Artificial intelligence (AI) has the potential of reshaping GI oncology by enabling more nuanced interpretation of complex clinical, imaging, and molecular data, while supporting more timely and patient-centered decisions. This article synthesizes perspectives across the GI cancer continuum, beginning with a framework for context-aware AI that emphasizes metadata, multimodal integration, and lifecycle quality and safety as foundations for trustworthy tools that clarify, rather than conceal, uncertainty. Next, AI in endoscopy is highlighted as an example in clinic practice, focusing on computer-aided detection and diagnosis systems that not only increase adenoma detection rates but also raise questions about surveillance burden, real-world effectiveness, and the balance between skill enhancement and potential deskilling of endoscopists. Another section explores how AI can help GI oncologists design, prioritize, and implement highly innovative clinical trials-particularly multi-omic and imaging-driven approaches-while envisioning a future in which far more patients participate in trials that align with their goals and values. The final section reviews emerging AI-enabled clinical trial matching pipelines, including large language model-based retrieval and prescreening tools that operate on real-world electronic health record and protocol data, and discusses challenges related to bias, privacy, explainability, and workflow integration. Together, these contributions argue that the greatest impact of AI in GI oncology will come from deliberately aligning technical capabilities with highly relevant patient-centered clinical questions, ethical governance, and implementation strategies that expand access to trials and improve outcomes for patients with GI malignancies.

The purpose of this correspondence is to expand upon the recent review article by Noiret et al. addressing management of locally advanced rectal cancer (LARC) and proposing anatomically guided treatment strategies. While tumor location influences surgical complexity and functional outcomes, we caution against an overly anatomy centric framework that may oversimplify treatment selection and underemphasize patient preferences and biological determinants of response. Current evidence does not support the assertion that chemotherapy followed by surgery provides superior long-term functional outcomes compared with total neoadjuvant therapy (TNT) with organ preservation (OP). Contemporary management of LARC includes multiple curative-intent strategies, each associated with distinct tradeoffs in oncologic control, toxicity, and quality of life. In particular, modern radiotherapy techniques and OP strategies have demonstrated favorable response rates, functional outcomes, and quality of life compared with radical surgery. We argue that future treatment paradigms should move beyond anatomy alone and prioritize biologic risk stratification, response adaptive treatment, and incorporation of multi-omic biomarkers. Ultimately, treatment decisions should integrate patient preferences, oncologic risk, functional outcomes, and evolving biologic understanding to optimize individualized care for patients with LARC.

Importance:The ideal duration of androgen deprivation therapy (ADT) for treating localized prostate cancer is unknown due to variable adherence and treatment durations tested in clinical trials. Objective:To determine the ideal duration of ADT for patients with prostate cancer treated with radiotherapy. Data Sources:This individual patient data meta-analysis of 13 randomized phase 3 clinical trials evaluated the use of radiotherapy alone or with ADT. It included patients with a median follow-up of 11.3 (IQR, 9.5-14.5) years and ADT duration of 0 to 36 months. Most patients (7392 [72%]) included had National Comprehensive Cancer Network high-risk or very high-risk disease. Study Selection:For this meta-analysis, a systematic literature search from 1980 to 2020 was performed in trial registries (Cochrane Central Register of Controlled Trials and ClinicalTrials.gov), MEDLINE (1966-2020), Embase (1982-2020), Web of Science, and Scopus to identify trials. Data Extraction and Synthesis:Intention-to-treat and as-treated analyses were performed. The number needed to treat to prevent 1 distant metastasis at 10 years was calculated based on prognostic risk group. The analyses were conducted from January 5 to August 15, 2023. Main Outcomes and Measures:The primary end point for this study was overall survival, defined as time to death or last follow-up from randomization. Secondary end points included biochemical recurrence, distant metastasis (DM), prostate cancer-specific mortality, and other-cause mortality. Results:The median (IQR) age among the 10 266 male patients was 70 (65-74) years. Longer durations of ADT were associated with nonlinear improvement in relative benefits of DM, prostate cancer-specific mortality, and overall survival, with reduced estimated benefits beyond 9 to 12 months of ADT based on the end point. There was a near-linear increase in other-cause mortality associated with long-term ADT use (hazard ratio, 1.28; 95% CI, 1.09-1.50; P = .002 for 28 vs 0 months of ADT). The optimal ADT duration based on 10-year DM was 0, 6, 12 months, and undefined for patients with 1 intermediate-risk factor, 2 or more intermediate-risk factors, and National Comprehensive Cancer Network high-risk and very high-risk disease, respectively. Conclusions and Relevance:The results of this meta-analysis suggest that, for men with localized prostate cancer treated with definitive radiotherapy and ADT, there are relative and absolute benefits from increasing durations of ADT that help provide individualized risk estimates.

