Emerging evidence indicates bacterial infections contribute to the formation of cancers. Bacterial genotoxins are effectors that cause DNA damage by introducing single- and double-strand DNA breaks in the host cells. The first bacterial genotoxin cytolethal distending toxin (CDT) was a protein identified in 1987 in a pathogenic strain in Escherichia coli (E. coli) isolated from a young patient. The peptide-polyketide genotoxin colibactin is produced by the phylogenetic group B₂ of E. coli. Recently, a protein produced by attaching/effacing (A/E) pathogens, including enteropathogenic and enterohemorrhagic E. coli (EPEC and EHEC) and their murine equivalent Citrobacter rodentium (CR), has been reported as a novel protein genotoxin, being injected via the type III secretion system (T3SS) into host cells and harboring direct DNA digestion activity with a catalytic histidine-aspartic acid dyad. These E. coli-produced genotoxins impair host DNA, which results in senescence or apoptosis of the target cells if the damage is beyond repair. Conversely, host cells can survive and proliferate if the genotoxin-induced DNA damage is not severe enough to kill them. The surviving cells may accumulate genomic instability and acquire malignant traits. This review presents the cellular responses of infection with the genotoxins-producing E. coli and discusses the current knowledge of the tumorigenic potential of these toxins.

Background Tertiary lymphoid structures (TLS) within the tumor microenvironment have been associated with cancer prognosis and therapeutic response. However, the immunological pattern of a high peritumoral TLS (pTLS) density and its clinical potential in hepatocellular carcinoma (HCC) remain poor. This study aimed to elucidate biological differences related to pTLS density and develop a radiomic classifier for predicting pTLS density in HCC, offering new insights for clinical diagnosis and treatment. Methods Spatial transcriptomics (n=4) and RNA sequencing data (n=952) were used to identify critical regulators of pTLS density and evaluate their prognostic significance in HCC. Baseline MRI images from 660 patients with HCC who had undergone surgery treatment between October 2015 and January 2023 were retrospectively recruited for model development and validation. This included training (n=307) and temporal validation (n=76) cohorts from Xiangya Hospital, and external validation cohorts from three independent hospitals (n=277). Radiomic features were extracted from intratumoral and peritumoral regions of interest and analyzed using machine learning algorithms to develop a predictive classifier. The classifier’s performance was evaluated using the area under the curve (AUC), with prognostic and predictive value assessed across four independent cohorts and in a dual-center outcome cohort of 41 patients who received immunotherapy. Results Patients with HCC and a high pTLS density experienced prolonged median overall survival (p<0.05) and favorable immunotherapy response (p=0.03). Moreover, immune infiltration by mature B cells was observed in the high pTLS density region. Spatial pseudotime analysis and immunohistochemistry staining revealed that expansion of pTLS in HCC was associated with elevated CXCL9 and CXCL10 co-expression. We developed an optimal radiomic-based classifier with excellent discrimination for predicting pTLS density, achieving an AUC of 0.91 (95% CI 0.87, 0.94) in the external validation cohort. This classifier also exhibited promising stratification ability in terms of overall survival (p<0.01), relapse-free survival (p<0.05), and immunotherapy response (p<0.05). Conclusion We identified key regulators of pTLS density in patients with HCC and proposed a non-invasive radiomic classifier capable of assisting in stratification for prognosis and treatment.

Background: Intratumoral tertiary lymphoid structures (iTLS) in hepatocellular carcinoma (HCC) are associated with improved survival and may influence treatment decisions. However, their non-invasive detection remains challenging in HCC. We aim to develop a non-invasive model using baseline contrast-enhanced MRI to predict the iTLS status. Methods: A total of 660 patients with HCC who underwent surgery were retrospectively recruited from four centers between October 2015 and January 2023 and divided into training, internal test, and external validation sets. After features dimensionality and selection, corresponding features were used to construct transfer learning radiomic (TLR) models for diagnosing iTLS, and model interpretability was explored with pathway analysis in The Cancer Genome Atlas-Liver HCC. The performances of models were assessed using the area under the receiver operating characteristic curve (AUC). The log-rank test was used to evaluate the prognostic value of the TLR model. The combination therapy set of 101 patients with advanced HCC treated with first-line anti-programmed death 1 or ligand 1 plus antiangiogenic treatment between January 2021 and January 2024 was used to investigate the value of the TLR model for evaluating the treatment response. Results: The presence of iTLS was identified in 46.0% (n=308) patients. The TLR model demonstrated excellent performance in predicting the presence of iTLS in training (AUC=0.91, 95% CI: 0.87, 0.94), internal test (AUC=0.85, 95% CI: 0.77, 0.93) and external validation set (AUC=0.85, 95% CI: 0.81, 0.90). The TLR model-predicted iTLS group has favorable overall survival (HR=0.66; 95% CI: 0.48, 0.90; p=0.007) and relapse-free survival (HR=0.64; 95% CI: 0.48, 0.85; p=0.001) in the external validation set. The model-predicted iTLS status was associated with inflammatory response and specific tumor-associated signaling activation (all p<0.001). The proportion of treatment responders was significantly higher in the model-predicted group with iTLS than in the group without iTLS (36% vs 13.73%, p=0.009). Conclusion: The TLR model has indicated accurate prediction of iTLS status, which may assist in the risk stratification for patients with HCC in clinical practice.

