Multi-omics analysis of tumor mutational burden combined with prognostic assessment in epithelial ovarian cancer based on TCGA database

Identification of Copper Homeostasis-Related Gene Signature for Predicting Prognosis in Patients with Epithelial Ovarian Cancer

Objectives

This research aims to establish a copper homeostasis-related gene signature for predicting the prognosis of epithelial ovarian cancer and to investigate its underlying mechanisms.

Methods

We mainly constructed the copper homeostasis-related gene signature by LASSO regression analysis. Then multiple methods were used to evaluate the independent predictive ability of the model and explored the mechanisms.

Results

The 15-copper homeostasis-related gene (15-CHRG) signature was successfully established. Utilizing an optimal cut-off value of 0.35, we divided the training dataset into high-risk and low-risk subgroups. Kaplan-Meier analysis revealed that survival times for the high-risk subgroup were significantly shorter than those in the low-risk group (P < .05). Additionally, the Area Under the Curve (AUC) of the 15-CHRG signature achieved 0.822 at 1 year, 0.762 at 3 years, and 0.696 at 5 years in the training set. COX regression analysis confirmed the 15-CHRG signature as both accurate and independent. Gene set enrichment (GSEA), Kyoto Encyclopedia of Gene and Genome (KEGG) and Gene Ontology (GO) analysis showed that there were significant differences in apoptosis, p53 pathway, protein synthesis, hydrolase and transport-related pathways between high-risk group and low-risk group. In tumor immune cell (TIC) analysis, the increased expression of resting mast cells was positively correlated with the risk score.

Conclusion

Consequently, the 15-CHRG signature shows significant potential as a method for accurately predicting clinical outcomes and treatment responses in patients with epithelial ovarian cancer.

Epithelial ovarian cancer is infiltrated by activated effector T cells co-expressing CD39, PD-1, TIM-3, CD137 and interacting with cancer cells and myeloid cells

Introduction

Despite predicted efficacy, immunotherapy in epithelial ovarian cancer (EOC) has limited clinical benefit and the prognosis of patients remains poor. There is thus a strong need for better identifying local immune dynamics and immune-suppressive pathways limiting T-cell mediated anti-tumor immunity.

Methods

In this observational study we analyzed by immunohistochemistry, gene expression profiling and flow cytometry the antigenic landscape and immune composition of 48 EOC specimens, with a focus on tumor-infiltrating lymphocytes (TILs).

Results

Activated T cells showing features of partial exhaustion with a CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ surface profile were exclusively present in EOC specimens but not in corresponding peripheral blood or ascitic fluid, indicating that the tumor microenvironment might sustain this peculiar phenotype. Interestingly, while neoplastic cells expressed several tumor-associated antigens possibly able to stimulate tumor-specific TILs, macrophages provided both co-stimulatory and inhibitory signals and were more abundant in TILs-enriched specimens harboring the CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ signature.

Conclusion

These data demonstrate that EOC is enriched in CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ T lymphocytes, a phenotype possibly modulated by antigen recognition on neoplastic cells and by a combination of inhibitory and co-stimulatory signals largely provided by infiltrating myeloid cells. Furthermore, we have identified immunosuppressive pathways potentially hampering local immunity which might be targeted by immunotherapeutic approaches.

The Ubiquitin-Proteasome System Participates in Sperm Surface Subproteome Remodeling during Boar Sperm Capacitation

Sperm capacitation is a complex process endowing biological and biochemical changes to a spermatozoon for a successful encounter with an oocyte. The present study focused on the role of the ubiquitin-proteasome system (UPS) in the remodeling of the sperm surface subproteome. The sperm surface subproteome from non-capacitated and in vitro capacitated (IVC) porcine spermatozoa, with and without proteasomal inhibition, was selectively isolated. The purified sperm surface subproteome was analyzed using high-resolution, quantitative liquid chromatography-mass spectrometry (LC-MS) in four replicates. We identified 1680 HUGO annotated proteins, out of which we found 91 to be at least 1.5× less abundant (p < 0.05) and 141 to be at least 1.5× more abundant (p < 0.05) on the surface of IVC spermatozoa. These proteins were associated with sperm capacitation, hyperactivation, metabolism, acrosomal exocytosis, and fertilization. Abundances of 14 proteins were found to be significantly different (p < 0.05), exceeding a 1.5-fold abundance between the proteasomally inhibited (100 µM MG132) and vehicle control (0.2% ethanol) groups. The proteins NIF3L1, CSE1L, NDUFB7, PGLS, PPP4C, STK39, and TPRG1L were found to be more abundant; while BPHL, GSN, GSPT1, PFDN4, STYXL1, TIMM10, and UBXN4 were found to be less abundant in proteasomally inhibited IVC spermatozoa. Despite the UPS having a narrow range of targets, it modulated sperm metabolism and binding by regulating susceptible surface proteins. Changes in CSE1L, PFDN4, and STK39 during in vitro capacitation were confirmed using immunocytochemistry, image-based flow cytometry, and Western blotting. The results confirmed the active participation of the UPS in the extensive sperm surface proteome remodeling that occurs during boar sperm capacitation. This work will help us to identify new pharmacological mechanisms to positively or negatively modulate sperm fertilizing ability in food animals and humans.

