitors (ICIs). However, tumor sampling bias and the impracticality of acquiring serial tumor biopsies have made it challenging to profile the TME clinically. To address this challenge, we developed Liquid EcoTyper, a multi-analyte AI framework to quantify TME spatial cellular ecosystems—termed spatial ecotypes (SEs)—noninvasively from cell-free DNA (cfDNA) methylation data. Methods: In previous work, we discovered nine spatial ecotypes, including SEs associated with ICI response (e.g., SE7 with benefit, SE4 with resistance), and quantified them from 1,249 bulk tumor RNA-seq profiles of melanoma, non-small cell lung cancer (NSCLC), and bladder cancer (BC) patients (Cancer Res (2025) 85 (8_Supplement_1): 153). Here we trained Liquid EcoTyper, an interpretable deep learning model, to transfer SE profiling to cell-free DNA using CpG methylation profiles. Performance was quantified using simulated and real data, including methylation profiles (EM-seq) of plasma cfDNA paired with tumor biopsy-derived SE levels determined by EM-seq (n=20 pairs) or 10x Visium (n=15 pairs). Clinical outcome prediction was evaluated using pretreatment plasma from patients treated with ICI alone (n=78 melanoma pts), chemotherapy and ICI (n=25 NSCLC pts), and enfortumab vedotin and ICI (n=10 localized muscle-invasive BC (MIBC) pts). Tumor mutational burden (TMB), tumor PD-L1, or circulating tumor DNA (ctDNA) were profiled as a comparator where possible. Results: We observed striking concordance between plasma-derived SE levels and tumor biopsy-confirmed SE levels from the same patients, demonstrating that liquid biopsy analysis of cfDNA methylomes can recapitulate TME spatial biology. Underscoring specificity, no reliable SE signal was detectable from peripheral blood mononuclear cells. In pre-ICI plasma, liquid SE levels were significantly associated with ICI-based response (SE7) versus resistance (SE4) in patients with melanoma, NSCLC, and MIBC, with a mean cross-cancer area under the curve (AUC) of 0.87 for SE7 (range 0.8-0.97) and 0.81 for SE4 (range 0.76-0.85)—far surpassing TMB, tumor PD-L1, and ctDNA in evaluable patients, both in binary analyses of response and multivariable models of survival. Our results also showed potential to predict pathologic complete response in the neoadjuvant setting. Conclusion: Liquid EcoTyper is a scalable noninvasive AI-based framework for spatiotemporal assessment of the TME. By enabling TME-informed risk stratification without surgical biopsies, Liquid EcoTyper has potential to enable more precise and actionable decision making in patients with solid tumors. Citation Format: Erin L. Brown, Wubing Zhang, Abul Usmani, Noah Earland, Ayesha Hashmi, Chibuzor Olelewe, Anushka Viswanathan, Pradeep S. Chauhan, Minji Kang, Chloé B. Steen, Hyun Soo Jeon, Susanna Avagyan, Irfan Alahi, Nicholas P. Semenkovich, Matteo Bergsagel, Janella C. Schwab, Chloe M. Sachs, Faridi Qaium, Peter K. Harris, Antonella Bacchiocchi, Qingyuan Cai, Andrew J. Gentles, Rondell P. Graham, Peter C. Lucas, Ryan C. Fields, Jacob J. Orme, Aaron S. Mansfield, Mario Sznol, Ruth Halaban, David Y. Chen, Aaron M. Newman, Aadel A. Chaudhuri. Liquid biopsy profiling of the tumor microenvironment to determine response to immunotherapy regimens across solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 94.