The mechanism of cuproptosis, a novel copper-induced cell death by regulating tricarboxylic acid cycle (TCA)-related genes, has been reported to regulate oxidative phosphorylation system (OXPHOS) in cancers and can be regarded as potential therapeutic strategies in cancer; however, the characteristics of cuproptosis in pan-cancer have not been elucidated. The multi-omics data of The Cancer Genome Atlas were used to evaluate the cuproptosis-associated characteristics across 32 tumor types. A cuproptosis enrichment score (CEScore) was established using a single sample gene enrichment analysis (ssGSEA) in pan-cancer. Spearman correlation analysis was used to identify pathway most associated with CEScore. Lasso-Cox regression was used to screen prognostic genes associated with OXPHOS and further construct a cuproptosis-related prognostic model in clear cell renal cell carcinoma (ccRCC). We revealed that most cuproptosis-related genes (CRGs) were differentially expressed between tumors and normal tissues, and somatic copy number alterations contributed to their aberrant expression. We established a CEScore index to indicate cuproptosis status which was associated with prognosis in most cancers. The CEScore was negatively correlated with OXPHOS and significantly featured prognosis in ccRCC. The ccRCC patients with high-risk scores show worse survival outcomes and bad clinical benefits of Everolimus (mTOR inhibitor). Our findings indicate the importance of abnormal CRGs expression in cancers. In addition, identified several prognostic CRGs as potential markers for prognostic distinction and drug response in the specific tumor. These results accelerate the understanding of copper-induced death in tumor progression and provide cuproptosis-associated novel therapeutic strategies.

Postoperative adjuvant chemotherapy followed surgery is the standard management for localized advanced colorectal carcinoma (CRC). Mucinous adenocarcinoma (MAC) is a peculiar histological subtype of CRC, but the prognosis of MAC patients is controversial. The objective of this study is to assess the implication of MAC in survival of patients treated with surgery and firs-line adjuvant chemotherapy. Studies describing outcomes for advanced MAC and non-specific adenocarcinoma (AC) of CRC patients treated with first-line postoperative adjuvant chemotherapy followed surgery were searched in PubMed, Embase, Medline, EBSCO, Wiley, and Cochrane Library (January 1963-August 2021). Hazard ratios (HRs) of overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS) for MAC to AC were extracted. Random-effects model was used for calculating the pooled HRs and 95% confidence interval (CI). This meta-analysis is comprised of 8 studies involving a total of 124,303 CRC patients treated with first-line adjuvant chemotherapy followed surgery. The pooled HR for MAC was 1.23 (95% CI, 1.07-1.41, p < 0.01, I² = 80%), and the DFS (HR, 2.95, 95% CI, 1.22-7.14) of MAC patients were significantly poorer than AC patients. Similar results were also observed in stage III and FOLFOX regimen subgroups. MAC was a risk factor for prognosis of localized advanced CRC patients treated with postoperative first-line adjuvant chemotherapy. Thus, the role of first-line adjuvant chemotherapy regimens should be further studied in these MAC patients.

Tripartite motif-containing 24 (TRIM24), also known as transcriptional intermediary factor 1α (TIF1α), is the founding member of TIF1 family. Recent evidence indicates that aberrant expression of TRIM24, functions as an oncogene, is associated with poor prognosis across various cancer types. TRIM24 exhibits a multifaceted structure comprising an N-terminal TRIM region with a RING domain, B-box type 1 and type 2 domains, and a coiled-coil region, as well as a C-terminal plant-homeodomain (PHD)-bromodomain. The bromodomain serves as a ‘reader’ of epigenetic histone marks, regulating chromatin structure and gene expression by linking associated proteins to acetylated nucleosomal targets, thereby controlling transcription of genes. Notably, bromodomains have emerged as compelling targets for cancer therapeutic development. In addition, TRIM24 plays specialized roles as a signal transduction molecule, orchestrating various cellular signaling cascades in cancer cells. Herein, we review the recent advancements in understanding the functions of TRIM24, and demonstrate the research progress in utilizing TRIM24 as a target for cancer therapy.