BackgroundPersistent high-risk human papillomavirus (hrHPV) infection causes virtually all high-grade squamous intraepithelial lesions (HSIL) and cervical cancer, but only a minority progress, implicating host and microenvironmental cofactors. The cervicovaginal microbiome (CVM), particularly Lactobacillus-dominated communities, may influence hrHPV persistence, clearance, and response to HSIL treatment.ObjectiveTo map evidence linking the CVM with hrHPV clearance and outcomes after HSIL treatment, including loop electrosurgical excision procedure (LEEP) and conization, using PRISMA-ScR and Arksey and O’Malley frameworks.MethodsLiterature on cervicovaginal microbiota, community state types (CSTs), HPV natural history, HSIL/CIN treatment, probiotics, microbiome-directed interventions, and predictive biomarkers was systematically searched and narratively synthesized using a Population-Concept-Context framework.ResultsSixty-six sources were charted. Lactobacillus crispatus-dominated communities (CST-I) were associated with hrHPV clearance and favorable post-treatment outcomes, whereas CST-IV, bacterial vaginosis, and increased alpha-diversity were associated with hrHPV persistence, greater HSIL severity, and treatment failure. Proposed mechanisms include lactic acid-mediated pH regulation, D-lactic acid signaling, and modulation of viral oncoproteins and immune responses. Excision altered the CVM, with restoration of Lactobacillus dominance accompanying viral clearance. Microbial-signature machine-learning models showed promising but preliminary predictive performance. Oral and intravaginal probiotics showed inconsistent but generally favorable trends, with strongest evidence for intravaginal L. crispatus transplantation. Gut microbiome diversity may also influence chemoradiotherapy outcomes in invasive cervical cancer.ConclusionThe CVM is a promising predictor of hrHPV clearance and HSIL treatment response. However, methodological heterogeneity, small cohorts, and limited prospective evidence restrict clinical translation. Large prospective studies and rigorously designed trials are needed to validate predictive signatures and determine whether microbiome profiling or targeted modulation can improve HSIL management and outcomes.
Immune checkpoint inhibitors have improved outcomes in selected patients with breast cancer, particularly those with triple-negative disease, but most tumors remain refractory. Abnormal tumor vasculature is one contributor to this resistance. Disorganized, hyperpermeable vessels produce heterogeneous perfusion, hypoxia, acidosis, and elevated interstitial pressure; these changes impede drug delivery and lymphocyte trafficking while favoring regulatory T cells, myeloid-derived suppressor cells, and dysfunctional antigen presentation. Anti-angiogenic therapy can transiently reverse part of this phenotype. When dose and timing are appropriate, a vascular-normalization window improves perfusion and oxygenation, restores endothelial adhesiveness, and creates conditions in which chemotherapy and immune checkpoint blockade may work more effectively. This framework is biologically compelling, but clinical evidence in breast cancer remains uneven: activity has been reported in several early-phase combination studies, whereas large trials of bevacizumab-containing regimens have not consistently improved overall survival. Candidate biomarkers—including VEGF/VEGFR signaling, angiopoietin–Tie2 activity, PD-L1, high endothelial venules, tertiary lymphoid structures, circulating cytokines, and spatial patterns of immune exclusion—remain exploratory and are limited by assay variability and temporal heterogeneity. This narrative review examines the vascular – immune interface across breast cancer subtypes, distinguishes mechanistic rationale from clinical proof, and identifies priorities for biomarker-guided trials designed to define dose, sequence, and the normalization window.
IntroductionAs a core drug in chemotherapy regimens for colorectal cancer, the clinical efficacy of oxaliplatin is compromised by multiple resistance mechanisms. Lipid metabolism, a crucial component of metabolic pathways, is known to affect the efficacy of various chemotherapeutic agents. However, to the best of our knowledge, the role of lipid metabolism in oxaliplatin resistance remains unreviewed.Areas coveredIn this review, we analyze the relationship between lipid metabolism and oxaliplatin efficacy from the perspectives of DNA damage, ferroptosis, ROS accumulation, cellular dormancy, antitumor immunity, vascular remodeling, and autophagy. This review covers nearly all known oxaliplatin resistance factors, summarizing the regulatory role of lipid metabolism across both basic and clinical studies. Given that clinical studies remain relatively scarce compared to basic research, the impact of factors directly regulated by lipid metabolism on clinical outcomes is analyzed. Based on this, their relationship with oxaliplatin efficacy is inferred, and potential directions for future clinical research are highlighted.Expert opinion/commentaryBy summarizing the relationship between lipid metabolism and oxaliplatin resistance, this review provides an important theoretical basis for improving chemotherapy efficacy in colorectal cancer and developing novel combination therapies based on metabolic interventions.
ObjectiveTo systematically evaluate published nomograms developed for patients with locally advanced cervical cancer (LACC) treated with radiotherapy, focusing on prognostic performance, core predictive variables, and implications for future model development.MethodsA systematic literature search of PubMed, Embase, Scopus, Web of Science, and the Cochrane Library identified studies published between 2010 and 2025 that developed new nomograms for LACC cohorts treated with radiotherapy or chemoradiotherapy. Data extraction included study population, predicted outcomes (overall survival [OS], progression-free survival [PFS], or disease-free survival [DFS]), model performance (C-index), validation methods, calibration, and predictor variables. Predictor patterns were summarized primarily by frequency of inclusion across nomograms, with β-coefficients used only for exploratory within-model descriptions.ResultsNine studies met the inclusion criteria; eight developed nomograms for OS and three evaluated disease progression outcomes (PFS or DFS), with two studies evaluating both outcome categories. Reported C-indices ranged from 0.68 to 0.835, indicating moderate to good discrimination. Lymph node status, FIGO stage, and tumor size were among the most frequently incorporated predictors, while histology and SCC-Ag were also recurrently included. Validation in independent cohorts remained limited. Graphical calibration was commonly reported, whereas quantitative calibration measures and decision-curve analyses were inconsistently reported.ConclusionsNomograms for LACC treated with radiotherapy generally demonstrate moderate-to-good discriminative performance and frequently incorporate lymph node status, stage, and tumor size. However, methodological heterogeneity, incomplete validation, and evolving treatment paradigms limit their immediate generalizability. Future work should focus on robust external validation, recalibration, and evaluation in contemporary treatment cohorts before clinical implementation.
