Artificial Intelligence to Predict the Risk of Lymph Node Metastasis in T2 Colorectal Cancer.

OBJECTIVE: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC). SUMMARY BACKGROUND DATA: Recent technical advances allow complete local excision of T2 CRC, traditionally treated with surgical resection. Yet, the widespread adoption of this approach is hampered by the inability to stratify the risk of LNM. METHODS: Data from pT2 CRC patients undergoing surgical resection between April 2000 and May 2022 at one Japanese and one Italian center were analyzed. Primary goal was AI system development for accurate LNM prediction. Predictors encompassed seven variables: age, sex, tumor size and location, lympho-vascular invasion, histological differentiation, and carcinoembryonic antigen level. The tool's discriminating power was assessed via Area Under the Curve (AUC), sensitivity, and specificity. RESULTS: Out of 735 initial patients, 692 were eligible. Training and validation cohorts comprised of 492 and 200 patients, respectively. The AI model displayed an AUC of 0.75 in the combined validation dataset. Sensitivity for LNM prediction was 97.8% and specificity was 15.6%. The Positive and the Negative Predictive Value were 25.7% and 96% respectively. The False Negative (FN) rate was 2.2%, the False Positive was 84.4%. CONCLUSIONS: Our AI model, based on easily accessible clinical and pathological variables, moderately predicts LNM in T2 CRC. However, the risk of FN needs to be considered. The training of the model including more patients across Western and Eastern centers -differentiating between colon and rectal cancers- may improve its performance and accuracy.

Delta Radiomic Features Predict Resection Margin Status and Overall Survival in Neoadjuvant-Treated Pancreatic Cancer Patients.

BACKGROUND: Neoadjuvant therapy (NAT) emerged as the standard of care for patients with pancreatic ductal adenocarcinoma (PDAC) who undergo surgery; however, surgery is morbid, and tools to predict resection margin status (RMS) and prognosis in the preoperative setting are needed. Radiomic models, specifically delta radiomic features (DRFs), may provide insight into treatment dynamics to improve preoperative predictions. METHODS: We retrospectively collected clinical, pathological, and surgical data (patients with resectable, borderline, locally advanced, and metastatic disease), and pre/post-NAT contrast-enhanced computed tomography (CT) scans from PDAC patients at the University of Texas Southwestern Medical Center (UTSW; discovery) and Humanitas Hospital (validation cohort). Gross tumor volume was contoured from CT scans, and 257 radiomics features were extracted. DRFs were calculated by direct subtraction of pre/post-NAT radiomic features. Cox proportional models and binary prediction models, including/excluding clinical variables, were constructed to predict overall survival (OS), disease-free survival (DFS), and RMS. RESULTS: The discovery and validation cohorts comprised 58 and 31 patients, respectively. Both cohorts had similar clinical characteristics, apart from differences in NAT (FOLFIRINOX vs. gemcitabine/nab-paclitaxel; p < 0.05) and type of surgery resections (pancreatoduodenectomy, distal or total pancreatectomy; p < 0.05). The model that combined clinical variables (pre-NAT carbohydrate antigen (CA) 19-9, the change in CA19-9 after NAT (∆CA19-9), and resectability status) and DRFs outperformed the clinical feature-based models and other radiomics feature-based models in predicting OS (UTSW: 0.73; Humanitas: 0.66), DFS (UTSW: 0.75; Humanitas: 0.64), and RMS (UTSW 0.73; Humanitas: 0.69). CONCLUSIONS: Our externally validated, predictive/prognostic delta-radiomics models, which incorporate clinical variables, show promise in predicting the risk of predicting RMS in NAT-treated PDAC patients and their OS or DFS.

Management of proctitis in ulcerative colitis and the place of biological therapies.

INTRODUCTION: Approximately 20-30% of the patients with ulcerative colitis (UC) may present with isolated proctitis. Ulcerative proctitis (UP) is a challenging condition to manage due to its significant burden in terms of disabling symptoms. AREAS COVERED: PubMed was searched up to March 2024 to identify relevant studies on UP. A comprehensive summary and critical appraisal of the available data on UP are provided, highlighting emerging treatments and areas for future research. EXPERT OPINION: Patients with UP are often undertreated, and the disease burden is often underestimated in clinical practice. Treat-to-target management algorithms can be applied to UP, aiming for clinical remission in the short term, and endoscopic remission and maintenance of remission in the long term. During their disease, approximately one-third of UP patients require advanced therapies. Escalation to biologic therapy is required for refractory or steroid dependent UP. For optimal patient care and management of UP, it is necessary to include these patients in future randomized clinical trials.

Co-existing Neuroendocrine Tumors in the Ileum and Pancreas: A Clinico-Pathological Challenge.

