Cancer Medicine

ABSTRACT BACKGROUND: Next-generation sequencing (NGS) and the development of targeted therapies have revolutionized cancer treatment. Molecular Tumour Boards (MTB) serve as collaborative platforms to integrate individual clinical and molecular information to make recommendations for personalized treatment. METHOD: This is a single-center, retrospective cohort study of patients presented at the Jewish General Hospital (JGH) MTB between July 2018 and Dec 2022. Clinical, molecular/pathologic data, MTB recommendations, and treatment details were collected. Treatment response was determined by radiological evaluation and physician clinical assessment. Fishers exact test and Log-rank tests were used to assess differences between groups. RESULTS: A total of 328 patients were presented to the MTB, including 23 with repeat presentations, resulting in 355 case reviews. Tumour-agnostic biomarkers were detected in 18.9% of cases, most commonly high tumour mutational burden (TMB, 9.5%) and HER2 amplification (4.3%). The most frequent actionable mutations were PIK3CA (19.8%) and PTEN (13.1%), often leading to recommendations for mTOR inhibitor therapy (26.0%). Overall, therapeutic recommendations were issued in 84.5% (300/355) of cases, and implemented in 43.3% (130/300). Patients who received MTB-recommended therapies achieved significantly higher objective response rates (ORR) (14.2% vs. 4.2%; P = 0.047), longer real-world progression-free survival (rwPFS) (5.6 vs. 3.5 months; HR 0.57; 95% CI 0.390 - 0.828; P = 0.003), and improved median overall survival (OS) (12.8 vs. 5.2 months; HR 0.60, 95% CI 0.452 - 0.793; P < 0.001) compared with those treated without MTB guidance. CONCLUSION: MTB is effective in identifying biomarker-matched therapeutic recommendations for advanced malignancies where limited standard-of-care treatment option is available.

Background: Stroke risk is increased in cancer patients, but variations by stroke type, cancer characteristics, and treatment timing remain incompletely characterized. We investigated stroke incidence after cancer diagnosis and temporal patterns of ischemic stroke around treatments. Methods: We conducted a retrospective multicenter cohort study using linked cancer registry and administrative data from 68 cancer hospitals in Osaka, Japan. Patients diagnosed between 2019 and 2022 were followed for up to 1 year. In diagnosis-based analyses, standardized incidence ratios (SIRs) compared stroke incidence with the general population. In treatment-based analyses, ischemic stroke incidence rates and adjusted incidence rate ratios (IRRs) were estimated from 14 days before through 365 days after cancer treatments (surgery, chemotherapy, or radiotherapy). Results: Among 190,471 patients, 1660 strokes occurred: 1296 (78.0%) ischemic strokes, 315 (19.0%) intracerebral hemorrhages, and 49 (3.0%) subarachnoid hemorrhages. In diagnosis-based analyses, the overall stroke SIR was 2.13 (95% CI, 2.03?2.24), with a 1.01% 1-year cumulative incidence. SIRs were 2.37 (95% CI, 2.24?2.50), 1.72 (95% CI, 1.53?1.92), and 1.22 (95% CI, 0.91?1.62) for ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage, respectively. SIRs peaked immediately after diagnosis and declined thereafter. Excess risk persisted through 180 days for ischemic stroke, 30 days for intracerebral hemorrhage, and 7 days for subarachnoid hemorrhage. In treatment-based analyses, ischemic stroke incidence increased transiently around treatments. After surgery, the adjusted IRR peaked during days 0?7 (12.27 [95% CI, 8.50?17.71]) and remained elevated through days 31?90 versus days 181?365. A postoperative increase was observed even in early-stage disease. For chemotherapy, incidence was relatively high before treatment initiation. Conclusions: Stroke risk after cancer diagnosis varied by stroke type, cancer characteristics, and time since diagnosis. Ischemic stroke incidence increased transiently around cancer treatment, including an early postoperative increase in patients with early-stage disease. These findings identify periods and patient groups that may warrant heightened clinical vigilance.

