RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment

The RNA-binding protein sorbin and SH3 domain-containing 2 are transcriptionally regulated by specificity protein 1 and function as tumor suppressors in bladder cancer by stabilizing tissue factor pathway inhibitor

Sorbin and SH3 domain-containing 2 (SORBS2) is an RNA-binding protein and has been implicated in the development of some cancers. However, its role in bladder cancer (BC) is yet to be established. The expression of SORBS2 in BC tissues was determined from the Gene Expression Omnibus and Gene Expression Profiling Interactive Analysis databases and collected paired tumor/normal samples. The effects of SORBS2 on BC cells were detected by CCK-8, colony formation, Transwell, dual-luciferase, RNA immunoprecipitation, chromatin immunoprecipitation, and DNA pull-down assays. In vivo, BC cell growth and metastasis were studied by a xenograft subcutaneous model and a tail-vein metastasis model. The results showed that SORBS2 expression was significantly decreased in BC tissues and cells. SORBS2 overexpression inhibited cell proliferation, migration, invasion, and epithelial-mesenchymal transition in vitro and tumor growth and metastasis in vivo, while silencing SORBS2 produced the opposite effect. Mechanistically, we found that SORBS2 enhanced the stability of tissue factor pathway inhibitor (TFPI) mRNA via direct binding to its 3' UTR. Restoration of TFPI expression reversed SORBS2 knockdown-induced malignant phenotypes of BC cells. In addition, SORBS2 expression was negatively regulated by the transcription factor specificity protein 1 (SP1). Conversely, SORBS2 can be transcriptionally regulated by SP1 and inhibit BC cell growth and metastasis via stabilization of TFPI mRNA, indicating SORBS2 may be a promising therapeutic target for BC.

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) still present a huge threaten to women's health, especially the local advanced patients. Hence, developing more effectiveness prognostic signatures is urgently needed. This study constructed and verified a robust RNA-binding proteins (RBPs) related signature through a series of bioinformatics methods and explored the biological function of hub RBP in vitro experiments. As a result, the 10 RBPs signature was successfully established and could act as an independent prognostic biomarker in CESC patients, which displayed the highest sensitivity and specificity in prognosis prediction compared with other clinicopathological parameters. The risk model also presented good performance in risk stratification among CESC patients. Besides, a nomogram was constructed based on pathological stage and the risk signature and exhibited satisfactory accuracy in prognosis prediction. Functional enrichment indicated that the risk signature mainly participated in immune-related pathways and cancer-related pathways, and the infiltration level of immune cells and immune checkpoints showed a significantly higher degree in low-risk patients compared with high-risk patients. Notably, the 10 RBPs signature act as a novel biomarker in immunotherapy and chemotherapy response. In addition, PRPF40B was selected as hub RBP and its transcription and translation levels were obviously increased in CESC tissues, as well as Hela and Siha cells. Knockdown of PRPF40B inhibits the proliferation, migration and invasion of Hela and Siha cells in vitro. In conclusion, our research provides a noticeable strategy in prognostic prediction among CESC patients, which may illuminate the prospect of CESC patients' clinical outcome.

Identification of a basement membrane-related genes signature with immune correlation in bladder urothelial carcinoma and verification in vitro

BACKGROUND

Bladder urothelial carcinoma (BLCA) is the most common genitourinary cancer and the prognosis of patients is often poor. However, studies of basement membrane-related genes (BM-related genes) in BLCA are less reported. Therefore, we established a BM-related genes signature to explore their functional and prognostic value in BLCA.

METHODS

In this study, a BM-related genes signature was constructed by LASSO-Cox regression analysis, and then a series of bioinformatics methods was used to assess the accuracy and validity of the signature. We constructed a nomogram for clinical application and also screened for possible therapeutic drugs. To investigate the functions and pathways affected by BM-related genes in BLCA, we performed functional enrichment analyses. In addition, we analyzed the immune cell infiltration landscape and immune checkpoint-related genes in the high and low-risk groups. Finally, we confirmed the prognostic value of BM-related genes in BLCA in vitro.

