Citations

Abstract Purpose: Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor, with a median survival of only 15 months. Effective therapeutic advances remain limited, with few clinical trial patients exhibiting robust responses to experimental therapies. This has led to efforts to identify molecular biomarker signatures capable of stratifying patient responses either prognostically (pre-treatment) or diagnostically (post-treatment). This study aims to assess the robustness and reproducibility of published transcriptional GBM biomarker signatures for predicting clinical outcomes in GBM trials. Methods: We analyzed published RNA-seq data from 4 clinical trials involving oncolytic virotherapy and immune checkpoint inhibitors, as well as multiple cohorts of patients treated via the Stupp protocol. The performance of reported immune gene signatures was evaluated across all datasets using both grouped and continuous survival modeling. Intra-patient signature variation between different biopsy sites and timepoints was assessed using longitudinal, multi-site sampling collected by the Break Through Cancer Accelerating GBM Therapies TeamLab. LASSO, multivariate Cox regression, and risk scoring with FDR adjustment were used to identify novel signatures with cross-cohort utility. Key Findings: No single published signature consistently predicted survival across all analyzed trials. A post-treatment ssGSEA antitumor cytokine signature that was associated with survival in the CAN-3110 OV trial (R = 0.74, p < 0.01) was also significantly associated with improved survival in an adjuvant anti-PD1 trial (R = 0.75, p = 0.03) and neoadjuvant anti-PD1 trial (R = 0.30, p = 0.05), but not in standard-of-care controls. PAM clustering of MCP immune signatures, as reported for the DNX-2401 OV+Anti-PD1 trial, also stratified post-treatment survival in the CAN-3110 OV trial (p < 0.01), with the coldest TME subtype consistently predicting worse survival. However, the prognostic value of the most immune enriched TME subtype was inconsistent and did not extend to the Anti-PD1 trials. Furthermore, multi-site, longitudinal biopsy samples revealed marked heterogeneity in biomarker signatures between biopsies from individual patients, even when assessed at the same timepoint. We’ve identified several candidate transcriptomic signatures that show promise for generalizable prognostic value in GBM patient cohorts and are characterizing their spatiotemporal variability. Conclusions: While no individual immune signature is universally predictive in GBM immunotherapy, certain post-treatment cytokine signatures and TME stratifications are significant in multiple immunotherapy contexts, though not in standard-of-care patient cohorts. Marked spatiotemporal heterogeneity in these signatures underscores the need for composite prognostic markers resilient to sampling variance. Citation Format: Christopher M. Jannotta, C Zoe Linke, Charles A. Whittaker, Vikas Patil, Accelerating GBM Therapies TeamLab, Farshad Nassiri, Gelareh Zadeh, E Antonio Chiocca, Alexander L. Ling. Assessing biomarker reproducibility for glioblastoma patient response stratification [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 1055.

Abstract Background: In metastatic cancer, Circulating Tumor cells (CTCs) are established prognostic indictors of patients (pts) less likely to respond to new lines of systemic therapy, with poor clinical outcomes, such as shorter progression free survival (PFS) and overall survival (OS). However, CTCs are typically found in specific malignancies (breast, prostate & colon), often in <20% of pts with metastatic disease, and pts without CTCs may also rapidly progress. Recently, an inflammatory pro-tumorigenic macrophage emanating from tumor stroma (i.e. Cancer associated macrophage-like cell [CAML]) was found in >90% of metastatic cancer pts, and whose phagocytic engorgement appears to correlate with poor outcomes, independent of CTCs. As CTCs and CAMLs are isolated in conjunction from a single blood sample, and both are prognostic for outcomes, we evaluated their utilization prior to induction of new systemic therapy in 6 types of metastatic cancer to model pt risk stratification based on 2 year outcomes. Methods: A prospective 2 year blind multi-institutional study was undertaken to model CTCs and CAMLs in prognosticating outcomes prior to induction of a new line of systemic therapy (n=233) in metastatic: Breast (n=60), Prostate (n=40), Pancreas (n=25), Colon (n=28), Renal Cell Carcinoma (RCC) (n=39), and Lung (n=40). Blood was filtered by CellSieveTM filters with subtypes of CTCs & hyper-enlarged CAMLs (≥100µm) enumerated. A