Correlations between pre- and posttreatment MRI tumor volumes

Therapies targeting the RAF-MEK-ERK pathway are generally considered to have limited efficacy in KRAS-mutant cancers. However, specific KRAS mutants exhibit distinct behaviors. Notably, KRASG12R pancreatic ductal adenocarcinoma (PDAC) tumors have shown sensitivity to MEK inhibitors (MEKi) in combination with autophagy inhibitors, but a better understanding of the underlying mechanisms is needed to optimize this treatment strategy. Using a systems-level approach, we uncovered a mechanistic explanation for this phenomenon. Due to distinct biophysical properties, KRASG12R had an impaired ability to activate wild-type HRAS and NRAS (WT-RAS) compared with other KRAS mutants, such as KRASG12D. This reduced activation stemmed from the weaker interaction between KRASG12R and guanine exchange factors (SOS), as well as the tumor suppressor neurofibromin (NF1), crucial in regulating WT-RAS activity. The impaired ability to activate WT-RAS led to weaker holistic MAPK signaling in KRASG12R-driven tumors, which conferred increased sensitivity to MEKi. To substantiate the preclinical findings, the utility of MEKi in combination with the autophagy inhibitor hydroxychloroquine was analyzed in patients with KRASG12R-mutated metastatic PDAC. Five of the eight (62.5%) patients treated in first- or second-line settings had a progression-free survival exceeding 6 months. Three patients had impressive disease control: two had stable disease of 11 and 22.7 months, and one achieved a partial response with an 83% decrease in tumor size that lasted for 8.9 months. Overall, this work highlights how systems-based approaches in precision medicine can uncover mechanistic insights to guide the identification of patients with PDAC most likely to benefit from tailored therapeutic strategies. SIGNIFICANCE:The unique sensitivity of KRASG12R-mutant cancers to MEK inhibitors offers a critical advancement in understanding MAPK signaling and paving the way for precision-targeted therapies in previously untreatable contexts. See related commentary by Tiriac and Engle, p. 1817 See related article by Burge et al., p. 1854 See related article by Burge et al., p. 1868.

Background:Prostate cancer (PCa) is the most prevalent male cancer in the U.S., accounting for 29% of new cancer diagnoses. Multiparametric MRI (MP-MRI), including T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps, is an effective tool for detecting PCa; however, accuracy varies, and false-positives may lead to unnecessary biopsies or overtreatment. Radio-pathomic maps (RPMs), derived from MP-MRI and machine learning, have been advantageous in differentiating clinically significant PCa. This study tested whether RPMs of tissue density and histo-morphometric features could better predict cancer presence than conventional MR imaging. Materials and Methods:MP-MRI from 236 patients prospectively recruited between 2014 and 2023 with confirmed PCa were analyzed. Whole-mount prostate sections sliced to match the MRI were processed, digitized, and Gleason-pattern annotated by a GU pathologist. Automated algorithms identified glands and calculated quantitative histo-morphometric features, which were mapped across whole slide images. Slides were nonlinearly aligned to each patient's T2WI using in-house software, enabling direct comparison of slides, features, and annotations in MR-space. A multi-step prediction model was trained using a 2/3 - 1/3 train/test split to predict histo-morphometric features using 5×5 voxel tiles from T2WI and ADC. These feature maps were then used generate tumor probability maps. Results:Histological feature models produced RMSE values approximately within one standard deviation of the ground truth's variability, indicating acceptable performance. The best RPM, using histological density features, achieved an accuracy of ~80%. Visual inspection of RPMs showed good concordance to high-grade cancer annotations. Conclusion:This study demonstrates that the use of MRI intensities can predict complex histo-morphometric features and delineate regions of PCa non-invasively. Future research is warranted to determine the clinical benefit of using RPMs in treatment guidance.

