SPOP promotes cervical cancer progression by inducing the movement of PD-1 away from PD-L1 in spatial localization

Unraveling role of ubiquitination in drug resistance of gynecological cancer

Chemotherapy is the principal treatment for advanced cancer patients. However, chemotherapeutic resistance, an important hallmark of cancer, is considered as a key impediment to effective therapy in cancer patients. Multiple signaling pathways and factors have been underscored to participate in governing drug resistance. Posttranslational modifications, including ubiquitination, glycosylation, acetylation and phosphorylation, have emerged as key players in modulating drug resistance in gynecological tumors, such as ovarian cancer, cervical cancer and endometrial cancer. In this review article, we summarize the role of ubiquitination in governing drug sensitivity in gynecological cancers. Moreover, we describe the numerous compounds that target ubiquitination in gynecological cancers to reverse chemotherapeutic resistance. In addition, we provide the future perspectives to fully elucidate the mechanisms by which ubiquitination controls drug resistance in gynecological tumors, contributing to restoring drug sensitivity. This review highlights the complex interplay between ubiquitination and drug resistance in gynecological tumors, providing novel insights into potential therapeutic targets and personalized treatment strategies to overcome the bottleneck of drug resistance.

PARP1-stabilised FOXQ1 promotes ovarian cancer progression by activating the LAMB3/WNT/β-catenin signalling pathway

Metastasis is an important factor that causes ovarian cancer (OC) to become the most lethal malignancy of the female reproductive system, but its molecular mechanism is not fully understood. In this study, through bioinformatics analysis, as well as analysis of tissue samples and clinicopathological characteristics and prognosis of patients in our centre, it was found that Forkhead box Q1 (FOXQ1) was correlated with metastasis and prognosis of OC. Through cell function experiments and animal experiments, the results show that FOXQ1 can promote the progression of ovarian cancer in vivo and in vitro. Through RNA-seq, chromatin immunoprecipitation sequencing (ChIP-seq), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Western blotting (WB), quantitative real-time polymerase chain reaction (qRT‒PCR), immunohistochemistry (IHC), luciferase assay, and ChIP-PCR, it was demonstrated that FOXQ1 can mediate the WNT/β-catenin pathway by targeting the LAMB promoter region. Through coimmunoprecipitation (Co-IP), mass spectrometry (MS), ubiquitination experiments, and immunofluorescence (IF), the results showed that PARP1 could stabilise FOXQ1 expression via the E3 ubiquitin ligase Hsc70-interacting protein (CHIP). Finally, the whole mechanism pathway was verified by animal drug combination experiments and clinical specimen prognosis analysis. In summary, our results suggest that PARP1 can promote ovarian cancer progression through the LAMB3/WNT/β-catenin pathway by stabilising FOXQ1 expression.

The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma

Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

BACKGROUND

Cervical cancer (CC) is highly lethal and aggressive with an increasing trend of mortality for females. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response.

METHODS

The mRNAs expression data of CC patients and cellular senescence-related genes were obtained from the Cancer Genome Atlas (TCGA) and CellAge databases, respectively. Differentially expressed genes (DEGs) of senescence related genes between tumor and normal tissues were used for Least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. Univariate and LASSO regression analyses were applied to establish a predictive nomogram. The performance of the nomogram were evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index), and calibration curve. GSE44001 and GSE52903 were used for external validation.

RESULTS

We established a cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of CC patients in the TCGA database. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS, P =2.021e-05). The area under the ROC curve (AUC) of this model was 0.743 for OS. Multivariate analysis found that the 6-gene risk signature (HR=3.166, 95%CI: 1.660-6.041, P<0.001) was an independent risk factor for CC patients. We then designed an OS-associated nomogram that included the risk signature and clinicopathological factors. The AUC reached 0.860 for predicting 5-year OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Two external GEO validations were corresponding to the gene expression pattern in TCGA.

CONCLUSIONS

Our results suggested a six-senescence related signature and established a prognostic nomogram that reliably predicted the overall survival for CC. These findings may be beneficial to personalized treatment and medical decision-making.