VGLL3 expression is associated with macrophage infiltration and predicts poor prognosis in epithelial ovarian cancer

Background/objective

High-grade serous ovarian carcinoma (HGSOC) is the most common histologic type of epithelial ovarian cancer (EOC). Due to its poor survival outcomes, it is essential to identify novel biomarkers and therapeutic targets. The hippo pathway is crucial in various cancers, including gynaecological cancers. Herein, we examined the expression of the key genes of the hippo pathway and their relationship with clinicopathological significance, immune cells infiltration and the prognosis of HGSOC.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data were curated to analyse the mRNA expression as well as the clinicopathological association and correlation with immune cell infiltration in HGSOC. The protein levels of significant genes in the HGSOC tissue were analysed using Tissue Microarray (TMA)-based immunohistochemistry. Finally, DEGs pathway analysis was performed to find the signalling pathways associated with VGLL3.

Results

VGLL3 mRNA expression was significantly correlated with both advanced tumor stage and poor overall survival (OS) (p=0.046 and p=0.003, respectively). The result of IHC analysis also supported the association of VGLL3 protein with poor OS. Further, VGLL3 expression was significantly associated with tumor infiltrating macrophages. VGLL3 expression and macrophages infiltration were both found to be independent prognostic factors (p=0.003 and p=0.024, respectively) for HGSOC. VGLL3 was associated with four known and three novel cancer-related signalling pathways, thus implying that VGLL3 is involved in the deregulation of many genes and pathways.

Conclusion

Our study revealed that VGLL3 may play a distinct role in clinical outcomes and immune cell infiltration in patients with HGSOC and that it could potentially be a prognostic marker of EOC.

Th2 cells infiltrating high-grade serous ovarian cancer: a feature that may account for the poor prognosis

OBJECTIVE

We aimed to investigate the differences of transcriptome profile between 2 groups of high-grade serous ovarian cancer (HGSOC) patients with distinct outcomes and identify potential biomarkers for recurrence.

METHODS

RNA sequencing was performed in 2 groups of HGSOC patients with similar demographic characteristics but exhibiting distinct progression-free survival (PFS). Transcriptome data of poor response (PR; PFS ≤6 months) and good response (GR; PFS ≥12 months) group were compared. We employed xCell to evaluate the abundance of 63 cells in tumor microenvironment. The predictive value of recurrence-related tumor infiltration cells was validated in cohort data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) dataset. The weighted correlation network analysis was performed to identify the genes related to cell infiltration.

RESULTS

PR patients exhibited a distinct tumor infiltration immune cells-related transcriptional profile compared to GR patients, such as lower signatures of leukocyte differentiation, activation and chemotaxis. The fraction of T-helper 2 (Th2) cells infiltration was significantly higher in PR group than in GR group. High infiltration of Th2 was significantly associated with unfavorable prognosis in the GEO cohort (area under the curve=0.84 at 6 months recurrence) and TCGA cohort (p=0.008). Genes enriched to extracellular matrix organization and integrin binding were relevant to Th2 infiltration.

CONCLUSION

Patients with HGSOC having shorter PFS exhibited a distinct gene signature that related to tumor-infiltrating immune cells. The level of Th2 infiltration could facilitate patient recurrence risk stratification and may be a promising biomarker for prognosis prediction and immune-related treatment.