machine learning algorithm was trained on this initial data set to develop predictive models which could stratify pt populations by risk for likelihood of PFS & OS over 2 years, including known clinical variables. Results: CTCs were absent in 80% (n=185/233) of pts, and their absence was prognostic for better PFS (HR=1.6, p=0.046), but not OS (HR=1.3, p=0.2045). In parallel, enlarged CAMLs (≥100µm) were found in 28% (n=51/185) of pts without CTCs, and were also prognostic for worse PFS (HR=2.0, p=0.0082) and OS (HR=1.9, p=0.0412). Specifically, CTCs were found in 55% (n=33) breast, 20% (n=8) prostate, 12% (n=3) pancreas, 11% (n=3) colon, 0% (n=0) RCC, and 0% (n=0) lung pts. Enlarged CAMLs were found in 45% (n=27) breast, 20% (n=8) prostate, 44% (n=11) pancreas, 44% (n=17) colon, 18% (n=7) RCC and 20% (n=8) lung pts. Overall, models indicated that ≥1 CTC (n=47) had mPFS=3.9 & mOS=14.9, while pts with 0 CTCs and ≥100µm CAMLs (n=51) had a mPFS=6.9 & mOS=13.8, and pts with 0 CTCs and <100µm CAMLs (n=134) had a mPFS=10.7 & mOS>24 months. Conclusions: These initial models confirm that both CTCs and enlarged CAMLs are prognostic indicators of worse PFS & OS. The simultaneous quantification both CTCs and CAMLs allows for more accurate pan-cancer risk stratification in an array of cancer pt populations. Additional clinical variables incorporated into the models may allow better risk subtyping and possibly forecast optimal treatment regimens. Citation Format: Daniel L. Adams, Steven H. Lin, Massimo Cristofanilli, Carolina Reduzzi, Saranya Chumsri, Martin J. Edelman, Susan Tsai, Raymond C. Bergan, Mohammed Aldakkak, Thai H. Ho, Cha-Mei Tang. Combining circulating tumor cells and cancer associated macrophage-like cells enhances risk stratification models in pan-cancer metastatic disease [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 1068.

Abstract The detection of genetic abnormalities is required during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this relies on invasive bone marrow (BM) biopsies, severely limiting early detection, frequent longitudinal monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. To address these needs, we recently launched GenoPredicta, a CLIA-approved LDT that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively characterizing MM genomes with whole genome sequencing (WGS) from as few as 50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Briefly, tumor cells are isolated from samples using fluorescence-activated cell sorting and subjected to WGS, from which copy number alterations, structural variants, and short variants (SNVs/indels) are identified using a fully automated pipeline generating physician-ready clinical reports from raw sequencing data in ∼6h. Analytical validation of GenoPredicta showed complete concordance with FISH results. Identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding MM immunotherapies is becoming increasingly important. Here, we describe GenoPredicta results from relapsed/refractory MM patients, highlighting resistance-conferring alterations that can only be detected by WGS, such as deletions in the kilo- to megabase scales that are observed in conjunction with SNVs and indels, leading to biallelic loss/inactivation of the gene, including at subclonal levels. In addition to biallelic loss of BCMA and GPRC5D in response to CAR T or T cell engager therapies, we observed similar resistance mechanisms for targets of immunomodulatory drugs, e.g., CRBN. The observation of these resistance mechanisms was consistent with patients’ clinical histories. In summary, we demonstrate that low input WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with CTC-based measurements enabling comprehensive profiling of the MM genome. Crucially, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection and guidance of therapy. The dramatically improved variant calling ability from WGS, especially in low-input CTC applications, extends to other malignancies and will gain wider adoption as sequencing costs continue to decrease. Citation Format: Bruno Paiva, Peter Voorhees, Patricia T. Greipp, Danielle Sookiasian, Julian Hess, Marisa DeMeo, Vicki Pounder, Sarah Calkins, Reid Meyer, Linda B. Baughn, Christine-Ivy Liacos, Meletios-Athanasios Dimopoulos, Alexandra Papadimou, Taouxi Konstantina, Efstathios Kastritis, Jesus Berdeja, Daniel Auclair, Valentina Nardi, Thomas Mullen, Francois Aguet, Shaji Kunnathu Kumar. Whole genome sequencing of multiple myeloma genomes with a novel clinical assay enables identification of genetic alterations underlying immunotherapy resistance [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 1067.

