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6 recordsLinked to original sources

Effects of Esketamine on Postoperative Hospital Anxiety and Depression Scale Scores in Patients Undergoing Laparoscopic Radical Resection for Colorectal Cancer.

OBJECTIVE: To investigate the effects of intravenous esketamine on postoperative Hospital Anxiety and Depression Scale (HADS) scores in patients undergoing laparoscopic radical resection for colorectal cancer. METHODS: In this prospective, randomized, placebo-controlled study, adult patients for elective laparoscopic radical resection were randomly assigned (1:1) to a control group (group C) or an esketamine group (group PE). Group C received conventional general anesthesia and patient-controlled intravenous analgesia (PCIA). In group PE, esketamine 0.5&#x2009;mg/kg was injected during induction of anesthesia, with esketamine 1&#x2009;mg/kg added to PCIA. Primary outcome was HADS score on postoperative day 1. Secondary outcomes included HADS scores on postoperative days 3 and 7, sleep quality scores, postoperative level of consciousness, complication rate, length of hospital stay, 24&#x2009;h inflammatory factors, and satisfaction scores. RESULTS: Group PE showed significantly lower HADS-A and HADS-D scores on postoperative days 1 and 3 , reduced 24&#x2009;h interleukin-6 (IL-6) leveland higher patient satisfaction compared with group C (all p&#x2009;<&#x2009;0.05). CONCLUSIONS: Esketamine given during induction and in PCIA reduced early-stage postoperative HADS scores and improved patient satisfaction in colorectal cancer patients.

Humans

Mechanisms linking the gut microbiota to colorectal cancer development and progression.

Colorectal cancer remains a leading cause of global cancer mortality, with a concerning rise in early-onset cases driven by complex interactions between environmental exposures, lifestyle factors, and host genetics. Mounting evidence indicates that gut microbiota dysbiosis critically modulates this oncogenic process, acting as an active participant rather than a passive bystander. This review systematically synthesizes the dichotomous roles of the intestinal microbiome in colorectal tumorigenesis through the conceptual framework of the driver-passenger model. We discuss how early initiating driver bacteria, such as Polyketide synthase-positive Escherichia coli and enterotoxigenic Bacteroides fragilis, compromise mucosal barriers, induce chronic mucosal inflammation, and inflict direct genomic instability. As the local tumor microenvironment undergoes profound metabolic remodeling, opportunistic passenger pathogens, notably Fusobacterium nucleatum, become enriched, further promoting cellular proliferation and facilitating tumor immune evasion. Conversely, protective commensals, exemplified by Clostridium butyricum and Streptococcus thermophilus, exert robust tumor-suppressive effects through multifaceted mechanisms. These beneficial microbes actively antagonize malignant progression by redirecting tumor metabolic fluxes toward oxidative stress, orchestrating deep epigenetic reprogramming, and degrading core oncoproteins to reverse chemoresistance. Transitioning from fundamental mechanisms to clinical application, we evaluate a comprehensive spectrum of microbiota-targeted interventions, encompassing non-invasive diagnostic biomarkers, fecal microbiota transplantation, engineered bacteria, phage therapy, and postbiotics. Finally, we critically address the formidable translational challenges associated with microbial heterogeneity, long-term safety, and regulatory standardization, aiming to provide a balanced perspective on integrating microbiome-based strategies into next-generation precision oncology for colorectal cancer.

Humans

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n&#xa0;=&#xa0;907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n&#xa0;=&#xa0;35), colorectal cancer (n&#xa0;=&#xa0;21), and pancreatic cancer (n&#xa0;=&#xa0;9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans

Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.

Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.

Humans

Randomized phase-II trial of surufatinib plus FOLFOX/FOLFIRI versus FOLFOXIRI as second-line therapy for metastatic colorectal cancer.