Body Composition and Metabolic Dysfunction Really Matter for the Achievement of Better Outcomes in High-Grade Serous Ovarian Cancer

Although obesity-associated metabolic disorders have a negative impact on various cancers, such evidence remains controversial for ovarian cancer. Here, we aimed to evaluate the impact of body composition (BC) and metabolism disorders on outcomes in high-grade serous ovarian cancer (HGSOC).

METHODS

We analyzed clinical/genomic data from two cohorts (PUC n = 123/TCGA-OV n = 415). BC was estimated using the measurement of adiposity/muscle mass by a CT scan. A list of 425 genes linked to obesity/lipid metabolism was used to cluster patients using non-negative matrix factorization. Differential expression, gene set enrichment analyses, and Ecotyper were performed. Survival curves and Cox-regression models were also built-up.

RESULTS

We identified four BC types and two clusters that, unlike BMI, effectively correlate with survival. High adiposity and sarcopenia were associated with worse outcomes. We also found that recovery of a normal BC and drug interventions to correct metabolism disorders had a positive impact on outcomes. Additionally, we showed that immune-cell-depleted microenvironments predominate in HGSOC, which was more evident among the BC types and the obesity/lipid metabolism cluster with worse prognosis.

CONCLUSIONS

We have demonstrated the relevance of BC and metabolism disorders as determinants of outcomes in HGSOC. We have shone a spotlight on the relevance of incorporating corrective measures addressing these disorders to obtain better results.

Unraveling the Transcriptomic Signatures of Homologous Recombination Deficiency in Ovarian Cancers

Homologous recombination deficiency (HRD) is a crucial driver of tumorigenesis by inducing impaired repair of double-stranded DNA breaks. Although HRD possibly triggers the production of numerous tumor neoantigens that sufficiently stimulate and activate various tumor-immune responses, a comprehensive understanding of the HRD-associated tumor microenvironment is elusive. To investigate the effect of HRD on the selective enrichment of transcriptomic signatures, 294 cases from The Cancer Genome Atlas-Ovarian Cancer project with both RNA-sequencing and SNP array data are analyzed. Differentially expressed gene analysis and network analysis are performed to identify HRD-specific signatures. Gene-sets associated with mitochondrial activation, including enhanced oxidative phosphorylation (OxPhos), are significantly enriched in the HRD-high group. Furthermore, a wide range of immune cell activation signatures is enriched in HRD-high cases of high-grade serous ovarian cancer (HGSOC). On further cell-type-specific analysis, M1-like macrophage genes are significantly enriched in HRD-high HGSOC cases, whereas M2-macrophage-related genes are not. The immune-response-associated genomic features, including tumor mutation rate, neoantigens, and tumor mutation burdens, correlated with HRD scores. In conclusion, the results of this study highlight the biological properties of HRD, including enhanced energy metabolism, increased tumor neoantigens and tumor mutation burdens, and consequent exacerbation of immune responses, particularly the enrichment of M1-like macrophages in HGSOC cases.

Systematic Pan-Cancer Analysis Identifies CDK1 as an Immunological and Prognostic Biomarker

Cyclin-dependent kinase 1 (CDK1) plays an important role in cancer development, progression, and the overall process of tumorigenesis. However, no pan-cancer analysis has been reported for CDK1, and the predictive role of CDK1 in immune checkpoint inhibitors (ICIs) therapy response remains unexplored. Thus, in this study, we first investigated the potential oncogenic role of CDK1 in 33 tumors by multidimensional bioinformatics analysis based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Bioinformatic analysis and immunohistochemical experiments confirmed that CDK1 is significantly upregulated in most common cancers and is strongly associated with prognosis. Further analysis indicated that CDK1 may influence tumor immunity mainly by mediating the degree of tumor infiltration of immune-associated cells, and the effect of CDK1 on immunity is diverse across tumor types in tumor microenvironment. CDK1 was also positively correlated with tumor mutational burden (TMB) and microsatellite instability (MSI) in certain cancer types, linking its expression to the assessment of possible treatment response. The results of the pan-cancer analysis study showed that the CDK1 gene was positively associated with the expression of three classes of RNA methylation regulatory proteins, and affects RNA function through multiple mechanisms of action and plays an important role in the posttranscriptional regulation of the tumor microenvironment. These findings shed light on the role of the CDK1 gene in cancer progression and provide information to further study the CDK1 gene as a potential target for pan-cancer.

