Pai, Rish K.

Aims Accurate determination of histological activity in ulcerative colitis (UC) is essential given its diagnostic and prognostic importance. Data on the relationship between histology and immune cell markers are limited. We aimed to evaluate the association between histological disease activity and immune cell marker concentration in colonic biopsies from patients with UC. Methods Sigmoid colon biopsies from 20 patients with UC were retrospectively assessed using the Robarts Histopathology Index (RHI). Targeted mass spectrometry determined the concentration of 18 immune cell markers (cluster of differentiation (CD) 4, CD8, CD19, CD20, CD40, CD56, CD68, CD103, forkhead box p3 (FOXP3), human leucocyte antigen, DR alpha chain (HLA-DRA), interleukin 10 (IL-10), IL-23 subunit alpha (IL-23A), IL-23 receptor (IL-23R), IL-2 receptor alpha chain (IL-2RA), Ki67, lymphocyte-activation gene 3 (LAG-3), programmed cell death protein 1 (PD-1) and PD ligand 1 (PD-L1)). The association between RHI score and immune cell marker concentration was quantified using Spearman’s rank correlation coefficient (ρ) and related 95% CIs. Results Fourteen of the 18 immune cell marker proteins were detected, with tissue concentration ranging from 0.003 to 11.53 fmol/µg. The overall RHI score was positively correlated with CD19, CD20, CD40, FOXP3, LAG-3, PD-1 and PD-L1 concentration (ρ=0.596–0.799) and negatively correlated with CD56 concentration (ρ=−0.460). There was no significant association between RHI score and CD4, CD8, CD68, CD103, HLA-DRA or Ki67 concentration. Conclusions This study provides insight into the correlation between immune cell marker expression and histological disease activity and the possible molecular and immunological determinants underlying microscopic disease activity in UC.

688 Background: PACC is a rare malignancy originating from the exocrine pancreas, accounting for less than 1% of all pancreatic cancers. Due to the rarity of the disease entity, there is a paucity of data to guide treatment decisions. This retrospective study aims to provide additional clinical characteristics and outcomes to aid in future treatment decisions. Methods: Pathology records from Mayo Clinic (AZ, FL, MN) patients (pts) denoting acinar or mixed-acinar cell carcinoma were searched between 2002 to 2023 and selected for retrospective review. Pt demographics, treatment courses, and next generation sequencing (NGS) were collected. Results: A total of 62 pts (74% male, n = 46) were identified with median age 64 years old. Histologic subtypes were 67% pure acinar cell carcinoma (42/62), 24% mixed acinar-neuroendocrine (15/62), and 8% mixed acinar-adenocarcinoma (5/62). AJCC stages at diagnosis were 34% stage I/II (21/62), 16% stage III (10/62), and 50% stage IV (31/62). Early-stage disease was treated with upfront surgical resection (81%, 17/21). Locally advanced disease received neoadjuvant therapy (NAT) followed by surgical resection (80%, 8/10). FOLFIRINOX was most often chosen as NAT (65%, 11/17), while others received gemcitabine-based NAT. The R0 resection rate was 86%. The 3 and 5-year survival estimates for stage III were 90.9% (95% CI: 75.4 – 100%) and 67.3% (95% CI: 42.3 – 100%), respectively. The 3 and 5-year survival estimates for stage IV were 36.6% (95% CI: 18.6 – 71.9%) and 29.3% (95% CI: 13.1 – 65.5%), respectively. Median survival time for stage IV was 3 years. Somatic NGS testing was done in 24 pts with alterations found in: homologous recombination (HR) in 42% (10/24); RAF alterations in 25% (6/24); mismatch repair (MMR) in 13% (3/24; none of them with MMR germline mutations), 1 ETV6-NTRK3 fusion, and 1 FGFR mutation. Germline NGS testing was done in 21 pts and alterations in HR were seen in 33% (7/21) of pts. This led to additional therapeutic options in 46% (11/24) of pts. Conclusions: Unlike PDAC, PACC is a genomically diverse disease, with potentially targetable alterations in RAF, HRD, and MMR genes, offering additional therapeutic options for significant number of pts. In addition, more than one-third of the pts harbored germline mutations in HR genes. Therefore, somatic and germline testing should be considered for any pt diagnosed with PACC.

