Citations

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies due to its silent clinical onset, rapid progression, and limited responsiveness to current treatment options. These features underscore the urgent need for early detection strategies and for new molecular targets that can be exploited therapeutically. Epithelial Cell Transforming Sequence 2 (ECT2) is a Rho family guanine nucleotide exchange factor that was originally identified as an oncoprotein and later shown to regulate cytokinesis. In this study, we examined the clinical relevance of ECT2 expression in PDAC and determined its functional contribution to transformed growth and tumorigenicity. Our analyses revealed that ECT2 expression increases at the earliest stages of PDAC development, remains persistently elevated during disease progression, and associates with reduced overall patient survival. Furthermore, a substantial fraction of ECT2 is aberrantly localized to the cytoplasm of PDAC cells. Functional studies demonstrated that depletion of ECT2 suppresses three-dimensional growth, invasive behavior, and tumor formation in vivo, while having little impact on PDAC cell cytokinesis. Mechanistically, we found that ECT2 is required for activation of Rac1 and RhoA and downstream MEK/ERK and ROCK signaling, respectively. Consistent with these results, analyses of PDAC patient datasets revealed a strong positive association between ECT2 expression and Rho GTPase as well as MEK/ERK and ROCK pathway signatures. Together, our data identify ECT2 as an early driver of PDAC transformation and highlight it as a promising therapeutic target. Citation Format: Dania Al-Qasrawi, Nayya N. Murray, Ryan A. Argo, Alicia K. Fleming Martinez, Prita Pandya, Anaya Y. Clarke, Kayla C. Winter, Murli Krishna, Peter Storz, Nicole R. Murray, Verline Justilien, . The Rho-GEF ECT2 links Rho GTPases to MEK/ERK pathway activation in pancreatic ductal adenocarcinoma [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 5993.

Abstract Glioma stem cells (GSCs) are considered a major driver of glioblastoma (GBM) progression and are highly resistant to standard cytotoxic treatments. BMP4 has been shown to promote GSC differentiation, enhance radiosensitivity, slow tumor growth, and extend survival in animal models. Despite this promise, BMP4 has yet to achieve clinical impact, owing largely to heterogeneous and nonlinear responses across preclinical experimental systems. To elucidate how BMP4 could function as an effective targeted differentiation therapy in GBM, we develop a mathematical model that describes the growth of a GBM tumor via a hierarchy of GSCs, progenitor and terminally differentiated cells. We parameterize our model using new radiotherapy and proliferation assay data (with and without BMP4 exposure) from twelve patient-derived GSC lines. This integration of model and data allows us, for the first time, to quantitatively capture patient-specific heterogeneity in BMP4 sensitivity. We perform global sensitivity analysis on the model, identifying proliferation rate and GSC self-renewal sensitivity as key determinants of BMP4 efficacy. These parameters act as model-derived biomarkers that distinguish BMP4-responsive tumors from non-responsive ones. In an in silico analysis across a broad cohort of virtual patients, we find that continuous BMP4 delivery from surgical resection through radiotherapy consistently outperforms a single-dose strategy. Virtual clinical trials further show that, without stratification using these model-derived biomarkers, BMP4 yields little observable therapeutic benefit. In contrast, selecting patients with more proliferative, BMP4-responsive GSCs markedly increases the likelihood of observing a significant treatment effect. Citation Format: Nicholas Harbour, Lee Curtin, Loizos Michaelides, Matthew E. Hubbard, Pamela Jackson, Vinitha Rani, Rajappa Kenchappa, Virginea Farias, Anna Carrano, Markus Owen, Alfredo Quinones-Hinojosa, Kristin Swanson. Virtual clinical trials of BMP4 differentiation therapy [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 6831.