Developing a nomogram for preoperative prediction of cervical cancer lymph node metastasis by multiplex immunofluorescence

BACKGROUND

Most traditional procedures can destroy tissue natural structure, and the information on spatial distribution and temporal distribution of immune milieu in situ would be lost. We aimed to explore the potential mechanism of pelvic lymph node (pLN) metastasis of cervical cancer (CC) by multiplex immunofluorescence (mIF) and construct a nomogram for preoperative prediction of pLN metastasis in patients with CC.

METHODS

Patients (180 IB1-IIA2 CC patients of 2009 FIGO (International Federation of Gynecology and Obstetrics)) were divided into two groups based on pLN status. Tissue microarray (TMA) was prepared and tumor-infiltrating immune markers were assessed by mIF. Multivariable logistic regression analysis and nomogram were used to develop the predicting model.

RESULTS

Multivariable logistic regression analysis constructs a predictive model and the area under the curve (AUC) can reach 0.843. By internal validation with the remaining 40% of cases, a new ROC curve has emerged and the AUC reached 0.888.

CONCLUSIONS

This study presents an immune nomogram, which can be conveniently used to facilitate the preoperative individualized prediction of LN metastasis in patients with CC.

The E3 ubiquitin ligases regulate PD-1/PD-L1 protein levels in tumor microenvironment to improve immunotherapy

The tumor microenvironment (TME) is the tumor surrounding environment, which is critical for tumor development and progression. TME is also involved in clinical intervention and treatment outcomes. Modulation of TME is useful for improving therapy strategies. PD-L1 protein on tumor cells interacts with PD-1 protein on T cells, contributing to T cell dysfunction and exhaustion, blockage of the immune response. Evidence has demonstrated that the expression of PD-1/PD-L1 is associated with clinical response to anti-PD-1/PD-L1 therapy in cancer patients. It is important to discuss the regulatory machinery how PD-1/PD-L1 protein is finely regulated in tumor cells. In recent years, studies have demonstrated that PD-1/PD-L1 expression was governed by various E3 ubiquitin ligases in TME, contributing to resistance of anti-PD-1/PD-L1 therapy in human cancers. In this review, we will discuss the role and molecular mechanisms of E3 ligases-mediated regulation of PD-1 and PD-L1 in TME. Moreover, we will describe how E3 ligases-involved PD-1/PD-L1 regulation alters anti-PD-1/PD-L1 efficacy. Altogether, targeting E3 ubiquitin ligases to control the PD-1/PD-L1 protein levels could be a potential strategy to potentiate immunotherapeutic effects in cancer patients.

A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma

Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients' prognosis. Herein, a panel of immune-related genes was established for more accurate prognostic prediction. Methods: The transcriptome information of tumor and normal samples were obtained from TCGA-CSCC and GTEx. Differentially expressed genes (DEGs) were defined from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data which not mentioned in GSE44001, IR-DEGs were preliminarily identified. Then, TCGA-CSCC samples were divided into training and testing set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the signature to predict the overall survival (OS) and disease-free survival (DFS). External validation was performed in GSE44001, and initial clinical validation was performed by qRT-PCR. Function enrichment analysis, immune infiltration analysis and establishment of nomogram were conducted as well. Results: A prognostic prediction signature consisting of seven IR-DEGs was established. High expression of NRP1, IGF2R, SERPINA3, TNF and low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809. Analyses in other validation sets showed good consistency with the results in training set. The signature can serve as an independent prognostic factor for OS (HR = 1.166, p < 0.001). AUC values of 1-, 3-, five- year OS based on the nomogram were 0.769, 0.820 and 0.807. Functional enrichment analysis suggested that these IR-DEGs were associated with receptor interaction and immune cell activity. Immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Through qRT-PCR on clinical samples, expression of NRP1, IGF2R, SERPINA3 and TNF were significantly upregulated in tumor tissue, while ICOS and DES were significantly downregulated. Conclusion: To conclude, the immune-related signature can provide strong support for exploration of immune infiltration, prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.