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 Introduction: Long intergenic noncoding RNAs (lincRNAs) and circular (circ) RNAs have been shown to play key roles in carcinogenesis and tumor progression. Urine represents a promising source of tumor-reflective signals shed directly from the urothelial microenvironment in bladder cancer (BC) patients. Here, we evaluate the urine cell-free (cf) RNA transcriptome in a cohort of 50 patients with localized BC. Methods: A total of 50 localized BC patients and 24 healthy adults were enrolled. Pre-operative urine (collected on the day of radical cystectomy) was processed to isolate cfRNA from urine supernatant. Libraries were prepared using an Illumina tagmentation-based RNA enrichment workflow and sequenced to 100M paired-end reads per sample on a NovaSeq X. FASTQ files were concatenated per sample and QC-checked with RNA-SeQC and Samtools. Reads were aligned to GRCh38/hg38 with STAR, and gene counts were generated using Feature Counts. Linear differential expression analysis (DEA) was performed with DESeq2. For discovery we used random halves of TCGA-BLCA and healthy urine cfRNA samples, alongside a second DEA with random halves of urine BC cfRNA vs. controls; overlapping upregulated genes were validated in the remaining samples. For circular (circ) RNAs, annotations from MiOncoCirc were used; junctions with ≥5 supporting reads were retained, and DEA was conducted with edgeR. Results: In this study, the median age was 68 years, and 80% (40/50) were male. Among the cohort, 66% (33/50) had muscle-invasive bladder cancer (MIBC), of whom 54% received neoadjuvant chemotherapy. Differential expression analysis of TCGA-BLCA tumors and BC urine cfRNA, identified 27 genes commonly upregulated, with 23 of the 27 shared genes strikingly being long intergenic noncoding RNAs (lincRNAs). These BC/urine-specific lincRNAs—including LINC00930, LINC01004, DLG5-AS1, APTR, PSORS1C3, and SERPINB9P1—have known roles in proliferation, EMT, metabolism, and immune signaling. Outside of lincRNAs, tumor-reflective coding transcripts in BC/urine were enriched for autophagy, driven by MAP1LC3B2.TCGA-BLCA survival analysis showed that LINC00930 and PSORS1C3 were associated with worse overall survival. Expanding beyond linear RNA sequences, analysis of urine circRNAs from BC patients revealed a strong cancer-specific dysregulation pattern, with 77 circRNAs significantly upregulated compared with healthy controls. Upregulated urine circRNAs arose from host genes involved in BC-relevant pathways, including invasion (DOCK1, ARHGAP5), autophagy/ER stress (VMP1, ERN1), and luminal differentiation (GRHL2, ESRP1). Conclusion: Cell-free RNA profiling reveals a distinct transcriptomic signature including differential lincRNA- and circRNA-driven autophagy, EMT, proliferation, metabolic, differentiation, and immune signaling programs in the urine of bladder cancer patients. Citation Format: Pradeep Chauhan, Li Lin, Irfan Alahi, Jessica Linford, Lilli J. Greiner, Ayesha Hashmi, Anushka Viswanathan, Nathan Colon, Faridi Qaium, Peter K. Harris, John Sheng, Jacob J. Orme, Eric H. Kim, Zachary L. Smith, Woodson Smelser, Christopher A. Maher, Aadel A. Chaudhuri. Urine cell-free RNA captures tumor-reflective long intergenic noncoding and circular RNA programs in bladder cancer [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 1133.

Abstract Background. Mitophagy plays a crucial role in removing dysfunctional mitochondria to maintain cellular homeostasis but also has been implicated in cancer tumorigenesis. Previously, we showed that genetic variation in mitophagy pathway genes holds a predictive value in metastatic CRC (mCRC) patients (pts) treated with bevacizumab-based chemotherapy. In this study, we analyzed the correlation between tumor expression profiles of genes associated with PINK1/Parkin and BNIP3/NIX/FUNDC1 mitophagy pathways with clinical outcome in a large phase III randomized clinical trial CALGB SWOG 80405. Method. We analyzed 433 pts with mCRC treated with first-line chemotherapy in combination with the targeted agents bevacizumab (Bev, n = 226) or cetuximab (Cet, n = 207). Tumor RNA isolated from FFPE samples was sequenced using the HiSeq 2500 platform (Illumina). Median Overall survival (mOS) and median progression-free survival (mPFS) were