Abstract Phosphatase and Tensin Homolog (PTEN) is a critical tumor suppressor frequently mutated in cancers, notably endometrial cancer (EC), where it drives early carcinogenesis. PTEN mutations disrupt lipid phosphatase activity, causing PI3K/AKT/mTOR pathway hyperactivation. However, clinical trials targeting this pathway in advanced EC yield suboptimal outcomes, with PTEN loss showing poorly predictive value for therapeutic response, indicating other mechanisms are involved. TCGA Pan-Cancer Atlas data show a 39.1% co-mutation rate of PTEN and PIK3CA in EC, much higher than the 3.6% pan-cancer rate, challenging the idea of mutual exclusivity in driver mutations within the same pathway. PTEN missense mutations are most common in EC (41.44%), with R130 as a hotspot, especially among PIK3CA-mutant patients (45.28%), while other cancers with frequent PTEN mutations show much lower R130 rates. These findings suggest PTEN R130 missense mutants undergo positive selection and may have unique oncogenic effects in EC.To characterize these mutants, a Tet-on inducible system in PTEN-null SPAC-1-S EC cells compared wild-type PTEN (PTENWT), loss of function mutant PTENR173C, and ultrahigh frequency mutant PTENR130G. PTENWT suppressed proliferation, PTENR173C showed reduced tumor suppressive activity, while PTENR130G increased proliferation, indicating a PTENWT-independent tumor-promoting function. In MFE 296 cells with PTEN R130Q/N332fs mutations, knockdown of PTENR130Q suppressed proliferation, providing functional evidence that PTENR130G has PTENWT-independent oncogenic activity in EC. To elucidate the underlying mechanisms, we performed quantitative proteomic and BioSITe analyses in SPAC-1-S cells inducibly expressing PTENWT or PTENR130G, enabling comprehensive mapping of the unique signaling alterations specific to this ultrahigh-frequency PTENR130G mutant. Our initial analysis revealed that PTENWT induction caused broad transcriptional suppression of oncogenic and structural pathways, including MAPK/ERBB, focal adhesion, ECM-receptor interaction, and lysosomal function, consistent with restored tumor-suppressive activity. In contrast, PTENR130G induction led to a distinct transcriptional response; while partially repressing lysosomal and adhesion pathways, stress-adaptive and metabolic programs like TGF-β signaling and glutathione metabolism remained active or were reactivated. These results suggest PTENR130G not only loses PTEN’s inhibitory functions but may gain new transcriptional and metabolic activities that promote cell survival and tumor progression. Overall, our analysis indicates wildtype PTEN restores signaling restraint, while PTENR130G reprograms the transcriptome toward a pro-cancer, stress-resilient state, suggesting a gain-of-function oncogenic role. Citation Format: Xiangyi Kong, Li Wang, Md Kamrul Hasan Khan, Jidong Wang, Huaijun Zhou, Xinyan Wu. Unique oncogenic mechanisms of ultrahigh-frequency mutant PTENR130Gin endometrial 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 7654.

