Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

The HOX Gene Family's Role as Prognostic and Diagnostic Biomarkers in Hematological and Solid Tumors

The HOX gene family encodes for regulatory transcription factors that play a crucial role in embryogenesis and differentiation of adult cells. This highly conserved family of genes consists of thirty-nine genes in humans that are located in four clusters, A-D, on different chromosomes. While early studies on the HOX gene family have been focused on embryonic development and its related disorders, research has shifted to examine aberrant expression of HOX genes and the subsequent implication in cancer prediction and progression. Due to their role of encoding master regulatory transcription factors, the abnormal expression of HOX genes has been shown to affect all stages of tumorigenesis and metastasis. This review highlights the novel role of the HOX family's clinical relevance as both prognostic and diagnostic biomarkers in hematological and solid tumors.

A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause

The fallopian tube undergoes extensive molecular changes during the menstrual cycle and menopause. We use single-cell RNA and ATAC sequencing to construct a comprehensive cell atlas of healthy human fallopian tubes during the menstrual cycle and menopause. Our scRNA-seq comparison of 85,107 pre- and 46,111 post-menopausal fallopian tube cells reveals substantial shifts in cell type frequencies, gene expression, transcription factor activity, and cell-to-cell communications during menopause and menstrual cycle. Menstrual cycle dependent hormonal changes regulate distinct molecular states in fallopian tube secretory epithelial cells. Postmenopausal fallopian tubes show high chromatin accessibility in transcription factors associated with aging such as Jun, Fos, and BACH1/2, while hormone receptors were generally downregulated, a small proportion of secretory epithelial cells had high expression of ESR2, IGF1R, and LEPR. While a pre-menopausal secretory epithelial gene cluster is enriched in the immunoreactive molecular subtype, a subset of genes expressed in post-menopausal secretory epithelial cells show enrichment in the mesenchymal molecular type of high-grade serous ovarian cancer.

MECOM Locus classical transcript isoforms affect tumor immune microenvironment and different targets in ovarian cancer

The MECOM locus is a gene frequently amplified in high-grade serous ovarian carcinoma (HGSOC). Nevertheless, the body of research examining the associations among MECOM transcripts, patient prognosis, and their role in modulating the tumor immune microenvironment (TIME) remains sparse, particularly in large cohorts. This study assessed the expression of MECOM transcripts in 352 HGSOC patients and 88 normal ovarian tissues from the combined GTEx/TCGA database. Using resources such as the UCSC Genome Browser, Ensembl, and NextProt, two transcripts corresponding to classical protein isoforms from MECOM were identified. Cox proportional hazards regression analysis, Kaplan-Meier survival curves, and a comprehensive TIME evaluation algorithm were employed to elucidate the connections between the expression levels of these transcripts and both patient prognosis and TIME status. Chromatin Immunoprecipitation sequencing (ChIP-seq) data for the two protein isoforms, as well as RNA sequencing data post-targeted silencing, were analyzed to identify potential regulatory targets of the different transcription factors. Elevated expression of the MECOM isoform transcripts was correlated with poorer survival in HGSOC patients, potentially through the modulation of cancer-associated fibroblasts (CAFs) and immunosuppressive cell populations. In contrast, higher levels of EVI1 isoform transcripts were linked to enhanced survival, possibly due to the regulation of CD8+ T cells, macrophages, and a reduction in the expression of JUN protein, or its DNA-binding activity on downstream genes. Diverse protein isoforms derived from MECOM were found to differentially affect the survival and tumor development in ovarian cancer patients through specific mechanisms. Investigating the molecular mechanisms underlying disease pathogenesis and identifying potential drug target proteins at the level of splice variant isoforms were deemed crucial.