Background Hereditary cancers account for approximately 5% to 10% of all malignancies and are more frequently observed in individuals with early-onset disease or a significant family history of cancer. However, large pan-India datasets describing germline variant distributions across multiple cancer types remain limited. Methods We retrospectively analysed 23,070 individuals who underwent germline hereditary cancer testing at MedGenome Labs Ltd., Bangalore, India from 2016 to 2025. Clinical indication based major cancer sub-type groups were breast cancer (N=10486), ovarian cancer (N=3990), colorectal cancer (N=1275), prostate cancer (N=765), endometrial cancer (N=541) and asymptomatic individuals (N=2,775). Germline testing was conducted using clinically validated multigene next-generation sequencing (NGS) panels, with multiplex ligation-dependent probe amplification (MLPA) used for copy number variant detection in a subset of cases. Results The overall diagnostic yield of genetic testing was 23.85%, with the highest yields observed in colorectal (42%) and ovarian cancers (31.6%), followed by endometrial (22.6%), breast (20.2%) and prostate cancer (8.6%) formed the top 5 cancer types. In addition, there is an asymptomatic group where individuals with no symptoms reported but had a positive family history of cancer, where diagnostic rate was 18.9%. Among breast cancer patients diagnosed at [&le;]50 years of age, one of the National Comprehensive Cancer Network (NCCN) criteria for hereditary cancer testing, the diagnostic yield was 24.2%. Individuals with a positive family history had a significantly higher diagnostic rate (2.5% to 16%) compared to those without a positive family history across all cancer types. BRCA1 and BRCA2 were the most frequent genes with pathogenic variants in breast and ovarian cancers, while mismatch repair genes (MLH1, MSH2, MSH6) predominated in colorectal and endometrial cancers, and BRCA2 was the most frequently altered gene in prostate cancer. The well-known BRCA1 gene founder frameshift variant (c.68_69delAG; p.Glu23ValfsTer17) was identified in 358 individuals, representing the most frequent pathogenic variant in the cohort. Additional BRCA1 gene recurrent variants observed in the sample set includes a canonical splice-site variant (c.5074+1G>A;N=123), followed by a non-sense mutation (c.3607C>T;p.Arg1203Ter;N=44). A strong concordance between clinical classification and functional annotations was observed when compared with BRCA1 saturation mutagenesis findings. Reanalysis of variants of uncertain significance and undiagnosed cases improved the diagnostic yield by approximately about 5% average across major cancer types. A multivariate regression analysis showed a positive family history significantly contribute to improved diagnosis. Notably, early genetic testing correlated well with significantly contribute to improved diagnosis, suggestive for universal genetic testing over guideline-based testing. In addition, the regression analysis showed a decline in diagnostic yield with increasing age for all five major cancer types analysed, suggesting that the universal criteria for genetic testing is preferable for early detection. Among breast cancer cases with hormone receptor data, the triple-negative and ER+PR-HER2+ cases had a higher diagnostic rate compared to other subtypes of breast cancer. The MLPA-based CNV analysis further validated additional clinically relevant variants in a subset of the cohort. Conclusions To the best of our understanding, this retrospective study showcases the largest comprehensive characterization of the hereditary cancer genetics in India and South Asian region till date, demonstrating a substantial burden of inherited cancer susceptibility and distinct gene-cancer associations across major tumor types. These findings support the implementation of comprehensive multigene testing, periodic variant reinterpretation, and population-adapted hereditary cancer testing strategies to improve hereditary cancer risk assessment and advance precision oncology in underrepresented populations.

Background: Patient-reported measures (PRMs), including patient-reported outcome and experience measures, capture patients perspectives on their health status and healthcare experiences. In cancer genetics, PRMs have been used to assess genetic knowledge, psychosocial outcomes, and decision-making. However, patients must understand these measures to provide useful information, an ability which is influenced by general and health literacy levels. Readability guidelines recommend that patient-facing materials be written at or below a Grade 6 level. This study evaluated the readability of PRMs used in a cancer genetic testing context. Objective: To assess whether PRMs used in heritable cancer genetic testing meet recommended readability levels using validated indices. Methods: PRMs were identified from a recent systematic review of PRMs used in heritable cancer genetic testing, which reported 83 instruments across eight categories. English-language PRMs containing structured question items and response scales were eligible for extraction and converted into plain text for analysis. Readability was assessed using four validated indices: Flesch Kincaid Grading Level (FKGL), FORd, CAylor, and STicht (FORCAST) formula, Flesch Reading Ease Score (FRES), and Simple Measure of Gobbledygook (SMOG) via an automated readability software. Descriptive analysis and numerical comparison evaluated readability levels across PRM categories and against the recommended Grade 6 reading level. Results: Sixty-five PRMs met the eligibility criteria, with most, including validated instruments, exceeding the recommended Grade 6 reading level. Across the eight categories, genetics-specific PRMs required the highest readability levels, indicating higher readability demands. Conclusions: Most PRMs, particularly those specific to genetics, do not meet readability guidelines. This may limit their accessibility to individuals with limited general and health literacy. Development of PRMs specific to genetics should consider strategies to improve readability, such as plain-language approaches and involvement of individuals with limited general or health literacy. Keywords: readability, patient-reported measures, cancer, genetic testing, health literacy

