Mining TCGA database for gene expression in ovarian serous cystadenocarcinoma microenvironment

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma

BACKGROUND

Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood.

METHODS

The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan-Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray.

RESULT

ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma.

CONCLUSION

ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Comprehensive analysis of paraspeckle-associated gene modules unveils prognostic signatures and immunological relevance in multi-cancers

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, characterized by high rates of angiogenesis and immune evasion. Paraspeckle genes, involved in gene regulation and RNA metabolism, have recently been linked to tumor progression. This study aims to elucidate the relationship between paraspeckle genes and HCC prognosis, focusing on SFPQ, DDX39B, and UBAP2.

METHODS

We analyzed HCC (LIHC) and prostate cancer (PRAD) samples from the TCGA database to explore the correlation between paraspeckle genes and angiogenesis. We conducted unsupervised clustering, risk scoring, and survival analysis to identify distinct patient groups and their clinical outcomes. Gene expression data were used to perform differential analysis and Gene Ontology (GO) enrichment.

RESULTS

Our analysis identified significant correlations between paraspeckle genes and angiogenesis across multiple cancer types. Elevated expression levels of SFPQ, DDX39B, and UBAP2 were associated with poor prognosis in HCC patients, and all of them has statistical significance. Unsupervised clustering of HCC samples based on paraspeckle gene expression revealed two distinct clusters, with high-risk patients exhibiting stronger immune suppression and tumor immune evasion. GO enrichment highlighted critical pathways related to angiogenesis and immune regulation. Additionally, a risk scoring model based on these genes effectively distinguished high-risk and low-risk patient groups, providing valuable prognostic insights.

CONCLUSION

This study demonstrates that SFPQ, DDX39B, and UBAP2 are significantly associated with poor prognosis in HCC, likely due to their roles in promoting angiogenesis and immune suppression. These findings highlight the potential of paraspeckle genes as prognostic biomarkers and therapeutic targets, offering new avenues for personalized treatment strategies in HCC. Further research into their functional mechanisms and clinical applicability is crucial for advancing HCC treatment and improving patient outcomes.

TGFBI: A novel therapeutic target for cancer

TGFBI, an extracellular matrix protein induced by transforming growth factor β, has been found to exhibit aberrant expression in various types of cancer. TGFBI plays a crucial role in tumor cell proliferation, angiogenesis, and apoptosis. It also facilitates invasion and metastasis in various types of cancer, including colon, head and neck squamous, renal, and prostate cancers. TGFBI, a prominent p-EMT marker, strongly correlates with lymph node metastasis. TGFBI demonstrates immunosuppressive effects within the tumor immune microenvironment. Targeted therapy directed at TGFBI shows promise as a potential strategy to combat cancer. Hence, a comprehensive review was conducted to examine the impact of TGFBI on various aspects of tumor biology, including cell proliferation, angiogenesis, invasion, metastasis, apoptosis, and the immune microenvironment. This review also delved into the underlying biochemical mechanisms to enhance our understanding of the research advancements related to TGFBI in the context of tumors.

GPX3 supports ovarian cancer tumor progression in vivo and promotes expression of GDF15

OBJECTIVE

We previously reported that high expression of the extracellular glutathione peroxidase GPX3 is associated with poor patient outcome in ovarian serous adenocarcinomas, and that GPX3 protects ovarian cancer cells from oxidative stress in culture. Here we tested if GPX3 is necessary for tumor establishment in vivo and to identify novel downstream mediators of GPX3's pro-tumorigenic function.

METHODS

GPX3 was knocked-down in ID8 ovarian cancer cells by shRNA to test the role of GPX3 in tumor establishment using a syngeneic IP xenograft model. RNA sequencing analysis was carried out in OVCAR3 cells following shRNA-mediated GPX3 knock-down to identify GPX3-dependent gene expression signatures.

RESULTS

GPX3 knock-down abrogated clonogenicity and intraperitoneal tumor development in vivo, and the effects were dependent on the level of GPX3 knock-down. RNA sequencing showed that loss of GPX3 leads to decreased gene expression patterns related to pro-tumorigenic signaling pathways. Validation studies identified GDF15 as strongly dependent on GPX3. GDF15, a member of the TGF-β growth factor family, has known oncogenic and immune modulatory activities. Similarly, GPX3 expression positively correlated with pro-tumor immune cell signatures, including regulatory T-cell and macrophage infiltration, and displayed significant correlation with PD-L1 expression.

