Immune profiling reveals prognostic genes in high-grade serous ovarian cancer

Immune cell landscapes are associated with high-grade serous ovarian cancer survival

High-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcriptome deconvolution was performed to address cellular heterogeneity. Kaplan-Meier survival curves were plotted to illustrate the outcomes of patients with varying cellular abundances. The association between gene expression and chemotherapy response was tested. After adjusting for surgery status and grading, several cell states exhibited a significant correlation with patient survival. Cell states can organize into carcinoma ecotypes (CE). CE9 and CE10 were proinflammatory, characterized by higher immunoreactivity, and were associated with favorable survival outcomes. Ratios of cell states and ecotypes had better prognostic abilities than a single cell state or ecotype. A total of 1265 differentially expressed genes were identified between samples with high and low levels of C9 or CE10. These genes were partitioned into three co-expressed modules, which were associated with tumor cells and immune cells. Pogz was identified to be linked with immune cell genes and the chemotherapy response of paclitaxel. Collectively, the survival of HGSOC patients is correlated with specific cell states and ecotypes.

Pro-inflammatory cytokines and CXC chemokines as game-changer in age-associated prostate cancer and ovarian cancer: Insights from preclinical and clinical studies' outcomes

Prostate cancer (PC) and Ovarian cancer (OC) are two of the most common types of cancer that affect the reproductive systems of older men and women. These cancers are associated with a poor quality of life among the aged population. Therefore, finding new and innovative ways to detect, treat, and prevent these cancers in older patients is essential. Finding biomarkers for these malignancies will increase the chance of early detection and effective treatment, subsequently improving the survival rate. Studies have shown that the prevalence and health of some illnesses are linked to an impaired immune system. However, the age-associated changes in the immune system during malignancies such as PC and OC are poorly understood. Recent research has suggested that the excessive production of inflammatory immune mediators, such as interleukin-6 (IL-6), interleukin-8 (IL-8), transforming growth factor (TGF), tumor necrosis factor (TNF), CXC motif chemokine ligand 1 (CXCL1), CXC motif chemokine ligand 12 (CXCL12), and CXC motif chemokine ligand 13 (CXCL13), etc., significantly impact the development of PC and OC in elderly patients. Our review focuses on the latest functional studies of pro-inflammatory cytokines (interleukins) and CXC chemokines, which serve as biomarkers in elderly patients with PC and OC. Thus, we aim to shed light on how these biomarkers affect the development of PC and OC in elderly patients. We also examine the current status and future perspective of cytokines (interleukins) and CXC chemokines-based therapeutic targets in OC and PC treatment for elderly patients.

ETV7 promotes colorectal cancer progression through upregulation of IFIT3

Members of the E26 transformation-specific (ETS) variant transcription factor family act as either tumor suppressors or oncogenic factors in numerous types of cancer. ETS variant transcription factor 7 (ETV7) participates in the development of malignant tumors, whereas its involvement in colorectal cancer (CRC) is less clear. In this study, The Cancer Genome Atlas (TCGA) and immunochemistry staining were applied to check the clinical relevance of ETV7 and interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) in CRC patients. Overexpression and knockdown of ETV7 and IFIT3 were conducted by transfecting the cells with pCDNA3.1 plasmids and siRNAs, respectively. Western blotting was used to detect the protein expression of ETV7 in CRC cells. Cell Counting Kit-8, cell colony formation, and Transwell assays, as well as flow cytometry, were used to evaluate the proliferation, migration, cell cycle, and apoptosis of CRC cells. Furthermore, western blotting, RT-qPCR, and luciferase assay were used to explore the regulation of ETV7 on IFIT3. Rescue assay was used to investigate the significance of ETV7/IFIT3 axis on CRC progression. We found that ETV7 was upregulated in CRC tissues and cells. Overexpression of ETV7 stimulated the proliferation, migration, and cell cycle amplification, and reduced the apoptosis of CRC cells. Downregulation of ETV7 exerted the opposite effect on CRC cell progression. Moreover, we demonstrated that ETV7 stimulated the transcription activity, the mRNA and protein expression of IFIT3 in CRC cells. There was a positive correlation between ETV7 and IFIT3 in CRC patients. IFIT3 knockdown reversed the promotive effect exerted by overexpression of ETV7 on the amplification and migration of CRC cells. By contrast, overexpression of IFIT3 blocked the inhibitory effect of ETV7-targeting siRNA. In summary, ETV7 induces progression of CRC by activating the transcriptional expression of IFIT3. The EVT7/IFIT3 axis may be a novel target for CRC therapy.