Abstract INTRODUCTION: Colorectal cancer (CRC) is the 2nd most fatal cancer in the U.S.; most benefits of CRC screening are from detection of advanced pre-cancerous lesions (APLs). With a goal to improve non-invasive stool test APL sensitivity, we sought novel APL signatures in stool metaproteomes (host- and gut microbiome-derived proteins) among cancer-free controls (CTRL), APL, and CRC patients. Since dysbiosis in gut microbiota is associated with CRC initiation, we also examined the microbial source of differentially expressed proteins (DEPs). METHODS: Mass spectrometry was performed on archival stool supernatants (n=63 patients; 15 CTRL, 32 APL [16 adenomas & 16 sessile serrated lesions], 16 CRC). A sectioning and database-enrichment strategy was applied for peptide-spectrum matching. Microbial and human-derived proteins were searched against the Integrated Gene Catalogue (IGC) and UniProt human reference proteome. DEPs were identified using thresholds of P < 0.05 and fold-change ≥ 1.5. Pathway annotation of human DEPs was performed with the REVIGO webserver, while gut microbial DEPs were functionally categorized using the KEGG Automatic Annotation Server (KAAS). To assess the taxonomic distribution of microbial DEPs, sequences were aligned against the NCBI non-redundant database using BLASTP. RESULTS: Mass spectrometry detected 879 human and 32,514 microbiome-derived proteins. When limiting detection to proteins present in ≥ 75% of patients, only 117 human and 204 microbial proteins remained. There were 17 (4,875), 288 (9,638), and 63 (3,053) unique human (microbial) proteins detected in CTRL, APL, and CRC groups, respectively. When the protein presence cutoff was set at >30% of patients, there were 52 (13 human [11 upregulated, 2 downregulated], 39 microbial [28 upregulated, 11 downregulated]) DEPs detected for the CRC + APL vs CTRL comparison. Some pathways associated with upregulated human DEPs included: inflammatory response, cellular response to iron, and endothelial cell migration. The top upregulated microbial DEPs were derived from the Phocaeicola, Lachnospiraceae, and Oscillospiraceae genera. The top downregulated microbial DEPs belonged to the Bacteroides, Eubacterium, Agathobacter, Coprococcus, and Blautia genera. CONCLUSION: This work highlights the biological diversity and molecular heterogeneity of the stool proteome. We identified several host and microbial protein markers that differentiate APLs and early CRC from controls. These results provide a foundation for future validation studies, which are necessary to determine the clinical utility of these protein biomarkers prior to their integration into a noninvasive stool test. Citation Format: Emmalee J. Northrop-Albrecht, Vinod K. Gupta, William R. Taylor, Jason P. Sinnwell, Doug W. Mahoney, Patrick H. Foote, Kelli N. Burger, Jaeyun Sung, John B. Kisiel, . Comprehensive investigation of stool metaproteomes among patients with precancerous lesions and colorectal 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 7656.

Abstract Introduction: The intricate cellular structure is a constantly evolving environment where cells interact, communicate, and adapt to their surroundings. The fate, role, and actions of each cell are shaped by its specific location within the tissue. Therefore, studying the spatial proteome is crucial for gaining a deeper understanding of physiological or pathological processes. With significant advancements in microscopy and mass spectrometry, it has become feasible to explore the cellular proteome at low or even single cell numbers. However, spatial proteomics is an evolving field with scope for newer sample preparation and data analysis techniques. Our objective was to develop a sample preparation workflow for analyzing proteome from limited cells extracted from formalin fixed paraffin embedded (FFPE) tissue using laser capture microdissection (LCM). Methods: One hundred cells from the FFPE normal colon tissue were extracted by LCM and collected into an AFA-compatible 96-well plate. Decrosslinking was performed at 900C for 50 minutes followed by lysis in a buffer composed of 100 mM triethylammonium bicarbonate and 0.1% n-dodecyl-β-D-maltoside using adaptive focused acoustic (AFA) energetics in scanning mode for 5 minutes. After lysis, the proteins were digested using Trypsin/Lys-C mix using AFA energetics for 1 hour. The resulting peptides were acidified with trifluoroacetic acid and analyzed on a timsTOF Ultra 2 mass spectrometer coupled to a nanoElute 2 liquid chromatography system using a 15 cm (75 μm) IonOpticks column, in DDA-PASEF mode for a total run time of 34 minutes. The data were searched against the UniProt Human Reviewed protein database using MSFragger. Results: We utilized AFA energetics to extract and digest proteins from a limited number of cells isolated from FFPE tissue using LCM. This experiment was conducted with technical replicates to ensure accuracy and reliability. A total of 3,723 proteins were identified across the three replicates, with replicate 1 identifying 3,895 proteins, replicate 2 identifying 3,754 proteins, and replicate 3 identifying 3,519 proteins. In total, we identified 21,005 peptides, with replicate 1 identifying 22,896 peptides, replicate 2 identifying 22,377 peptides, and replicate 3 identifying 17,741 peptides from 100 colon cells. Notably, we observed a 70% overlap in the proteins identified across the three replicates, which highlights the reproducibility of the approach. Conclusion: The entire sample preparation process, after cell collection, was completed within a concise four-hour timeframe, demonstrating the efficiency of this methodology for analyzing protein profiles from small cell populations. Further, this approach is highly adaptable to automation and high-throughput applications. Its adaptability and scalability make it a promising strategy for spatial proteomics applications. Citation Format: Dong-Gi Mun, Kiran Mangalaparthi, Daigo Gunji, Amy J. French, Raghavendra Pasupuleti, Cristine Charlesworth, Sameer Vasantgadkar, DEB BHATTACHARYYA, Akhilesh Pandey. An AFA assisted workflow for mass-spectrometry based proteomics of FFPE samples [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 7657.