TPS3650 Background: A total neoadjuvant therapy (TNT) approach improves compliance with chemotherapy and increases rates of tumor response compared to neoadjuvant chemoradiation (CRT) alone in those with locally advanced rectal cancer. Recent data indicate that optimal sequencing of TNT involves consolidation (rather than induction) chemotherapy to improve complete response rates. The use of FOLFIRINOX has shown to improve response and outcomes compared to CRT and surgery alone. Data have also shown that patients with clinical complete response (cCR) after TNT may be managed with a watch and wait approach (WW) instead of preemptive total mesorectal resection (TME). However, the optimal consolidation chemotherapy regimen to improve cCR rates has not been established, and a randomized clinical trial has not robustly evaluated cCR as a primary endpoint. We designed this NCI-sponsored study of chemotherapy intensification to address this and to increase cCR rates, provide opportunity for organ preservation, and survival outcomes. Methods: In this multigroup randomized, seamless phase II/III trial (1:1), up to 760 patients with LARC, T4N0, any T with node positive disease (any T, N+) or T3N0 requiring abdominoperineal resection or coloanal anastomosis and distal margin within 12 cm of anal verge will be enrolled. Stratification factors include tumor stage (T4 vs T1-3), nodal stage (N+ vs N0) and distance from anal verge (0–4; 4–8; 8–12 cm). Patients will be randomized to receive neoadjuvant long-course chemoradiation (LCRT) followed by consolidation doublet (mFOLFOX6 or CAPOX (control arm)) or triplet chemotherapy (FOLFIRINOX (experimental arm)) for 3–4 months. LCRT in both arms involve 4500 cGy in 25 fractions over 5 weeks +900 cGy boost in 5 fractions with a fluoropyrimidine. Patients will undergo assessment 8–12 (±4) weeks post-TNT completion. The primary endpoint for the phase II portion will compare cCR between treatment arms. A total number of 312 patients (156 per arm) will provide statistical power of 90.5% to detect a 17% increase in cCR rate, at a one-sided alpha = 0.048. The primary endpoint for the phase III portion will compare disease-free survival (DFS) between arms. A total of 285 DFS events will provide 85% power to detect an effect size of hazard ratio 0.70 at a one-sided alpha of 0.025, requiring enrollment of 760 patients (380 per arm). Secondary objectives include overall survival, organ preservation time, time to distant metastasis, and adverse event rates. This study has accrued 587 patients as of January 2025, and is investigating exploratory correlatives (e.g., ctDNA). Support: U10CA180821, U10CA180882, U24 CA196171. https://acknowledgments.alliancefound.org. Clinicaltrials.gov ID: NCT05610163. Clinical trial information: NCT05610163 .

Clinicogenomic characteristics and treatment lines of 8 patients with metastatic PDAC and KRAS G12R alteration treated with MEK inhibitor + hydroxychloroquine