Background: Testicular germ cell tumors (TGCTs) are the most common solid malignancies in young men. Despite high cure rates with cisplatin-based chemotherapy, resistance and long-term toxicities remain clinical challenges in TGCTs. Selinexor, an FDA-approved XPO1 inhibitor, has demonstrated anti-tumor activity in other cancers, but its potential in TGCTs remains unknown. Objective: We investigated the antitumor effects of selinexor in TGCT cell lines. Materials and methods: XPO1 RNA expression, protein abundance and localization were evaluated by immunohistochemistry in TGCT tissue microarrays and non-neoplastic testicular tissues, and by meta-analysis of publicly available gene-expression microarray datasets from normal testis, primary TGCT specimens as well as TGCT cell lines. Selinexor effects on cell viability, cell-cycle distribution and apoptosis were evaluated using XTT assay and flow cytometry. p53 and p21 expression and localization were analyzed by Western blotting and Immunofluorescence. Results: XPO1 expression was heterogeneous across normal testis, TGCT tissues and cell lines. Yet, selinexor reduced TGCT cell viability and induced G1 or G2/M cell-cycle arrest, apoptosis, increased total p53 and p21 protein levels, and their nuclear accumulation. Of note, control fibroblast exhibited limited sensitivity to selinexor. Discussion and conclusion: Our findings demonstrate that inhibition of XPO1 with selinexor might be potential therapeutic strategy for TGCTs.

Background: Small cell lung cancer (SCLC) is an aggressive, high-grade neuroendocrine carcinoma (hgNEC) with poor prognosis. Tarlatamab, a DLL3-targeting T cell engager was approved in 2024 for relapsed SCLC, with almost doubled overall survival benefit compared to chemotherapy. However, over half of patients do not respond to tarlatamab and others develop resistance within months. With multiple DLL3-targeting therapies in clinical trials, there are currently no validated predictive biomarkers to identify patients most likely to benefit from tarlatamab. In this study, we evaluate baseline DLL3 IHC level in patients as a predictive biomarker to tarlatamab clinical outcome. Methods: We assembled a cohort of 138 patients within IRB-approved MD Anderson GEMINI database (PA13-0589) with DLL3 expression by CLIA-validated immunohistochemistry (IHC), and those treated with tarlatamab from 7/1/2024 to 3/30/2026. Only those with DLL3 IHC results and treated with tarlatamab were included in this predictive biomarker study. All DLL3 levels were reported as percentage cells with cytoplasmic or surface DLL3 expression, including 24 with additional intensity score and H-score calculation. demographic, clinical, and outcome data were collected. Systemic and intracranial response data were assessed by RECIST and mRANO BM criteria respectively. Longitudinal liquid biopsies were taken from a subset of patients for circulating tumor DNA (ctDNA) and (Cytometry by Time-of-Flight) CyTOF analyses. Results: In the predictive biomarker cohort of 54 patients with SCLC treated with tarlatamab, Median DLL3% level in tarlatamab treated cohort was 75%. Median follow-up time was 9.9 months, median time on tarlatamab treatment (ToT) was 5.8 months. At the data cut-off, 61% (33 out of 54) patients were alive. Kaplan-Meier curve stratified by DLL3 % of <=75% vs. >75 showed significant longer ToT and a trend toward longer median OS (mOS). In DLL3>75% compared to DLL3 <=75%: mToT was 10.1 months vs. 2.9 months (p=0.036), mOS: not reached vs. 9.5 months (p= 0.066). Among 41 patients who completed one cycle of tarlatamab treatment and were eligible for systemic (extra-cranial) response per RECIST criteria; we observed partial response (PR) in 51% (21) patients, stable disease (SD) in 22% (9) patients; and progressive disease (PD) in 27% (11) patients. The median DLL3 % in those with PR vs. PD were 80% vs. 40% (p=0.006); median DLL3% comparing PR and SD were 80% vs. 60% (p=0.051). Among 35 patients evaluable for intracranial response, best objective response prior to any brain radiation were 5 (14%) CR,11(31%) PR, 8 (23%) SD and 11 (31%) PD. 9 received brain radiation (8 SRS, 1 WBRT) during tarlatamab to achieve better intracranial control while systemic control is maintained. DLL3% does not appear to be correlated with intracranial response. Longitudinal ctDNA and CyTOF analyses showed persistent ctDNA positivity, as well as increasing NEUROD1 subtype cells in circulating tumor cells in post-tarlatamab progression samples. We additionally profiled DLL3 expression by IHC in 138 patients with SCLC and found heterogenous DLL3 expression, with Median DLL3% of 70% across different biopsy sites. Conclusions: Our data suggests DLL3 expression in patients with SCLC is heterogeneous and not ubiquitous, with median DLL3 IHC of 70%. DLL3 IHC predicts objective response and long-term outcome with tarlatamab. In addition, dynamic monitoring of ctDNA level and CTCs by CyTOF are suggestive of development of tarlatamab resistance, however further studies with larger cohort of paired longitudinal samples are needed to validate the novel blood-based biomarkers. To our knowledge, this study is the first to validate DLL3 IHC as a predictive biomarker for tarlatamab in SCLC, which leads the way for optimizing treatment selection and combinatorial therapies for the subset of patients less likely to respond to tarlatamab.

