The Identification of the Metabolism Subtypes of Skin Cutaneous Melanoma Associated With the Tumor Microenvironment and the Immunotherapy

Comparative Analysis of the Effect of the BRAF Inhibitor Dabrafenib in 2D and 3D Cell Culture Models of Human Metastatic Melanoma Cells

BACKGROUND/AIM

Melanoma, a variant of skin cancer, presents the highest mortality rates among all skin cancers. Despite advancements in targeted therapies, immunotherapies, and tissue culture techniques, the absence of an effective early treatment model remains a challenge. This study investigated the impact of dabrafenib on both 2D and 3D cell culture models with distinct molecular profiles.

MATERIALS AND METHODS

We developed a high-throughput workflow enabling drug screening on spheroids. Our approach involved cultivating 2D and 3D cultures derived from normal melanocytes and metastatic melanoma cells, treating them with dabrafenib and conducting viability, aggregation, migration, cell cycle, and apoptosis assays.

RESULTS

Dabrafenib exerted multifaceted influences, particularly on migration at concentrations of 10 and 25 μM. It induced a decrease in cell viability, impeded cellular adhesion to the matrix, inhibited cellular aggregation and spheroid formation, arrested the cell cycle in the G1 phase, and induced apoptosis.

CONCLUSION

These results confirm the therapeutic potential of dabrafenib in treating melanoma with the BRAF V600E mutation and that 3D models are validated models to study the potential of new molecules for therapeutic purposes. Furthermore, our study underscores the relevance of 3D models in simulating physiological in vivo microenvironments, providing insights into varied treatment responses between normal and tumor cells.

Research progress on the role of cationic amino acid transporter (CAT) family members in malignant tumors and immune microenvironment

Amino acids are essential for the survival of all living organisms and living cells. Amino acid transporters mediate the transport and absorption of amino acids, and the dysfunction of these proteins can induce human diseases. Cationic amino acid transporters (CAT family, SLC7A1-4, and SLC7A14) are considered to be a group of transmembrane transporters, of which SLC7A1-3 are essential for arginine transport in mammals. Numerous studies have shown that CAT family-mediated arginine transport is involved in signal crosstalk between malignant tumor cells and immune cells, especially T cells. The modulation of extracellular arginine concentration has entered a number of clinical trials and achieved certain therapeutic effects. Here, we review the role of CAT family on tumor cells and immune infiltrating cells in malignant tumors and explore the therapeutic strategies to interfere with extracellular arginine concentration, to elaborate its application prospects. CAT family members may be used as biomarkers for certain cancer entities and might be included in new ideas for immunotherapy of malignant tumors.

Imaging Mass Spectrometry for the Classification of Melanoma Based on BRAF/NRAS Mutational Status

Mutations of the oncogenes v-raf murine sarcoma viral oncogene homolog B1 (BRAF) and neuroblastoma RAS viral oncogene homolog (NRAS) are the most frequent genetic alterations in melanoma and are mutually exclusive. BRAF V600 mutations are predictive for response to the two BRAF inhibitors vemurafenib and dabrafenib and the mitogen-activated protein kinase kinase (MEK) inhibitor trametinib. However, inter- and intra-tumoral heterogeneity and the development of acquired resistance to BRAF inhibitors have important clinical implications. Here, we investigated and compared the molecular profile of BRAF and NRAS mutated and wildtype melanoma patients' tissue samples using imaging mass spectrometry-based proteomic technology, to identify specific molecular signatures associated with the respective tumors. SCiLSLab and R-statistical software were used to classify peptide profiles using linear discriminant analysis and support vector machine models optimized with two internal cross-validation methods (leave-one-out, k-fold). Classification models showed molecular differences between BRAF and NRAS mutated melanoma, and identification of both was possible with an accuracy of 87-89% and 76-79%, depending on the respective classification method applied. In addition, differential expression of some predictive proteins, such as histones or glyceraldehyde-3-phosphate-dehydrogenase, correlated with BRAF or NRAS mutation status. Overall, these findings provide a new molecular method to classify melanoma patients carrying BRAF and NRAS mutations and help provide a broader view of the molecular characteristics of these patients that may help understand the signaling pathways and interactions involving the altered genes.