Function and mechanism of GBP1 in the development and progression of cervical cancer

Guanylate binding protein 1 (GBP1) is the most concerned member of the GBP family, which has a series of effects such as anti-infection and anti-angiogenesis. Its role in malignant tumors including cervical cancer is still controversial. We aim to explore the effects of GBP1 on cervical cancer through bioinformatics and related experiments. In this study, we first found that GBP1 was generally expressed in cervical cancer in various online databases and was closely related to immune invasion. Secondly, we used multicolor immunofluorescence technology to verify the expression of GBP1 in cervical cancer tissues and its relationship with immune invasion, and explored its relationship with the prognosis of patients with cervical cancer. Knockdown and overexpression assays of GBP1 in vitro were used to prove GBP1 as a potential oncogene of cervical cancer, and its carcinogenicity was verified by in vivo experiment. In order to explore the potential mechanism of GBP1 in promoting cancer, RNA-seq was performed on GBP1 overexpression and knockdown expression cell lines, and GBP1 knockdown and overexpression were found to be associated with many RNA alternative splicing events, suggesting that GBP1 maybe a RNA binding protein (RBP) which affect the biological characteristics of cervical cancer cells through the alternative splicing pathway. However, the later RNA binding protein immunoprecipitation (RIP) assay proved that GBP1 was not a direct alternative splicing factor, while the co-immunoprecipitation (CoIP)-mass spectroscopy (MS) assay combined with protein protein interaction (PPI) analysis proved that 8 alternative splicing factors including Heterogeneous Nuclear Ribonucleoprotein K (HNRNPK) were interacting proteins of GBP1. Combined with the existing reports and the results of RNA-seq alternative splicing analysis, it is speculated that GBP1 may regulate the alternative splicing of CD44 protein by binding to interacting protein-HNRNPK, and thus play a role in promoting cancer in cervical cancer.

Construction of Metastasis-Specific Regulation Network in Ovarian Cancer Based on Prognostic Stemness-Related Signatures

WE aimed to reveal the correlation between ovarian cancer (OV) metastasis and cancer stemness in OV. RNA-seq data and clinical information of 591 OV samples (551 without metastasis and 40 with metastasis) were obtained from TCGA. The edgeR method was used to determine differentially expressed genes (DEGs) and transcription factors (DETFs). Then, mRNA expression-based stemness index was calculated using one-class logistic regression (OCLR). Weighted gene co-expression network analysis (WGCNA) was used to define stemness-related genes (SRGs). Univariate and multivariate Cox proportional hazard regression were conducted to identify the prognostic SRGs (PSRGs). PSRGs, DETFs, and 50 hallmark pathways quantified by gene set variation analysis (GSVA) were integrated into Pearson co-expression analysis. Significant co-expression interactions were utilized to construct an OV metastasis-specific regulation network. Cell communication analysis was carried out based on single cell RNA sequencing data to explore the molecular regulation mechanism of OV. Eventually, assay for targeting accessible-chromatin with high throughout sequencing (ATAC), chromatin immunoprecipitation sequencing (ChIP-seq) validation, and multiple data sets were used to validate the expression levels and prognostic values of key stemness-related signatures. Moreover, connectivity map (CMap) was used to identify potential inhibitors of stemness-related signatures. Based on edgeR, WGCNA, and Cox proportional hazard regression, 22 PSRGs were defined to construct a prognostic prediction model for metastatic OV. In the metastasis-specific regulation network, key TF-PSRS interaction pair was NR4A1-EGR3 (correlation coefficient = 0.81, p < 0.05, positive), and key PSRG-hallmark pathway interaction pair was EGR3-TNFα signaling via NFκB (correlation coefficient = 0.44, p < 0.05, positive), which were validated in multi-omics databases. Thioridazine was postulated to be the most significant compound in treatment of OV metastasis. PSRGs played critical roles in OV metastasis. Specifically, EGR3 was the most significant PSRG, which was positively regulated by DETF NR4A1, inducing metastasis via TNFα signaling.

Impacts of vitrification on the transcriptome of human ovarian tissue in patients with gynecological cancer

Objective: This study investigated the effects of a vitrification/warming procedure on the mRNA transcriptome of human ovarian tissues.

Design: Human ovarian tissues were collected and processed through vitrification (T-group) and then subjected to RNA sequencing (RNA-seq) analysis, HE, TdT-mediated dUTP nick-end labeling (TUNEL), and real-time quantitative PCR, and the results were compared to those of the fresh group (CK).

Results: A total of 12 patients, aged 15–36 years old, with a mean anti-Müllerian hormone level of 4.57 ± 3.31 ng/mL were enrolled in this study. According to the HE and TUNEL results, vitrification effectively preserved human ovarian tissue. A total of 452 significantly dysregulated genes (|log2FoldChange| &gt; 1 and p &lt; 0.05) were identified between the CK and T groups. Among these, 329 were upregulated and 123 were downregulated. A total of 372 genes were highly enriched for 43 pathways (p &lt; 0.05), which were mainly related to systemic lupus erythematous, cytokine–cytokine receptor interaction, the TNF signaling pathway, and the MAPK signaling pathway. IL10, AQP7, CCL2, FSTL3, and IRF7 were significantly upregulated (p &lt; 0.01), while IL1RN, FCGBP, VEGFA, ACTA2, and ASPN were significantly downregulated in the T-group (p &lt; 0.05) compared to the CK group, which agreed with the results of the RNA-seq analysis.

