Prognostic Implications Research Articles

Abstract 4661: PTPRT mutations in gastric cancer: prognostic implications and functional domain analysis

Abstract Background: The PTPRT gene is recognized as a tumor suppressor in human cancers. However, prior investigations have predominantly concentrated on PTPRT mutations in colon cancer, leaving a dearth of information regarding gastric cancer. Existing studies have proposed that mutations in the PTPRT phosphatase domain are infrequent in common human cancers and have no bearing on prognosis. Conversely, our research on gastric cancer has produced conflicting outcomes, thus presenting an alternative perspective. Methods: This study included a cohort of 369 gastric cancer patients from TCGA database and 234 gastric cancer patients from real-world settings. The mutation rate of the PTPRT gene in gastric cancer patients and the mutations at different functional domain sites were analyzed using EXEL. Furthermore, the impact of mutations in different functional domain sites on survival was assessed using Kaplan-Meier survival curves. Results: The mutation rate of PTPRT was 10.84% (40/369) in the TCGA cohort and 11.54% (27/234) in the real-world cohort. The predominant mutations were observed in the Tyrosine-protein phosphatase domain, accounting for 52.50% (21/40) of total mutations in the TCGA cohort and 37.04% (10/27) in the real-world cohort. Additional mutations were also detected in domains such as Fibronectin type-III and HAM. Survival analysis of the TCGA cohort demonstrated that patients with PTPRT mutations had significantly higher survival rates compared to those with wild-type PTPRT (p=0.0197). Specifically, patients with mutations in the Tyrosine-protein phosphatase domain exhibited significantly improved survival outcomes compared to the remaining patients (p=0.0325). However, there were no significant differences in survival among patients with mutations in other functional domains (p>0.05). Conclusion: In summary, our study elucidated a mutation rate of approximately 10.84% (TCGA cohort) and 11.54% (real-world cohort) for the PTPRT gene in gastric cancer. The Tyrosine-protein phosphatase domain emerged as the primary hotspot for these mutations. Notably, patients harboring PTPRT mutations, particularly in the Tyrosine-protein phosphatase domain, exhibited significantly improved survival outcomes compared to those without mutations in this domain. These findings underscore the potential prognostic significance of PTPRT mutations in gastric cancer and emphasize the need for further investigations to explore their therapeutic implications. Citation Format: Jianbiao Xu, Lei Zou, Yun Shang, Tongmin Wang, Jianlin Song, Wenchuan Zhu, Yunjun Zeng, Jianxun Wang, Chuntao Li, Qinglan Zong, Ning Gao, Ding Zhang. PTPRT mutations in gastric cancer: prognostic implications and functional domain analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4661.

Abstract 2299: Risk assessment and development of a machine learning-based prediction model for survival in patients with medulloblastoma

Background: While clinical risk factors have long guided medulloblastoma (MB) treatment, the significance of genetic events in therapeutic strategies has not been fully elucidated. We aimed to explore whether revised molecular risk categories could inform management by analyzing long-term follow-up profiles, and concurrently to establish and validate an explainable prediction model for MB based on machine learning (ML) approaches, and to assess its prognostic implications in patients. Methods: A multicenter cohort of 729 patients from 2001 to 2023 was enrolled as a discovery cohort. Multivariate survival analyses assessed the associations between radiotherapy dose and survival by different revised molecular risk stratifications which integrated clinical and genetic events, followed by utilizing this cohort for training and internal validation of the model. The area under the receiver-operating-characteristic curve (AUROC) and decision curve analysis (DCA) were used to compare the predictive performance. The SHapley Additive exPlanation method was used to explain the final model. Results: Fifteen-year OS and DFS rates were 64.1% (95% CI, 57.9 to 71.0) and 59.1% (95% CI, 53.2 to 65.5) for clinical average-risk group (n = 554), and 55.9% (95% CI, 44.4 to 70.2) and 60.6% (95% CI, 51.9 to 70.7) for clinical high-risk group (n = 175), respectively. Within this revised high-risk stratification of SHH-MB, higher PF dose (≥ 55.8 Gy) combined with reduced CSI dose (23.4 ∼ < 30.6 Gy) was associated with better prognoses. In Gr.3-MB, MYC amplification (activation), as a high-risk marker of dissemination, indicated that CSI dose should be escalated to high intensity (36.0 Gy, p = 0.03) for survival benefits. In the revised model of Gr.4-MB, CDK6 activation well stratified the patients, with 10-year OS of 71.0% (95% CI, 54.0 to 93.5) for average-risk and 52.1% (95% CI, 39.5 to 68.8) for high-risk group. Furthermore, Clinical and molecular information from discovery and validation cohort was involved into model training. The Random survival forest method demonstrated the most optimal predictive efficacy among the six ML models, as evidenced by the training set AUROC of 0.73 (95% CI 0.68-0.78) for 5-year survival rates, 0.76 (0.70-0.82) for 10-year survival rates, and 0.86 (0.81-0.92) for 15-year survival rates in all patients. The final model could accurately predict survival rates in both internal and external validations, and has been deployed through a free, publicly available online software interface. Conclusion: The revised molecular risk stratification was suggested to potentially guide risk-adapted radiotherapy. Except that 36.0 Gy CSI dose is warranted for Gr.3-MB with MYC amplification, CSI reduction is recommended. Furthermore, this study, based on clinical and molecular information, constructs an available survival prediction tools for MB patients. Citation Format: Yu Su, Kaiwen Deng, Tao Jiang, Xiaoguang Qiu, Jiao Zhang, Hailong Liu, Yu Tian. Risk assessment and development of a machine learning-based prediction model for survival in patients with medulloblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2299.