Introduction: Small cell lung cancer (SCLC) patients have an ~8% 5-year survival; new therapies are urgently needed. Approximately 15% of SCLC patients have naturally-occurring low-titer antibodies against neuronal ELAVL proteins, associated with improved response to therapy and significantly improved survival. We previously determined that the anti-ELAVL4 response is triggered by isoaspartylation in the unstructured ELAVL4 N-terminal region. Methods: We used a Tp53fl/fl;Rb1fl/fl inducible SCLC mouse model to test whether 1) immunization with isoaspartylated Elavl4 (isoAsp-Elavl4) prior to SCLC induction improves survival in the absence of any other treatment, and 2) immunization with isoAsp-Elavl4 following completion of 3 rounds of cisplatin+etoposide therapy improves survival. Immunizations contained incomplete Freund's adjuvant with either a recombinant N-terminal fragment of Elavl4 (amino acids 1-117), incubated under isoaspartyl-inducing conditions, or phosphate-buffered saline (used as the negative control, since Elavl4 spontaneously isoaspartylates). Mice were monitored by blinded assessors until euthanasia was indicated. Results: IsoAsp-Elavl4-immunized animals all became immune responsive, and spontaneous anti-isoAsp-Elavl4 antibodies were observed in 7% of the control animals. Kaplan-Meier analyses revealed that pre-SCLC immunization with isoAsp-ELAVL4 in the absence of other treatments did not affect survival. In contrast, immunization of SCLC mice following chemotherapy significantly improved survival. Conclusions: An anti-isoAsp-ELAVL4 response can be actively induced in mice and significantly increases SCLC survival when given following chemotherapy. This indicates that the anti-isoAsp-ELAVL4 immune response can be leveraged to develop new therapies for SCLC patients.

Background: Objective assessment of tumor burden in patients with solid tumors remains inexact. Furthermore, while mutation-based liquid biopsies are specific, they are limited by tumor heterogeneity and the requirement for detectable clonal mutations. Cell-free DNA (cfDNA) concentration, a cost-effective substrate for mutation-focused liquid biopsy, has shown promise as a "molecular tumor burden" biomarker. Methods: We analyzed cfDNA concentration from 1000 unique cancer patients using standardized protocols. Demographics, AJCC stage, clinical anatomic tumor burden and oncologic outcome variables were collected. Associations were assessed with non-parametric tests. Multivariable linear regression and Cox proportional hazards models were used to identify independent predictors and survival associations. Results: CfDNA concentration varied broadly (median 6.25 ng/mL; range 0.5-1132.9). Anatomic tumor burden, including tumor number (rho=0.25, p<0.0001) and largest tumor diameter (rho=0.25, p<0.0001), correlated significantly with cfDNA, especially in stage IV disease. Primary tumor site influenced cfDNA levels, with liver/bile duct cancers having higher cfDNA than other sites (median 13.5 vs 6.1 ng/mL, p<0.0001). Multivariable analysis confirmed overall tumor burden and hepatic tumor location (primary or metastatic) as principal drivers of cfDNA. Critically, cfDNA concentration was an independent predictor of shorter PFS (p=0.001) and DSS (p<0.0001), demonstrating increased value in advanced disease settings, irrespective of treatment intent. Conclusions: CfDNA concentration is a robust, biologically integrated biomarker that provides an objective measure of total systemic tumor burden and prognosis in a large, pan-cancer cohort. By capturing disease activity irrespective of mutational status, it offers a valuable adjunct to targeted profiling, particularly in heterogeneous or advanced malignancies. Although these findings require prospective clinical validation, cfDNA concentration may eventually augment patient selection for aggressive versus palliative interventions, especially in advanced disease.

