Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer

Strategies for data normalization and missing data imputation and consequences for potential diagnostic microRNA biomarkers in epithelial ovarian cancer

MicroRNAs (miRNAs) are small non-coding RNA molecules regulating gene expression with diagnostic potential in different diseases, including epithelial ovarian carcinomas (EOC). As only a few studies have been published on the identification of stable endogenous miRNA in EOC, there is no consensus which miRNAs should be used aiming standardization. Currently, U6-snRNA is widely adopted as a normalization control in RT-qPCR when investigating miRNAs in EOC; despite its variable expression across cancers being reported. Therefore, our goal was to compare different missing data and normalization approaches to investigate their impact on the choice of stable endogenous controls and subsequent survival analysis while performing expression analysis of miRNAs by RT-qPCR in most frequent subtype of EOC: high-grade serous carcinoma (HGSC). 40 miRNAs were included based on their potential as stable endogenous controls or as biomarkers in EOC. Following RNA extraction from formalin-fixed paraffin embedded tissues from 63 HGSC patients, RT-qPCR was performed with a custom panel covering 40 target miRNAs and 8 controls. The raw data was analyzed by applying various strategies regarding choosing stable endogenous controls (geNorm, BestKeeper, NormFinder, the comparative ΔCt method and RefFinder), missing data (single/multiple imputation), and normalization (endogenous miRNA controls, U6-snRNA or global mean). Based on our study, we propose hsa-miR-23a-3p and hsa-miR-193a-5p, but not U6-snRNA as endogenous controls in HGSC patients. Our findings are validated in two external cohorts retrieved from the NCBI Gene Expression Omnibus database. We present that the outcome of stability analysis depends on the histological composition of the cohort, and it might suggest unique pattern of miRNA stability profiles for each subtype of EOC. Moreover, our data demonstrates the challenge of miRNA data analysis by presenting various outcomes from normalization and missing data imputation strategies on survival analysis.

A risk score system based on a six-microRNA signature predicts the overall survival of patients with ovarian cancer

BACKGROUND

Ovarian cancer (OVC) is a devastating disease worldwide; therefore the identification of prognostic biomarkers is urgently needed. We aimed to determine a robust microRNA signature-based risk score system that could predict the overall survival (OS) of patients with OVC.

METHODS

We extracted the microRNA expression profiles and corresponding clinical data of 467 OVC patients from The Cancer Genome Atlas (TCGA) database and further divided this data into training, validation and complete cohorts. The key prognostic microRNAs for OVC were identified and evaluated by robust likelihood-based survival analysis (RLSA) and multivariable Cox regression. Time-dependent receiver operating characteristic (ROC) curves were then constructed to evaluate the prognostic performance of these microRNAs. A total of 172 ovarian cancer samples and 162 normal ovarian tissues were used to verify the credibility and accuracy of the selected markers of the TCGA cohort by quantitative real-time polymerase chain reaction (PCR).

RESULTS

We successfully established a risk score system based on a six-microRNA signature (hsa-miR-3074-5p, hsa-miR-758-3p, hsa-miR-877-5p, hsa-miR-760, hsa-miR-342-5p, and hsa-miR-6509-5p). This microRNA based system is able to characterize patients as either high or low risk. The OS of OVC patients, with either high or low risk, was significantly different when compared in the training cohort (p < 0.001), the validation cohort (p < 0.001) and the complete cohort (p < 0.001). Analysis of clinical samples further demonstrated that these microRNAs were aberrantly expressed in OVC tissues. The six-miRNA-based signature was correlated with the prognosis of OVC patients (p < 0.001).

CONCLUSIONS

The study established a novel risk score system that is predictive of patient prognosis and is a potentially useful guide for the personalized treatment of OVC patients.

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.

Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer

BACKGROUND

Increasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored.

METHODS

We developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patients with NSCLC through integrative analysis for lncRNA, immune and clinical profiles of 115 immune cell lines, 187 NSCLC cell lines and 1533 patients with NSCLC. Then the influence of the TILSig on the prognosis and immunotherapy in NSCLC was comprehensively investigated.

RESULTS

Computational immune and lncRNA profiling analysis identified an lncRNA signature (TILSig) consisting of seven lncRNAs associated with tumor immune infiltration. The TILSig significantly stratified patients into the immune-cold group and immune-hot group in both training and validation cohorts. These immune-hot patients exhibit significantly improved survival outcome and greater immune cell infiltration compared with immune-cold patients. Multivariate analysis revealed that the TILSig is an independent predictive factor after adjusting for other clinical factors. Further analysis accounting for TILSig and immune checkpoint gene revealed that the TILSig has a discriminatory power in patients with similar expression levels of immune checkpoint genes and significantly prolonged survival was observed for patients with low TILSig and low immune checkpoint gene expression implying a better response to immune checkpoint inhibitor (ICI) immunotherapy.