Comprehensive analysis of mRNA expression of Piezo1 and Piezo2 in tumor samples and their prognostic implications in gastric cancer.

This study aims to investigate the expression pattern and clinical significance of Piezo1 and Piezo2 in various cancers, focusing on gastric cancer (GC). The study investigated the mRNA expression levels of Piezo1 and Piezo2 in tumor samples from different cancers using the BEST online database. The case-control studies about the relation between Piezo1 and Piezo2 and GC were retrieved from PubMed, Embase, Web of Science, and Cochrane Library. The retrieval time was from inception to October, 2023. The meta-analysis of the included literatures was conducted by the STATA 12.0 software. Additionally, the expression profiles of Piezo1 and Piezo2 in tumor and normal gastric tissues were analyzed, and their clinical drug relevance was assessed using the CPADS database. The research program has been registered with PROSPERO (CRD42023495836). The analysis demonstrated elevated mRNA expression of both Piezo1 and Piezo2 in the majority of tumor samples. Of particular note was the significant increase observed in GC tissue compared to normal tissue (all p < 0.05). Additionally, the meta-analysis revealed a meaningful correlation between high expression levels of Piezo1 and Piezo2 and poor prognosis in patients with GC (HR = 1.48, 95% CI = 1.27-1.69, p < 0.0001). This study identified a significant correlation between high levels of Piezo1 expression and the TNM phase (OR = 1.87, 95% CI = 1.21-2.91, p = 0.005). Furthermore, enhanced Piezo2 expression was observed to be positively correlated with survival status (OR = 2.12, 95% CI = 1.31-3.44, p = 0.002). Piezo1 (p = 0.028, R2 = 0.12) and Piezo2 (p = 0.049, R2 = 0.09) have been identified as potential therapeutic targets for GC treatment, according to drug sensitivity analyses. The findings of this study indicate that the expression levels of Piezo1 and Piezo2 have the potential to serve as diagnostic indicators or therapeutic targets for GC management. CRD42023495836 (PROSPERO).

Transformed to myelofibrosis is a risk factor for pulmonary hypertension in Philadelphia chromosome-negative myeloproliferative neoplasms.

Philadelphia chromosome-negative myeloproliferative neoplasms (Ph-MPNs) are a group of malignant clonal disorders originating from bone marrow hematopoietic stem cells, and pulmonary hypertension (PH) is a serious progressive disease often coexisting with Ph-MPNs, with a prevalence ranging from 5 to 50%. The aim of this study was to analyze the prevalence, clinical characteristics, and associated risk factors of PH in 130 patients with Ph-MPNs, to investigate the impact of PH on patients' prognosis, and to provide a reference for the clinical identification of adverse prognostic factors and early prevention and treatment of PH. One hundred and thirty patients with Ph-MPNs treated at Beijing Anzhen Hospital from January 1, 2020 to December 31, 2024 were included in the study. PH risk was assessed by echocardiography (ECHO), and tricuspid regurgitation velocity (TRV) > 2.8m/s was used as the criterion for high risk of PH. General information, hematological indices, biochemical indices, gene mutations and echocardiographic data of the patients were collected and statistically analyzed. The overall prevalence of PH among the 130 patients with Ph-MPNs was 15.4%. patients with PMF had the highest prevalence of PH (72.3%), which was significantly higher than that of patients with PV (9.9%) and ET (10.4%) (P < 0.05). patients in the PH high-risk group were older, had lower hemoglobin levels, and had a higher prevalence of splenomegaly and secondary myelofibrosis. the PH high-risk group Patients had a significantly higher mortality rate than the normal risk group (20% vs. 1.81%, P = 0.0004). Multifactorial Cox regression analysis showed that advanced age (HR = 1.029, P = 0.0332) and high risk of PH (HR = 1.034, P = 0.0432) were independent risk factors for patient survival.Logistic regression analysis showed that decreased hemoglobin (OR = 0.9657, P = 0.0062), splenomegaly (OR = 5.105, P = 0.0413) and secondary myelofibrosis (OR = 7.959, P = 0.0321) were independent risk factors for high risk of PH. This study revealed the prevalence of PH, risk factors, and their prognostic implications in patients with Ph-MPNs. It is suggested that regular monitoring of changes in relevant risk factors and vigilance and prevention of PH during the treatment of patients with Ph-MPNs are clinically important to improve the prognosis of patients.

Abstract 5915: Real world clinical characteristics of claudin 18.2 expression in patients with pancreatic adenocarcinoma