200 Background: We developed and validated a quantitative segmentation algorithm (QuantCRC) to predict disease recurrence in stage I-III colorectal cancer patients (pts) based on the analysis of digitized hematoxylin and eosin (H+E) stained pathology slides. In this study, we aim to determine if QuantCRC analysis on pre-treated RC biopsies can predict pathological complete response (pCR) after NAT which include total neoadjuvant therapy (TNT), chemoradiation (CRT) and others. Methods: Stage II-IV RC pts treated with curative intent modalities between 2005-2023 at Mayo Clinic and University of Pittsburgh were evaluated. Eligible pts had pre and post-treatment tissue available for analysis. Clinical characteristics, treatment, and outcome data were extracted from the medical record. QuantCRC extracted 15 features: %tumor, %stroma, tumor:stroma ratio, %TB/PDC, %mucin, %necrosis, %high-grade, %signet ring cells, tumor-infiltrating lymphocytes (TILs) per cm2 of a tumor, %immature stroma (tumor bed), %inflammatory stroma (tumor bed), %mature stroma (tumor bed), %immature (stromal region), %inflammatory (stromal region), and %mature (stromal region). The associations between the QuantCRC features and pCR were evaluated using Wilcoxon rank-sum tests and logistic regression models while adjusting for primary tumor location and NAT. Results: The identified 288 pts had the following demographics: median age 60, 59% male, 52% distal tumor, 42% TNT. Pts who achieved pCR had smaller pre-treatment tumors (p=0.03), higher TILS, and lower %immature (stroma) (Table 1). After multivariable adjustment, higher TILS and lower %immature (stroma) remain to be significantly associated with a higher likelihood of pCR. A higher %mature (stroma) and %mature stroma (tumor bed) were also identified, in multivariable models, to be associated with a higher rate of pCR. NAT protocol and tumor location (proximal vs. distal) were not associated with pCR. Conclusions: The ability to integrate pathological features with AI may allow for personalized treatment. Using this technology, we recognize that patients who harbor a more mature stromal archetype and inflammatory tumor predisposition, are more likely to achieve pCR to conventional NAT. These pathological features are not currently incorporated into risk stratification in RC. Additional validation and integration into current risk stratification methods is warranted. [Table: see text]

162 Background: There is a need to improve current risk stratification of stage II and III colorectal cancer (CRC) to better inform risk of recurrence and guide adjuvant chemotherapy. The purpose of this study is to examine whether integration of QuantCRC, an AI-based digital pathology biomarker utilizing hematoxylin and eosin-stained slides, provides improved risk stratification over current American Society of Clinical Oncology (ASCO) guidelines. Methods: ASCO and QuantCRC-integrated risk schemes were applied to an observational cohort of 1,068 stage II and III CRCs. The stage II integrated scheme utilizes pT3 vs. pT4 and QuantCRC-derived risk groups. The stage III integrated scheme utilizes pT1-3 vs. pT4, pN1 vs. pN2, and QuantCRC-derived risk groups. Performance metrics included log-rank test, hazard ratios and Somers’ Dxy rank correlation. Results: Integration of QuantCRC provides improved risk stratification compared to the ASCO scheme for stage II and III CRC. The QuantCRC-integrated scheme placed more stage II tumors in the low-risk group compared to the ASCO scheme (69.3% vs. 60.4%) without decreased 3-year RFS. The QuantCRC-integrated scheme provided larger hazard ratios (HR) for both intermediate-risk (3.04, 95%CI 1.81-5.10, P=2.8x10-5) and high-risk (4.62, 95%CI 2.02-10.61, P=0.0003) groups compared to ASCO intermediate-risk (2.09, 95%CI 1.21-3.63, P=0.008) and high-risk (3.08, 95%CI 1.57-6.01, P=0.001) groups. The QuantCRC-integrated scheme for stage III tumors identified a small group of 80/518 (15.4%) CRCs at very high risk of recurrence with HR of 4.08 (95%CI 2.68-6.23, P=6.5x10-11) compared to a HR of 2.42 (95%CI 1.72-3.38, P=3.1x10-7) for 228/518 (44.0%) high-risk CRCs in the ASCO scheme. QuantCRC-integrated risk groups remained prognostic in stage III CRCs when stratified by presence or absence of any adjuvant chemotherapy. No difference in RFS were seen in QuantCRC-integrated low-risk and intermediate-risk stage III CRCs stratified by 3 vs. 6-months of oxaliplatin-based adjuvant chemotherapy suggesting that these two groups can be treated with 3-months of adjuvant therapy. Conclusions: Incorporation of QuantCRC into risk stratification provides a powerful predictor of RFS that has potential to guide subsequent treatment and surveillance.