Conclusion: These results showed (for the first time to the authors’ knowledge) that vitrification can induce changes in mRNA expression in human ovarian tissues. Further molecular studies on human ovarian tissues are required to determine whether altered gene expression could result in any downstream consequences.

Identification of Novel Immunologic Checkpoint Gene Prognostic Markers for Ovarian Cancer

Ovarian cancer has a higher resistance to chemotherapy, displaying the highest mortality rate among gynecological cancers. Recently, immune checkpoint inhibitor therapy is an effective treatment for selected patients. However, a low response rate for immune checkpoint treatment was observed for ovarian cancer patients. Therefore, it is necessary to identify ovarian cancer patients who might gain benefits from immune checkpoint treatment. Datasets containing ovarian cancer samples with mRNA-seq and clinical follow-up data were downloaded from different databases like The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The researchers applied the univariate analysis for selecting the immune checkpoint genes (ICGs) at a significance level of P < 0.05 as the candidate ICGs. The Spearman correlation coefficients were calculated to compare the correlation between tumor mutation burden and candidate ICGs, and the Kaplan-Meier plots were generated. They also assessed the external validation datasets and the results of immunohistochemical staining. 46 and 35 ICGs were extracted from the TCGA and GEO datasets, respectively, and we categorized the ICGs into 3 expression patterns. Nine (TCGA) and three (GEO) ICGs were significantly related to the prognosis. Univariate survival analysis indicated a significant prognostic relationship between the expression levels of ICOS, TIGIT, and TNFRSF8 and overall survival (OS). Moreover, the expression of ICOS and TIGIT also presented a significantly positive relationship with the CD8A expression. Importantly, patients with a higher CD8A and ICOS expression level (ICOS-H/CD8A-H) showed a better survival rate compared to other patients. Stratified analysis using TIGIT, TNFRSF8, and CD8A expression also showed an improved prognosis for the high TIGIT/high CD8A expression subgroup and the low TNFRSF8/low CD8A expression subgroup compared to the other subgroups. This study identified different immune subtypes that can predict the OS of ovarian cancer patients. This data could prove to be beneficial for making important clinical decisions and designing individual immunotherapeutic strategies.

Adaptive transcriptomic and immune infiltrate responses in the tumor immune microenvironment following neoadjuvant chemotherapy in high grade serous ovarian cancer reveal novel prognostic associations and activation of pro-tumorigenic pathways

The high rate of ovarian cancer recurrence and chemoresistance necessitates further research into how chemotherapy affects the tumor immune microenvironment (TIME). While studies have shown that immune infiltrate increases following neoadjuvant (NACT) chemotherapy, there lacks a comprehensive understanding of chemotherapy-induced effects on immunotranscriptomics and cancer-related pathways and their relationship with immune infiltrate and patient responses. In this study, we performed NanoString nCounter^® PanCancer IO360 analysis of 31 high grade serous ovarian cancer (HGSOC) patients with matched pre-treatment biopsy and post-NACT tumor. We observed increases in pro-tumorigenic and immunoregulatory pathways and immune infiltrate following NACT, with striking increases in a cohort of genes centered on the transcription factors ATF3 and EGR1. Using quantitative PCR, we analyzed several of the top upregulated genes in HGSOC cell lines, noting that two of them, ATF3 and AREG, were consistently upregulated with chemotherapy exposure and significantly increased in platinum resistant cells compared to their sensitive counterparts. Furthermore, we observed that pre-NACT immune infiltrate and pathway scores were not strikingly related to platinum free interval (PFI), but post-NACT immune infiltrate, pathway scores, and gene expression were. Finally, we found that higher levels of a cohort of proliferative and DNA damage-related genes was related to shorter PFI. This study underscores the complex alterations in the ovarian TIME following chemotherapy exposure and begins to untangle how immunologic factors are involved in mediating chemotherapy response, which will allow for the future development of novel immunologic therapies to combat chemoresistance.

A novel 4 immune-related genes as diagnostic markers and correlated with immune infiltrates in major depressive disorder

Background

Immune response is prevalently related with major depressive disorder (MDD) pathophysiology. However, the study on the relationship between immune-related genes (IRGs) and immune infiltrates of MDD remains scarce.