RESULTS

Combining multiple bioinformatics approaches, we identified a seven-gene signature. The accuracy and validity of this signature in predicting BLCA patients were confirmed by the test cohort. In addition, the risk score was strongly correlated with prognosis, immune checkpoint genes, drug sensitivity, and immune cell infiltration landscape. The risk score is an independent prognostic factor for BLCA patients. Further experiments revealed that all seven signature genes were differentially expressed between BLCA cell lines and normal bladder cells. Finally, overexpression of LAMA2 inhibited the migration and invasion ability of BLCA cell lines.

CONCLUSIONS

In summary, the BM-related genes signature was able to predict the prognosis of BLCA patients accurately, indicating that the BM-related genes possess great clinical value in the diagnosis and treatment of BLCA. Moreover, LAMA2 could be a potential therapeutic target, which provides new insights into the application of the BM-related genes in BLCA patients.

Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancer

Background: Ovarian cancer (OC) is the most troubling malignant tumor of the female reproductive system. It has a low early diagnosis rate and a high tumor recurrence rate after treatment. Immunogenic cell death (ICD) is a unique form of regulated cell death that can activate the adaptive immune system through the release of DAMPs and cytokines in immunocompromised hosts and establish long-term immunologic memory. Therefore, this study aims to explore the prognostic value and underlying mechanisms of ICD-related genes in OC on the basis of characteristics.

Methods: The gene expression profiles and related clinical information of OC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. ICD-related genes were collected from the Genecards database. ICD-related prognostic genes were obtained by intersecting ICD-related genes with the OC prognostic-related genes that were analyzed in the TCGA database. Functional enrichment, genetic mutation, and immune infiltration correlation analyses were further performed to identify underlying mechanisms. Subsequently, we developed a TCGA cohort-based prognostic risk model that included a nine-gene signature through univariate and multivariate Cox regression and LASSO regression analyses. Meanwhile, external validation was performed on two sets of GEO cohorts and the TCGA training cohort for three other common tumors in women. In addition, a nomogram was established by integrating clinicopathological features and ICD-related gene signature to predict survival probability. Finally, functional enrichment and immune infiltration analyses were performed on the two risk subgroups.

Results: By utilizing nine genes (ERBB2, RB1, CCR7, CD38, IFNB1, ANXA2, CXCL9, SLC9A1, and SLAMF7), we constructed an ICD-related prognostic signature. Subsequently, patients were subdivided into high- and low-risk subgroups in accordance with the median value of the risk score. In multivariate Cox regression analyses, risk score was an independent prognostic factor (hazard ratio = 2.783; p < 0.01). In the TCGA training cohort and the two GEO validation cohorts, patients with high-risk scores had worse prognosis than those with low-risk scores (p < 0.05). The time-dependent receiver operating characteristic curve further validated the prognostic power of the gene signature. Finally, gene set enrichment analysis indicated that multiple oncological pathways were significantly enriched in the high-risk subgroup. By contrast, the low-risk subgroup was strongly related to the immune-related signaling pathways. Immune infiltration analysis further illustrated that most immune cells showed higher levels of infiltration in the low-risk subgroup than in the high-risk subgroup.

Conclusion: We constructed a novel ICD-related gene model for forecasting the prognosis and immune infiltration status of patients with OC. In the future, new ICD-related genes may provide novel potential targets for the therapeutic intervention of OC.

Efficacy evaluation of multi-immunotherapy in ovarian cancer: From bench to bed

Ovarian cancer, one of the most common gynecological malignancies, is characterized by high mortality and poor prognosis. Cytoreductive surgery and chemotherapy remain the mainstay of ovarian cancer treatment, and most women experience recurrence after standard care therapies. There is compelling evidence that ovarian cancer is an immunogenic tumor. For example, the accumulation of tumor-infiltrating lymphocytes is associated with increased survival, while increases in immunosuppressive regulatory T cells are correlated with poor clinical outcomes. Therefore, immunotherapies targeting components of the tumor microenvironment have been gradually integrated into the existing treatment options, including immune checkpoint blockade, adoptive cell therapy, and cancer vaccines. Immunotherapies have changed guidelines for maintenance treatment and established a new paradigm in ovarian cancer treatment. Despite single immunotherapies targeting DNA repair mechanisms, immune checkpoints, and angiogenesis bringing inspiring efficacy, only a subset of patients can benefit much from it. Thus, the multi-immunotherapy investigation remains an active area for ovarian cancer treatment. The current review provides an overview of various clinically oriented forms of multi-immunotherapy and explores potentially effective combinational therapies for ovarian cancer.