PurposeTo identify dietary patterns among adult childhood cancer survivors (CCSs), examine their determinants, and assess whether they differ according to cardiovascular disease (CVD) risk profiles. MethodsCCSs from the Swiss Childhood Cancer Survivor Study diagnosed before age 21 years (1976-2005), surviving [&ge;]5 years and aged [&ge;]18 years in 2017, completed a food frequency questionnaire (SCCSS-Nutrition). Factor and hierarchical cluster analyses of 52 food groups identified dietary patterns. We categorised CCSs as having CVD, CVD risk factors (obesity, hypertension, diabetes, high cholesterol), or being CVD risk-free. Multinomial logistic regression assessed associations between dietary patterns and CVD risk profiles. ResultsAmong 802 CCSs (median age: 35 years; IQR: 29-41; 50% male), we identified five dietary patterns: Mediterranean-inspired diet (22%), Western indulgence diet (38%), Western sweet & fatty diet (26%), restrained indulgence diet (9%), plant-based & alcohol-rich diet (6%). Male sex, younger age, German-speaking region, smoking, and living with others were associated with Western indulgence, Western sweet & fatty, and restrained indulgence diets. Higher Swiss socioeconomic position (Swiss-SEP) and education, and not having children, were associated with the plant-based & alcohol-rich diet, higher Swiss-SEP was also associated with the Western indulgence diet. No associations were observed between dietary patterns and CVD risk profiles. ConclusionsDietary patterns among adult CCSs were socially patterned and differed according to sociodemographic and lifestyle characteristics, but were not associated with CVD risk profiles. Implications for Cancer SurvivorsDietary counselling and broader lifestyle support should be considered as part of long-term survivorship care for CCSs.

Background: Oral mucositis is a clinically significant, potentially severe side effect of systemic chemotherapy in children with cancer. Understanding genetic predisposition to this side effect may assist in development of stratified prophylactic and treatment strategies. However, existing literature primarily focuses on children with haematological malignancies. Methods: We performed a candidate gene study of 101 children with solid tumours enrolled in the MARVEL-PIC study at the Royal Children's Hospital, Melbourne. Clinical data were extracted from the electronic medical record, with NCI-CTCAE v6.0 grade >2 oral mucositis defined as the primary outcome. Genetic variants previously associated with oral mucositis were analysed under an additive genetic model to identify significant associations. Exploratory gene-drug interactions were identified based on chemotherapy exposure. Results: 29 patients (28.7%) developed grade >2 oral mucositis. MTHFR A1298C (rs1801131) was associated with lower odds of grade >2 oral mucositis, lower peak mucositis grade, and lower odds of opioid use for oral mucositis. 25 exploratory gene-drug interaction signals were identified, including miR-1206 rs2114358 with methotrexate exposure and ABCB1 rs1045642 with anthracycline exposure. Conclusions: MTHFR A1298C (rs1801131) demonstrated a protective effect against chemotherapy-induced oral mucositis in our cohort of children with solid tumours. Larger, ancestry-informed studies are required to validate our findings.

Objectives Contemporary oncology has achieved remarkable advances in biomedical treatment while increasingly emphasizing patient-centered care. Nevertheless, routine oncology consultations must address multiple competing clinical priorities, potentially limiting opportunities for patients' experiences to become visible. To address this gap, we established a Dialogue-Based Outpatient Clinic, a complementary patient-directed consultation model embedded within routine oncology care. This study explored the dimensions of patients' experiences that became visible through this consultation model. Methods We conducted a qualitative study of 44 consecutive patients who attended a Dialogue-Based Outpatient Clinic embedded within routine oncology care between 2021 and 2023. Patients attended the clinic either on their own initiative or following a recommendation from a healthcare professional who recognized that they were struggling. Regardless of how they came to the clinic, patients independently determined the consultation agenda. Results Of the 44 patients, 13 (29.5%) sought biomedical information regarding diagnosis, treatment, or adverse effects, whereas 31 (70.5%) discussed concerns extending beyond biomedical issues. Reflexive thematic analysis of these 31 patients identified four interconnected themes: (1) making sense of a cancer diagnosis within one's own life; (2) negotiating treatment in relation to personal values and life priorities; (3) being treated for disease but not seen as a person; and (4) reconstructing life and identity through the cancer journey. Across all themes, patient-directed dialogue consistently revealed how patients understood cancer within the broader context of their lives rather than as an isolated biomedical condition. Conclusions Patient-directed dialogue within routine oncology care revealed dimensions of patients' experiences that may be less readily recognized in conventional consultations. A complementary consultation model that allows patients to determine the agenda may provide opportunities for these experiences to become clinically recognizable.