Cancer-associated Fibroblasts-derived Exosomes with HOXD11 Overexpression Promote Ovarian Cancer Cell Angiogenesis Via FN1

Cancer-associated fibroblasts (CAFs) represent a critical stromal component of metastatic niche and promote metastasis in patients with ovarian cancer (OC). Here, we try to further understand the mechanism by which CAFs-derived exosomes (CAFs-Exo) promoted angiogenesis in OC. We intersected differentially expressed genes in OC cells after CAFs-Exo treatment in the GSE147610 dataset with a list of transcription factors to identify homeobox protein hox-D11 (HOXD11) as a possible cargo of CAFs-Exo. HOXD11 encapsulated by CAFs-Exo enhanced colony formation, migration, and invasion of OC cells. HOXD11 bound to the promoter of fibronectin (FN1) and promoted its transcription. HOXD11 knockdown from CAFs-Exo significantly repressed the VEGF and CD31 protein expression and tube formation, viability, and migration of human umbilical vein endothelial cells (HUVEC) and slowed angiogenesis and tumor growth in mice. Furthermore, we found that overexpression of FN1 increased the expression of angiogenic factors and activity of HUVEC in the presence of HOXD11 knockdown. These results verify the significant contribution of CAFs-Exo to angiogenesis in OC, which could be partially due to the promotion of FN1 mediated by HOXD11.

18F-Fluoro-2-Deoxyglucose Positron Emission Tomography/Computed Tomography Measures of Spatial Heterogeneity for Predicting Platinum Resistance of High-Grade Serous Ovarian Cancer

BACKGROUND

The purpose of this study is to construct models for predicting platinum resistance in high-grade serous ovarian cancer (HGSOC) derived from quantitative spatial heterogeneity indicators obtained from 18F-FDG PET/CT images.

METHODS

A retrospective study was conducted on patients diagnosed with HGSOC. Quantitative indicators of spatial heterogeneity were generated using conventional features and Haralick texture features from both CT and PET images. Three groups of predictive models (conventional, heterogeneity, and integrated) were built. Each group's optimal model was the one with the highest area under curve (AUC). Postoperative immunohistochemical staining for Ki-67 and p53 was conducted. The correlation between the heterogeneity indicators and scores for Ki-67 and p53 was assessed by Spearman's correlation coefficient (ρ).

RESULTS

A total of 286 patients (54.6 ± 9.3 years) were enrolled. And 107 spatial heterogeneity indicators were extracted. The optimal models for each group were obtained using the Gradient Boosting Machine (GBM) algorithm. There was an AUC of 0.790 (95% CI: 0.696, 0.885) in the conventional model for the validation set, and an AUC of 0.904 (95% CI: 0.842, 0.966) in the heterogeneity model for the validation set. The integrated model achieved the highest predictive performance, with an AUC value of 0.928 (95% CI: 0.872, 0.984) for the validation set. Spearman's correlation showed that HU_Kurtosis had the strongest correlation with p53 scores with ρ = 0.718, while cluster site entropy had the strongest correlation with Ki-67 scores with ρ = 0.753.

CONCLUSIONS

Adding quantitative spatial heterogeneity indicators derived from PET/CT images can improve the prediction of platinum resistance in patients with HGSOC. Spatial heterogeneity indicators were related to Ki-67 and p53 scores.

THUMPD3-AS1 inhibits ovarian cancer cell apoptosis through the miR-320d/ARF1 axis

Ovarian cancer is one of the most common gynecologic malignancies that has a poor prognosis. THUMPD3-AS1 is an oncogenic long noncoding RNA (lncRNA) in several cancers. Moreover, miR-320d is downregulated and inhibited proliferation in ovarian cancer cells, whereas ARF1 was upregulated and promoted the malignant progression in epithelial ovarian cancer. Nevertheless, the role of THUMPD3-AS1 in ovarian cancer and the underlying mechanism has yet to be elucidated. Human normal ovarian epithelial cells (IOSE80) and ovarian cancer cell lines (CAVO3, A2780, SKOV3, OVCAR3, and HEY) were adopted for in vitro experiments. The functional roles of THUMPD3-AS1 in cell viability and apoptosis were determined using CCK-8, flow cytometry, and TUNEL assays. Western blot was performed to assess the protein levels of ARF1, Bax, Bcl-2, and caspase 3, whereas RT-qPCR was applied to measure ARF1 mRNA, THUMPD3-AS1, and miR-320d levels. The targeting relationship between miR-320d and THUMPD3-AS1 or ARF1 was validated with dual luciferase assay. THUMPD3-AS1 and ARF1 were highly expressed in ovarian cancer cells, whereas miR-320d level was lowly expressed. THUMPD3-AS1 knockdown was able to repress cell viability and accelerate apoptosis of OVCAR3 and SKOV3 cells. Also, THUMPD3-AS1 acted as a sponge of miR-320d, preventing the degradation of ARF1. MiR-320d downregulation reversed the tumor suppressive function induced by THUMPD3-AS1 depletion. Additionally, miR-320d overexpression inhibited ovarian cancer cell viability and accelerated apoptosis, which was overturned by overexpression of ARF1. THUMPD3-AS1 inhibited ovarian cancer cell apoptosis by modulation of miR-320d/ARF1 axis. The discoveries might provide a prospective target for ovarian cancer treatment.