compared across pts groups divided into high, medium, and low tertiles based on mitophagy-related gene (BNIP3, BNIP3L, PINK1, PRKN) expression levels. Likelihood ratio tests, hazard ratios (HRs), and 95% confidence intervals (CIs) were calculated using multivariable Cox proportional hazards models, adjusting for age, sex, ECOG performance status, tumor location, number of metastatic sites, KRAS status, Consensus Molecular Subtypes, and treatment arm. Results: Overall, BNIP3L demonstrated significant prognostic value for both PFS and OS after adjustment for multiple testing (false discovery rate [FDR] < 0.05). Tumors with low BNIP3L expression showed longer PFS and OS compared to those with medium or high expression levels (mPFS 14.8 vs. 10.0 vs. 9.2 months, HR 1.16, 95% CI 1.04 - 1.29p = 0.0182; mOS: 37.4 vs. 30.2 vs. 24.4 months, HR 1.22, 95% CI 1.09 - 1.38, p = 0.0036), independent of treatment. In pts treated with Cet, high PRKN expression was associated with improved PFS and OS (mPFS: 8.9 vs. 10.3 vs. 14.6 months, HR 0.79; 95% CI 0.69 - 0.91, p = 7.3e-05; mOS: 21.2 vs. 27.7 vs. 41.1 months, HR 0.87; 95% CI 0.75 - 1.01, p = 0.00084), whereas low PINK1 expression was significantly associated with longer OS (mOS: 24.9 vs. 30.9 vs. 39.2 months, HR 1.23; 95% CI 1.04 -1.46, p = 0.013). No significant associations were observed in Bev-treated patients for PRKN or PINK1. No significant results were found for BNIP3 expression analysis. Conclusion. Mitophagy is a crucial player in CRC biology due to its tumor-intrinsic (mitochondrial bioenergetics) and microenvironment (interacts with immune components) effects. Our study highlights the prognostic value of BNIP3L and predictive potential of PINK1 and PRKN, suggesting a potential combinatorial therapeutic approach using mitochondrial targeting drugs and targeted agents e.g Cet, which warrants further investigation. Support: Genentech; Clinicaltrials.gov Identifier: NCT00265850 Citation Format: Shivani Soni, Yan Yang, Michela Bartolini, Pooja Mittal, Fang-Shu Ou, Lesly Torres-Gonzalez, Unnati Hemant Shah, Jae Ho Lo, Steve Soto Trujillo, Yitzhar Goretsky, Wu Zhang, Alan P. Venook, Sandra Algaze, Joshua Millstein, Heinz-Josef Lenz. Correlation of mitophagy related genes expression and clinical outcome in metastatic colorectal cancer patients enrolled in CALGB (Alliance)/SWOG 80405 [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 1011.

Abstract Introduction: Detectable circulating tumor DNA (ctDNA) is associated with inferior outcomes in Ewing sarcoma (ES); however, ctDNA clears in nearly all patients within 2 of the 6 chemotherapy cycles before radiotherapy (RT) or surgery. Given a 3-year EFS of 37% on AEWS 1221 (metastatic) and 5-year EFS of 78% on AEWS 1031 (localized), current ctDNA testing fails to predict most relapses. Extracellular vesicles (EVs) are microscopic particles studied as a biomarker in multiple cancer types. We hope to improve the sensitivity of ctDNA in ES and provide the first application of EVs in ES. Methods: cfDNA was isolated from 1mL plasma, quantified by Qubit, and sequenced as NEBNext Enzymatic Methyl-seq v2 libraries. We performed a systematic unsupervised clustering analysis of 27 ES plasma cfDNA profiles using 4 differentially methylated regions (DMR) subsets (63 strong DMRs, top 30, top 15, and 10 promoter-proximal loci), 3 clustering algorithms (k-means, Ward hierarchical, PAM), and k=2-5 clusters, testing associations with tumor burden and progression. EV analysis involved antibody detection against ES surface markers, including LINGO1, ENPP1, CDH11, and CD99. Concentrations of EVs were determined by standardized and calibrated high-resolution flow cytometry then analyzed with custom-built software to automatically determine and apply gates. Samples were de-identified, randomly coded, and run in triplicates. The senior research technologist responsible for EV analysis was blinded to patient information and clinical data. Results: EV analysis included 36 pre-RT samples from 16 metastatic and 20 localized ES patients from a prospectively maintained biobank, with 27 pre-RT samples in the cfDNA analysis and 19 healthy donor (HD) samples. 