Kaplan-Meier estimates of progression-free survival

Supporting Data for Isogenic cells

Importance:Cancer antigen 19-9 (CA19-9) is used to assess treatment response among patients with pancreatic ductal adenocarcinoma (PDAC); however, nearly 30% of patients with PDAC do not produce elevated CA19-9. Objective:To develop, validate, and apply an electronic tumor marker (e19-9) derived from routine laboratory data available in the electronic health record to assess treatment response and predict outcomes among patients with PDAC who do not produce CA19-9. Design, Setting, and Participants:In this cohort study, an artificial intelligence (AI) model was trained using routinely collected serum laboratory data from patients with PDAC and elevated CA19-9. The model was externally validated and then applied to a separate cohort of CA19-9 nonproducers. Model development and internal testing were conducted at a single institution using patient data from 2010 to 2022. External validation used a deidentified patient network across 58 health care organizations over the same period. The training cohort included 3239 patients with pancreatic cancer and elevated CA19-9. The external validation cohort included 4384 similar patients. The model was applied to 121 patients with resectable or borderline resectable PDAC who did not produce elevated CA19-9 and received neoadjuvant therapy with curative intent. These data were analyzed from November 2021 through March 2025. Main outcomes and measures:Model performance was assessed using root mean square error and R2. Clinical outcomes included completion of all neoadjuvant treatment and surgery, metastatic progression, and overall survival (OS). Results:The final fitted model demonstrated stable performance across both internal and external validation cohorts. Among 121 patients (59 female and 62 male) with localized PDAC who did not produce elevated CA19-9, a 50% or more decline in e19-9 (area under the curve [AUC], 0.79) and e19-9 level of less than 100 (AUC, 0.84) were objectively determined cut points associated with prognosis. A total of 93 patients (77%) completed all planned neoadjuvant therapy and surgery. A 50% or more decline in e19-9 levels and an e19-9 level less than 100 was associated with completion of all intended therapy (odds ratio [OR], 5.00; 95% CI, 1.60-15.66; P = .006 and OR, 19.31; 95% CI, 5.80-64.26; P < .001). An e19-9 level less than 100 was independently associated with OS (hazard ratio, 0.49; 95% CI, 0.25-0.97; P = .04). Conclusions and relevance:In this study, e19-9 was a noninvasive AI-derived marker that may provide accurate and relevant information to assess treatment response for the approximately 30% of patients with PDAC who do not produce CA19-9 at elevated levels. The development and validation of scalable, noninvasive screening methods using machine-learning algorithms may pave the way for early detection, prognostication, and treatment of cancers.

Aim Prostate stereotactic body radiotherapy (SBRT) can be delivered using MRI-guided radiotherapy (MRgRT) with the aim of increased precision and reduced toxicity. The overall treatment time (OTT) for SBRT varies, ranging from daily fractions to once-weekly schedules. However, it is unclear whether OTT affects clinical outcomes when using MRgRT. The aim of this study was to establish whether OTT impacts toxicity, quality of life and prostate specific antigen (PSA) control in prostate MRgRT. Methods For this study, outcomes from the MOMENTUM Study were utilized (NCT04075305). Patients with localized prostate cancer receiving 36.25 Gy to 40 Gy in five fractions of whom OTT was available, were analyzed. Physician-reported CTCAE toxicity, patient-reported outcomes (PROs) and PSA dynamics were collected at baseline and three, six, twelve and 24 months after MRgRT. Univariate ordinal logistic regression and mixed model analysis were performed to study the impact of OTT on changes in genitourinary (GU) and gastrointestinal (GI) toxicity, and QoL and PSA levels compared to baseline, respectively. Results A total of 858 patients were included with a median OTT of 14 days, ranging from five to 47 days. Excluding erectile function, no grade ≥3 GU or GI toxicity was reported. OTT was not associated with acute or late GU toxicity (OR 0.97 [95% CI 0.92 – 1.02]; P = 0.21 and OR 0.99 [95% 0.94 – 1.05]; P = 0.83) or acute and late GI toxicity (OR 0.89 [95% CI 0.79 – 1.00]; P = 0.05 and OR 0.99 [95% CI 0.92 – 1.07]; P = 0.83). In addition, OTT had no apparent impact on QoL scores and PSA kinetics. Conclusion This study suggests that OTT, generally between 8 and 18 days, in five fraction MRgRT for prostate cancer does not affect GU and GI toxicity, QoL and PSA control. Clinicians should consider discussing OTT with patients, as this will facilitate treating patients to the time frame that suits them best, reducing the impact of treatment on their QoL whilst also allowing flexibility for busy departments.