Unraveling the molecular mechanisms of lymph node metastasis in ovarian cancer: focus on MEOX1

BACKGROUND

Lymph node metastasis (LNM) is a major factor contributing to the high mortality rate of ovarian cancer, making the treatment of this disease challenging. However, the molecular mechanism underlying LNM in ovarian cancer is still not well understood, posing a significant obstacle to overcome.

RESULTS

Through data mining from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we have identified MEOX1 as a specific gene associated with LNM in ovarian cancer. The expression of MEOX1 was found to be relatively high in serous ovarian adenocarcinoma, and its higher expression were associated with increased tumor grade and poorer clinical prognosis for ovarian cancer patients. Bioinformatics analysis revealed that MEOX1 exhibited the highest mRNA levels among all cancer types in ovarian cancer tissues and cell lines. Furthermore, gene set enrichment analysis (GSEA) and pathway analysis demonstrated that MEOX1 was involved in various LNM-related biological activities, such as lymphangiogenesis, lymphatic vessel formation during metastasis, epithelial-mesenchymal transition (EMT), G2/M checkpoint, degradation of extracellular matrix, and collagen formation. Additionally, the expression of MEOX1 was positively correlated with the expression of numerous prolymphangiogenic factors in ovarian cancer. To validate our findings, we conducted experiments using clinical tissue specimens and cell lines, which confirmed that MEOX1 was highly expressed in high-grade serous ovarian cancer (HGSOC) tissues and various ovarian cancer cell lines (A2780, SKOV3, HO8910, and OVCAR5) compared to normal ovarian tissues and normal ovarian epithelial cell line IOSE-80, respectively. Notably, we observed a higher protein level of MEOX1 in tumor tissues of LNM-positive HGSOC compared to LNM-negative HGSOC. Moreover, our fundamental experiments demonstrated that suppression of MEOX1 led to inhibitory effects on ovarian cancer cell proliferation and EMT, while overexpression of MEOX1 enhanced the proliferation and EMT capacities of ovarian cancer cells.

CONCLUSIONS

The results of our study indicate that MEOX1 plays a role in the lymph node metastasis of ovarian cancer by regulating multiple biological activities, including the proliferation and EMT of ovarian cancer, lymphangiogenesis, and ECM remodeling. Our findings suggest that MEOX1 could serve as a potential biomarker for the diagnosis and treatment of ovarian cancer with LNM.

Survival time prediction in patients with high-grade serous ovarian cancer based on 18F-FDG PET/CT- derived inter-tumor heterogeneity metrics

BACKGROUND

The presence of heterogeneity is a significant attribute within the context of ovarian cancer. This study aimed to assess the predictive accuracy of models utilizing quantitative 18F-FDG PET/CT derived inter-tumor heterogeneity metrics in determining progression-free survival (PFS) and overall survival (OS) in patients diagnosed with high-grade serous ovarian cancer (HGSOC). Additionally, the study investigated the potential correlation between model risk scores and the expression levels of p53 and Ki-67.

METHODS

A total of 292 patients diagnosed with HGSOC were retrospectively enrolled at Shengjing Hospital of China Medical University (median age: 54 ± 9.4 years). Quantitative inter-tumor heterogeneity metrics were calculated based on conventional measurements and texture features of primary and metastatic lesions in 18F-FDG PET/CT. Conventional models, heterogeneity models, and integrated models were then constructed to predict PFS and OS. Spearman's correlation coefficient (ρ) was used to evaluate the correlation between immunohistochemical scores of p53 and Ki-67 and model risk scores.