Abstract Background: Pancreatic cancer is a frequently fatal disease that is often diagnosed at a late stage associated with a poor prognosis and an increasing impact on cancer related mortality. Despite advances, chemotherapy remains the mainstem of therapeutic interventions for this disease and most of the currently identified molecular alterations are not currently targetable. Therefore, novel biomarkers and strategies are necessary to impact patient outcomes. Claudin-18.2 (CLDN18.2) is a splice variant of the Claudin 18 family and is a component of tight junctions, which seal the paracellular spaces of epithelial and endothelial cells. CLDN18.2 is frequently retained in malignant gastric tissue and overexpressed in pancreatic and gastroesophageal adenocarcinomas. CLDN18.2 overexpression at the message and protein levels has been observed in pre-clinical studies involving pancreatic cancer cell lines and in tumors from pancreatic cancer patients. The goal of this study was to obtain a deeper understanding of CLDN18.2 positivity and CLDN18.2 expression and the associated clinical prevalence, prognostic implications, patient clinical characteristics and relationship with other biomarkers in pancreatic ductal adenocarcinoma (PDAC) patient samples. Design: This was a single institution/reference laboratory based retrospective study including as many as 320 patients, in which CLDN18.2 positivity as defined by ≥ 75% of the tumor cells expressing moderate to strong membranous staining was examined. The goals were to evaluate CLDN18.2 in tumor samples by immunohistochemistry for prevalence in pancreatic adenocarcinoma patients. Claudin 18.2 expression was assessed by the Ventana (43-14A) Class I IVD that was purchased from Ventana/Roche Diagnostics. In addition to prevalence, CLDN18.2 was evaluated with respect to the clinicopathological features of patients, patient prognosis, adjusted for clinical covariables, response to treatments and relationship to patient demographics, tumor grade and disease status. Patient information has been obtained from electronic medical records and research database to establish clinical course (survival status, metastatic sites, etc.) along with patient demographics. Conclusions: CLDN18.2 is a novel potentially actionable biomarker in patients with advanced and metastatic pancreatic adenocarcinoma. This study provides important clinical information regarding CLDN18.2 expression in these patients that is important to consider when evaluating biomarkers in these patients. Funding for the study was provided by Astellas Pharma Global Development, Inc. Citation Format: Allison Kerper, Robert H. Getzenberg, Rondell P. Graham. Real world clinical characteristics of claudin 18.2 expression in patients with pancreatic adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5915.

Abstract 3403: The landscape of TP53 Y220C mutations in cancer

Abstract Background: TP53 encodes the critical tumor suppressor p53 and is the most commonly mutated gene in cancer. The TP53 Y220C hotspot mutation occurs in approximately 1% of solid tumors, reduces thermal stability of TP53, and impairs its DNA binding. TP53 Y220C creates a unique conformational change that is amenable to small molecules that can restore TP53 function. Several TP53 Y220C reactivators are in development. Despite emerging evidence that TP53 Y220C is a therapeutic target, the clinicopathologic features of patients with these tumors remain poorly understood. We describe the landscape of TP53 Y220C solid tumors at Memorial Sloan Kettering Cancer Center (MSK). Methods: This retrospective study included patients with TP53 Y220C solid tumors at MSK from July 2014 to March 2024. Patients were identified using paired tumor-normal next-generation sequencing (NGS) with MSK-IMPACT, a hybridization capture-based NGS assay that detects mutations, copy number alterations, and select structural rearrangements. Clinicopathologic data including sex, age and stage at diagnosis, race, and cancer type were automatically extracted from the medical record. Allele-specific copy number analysis was performed using FACETS, which infers purity and ploidy corrected integer DNA copy number calls from sequencing data. Genomic characteristics of TP53 Y220C solid tumors were compared to those with other TP53 missense mutations, truncating mutations, and complex alterations involving TP53, in addition to TP53 wild-type tumors. Results: 498 patients were identified with TP53 Y220C-mutated solid tumors. The majority were female (67%), White (71%), never smokers (52%), with a median age of 63 years-old (range 16-90, n=479). Approximately half (56%) had stage I-III disease at diagnosis, 33% stage IV, 11% unknown. The most common tumor types were ovarian (22%), pancreatic (11%), breast (11%), and non-small cell lung cancer (10%). TP53 Y220C prevalence was highest in high-grade serous ovarian cancer (4.5%). TP53 Y220C rarely co-occurred with other TP53 mutations (0.07%). The co-mutational profile, tumor mutational burden, copy number profile, and fraction of genome altered of TP53 Y220C-mutated tumors was similar to tumors with p53 non-Y220C mutations. Whole genome doubling (WGD) occurred in approximately half of TP53 altered cases, with similar frequencies for TP53 Y220C and TP53 non-Y220C mutated cancer. The frequency of WGD was higher in the altered groups compared to the TP53 wild-type group. Mutations were predominantly clonal, with subclonal alterations found in only 0.7% of cases. Conclusion: TP53 Y220C is a newly described clinically actionable target found across solid tumors at low frequency. The genomic features of TP53 Y220C-mutated cancers are similar to TP53 non-Y220C mutated cancers. Research is ongoing to determine the natural history of TP53 Y220C mutated cancers and whether this biomarker has unique predictive or prognostic implications. Citation Format: Alison M. Schram, Fatema Nagib, Mara Rao, Rogelio Velasco, Michael Gormally, Alexandra Waksmundzki, Henry Walch, Michael Berger, Nikolaus Schultz, Mark Donoghue, Walid Chatila. The landscape of TP53 Y220C mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3403.

Abstract 5013: The interplay of genomic aberrations, transcriptional states, and therapeutic responses in lung cancer