Radiomic features of radiation response

Patient, tumor and treatment characteristics

Abstract Purpose/Objective Genitourinary (GU) adverse events (AEs) are common during and after pelvic radiation therapy (RT) for prostate cancer and can substantially impact quality of life. We convened an international committee to establish consensus in the prevention, mitigation, and management of radiation-related acute and late GU AEs, as there are no relevant evidence-based consensus guidelines to inform treating providers. Materials/Methods A systematic evidence review focused on mitigation and management of radiation-related acute and late GU AEs was performed in PubMed, Embase and Cochrane. The following topics were addressed: management of acute GU AEs in the intact and post-operative settings; RT techniques; bladder outlet obstruction procedures; and indications for urology referral or hyperbaric oxygen therapy (HBO). Evidence-based consensus recommendations were developed using a Delphi process. We highlight the current state of evidence and evidence gaps worthy of future study. Results Consensus was reached for 31 key questions. For management of lower urinary tract symptoms (LUTS), most evidence comes from trials in patients without cancer and not undergoing RT. A consensus algorithm for medical management of acute GU AEs was developed with the following highlights: (a) alpha blockers as 1st-line for obstructive symptoms in the intact setting, (b) anti-spasmodics as 1st -line for irritative symptoms in the intact setting, and (c) anti-spasmodics as 1st -line in the post-operative setting. The consensus algorithm provides an ordered list of medications to offer if 1st -line options afford inadequate relief. For RT fractionation, randomized clinical trial (RCT) data are available. 40% of panelists rarely or never use standard fractionation over moderate hypofractionation for patients with baseline LUTS, but most consider moderate hypofractionation over SBRT for AUA IPSS > 15. For patients with severe obstructive LUTS (most commonly AUA IPSS >20), the panel recommends a prophylactic bladder outlet obstruction procedure and, if obstructive symptoms improve, consideration of moderate hypofractionation or SBRT, based on retrospective data. There is one RCT supporting use of HBO for late radiation cystitis. Conclusions The consensus guideline synthesizes available evidence and expert opinion across key clinical decision points to provide practical guidance in the prevention, mitigation, and management of radiation-related acute and late GU AEs in prostate cancer RT. Envisioned as a living document with periodic updates, this guideline serves as a resource for practicing radiation oncologists by outlining expert-derived consensus recommendations of evidence-based care in areas where high-quality data is limited.

