P-MAPA activates TLR2 and TLR4 signaling while its combination with IL-12 stimulates CD4+ and CD8+ effector T cells in ovarian cancer

Recent advances in understanding the immune microenvironment in ovarian cancer

The occurrence of ovarian cancer (OC) is a major factor in women's mortality rates. Despite progress in medical treatments, like new drugs targeting homologous recombination deficiency, survival rates for OC patients are still not ideal. The tumor microenvironment (TME) includes cancer cells, fibroblasts linked to cancer (CAFs), immune-inflammatory cells, and the substances these cells secrete, along with non-cellular components in the extracellular matrix (ECM). First, the TME mainly plays a role in inhibiting tumor growth and protecting normal cell survival. As tumors progress, the TME gradually becomes a place to promote tumor cell progression. Immune cells in the TME have attracted much attention as targets for immunotherapy. Immune checkpoint inhibitor (ICI) therapy has the potential to regulate the TME, suppressing factors that facilitate tumor advancement, reactivating immune cells, managing tumor growth, and extending the survival of patients with advanced cancer. This review presents an outline of current studies on the distinct cellular elements within the OC TME, detailing their main functions and possible signaling pathways. Additionally, we examine immunotherapy rechallenge in OC, with a specific emphasis on the biological reasons behind resistance to ICIs.

The potential role of interleukins and interferons in ovarian cancer

Ovarian cancer poses significant challenges and remains a highly lethal disease with limited treatment options. In the context of ovarian cancer, interleukins (ILs) and interferons (IFNs), important cytokines that play crucial roles in regulating the immune system, have emerged as significant factors influencing its development. This article provides a comprehensive review of the involvement of various ILs, including those from the IL-1 family, IL-2 family, IL-6 family, IL-8 family, IL-10 family, and IL-17 family, in ovarian cancer. The focus is on their impact on tumor growth, metastasis, and their role in evading immune responses within the tumor microenvironment. Additionally, the article conducts an in-depth examination of the oncogenic or antitumor roles of each IL in the context of ovarian cancer pathogenesis and progression. Besides, we elucidated the enhancements in the treatment of ovarian cancer through the utilization of type-I IFN and type-II IFN. Recent research has shed light on the intricate mechanisms through which specific ILs and IFNs contribute to the advancement of the disease. By incorporating recent findings, this review also seeks to inspire further investigations into unexplored mechanisms, fostering ongoing research to develop more effective therapeutic strategies for ovarian cancer. Moreover, through an in-depth analysis of IL- and IFN-associated clinical trials, we have highlighted their promising potential of in the treatment of ovarian cancer. These clinical trials serve to reinforce the significant outlook for utilizing ILs and IFNs as therapeutic agents in combating this disease.

Integrative evaluation and experimental validation of the immune-modulating potential of dysregulated extracellular matrix genes in high-grade serous ovarian cancer prognosis

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is a challenging malignancy characterized by complex interactions between tumor cells and the surrounding microenvironment. Understanding the immune landscape of HGSOC, particularly the role of the extracellular matrix (ECM), is crucial for improving prognosis and guiding therapeutic interventions.

METHODS AND RESULTS

Using univariate Cox regression analysis, we identified 71 ECM genes associated with prognosis in seven HGSOC populations. The ECMscore signature, consisting of 14 genes, was validated using Cox proportional hazards regression with a lasso penalty. Cox regression analyses demonstrated that ECMscore is an excellent indicator for prognostic classification in prevalent malignancies, including HGSOC. Moreover, patients with higher ECMscores exhibited more active stromal and carcinogenic activation pathways, including apical surface signaling, Notch signaling, apical junctions, Wnt signaling, epithelial-mesenchymal transition, TGF-beta signaling, and angiogenesis. In contrast, patients with relatively low ECMscores showed more active immune-related pathways, such as interferon alpha response, interferon-gamma response, and inflammatory response. The relationship between the ECMscore and genomic anomalies was further examined. Additionally, the correlation between ECMscore and immune microenvironment components and signals in HGSOC was examined in greater detail. Moreover, the expression of MGP, COL8A2, and PAPPA and its correlation with FAP were validated using qRT-PCR on samples from HGSOC. The utility of ECMscore in predicting the prospective clinical success of immunotherapy and its potential in guiding the selection of chemotherapeutic agents were also explored. Similar results were obtained from pan-cancer research.

CONCLUSION

The comprehensive evaluation of the ECM may help identify immune activation and assist patients in HGSOC and even pan-cancer in receiving proper therapy.