Lung cancer leads cancer-related deaths worldwide, with 2024 estimates of 234,580 new cases in the United States. This study explores the roles of tumor driver aberrations, epithelial transcriptional states, and microenvironment composition in lung cancer outcomes using proteogenomic data from 965 patients across the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and International Cancer Proteogenome Consortium (ICPC). We examined oncogenic alterations, epithelial and stromal cell type enrichment distributions, transcriptional modules activities, and drug sensitivities in lung adenocarcinoma (LUAD), squamous carcinoma (LUSC) and adenocarcinoma with no conventional drivers (NCD-LUAD).LUAD tumors displayed mutual exclusivity in RAS/Receptor Tyrosine Kinase (RTK) pathway aberrations, complemented by significant patterns of co-occurrence and exclusivity in tumor suppressor genes like TP53, STK11, RBM10, and CDKN2A. Our integrative analysis used gene expression from single-cell RNA-seq (scRNA) derived cell types reference and CPTAC bulk RNA/proteomic data for correlation-based estimation of epithelial/stromal cell type enrichment. We assembled scRNA references from 3 different studies that profiled normal tissues containing, 142 cell types from 38 tissue types, 20 stromal cell types from 11 tissues, and lastly exclusive lung cell types reference respectively. We found significant enrichment of AT2 and Club cells in LUAD tumors (p-value &amp;lt; 0.0001), in addition heterogeneity in epithelial cell type enrichment within each driver group. Patients enriched for AT2 and AT1 cells demonstrated better survival outcomes (p-value &amp;lt; 0.0001) while, secretory Goblet and Basal cells enrichment was associated with poor survival (p-value &amp;lt; 0.0001), underscoring the potential link between tumor transcriptional / differentiation states and prognostic implications. NCD-LUAD showed similar epithelial cell type enrichment patterns like LUADs with known drivers while LUSC tumors show predominant basal cell enrichment. Importantly we saw specific transcriptional modules (up: E2F1,MYBL2, down: NKX2-1, NFE2L2) and cell type enrichment differences in genome unstable (high copy number burden) tumors associated with poor survival. Finally, enrichment of a myofibroblast subtype associated with survival and immune infiltration status, warrants further investigation. Cell line drug sensitivity analysis showed that the RTK-altered group with poor response to targeted therapy was enriched with undetermined differentiation transcriptional status compared to more defined cell type enrichments in the good response group (p-value = 0.016). Our study underscores the importance of multi-dimensional integrative analysis approaches of molecular, cellular, and pharmacological data to understand and advance lung cancer biology, potential cell of origin, and therapeutic strategies. Citation Format: Hanbyul Cho, Noshad Hosseini, Yi Hsiao, Rahul Mannan, Chandan Kumar-Sinha, Yuping Zhang, Gabriel Cruz, Yamei Deng, Taiwan Cancer Moonshot Program and Clinical Proteomic Tumor Analysis Consortium, Natalie Clark, Shankha Satpathy, Gilbert S. Omenn, Yu-Ju Chen, Michael Gillette, Marcin Cieslik, Saravana Dhanasekaran, Alexey I. Nesvizhskii, Arul M. Chinnaiyan. The interplay of genomic aberrations, transcriptional states, and therapeutic responses in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5013.

Abstract 5103: Digital spatial profling with GeoMx to identify differential protein expression in Non-Hispanic/Latino and Hispanic/Latino Patients with metastatic hormone sensitive prostate cancer

Background: Emerging evidence suggests that there is a complex interplay between ethnicity and disease biology in metastatic hormone sensitive prostate cancer (mHSPC). We examined digital spatial profiling with GeoMx to evaluate differential protein expression between non-Hispanic/non-Latino (NHL) and Hispanic/Latino (HL) patients with mHSPC. Methods: Pre-treatment prostate biopsy specimens were obtained from patients on a clinical trial as part of an IRB approved protocol. The GeoMx Digital Spatial Profiler (DSP) was used to evaluate protein expression in selected regions of interest (ROIs). Differential expression analysis was performed using R (v 4.4.2). To determine significant differences in protein expression, a false discovery rate (FDR)-adjusted q-value was applied and a Log2Fold change (Log2FC) with a q-value &amp;lt; 0.01 was considered significantly differentially expressed. Results: A total of 8 patients (4 NHL and 4 HL) were enrolled at City of Hope including network sites and who had pre-treatment biopsy specimens that were available for digital spatial profiling analysis. We examined the Log2FC between protein expression in NHL and HL patients and filtered for q-values &amp;lt; 0.01. We identified multiple proteins that were significantly differentially expressed. Proteins that were more highly expressed (Log2FC &amp;gt; 1) in NHL patients included CD44, fibronection, and Ki-67. Proteins that were more moderately expressed (Log2FC &amp;lt; 1) in NHL patients included beta-2 microglobulin and. In contrast, HL patients were found to have higher expression in BCL6, CD68, CD80, Foxp3, PARP, and STING (Log2FC &amp;lt; 0). Conclusions: Digital spatial profiling with GeoMx reveals significant differences in protein expression in NHL vs. HL patients with mHSPC. Notably, these include markers of cancer stem cells (CD44), DNA damage pathway proteins (PARP), and both immunoregulatory (Foxp3) and immunostimulatory (STING) proteins. This may have both prognostic and therapeutic implications. Citation Format: Peter D. Zang, Joe Bonner, Alexander Chehrazi-Raffle, Lixin Yang, Natasha Garg, Swapnil Rajurkar, James Shen, Naveen Gupta, Amartej Merla, Sumanta Pal, Raju Pillai, Stephen Gruber, Tanya B. Dorff. Digital spatial profling with GeoMx to identify differential protein expression in Non-Hispanic/Latino and Hispanic/Latino Patients with metastatic hormone sensitive prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5103.