CONCLUSIONS

Our finding demonstrated the importance and value of lncRNAs in evaluating the immune infiltrate of the tumor and highlighted the potential of lncRNA coupled with specific immune checkpoint factors as predictive biomarkers of ICI response to enable a more precise selection of patients.

MiRNAs Correlate with HLA Expression in Uveal Melanoma: Both Up- and Downregulation Are Related to Monosomy 3

Simple Summary

Uveal melanoma (UM) is a rare ocular malignancy that often gives rise to metastases. Tumours with an inflammatory phenotype have an especially bad prognosis. As an increased HLA expression and the presence of tumour-infiltrating lymphocytes and macrophages may be regulated by miRNAs, we set out to investigate whether any miRNAs are associated with inflammatory parameters in this malignancy. Some miRNAs were increased in UM with a high HLA expression and high T cell numbers, while others were decreased, showing two opposing patterns; however, both patterns were related to the tumour’s chromosome 3/BAP1 status. We conclude that specific miRNAs are related to the inflammatory phenotype and that these are differentially expressed between disomy 3/BAP1-positive versus monosomy 3/BAP1-negative UM.

Abstract

MicroRNAs are known to play a role in the regulation of inflammation. As a high HLA Class I expression is associated with a bad prognosis in UM, we set out to determine whether any miRNAs were related to a high HLA Class I expression and inflammation. We also determined whether such miRNAs were related to the UM’s genetic status. The expression of 125 miRNAs was determined in 64 primary UM from Leiden. Similarly, the mRNA expression of HLA-A, HLA-B, TAP1, BAP1, and immune cell markers was obtained. Expression levels of 24 of the 125 miRNAs correlated with expression of at least three out of four HLA Class I probes. Four miRNAs showed a positive correlation with HLA expression and infiltration with leukocytes, 20 a negative pattern. In the first group, high miRNA levels correlated with chromosome 3 loss/reduced BAP1 mRNA expression, in the second group low miRNA levels. The positive associations between miRNA-22 and miRNA-155 with HLA Class I were confirmed in the TCGA study and Rotterdam cohort, and with TAP1 in the Rotterdam data set; the negative associations between miRNA-125b2 and miRNA-211 and HLA-A, TAP1, and CD4 were confirmed in the Rotterdam set. We demonstrate two patterns: miRNAs can either be related to a high or a low HLA Class I/TAP1 expression and the presence of infiltrating lymphocytes and macrophages. However, both patterns were associated with chromosome 3/BAP1 status, which suggests a role for BAP1 loss in the regulation of HLA expression and inflammation in UM through miRNAs.

Small non-coding RNAs in human cancer: function, clinical utility, and characterization

Small non-coding RNAs (sncRNAs) play critical roles in multiple regulatory processes, including transcription, post-transcription, and translation. Emerging evidence reveals the critical roles of sncRNAs in cancer development and their potential role as biomarkers and/or therapeutic targets. In this paper, we review recent research on four sncRNA species with functional significance in cancer: small nucleolar RNAs, transfer RNA, small nuclear RNAs, and piwi-interacting RNAs. We introduce their functional roles in tumorigenesis and discuss the potential utility of sncRNAs as prognostic and diagnostic biomarkers and therapeutic targets. We further summarize approaches to characterize sncRNAs in a high-throughput manner, including the specific library construction and computational framework. Our review provides a perspective of the functions, clinical utility, and characterization of sncRNAs in cancer.

Six-gene-based prognostic model predicts overall survival in patients with uveal melanoma

BACKGROUND

Uveal melanoma (UM) is the most common primary intraocular tumor in adults, which has a high mortality rate and worse prognosis. Therefore, early potential molecular detection and prognostic evaluation seem more important for early diagnosis and treatment.

METHODS

Gene expression data were obtained from The Cancer Genome Atlas-Uveal melanomas database. Survival genes were identified by univariate analysis and were regarded to be associated with the overall survival of UM patients. Then, pathway enrichment analysis of these survival genes was performed. Robust likelihood-based survival model and multivariate survival analysis were conducted to identify more reliable genes and the prognostic signature for UM survival prediction. Two internal datasets and another two UM datasets from Gene Expression Omnibus (GEO) were used for the validation of prognostic signature.

RESULTS

Firstly, 2,010 survival genes were screened by univariate survival analysis. GO and KEGG analysis revealed that these genes were mainly involved in pathways such as mRNA processing, RNA splicing, spliceosome and ubiquitin mediated proteolysis. Secondly, a six-gene signature was identified by Robust likelihood-based survival model approach. The gene expression of the six genes can successfully divide UM samples into high- and low-risk groups and have strong survival prediction ability. What's more, the expression of six genes was compared in 80 healthy adipose tissue samples obtained from GTEx (Genotype-Tissue Expression) database and further validated in internal datasets and GEO datasets, which also can predict UM patient survival.

CONCLUSIONS

The six genes (SH2D3A, TMEM201, LZTS1, CREG1, NIPA1 and HIST1H4E) model might play a vital role in prognosis of UM, which should be helpful for further insight into the treatment of uveal melanoma.

