Epithelial cancers such as stomach and ovarian cancer tend to metastasize to the peritoneum, often leading to intractable disease and poor survival. The mechanisms that enable gastric cancer cells to implant, invade, and survive in the peritoneal niche are poorly understood. We developed a novel human peritoneal explant model using freshly harvested peritoneal tissue samples. GFP-labeled human gastric adenocarcinoma cells (AGS) were co-cultured with the peritoneal samples, and 2% of these cells implanted into the peritoneum. The transcriptomic profile of the implanted AGS cells was compared to AGS cells that failed to implant using RNA sequencing. Differentially expressed genes in implanted AGS cells were enriched for cell adhesion and motility. We functionally validated these genes with CRISPR knockout and identified ADAM12 as a regulator of peritoneal metastasis. ADAM12 KO significantly impaired peritoneal metastasis in vivo and ex vivo and marked disruption of the ITGβ1 interactome in GCa cells. Our approach and the new data identify a distinct peritoneal metastasis gene set that facilitates the implantation and invasion of gastric cancer cells within the peritoneum. Disruption of these pathways with peritoneal-directed therapies has the potential to improve survival in patients with high-risk primary gastric cancer.

BACKGROUND:Colonic surgery for Crohn's disease (CD) frequently involves sparing uninvolved segments of the colon. Few studies have assessed recurrence rates after segmental colectomy (SC). The aim of this study was to determine the rate of and identify the risk factors for postoperative CD recurrence. METHODS:This was a multicenter retrospective study from 3 tertiary inflammatory bowel disease (IBD) referral centers of CD patients who underwent SC between 2000 and 2019. We defined endoscopic recurrence as the presence of ulcers in the remaining colon upon postoperative colonoscopy. RESULTS:A total of 108 patients were included. Sixty-nine (63.9%) patients had evidence of postoperative CD endoscopic recurrence. Age at surgery <40 years and disease duration ≤156 months predicted an increased likelihood for postoperative recurrence (odds ratio [OR], 2.43; P = .031 and OR, 3.29; P = .005, respectively), whereas abdominal perineal resection (OR, 0.21; P = .005), indication for SC of malignancy (OR, 0.14; P = .016), and postoperative use of tumor necrosis factor α (TNFα) inhibitor for prophylactic purposes (OR, 0.38; P = .040) negatively predicted disease recurrence. Disease duration ≤156 months (OR, 2.86; P = .039) and postoperative TNFα inhibitor prophylaxis remained significant (OR, 0.26; P = .013) upon multivariable modeling. CONCLUSION:Although high rates of recurrence persist within the postoperative phase of SC for CD, the postoperative use of TNFα inhibitor for prophylactic purposes for a subset of patients may promote a more durable endoscopic remission.

According to the National Comprehensive Cancer Network (NCCN), submucosally invasive (pT1) colorectal carcinomas (CRCs) should be evaluated for tumor grade, lymphatic invasion, and tumor budding to determine the risk of lymph node metastasis. The presence of any one of these high-risk features is an indication for surgery in endoscopically removed pT1 CRCs. In this study, we determined if quantitative pathologic analysis with the QuantCRC algorithm can augment NCCN risk stratification in a multi-institutional cohort of 512 surgically resected pT1 CRC. LASSO regression identified

Supplementary Figure S1. Flow diagram outlining the steps undertaken in this study.

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.

Multivariable models for the prediction of TTR by morphologic features and clinicopathological variables in initial cohort [p-MMR (n = 189) or d-MMR (n = 191) stage III colon cancers]

Supplementary Table S2. Concordance between ASCO and QuantCRC-Integrated risk groups

On a global scale, gastric adenocarcinoma (GCa) accounts for a large burden of death from cancer. Despite advances in systemic therapy and surgical technique, the fatality rate for GCa remains unacceptably high in Europe and North America, where diagnosis is typically made at an advanced stage. Biomarkers that can accurately predict response to new therapies and provide novel therapeutic strategies are urgently sought. FAM46C, a putative noncanonical nucleotidyltransferase, has garnered interest for its tumor suppressor function in multiple myeloma. A frequent and profound depletion of FAM46C has been described in GCa patients from China, Japan and now Canada. Furthermore, the degree of FAM46C depletion meaningfully portends cancer recurrence following resection, and death from GCa. In this review, we provide an updated summary of the literature regarding FAM46C as a biomarker in GCa and explore the potential mechanism(s) through which FAM46C depletion promotes GCa progression, including disinhibition of oncogenic Plk4 kinase activity. We highlight the potential for restoration of FAM46C levels as a therapeutic strategy. Norcantharidin, a synthetic analogue of the traditional Chinese medicine cantharidin derived from the blister beetle, is the only bio-available compound presently known to upregulate FAM46C expression and is under investigation in phase one trials in cancer patients.