The emerging roles of TLR and cGAS signaling in tumorigenesis and progression of ovarian cancer

Ovarian cancer is fatal to women and has a high mortality rate. Although on-going efforts are never stopped in identifying diagnostic and intervention strategies, the disease is so far unable to be well managed. The most important reason for this is the complexity of pathogenesis for OC, and therefore, uncovering the essential molecular biomarkers accompanied with OC progression takes the privilege for OC remission. Inflammation has been reported to participate in the initiation and progression of OC. Both microenvironmental and tumor cell intrinsic inflammatory signals contribute to the malignancy of OC. Inflammation responses can be triggered by various kinds of stimulus, including endogenous damages and exogenous pathogens, which are initially recognized and orchestrated by a series of innate immune system related receptors, especially Toll like receptors, and cyclic GMP-AMP synthase. In this review, we will discuss the roles of innate immune system related receptors, including TLRs and cGAS, and responses both intrinsic and exogenetic in the development and treatment of OC.

KIF26B-AS1 Regulates TLR4 and Activates the TLR4 Signaling Pathway to Promote Malignant Progression of Laryngeal Cancer

Laryngeal cancer is one of the highest incidence, most prevalently diagnosed head and neck cancers, making it critically necessary to probe effective targets for laryngeal cancer treatment. Here, real-time quantitative reverse transcription PCR (qRT-PCR) and western blot analysis were used to detect gene expression levels in laryngeal cancer cell lines. Fluorescence in situ hybridization (FISH) and subcellular fractionation assays were used to detect the subcellular location. Functional assays encompassing Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), transwell and wound healing assays were performed to examine the effects of target genes on cell proliferation and migration in laryngeal cancer. The in vivo effects were proved by animal experiments. RNA-binding protein immunoprecipitation (RIP), RNA pulldown and luciferase reporter assays were used to investigate the underlying regulatory mechanisms. The results showed that KIF26B antisense RNA 1 (KIF26B-AS1) propels cell proliferation and migration in laryngeal cancer and regulates the toll-like receptor 4 (TLR4) signaling pathway. KIF26B-AS1 also recruits FUS to stabilize TLR4 mRNA, consequently activating the TLR4 signaling pathway. Furthermore, KIF26B-AS1 plays an oncogenic role in laryngeal cancer via upregulating TLR4 expression as well as the FUS/TLR4 pathway axis, findings which offer novel insight for targeted therapies in the treatment of laryngeal cancer patients.

Immune-Related Long Non-coding RNA Constructs a Prognostic Signature of Ovarian Cancer

Background

Since ovarian cancer leads to the poor prognosis in women all over the world, we aim to construct an immune-related lncRNAs signature to improve the survival of ovarian cancer patients.

Methods

Normal and cancer patient samples and corresponding clinical data of ovarian were obtained from The Genotype-Tissue Expression (GTEx) portal and The Cancer Genome Atlas (TCGA) database. The predictive signature was constructed by the lasso penalty Cox proportional hazard regression model. The division of different risk groups was accounting for the optimal critical value of the time-dependent Receiver Operating Characteristic (ROC) curve. Finally, we validated and evaluated the application of this prognostic signature based on the clinical factors, chemo-sensitivity and immune status of different risk groups.

Results

The signature was established from 145 DEirlncRNAs and can be shown as an independent prognostic risk factor with accurate prediction on overall survival in ovarian cancer patients. Further analysis on the application of the prognostic signature showed that patients with low-risk had a better sensitivity to chemotherapy and a higher immunogenicity.

Conclusion

We constructed and verified an effective signature based on DEirlncRNA pairs, which could predict the prognosis, drug sensitivity and immune status of ovarian cancer patients and promote the prognostic estimation and individualized treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12575-021-00161-9.

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.

Toll-like receptor 2 (TLR2) is a candidate prognostic factor in testicular germ cell tumors as well as an indicator of immune function in the tumor microenvironment

Testicular cancer is the most common malignant tumor in young men, and its incidence has increased in recent years. The tumor microenvironment (TME) plays a crucial role in the development and progression of tumors; however, the TME of testicular germ cell tumor (TGCT) is poorly understood. In this study, we downloaded information for 156 TGCT cases from The Cancer Genome Atlas (TCGA) database, used the ESTIMATE method to determine immune and stromal scores, and used CIBERSORT to calculate the proportion of tumor-infiltrating immune cells (TICs). The differentially expressed genes were subjected to a COX regression analysis and used for the construction of a protein–protein interaction (PPI) network. Toll-like receptor 2 (TLR2) was identified as a predictive marker by combining the results of the Cox regression analysis and PPI network. A survival analysis showed that TLR2 was positively correlated with TGCT survival. A gene set enrichment analysis indicated that genes in the high TLR2 expression group were enriched for cell adhesion molecules (CAMs) and the chemokine signaling pathway, and genes in the low TLR2 expression group were mainly enriched in the spliceosome. Regarding proportions of TICs, naive B cells and follicular helper T cells were negatively correlated with the expression of TLR2. This suggests that as TLR2 expression increases, the immunocompetence of the TME decreases. The expression of TLR2 may affect the prognosis of TGCT, suggesting that this locus can be used as a prognostic factor for TGCT.