Overexpression of TEM8 promotes ovarian cancer progression via Rac1/Cdc42/JNK and MEK/ERK/STAT3 signaling pathways

Tumor endothelial cell marker 8 (TEM8) is a type I transmembrane protein, that has been widely studied in the areas of anthrax toxin infection and tumor angiogenesis. However, the role of TEM8 in the progression of epithelial ovarian cancer (EOC) remains unclear. In this study, we determined that TEM8 was highly expressed in ovarian cancer and associated with poor prognosis in EOC patients. In vitro experiments showed that TEM8 overexpression significantly promoted ovarian cancer proliferation. TEM8 overexpression also promoted the G0/G1 phase transition, migration, and invasion of ovarian cancer cells but suppressed apoptosis. Moreover, experimental verification confirmed that TEM8 overexpression increased the expression of Ki-67, cyclin D1, Bcl2/Bax, MMP2, MMP9, and VEGFA and the phosphorylation of Rac1/Cdc42, JNK, MEK, ERK, and STAT3 (Ser727). Subsequently, the addition of RAC1 (EHop-016) and MEK (PD98059) pathway inhibitors suppressed malignant behaviors in the TEM8 overexpression group, which robustly indicated that TEM8 activated Rac1/Cdc42/JNK and MEK/ERK/STAT3 signaling pathways. In addition, we also revealed that the transcription factor GATA2 bound to the TATTAGTTATCTTT site of the TEM8 promoter region and regulated its expression. In conclusion, our study may provide a new theoretical basis for TEM8 application as a clinical biomarker and potential target in EOC patients.

Regulation of PD-1/PD-L1 Pathway in Cancer by Noncoding RNAs

Immune checkpoint blockade has demonstrated significant anti-tumor immunity in an array of cancer types, yet the underlying regulatory mechanism of it is still obscure, and many problems remain to be solved. As an inhibitory costimulatory signal of T-cells, the programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) pathway can paralyze T-cells at the tumor site, enabling the immune escape of tumor cells. Although many antibodies targeting PD-1/PD-L1 have been developed to block their interaction for the treatment of cancer, the reduced response rate and resistance to the therapies call for further comprehension of this pathway in the tumor microenvironment. MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are two main types of noncoding RNAs that play critical parts in the regulation of immune response in tumorigenesis, including the PD-1/PD-L1 pathway. Here we summarize the most recent studies on the control of this pathway by noncoding RNAs in cancer and hopefully will offer new insights into immune checkpoint blockade therapies.

Inhibition of miR-328-3p Impairs Cancer Stem Cell Function and Prevents Metastasis in Ovarian Cancer

Cancer stem cells (CSC) play a central role in cancer metastasis and development of drug resistance. miRNA are important in regulating CSC properties and are considered potential therapeutic targets. Here we report that miR-328-3p (miR-328) is significantly upregulated in ovarian CSC. High expression of miR-328 maintained CSC properties by directly targeting DNA damage binding protein 2, which has been shown previously to inhibit ovarian CSC. Reduced activity of ERK signaling in ovarian CSC, mainly due to a low level of reactive oxygen species, contributed to the enhanced expression of miR-328 and maintenance of CSC. Inhibition of miR-328 in mouse orthotopic ovarian xenografts impeded tumor growth and prevented tumor metastasis. In summary, our findings provide a novel mechanism underlying maintenance of the CSC population in ovarian cancer and suggest that targeted inhibition of miR-328 could be exploited for the eradication of CSC and aversion of tumor metastasis in ovarian cancer. SIGNIFICANCE: These findings present inhibition of miR-328 as a novel strategy for efficient elimination of CSC to prevent tumor metastasis and recurrence in patients with epithelial ovarian cancer.

Epigenetic Crosstalk between the Tumor Microenvironment and Ovarian Cancer Cells: A Therapeutic Road Less Traveled

Metastatic dissemination of epithelial ovarian cancer (EOC) predominantly occurs through direct cell shedding from the primary tumor into the intra-abdominal cavity that is filled with malignant ascitic effusions. Facilitated by the fluid flow, cells distribute throughout the cavity, broadly seed and invade through peritoneal lining, and resume secondary tumor growth in abdominal and pelvic organs. At all steps of this unique metastatic process, cancer cells exist within a multidimensional tumor microenvironment consisting of intraperitoneally residing cancer-reprogramed fibroblasts, adipose, immune, mesenchymal stem, mesothelial, and vascular cells that exert miscellaneous bioactive molecules into malignant ascites and contribute to EOC progression and metastasis via distinct molecular mechanisms and epigenetic dysregulation. This review outlines basic epigenetic mechanisms, including DNA methylation, histone modifications, chromatin remodeling, and non-coding RNA regulators, and summarizes current knowledge on reciprocal interactions between each participant of the EOC cellular milieu and tumor cells in the context of aberrant epigenetic crosstalk. Promising research directions and potential therapeutic strategies that may encompass epigenetic tailoring as a component of complex EOC treatment are discussed.