The development and progression of gastric cancer (GC) is greatly influenced by gastric microbiota and their metabolites. Here, we characterized the gastric microbiome and metabolome profiles of 37 GC tumor tissues and matched non-tumor tissues using 16s rRNA gene sequencing and ultrahigh performance liquid chromatography tandem mass spectrometry, respectively. Microbial diversity and richness were higher in GC tumor tissues than in non-tumor tissues. The abundance of Helicobacter was increased in non-tumor tissues, while the abundance of Lactobacillus, Streptococcus, Bacteroides, Prevotella, and 6 additional genera was increased in the tumor tissues. The untargeted metabolome analysis revealed 150 discriminative metabolites, among which the relative abundance of the amino acids, carbohydrates and carbohydrate conjugates, glycerophospholipids, and nucleosides was higher in tumor tissues compared to non-tumor tissues. The targeted metabolome analysis further demonstrated that the combination of 1-methylnicotinamide and N-acetyl-D-glucosamine-6-phosphate could serve as a robust biomarker for distinction between GC tumors and non-tumor tissues. Correlation analysis revealed that Helicobacter and Lactobacillus were negatively and positively correlated with the majority of differential metabolites in the classes of amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids, respectively, suggesting that Helicobacter and Lactobacillus might play a role in degradation and synthesis of the majority of differential metabolites in these classes, respectively. Acinetobacter, Comamonas, Faecalibacterium, Sphingomonas, and Streptococcus were also significantly correlated with many differential amino acids, carbohydrates, nucleosides, nucleotides, and glycerophospholipids. In conclusion, the differences in metabolome profiles between GC tumor and matched non-tumor tissues may be partly due to the collective activities of Helicobacter, Lactobacillus, and other bacteria, which eventually affects GC carcinogenesis and progression.

Bladder cancer (BCa) is the tenth most common tumor in humans. DNA damage repair genes (DDRGs) play important roles in many malignant tumors; thus, their functions in BCa should also be explored. We performed a comprehensive analysis of the expression profiles of DDRGs in 410 BCa tumors and 19 normal tissues from The Cancer Genome Atlas database. We identified 123 DDRGs differentially expressed between BCa tumors and normal tissues, including 95 upregulated and 28 downregulated genes. We detected 22 DDRGs associated with overall survival (OS) of patients with BCa by performing univariate Cox regression analysis. To explore the interactions between OS-associated DDRGs, we constructed a PPI network, which showed that the top six DDRGs (CDCA2, FOXM1, PBK, RRM2, ORC1, and HDAC4) with the highest scores in the PPI network might play significant roles in OS of BCa. Moreover, to investigate the latent regulatory mechanism of these OS-associated DDRGs, we analyzed the transcription factors (TFs)-DDRGs regulatory network. The core seven TFs (NCAPG, DNMT1, LMNB1, BRCA1, E2H2, CENPA, and E2F7) were shown to be critical regulators of the OS-related DDRGs. The 22 DDRGs were incorporated into a stepwise multivariable Cox analysis. Then, we built the index of risk score based on the expression of 8 DDRGs (CAD, HDAC10, JDP2, LDLR, PDGFRA, POLA2, SREBF1, and STAT1). The p-value < 0.0001 in the Kaplan–Meier survival plot and an area under the ROC curve (AUC) of 0.771 in TCGA-BLCA training dataset suggested the high specificity and sensitivity of the prognostic index. Furthermore, we validated the risk score in the internal TCGA-BLCA and an independent GSE32894 dataset, with AUC of 0.743 and 0.827, respectively. More importantly, the multivariate Cox regression and stratification analysis demonstrated that the predictor was independent of various clinical parameters, including age, tumor stage, grade, and number of positive tumor lymph nodes. In summary, a panel of 8 DNA damage repair genes associated with overall survival in bladder cancer may be a useful prognostic tool.