TREM2 as a Potential Immune-Related Biomarker of Prognosis in Patients with Skin Cutaneous Melanoma Microenvironment

Background

The skin cutaneous melanoma (SKCM) is a devastating form of skin cancer triggered by genetic and environmental factors, and the incidence of SKCM has rapidly increased in recent years. Immune infiltration of the tumor microenvironment is positively associated with overall survival in many tumors. Triggering receptor expressed on myeloid cells 2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although numerous evidences suggest a crucial role for TREM2 in tumorigenesis of some tumors, no systematic SKCM analysis of TREM2 is available. Mehods. The relationship between TREM2 expression and diagnostic and prognostic value of SKCM patients via using The Cancer Genome Atlas (TCGA) data. The expression level of TREM2 and clinical characteristic correlation in SKCM patients were assessed by the Wilcoxon rank sum test. The cox regression methods, Kaplan-Meier (KM), and log-rank test were used to assess the impact of TREM2 expression on the overall survival (OS). Furthermore, the Gene Set Enrichment Analysis (GSEA) and TIMER were performed to evaluate the enrichment pathways and potential functions and quantify the immune cell infiltration level for TREM2 expression.

Results

The TREM2 in SKCM sample expression levels was significantly higher than in normal tissues. Moreover, this expression level of TREM2 was also associated with the BMI of SKCM patients. KM overall survival analysis and OS curve displayed that a high-level TREM2 expression was significantly correlated with a better SKCM prognosis of patients as compared with a low level of TREM2 expression. The GSEA analysis also revealed that TREM2 was associated with immune functions, such as neutrophil activation.

Conclusion

TREM2 played a crucial role in SKCM, which might be a prognostic biomarker and correlated with immune infifiltrates in SKCM patients.

A novel prognostic model for prostate cancer based on androgen biosynthetic and catabolic pathways

Prostate cancer (PCa) is one of the most common malignancies in males globally, and its pathogenesis is significantly related to androgen. As one of the important treatments for prostate cancer, androgen deprivation therapy (ADT) inhibits tumor proliferation by controlling androgen levels, either surgically or pharmacologically. However, patients treated with ADT inevitably develop biochemical recurrence and advance to castration-resistant prostate cancer which has been reported to be associated with androgen biosynthetic and catabolic pathways. Thus, gene expression profiles and clinical information of PCa patients were collected from TCGA, MSKCC, and GEO databases for consensus clustering based on androgen biosynthetic and catabolic pathways. Subsequently, a novel prognostic model containing 13 genes (AFF3, B4GALNT4, CD38, CHRNA2, CST2, ADGRF5, KLK14, LRRC31, MT1F, MT1G, SFTPA2, SLC7A4, TDRD1) was constructed by univariate cox regression, lasso regression, and multivariate cox regression. Patients were divided into two groups based on their risk scores: high risk (HS) and low risk (LS), and survival analysis was used to determine the difference in biochemical recurrence-free time between the two. The results were validated on the MSKCC dataset and the GEO dataset. Functional enrichment analysis revealed some pivotal pathways that may have an impact on the prognosis of patients including the CDK-RB-E2F axis, G2M checkpoint, and KRAS signaling. In addition, somatic mutation, immune infiltration, and drug sensitivity analyses were performed to further explore the characteristics of HS and LS groups. Besides, two potential therapeutic targets, BIRC5 and RHOC, were identified by us in prostate cancer. These results indicate that the prognostic model may serve as a predictive tool to guide clinical treatment and provide new insight into the basic research in prostate cancer.

Identification of cell senescence molecular subtypes in prediction of the prognosis and immunotherapy of hepatitis B virus-related hepatocellular carcinoma

Hepatitis B virus (HBV)-infected hepatocellular carcinoma (HCC) has a high incidence and fatality rate worldwide, being among the most prevalent cancers. The growing body of data indicating cellular senescence (CS) to be a critical factor in hepatocarcinogenesis. The predictive value of CS in HBV-related HCC and its role in the immune microenvironment are unknown. To determine the cellular senescence profile of HBV-related HCC and its role in shaping the immune microenvironment, this study employed a rigorous evaluation of multiple datasets encompassing 793 HBV-related HCC samples. Two novel distinct CS subtypes were first identified by nonnegative matrix factorization, and we found that the senescence-activated subgroup had the worst prognosis and correlated with cancer progression. C1 and C2 were identified as the senescence-suppressed and senescence-activated subgroups. The immune microenvironment indicated that C2 exhibited a relatively low immune status, higher tumor purity, and lower immune scores and estimated scores, while the C1 subgroup possessed a better prognosis. The CS score signature based on five genes (CENPA, EZH2, G6PD, HDAC1, and PRPF19) was established using univariate Cox regression and the lasso method. ICGC-LIRI and GSE14520 cohorts were used to validate the reliability of the CS scoring system. In addition, we examined the association between the risk score and hallmark pathways through gene set variation analysis and gene set enrichment analysis. The results revealed a high CS score to be associated with the activation of cell senescence-related pathways. The CS score and other clinical features were combined to generate a CS dynamic nomogram with a better predictive capacity for OS at 1, 2, and 3 years than other clinical parameters. Our study demonstrated that cellular senescence patterns play a non-negligible role in shaping the characteristics of the immune microenvironment and profoundly affecting tumor prognosis. The results of this study will help predict patient prognosis more accurately and may assist in development of personalized immunotherapy for HBV-related HCC patients.

