Coexpressed Genes That Promote the Infiltration of M2 Macrophages in Melanoma Can Evaluate the Prognosis and Immunotherapy Outcome

Proteogenomic insights into the biology and treatment of pan-melanoma

Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.

NOTCH3 as a prognostic biomarker and its correlation with immune infiltration in gastrointestinal cancers

NOTCH receptor 3 (NOTCH3) is known to regulate the transcription of oncogenes or tumor suppressor genes, thereby playing a crucial role in tumor development, invasion, maintenance, and chemotherapy resistance. However, the specific mechanism of how NOTCH3 drives immune infiltration in gastrointestinal cancer remains uncertain. The expression of NOTCH3 was analyzed through Western blot, PCR, Oncomine database, and the Tumor Immune Estimation Resource (TIMER) site. Kaplan-Meier plotter, PrognoScan database, and gene expression profile interactive analysis (GEPIA) were used to assess the impact of NOTCH3 on clinical prognosis. The correlation between NOTCH3 expression and immune infiltration gene markers was investigated using TIMER and GEPIA. NOTCH3 was found to be commonly overexpressed in various types of gastrointestinal tumors and was significantly associated with poor prognosis. Furthermore, the expression level of NOTCH3 showed a significant correlation with the tumor purity of gastrointestinal tumors and the extent of immune infiltration by different immune cells. Our findings suggest that NOTCH3 may act as a crucial regulator of tumor immune cell infiltration and can serve as a valuable prognostic biomarker in gastrointestinal cancers.

TPR is a prognostic biomarker and potential therapeutic target associated with immune infiltration in hepatocellular carcinoma

Liver cancer is the fourth leading cause of cancer-related mortality worldwide and hepatocellular carcinoma (HCC) is the most common primary liver cancer. In the present study, it was demonstrated that translocated promoter region (TPR) was upregulated in tumor tissues and associated with prognosis and immune infiltration in HCC. The clinical outcome of patients with HCC with aberrant expression of TPR was examined using multiple databases, including Gene Expression Omnibus, The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression, Kaplan-Meier (KM) Plotter and Xiantao tool. The clinicopathologic characteristics of patients from TCGA database that were associated with overall survival were assessed using Cox regression and KM analysis. The potential hallmarks associated with TPR expression were further predicted by Metascape and Gene Set Enrichment Analysis, and the relationship between TPR and immune infiltration was explored using the Tumor-Immune System Interactions Database and the Tumor Immune Estimation Resource. The results demonstrated that TPR expression was higher in HCC and its overexpression was associated with a worse prognosis, alongside a correlation with several clinical features. Furthermore, cell differentiation, a prospective new hallmark of cancer, was differentially enriched in the high TPR expression phenotype pathway. Moreover, TPR may also modulate the tumor immune microenvironment as it was significantly associated with immunoregulators and chemokines, as well as different tumor infiltration immune cells. According to the in vitro experiments, TPR silencing inhibited the phosphorylation of AKT and the proliferation of HCC cells. In summary, TPR may be a new marker and target for HCC therapy.

Immune infiltration and clinical significance analyses of the cancer-associated fibroblast-related signature in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) is one of the most aggressive cancers with high mortality rates. Cancer-associated fibroblasts (CAFs) play essential roles in tumor growth, metastasis and the establishment of a pro-tumor microenvironment. This study aimed to establish a CAF-related signature for providing a new perspective for indicating prognosis and guiding therapeutic regimens of SKCM patients.

METHODS

In this study, the CAF-related genes were screened out based on melanoma-associated fibroblast markers identified from single-cell transcriptome analysis in the Gene Expression Omnibus (GEO) database and a CAF-related module identified from weighted gene co-expression analysis using The Cancer Genome Atlas (TCGA) dataset. We extracted these gene expression data of SKCM samples from TCGA and constructed a prognostic CAF-related signature. The prediction abilities of the signature for survival prognosis, tumor immune landscape and responses to chemo-/immunotherapies were evaluated in the TCGA-SKCM cohort.