RESULTS

The C-indices of the integrated models were the highest for both PFS and OS models. The C-indices of the training set and testing set of the integrated PFS model were 0.898 (95% confidence interval [CI]: 0.881-0.914) and 0.891 (95% CI: 0.860-0.921), respectively. For the integrated OS model, the C-indices of the training set and testing set were 0.894 (95% CI: 0.871-0.917) and 0.905 (95% CI: 0.873-0.936), respectively. The integrated PFS model showed the strongest correlation with the expression levels of p53 (ρ = 0.859, p < 0.001) and Ki-67 (ρ = 0.829, p < 0.001).

CONCLUSIONS

The models based on 18F-FDG PET/CT quantitative inter-tumor heterogeneity metrics exhibited good performance for predicting the PFS and OS of patients with HGSOC. p53 and Ki-67 expression levels were strongly correlated with the risk scores of the integrated predictive models.

Biology-driven therapy advances in high-grade serous ovarian cancer

Following a period of slow progress, the completion of genome sequencing and the paradigm shift relative to the cell of origin for high grade serous ovarian cancer (HGSOC) led to a new perspective on the biology and therapeutic solutions for this deadly cancer. Experimental models were revisited to address old questions, and improved tools were generated. Additional pathways emerging as drivers of ovarian tumorigenesis and key dependencies for therapeutic targeting, in particular, VEGF-driven angiogenesis and homologous recombination deficiency, were discovered. Molecular profiling of histological subtypes of ovarian cancer defined distinct genetic events for each entity, enabling the first attempts toward personalized treatment. Armed with this knowledge, HGSOC treatment was revised to include new agents. Among them, PARP inhibitors (PARPis) were shown to induce unprecedented improvement in clinical benefit for selected subsets of patients. Research on mechanisms of resistance to PARPis is beginning to discover vulnerabilities and point to new treatment possibilities. This Review highlights these advances, the remaining challenges, and unsolved problems in the field.

A Cellular atlas of the human fallopian tube reveals the metamorphosis of secretory epithelial cells during the menstrual cycle and menopause

The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

Graphical summary

Graphical summary of results. During the proliferative phase (estrogen high ) of the menstrual cycle, SE2 cells (OVGP1 + ) dominate the fallopian tube (FT) epithelium, while SE1 cells (OVGP1 - ) dominate the epithelium during the secretory phase. Though estrogen levels decrease during menopause, SE post-cells (OVGP1 + , CXCL2 + ) make up most of the FT epithelium.

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.

Whole-exome mutational landscape and molecular marker study in mucinous and clear cell ovarian cancer cell lines 3AO and ES2

BACKGROUND

Ovarian cancer is one of the most lethal cancers in women because it is often diagnosed at an advanced stage. The molecular markers investigated thus far have been unsatisfactory.

METHODS

We performed whole-exome sequencing on the human ovarian cancer cell lines 3AO and ES2 and the normal ovarian epithelial cell line IOSE-80. Molecular markers of ovarian cancer were screened from shared mutation genes and copy number variation genes in the 6q21-qter region.

RESULTS

We found that missense mutations were the most common mutations in the gene (93%). The MUC12, FLG and MUC16 genes were highly mutated in 3AO and ES2 cells. Copy number amplification occurred mainly in 4p16.1 and 11q14.3, and copy number deletions occurred in 4q34.3 and 18p11.21. A total of 23 hub genes were screened, of which 16 were closely related to the survival of ovarian cancer patients. The three genes CCDC170, THBS2 and COL14A1 are most significantly correlated with the survival and prognosis of ovarian cancer. In particular, the overall survival of ovarian cancer patients with high CCDC170 gene expression was significantly prolonged (P < 0.001). The expression of CCDC170 in normal tissues was significantly higher than that in ovarian cancer tissues (P < 0.05), and its expression was significantly decreased in advanced ovarian cancer. Western blotting and immunofluorescence assays also showed that the expression of CCDC170 in ovarian cancer cells was significantly lower than that in normal cells (P < 0.001, P < 0.01).