Abstract 5267: Unveiling associations between Duffy-null status and circulating chemokines among a diverse breast cancer patient cohort

Abstract Breast cancer (BC), the most diagnosed cancer and the leading cause of cancer-related mortality among women worldwide, includes triple-negative breast cancer (TNBC), its most aggressive subtype, which is disproportionately prevalent among individuals of West African ancestry. Our previous studies have demonstrated a correlation between West African ancestry-specific expression of the Duffy Antigen Receptor for Chemokines (DARC) and TNBC incidence. DARC regulates CC and CXC chemokines, maintaining homeostatic chemokine levels. However, the Duffy-null polymorphism (rs2814778), fixed in individuals of West African descent as an evolutionary defense against Plasmodium vivax malaria, results in the absence of DARC on erythrocytes. We aim to understand how this absence may influence chemokine regulation and contribute to ancestry-specific differences in the tumor microenvironment. We hypothesize that individuals with the Duffy-null genotype exhibit higher circulating chemokine levels than those with the DARC allele among BC cases. Since 2006, the International Center for the Study of Breast Cancer Subtypes (ICSBCS) has recruited patients from sites across the United States and Africa, collecting blood and tumor tissue samples. We utilized the Luminex multiplex assay to analyze plasma from the ICSBCS cohort, quantifying 50 biomarkers using the bead-based ELISA platform. Plate/batch effect normalization was done with MDimnNormn, and statistical tests were performed using JMP Pro 16. Genotyping for the Duffy-null allele (C) was conducted using TaqmanTM GTXpressTM Master Mix and specific probes on an Applied Biosystems 7500 Fast Real-Time PCR system. Our cohort included Duffy-null (CC, n = 183), Duffy-null carriers (CT, n = 40), and non-Duffy-null (TT, n = 294) individuals. Univariate analysis of chemokine levels revealed significant associations between Duffy-null status and the following biomarkers: MCP-1/CCL2 (p = 0.0116), Gro- b/CXCL2 (p = 0.0137), MIP1a/CCL3 (p = 0.0316), GCP2/CXCL6 (p = 0.0423), I-TAC/CXCL11 (p = 0.0008), BCA- 1/CXCL13 (p = 0.0252), MIP3b/CCL19 (p = 0.0023), 6Ckine/CCL21 (p = 0.0066), and MPIF1/CCL23 (p &amp;lt; 0.0001). These findings highlight significant associations between Duffy-null status and circulating chemokine levels, introducing novel BC biomarkers that characterize the relationship between Duffy-null status, BC, and West African ancestry. Moreover, these findings have important prognostic and therapeutic implications, particularly for addressing ancestry-specific factors in BC. Understanding these associations advances precision medicine efforts to address BC disparities affecting individuals of West African ancestry globally. Multivariate analyses to control for co-variates are ongoing to support these findings further. Citation Format: Stevens M. Patino, Kenya Bynes, Jason White, Danielle S. Doucette, Emma Guyonnet, Julie Sahler, Brian Stonaker, Avery August, Lisa Newman, Rachel Martini, Melissa Davis. Unveiling associations between Duffy-null status and circulating chemokines among a diverse breast cancer patient cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5267.

Abstract 3893: Enhanced detection of molecular subtypes in prostate cancer using saturation biopsy: Insights into tumor heterogeneity and racial disparities

Abstract Prostate cancer is characterized by remarkable molecular heterogeneity associated with disease progression and clinical outcomes. We have identified distinct molecular subtypes between CA and AA in biomarker expression associated with altered clinical outcomes. This study compares the effectiveness of standard 12-core biopsy and saturation biopsy in identifying molecular subtypes of prostate cancer and evaluating biomarker expression patterns across racial groups. We analyzed 104 cases that underwent saturation biopsies (median min, max 23 [14, 27], cores with cancer (median 11 [5, 25] and compared them with 130 cases with standard 12-core biopsies (median min, max 12 [12, 16]; cores with cancer median min, max 4 [1, 16] using ERG, ETV1, ETV4 and SPINK1 by combined multiplex IHC and RNA ISH. Saturation biopsy demonstrated superior detection of molecular subtypes, identifying higher rates of SPINK1- and ETV4-positive tumor foci than standard biopsy (p &amp;lt;.001). It also reduced the frequency of negative cases for all four biomarkers, indicating a higher prevalence of ETS gene fusions in prostate cancer (94%) than was reported previously. Caucasian American (CA) patients exhibited higher frequencies of ERG- and ETV1-positive tumor foci, while African American (AA) patients showed higher frequencies of SPINK1- and ETV4-positive foci and presented with higher Gleason Grade Groups at the time of biopsy. ERG positivity was associated with lower Gleason Grade Groups in both racial groups (CA p=.004; AA p &amp;lt;.001), and ETV1 positivity was linked to higher Gleason Grade Groups (CA p&amp;lt;.001; AA p&amp;lt;.001). These findings concord with our previous observations on the association of ETV1 And ETV4 with worse recurrence-free survival in CA and AA, respectively, underscoring significant racial variations in prostate cancer biology and the prognostic implications of biomarker expression. Saturation biopsy identified 16 distinct molecular subtypes with one or more than one ETS gene fusion, compared with 13 detected by standard 12-core biopsy. By uncovering a greater diversity of tumor subtypes, saturation biopsy highlights the extent of complex tumor heterogeneity and prostate cancer biology. It reveals fewer cases classified as ETS fusions compared with standard biopsies. This study demonstrates that saturation biopsy is a more effective diagnostic tool for detecting molecular subtypes and evaluating tumor heterogeneity in prostate cancer. The enhanced detection of subtype diversity and its ability to identify biomarker expression patterns associated with racial disparities underscores the potential of saturation biopsy in guiding precision oncology. These findings have profound implications for improving diagnostic accuracy, addressing racial inequality, and informing tailored treatment strategies for prostate cancer patients. Citation Format: Wei Zhao, Pin Li, Shannon Carskadon, Jessica Ryba, Hristina Trpevski, Vishnav Ramesh, Dhananjay Chitale, Firas Abdollah, Wooju Jeong, Craig Rogers, Daniel Isaac, Nilesh Gupta, Nallasivam Palanisamy. Enhanced detection of molecular subtypes in prostate cancer using saturation biopsy: Insights into tumor heterogeneity and racial disparities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3893.

