Segovia, Diana I.

e19023 Background: Undetectable measurable residual disease (uMRD) is associated with prolonged progression free survival in patients with chronic lymphocytic leukemia (CLL) (Rios-Olais et al., 2024). Peripheral blood (PB) MRD testing is less invasive and allows more frequent MRD monitoring than bone marrow (BM) MRD testing. As MRD testing and MRD-guided time-limited therapies become more common, there is a need to determine the concordance between rates of uMRD in the PB and BM. Methods: We performed a systematic review and meta-analysis of studies in CLL to determine the concordance between rates of uMRD in the PB and BM. Prospective clinical trials evaluating first-line, time-limited treatment of CLL with targeted agents or anti-CD20 monoclonal antibodies (mAbs) were identified via searches of PubMed, Embase, Scopus, and Web of Science from inception until December 15 th , 2025. Studies were included if they reported rates of BM and PB uMRD at the same timepoint using the same method of MRD testing. Study arms evaluating chemotherapy, single-agent targeted therapy or single-agent anti-CD20 mAbs were excluded. Study sample size, number of patients receiving MRD testing, rates of uMRD in PB and BM, time and method of MRD testing, depth of MRD testing, and treatment arm were extracted. The agreement of uMRD rates between PB and BM was assessed using intraclass correlation coefficients (ICC). Results: 3128 studies were identified on initial search. After study selection criteria were applied, 24 timepoints across 12 prospective clinical trials were analyzed. Across all timepoints, 3121 PB and 2782 BM MRD measurements were included. All timepoints defined uMRD at a depth of under 0.01% CLL cells (10^-4). 20/24 timepoints utilized flow cytometry for MRD testing, 3 utilized allele-specific oligonucleotide PCR (ASO-PCR), and one utilized next-generation sequencing (NGS). 8 timepoints evaluated patients treated with a BTK inhibitor + venetoclax, 10 evaluated patients treated with venetoclax + an anti-CD20 mAb, and 6 evaluated patients treated with triplet therapy. The ICC between rates of uMRD in PB and BM was 0.925 (95% CI: 0.89, 0.95), indicating an excellent degree of agreement between the two methods of testing.(Koo & Li, 2016) The mean uMRD rates in PB and BM were 70.1% and 64.3%, respectively. The mean rate of uMRD in the PB was 5.87% (95% CI: -7.05, 18.80%) higher than in the BM; indicating a consistent slight bias of higher PB uMRD rates compared to BM across timepoints. Conclusions: Overall, we demonstrate that in patients with CLL treated with modern, time-limited therapy, there is high concordance in uMRD rates between PB and BM. Rates of uMRD in the PB are typically slightly higher than in BM.

3525 Background: Tumor microenvironment (TME) features of colorectal cancer (CRC) may influence detection of circulating tumor DNA (ctDNA) and further refine prognosis. We applied a deep learning histopathologic algorithm to quantify TME features in stage III colon cancers and evaluated their association with postoperative ctDNA status among participants in a phase III FOLFOX-based adjuvant trial (NCCTG N0147). Methods: QuantCRC (Aiforia Technologies) was applied to digitized hematoxylin and eosin-stained whole-slide images of stage III colon adenocarcinomas to extract quantitative histopathologic features. Among cases where data met quality control (N=1817), associations between 15 distinct pathologist-defined features and clinical outcomes—time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS)—were evaluated, stratified by postoperative ctDNA status assessed by a tissue-free assay (Guardant Reveal). Relationships were analyzed using univariate and multivariable Cox proportional hazards models that were adjusted for clinicopathologic and molecular features ( KRAS , BRAF V600E , MMR status). Interaction testing was performed. Results: We found statistically significant quantitative differences for histopathological features by ctDNA status. Features associated with ctDNA positivity(+) included lymphovascular invasion (LVI), and increased %high grade, %tumor budding, %necrosis, and %stroma. ctDNA+ cases had lower %inflammatory stroma and fewer %signet ring cells (all p< 0.006). Multivariable analyses, irrespective of ctDNA status, identified %tumor budding, %mucin, %signet ring cells, %inflammatory tumor bed, and %inflammatory stroma as significantly associated with adverse outcomes (TTR, DFS, OS). Within ctDNA+ cases, higher %immature tumor bed was associated with adverse outcome for all 3 variables. Among ctDNA-negative cases, significantly poorer outcomes (TTR, DFS, OS) were observed for tumors with lower tumor infiltrating lymphocyte (TIL) density and reduced %necrosis. After adjustment, significant interactions with ctDNA status were observed for LVI (p< 0.006) and %signet ring cells (p< 0.035) across all outcome variables, for %necrosis with DFS, OS (p<0.040), and for TILs with TTR (p<0.015). Analysis is ongoing for ctDNA tumor fraction as well as tumor genotyping data (739 genes; Guardant360). Conclusions: QuantCRC identifies TME features associated with postoperative ctDNA status that enable risk-stratification within ctDNA groups. Among ctDNA-negative patients, reduced intratumoral TIL density and reduced tumor necrosis identify high-risk subgroups with inferior clinical outcomes, and may have clinical utility.