CONCLUSIONS

CCDC170 is expected to become a new diagnostic molecular target and prognostic indicator for ovarian cancer patients, which can provide new ideas for the design of antitumor drugs.

The role of RNA methyltransferase METTL3 in gynecologic cancers: Results and mechanisms

N6-methyladenosine (m6A) methylation is the most prevalent mRNA modification in eukaryotes, and it is defined as the methylation of nitrogen atoms on the six adenine (A) bases of RNA in the presence of methyltransferases. Methyltransferase-like 3 (Mettl3), one of the components of m6A methyltransferase, plays a decisive catalytic role in m6A methylation. Recent studies have confirmed that m6A is associated with a wide spectrum of biological processes and it significantly affects disease progression and prognosis of patients with gynecologic tumors, in which the role of Mettl3 cannot be ignored. Mettl3 is involved in numerous pathophysiological functions, such as embryonic development, fat accumulation, and tumor progression. Moreover, Mettl3 may serve as a potential target for treating gynecologic malignancies, thus, it may benefit the patients and prolong survival. However, there is a need to further study the role and mechanism of Mettl3 in gynecologic malignancies. This paper reviews the recent progression on Mettl3 in gynecologic malignancies, hoping to provide a reference for further research.

chromMAGMA: regulatory element-centric interrogation of risk variants

Candidate causal risk variants from genome-wide association studies reside almost exclusively in noncoding regions of the genome and innovative approaches are necessary to understand their biological function. Multi-marker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA to create chromatin-MAGMA (chromMAGMA), a method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants for complex diseases.

Ferroptosis, necroptosis, and pyroptosis in the occurrence and development of ovarian cancer

Ovarian cancer (OC) is one of the most common malignancies that causes death in women and is a heterogeneous disease with complex molecular and genetic changes. Because of the relatively high recurrence rate of OC, it is crucial to understand the associated mechanisms of drug resistance and to discover potential target for rational targeted therapy. Cell death is a genetically determined process. Active and orderly cell death is prevalent during the development of living organisms and plays a critical role in regulating life homeostasis. Ferroptosis, a novel type of cell death discovered in recent years, is distinct from apoptosis and necrosis and is mainly caused by the imbalance between the production and degradation of intracellular lipid reactive oxygen species triggered by increased iron content. Necroptosis is a regulated non-cysteine protease–dependent programmed cell necrosis, morphologically exhibiting the same features as necrosis and occurring via a unique mechanism of programmed cell death different from the apoptotic signaling pathway. Pyroptosis is a form of programmed cell death that is characterized by the formation of membrane pores and subsequent cell lysis as well as release of pro-inflammatory cell contents mediated by the abscisin family. Studies have shown that ferroptosis, necroptosis, and pyroptosis are involved in the development and progression of a variety of diseases, including tumors. In this review, we summarized the recent advances in ferroptosis, necroptosis, and pyroptosis in the occurrence, development, and therapeutic potential of OC.

N6-methyladenosine (m6A) modification in gynecological malignancies

N6-methyladenosine (m6A) modification is one of the most abundant modifications in eukaryotic mRNA, regulated by m6A methyltransferase and demethylase. m6A modified RNA is specifically recognized and bound by m6A recognition proteins, which mediate splicing, maturation, exonucleation, degradation, and translation. In gynecologic malignancies, m6A RNA modification-related molecules are expressed aberrantly, significantly altering the posttranscriptional methylation level of the target genes and their stability. The m6A modification also regulates related metabolic pathways, thereby controlling tumor development. This review analyzes the composition and mode of action of m6A modification-related proteins and their biological functions in the malignant progression of gynecologic malignancies, which provide new ideas for the early clinical diagnosis and targeted therapy of gynecologic malignancies.

Construction and validation of a transcription factors-based prognostic signature for ovarian cancer

BACKGROUND

Ovarian cancer (OC) is one of the most common and lethal malignant tumors worldwide and the prognosis of OC remains unsatisfactory. Transcription factors (TFs) are demonstrated to be associated with the clinical outcome of many types of cancers, yet their roles in the prognostic prediction and gene regulatory network in patients with OC need to be further investigated.