Abstract 5780: Prognostic implications of prostatic gonadotropin releasing hormone receptor and androgen receptor expression in non-metastatic prostate adenocarcinoma

Abstract Background: Suppression of pituitary gonadotropin releasing hormone receptor (GnRHR) is the mainstay systemic therapy for prostate cancer. GnRHR is also expressed in the prostate and its correlation with direct anti-tumorigenic effects have been demonstrated. The inhibition of prostatic androgen receptor (AR) signaling is another potent therapeutic option. Despite their crucial role in prostate cancer proliferation, prognostic implications of prostatic GNRHR and AR expressions remain uncertain. To investigate the prognostic utility of GNRHR and AR expressions, a public prostate cancer transcriptomic profile and progression-free survival (PFS) data were reviewed. Methods: The Cancer Genome Atlas (TCGA) Pan-Cancer project batch-corrected treatment-naïve primary tumor mRNA expression profiles (RNA Seq V2 RSEM) of 324 non-metastatic (M0) prostate adenocarcinoma cases and their associated clinical data were retrieved from the cBioPortal. Log-rank Kaplan-Meier was used for survival analysis. The “low” vs. “high” expression cutoffs for GNRHR and AR were defined as the cohort’s lower 30th and 25th percentiles, respectively. Results: Prostatic GNRHR and AR mRNA expressions were heterogeneous, but apart from low AR expression in Gleason grade group (GGG) 1, levels were similar across age, anatomical T N stage or all other GGGs. For T2b-4 N0 disease, neither GNRHR nor AR expression alone was significantly associated with PFS. However, in a subgroup of patients with T2b-3a N0 disease with high GNRHR, those with concomitant low AR (n=21) were associated with superior 4-year PFS compared to high AR (n=119) with hazard ratio (HR) 0.28 (95% CI 0.080-0.976, p=0.046). The composition of GGG was similar between these groups. GNRHR or AR expression-dependent differential PFS was not observed in patients with T3b-4 N0 disease. For N1 disease, high GNRHR (n=38) was associated with superior 4-year PFS compared to low GNRHR (n=25) with HR 0.32 (95% CI 0.12-0.85, p=0.007), independent from AR expression levels. Conclusions: High GNRHR and low AR expression were associated with superior PFS in an anatomical stage-dependent manner. The superior PFS of low AR was more pronounced for localized T2b-3a N0 disease, while high GNRHR was most pronounced in regional node-positive N1 disease. Prostatic GNRHR and AR mRNA expression levels may allow tailored strategies in utilizing GnRH agonist/antagonist and AR signaling inhibitors in treating non-metastatic castrate-sensitive disease. Further investigation is warranted. Citation Format: Donghyun Kim. Prognostic implications of prostatic gonadotropin releasing hormone receptor and androgen receptor expression in non-metastatic prostate adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5780.

Abstract 2812: Prognostic implications of gastric cancer-specific tsRNA subtypes and functional validation

Abstract Background: Gastric cancer is a global malignant disease of the digestive tract. The marked heterogeneity of gastric cancer leads to prognostic and therapeutic challenges. tRNA-derived fragments (tsRNAs), a novel class of small non-coding RNAs closely associated with tumor progression, have an imperfect role in prognostic assessment and treatment of gastric cancer. We aimed to identify specific tsRNA isoforms associated with the tumor microenvironment of gastric cancer, establish a tsRNA-based prognostic model for gastric cancer, and screen-specific factors that may inhibit gastric cancer to guide prognosis and treatment. Methods: We performed matrix score analysis and consensus clustering analysis using tsRNA expression profiles from the tsRFun database and gastric cancer sample information from the TCGA database. Ten machine learning (Lasso, Enet, plsRcox, CoxBoost, StepCox, GBM, Ridge, RSF, survival-SVM, and SuperPC) were used to construct tsRNA-related prognostic models (TRS). In-house development of an R package called ‘GCtsRNAscore’ for calculating tsRNA score (RS) in gastric cancer patients. TMB and IMvigor210 cohorts were evaluated for immunotherapy efficacy. Pandora sequencing screened for gastric cancer-specific tsRNAs for functional validation in cellular, organoid, and animal models for functional validation. Results: We classified 80 gastric cancer-specific tsRNAs into three immunological subtypes, Stromal_L, Stromal_M, and Stromal_H, based on stromal cell infiltration analysis, with Stromal_L having the best prognosis. A multi-omics approach revealed significant differences in biological characteristics, CNVs, and mutation patterns among the subtypes (P &amp;lt; 0.05). The TCGA and GEO gastric cancer cohorts validated that TRS was the best prognostic model for tsRNA-associated tsRNAs in gastric cancer (P &amp;lt; 0.0001, AUC = 0.967). Gastric cancer patients were categorized into high-risk and low-risk based on their respective RS. High-risk patients responded well to axitinib, bexarotene, and dasatinib, while low-risk patients responded well to immunotherapy. In addition, we identified six subtype-specific tsRNAs, which were combined with Pandora sequencing to screen for the gastric cancer-specific suppressor Gly-tsRNA-4. Overexpression of Gly-tsRNA-4 was found to inhibit tumor growth in cellular, organoid, and animal experiments. Conclusion: In this study, tsRNA-related indicators accurately predicted the prognosis of gastric cancer and provided insight into the response of GC patients to therapeutic drugs. Gly-tsRNA-4 may act as a tumor suppressor to inhibit gastric cancer progression. The above study can help to explore new targets for gastric cancer treatment, but further comprehensive validation is needed. Citation Format: Yuan Liu, Xin Hu, Ye Tian, Wei Wang, Kexin Chen, Hongji Dai, Ben Liu, Fengju Song. Prognostic implications of gastric cancer-specific tsRNA subtypes and functional validation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2812.