Tumor Immune Microenvironment Related Gene-Based Model to Predict Prognosis and Response to Compounds in Ovarian Cancer

BACKGROUND

The tumor immune microenvironment (TIME) has been recognized to be an imperative factor facilitating the acquisition of many cancer-related hallmarks and is a critical target for targeted biological therapy. This research intended to construct a risk score model premised on TIME-associated genes for prediction of survival and identification of potential drugs for ovarian cancer (OC) patients.

METHODS AND RESULTS

The stromal and immune scores were computed utilizing the ESTIMATE algorithm in OC patient samples from The Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network and differentially expressed genes analyses were utilized to detect stromal-and immune-related genes. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was utilized for additional gene selection. The genes that were selected were utilized as the input for a stepwise regression to construct a TIME-related risk score (TIMErisk), which was then validated in Gene Expression Omnibus (GEO) database. For the evaluation of the protein expression levels of TIME regulators, the Human Protein Atlas (HPA) dataset was utilized, and for their biological functions, the TIMER and CIBERSORT algorithm, immunoreactivity, and Immune Cell Abundance Identifier (ImmuCellAI) were used. Possible OC medications were forecasted utilizing the Genomics of Drug Sensitivity in Cancer (GDSC) database and connectivity map (CMap). TIMErisk was developed based on ALPK2, CPA3, PTGER3, CTHRC1, PLA2G2D, CXCL11, and ZNF683. High TIMErisk was recognized as a poor factor for survival in the GEO and TCGA databases; subgroup analysis with FIGO stage, grade, lymphatic and venous invasion, debulking, and tumor site also indicated similar results. Functional immune cells corresponded to more incisive immune reactions, including secretion of chemokines and interleukins, natural killer cell cytotoxicity, TNF signaling pathway, and infiltration of activated NK cells, eosinophils, and neutrophils in patients with low TIMErisk. Several small molecular medications which may enhance the prognosis of patients in the TIMErisk subgroup were identified. Lastly, an enhanced predictive performance nomogram was constructed by compounding TIMErisk with the FIGO stage and debulking.

CONCLUSION

These findings may offer a valuable indicator for clinical stratification management and personalized therapeutic options for OC patients and may be a foundation for future mechanistic research of their association.

The Role of CCL20-CCR6 Axis in Ovarian Cancer Metastasis

Background

Chemokine networks play a key and complex role in tumor progression. CCL20 and its unique receptor CCR6 have been reported to mediate malignant biological activities in various cancers, but their role in ovarian cancer metastasis remains unclear.

Purpose

Our study aims to explore the effect of CCL20-CCR6 axis on ovarian cancer metastasis and its potential mechanism.

Methods

The transwell assay was used to detect the cell migration and invasion after CCL20 treatment. The CCK-8 assay was used to detect the cell viability after CCL20 treatment and CCR6 depletion. The mRNA and protein expression were assayed through qRT-PCR and Western blotting. The siRNAs and CRISPR-Cas9 system were adopted to suppress CCR6 expression. Intraperitoneal xenograft mouse model was constructed to test the pro-metastasis effect of CCL20-CCR6 axis in vivo. The differentially expressed genes induced by CCL20 were identified through RNA-sequencing, and immunohistochemistry staining was used to detect their protein expression in tumor tissues.

Results

Our results revealed that CCL20 treatment selectively promoted the migration and invasion of CCR6^high ovarian cancer cells, but had no effect on CCR6^low cells. Blockade of CCR6 expression effectively reversed the cell migration and invasion induced by CCL20 stimulation. Animal experiment proved that CCL20-CCR6 axis mediated ovarian cancer metastasis in vivo. The differentially expressed genes after CCL20 stimulation were associated with metastasis, and CCL20 induced an increased expression of CDH2 and VCAN and decreased CDH1 expression in cancer cells. Moreover, CCL20 stimulated the expression of N-cadherin and versican in tumor tissues and inhibited the expression of E-cadherin, while CCR6 knockout successfully blocked the expression changes.

Conclusion

Our findings revealed that CCL20-CCR6 axis promotes ovarian cancer metastasis both in vivo and in vitro, probably through increasing cancer cell adhesion and epithelial–mesenchymal transition. Blockade of CCL20-CCR6 axis might become a novel anti-tumor therapeutic target for ovarian cancer.