METHODS

TFs from GEO datasets were collected and analyzed. Differential expression analysis, WGCNA and Cox-LASSO regression model were used to identify the hub-TFs and a prognostic signature based on these TFs was constructed and validated. Moreover, tumor-infiltrating immune cells were analyzed, and a nomogram containing age, histology, FIGO_stage and TFs-based signature were established. Potential biological functions, pathways and the gene regulatory network of TFs in signature was also explored.

RESULTS

In this study, 6 TFs significantly associated with the prognosis of OC were identified. These TFs were used to build up a TFs-based signature for predicting the survival of patients with OC. Patients with OC in training and testing datasets were divided into high-risk and low-risk groups, according to the median value of risk scores determined by the signature. The two groups were further used to validate the performance of the signature, and the results showed the TFs-based signature had effective prediction ability. Immune infiltrating analysis was conducted and abundance of B cells naïve, T cells CD4 memory resting, Macrophages M2 and Mast cells activated were significantly higher in high-risk group. A nomogram based on the signature was established and illustrated good predictive efficiencies for 1, 2, and 3-year overall survival. Furthermore, the construction of the TFs-target gene regulatory network revealed the potential mechanisms of TFs in OC.

CONCLUSIONS

To our best knowledge, it is for the first time to develop a prognostic signature based on TFs in OC. The TFs-based signature is proven to be effective in predicting the survival of patients with OC. Our study may facilitate the clinical decision-making for patients with OC and help to elucidate the underlying mechanism of TFs in OC.

Meta-analysis identifying epithelial-derived transcriptomes predicts poor clinical outcome and immune infiltrations in ovarian cancer

BACKGROUND

Previous studies revealed that the epithelial component is associated with the modulation of the ovarian tumor microenvironment (TME). However, the identification of key transcriptional signatures of laser capture microdissected human ovarian cancer epithelia remains lacking.

METHODS

We identified the differentially expressed transcriptional signatures of human ovarian cancer epithelia by meta-analysis of GSE14407, GSE2765, GSE38666, GSE40595, and GSE54388. Then we investigated the enrichment of KEGG pathways that are associated with epithelia-derived transcriptomes. Finally, we investigated the correlation of key epithelia-hub genes with the survival prognosis and immune infiltrations. Finally, we investigated the genetic alterations of key prognostic hub genes and their diagnostic efficacy in ovarian cancer epithelia.

RESULTS

We identified 1339 differentially expressed genes (DEGs) in ovarian cancer epithelia including 541upregulated and 798 downregulated genes. We identified 21 (such as E2F4, FOXM1, TFDP1, E2F1, and SIN3A) and 11 (such as JUN, DDX4, FOSL1, NOC2L, and HMGA1) master transcriptional regulators (MTRs) that are interacted with upregulated and the downregulated genes in ovarian tumor epithelium, respectively. The STRING-based analysis identified hub genes (such as CDK1, CCNB1, AURKA, CDC20, and CCNA2) in ovarian cancer epithelia. The significant clusters of identified hub genes are associated with the enrichment of KEGG pathways including cell cycle, DNA replication, cytokine-cytokine receptor interaction, pathways in cancer, and focal adhesion. The upregulation of SCNN1A and CDCA3 and the downregulation of SOX6 are correlated with a shorter survival prognosis in ovarian cancer (OV). The expression level of SOX6 is negatively correlated with immune score and positively correlated with tumor purity in OV. Moreover, SOX6 is negatively correlated with the infiltration of TILs, CD8+ T cells, CD4+ Regulatory T cells, cytolytic activity, T cell activation, pDC, neutrophils, and macrophages in OV. Also, SOX6 is negatively correlated with various immune markers including CD8A, PRF1, GZMA, GZMB, NKG7, CCL3, and CCL4, indicating the immune regulatory efficiency of SOX6 in the TME of OV. Furthermore, SCNN1A, CDCA3, and SOX6 genes are genetically altered in OV and the expression levels of SCNN1A and SOX6 genes showed diagnostic efficacy in ovarian cancer epithelia.

CONCLUSIONS

The identified ovarian cancer epithelial-derived key transcriptional signatures are significantly correlated with survival prognosis and immune infiltrations, and may provide new insight into the diagnosis and treatment of epithelial ovarian cancer.