Ileal (I) and pancreatic (Pan) neuroendocrine tumors (NETs) are among the most common digestive neuroendocrine neoplasms (NENs). Coexisting NETs at both sites are rare, and establishing the primary or metastatic nature of the two lesions may be crucial for the appropriate treatment. We reviewed all the clinical reports of patients with INETs or PanNETs, diagnosed and treated in our ENETS Center of Excellence between 2012 and 2022. We selected patients with a history of synchronous or metachronous neuroendocrine (NE) lesions at the ileum and pancreas. For those with available histological samples from both sites, an immunohistochemistry (IHC) analysis for CDX2, Islet1, and serotonin has been performed. We found seven patients with NET in both the ileum and pancreas. F to M ratio was 4:3, and the median age at first diagnosis was 54 years (42-79). Five cases had synchronous lesions; in 2 cases, PanNETs were diagnosed respectively 8 and 56 months, after INETs. In four patients, with available histological samples from both the sites, a pathologic review and the IHC analysis have been performed, identifying three different scenarios: (i) primary INET metastatic to the pancreas, (ii) primary PanNET metastatic to the ileum, and (iii) synchronous primary PanNET and INET. In our experience, coexisting ileal and pancreatic NENs are rare occurrences. A multidisciplinary evaluation case-by-case and, whenever feasible, a comprehensive histopathological examination are needed to distinguish between metastatic and primary disease, in order to properly treat the patient.

Eosinophils, Eosinophilic Gastrointestinal Diseases, and Inflammatory Bowel Disease: A Critical Review.

BACKGROUND/OBJECTIVES: Inflammatory bowel disease (IBD) and eosinophilic gastrointestinal diseases (EGIDs) are complex, multifactorial chronic inflammatory disorders affecting the gastrointestinal tract. Their epidemiology, particularly for eosinophilic esophagitis (EoE), is increasing worldwide, with a rise in the co-diagnosis of IBD and EGIDs. Both disorders share common risk factors, such as early exposure to antibiotics or specific dietary habits. Moreover, from a molecular perspective, eosinophilic infiltration is crucial in the diagnosis of eosinophilic disorders, and it also plays a pivotal role in IBD histological diagnosis. Indeed, recent evidence highlights the significant role of eosinophils in the health of the intestinal mucosal barrier and as mediators between innate and acquired immunity, even indicating a potential role in IBD pathogenesis. This narrative review aims to summarize the current evidence regarding the common clinical and molecular aspects of EGIDs and IBD and the current state of knowledge regarding overlap conditions and their pathogenesis. METHODS: Pubmed was searched until May 2023 to assess relevant studies describing the epidemiology, pathophysiology, and therapy of EGIDs in IBD. RESULTS: The immune pathways and mechanisms underlying both EGIDs and IBD remain partially known. An improved understanding of the role of eosinophils in overlapping conditions could lead to enhanced diagnostic precision, the development of more effective future therapeutic strategies, and a more accurate prediction of patient response. Consequently, the identification of red flags indicative of an eosinophilic disorder in IBD patients is of paramount importance and must be evaluated on a case-by-case basis.

Mapping functional to morphological variation reveals the basis of regional extracellular matrix subversion and nerve invasion in pancreatic cancer.

Intratumor morphological heterogeneity of pancreatic ductal adenocarcinoma (PDAC) predicts clinical outcomes but is only partially understood at the molecular level. To elucidate the gene expression programs underpinning intratumor morphological variation in PDAC, we investigated and deconvoluted at single cell level the molecular profiles of histologically distinct clusters of PDAC cells. We identified three major morphological and functional variants that co-exist in varying proportions in all PDACs, display limited genetic diversity, and are associated with a distinct organization of the extracellular matrix: a glandular variant with classical ductal features; a transitional variant displaying abortive ductal structures and mixed endodermal and myofibroblast-like gene expression; and a poorly differentiated variant lacking ductal features and basement membrane, and showing neuronal lineage priming. Ex vivo and in vitro evidence supports the occurrence of dynamic transitions among these variants in part influenced by extracellular matrix composition and stiffness and associated with local, specifically neural, invasion.

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

Introduction: Metabolic reprogramming is a hallmark feature of pancreatic ductal adenocarcinoma (PDAC). A pancreatic juice (PJ) metabolic signature has been reported to be prognostic of oncological outcome for PDAC. Integration of PJ profiling with transcriptomic and spatial characterization of the tumor microenvironment would help in identifying PDACs with peculiar vulnerabilities. Methods: We performed a transcriptomic analysis of 26 PDAC samples grouped into 3 metabolic clusters (M_CL) according to their PJ metabolic profile. We analyzed molecular subtypes and transcriptional differences. Validation was performed by multidimensional imaging on tumor slides. Results: Pancreatic juice metabolic profiling was associated with PDAC transcriptomic molecular subtypes (p=0.004). Tumors identified as M_CL1 exhibited a non-squamous molecular phenotype and demonstrated longer survival. Enrichment analysis revealed the upregulation of immune genes and pathways in M_CL1 samples compared to M_CL2, the group with worse prognosis, a difference confirmed by immunofluorescence on tissue slides. Enrichment analysis of 39 immune signatures by xCell confirmed decreased immune signatures in M_CL2 compared to M_CL1 and allowed a stratification of patients associated with longer survival. Discussion: PJ metabolic fingerprints reflect PDAC molecular subtypes and the immune microenvironment, confirming PJ as a promising source of biomarkers for personalized therapy.