Abstract Artificial intelligence (AI)-scores estimated from digital mammograms predict future breast cancer (BC) risk. MIRAI is a deep learning BC risk model that provides a continuous 5-year risk of overall BC from four screening full field digital mammograms. Common germline genetic variation in the form of a polygenic risk score (BC-PRS) is associated with increased BC risk and may improve MIRAI’s 5-year risk prediction. Our goal was to develop an updated MIRAI 5-year risk model that incorporates the BC-PRS (MIRAI+PRS) and to evaluate its discriminatory accuracy and calibration for both overall and invasive BC compared to MIRAI alone. We developed the MIRAI+PRS model by multiplying each woman’s 5-year MIRAI risk estimate by their relative risk based on their BC-PRS relative to the population mean. We evaluated the models within the Mayo Clinic Biobank mammography cohort, comprised of 12,307 women without a prior history of BC; 176 invasive and 250 overall BC were diagnosed within 5 years. MIRAI was estimated on screening mammograms closest to enrollment but at least 6 months prior to BC. Discriminatory accuracy, assessed by C-statistic, was high and similar for MIRAI+PRS vs. MIRAI models, for overall BC and invasive BC (Table). Calibration assessed by observed to expected (O/E) ratios was also similar for MIRAI+PRS compared to MIRAI predictions for BC outcomes (Table), although there was improvement in decile-specific O/E ratios across the lowest risk deciles (<1.67%) for MIRAI+PRS. Calibration for invasive cancer was poor for MIRAI with or without PRS. In summary, the MIRAI+PRS risk model did not result in significant difference of discriminatory accuracy or overall calibration compared to the MIRAI model, but there was evidence for improved calibration for women with 5-year risk below 1.67%. For invasive BC, the model had poor calibration regardless of whether PRS was included, underscoring the importance of training AI models for BC outcomes that are associated with a clinical intervention. Citation Format: Christopher G. Scott, Peter Kraft, Imon Banerjee, Ramon Correa Medero, Aaron D. Norman, Fergus J. Couch, Karla Kerlikowske, Stacey J. Winham, Celine M. Vachon. Development and evaluation of a MIRAI 5-year risk model with a breast cancer polygenic risk score [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 2779.