GPX4 has attracted much attention as a key molecule of cell ferroptosis, but its role in cell apoptosis is rarely reported, and its role in apoptosis of thyroid cancer (TC) cell has not been reported. The analysis of TCGA database showed that both GPX4 and FKBP8 were highly expressed in TC tumor tissues; The expression of GPX4 and FKBP8 were positively correlated. The immunohistochemical analysis further confirmed that GPX4 and FKBP8 were highly expressed in TC tumor tissues. In addition, the high expression of GPX4 and FKBP8 were both significantly correlated with the poor prognosis of TC. Silencing GPX4 significantly inhibited the proliferation, induced apoptosis of TC cells, and reduced tumor growth in mice. The co-immunoprecipitation assay revealed a physical interaction between GPX4 and FKBP8 observed in the TC cells. Knockdown of FKBP8 significantly inhibited the proliferation and induced apoptosis of TC cells. Rescue experiments suggested that knockdown of FKBP8 could reverse the strengthens of cell proliferation and apoptosis and the higher expression of FKBP8 and Bcl-2 caused by overexpression of GPX4. Our results suggest that the GPX4/FKBP8/Bcl-2 axis promotes TC development by inhibiting TC cell apoptosis, which provides potential molecular targets for TC therapeutic strategies.

Aim: Small extracellular vesicles (sEVs) are promising noninvasive biomarkers for several malignancies, including thyroid carcinoma (TC). However, their heterogeneity is frequently overlooked in bulk-level analyses. Methods: Plasma samples from TC and healthy controls (HC) were collected for a proximity-dependent barcoding assay (PBA) to identify plasma sEV biomarkers at the single-sEV level. We screened the potential biomarkers using the Panel260 (the panel that detects 260 proteins) of PBA in Cohort 1, and validated them using Panel550 (the panel that detects 550 proteins) in Cohort 2. Results: Plasma exosome counts were significantly elevated in TC compared with those in HC in both Cohort 1 and Cohort 2. Receiver operating characteristic curve analysis showed that sEV counts exhibited an area under the curve > 0.75 in both cohorts. The sEV proteomic analysis revealed that sEV epithelial cell adhesion molecule (EPCAM) levels were significantly increased, whereas claudin-11, integrin alpha X, and lymphocyte-activating 3 were significantly decreased in TC compared with HC. The increase in EPCAM in the plasma and tumor tissues was confirmed by enzyme-linked immunosorbent assay and immunohistochemistry analyses, respectively. The sEV subpopulation analysis further demonstrated that EPCAM+ sEVs were significantly elevated in TC compared with HC in both cohorts. The reduction in sEV counts was observed in 18 out of 20 patients after the operation. The decrease in EPCAM+ sEVs was observed in 20 patients with TC post-operatively, whereas the reduction in the conventional biomarker serum thyroglobulin (Tg) was observed in 14 patients. TC-derived plasma sEVs promoted TC cell proliferation, migration, invasion, and TC xenograft growth. Conclusion: EPCAM+ sEVs could serve as a promising biomarker for the early diagnosis of TC and perform better in monitoring post-operative remission of TC than serum Tg.

Anaplastic thyroid carcinoma (ATC) is an exceptionally aggressive malignancy with dismal survival, largely due to intrinsic cisplatin resistance. This study identifies a novel mechanism by which small extracellular vesicles (sEVs) promote chemoresistance by enhancing DNA repair via protein lactylation. ATC cells secrete sEVs enriched with Annexin A2 (ANXA2). Upon delivery to recipient ATC cells, ANXA2 stabilizes the interaction between SRC kinase and lactate dehydrogenase A (LDHA), leading to increased LDHA phosphorylation (Y10), enzyme activity, and lactate production. The resulting lactate surge serves as a substrate for lysine lactylation. Ku80 (XRCC5) is identified as a key lactylation target at K265, catalyzed by the acyltransferase KAT5. This lactylation modification strengthens the interaction between Ku80 and its partner Ku70 (XRCC6), stabilizing the initial DNA‐end binding complex in the non‐homologous end‐joining (NHEJ) repair pathway. Consequently, NHEJ efficiency is significantly enhanced, enabling ATC cells to rapidly repair cisplatin‐induced DNA double‐strand breaks and survive treatment. Genetic disruption of the XRCC5‐K265 lactylation site or pharmacological inhibition of LDHA sensitizes ATC xenograft tumors to cisplatin, while in vitro, inhibition of the SRC/LDHA axis produces a similar chemosensitizing effect. This work unveils the ANXA2 ⁺ sEV/SRC/LDHA/lactate/XRCC5‐lactylation axis as a critical driver of NHEJ‐mediated chemoresistance in ATC, offering new potential therapeutic targets.