The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer

Background: OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. Method: The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis of the TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model of mRLs. K-M analysis, PCA, GSEA and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune feature comparison, consensus clustering analysis and pan-cancer analysis. Results: A prognostic signature comprising four mRLs, WAC-AS1, LINC00997, DNM3OS and FOXN3-AS1, was constructed and verified for OV according to the TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, one can identify patients more effectively. The samples were divided into two clusters, and the clusters had different overall survival rates, clinical features and tumor microenvironments. Finally, pan-cancer analysis further demonstrated that the four mRLs were significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. Conclusions: This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.

Identification of necroptosis-related subtypes and prognosis model in triple negative breast cancer

Background

Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear.

Methods

We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed.

Results

A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing TPSG1, KRT6A, GPR19, EIF4EBP1, TLE1, SLC4A7, ESPN. The low-risk group has a better OS, higher immune score, TMB and CSC index, and lower IC50 value of common therapeutic agents in TNBC. To improve clinical practicability, we added age, stage_T and stage_N to the risk_score and construct a more comprehensive nomogram for predicting OS. It was verified that nomogram had good predictive capability, the AUC values for 1-, 3-, and 5-year OS were 0.847, 0.908, and 0.942.

Conclusion

Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.

A bioinformatic analysis of WFDC2 (HE4) expression in high grade serous ovarian cancer reveals tumor-specific changes in metabolic and extracellular matrix gene expression

Human epididymis protein-4 (HE4/WFDC2) has been well-studied as an ovarian cancer clinical biomarker. To improve our understanding of its functional role in high grade serous ovarian cancer, we determined transcriptomic differences between ovarian tumors with high- versus low-WFDC2 mRNA levels in The Cancer Genome Atlas dataset. High-WFDC2 transcript levels were significantly associated with reduced survival in stage III/IV serous ovarian cancer patients. Differential expression and correlation analyses revealed secretory leukocyte peptidase inhibitor (SLPI/WFDC4) as the gene most positively correlated with WFDC2, while A kinase anchor protein-12 was most negatively correlated. WFDC2 and SLPI were strongly correlated across many cancers. Gene ontology analysis revealed enrichment of oxidative phosphorylation in differentially expressed genes associated with high-WFDC2 levels, while extracellular matrix organization was enriched among genes associated with low-WFDC2 levels. Immune cell subsets found to be positively correlated with WFDC2 levels were B cells and plasmacytoid dendritic cells, while neutrophils and endothelial cells were negatively correlated with WFDC2. Results were compared with DepMap cell culture gene expression data. Gene ontology analysis of k-means clustering revealed that genes associated with low-WFDC2 were also enriched in extracellular matrix and adhesion categories, while high-WFDC2 genes were enriched in epithelial cell proliferation and peptidase activity. These results support previous findings regarding the effect of HE4/WFDC2 on ovarian cancer pathogenesis in cell lines and mouse models, while adding another layer of complexity to its potential functions in ovarian tumor tissue. Further experimental explorations of these findings in the context of the tumor microenvironment are merited.

Comprehensive Analysis of the Prognostic Signature of Mutation-Derived Genome Instability-Related lncRNAs for Patients With Endometrial Cancer

Background: Emerging evidence shows that genome instability-related long non-coding RNAs (lncRNAs) contribute to tumor–cell proliferation, differentiation, and metastasis. However, the biological functions and molecular mechanisms of genome instability-related lncRNAs in endometrial cancer (EC) are underexplored.

Methods: EC RNA sequencing and corresponding clinical data obtained from The Cancer Genome Atlas (TCGA) database were used to screen prognostic lncRNAs associated with genomic instability via univariate and multivariate Cox regression analysis. The genomic instability-related lncRNA signature (GILncSig) was developed to assess the prognostic risk of high- and low-risk groups. The prediction performance was analyzed using receiver operating characteristic (ROC) curves. The immune status and mutational loading of different risk groups were compared. The Genomics of Drug Sensitivity in Cancer (GDSC) and the CellMiner database were used to elucidate the relationship between the correlation of prognostic lncRNAs and drug sensitivity. Finally, we used quantitative real-time PCR (qRT-PCR) to detect the expression levels of genomic instability-related lncRNAs in clinical samples.