BACKGROUND: Second-line treatment for metastatic colorectal cancer (mCRC) typically involves oxaliplatin- or irinotecan-based doublet chemotherapy with or without anti-angiogenic antibodies. Triplet regimens such as FOLFOXIRI have demonstrated synergy and improved efficacy as first-line therapy. Surufatinib, an oral multi-kinase inhibitor targeting VEGFR1-3, FGFR1, and CSF-1R, may enhance chemotherapy efficacy. We evaluated surufatinib combined with doublet (FOLFOX/FOLFIRI) versus triplet (FOLFOXIRI) chemotherapy as second-line treatment for mCRC. PATIENTS AND METHODS: This multicentre, open-label, randomized phase-II trial used Simon's minimax two-stage design. Eligible patients had mCRC progressing on or within 6&#x2009;months after first-line doublet chemotherapy. Patients were randomized 1:1 to surufatinib 250&#x2009;mg once daily plus either mFOLFOX6/FOLFIRI (doublet cohort, selected based on prior regimen) or FOLFOXIRI (triplet cohort). The primary endpoint was objective response rate (ORR). RESULTS: From September 2021 to November 2023, 57 patients were randomized (28 per cohort after one withdrawal). In the doublet cohort, ORR was 35.7% (95% CI: 18.6-55.9), median progression-free survival (PFS) was 5.4&#x2009;months (95% CI: 3.8-7.0), and median overall survival (OS) was 19.0&#x2009;months (95% CI: 9.2-28.8). In the triplet cohort, ORR was 39.3% (95% CI: 21.5-59.4), median PFS was 5.8&#x2009;months (95% CI: 3.3-8.2), and median OS was 10.9&#x2009;months (95% CI: 6.0-15.8). Grade &#x2265;3 treatment-emergent adverse events occurred more frequently in the triplet (71.4%) versus doublet (57.1%) cohort, with higher rates of treatment delays (89.3% versus 72.0%) and discontinuations (25.0% versus 14.3%). CONCLUSIONS: Surufatinib plus doublet chemotherapy showed encouraging antitumor activity and acceptable tolerability in second-line mCRC, warranting further evaluation in a larger randomized trial. In contrast, surufatinib plus triplet chemotherapy was associated with increased toxicity, more frequent treatment delays or discontinuations, and shorter overall survival; this combination is not recommended for further investigation in this setting.ClinicalTrials.gov: NCT04734249Date of registration: January 31, 2021.

Humans

Impact of stromal maturity and proportion on prognosis and immune landscape in colorectal cancer.

BACKGROUND: Tumour microenvironment and cancer cells have constant interaction affecting cancer progression. Tumour-stroma ratio (TSR) in the tumour centre and desmoplastic reaction (DR) classification at the invasive margin are prognostic factors based on stroma evaluation on H&E slides. However, their combined value and immunological associations remain poorly defined. This study examines the prognostic and immunological value of TSR, DR, and their combination in two large colorectal cancer cohorts. METHODS: Two colorectal cancer cohorts (N&#x2009;=&#x2009;1,876) were analyzed. We introduced a three-tiered Stromal Maturity and Proportion Score (SMAPS) based on the presence of high (>50%) TSR and myxoid stroma (immature DR classification). Alcian blue staining was used to further quantify myxoid stroma. Multiplex immunohistochemistry combined with digital image analyses, was utilized to study immune cell densities associated with SMAPS, TSR, DR, and Alcian blue intensity. RESULTS: In the study cohort (N&#x2009;=&#x2009;1,100), SMAPS was a stronger predictor of cancer-specific mortality [HR for high (vs. low) SMAPS 2.01 (95% CI 1.47-2.75), p&#x2009;<&#x2009;0.0001] compared to TSR [HR for stroma-high (vs. stroma-low) 1.49 (95% CI 1.15-1.93), p&#x2009;=&#x2009;0.003] and DR classification [HR for immature (vs. mature) 1.84 (95% CI 1.39-2.45), p&#x2009;<&#x2009;0.0001]. High SMAPS, stroma-high TSR, and immature DR correlated with lower densities of CD3+ T cells, B cells, M1-like macrophages, CD66B+ granulocytes, and mast cells. Alcian blue staining was associated with immature DR and corresponding immune cells. The validation cohort (N&#x2009;=&#x2009;776) confirmed the association of SMAPS with survival and T cell densities. CONCLUSIONS: TSR and DR are independent prognostic factors for cancer-specific survival. SMAPS is a promising prognostic tool that integrates stromal maturity at the invasive margin and stromal proportion in the tumour centre. SMAPS has stronger prognostic value compared to TSR and DR classifications alone. A high stromal proportion and myxoid content are associated with an immunosuppressive microenvironment characterized by lower densities of antitumourigenic immune cells.

Humans