Mutant KRAS allele dependent activation of WT-RAS

Gene list of a prostate cancer-specific TGF-β activity signature

Abstract Introduction: Even after neoadjuvant therapy (NAT) and resection for localized pancreatic ductal adenocarcinoma (PDAC), overall survival (OS) varies greatly. Clinical factors such as positive lymph nodes (LNs) can stratify risk, but greater precision is needed; comprehensive genomic profiling (CGP) can bridge this gap. We present a novel method of combining machine learning (ML) with variant allelic frequency (VAF) to identify drivers of OS. Methods: We identified all localized PDAC patients who completed NAT, resection, and had CGP data. Stratifying OS from surgery by median, an XGBoost ML framework was utilized to extract features of importance using clinicopathologic variables, as well as VAFs for any present pathogenic mutations (with VAF=0% for wildtype [wt]). Model performance was evaluated using area under the curve (AUC) and Shapley additive explanation plots (SHAP), with Kaplan-Meier curves for clinical validation. In patients with available whole transcriptome data, DESeq2 was utilized for differential expression profiling. Results: Among 110 patients with CGP data, 89 (81%) were KRAS mutated (G12D 33%, G12V 23%, and G12R 18%), and 67 (61%) had pathogenic TP53 mutation (mut). Initial models using known pathogenic mut VAFs identified TP53 as the highest impact feature. Addition of TP53 VAF, when combined with time-of-surgery clinical variables (age, comorbidity index, pathologic LN and T stage, lymphovascular or perineural invasion), improved prediction of OS (AUC = 0.81), vs. clinical variables alone (AUC = 0.73). SHAP analysis showed high TP53 VAF and LN+ status as the two highest contributing features for poor OS. When categorized by TP53 and LN status, TP53 mut/LN+ patients had significantly worse OS than all other groups (median 11.0 mo [95%CI 7.4-15.3] vs. 23.0 mo [20.4-32.1], p<0.0001); there was no difference in OS between TP53 wt/LN+, TP53 mut/LN-, and TP53 wt/LN-. When stratified into high vs. low VAF by median (6.5%), only high VAF patients had worse OS (10.7 mo [6.7-22.0]) compared to wt(25.9 mo [16.5-38.7], p=0.05.)78 of the 110 patients had bulk transcriptomic data available on the same specimens. TP53 mut tumors had significantly higher expression of LYPD2 (one of the human lymphocyte antigen-6 proteins associated with worse outcomes; log10 fold 4.4, p<1e-9), as well as keratin genes KRT13 (log10 fold 2.3, p <0.0001) and KRT15 (log10 fold 1.3, p <0.0001) - associated with basal subtypes and worse outcomes. Conclusion: VAF analysis from CGP can uncover novel predictive targets for post-surgical outcomes. TP53 mut tumors express higher levels of genes associated with worse prognosis (e.g. LYPD2, KRT genes). When present with LN+, TP53 mut confers worst OS and may be a clonally dependent process (based on VAF). Post surgical TP53 mut/LN+ cohorts should be stratified as high risk and be considered for adjuvant treatment and clinical trials. Citation Format: Imaad Said, Eugene Chen, Megan Zeller, Mohammed Aldakkak, Matthew Sochor, Bhabishya Neupane, Kshitij Gaur, Mandana Kamgar, Alexandria Phan, Janice Zhao, Samih Thalji, Beth Erickson, Christina Small-Tom, Callisia Clarke, Kathleen K. Christians, Nikki K. Lytle, Thomas McFall, William A. Hall, Anai N. Kothari, Douglas B. Evans, Yongwoo David Seo. Variant allele frequency machine learning model identifies unique TP53-mutant phenotypes with worse post-operative survival in pancreatic 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 5344.

Purpose: This study aimed to generate a map of local recurrences after neoadjuvant chemotherapy and radiation (total neoadjuvant therapy [TNT]) followed by surgical resection for pancreatic ductal adenocarcinoma (PDAC). Such recurrence patterns will serve to inform radiation treatment planning volumes that should be given in the neoadjuvant setting. Methods and Materials: Locoregional recurrences after TNT followed by surgery treated between 2009 and 2022 were radiologically identified. Recurrences were individually segmented using MIM software and complied in a single base scan. All contour compilations were used to create a threshold contour encompassing 80% of recurrences among all patients, head only, and body/tail only. The distance between organs at risk and the threshold contour were measured to design an optimal clinical target volume contour for patients treated with TNT. Recurrence patterns were also compared with existing adjuvant guidelines to assess coverage. Results: A database of 474 patients managed with TNT for PDAC was queried. While locoregional recurrences were rare in this cohort, we identified 80 patients with either isolated locoregional or simultaneous local and distant recurrences. Patients with diagnostic imaging at the time of recurrence were identified. The majority of recurrences were partially in the field of published contouring guidelines or volumetric expansions off of vessels, and volumetric coverage was low for all. Common areas of recurrence include the aorticodiaphragmatic junction, retropancreatic duodenal nodal basin, and the region to the right of the superior mesenteric artery. A novel set of proposed neoadjuvant contours was designed to cover the central-most 80% of recurrences. Conclusions: This is the largest collection of local/regional PDAC recurrences from a cohort of patients treated exclusively with TNT. Patterns of local/regional recurrence using TNT in PDAC vary significantly from those patients with PDAC treated with a surgery-first approach. Novel contouring guidelines presented in this study can help to ensure optimal coverage of high risk regions and avoid reliance on the current adjuvant guidelines to guide treatment planning. Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.