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 RMC-6236 (daraxonrasib) is a novel multiselect RAS(ON) inhibitor under investigation for pancreatic ductal adenocarcinoma (PDAC) and other RAS-mutant cancers. This compound shares structural similarities with RMC-7977 and exhibits a conserved binding site and interaction pattern within the tri-complex formed between active RAS (RAS(ON)) proteins and cyclophilin A (CypA). Tumor Treating Fields (TTFields) are low-intensity, alternating electric fields that disrupt mitosis and have shown clinical benefit in solid tumors. The PANOVA-3 trial demonstrated that TTFields combined with gemcitabine plus nab-paclitaxel improved survival, pain control, and quality of life in locally advanced PDAC. Our previous work demonstrated that TTFields abrogate oncogenic KRAS pathway. We thus hypothesize a potential for increase in effectievness with the combination. In this study, the metastatic PDAC cell line AsPC-1 was treated with TTFields (150 kHz, 1.8 V/cm), RMC-6236 (15 nM; sub-IC50), or combination. A sub-IC50 concentration (15 nM) of RMC-6236 was selected based on MTS assay results, and subsequent experiments were performed at this dose. The MTS assay revealed that both TTFields and RMC-6236 independently reduced AsPC-1 cell viability, with a more pronounced reduction observed at 72 hours compared to 48 hours. RMC-6236 alone produced minimal effects at either 48 hours (85.82 ± 13.9%) or 72 hours (90.48 ± 15.4%) compared with control (100.0 ± 8.4%, 48 h; 100.0 ± 8.2%, 72 h). TTFields treatment significantly reduced viability to 74.42 ± 21.4% at 48 hours and 50.17 ± 26.5% at 72 hours. The combination treatment (TTFields + RMC-6236) further decreased viability to 63.8 ± 25.2% at 48 hours and 40.93 ± 18.1% at 72 hours, demonstrating synergistic cytotoxicity relative to monotherapy. Clonogenic assays were performed to evaluate cell survival fractions following treatment with RMC-6236, TTFields, and their combination. Cell migration was assessed using scratch assays, revealing that untreated cells exhibited a migration rate of 91.49 ± 0.85%, RMC-6236-treated cells showed 89.48 ± 1.3%, TTFields alone reduced migration to 61.33 ± 16.3%, and combination treatment markedly suppressed migration to 24.6 ± 22.13% . For every case we were compared with 72h cell migration rate with 0 h migration rate. These findings indicate that TTFields alone significantly impair cellular motility, while their combination with RMC-6236 results in a profound anti-migratory effect, substantially inhibiting wound closure. Additionally, western blot analysis was performed to assess changes in KRAS protein expression, a key PDAC biomarker. Overall, our results demonstrate that the combination of TTFields and RMC-6236 significantly inhibits PDAC cell growth, migration, and survival at sub-IC50 concentrations, suggesting a promising alternative therapeutic approach for PDAC management. Citation Format: Ishita Saha, Santanu Bhattacharya, Debabrata Mukhopadhyay, Hani M. Babiker. Synergistic antitumor activity of tumor-treating fields and multiselect-RAS (ON) inhibitor RMC-6236 in pancreatic ductal adenocarcinoma [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 4478.

Abstract Introduction: Clinical staging of multifocal non-small cell lung cancer (NSCLC) is facilitated by comparative genomic analysis of separate tumor nodules, but the role of genome-wide copy number profiling for this purpose is uncertain. Methods: We analyzed single nucleotide variants (SNVs), gene fusions, small copy number variants (gene amplifications and homozygous deletions) (sCNVs), and large-scale copy number variants (lCNVs) in a retrospective cohort of 34 patients with >1 lung cancer nodule tested on a previously validated tumor-only 515-gene next generation sequencing (NGS) panel (MayoComplete Solid Tumor Panel). For patients with <2 shared SNVs, a Bayesian approach was formulated to calculate the probability of shared versus independent events occurring in different tumor nodules in the same patient. The prevalence of specific lCNVs in NSCLC was derived from an independent dataset of 100 NSCLC peers tested by the same panel, and the prevalence of SNVs, fusions, and sCNVs in NSCLC was derived from publicly available data. Alterations unique to different tumor nodules and suspected germline alterations were excluded from the Bayesian