Methods

We extracted expression data of 148 MDD patients from 2 cohorts, and systematically characterized differentially expressed IRGs by using limma package in R software. Then, the LASSO and multivariate logistic regression analysis was used to identify the most powerful IRGs. Next, we analyzed the relationship between IRGs and immune infiltrates of MDD. Finally, GSE76826 was used to to verificate of IRGs as a diagnostic markers in MDD.

Results

203 different IRGs s in MDD has been identified (P < 0.05). GSEA revealed that the different IRGs was more likely to be enriched in immune-specific pathways. Then, a 9 IRGs was successfully established to predict MDD based on LASSO. Next, 4 IRGs was obtained by multivariate logistic regression analysis, and AUC for CD1C, SPP1, CD3D, CAMKK2, and IRGs model was 0.733, 0.767, 0.816, 0.800, and 0.861, suggesting that they have a good diagnostic performance. Furthermore, the proportion of T cells CD8, T cells γδ, macrophages M0, and NK cells resting in MDD group was lower than that in the healthy controls, suggesting that the immune system in MDD group is impaired. Simultaneously, CD3D was validated a reliable marker in MDD, and was positively correlated with T cells CD8. GSEA revealed high expression CD3D was more likely to be enriched in immune-specific pathways, and low expression CD3D was more likely to be enriched in glucose metabolism metabolism-specific pathways.

Conclusions

We applied bioinformatics approaches to suggest that a 4 IRGs could serve as diagnostic markers to provide a novel direction to explore the pathogenesis of MDD.

Prognostic immunologic signatures in epithelial ovarian cancer

Epithelial Ovarian Cancer (EOC) is a deadly gynecologic malignancy in which patients frequently develop recurrent disease following initial platinum-taxane chemotherapy. Analogous to many other cancer subtypes, EOC clinical trials have centered upon immunotherapeutic approaches, most notably programmed cell death 1 (PD-1) inhibitors. While response rates to these immunotherapies in EOC patients have been low, evidence suggests that ovarian tumors are immunogenic and that immune-related genomic profiles can serve as prognostic markers. This review will discuss recent advances in the development of immune-based prognostic signatures in EOC that predict patient clinical outcomes, as well as emphasize specific research areas that need to be addressed to drive this field forward.

Gene Expression Subtyping Reveals Immune alterations:TCGA Database for Prognosis in Ovarian Serous Cystadenocarcinoma

Serous ovarian cancer is the most common and primary death type in ovarian cancer. In recent studies, tumor microenvironment and tumor immune infiltration significantly affect the prognosis of ovarian cancer. This study analyzed the four gene expression types of ovarian cancer in TCGA database to extract differentially expressed genes and verify the prognostic significance. Meanwhile, functional enrichment and protein interaction network analysis exposed that these genes were related to immune response and immune infiltration. Subsequently, we proved these prognostic genes in an independent data set from the GEO database. Finally, multivariate cox regression analysis revealed the prognostic significance of TAP1 and CXCL13. The genetic alteration and interaction network of these two genes were shown. Then, we established a nomogram model related to the two genes and clinical risk factors. This model performed well in Calibration plot and Decision Curve Analysis. In conclusion, we have obtained a list of genes related to the immune microenvironment with a better prognosis for serous ovarian cancer, and based on this, we have tried to establish a clinical prognosis model.

Immune Modeling Analysis Reveals Immunologic Signatures Associated With Improved Outcomes in High Grade Serous Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy worldwide, as patients are typically diagnosed at a late stage and eventually develop chemoresistant disease following front-line platinum-taxane based therapy. Only modest results have been achieved with PD-1 based immunotherapy in ovarian cancer patients, despite the fact that immunological responses are observed in EOC patients. Therefore, the goal of this present study was to identify novel immune response genes and cell subsets significantly associated with improved high grade serous ovarian cancer (HGSOC) patient prognosis. A transcriptomic-based immune modeling analysis was employed to determine levels of 8 immune cell subsets, 10 immune escape genes, and 22 co-inhibitory/co-stimulatory molecules in 26 HGSOC tumors. Multidimensional immune profiling analysis revealed CTLA-4, LAG-3, and Tregs as predictive for improved progression-free survival (PFS). Furthermore, the co-stimulatory receptor ICOS was also found to be significantly increased in patients with a longer PFS and positively correlated with levels of CTLA-4, PD-1, and infiltration of immune cell subsets. Both ICOS and LAG-3 were found to be significantly associated with improved overall survival in The Cancer Genome Atlas (TCGA) ovarian cancer cohort. Finally, PVRL2 was identified as the most highly expressed transcript in our analysis, with immunohistochemistry results confirming its overexpression in HGSOC samples compared to normal/benign. Results were corroborated by parallel analyses of TCGA data. Overall, this multidimensional immune modeling analysis uncovers important prognostic immune factors that improve our understanding of the unique immune microenvironment of ovarian cancer.