35 of 36 patients had chemotherapy before sample collection. cfDNA concentrations were markedly elevated in ES patients compared with HD (24.4 vs 4.6 ng/mL, p<0.0001), and 74% of ES samples exceeded the HD 95th-percentile detectability threshold (7.0 ng/mL). Across clustering configurations, ES cfDNA profiles consistently exhibited reproducible methylation substructure. One configuration (PAM clustering, k = 5, 63 strong DMRs) showed a modest but permutation-supported association with primary tumor size (nominal p ≈ 0.04; empirical p ≈ 0.03-0.04). ES samples had increased EV concentration compared to HD (p<0.001), with AUC 0.988 for distinguishing between ES and HD ENPP1 (p<0.0001). The highest ENPP1 EV values were in patients with large primary tumors (>8 cm vs. ≤ 8cm) and metastatic disease (p=0.066). Conclusions: cfDNA- and EV-based liquid biopsy provide encouraging signals for high ES detectability pre-RT. We also show the first study of EVs as a novel biomarker in ES, which may provide complementary information to ctDNA. Multimodal liquid biopsy in ES may identify candidate patients for systemic or local therapy escalation and facilitate personalized care. Citation Format: Roman O. Kowalchuk, Lilli J. Greiner, Yohan Kim, Rubia Noori, Jeffrey Szymanski, William S. Harmsen, Pradeep S. Chauhan, Adam C. Amundson, Andrea M. McMahon, Peter J. Schoettler, Wendy A. Allen-Rhoades, Stephanie F. Polites, Peter S. Rose, Kelly M. Bailey, Linda M. McAllister-Lucas, Anita Mahajan, Fabrice Lucien-Matteoni, Nadia N. Laack, Aadel A. Chaudhuri. Multimodal liquid biopsy of Ewing sarcoma reveals high sensitivity prior to radiotherapy [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 1149.

Abstract Background: Endometrial cancer (EC) remains a major gynecologic malignancy driven in part by aberrant estrogen receptor (ER) signaling. The active tamoxifen metabolite (Z)-endoxifen exhibits dual SERM/SERD-like activity, modulating ER function while exerting additional noncanonical antiproliferative effects. Understanding (Z)-endoxifen’s mechanisms of action and its interaction with cell-cycle regulators is critical to optimizing targeted therapy in EC. This study investigated the molecular and functional effects of (Z)-endoxifen, alone and in combination with the CDK4/6 inhibitor abemaciclib, across diverse EC models to define mechanistic activity and translational potential. Methods: ER+ (Ishikawa, HCI-EC23, patient derived organoid U1561.005) and ER-variable (ARK1, ARK2) EC models were treated with estrogen (0-10 nM), (Z)-endoxifen (125 nM-10 µM) or fulvestrant (0-2.5 μM), and abemaciclib (0-10 μM), as single agents or in combination. Cell viability was assessed using luminescence-based assays. Dose-response analyses and combinatorial synergy were evaluated to determine endocrine sensitivity, ER dependency, and downstream cell-cycle effects. Results: Estrogen induced biphasic proliferative responses in ER+ models, confirming ligand-driven mitogenic signaling. (Z)-Endoxifen monotherapy suppressed viability across all cell lines, demonstrating superior potency to fulvestrant and activity independent of ER expression status. Mechanistically, (Z)-endoxifen abrogated estrogen-induced proliferative peaks, consistent with ER antagonism and potential receptor degradation, while also exerting ER-independent effects suggestive of cell-cycle modulation. Abemaciclib monotherapy inhibited viability in both ER+ and ER− models, and its combination with (Z)-endoxifen yielded strong synergistic activity (Chou-Talalay combination index < 1), including in ER-negative ARK2 and the ER+ U1561.005 organoid. This synergy likely arises from concurrent disruption of ER signaling and CDK4/6-cyclin D regulatory pathways. Conclusions: (Z)-Endoxifen demonstrates dual ER-dependent and ER-independent activity in EC preclinical models. Synergy was observed in combination a CDK 4/6 inhibitor. These findings broaden the current understanding of (Z)-endoxifen’s efficacy and support further exploration of its potential therapeutic role in ER-driven and mixed-phenotype EC, including evaluation of responses across ER expression levels. Citation Format: Grace Choong, Xiaonan Hou, Sandra Suarez Hammer, Scott M. Blackburn, John Weroha, Steven C. Quay. (Z)-endoxifen modulates estrogen receptor and cell-cycle signaling to induce synergistic antiproliferative effects with CDK4/6 inhibition in endometrial cancer models [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 405.