analysis. Results: There were 54 total comparisons for 34 patients. Eleven of the patients (32.4%) had >=2 shared SNVs along with one or more shared lCNVs also identified in each patient. Eight patients (23.5%) had no shared SNVs, gene fusions, sCNVs, or lCNVs. Using the Bayesian approach for the remaining fifteen (44.1%) patients with at least one shared alteration (SNVs, sCNVs, and lCNVs), the probability of clonal relatedness ranged from 73% for a shared whole arm or whole chromosome lCNV to >99% for tumors with two or more shared alterations including multiple or complex lCNVs and SNVs. Whole chromosome or whole arm lCNVs were sometimes shared between tumor nodules with different driver SNVs. Conclusions: Incorporating lCNVs into comparative genomic analysis provides additional evidence of clonal relatedness in a subset of multifocal NSCLCs. However, differences in bioinformatics pipelines for calling lCNVs, concerns over the imprecision of genome-wide copy number profiling, and uncertainty regarding the temporal relationship between lCNVs and carcinogenesis (including somatic events possibly related to “field cancerization”) create challenges for integrating lCNVs into comparative genomic analysis with standard clinical workflows for tumor-only NGS on paraffin embedded tissue sections. Our simplified approach mitigates some of the uncertainty introduced by incorporating lCNVs into clonality determination. Citation Format: Claire Teigen, Ying-Chun Lo, Sounak Gupta, Stephanie Smoley, Beth Pitel, Hussam Al Kateb, Gopi Sivasankaran, Benjamin Kipp, Ande Rumilla, Gang Zheng, Kevin Halling, Katherine Geiersbach, . A Bayesian framework for evaluating somatic copy number variants into comparative genomic analysis of multifocal non-small cell lung 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 5423.

Abstract Approximately 288,000 men are diagnosed with prostate cancer (PCa) in the United States each year, with cases expected to double by 2040. While metastatic PCa can be treated with androgen deprivation therapy (ADT) and AR pathway inhibitors (ARPI), it inevitably develops into treatment resistant, lethal disease. The most common ARPI resistance mechanism in PCa is the expression of AR splice variant AR-V7 that lacks the ligand binding domain and is constitutively active. Patients with PCa expressing AR-V7 experience inferior overall survival. Speckle-type POZ protein (SPOP) is an adaptor protein of the Cullin3-based E3 ubiquitin ligase that facilitates both degradative and non-degradative polyubiquitination of targets such as AR. Loss-of-function SPOP mutations occur in approximately 10-15% of prostate cancers, and SPOP-mutant PCa is a unique subtype that has been shown to be exquisitely sensitive to ADT and ARPI treatment. This sensitivity is mediated in part by increased androgen availability via upregulation of hydroxysteroid 17-beta dehydrogenase 4 (HSD17B4) and related steroid synthesis pathways, reduced AR degradation, and enhanced AR cofactor activity. The remarkable efficacy of ARPI in ADT-resistant SPOP-mutant prostate cancer is not well understood. We hypothesized a novel mechanism by which wild-type SPOP promotes AR-V7-mediated resistance to ARPI in PCa. This mechanism may explain the exceptional ARPI sensitivity of SPOP-mutant PCa, distinct from its susceptibility to ADT. We further proposed that clinical SPOP inhibition may broaden this enhanced ARPI susceptibility to the 85-90% of PCa expressing wild-type SPOP. Our results show that SPOP drives ARPI resistance in prostate cancer that can be reversed by SPOP inhibitor. Bulk RNA sequencing showed that SPOP inhibitor targets spliceosome machinery and more importantly, abrogated AR-V7 expression both at transcriptional and protein level. Further investigation revealed that wild-type SPOP ubiquitinates spliceosome regulator SFPQ, promoting AR-V7 alternative splicing and ARPI resistance. While SPOP loss is pathogenic in PCa, leveraging the weakness conferred by SPOP mutation in the 85% of patients with SPOP-wild type provides an innovative strategy to sensitize ARPI resistant disease to standard of care treatment and save lives. Citation Format: Joanina K. Gicobi, Susanna M. Gregory, Nicole A. Becker, Elizabeth A. Bering, Jacob J. Orme.. SPOP drives AR-V7-mediated ARPI resistance in prostate 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 3904.