Chronic alcohol consumption is associated with increased breast cancer risk; however, the long-term effects of alcohol exposure on DNA damage response (DDR) signaling and therapeutic vulnerability in breast epithelial cells remain incompletely understood. In the present study, we established a chronic alcohol exposure model using immortalized human breast epithelial MCF-10A cells to investigate persistent alterations in DNA damage signaling and sensitivity to poly (ADP-ribose) polymerase (PARP) inhibition. MCF-10A cells that chronically exposed to 0.2% alcohol for 20 weeks and then withdrew alcohol treatment for 4 weeks still retained elevated {gamma}H2AX levels and sustained activation of ATM/ATR-associated DDR pathways. Chronic alcohol-exposed cells also exhibited increased sensitivity to the PARP inhibitors olaparib and veliparib, as demonstrated by reduced cell viability, decreased clonogenic survival, and enhanced apoptosis. Mechanistically, olaparib induced greater G2/M checkpoint activation and replication-associated DNA damage in chronic alcohol-exposed cells compared with control cells. In addition, chronic alcohol exposure increased PARP expression and enhanced activation of DDR signaling following PARP inhibition. These findings demonstrate that chronic alcohol exposure induces persistent DNA repair stress and sensitizes breast epithelial cells to PARP inhibition. Our study suggests that chronic alcohol-associated genomic stress may create potential vulnerability to PARP inhibition.

Background: Adjuvant therapy decision in early-stage node-negative breast cancer remains one of the most challenging problems in oncology. Although most patients in this population achieve favorable outcomes with endocrine therapy alone, a subset remains at risk of relapse and may benefit from chemotherapy. Accurate identification of high-risk and low-risk patients is therefore essential to prevent both undertreatment and overtreatment. Methods: In this study, machine learning models were assessed using MSK-IMPACT (n=645) and METABRIC (n=503) cohorts comprising node-negative stage I-II breast cancer patients. Three experimental settings were evaluated: training on MSK-IMPACT and testing on METABRIC, the reverse direction, and five-fold cross-validation on the combined cohort. Sensitivity analysis and data harmonization were applied to identify and mitigate cohort-specific bias. Survival analysis, SHapley Additive exPlanations (SHAP) interpretability, and ablation analyses were performed to validate clinical relevance and characterize feature contributions. Results: The combined cohort model achieved an area under the receiver operating characteristic curve (AUC) of 0.788{+/-}0.028 across five-fold cross-validation, while bidirectional cross-cohort validation yielded AUC of 0.741 when testing on MSK-IMPACT and AUC of 0.714 when testing on METABRIC. Survival validation on METABRIC out-of-fold predictions from the combined cohort model showed hazard ratios of 3.01 (95\% CI: 2.28-3.98) for disease-free survival and 2.35 (95\% CI: 1.79-3.09) for overall survival, consistent across Luminal A, Luminal B, and Triple-Negative subtypes. Conclusion: Validated across two geographically independent cohorts, the proposed model enables cost-effective, gene expression-free identification of patients at high-risk of distant relapse and may facilitate adjuvant chemotherapy decision-making in early-stage node-negative breast cancer.

Chimeric antigen receptor (CAR) T cells are patient-derived T cells engineered to recognize specific antigens on malignant cells, representing a major breakthrough in personalized cancer immunotherapy. While CAR-T cell therapy is an established treatment for relapsed or refractory hematologic malignancies, understanding the rationale and methodology behind its development is essential for training the next generation of oncology researchers. Here, we describe a novel, hands-on small-enrollment laboratory course designed to teach upper-level undergraduate and graduate students about immunotherapies and CAR-T cell technology by paralleling a typical bench-scale development process. Students isolated T cells from porcine peripheral blood mononuclear cells (PBMCs) via immunomagnetic selection, followed by flow cytometry to assess purity, viability, and yield. Students then used pre-engineered B7H3 CAR-T cells to perform co-culture assays with U87 glioblastoma cells to evaluate tumor cell killing efficacy. Cytotoxicity was qualitatively evaluated using immunofluorescence microscopy, while IFN-gamma release was quantified using Enzyme-linked Immunosorbent Assay (ELISA). Student performance was evaluated through electronic laboratory notebooks, discussion questions, a capstone project, and student-generated data. Our results demonstrate students high academic performance across assignments and the successful execution of complex laboratory workflows. Collectively, these findings establish the feasibility and implementation of a research-integrated curriculum providing foundational exposure to immuno-oncology research tools and CAR-T cell production techniques.