Supplementary Table S5. Adjuvant chemotherapy according to ASCO and QuantCRC-Integrated risk groups.

Supplementary Table S3. Carcinoembryonic antigen levels according to ASCO and QuantCRC-Integrated risk groups.

Supplementary Figure S2. Scatter plots of QuantCRC features stratified by QuantCRC-integrated and ASCO risk schemes.

Supplementary Table S1. Univariate and multivariate analysis of QuantCRC risk classification, pT stage, and any high-risk pathologic feature.

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.

A limited spectrum of inflammatory and neoplastic disorders arise in the gallbladder. This chapter includes an overview of acute and chronic cholecystitis and the most common forms of neoplasia involving the gallbladder and extrahepatic bile ducts. Rare neoplastic lesions are discussed briefly as well and the emphasis throughout is on highlighting key features in making the correct diagnosis and utility of any ancillary studies in resolving the relevant differential diagnoses.

Multivariable models for the prediction of TTR by morphologic features and clinicopathological variables in the validation cohort [p-MMR (n = 1,094) or d-MMR (n = 176) stage III colon cancers]

AbstractPurpose: There is a need to improve current risk stratification of stage II colorectal cancer to better inform risk of recurrence and guide adjuvant chemotherapy. We sought to examine whether integration of QuantCRC, a digital pathology biomarker utilizing hematoxylin and eosin–stained slides, provides improved risk stratification over current American Society of Clinical Oncology (ASCO) guidelines. Experimental Design: ASCO and QuantCRC-integrated schemes were applied to a cohort of 398 mismatch-repair proficient (MMRP) stage II colorectal cancers from three large academic medical centers. The ASCO stage II scheme was taken from recent guidelines. The QuantCRC-integrated scheme utilized pT3 versus pT4 and a QuantCRC-derived risk classification. Evaluation of recurrence-free survival (RFS) according to these risk schemes was compared using the log-rank test and HR. Results: Integration of QuantCRC provides improved risk stratification compared with the ASCO scheme for stage II MMRP colorectal cancers. The QuantCRC-integrated scheme placed more stage II tumors in the low-risk group compared with the ASCO scheme (62.5% vs. 42.2%) without compromising excellent 3-year RFS. The QuantCRC-integrated scheme provided larger HR for both intermediate-risk (2.27; 95% CI, 1.32–3.91; P = 0.003) and high-risk (3.27; 95% CI, 1.42–7.55; P = 0.006) groups compared with ASCO intermediate-risk (1.58; 95% CI, 0.87–2.87; P = 0.1) and high-risk (2.24; 95% CI, 1.09–4.62; P = 0.03) groups. The QuantCRC-integrated risk groups remained prognostic in the subgroup of patients that did not receive any adjuvant chemotherapy. Conclusions: Incorporation of QuantCRC into risk stratification provides a powerful predictor of RFS that has potential to guide subsequent treatment and surveillance for stage II MMRP colorectal cancers.

Tumor budding (TB) is a powerful prognostic factor in colorectal cancer (CRC). An internationally standardized method for its assessment (International Tumor Budding Consensus Conference [ITBCC] method) has been adopted by most CRC pathology protocols. This method requires that TB counts are reported by field area (0.785 mm2) rather than objective lens and a normalization factor is applied for this purpose. However, the validity of this approach is yet to be tested. We sought to validate the ITBCC method with a particular emphasis on normalization as a tool for standardization. In a cohort of 365 stage I-III CRC, both normalized and non-normalized TB were significantly associated with disease-specific survival and recurrence-free survival (P<0.0001). Examining both 0.95 and 0.785 mm(2) field areas in a subset of patients (n=200), we found that normalization markedly overcorrects TB counts: Counts obtained in a 0.95 mm(2) hotspot field were reduced by an average of 17.5% following normalization compared with only 3.8% when counts were performed in an actual 0.785 mm(2) field. This resulted in 45 (11.3%) cases being downgraded using ITBCC grading criteria following normalization, compared with only 5 cases (1.3%, P=0.0007) downgraded when a true 0.785 mm(2) field was examined. In summary, the prognostic value of TB was retained regardless of whether TB counts in a 0.95 mm(2) field were normalized. Normalization resulted in overcorrecting TB counts with consequent downgrading of most borderline cases. This has implications for risk stratification and adjuvant treatment decisions, and suggests the need to re-evaluate the role of normalization in TB assessment.