Accumulating evidence indicates that metabolic reprogramming of cancer cells supports the energy and metabolic demands during tumor metastasis. However, the metabolic alterations underlying lymph node metastasis (LNM) of cervical cancer (CCa) have not been well recognized. In the present study, it is found that lymphatic metastatic CCa cells have reduced dependency on glucose and glycolysis but increased fatty acid oxidation (FAO). Inhibition of carnitine palmitoyl transferase 1A (CPT1A) significantly compromises palmitate‐induced cell stemness. Mechanistically, FAO‐derived acetyl‐CoA enhances H3K27 acetylation (H3K27Ac) modification level in the promoter of stemness genes, increasing stemness and nodal metastasis in the lipid‐rich nodal environment. Genetic and pharmacological loss of CPT1A function markedly suppresses the metastatic colonization of CCa cells in tumor‐draining lymph nodes. Together, these findings propose an effective method of cancer therapy by targeting FAO in patients with CCa and lymph node metastasis.

Cuproptosis is a novel form of regulated cell death triggered by copper ion and copper ionophore. While cuproptosis has been actively explored as a potential target for cancer therapy, its role in ovarian cancer (OC) still remains unclear. In this study, we demonstrate that cuproptosis inhibits OC cell proliferation, migration, and invasion through FDX1 regulation and suppresses tumor growth in a mouse model. We also confirm that cuproptosis enhances OC sensitivity to cisplatin treatment both in vivo and in vitro. Moreover, our findings reveal that cuproptosis affects cholesterol biosynthesis in OC cells, with cholesterol playing a crucial role in its cytotoxic effect. Taken together, our results elucidate the effect of cuproptosis in OC and suggest it as a promising therapeutic strategy.

Lymph node metastasis (LNM), a hallmark of aggressive cervical cancer (CCa), severely compromises prognosis and limits therapeutic efficacy. Despite its clinical significance, the molecular mechanisms driving LNM in CCa remain poorly characterized, necessitating urgent exploration. In this study, leveraging an in vitro lymphangiogenesis screening model, we identified CREB5 as a gene markedly upregulated in metastatic CCa, with its expression strongly correlating with LNM and poor patient survival. Mechanistic investigations revealed that CREB5 transcriptionally activates apelin (APLN) by directly binding to its canonical TGACG motif in the promoter region, thereby driving APLN-mediated lymphangiogenesis. Inhibition of CREB5 or treatment with ML221, a selective APLN receptor (APLNR) antagonist, potently suppressed lymphatic metastasis in preclinical CCa models. These findings establish CREB5 as a critical regulator of APLN-dependent lymphangiogenesis and LNM, highlighting its potential as a dual diagnostic biomarker and therapeutic target for mitigating lymphatic dissemination in CCa patients.

Lymph node metastasis (LNM) confers significant treatment failure and adverse clinical outcomes in cervical cancer (CCa). However, large unknown lies in the mechanisms underlying LNM in CCa. In this study, we discovered that PRDX3 is elevated in CCa with LNM and associates with poor prognosis in CCa patients. Moreover, multivariate logistic analysis revealed that PRDX3 is an independent predictor of LNM in CCa. Functional investigations demonstrated that PRDX3 promotes invasion, lymphangiogenesis, and LNM of CCa. Mechanistically, PRDX3 activates NF-κB signaling pathway and upregulates the downstream pro-metastatic molecules VEGF-C and MMP-9 in CCa cells. Furthermore, PRDX3 could inhibit the anoikis of detached CCa cells by reducing the ROS level and hence promote LNM in CCa. Importantly, genetic inhibition of PRDX3 potently slows LNM of CCa. These findings highlight a novel PRDX3-mediated mechanism of LNM in CCa and recognize PRDX3 as a promising predictive marker and target of clinical intervention for LNM in CCa.

Existing biomarkers for epithelial ovarian cancer (EOC) have demonstrated limited sensitivity and specificity. This study aimed to investigate plasma protein and metabolite characteristics of EOC and identify novel biomarker candidates for noninvasive diagnosis and differential diagnosis. In this prospective diagnostic cohort study, plasma was preoperatively collected from 536 consecutive patients presenting with imaging-suspected adnexal masses, uterine fibroids, or pelvic organ prolapse. After exclusions, the final cohort comprised 251 participants: EOC (n = 97), borderline ovarian tumors (n = 38), benign ovarian tumors (n = 54), and healthy controls (n = 62). Proteomic and metabolomic profiling was performed. A machine learning model was trained on a training cohort (34 EOC patients and 62 non-OC individuals [borderline, benign, and healthy controls]) to distinguish EOC from other groups. The model was validated in two independent cohorts: validation cohort 1 (n = 25) and validation cohort 2 (n = 130) using targeted proteomics and untargeted metabolomics. External transcriptomic datasets (TCGA-OV, GTEx bulk RNA-seq; GSE180661 scRNA-seq) were leveraged to validate TDO2 upregulation in ovarian cancer tissues, particularly in fibroblasts. This TDO2 upregulation were experimentally confirmed through quantitative PCR, immunohistochemistry, and immunofluorescence using clinical specimens. We identified significant protein alterations in EOC patients’ plasma, implicating dysregulated metabolic and PI3K-Akt signaling pathways. Metabolite analysis further revealed aberrant sphingolipid metabolism, steroid hormone biosynthesis, and tryptophan metabolism in EOC patients’ plasma. A diagnostic panel comprising 4 proteins (LRG1, ITIH3, PDIA4, and PON1) and 3 metabolites (kynurenine, indole, and 3-hydroxybutyrate) achieved an AUC of 0.975 (95% CI 0.943–0.997) with 95.2% sensitivity and 91.2% specificity in the training cohort. Critically, the model demonstrated robust generalizability in two independent validation cohorts: validation cohort 1 (AUC = 0.962, 95% CI 0.878–1.000) and validation cohort 2 (AUC = 0.965, 95% CI 0.921–0.995). Furthermore, fibroblasts with high expression of tryptophan 2,3-dioxygenase are contributing factors to elevated levels of kynurenine. Our findings provide novel insights into the EOC metabolic and protein landscape. We developed and validated a plasma classifier demonstrating high sensitivity and specificity, which effectively distinguishes EOC patients from non-OC individuals. This classifier could enhance preoperative diagnostic accuracy and aid in differential diagnosis.

The clinical benefit of anti-programmed cell death protein 1 (PD-1)-based immunotherapy among patients with microsatellite instable (MSI) endometrial cancer (EC) precedes that of microsatellite stable (MSS) EC, the mechanisms of which have not been fully understood. Circular RNAs (circRNAs) were reported to modulate immune evasion in several types of malignancies, while their roles in the immune regulation in EC remain largely unknown. Here, we conducted circRNA array analysis and mRNA-Sequencing of 10 MSI EC samples and 10 MSS EC samples and identified 1083 differentially expressed circRNAs (DE-circRNAs) and 864 differentially expressed mRNAs, based on which we constructed a circRNA-miRNA-mRNA comprehensive network consisting of 35 DE-circRNAs, 56 predicted miRNAs and 24 differentially expressed mRNAs. Finally, we confirmed hsa_circ_0058230 being positively correlated with CD8+ T cells infiltration, suggesting that it might take a part in anti-tumor immunity in EC.