Purpose: Metastatic pancreatic ductal adenocarcinoma (PDAC) portends a poor prognosis. Prior studies have assessed the association of socioeconomic deprivation (SED) in PDAC often with large geographic areas. This study employed a causal framework to characterize neighborhood SED on treatment receipt and survival in metastatic PDAC. Methods: Using the incidence-based Florida Cancer Data System, metastatic PDAC patients diagnosed from 2007-2015 were identified. The Area Deprivation Index, a composite measure of SED that ranks neighborhoods from 1-100 (higher scores = higher deprivation), was used to assess receipt of systemic therapy and overall survival (OS). Exposures and covariates were assessed using descriptive statistics and a causal inference framework. Results: Overall, 9,574 patients met inclusion criteria. 46.6% of patients received systemic therapy, ranging 39.4% to 54% in the highest and lowest SED quartiles, respectively. After adjustment, the lowest quartile had increased odds of systemic therapy relative to the highest (OR 1.93; 95% CI 1.70-2.18). Median OS was 3.8 months for the lowest quartile and 2.4 months for the highest (p = 0.01). Patients in the highest quartile had an estimated 32% higher hazard of death than the lowest (HR 1.32, 95% bootstrap CI 1.20-1.40). Conclusion: In an incidence-based statewide cohort, most patients did not receive treatment for metastatic PDAC and median OS was poor-2.9 months. Using a causal inference framework, higher SED led to lower rates of systemic therapy receipt and worse overall survival in metastatic PDAC. Future research should focus on the mechanisms that shape these findings.

Objective: The purpose of this study is to determine how family history of cancer, genetic mutations, presenting symptoms, and comorbidity burden collectively influence cancer outcomes in patients with epithelial ovarian cancer. Methods: A retrospective analysis was conducted on all patients with epithelial ovarian cancer treated at the University of Missouri and Ellis Fischel Cancer Center between 2008 and 2024. Patient charts were reviewed for histological subtypes, stage of cancer, status of metastasis, CA-125 values, presenting symptoms, comorbidities, family history of cancer, genetic mutations, and survival outcome. Cox regression and association analyses were performed. Results: In this cohort of patients, comorbidities and genetic mutations did not influence ovarian cancer survival. While histological subtypes, CA-125 levels, and cancer stage remained strongly associated with survival. Significant associations were observed between certain presenting symptoms and cancer histological subtype, a family history of breast cancer, stage of cancer at diagnosis, the status of metastasis, and CA-125 levels. Conclusion: Comorbidities and genetic mutations were not significantly associated with ovarian cancer survival. Presenting symptoms were associated with several clinical and pathological variables linked to ovarian cancer diagnosis.

Background: Cancer patients face a significantly elevated risk of severe COVID-19 outcomes. Although vaccination is a cornerstone of prevention, data on vaccination coverage and association with survival among Russian cancer patients remain scarce. We assessed COVID-19 vaccination coverage and its association with overall survival in a population-based cohort of cancer patients in Northwest Russia. Methods: This retrospective registry-based cohort study integrated data from the Population-Based Cancer Registry (PBCR) of the Arkhangelsk Region and the Nenets Autonomous Okrug, regional vaccination records, and an artificial intelligence (AI)-based analysis of chest computed tomography (CT) scans. The cohort consisted of 1,144 cancer patients who underwent CT between August 2020 and April 2021. Vaccination status was ascertained via data linkage. Overall survival (OS) was compared between vaccinated and unvaccinated patients using Kaplan-Meier analysis and multivariable Cox proportional hazards regression, adjusted for demographic, clinical, and AI-derived CT biomarkers. To mitigate immortal time bias, the primary analysis used a landmark approach restricted to patients alive on March1, 2021 (N=1,136). A sensitivity analysis used a November1, 2021 landmark (N=894). Vaccination status was defined as receipt of at least one dose before the landmark date. Results: Only 6.6% (n=76) of patients received at least one dose of a COVID-19 vaccine (Sputnik V or Sputnik Light). Vaccinated patients were more likely to have earlier-stage cancer and were less likely to be receiving active treatment. In the primary landmark analysis, vaccination was associated with a significantly higher 3-year OS (80.3% vs. 45.7%, p<0.001). In multivariable analysis, vaccination was independently associated with a 60% lower hazard of all-cause mortality (adjusted HR 0.40, 95% CI 0.25-0.64). AI-detected COVID-19 pneumonia on baseline CT was also an independent predictor of poorer survival (adjusted HR 1.32, 95% CI 1.09-1.59). In the sensitivity analysis (November1, 2021 landmark), the adjusted HR for vaccination was 0.56 (95% CI 0.34-0.92), showing a consistent but attenuated association. Conclusion: This study reveals critically low COVID-19 vaccination coverage among cancer patients in Northwest Russia. Nevertheless, vaccination was strongly associated with a substantial survival benefit, underscoring its importance as a potentially lifesaving intervention for this vulnerable population.