399 Background: The standard of care for resectable GEA adenocarcinomas is perioperative chemotherapy with the FLOT (fluorouracil, leucovorin, oxaliplatin, docetaxel) regimen. Recent studies investigating the addition of checkpoint inhibitors (CPIs) to perioperative chemotherapy have shown mixed results. An NMA can leverage both direct and indirect comparisons to evaluate the relative efficacies of available regimens in this setting. Methods: MEDLINE, EMBASE, Scopus, Web of Science and CENTRAL were searched until August 27th, 2025. Eligible studies included phase 3 randomized trials evaluating perioperative or neoadjuvant chemotherapy +/- CPIs ± radiation in resectable GEA. The primary outcomes were disease-free survival (DFS) and overall survival (OS). Hazard ratios and 95% confidence intervals (CIs) were estimated using a frequentist NMA framework. Results: Fifteen trials including 8072 patients were analyzed. For DFS, perioperative durvalumab + FLOT (dFLOT) ranked highest (P-score = 0.99), followed by FLOT (P-score = 0.84) (HR for dFLOT vs. FLOT was 0.71, 95% CI 0.58-0.86). dFLOT also ranked higher than perioperative pembrolizumab + cisplatin and fluorouracil/capecitabine (KN-585), though this comparison was not statistically significant (HR 0.65, 95% CI 0.40-1.04). Compared with CROSS, dFLOT showed superior DFS (HR of 0.48, 95% CI 0.36-0.63). For OS, dFLOT ranked the highest (P-score=0.95) and was superior to CROSS (HR 0.57, 95% CI 0.42-0.77). While dFLOT appeared favorable versus FLOT (HR 0.78, 95% CI 0.62-0.98), this finding was primarily driven by MATTERHORN, which did not meet its prespecified OS significance boundary (P = 0.03 vs threshold P < 0.0001), and the proportional hazards assumption was violated. Similarly, no significant OS difference was observed between dFLOT and the KN-585 arms (HR 0.75, 95% CI 0.45-1.23). Conclusions: In this NMA, perioperative FLOT remained the benchmark regimen for resectable GEA. dFLOT has shown promising early results, ranking the highest for DFS and showing favorable, but not statistically definitive OS trends in comparison to FLOT. Importantly, the network enabled indirect comparisons not tested in head-to-head trials, demonstrating that dFLOT ranked above pembrolizumab+CF/CX (KN-585) without reaching statistical significance, and also outperformed CROSS. However, these findings should be interpreted with caution, as they are primarily driven MATTERHORN data in which OS did not cross the prespecified threshold and proportional hazards assumptions were violated. Perioperative immunotherapy combinations appear promising, but final MATTERHORN results and further confirmatory studies are needed before dFLOT can be considered as a new standard of care.