CONCLUSIONS

We show for the first time that tumor produced GPX3 is necessary for ovarian cancer growth in vivo and that it regulates expression of GDF15. The immune profile associated with GPX3 expression in serous ovarian tumors suggests that GPX3 may be an alternate marker of ovarian tumors susceptible to immune check-point inhibitors.

GPX3 supports ovarian cancer tumor progression in vivo and promotes expression of GDF15

Objective

We previously reported that high expression of the extracellular glutathione peroxidase GPX3 is associated with poor patient outcome in ovarian serous adenocarcinomas, and that GPX3 protects ovarian cancer cells from oxidative stress in culture. Here we tested if GPX3 is necessary for tumor establishment in vivo and to identify novel downstream mediators of GPX3's pro-tumorigenic function.

Methods

GPX3 was knocked-down in ID8 ovarian cancer cells by shRNA to test the role of GPX3 in tumor establishment using a syngeneic IP xenograft model. RNA sequencing analysis was carried out in OVCAR3 cells following shRNA-mediated GPX3 knock-down to identify GPX3-dependent gene expression signatures.

Results

GPX3 knock-down abrogated clonogenicity and intraperitoneal tumor development in vivo, and the effects were dependent on the level of GPX3 knock-down. RNA sequencing showed that loss of GPX3 leads to decreased gene expression patterns related to pro-tumorigenic signaling pathways. Validation studies identified GDF15 as strongly dependent on GPX3. GDF15, a member of the TGF-β growth factor family, has known oncogenic and immune modulatory activities. Similarly, GPX3 expression positively correlated with pro-tumor immune cell signatures, including regulatory T-cell and macrophage infiltration, and displayed significant correlation with PD-L1 expression.

Conclusions

We show for the first time that tumor produced GPX3 is necessary for ovarian cancer growth in vivo and that it regulates expression of GDF15. The immune profile associated with GPX3 expression in serous ovarian tumors suggests that GPX3 may be an alternate marker of ovarian tumors susceptible to immune check-point inhibitors.

The TGFBI gene and protein expression in topotecan resistant ovarian cancer cell lines

PURPOSE

The primary limiting factor in achieving cures for patients with cancer, particularly ovarian cancer, is drug resistance. The mechanisms of drug resistance of cancer cells during chemotherapy may include compounds of the extracellular matrix, such as the transforming growth factor-beta-induced protein (TGFBI). In this study, we aimed to analyze the TGFBI gene and protein expression in different sensitive and drug-resistant ovarian cancer cell lines, as well as test if TGFBI can be involved in the response to topotecan (TOP) at the very early stages of treatment.

MATERIALS AND METHODS

In this study, we conducted a detailed analysis of TGFBI expression in different ovarian cancer cell lines (A2780, A2780TR1, A2780TR2, W1, W1TR, SKOV-3, PEA1, PEA2 and PEO23). The level of TGFBI mRNA (QPCR), intracellular and extracellular protein (Western blot analysis) were assessed in this study.

RESULTS

We observed upregulation of TGFBI mRNA in drug-resistant cell lines and estrogen-receptor positive cell lines, which was supported by overexpression of both intracellular and extracellular TGFBI protein. We also showed the TGFBI expression after a short period of treatment of sensitive ovarian cancer cell lines with TOP.

CONCLUSION

The expression of TGFBI in ovarian cancer cell lines suggests its role in the development of drug resistance.

RNA-Seq Analysis of Clinical Samples from TCGA Reveal Molecular Signatures for Ovarian Cancer

Identifying differentially expressed genes and co-expression modules lead to novel biomarkers. GO, pathway enrichment, network, and tumor stage analysis of 318 ovarian cancer samples from TCGA, categorised into primary and recurrent, pre-menopause and post-menopause, and early and late stage tumors was performed. Upregulated and downregulated genes in primary vs recurrent, early stage vs late-stage and pre-menopause vs post-menopause tumors were 84 and 62, 84 and 35, and 88 and 14, respectively. IRAK2 and CXCL8 had higher expression in recurrent tumors while REG1A had higher expression in post-menopause samples. In late stage tumors constant expression of IRAK2 and REG1A was observed, while that of CXCL8 and EGF decreased. These genes may be potential biomarkers for the diagnosis of the disease.

XGBG: A Novel Method for Identifying Ovarian Carcinoma Susceptible Genes Based on Deep Learning

Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.