Deep learning (DL) applied to haematoxylin and eosin (H&E)-stained pathology images can predict microsatellite instability (MSI) in gastric cancer (GC). We evaluated its diagnostic accuracy and discriminative performance. PubMed, Embase, Cochrane Library and Web of Science were searched for studies applying DL to H&E images for MSI prediction in GC. The protocol was prospectively registered in PROSPERO (CRD420261503140). Risk of bias was assessed with QUADAS-2. Pooled sensitivity and specificity were estimated with a bivariate random-effects model, with subgroup analyses by validation strategy and data source; slide-level areas under the curve (AUCs) were pooled after logit transformation. Prespecified scenario analyses assessed robustness. Ten studies were included; seven independent datasets from six studies entered the primary synthesis. Pooled sensitivity, specificity and summary receiver operating characteristic AUC were 0.78 (95% CI 0.63-0.88), 0.85 (95% CI 0.77-0.90) and 0.89 (95% CI 0.86-0.91); nine studies contributed to the secondary AUC synthesis (pooled AUC 0.85, 95% CI 0.80-0.89). Hospital-derived cohorts showed numerically higher sensitivity (0.86) and diagnostic odds ratio (39.8) than TCGA-derived cohorts (0.71 and 11.5), but subgroup differences were limited by the small number of studies and substantial heterogeneity. DL models show good diagnostic accuracy for MSI prediction in GC, but clinical utility still requires confirmation in standardised multicentre, independent external and prospective studies.

Ovarian cancer stands out as one of the most lethal gynecological cancers among women in the United States. While patients with ovarian cancer often show positive responses to treatment, it is common for the cancer to reappear and develop resistance to treatment, so it is important to explore and create novel combinations to increase patient survival rates. ATRi (Ataxia telangiectasia and Rad3-related inhibitors) and ONC201 monotherapies have shown efficacy in ovarian cancer in preclinical models. We hypothesized that combining ATRi with ONC201 would enhance this efficacy. ONC201 induces apoptosis through the TRAIL-pathway following activation of the integrated stress response and inactivation of Akt which is upregulated in ovarian cancer. Six human ovarian cancer cell lines were treated alone and with the novel drug combination of ceralasertib (ATRi) and ONC201. We found an IC50 range of 0.88-20.16 microM for ONC201 and IC50 range of 0.55-54.75 microM for ceralasertib. The combination of ONC201 plus ceralasertib resulted in PARP cleavage consistent with apoptosis along with reduction in Bcl-XL, Xiap and p-Akt expression after 72 hours of treatment. Cytokine profiling showed a decrease in markers of inflammation and tumor progression. Our data provide evidence of synergy from the combination of ATRi ceralasertib and ONC201 against Ovarian cancer cells that merits further investigation including clinical translation.

Purpose: Metastatic pheochromocytoma and paraganglioma (PPGL) are rare neuroendocrine malignancies with limited systemic treatment options. Although inhibition of vascular endothelial growth factor (VEGF) signaling has demonstrated clinical benefit in metastatic PPGL, prospective data evaluating selective VEGF receptor inhibition remain limited. Axitinib is a potent and selective inhibitor of VEGFR-1, -2, and -3 with established activity in several solid tumors. We evaluated the efficacy and safety of axitinib in patients with progressive metastatic PPGL. Methods: Patients with progressive metastatic or unresectable PPGL were enrolled in a prospective, open-label, single-arm, phase II study (NCT03839498). Eligible patients had measurable disease according to RECIST version 1.1 and no prior treatment with a tyrosine kinase inhibitor. Axitinib was administered orally at an initial dose of 5 mg twice daily with protocol-defined dose modifications based on tolerability. The primary endpoints were objective response rate (ORR) and progression-free survival (PFS). Safety was assessed using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE). Results: Nineteen patients were enrolled, and 17 received study treatment. A confirmed partial response was achieved in 35.3% of treated patients. Median progression-free survival was 7.9 months (95% CI, 6.1-16.8 months), median duration of response was 7.4 months, median duration of treatment was 9.5 months, and median overall survival was 29 months. Hypertension, the most common treatment-related adverse event, occurring in 79% of patients, was effectively managed with antihypertensive therapy and dose modification. Other common treatment-related adverse events included fatigue, diarrhea, oral mucositis, and palmar-plantar erythrodysesthesia. No patient permanently discontinued treatment because of treatment-related toxicity. Conclusions: In patients with progressive metastatic PPGL, single-agent axitinib demonstrated clinically meaningful antitumor activity with a manageable safety profile. The observed efficacy compares favorably with sunitinib in this rare disease. The ability to maintain treatment despite predictable VEGF-associated toxicities suggests that axitinib represents a viable therapeutic option for patients with metastatic PPGL.