Integrated analysis reveals the pivotal interactions between immune cells in the melanoma tumor microenvironment

Melanoma is the most lethal type of skin cancer. Despite the breakthroughs in the clinical treatment of melanoma using tumor immunotherapy, many patients do not benefit from these immunotherapies because of multiple immunosuppressive mechanisms. Therefore, there is an urgent need to determine the mechanisms of tumor-immune system interactions and their molecular determinants to improve cancer immunotherapy. In this study, combined analysis of microarray data and single-cell RNA sequencing data revealed the key interactions between immune cells in the melanoma microenvironment. First, differentially expressed genes (DEGs) between normal and malignant tissues were obtained using GEO2R. The DEGs were then subjected to downstream analyses, including enrichment analysis and protein–protein interaction analysis, indicating that these genes were associated with the immune response of melanoma. Then, the GEPIA and TIMER databases were used to verify the differential expression and prognostic significance of hub genes, and the relationship between the hub genes and immune infiltration. In addition, we combined single cell analysis from GSE123139 to identify immune cell types, and validated the expression of the hub genes in these immune cells. Finally, cell-to-cell communication analysis of the proteins encoded by the hub genes and their interactions was performed using CellChat. We found that the CCL5-CCR1, SELPLG-SELL, CXCL10-CXCR3, and CXCL9-CXCR3 pathways might play important roles in the communication between the immune cells in tumor microenvironment. This discovery may reveal the communication basis of immune cells in the tumor microenvironment and provide a new idea for melanoma immunotherapy.

Identification and Comprehensive Analysis of FREM2 Mutation as a Potential Prognostic Biomarker in Colorectal Cancer

Gene mutations play an important role in tumor progression. This study aimed to identify genes that were mutated in colorectal cancer (CRC) and to explore their biological effects and prognostic value in CRC patients. We performed somatic mutation analysis using data sets from The Cancer Genome Atlas and International Cancer Genome Consortium, and identified that FREM2 had the highest mutation frequency in patients with colon adenocarcinoma (COAD). COAD patients were divided into FREM2-mutated type (n = 36) and FREM2-wild type (n = 278), and a Kaplan-Meier survival curve was generated to perform prognostic analysis. A FREM2-mutation prognosis model was constructed using random forest method, and the performance of the model was evaluated using receiver operating characteristic curve. Next, the random forest method and Cox regression analysis were used to construct a prognostic model based on the gene expression data of 36 FREM2-mutant COAD patients. The model showed a high prediction accuracy (83.9%), and 13 prognostic model characteristic genes related to overall survival were identified. Then, the results of tumor mutation burden (TMB) and microsatellite instability (MSI) analyses revealed significant differences in TMB and MSI among the risk scores of different prognostic models. Differentially expressed genes were identified and analyzed for functional enrichment and immune infiltration. Finally, 30 samples of CRC patients were collected for immunohistochemical staining to analyze the FREM2 expression levels, which showed that FREM2 was highly expressed in tumor tissues. In conclusion, CRC patients had a high level of FREM2 mutations associated with a worse prognosis, which indicated that FREM2 mutations may be potential prognostic markers in CRC.

Signal pathways of melanoma and targeted therapy

Melanoma is the most lethal skin cancer that originates from the malignant transformation of melanocytes. Although melanoma has long been regarded as a cancerous malignancy with few therapeutic options, increased biological understanding and unprecedented innovations in therapies targeting mutated driver genes and immune checkpoints have substantially improved the prognosis of patients. However, the low response rate and inevitable occurrence of resistance to currently available targeted therapies have posed the obstacle in the path of melanoma management to obtain further amelioration. Therefore, it is necessary to understand the mechanisms underlying melanoma pathogenesis more comprehensively, which might lead to more substantial progress in therapeutic approaches and expand clinical options for melanoma therapy. In this review, we firstly make a brief introduction to melanoma epidemiology, clinical subtypes, risk factors, and current therapies. Then, the signal pathways orchestrating melanoma pathogenesis, including genetic mutations, key transcriptional regulators, epigenetic dysregulations, metabolic reprogramming, crucial metastasis-related signals, tumor-promoting inflammatory pathways, and pro-angiogenic factors, have been systemically reviewed and discussed. Subsequently, we outline current progresses in therapies targeting mutated driver genes and immune checkpoints, as well as the mechanisms underlying the treatment resistance. Finally, the prospects and challenges in the development of melanoma therapy, especially immunotherapy and related ongoing clinical trials, are summarized and discussed.