Comprehensive Analysis of the Immune Implication of TEX41 in Skin Cutaneous Melanoma

Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update

INTRODUCTION

Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma.

AREAS COVERED

The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma.

EXPERT OPINION

While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.

Pyroptosis-related lncRNAs: A novel prognosis signature of colorectal cancer

Pyroptosis is a newly discovered programmed cell death mechanism involved in tumorigenesis. Long non-coding RNAs (lncRNAs) have been implicated in colorectal cancer (CRC). However, the potential role of pyroptosis-related lncRNAs (PRLs) in CRC remains unelucidated. Therefore, we retrieved transcriptomic data of CRC patients from The Cancer Genome Atlas (TCGA). With the use of univariate and multivariate Cox proportional hazards regression models and the random forest algorithm, a new risk model was constructed based on eight PRLs: Z99289.2, FENDRR, CCDC144NL-ASL, TEX41, MNX1-AS1, NKILA, LINC02798, and LINC02381. Then, according to the Kaplan-Meier plots, the relationship of PRLs with the survival of CRC patients was explored and validated with our risk model in external datasets (Gene Expression Omnibus (GEO) databases; GEO17536, n = 177, and GSE161158, n = 250). To improve its clinical utility, a nomogram combining PRLs that could predict the clinical outcome of CRC patients was established. A full-spectrum immune landscape of CRC patients mediated by PRLs could be described. The PRLs were stratified into two molecular subtypes involved in immune modulators, immune infiltration of tumor immune microenvironment, and inflammatory pathways. Afterward, Tumor Immune Dysfunction and Exclusion (TIDE) and microsatellite instability (MSI) scores were analyzed. Three independent methods were applied to predict PRL-related sensitivity to chemotherapeutic drugs. Our comprehensive analysis of PRLs in CRC patients demonstrates a potential role of PRLs in predicting response to treatment and prognosis of CRC patients, which may provide a better understanding of molecular mechanisms underlying CRC pathogenesis and facilitate the development of effective immunotherapy.

Long Noncoding RNA LINC02249 Is a Prognostic Biomarker and Correlates with Immunosuppressive Microenvironment in Skin Cutaneous Melanoma

Skin cutaneous melanoma (SKCM) is one of the most aggressive and life-threatening tumors. It has a high incidence rate, as well as significant metastasis and fatality rates. To successfully treat SKCM and to increase the overall survival rate, early identification and risk stratification are both absolutely necessary. Long noncoding RNAs (lncRNAs) play a significant regulatory role in a variety of cancers. However, the expression and function of many lncRNAs have not been investigated. We evaluated the expression profile of the long noncoding RNA LINC02249 (LINC02249) in pan-cancers by using data on gene expression obtained from TCGA and GTEx. The biological function of LINC02249 was determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic value of LINC02249 expression in SKCM patients was statistically analyzed. Besides, the ssGSEA approach was utilized in order to investigate the degree to which LINC02249 expression is correlated with tumor immune infiltration. In this study, the expression of LINC02249 was found to be abnormally high in a variety of tumors, according to our findings. When compared with nontumor specimens, the level of expression of LINC02249 was shown to be significantly elevated in SKCM samples. GO and KEGG assays revealed LINC02249 may be involved in tumor progression. High expression of LINC02249 was associated with shorter overall survival and disease-specific survival of SKCM patients. More importantly, multivariate methods revealed that LINC02249 expression was an independent prognostic factor for SKCM cases. Using ssGSEA, we found that the expression of LINC02249 was negatively associated with different tumor-infiltrating immune cells, especially aDC, Treg, and macrophages. Overall, our findings suggested that LINC02249 can serve as a novel biomarker to predict the prognosis and immune infiltration in SKCM.