Abstract Background: Digital Drug Assignment (DDA) is a computational reasoning model that scores cancer therapies based on the complete molecular profile of a tumor, and stratifies them by predicted efficacy (Petak et al., 2021). In a prior study of 111 lung cancer patients, DDA-derived high-score molecularly targeted agents (MTAs) were associated with improved clinical outcomes (Dirner et al., 2025). Here, we extend this analysis to the GENIE BPC NSCLC cohort to assess the broader clinical validity of DDA. Methods: From the GENIE BPC NSCLC cohort data available on Synapse, we included 1,078 patients with a single-sample genomic profile, available primary treatment data and survival outcomes (total 2,103 treatment lines, therapies included: afatinib, erlotinib, osimertinib, crizotinib, nivolumab, pembrolizumab, atezolizumab, bevacizumab+chemo, ramucirumab+chemo; and chemotherapy alone). DDA scores were generated for all cases, and the individual score of the administered MTAs (incl. immune checkpoint inhibitors) was used to stratify outcomes into low (<0), intermediate, and high DDA-score (≥1000) tiers. Progression-free survival (PFS, by imaging) and overall survival (OS) were analyzed using Kaplan-Meier statistics. Results: Median PFS and OS differed significantly across DDA score tiers, increasing with higher scores (see table). Intermediate-tier drugs had similar mPFS values as chemotherapies (3.9 vs 4.2 months). Six-month PFS and twelve-month OS rates increased with DDA-tiers and were all significantly different by χ2 test. DDA-high therapies provided greater benefit across treatment types than lower-score counterparts. Conclusions: Across a large, real-world NSCLC cohort, DDA effectively distinguished therapies with higher clinical efficacy based on the full molecular profile of each patient. These results reinforce the potential of DDA to enhance personalized treatment selection based on NGS diagnostics in precision oncology. Citation Format: Barbara Vodicska, Eniko Kispeter, Dora Lakatos, Gabor Gy Kalmar, Robert Doczi, Dora Gorog-Tihanyi, Anna Dirner, Reka Szalkai-Denes, William T. Beck, Arkadiusz Z. Dudek, Christophe Le Tourneau, Istvan Petak. Molecularly-informed prediction of treatment efficacy in the GENIE BPC NSCLC cohort using computational reasoning [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 7.

Abstract Lung cancer remains the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Despite advances in targeted and immuno-therapies, overall survival for NSCLC remains below 25%, due to late-stage detection and therapeutic resistance. Cancer stem cells (CSCs), a highly tumorigenic subpopulation within NSCLC, drive relapse, metastasis, and treatment failure. Understanding the mechanisms by which CSCs promote the aggressiveness of NSCLC may reveal new diagnostic and therapeutic opportunities. CSCs establish an intercellular communication network through the secretion of extracellular vesicles (EVs), membrane-bound nanoparticles that transport proteins, lipids, and nucleic acids that can influence recipient cell behavior. Our previous work demonstrated that CSCs secrete significantly more EVs compared to bulk cancer cells (BCCs) and induce an enhanced tumorigenic phenotype in BCCs. However, the EV protein cargo that mediates these CSC-driven phenotypes and the signaling they promote remain poorly understood. This study aimed to identify and characterize CSC-derived EV protein cargo that contributes to NSCLC growth and metastasis. CSC- and BCC-derived EVs were isolated using tangential flow filtration and characterized according to MISEV guidelines. Mass spectrometry and pathway analysis were performed to compare the proteome of CSC- and BCC-derived EVs, followed by functional characterization in vitro and in vivo. Our results showed that EVs exhibited expected morphological, biochemical, and physical properties. Pathway analyses showed that CSC-derived EVs were enriched in proteins that localize to exosomes and associate with metabolism and cell adhesion. Comparison of BCC and CSC-derived EVs revealed Desmoglein-2 (DSG2) as one of the proteins exclusively detected in CSC-derived EVs. shRNA-mediated knockdown of DSG2 significantly reduced invasion, clonal expansion, and transformed growth in vitro and decreased tumor growth and metastasis in vivo. Furthermore, DSG2-competent EVs partially rescued the effects of DSG2 knockdown on CSC tumor growth in vivo. Together, these findings identify DSG2 as a key CSC-specific EV protein cargo that promotes an enhanced tumorigenic phenotype and NSCLC tumor growth. This work highlights the role of CSC-derived EV proteins as mediators of NSCLC aggressiveness and as candidates for biomarker and therapeutic development. Citation Format: Prita Pandya, Aamena Ahmed, Nayya Murray, Dania S. Al-Qasrawi, Anaya Y. Clarke, Reagan Carris, Verline Justilien. Desmoglein-2 carrying cancer stem cell-derived extracellular vesicles promote lung cancer aggressiveness [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 833.