Background: Recognizing the early signs of cancer risk is vital for informing prevention, early detection, and survival. Methods: To investigate whether changes in circulating metabolites characterize the early stages of colorectal cancer (CRC) development, we examined the associations between a genetic risk score (GRS) associated with CRC liability (72 single-nucleotide polymorphisms) and 231 circulating metabolites measured by nuclear magnetic resonance spectroscopy in the Avon Longitudinal Study of Parents and Children (N = 6221). Linear regression models were applied to examine the associations between genetic liability to CRC and circulating metabolites measured in the same individuals at age 8 y, 16 y, 18 y, and 25 y. Results: The GRS for CRC was associated with up to 28% of the circulating metabolites at FDR-P < 0.05 across all time points, particularly with higher fatty acids and very-low- and low-density lipoprotein subclass lipids. Two-sample reverse Mendelian randomization (MR) analyses investigating CRC liability (52,775 cases, 45,940 controls) and metabolites measured in a random subset of UK Biobank participants (N = 118,466, median age 58 y) revealed broadly consistent effect estimates with the GRS analysis. In conventional (forward) MR analyses, genetically predicted polyunsaturated fatty acid concentrations were most strongly associated with higher CRC risk. Conclusions: These analyses suggest that higher genetic liability to CRC can cause early alterations in systemic metabolism and suggest that fatty acids may play an important role in CRC development. Funding: This work was supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol, the Wellcome Trust, the Medical Research Council, Diabetes UK, the University of Bristol NIHR Biomedical Research Centre, and Cancer Research UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work used the computational facilities of the Advanced Computing Research Centre, University of Bristol - http://www.bristol.ac.uk/acrc/ .

Abstract Background People with cancer experience high rates of venous thromboembolism (VTE). Risk of subsequent cancer is also increased in people experiencing their first VTE. The causal mechanisms underlying this association are not completely understood, and it is unknown whether VTE is itself a risk factor for cancer. Methods We used data from large genome-wide association study meta-analyses to perform bidirectional Mendelian randomization analyses to estimate causal associations between genetic liability to VTE and risk of 18 different cancers. Results We found no conclusive evidence that genetic liability to VTE was causally associated with an increased incidence of cancer, or vice versa. We observed an association between liability to VTE and pancreatic cancer risk [odds ratio for pancreatic cancer: 1.23 (95% confidence interval: 1.08–1.40) per log-odds increase in VTE risk, P = 0.002]. However, sensitivity analyses revealed this association was predominantly driven by a variant proxying non-O blood group, with inadequate evidence to suggest a causal relationship. Conclusions These findings do not support the hypothesis that genetic liability to VTE is a cause of cancer. Existing observational epidemiological associations between VTE and cancer are therefore more likely to be driven by pathophysiological changes which occur in the setting of active cancer and anti-cancer treatments. Further work is required to explore and synthesize evidence for these mechanisms.

Validated nonbiopsy methods to assure duodenal mucosal healing in celiac disease are lacking, yet ongoing mucosal injury is associated with anemia, osteoporosis, and lymphoma. Most providers utilize clinical data as surrogates of mucosal status to avoid additional esophagogastroduodenoscopy. The reliability of such surrogates to predict mucosal recovery has been incompletely evaluated. The aim of this study was to rigorously assess patterns of histologic mucosal recovery at follow-up in celiac disease and to correlate findings with clinical data. Gastrointestinal pathologists from 13 centers evaluated initial and follow-up duodenal biopsies from 181 celiac disease patients. Marsh scores and intraepithelial lymphocytes (IELs)/100 enterocytes were assessed blindly. Histology at follow-up was correlated with symptoms, immunoglobulin A anti–tissue transglutaminase titers and gluten-free diet adherence. Fifty-six/181 (31%) patients had persistent villous blunting and 46/181 (25%) patients had just persistently elevated IELs at follow-up, with only 79/181 (44%) patients having complete histologic remission. IEL normalization (82/181; 45%) lagged villous recovery (125/181;69%). In a minority of patients, villous blunting was limited to proximal duodenal biopsies. No correlation was found between Marsh scores and symptoms, normalization of immunoglobulin A anti–tissue transglutaminase serology, or diet adherence. Children showed greater recovery of Marsh score (P<0.001) and IELs (P<0.01) than adults. Persistent mucosal injury is common in celiac disease, with discordant villous/IEL normalization. Pathologist awareness of expected findings in celiac disease follow-up biopsies, including their frequent lack of correlation with clinical data, is important for patient management, and has implications for eligibility criteria for therapeutics currently in development.