Biomarker Discovery for Meta-Classification of Melanoma Metastatic Progression Using Transfer Learning

Promotion of apoptosis in melanoma cells by taxifolin through the PI3K/AKT signaling pathway: Screening of natural products using WGCNA and CMAP platforms

Melanoma is a skin cancer originating from melanocytes. The global incidence rate of melanoma is rapidly increasing, posing significant public health challenges. Identifying effective therapeutic agents is crucial in addressing this growing problem. Natural products have demonstrated promising anti-tumor activity. In this study, a plant flavonoid, taxifolin, was screened using Weighted Correlation Network Analysis (WGCNA) in combination with the Connectivity Map (CMAP) platform. Taxifolin was confirmed to inhibit the proliferation, migration, and invasion ability of melanoma A375 and MV-3 cells by promoting apoptosis. Additionally, it suppressed the Epithelial-Mesenchymal Transition (EMT) process of melanoma cells. Cyber pharmacological analysis revealed that taxifolin exerts its inhibitory effect on melanoma through the PI3K/AKT signaling pathway, specifically by downregulating the protein expression of p-PI3K and p-AKT. Notably, the addition of SC-79, an activator of the PI3K/AKT signaling pathway, reversed the effects of taxifolin on cell migration and apoptosis. Furthermore, in vivo experiments demonstrated that taxifolin treatment slowed tumor growth in mice without significant toxic effects. Based on these findings, taxifolin holds promise as a potential drug for melanoma treatment.

Current knowledge about immunotherapy resistance for melanoma and potential predictive and prognostic biomarkers

Melanoma still reaches thousands of new diagnoses per year, and its aggressiveness makes recovery challenging, especially for those with stage III/IV unresectable melanoma. Immunotherapy, emerging as a beacon of hope, stands at the forefront of treatments for advanced melanoma. This review delves into the various immunotherapeutic strategies, prominently featuring cytokine immunotherapy, adoptive cell therapy, immune checkpoint inhibitors, and vaccinations. Among these, immune checkpoint inhibitors, notably anti-programmed cell death-1 (PD-1) and anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) antibodies, emerge as the leading strategy. However, a significant subset of melanoma patients remains unresponsive to these inhibitors, underscoring the need for potent biomarkers. Efficient biomarkers have the potential to revolutionize the therapeutic landscape by facilitating the design of personalized treatments for patients with melanoma. This comprehensive review highlights the latest advancements in melanoma immunotherapy and potential biomarkers at the epicenter of recent research endeavors.

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.

Neurotransmitter receptor-related gene signature as potential prognostic and therapeutic biomarkers in colorectal cancer

Background: Colorectal cancer is one of the most common malignant tumors worldwide. A various of neurotransmitter receptors have been found to be expressed in tumor cells, and the activation of these receptors may promote tumor growth and metastasis. This study aimed to construct a novel neurotransmitter receptor-related genes signature to predict the survival, immune microenvironment, and treatment response of colorectal cancer patients. Methods: RNA-seq and clinical data of colorectal cancer from The Cancer Genome Atlas database and Gene Expression Omnibus were downloaded. Neurotransmitter receptor-related gene were collected from publicly available data sources. The Weighted Gene Coexpression Network Analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms were employed to construct the Neurotransmitter receptor-related gene prognostic signature. Further analyses, functional enrichment, CIBERSORTx, The Tumor Immune Single Cell Center (TISCH), survival analysis, and CellMiner, were performed to analyze immune status and treatment responses. Quantitative real-time polymerase chain reaction (qRT-PCR) assays were carried out to confirm the expression levels of prognostic genes. Results: By combining machine learning algorithm and WGCNA, we identified CHRNA3, GABRD, GRIK3, and GRIK5 as Neurotransmitter receptor-related prognostic genes signature. Functional enrichment analyses showed that these genes were enriched with cellular metabolic-related pathways, such as organic acid, inorganic acid, and lipid metabolism. CIBERSORTx and Single cell analysis showed that the high expression of genes were positively correlated with immunosuppressive cells infiltration, and the genes were mainly expressed in cancer-associated fibroblasts and endothelial cells. A nomogram was further built to predict overall survival (OS). The expression of CHRNA3, GABRD, GRIK3, and GRIK5 in cancer cells significantly impacted their response to chemotherapy. Conclusion: A neurotransmitter receptor-related prognostic gene signature was developed and validated in the current study, giving novel sights of neurotransmitter in predicting the prognostic and improving the treatment of CRC.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

An update on methods for detection of prognostic and predictive biomarkers in melanoma

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.