A Comprehensive RNA Expression Signature for Cervical Squamous Cell Carcinoma Prognosis

Characterization of a predictive signature for tumor microenvironment and immunotherapy response in hepatocellular carcinoma involving neutrophil extracellular traps

Neutrophil extracellular traps (NETs) and other factors play a significant role in impacting the prognosis of patients with Hepatocellular carcinoma (HCC). Nevertheless, further research is warranted to fully elucidate the prognostic implications of NETs in patients with HCC. We employed a hierarchical clustering technique to examine the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) data and identified subtypes associated with NETs. Subsequently, we utilized LASSO regression analysis to identify a distinct gene expression pattern within these subtypes. The strength of this signature was further validated through analysis of TCGA-LIHC and International Cancer Genome Consortium-Liver Cancer (ICGC-LIRI-JP) data. Our findings resulted in the construction of a six-gene signature related to NETs, which can predict survival outcomes in HCC patients. To enhance the predictive accuracy of our tool, we developed a nomogram that integrates the NETs signature with clinicopathological characteristics. We validated the significance of NETs in HCC patients using qRT-PCR and immunohistochemistry assays, along with in vitro experiments targeting high-risk genes. Furthermore, our exploration of the immune microenvironment uncovered augmented immune-specific metrics within the low-risk cohort, implying potential disparities in immune-related attributes between the high-risk and low-risk contingents. In summary, the NETs signature we discovered serves as a valuable biomarker and provides guidance for personalized therapy in HCC patients.

LncRNA JHDM1D-AS1 promotes osteogenic differentiation of periodontal ligament cells by targeting miR-532-5p to activate IGF1R signaling

OBJECTIVE

The aim of this study was to explore the mechanism underlying periodontal ligament cells (PDLCs) osteogenic differentiation.

BACKGROUND

Periodontitis causes damage to tooth-supporting apparatus and eventually leads to tooth loss. PDLCs hold great promise in periodontal regeneration due to their osteogenic features.

METHODS

The expression of osteogenic markers, lncRNA JHDM1D-AS1, miR-532-5p and IGF1R was examined. For osteogenic differentiation, primary human PDLCs (hPDLCs) were cultured in an osteogenic medium, and it was assessed by ALP activity and Alizarin Red staining. The interaction between JHDM1D-AS1, miR-532-5p and IGF1R was analyzed via dual luciferase, RIP and RNA pull-down assays.

RESULTS

JHDM1D-AS1 was up-regulated during osteogenic differentiation and its silencing inhibited hPDLC osteogenic differentiation. JHDM1D-AS1 worked as a miR-532-5p sponge in hPDLCs. miR-532-5p directly targeted IGF1R to suppress its expression, and miR-532-5p knockdown facilitated osteogenic differentiation of hPDLCs. Overexpression of IGF1R promoted osteogenic differentiation of hPDLCs via activating Notch/HES1 signaling in hPDLCs.

CONCLUSION

JHDM1D-AS1 promotes osteogenic differentiation of hPDLCs via sponging miR-532-5p to facilitate IGF1R expression and activate Notch/HES1 signaling.

The Role of MiRNA in Cancer: Pathogenesis, Diagnosis, and Treatment

Cancer is also determined by the alterations of oncogenes and tumor suppressor genes. These gene expressions can be regulated by microRNAs (miRNA). At this point, researchers focus on addressing two main questions: "How are oncogenes and/or tumor suppressor genes regulated by miRNAs?" and "Which other mechanisms in cancer cells are regulated by miRNAs?" In this work we focus on gathering the publications answering these questions. The expression of miRNAs is affected by amplification, deletion or mutation. These processes are controlled by oncogenes and tumor suppressor genes, which regulate different mechanisms of cancer initiation and progression including cell proliferation, cell growth, apoptosis, DNA repair, invasion, angiogenesis, metastasis, drug resistance, metabolic regulation, and immune response regulation in cancer cells. In addition, profiling of miRNA is an important step in developing a new therapeutic approach for cancer.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

Construction and validation of a novel prognostic signature of microRNAs in lung adenocarcinoma

MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.

OScc: an online survival analysis web server to evaluate the prognostic value of biomarkers in cervical cancer

Aim: To establish a web server that can mutually validate prognostic biomarkers of cervical cancer. Methods: Four datasets including expression profiling and relative clinical follow-up data were collected from Gene Expression Omnibus and The Cancer Genome Atlas. The web server was developed by R software. Results: The web server was named OScc including 690 patients and can be accessed at http://bioinfo.henu.edu.cn/CESC/CESCList.jsp . The Kaplan–Meier survival curves with log-rank p-value and hazard ratio will be generated of interested gene in OScc. Compared with previous predictive tools, OScc had the advantages of registration-free, larger sample size and subgroup analysis. Conclusion: The OScc is highly valuable to perform the preliminary assessment and validation of new or interested prognostic biomarkers for cervical cancer.

Observed Survival Interval: A Supplement to TCGA Pan-Cancer Clinical Data Resource

To drive high-quality omics translational research using The Cancer Genome Atlas (TCGA) data, a TCGA Pan-Cancer Clinical Data Resource was proposed. However, there is an out-of-step issue between clinical outcomes and the omics data of TCGA for skin cutaneous melanoma (SKCM), due to the majority of metastatic samples. In clinical cases, the survival time started from the initial SKCM diagnosis, while the omics data were characterized at TCGA sampling. This study aimed to address this issue by proposing an observed survival interval (OBS), which was defined as the time interval from TCGA sampling to patient death or last follow-up. We compared the OBS with the usual recommended overall survival (OS) by associating them with both clinical data and microRNA sequencing data of TCGA-SKCM. We found that the OS of primary SKCM was significantly shorter than that of metastatic SKCM, while the opposite happened if OBS was compared. OS was associated with the pathological stage of both primary and metastatic SKCM, while OBS was associated with the pathological stage of primary SKCM but not that of metastatic SKCM. Five previously cross-validated survival-associated microRNAs were found to be associated with the OBS rather than OS in metastatic SKCM. Thus, the OBS was more appropriate for associating microRNA-omics data of TCGA-SKCM than OS, and it is a timely supplement to TCGA Pan-Cancer Clinical Data Resource.