3504 Background: Among patients with resected node-positive colon cancer, nearly 30% will relapse despite standard adjuvant chemotherapy. Analysis of molecular residual disease (MRD) using circulating tumor DNA (ctDNA) may enable risk stratification for tumor recurrence and inform adjuvant treatment decisions. Methods: Postsurgical ctDNA was analyzed in patients with stage III colon carcinoma who participated in a phase 3 trial of adjuvant FOLFOX alone or combined with cetuximab (n = 3084) [NCCTG N0147]. We utilized a tissue-free epigenomic assay for ctDNA detection (Guardant Reveal) with sampling prior to start of adjuvant therapy. Among ctDNA positives, epigenomic tumor fraction (TF) was estimated and ctDNA genotyping was done with Guardant360 (panel of 739 genes). Median follow-up was 6.1 years (yr). Study endpoints included time-to-recurrence (TTR), disease-free survival (DFS) and overall survival (OS) analyzed by Kaplan–Meier method. Multivariable Cox proportional hazards models were used to assess prognostic utility of ctDNA status adjusting for confounders. Interaction between ctDNA and clinicopathological features were assessed. Results: Among 2260 patients with evaluable ctDNA data, 461 (20.4%) were ctDNA positive.Tumors were significantly associated with higher T, N stage, BRAF V600E , high grade, obstruction/perforation, and worse performance status. Positive vs negative ctDNA was significantly associated with shorter TTR (hazard ratio [HR] 4.33, 95% confidence interval [CI] 3.65-5.13, P < 0.0001), poorer DFS (HR 3.74, CI 3.18-4.39, P < 0.0001] and OS (HR 3.17, CI 2.63-3.83, P < 0.0001), adjusting for covariates and tissue MMR, KRAS and BRAF V600E . ctDNA positive vs negative patients had 3y DFS of 36.4% (95%CI 32.2-41.2%) vs 82.5% (95% CI 80.0-84.4%), respectively. Adverse prognosis was consistent across subgroups (all P < 0.05), with stronger detrimental effects for positive ctDNA in N1 (vs. N2), T1/2 (vs T3 or 4), and mismatch repair deficient tumors [interaction P = 0.0002 to 0.041). Among patients with positive ctDNA, TF in those who recurred/died within 3 yr was double of those who remained recurrence-free ( P = 0.0001). High vs. low ctDNA TF ( > vs ≤ median) further stratified TTR (HR 1.48, CI 1.17-1.88, P = 0.0011), DFS (HR 1.52, CI 1.21-1.92, P = 0.0004) and OS (HR 1.58, CI 1.21-2.07, P = 0.0009), adjusting for confounders. ctDNA positive cases, . Analyses of ctDNA detection by site of recurrence, ctDNA clearance, and genomic variant detection are ongoing. Conclusions: In the largest study evaluating tissue-free epigenomic-based MRD detection, we demonstrate a robust prognostic utility of postsurgical ctDNA. Tumor fraction provided further patient stratification and analysis is ongoing to identify a subgroup based on TF that may be unlikely to clear ctDNA despite adjuvant chemotherapy.

e16157 Background: The optimal treatment for resectable gastric/GEJ AC is unclear due to limited direct comparisons among chemotherapy and chemoradiation regimens. Addressing this gap is critical to improve patient outcomes. We performed this network meta-analysis (NMA) to determine the relative efficacy of multimodality regimens for resectable gastric/GEJ AC. Methods: MEDLINE, EMBASE, Scopus, and CENTRAL were searched from inception till September 20, 2024, to identify phase III trials evaluating perioperative/neoadjuvant systemic therapy ± radiation in resectable gastric/GEJ AC. Primary outcomes were disease-free survival (DFS) and overall survival (OS). A frequentist NMA was conducted to compare hazard ratios (HR) and 95% CI for each outcome. Relative treatment rankings were assessed using P-scores. Results: Fifteen trials (8,072 patients) were analyzed. pFLOT (perioperative fluorouracil, leucovorin, oxaliplatin, and docetaxel) ranked highest for DFS in the overall population (P score 91%) (Table), significantly outperforming surgery alone (HR 0.48, 95% CI 0.38-0.60) and