Results: GILncSig was built using five lncRNAs (AC007389.3, PIK3CD-AS2, LINC01224, AC129507.4, and GLIS3-AS1) associated with genomic instability, and their expression levels were verified using qRT-PCR. Further analysis revealed that risk score was negatively correlated with prognosis, and the ROC curve demonstrated the higher accuracy of GILncSig. Patients with a lower risk score had higher immune cell infiltration, a higher immune score, lower tumor purity, higher immunophenoscores (IPSs), lower mismatch repair protein expression, higher microsatellite instability (MSI), and a higher tumor mutation burden (TMB). Furthermore, the level of expression of prognostic lncRNAs was significantly related to the sensitivity of cancer cells to anti-tumor drugs.

Conclusion: A novel signature composed of five prognostic lncRNAs associated with genome instability can be used to predict prognosis, influence immune status, and chemotherapeutic drug sensitivity in EC.

Development and Validation of a Tumor Mutation Burden-Related Immune Prognostic Signature for Ovarian Cancers

Ovarian cancer (OC), one of the most common malignancies of the female reproductive system, is characterized by high incidence and poor prognosis. Tumor mutation burden (TMB), as an important biomarker that can represent the degree of tumor mutation, is emerging as a key indicator for predicting the efficacy of tumor immunotherapy. In our study, the gene expression profiles of OC were downloaded from TCGA and GEO databases. Subsequently, we analyzed the prognostic value of TMB in OC and found that a higher TMB score was significantly associated with a better prognosis (p = 0.004). According to the median score of TMB, 9 key TMB related immune prognostic genes were selected by LASSO regression for constructing a TMB associated immune risk score (TMB-IRS) signature, which can effectively predict the prognosis of OC patients (HR = 2.32, 95% CI = 1.68–3.32; AUC = 0.754). Interestingly, TMB-IRS is also closely related to the level of immune cell infiltration and immune checkpoint molecules (PD1, PD-L1, CTLA4, PD-L2) in OC. Furthermore, the nomogram combined with TMB-IRS and a variety of clinicopathological features can more comprehensively evaluate the prognosis of patients. In conclusion, we explored the relationship between TMB and prognosis and validated the TMB-IRS signature based on TMB score in an independent database (HR = 1.60, 95% CI = 1.13–2.27; AUC = 0.639), which may serve as a novel biomarker for predicting OC prognosis as well as possible therapeutic targets.

Shaping Immune Responses in the Tumor Microenvironment of Ovarian Cancer

Reciprocal signaling between immune cells and ovarian cancer cells in the tumor microenvironment can alter immune responses and regulate disease progression. These signaling events are regulated by multiple factors, including genetic and epigenetic alterations in both the ovarian cancer cells and immune cells, as well as cytokine pathways. Multiple immune cell types are recruited to the ovarian cancer tumor microenvironment, and new insights about the complexity of their interactions have emerged in recent years. The growing understanding of immune cell function in the ovarian cancer tumor microenvironment has important implications for biomarker discovery and therapeutic development. This review aims to describe the factors that shape the phenotypes of immune cells in the tumor microenvironment of ovarian cancer and how these changes impact disease progression and therapy.

Tumor Mutation Burden and Immune Invasion Characteristics in Triple Negative Breast Cancer: Genome High-Throughput Data Analysis

In recent years, the emergence of immunotherapy has provided a new perspective for the treatment and management of triple-negative breast cancer (TNBC). However, the relationship between tumor mutation burden (TMB) and immune infiltration and the prognosis of TNBC remains unclear. In this study, to explore the immunogenicity of TNBC, we divided patients with TNBC into high and low TMB groups based on the somatic mutation data of TNBC in The Cancer Genome Atlas (TCGA), and screened out genes with mutation rate ≥10. Then, Kaplan-Meier survival analysis revealed that the 5-year survival rate of the high TMB group was much higher than that of the low TMB group and the two groups also showed differences in immune cell infiltration. Further exploration found that the FAT3 gene, which displays significant difference and a higher mutation rate between the two groups, is not only significantly related to the prognosis of TNBC patients but also exhibits difference in immune cell infiltration between the wild group and the mutant group of the FAT3 gene. The results of gene set enrichment analysis and drug sensitivity analysis further support the importance of the FAT3 gene in TNBC. This study reveals the characteristics of TMB and immune cell infiltration in triple-negative breast cancer and their relationship with prognosis, to provide new biomarkers and potential treatment options for the future treatment of TNBC. The FAT3 gene, as a risk predictor gene of TNBC, is considered a potential biological target and may provide new insight for the treatment of TNBC.