Ultrasound evaluation of the optic nerve in patients with severe symptomatic hyponatremia.

Severe hyponatremia can precipitate significant neurological symptoms due to osmotic imbalances that induce intracranial hypertension (ICH). This study investigates the correlation between serum sodium levels and optic nerve sheath diameter (ONSD), measured by ultrasound, in patients presenting with symptomatic severe hyponatremia in the Emergency Department. Sixty-four patients with severe hyponatremia (Na+ < 125mmol/L) and neurological symptoms were enrolled and compared to a matched control group. Serial measurements of serum sodium and ONSD were obtained at 3, 12, and 24h post-correction. Results demonstrated a significant inverse correlation between sodium levels and ONSD, with ONSD decreasing as sodium levels were corrected (r = -0.71). ROC analysis confirmed ONSD as a sensitive and specific indicator of elevated intracranial pressure in these patients. This study highlights ultrasound ONSD measurement as a valuable non-invasive tool for monitoring ICH in severe hyponatremia, supporting its role in emergency settings to enhance diagnostic accuracy and therapeutic monitoring. Further research is needed to validate these findings and elucidate prognostic implications.

The impact of HER2-Low expression in salivary duct carcinoma: Clinicopathologic features, survival outcomes, and association with androgen receptor-targeted therapy.

The impact of HER2-Low expression in salivary duct carcinoma: Clinicopathologic features, survival outcomes, and association with androgen receptor-targeted therapy.

Gene expression profiling and pathway analysis in head and neck squamous cell carcinoma: focus on disulfidptosis

This study aimed to characterize the prognostic and therapeutic implications of disulfidptosis-related genes (DRGs) in head and neck squamous cell carcinoma (HNSCC). Using multi-omics data from the Cancer Genome Atlas (TCGA) (n = 500) and Gene Expression Omnibus (GEO) cohorts (n = 270), we performed unsupervised consensus clustering, functional enrichment, immune deconvolution, and survival analyses to identify DRG-driven molecular subtypes. A disulfidptosis score (DRGscore) was developed via principal component analysis of prognosis-associated genes and validated across immunotherapy cohorts. Key results revealed eight DRGs with prognostic significance (P < 0.05), including RAC1 and SLC7A11, which form interaction networks linked to redox regulation and immune evasion. Four DRGclusters stratified patients into subgroups with distinct survival outcomes (P = 0.002), immune profiles, and pathway activities. DRGscore effectively predicted survival (P < 0.001), immunotherapy response (anti-PD1/PD-L1 cohorts: P = 0.0099–0.018), and drug sensitivity (A443654 IC50 = 0.12 μM vs. AICAR = 8.3 μM). Mutational profiling identified TP53 and MUC16 as high-risk biomarkers. These findings establish DRGscore as a robust prognostic tool integrating disulfidptosis biology and immune contexture, enabling risk-stratified therapeutic strategies for HNSCC.

Comprehensive analysis of glycometabolism-related genes reveals PLOD2 as a prognostic biomarker and therapeutic target in gastric cancer

BackgroundGastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide, with limited therapeutic options and a poor prognosis, particularly in advanced stages. Glycometabolism, a hallmark of cancer, plays a critical role in tumor progression, immune evasion, and response to therapy. However, the specific roles of glycometabolism-related genes and their prognostic and therapeutic implications in GC remain inadequately understood.MethodsTranscriptomic and clinical data from GC patients were retrieved from TCGA and GEO databases. Glycometabolism-related genes were identified and analyzed using machine learning algorithms to construct a prognostic model. Functional assays, immune profiling, and pathway enrichment analyses were performed to explore the roles of these genes in tumor progression, immune-modulatory effects, and drug resistance. PLOD2, the gene with the highest prognostic significance, was further investigated to uncover its underlying regulatory mechanisms, roles in immune modulation, and contribution to therapeutic resistance.ResultsA glycometabolism-related prognostic model consisting of four genes (PLOD2, CHSY3, SLC2A3 and SLC5A1) was developed and validated, effectively stratifying GC patients into high- and low-risk subgroups with distinct survival outcomes. Among these, PLOD2 emerged as the most significant gene, exhibiting strong associations with tumor progression and poor survival. Functional analyses revealed that PLOD2 promotes glycolysis and tumor progression through activation of the PI3K/AKT/mTOR pathway. Immune profiling revealed that PLOD2 overexpression is associated with an immunosuppressive tumor microenvironment, characterized by increased M2 macrophage infiltration and reduced immune activity. Moreover, treatment with rapamycin, an mTOR inhibitor, significantly suppressed PLOD2-mediated proliferation and anchorage-independent growth in GC cells, highlighting the central role of the PI3K/AKT/mTOR pathway in PLOD2-driven oncogenic behaviors.ConclusionsThis study identifies PLOD2 as a key prognostic biomarker and therapeutic target in gastric cancer. As a central component in a glycometabolism-related model, PLOD2 promotes glycolysis, tumor progression, and immune evasion via the PI3K/AKT/mTOR pathway. The model effectively stratifies patient risk, offering both prognostic utility and therapeutic insight. Targeting PLOD2-mediated pathways may represent a promising strategy for precision therapy and improved clinical outcomes in gastric cancer.