nCROSS (neoadjuvant paclitaxel, carboplatin and radiotherapy) (0.67, 0.56-0.81). For OS, nPLF+nCRT(EP) (neoadjuvant cisplatin, leucovorin and fluorouracil for induction, followed by etoposide, cisplatin, and radiotherapy) (P score 90%) and pFLOT (P score 87%) were the top regimens, with pFLOT significantly outperforming surgery alone (0.57, 0.45-0.72), and nCROSS (0.73, 0.60-0.89). Adding neoadjuvant chemoradiation to pFLOT provided no additional OS (1.14, 0.76-1.72) or DFS (1.22, 0.83-1.82) benefit. Similarly, adding pembrolizumab to perioperative chemotherapy (CF/CX) (cisplatin and fluorouracil/capecitabine) was not superior to pFLOT in terms of DFS (1.10, 0.71-1.69) or OS (1.09, 0.69-1.72). Conclusions: pFLOT demonstrated superior efficacy in resectable gastric/GEJ AC, surpassing surgery alone, nCROSS, and other perioperative regimens. The additive role of immunotherapy to pFLOT requires further investigation to refine patient selection and optimize outcomes. Regimen Overall Population GEJ cohort OS DFS OS DFS nPLF+nCRT(EP) 1 (90) 2 (84) 1 (85) NA pFLOT 2 (87) 1 (91) 2 (79) 2 (88) pPembrolizumab+CF/CX 3 (75) 3 (81) 5 (41) - nECX 4 (61) 5 (55) - - pCF 5 (59) 8 (51) 3 (72) - pECF/ECX 6 (47) 6 (55) 7 (40) 3 (57) nECX+aCRT(CX) 7 (45) 7 (52) 9 (31) - nCF 8 (42) 10 (28) 6 (40) - nCROSS 9 (41) 9 (35) 8 (34) 4 (43) pECF/ECX/FLOT+nCRT(F/X) 10 (38) 4 (57) 4 (72) 1 (90) nCRT(CF) 11 (9) 11 (6) - 5 (14) Surgery 12 (7) 12 (5) 10 (5) 6 (9) Data reported as rank (P-score). Abbreviations: n: neoadjuvant; p: perioperative; ECX: epirubicin + cisplatin + capecitabine; CF: cisplatin + fluorouracil; ECF: epirubicin + cisplatin + fluorouracil; aCRT(CX): adjuvant radiotherapy + cisplatin + capecitabine; CRT(F/X): fluorouracil/capecitabine + radiotherapy; CRT(CF): cisplatin + fluorouracil + radiotherapy.

Abstract Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (MMR) groups using deep learning. Using a quantitative segmentation algorithm (QuantCRC) that identifies 15 distinct morphologic features, we analyzed 402 resected stage III colon carcinomas [191 deficient (d)-MMR; 189 proficient (p)-MMR] from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy. Results were validated in an independent cohort (176 d-MMR; 1,094 p-MMR). Association of morphologic features with clinicopathologic variables, MMR, KRAS, BRAFV600E, and time-to-recurrence (TTR) was determined. Multivariable Cox proportional hazards models were developed to predict TTR. Tumor morphologic features differed significantly by MMR status. Cancers with p-MMR had more immature desmoplastic stroma. Tumors with d-MMR had increased inflammatory stroma, epithelial tumor-infiltrating lymphocytes (TIL), high-grade histology, mucin, and signet ring cells. Stromal subtype did not differ by BRAFV600E or KRAS status. In p-MMR tumors, multivariable analysis identified tumor-stroma ratio (TSR) as the strongest feature associated with TTR [HRadj 2.02; 95% confidence interval (CI), 1.14–3.57; P = 0.018; 3-year recurrence: 40.2% vs. 20.4%; Q1 vs. Q2–4]. Among d-MMR tumors, extent of inflammatory stroma (continuous HRadj 0.98; 95% CI, 0.96–0.99; P = 0.028; 3-year recurrence: 13.3% vs. 33.4%, Q4 vs. Q1) and N stage were the most robust prognostically. Association of TSR with TTR was independently validated. In conclusion, QuantCRC can quantify morphologic differences within MMR groups in routine tumor sections to determine their relative contributions to patient prognosis, and may elucidate relevant pathophysiologic mechanisms driving prognosis. Significance: A deep learning algorithm can quantify tumor morphologic features that may reflect underlying mechanisms driving prognosis within MMR groups. TSR was the most robust morphologic feature associated with TTR in p-MMR colon cancers. Extent of inflammatory stroma and N stage were the strongest prognostic features in d-MMR tumors. TIL density was not independently prognostic in either MMR group.