Comprehensive pan-cancer analysis of PPP1R3G reveals its diagnostic, prognostic, and immunotherapeutic implications

BackgroundPPP1R3G, a regulatory subunit of protein phosphatase 1, plays a critical role in glycogen metabolism and has been implicated in various cancers. This study provides a comprehensive pan-cancer analysis of PPP1R3G, evaluating its expression, diagnostic and prognostic significance, and potential as a therapeutic target.MethodsWe performed an extensive pan-cancer analysis of PPP1R3G using several databases to assess its expression and investigate its correlations with clinical outcomes. Our investigation included assessing PPP1R3G’s impact on survival, its correlation with immune checkpoints and tumor stemness scores, and its prognostic significance. We also explored its relationship with immunomodulators, genomic profiles, and immunological characteristics, as well as its response to immunotherapy and involvement in various biological pathways.ResultsPPP1R3G expression varied significantly across different cancers and correlated with both diagnostic and prognostic outcomes. Moreover, PPP1R3G was significantly linked to immune checkpoints, immunomodulators, prognosis, immunoregulatory genes, tumor stemness, cellular function, and immune infiltration across numerous cancer types. Further analysis of PPP1R3G-related gene enrichment, mutation profiles, RNA modifications, and genomic heterogeneity revealed that missense mutations were the predominant alteration affecting PPP1R3G.ConclusionsOverall, the expression of PPP1R3G is closely associated with various cancers and may serve as a potential biomarker for cancer detection.

Can Longitudinal Biomarkers Guide Treatment Decisions? Time Will Tell.

Defining patterns of acquired resistance has important prognostic and therapeutic implications in patients with lung cancer. Longitudinal biomarker analysis has enhanced our understanding of tumor biology and treatment response. However, the role of temporally informed biomarkers in guiding clinical decisions, such as local therapy intervention, remains unproven. See related article by Mazzaschi et al., p. 1533.

Remdesivir associated with reduced mortality in hospitalized COVID-19 patients: treatment effectiveness using real-world data and natural language processing

BackgroundRemdesivir (RDV) was the first antiviral approved for mild–to–moderate COVID-19 and for those patients at risk for progression to severe disease after clinical trials supported its association with improved outcomes. Real-world evidence (RWE) generated by artificial intelligence techniques could potentially expedite the validation of new treatments in future health crises. We aimed to use natural language processing (NLP) and machine learning (ML) to assess the impact of RDV on COVID19-associated outcomes including time to discharge and in-hospital mortality.MethodsUsing EHRead®, an NLP technology including SNOMED-CT terminology that extracts unstructured clinical information from electronic health records (EHR), we retrospectively examined hospitalized COVID-19 patients with moderate-to-severe pneumonia in three Spanish hospitals between January 2021 and March 2022. Among RDV eligible patients, treated (RDV+) vs untreated (RDV‒) patients were compared after propensity score matching (PSM; 1:3.3 ratio) based on age, sex, Charlson comorbidity index, COVID-19 vaccination status, other COVID-19 treatment, hospital, and variant period. Cox proportional hazards models and Kaplan–Meier plots were used to assess statistical differences between groups.ResultsAmong 7,651,773 EHRs from 84,408 patients, 6,756 patients were detected with moderate-to-severe COVID-19 pneumonia during the study period. The study population was defined with 4,882 (72.3%) RDV eligible patients. The median age was 72 years and 57.3% were male. A total of 812 (16.6%) patients were classified as RDV+ and were matched to 2,703 RDV‒ patients (from a total of 4,070 RDV‒). After PSM, all covariates had an absolute mean standardized difference of less than 10%. The hazard ratio for in-hospital mortality at 28 days was 0.73 (95% confidence interval, CI, 0.56 to 0.96, p = 0.022) with RDV‒ as the reference group. Risk difference and risk ratio at 28 days was 2.7% and 0.76, respectively, both favoring the RDV+ group. No differences were found in length of hospital stay since RDV eligibility between groups.ConclusionsUsing NLP and ML we were able to generate RWE on the effectiveness of RDV in COVID-19 patients, confirming the potential of using this methodology to measure the effectiveness of treatments in pandemics. Our results show that using RDV in hospitalized patients with moderate-to-severe pneumonia is associated with significantly reduced inpatient mortality. Adherence to clinical guideline recommendations has prognostic implications and emerging technologies in identifying eligible patients for treatment and avoiding missed opportunities during public health crises are needed.

Myocardial flow reserve and resting contractility modulate the impact of contractile reserve in patients undergoing rubidum-82 positron emission tomography.

Although ejection fraction reserve (EFR) harbors prognostic value in patients undergoing positron emission tomography (PET) myocardial perfusion imaging (MPI), whether resting EF and myocardial flow reserve (MFR) modulate its prognostic value has not been studied. Consecutive patients undergoing stress/rest MPI using Rb-82 PET between 2019 and 2024 were included. The primary outcome was a composite of death and heart failure (HF) hospitalizations. Multivariable Andersen-Gill Cox models were used to assess the association of EFR with the primary outcome across the spectrum of resting EF and MFR. Restricted cubic splines were used to allow non-linearity. The 50th percentile of EFR served as the reference, with the 25th and 75th percentiles representing low and high EFR. The analysis included 7,737 consecutive patients among whom 463 deaths and 821 HF hospitalizations occurred over a median follow-up of 554 days. A low EFR was associated with a 25% greater risk of the primary outcome (HR: 1.25; 95% CI: 1.16 to 1.35). The association was stronger at higher values of resting EF (HR at EFs of 40% and 70%: 0.99 and 1.21 respectively) and MFR (HR at MFRs of 1 and 3: 1.06 and 1.27 respectively). Similarly, a high EFR carried a protective association that was more pronounced at a higher resting EF and MFR. The prognostic implications of contractile reserve, as measured by EFR, are most pronounced in patients with a higher resting EF and MFR.