664 Background: Postoperative complications in patients with borderline resectable pancreatic cancer treated with neoadjuvant therapy and pancreatectomy in the national cooperative group setting have not been previously characterized. Further, the impact of preoperative hypofractionated radiotherapy on postoperative outcomes is largely unknown. We sought to quantify perioperative morbidity among patients with pancreatic cancer who received neoadjuvant modified FOLFIRINOX chemotherapy with or without hypofractionated radiotherapy on a multicenter clinical trial. Methods: The A021501 phase 2 trial randomized patients with borderline resectable pancreatic ductal adenocarcinoma to 8 doses of mFOLFIRINOX (Arm 1) or 7 doses of mFOLFIRINOX then hypofractionated radiotherapy (Arm 2), followed by pancreatectomy (Dec 31, 2016-Jan 1, 2019). Patients underwent resection according to defined operative standards at enrolling centers without specific requirements for either surgeon or hospital volume. Surgical complications and adverse events were assessed and captured at a single time point of 90 days after surgery and compared between treatment arms. Results: Of 126 enrolled patients, 51 (40%) underwent pancreatectomy (n=32, Arm 1; n=19, Arm 2) at 28 institutions. Vascular resection was performed in 19 patients (37%). One patient in Arm 2 died within 90 days after surgery. Rates of any surgical complication were 19% (n=6) in Arm 1 and 42% (n=8) in Arm 2 (p=0.07). Median length of stay was 7 days (range 5-38 days). Five (10%) patients required reoperation within 90 days. Readmission rates were higher in Arm 2 than Arm 1 (16% vs. 42%, p=0.04) but there were no differences in rates of reoperation, pancreatic fistula or abscess requiring drainage, or wound infection between study arms. 54% of patients (n=26/48) experienced a grade 3 or higher adverse event, with no difference between treatment arms (47% versus 67%, p=0.7). Rates of initiation of adjuvant therapy did not differ between treatment arms (66% vs. 68%, p=0.4). Pancreatic fistula and abscess were associated with adjuvant therapy (p<0.01). No difference in overall survival was observed based on occurrence of surgical complications (HR 1.1; 95% CI 0.5-2.6). Conclusions: In this national cooperative group study of patients with borderline resectable pancreatic cancer,postoperative complications following neoadjuvant chemotherapy, radiation, and surgical resection were consistent with rates previously reported by high-volume institutions and using large datasets. Multimodality trials of preoperative therapy for locoregionally advanced pancreatic cancer may be safely performed in the cooperative group setting. Clinical trial information: NCT02839343 .

3542 Background: Solid tumors can be characterized by distinct immune phenotypes based on the level of T cell infiltration in the tumor microenvironment (TME) which may provide prognostic information and also inform strategies to restore the anti-tumor immune response. Immune phenotypes were determined using an artificial intelligence (AI) algorithm in digitized whole-slide images (WSI) of tumors with deficient (d) mismatch repair (MMR) vs proficient (p) MMR. Methods: Stage III colon carcinomas (N = 401; 393 met QC) from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy were analyzed including all available tumors with dMMR (n = 196) and a randomly selected cohort of pMMR tumors (n = 195). Using an AI algorithm (Lunit SCOPE) previously trained on solid tumors, digitized tumors were categorized into three immune phenotypes based on epithelial and stromal TIL data-driven cutpoints in dMMR and pMMR (inflamed: TIL high in epithelium (> upper 25%); excluded: TIL high in stroma (>lower 25%), low in epithelium; and desert: TIL low in epithelium and stroma). Phenotypes were then examined in relationship to disease-free survival (DFS) using Kaplan-Meier methodology. Results: Of the 3 immune phenotypes in dMMR tumors, 25% were inflamed, 50% were immune-excluded, and 25% were immune-desert. Based on univariate results, multivariable modeling was performed incorporating immune phenotype in addition to age, histological grade, N stage, T stage, performance status, treatment arm, BRAF and KRAS status and identified immune phenotypes and N stage to be significantly associated with DFS. Among dMMR tumors, immune desert phenotype was associated with the poorest DFS (Desert: HR adj 1.95, 95%CI (1.01, 3.80); Excluded: HR adj 0.89, 95%CI (0.47, 1.69); Inflamed: ref; p:0.01). When compared to immune desert tumors, immune-excluded tumors had significantly better DFS (HR adj 0.49, 95%CI (0.27, 0.88), p:0.01). At a median follow-up of 60 months, 3-year DFS of patients with dMMR was 71.2% with Immune inflamed, 78.5% with Excluded, and 54.5% with Desert phenotypes. In contrast to dMMR, univariate analyses of data-driven cutpoints in pMMR tumors was not prognostic. Using a different data-driven cutpoint (15%), the revised immune phenotypes remained non-significant for DFS within pMMR tumors. Conclusions: Distinct AI-derived immune phenotypes in the TME were identified that were significantly prognostic in patients with dMMR, but not pMMR colon cancers. A data-driven immune-desert phenotype was identified in dMMR tumors that was associated with significantly poorer survival. Further investigation of the potential predictive utility of these phenotypes for immunotherapy are planned. Support: https://acknowledgments.alliancefound.org . ClinicalTrials.gov Identifier: NCT00079274 .

3527 Background: Advances in deep learning may improve the ability to evaluate and quantify pathological features in solid tumors to improve prediction of patient disease-free survival (DFS). We used an artificial intelligence (AI) algorithm to quantify morphological features in the tumor microenvironment of stage III colon cancers. Methods: We analyzed digitized stage III colon carcinomas (N = 402; 382 met QC) from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy that included all available tumors with dMMR and a randomly selected cohort of pMMR tumors (median follow-up 60 months) [NCCTG N0147; Alliance for Clinical Trials in Oncology]. Fifteen morphological features were extracted using the QuantCRC algorithm that segments images into carcinoma (low-grade, high-grade, signet ring cell), stroma (immature, mature, and inflammatory), mucin, tumor/stroma ratio, tumor budding/poorly differentiated clusters (TB/PDC), necrosis, smooth muscle, fat, and tumor-infiltrating lymphocytes (TILs) and tumor area (mucin, epithelium and TB/PDC). Analysis of AI-derived features with clinical variables, molecular alterations ( BRAF/KRAS), and DFS were examined using Kaplan-Meier methodology and multivariable Cox regression. Results: Among the 15 AI-derived morphological features, the following differed significantly between dMMR (n = 191) and pMMR (n = 189) whereby dMMR tumors had lower mature stroma, but higher inflammatory stroma and tumor, higher tumor grade and increased mucin, TB/PDCs, signet ring cells, and TILs (all p< 0.05). Among dMMR tumors, multivariable analysis revealed that tumor area [mucin, epithelium and TB/PDC] (HR adj 0.45, 95%CI (0.24, 0.84), p:0.01, [Q2/3 vs Q1]) and N stage were the only significant and independent prognostic variables. Among pMMR tumors, multivariable analysis identified that tumor budding/poorly differentiated clusters (TB/PDCs) (HR adj 0.20, 95%CI (0.06, 0.61), p:0.01, [Q1 vs Q4]) was the strongest prognostic variable and the only morphological feature that was significantly associated with DFS along with age, N stage and T stage. Conclusions: Using AI, we can extract and quantify distinct morphological features in tumor sections that differ between dMMR and pMMR and multivariately, can significantly and robustly enhance prognostication within each MMR group. Among pMMR tumors, tumor budding/poorly differentiated clusters was the strongest predictor of DFS. Support: NIH U10CA180821, U10CA180882, U24CA196171, R01 CA210509 (to FAS). Study NCCTG N0147 received funds from Sanofi https://acknowledgments.alliancefound.org . ClinicalTrials.gov Identifier: NCT00079274 Key words Artificial Intelligence; Tumor Microenvironment; Colonic Neoplasms; Disease-free survival.