RESULTS

We suggested that CAFs were significantly involved in the clinical outcomes of SKCM. A 10-gene CAF-related model was constructed, and the high-CAF risk group exhibited immunosuppressive features and worse prognosis. Patients with high CAF score were more likely to not respond to immune checkpoint inhibitors but were more sensitive to some chemotherapeutic agents, suggesting a potential approach of chemotherapy/anti-CAF combination treatment to improve the SKCM patient response rate of current immunotherapies.

CONCLUSIONS

The CAF-related risk score could serve as a robust prognostic indicator and personal assessment of this score could uncover the degree of immunosuppression and provide treatment strategies to improve outcomes in clinical decision-making in SKCM patients.

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.

Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

A CD8+ T cell-associated immune gene panel for prediction of the prognosis and immunotherapeutic effect of melanoma

Background

Skin cutaneous melanoma (SKCM) is the most frequently encountered tumor of the skin. Immunotherapy has opened a new horizon in melanoma treatment. We aimed to construct a CD8⁺ T cell-associated immune gene prognostic model (CDIGPM) for SKCM and unravel the immunologic features and the benefits of immunotherapy in CDIGPM-defined SKCM groups.

Method

Single-cell SKCM transcriptomes were utilized in conjunction with immune genes for the screening of CD8⁺ T cell-associated immune genes (CDIGs) for succeeding assessment. Thereafter, through protein-protein interaction (PPI) networks analysis, univariate COX analysis, and multivariate Cox analysis, six genes (MX1, RSAD2, IRF2, GBP2, IFITM1, and OAS2) were identified to construct a CDIGPM. We detected cell proliferation of SKCM cells transfected with IRF2 siRNA. Then, we analyzed the immunologic features and the benefits of immunotherapy in CDIGPM-defined groups.

Results

The overall survival (OS) was much better in low-CDIGPM group versus high CDIGPM group in TCGA dataset and GSE65904 dataset. On the whole, the results unfolded that a low CDIGPM showed relevance to immune response-correlated pathways, high expressions of CTLA4 and PD-L1, a high infiltration rate of CD8⁺ T cells, and more benefits from immunotherapy.

Conclusion

CDIGPM is an good model to predict the prognosis, the potential immune escape from immunotherapy for SKCM, and define immunologic and molecular features.

Exploration of immune response mechanisms in cadmium and copper co-exposed juvenile golden cuttlefish (Sepia esculenta) based on transcriptome profiling

Sepia esculenta is a popular economic cephalopod with high yield, delicious meat, and rich nutrition. With the rapid development of heavy industry and medical industry, a large amount of waste has been released into the ocean recklessly in recent years, inducing a significant increase in the content of heavy metals, especially cadmium (Cd) and copper (Cu), in the ocean. This phenomenon significantly affects the growth and development of S. esculenta, causing a serious blow to its artificial breeding. In this study, transcriptome analysis is used to initially explore immune response mechanisms of Cd and Cu co-exposed juvenile S. esculenta. The results show that 1,088 differentially expressed genes (DEGs) are identified. And DEGs functional enrichment analysis results suggests that co-exposure may promote inflammatory and innate immune responses in juvenile S. esculenta. Fifteen key genes that might regulate the immunity of S. esculenta are identified using protein-protein interaction (PPI) network and KEGG enrichment analyses, of which the three genes with the highest number of interactions or involve in more KEGG pathways are identified as hub genes that might significantly affect the immune response processes. Comprehensive analysis of PPI network and KEGG signaling pathway is used for the first time to explore co-exposed S. esculenta juvenile immune response processes. Our results preliminarily reveal immune response mechanisms of cephalopods exposed to heavy metals and provide a valuable resource for further understanding of mollusk immunity.

Apprising Diagnostic and Prognostic Biomarkers in Cutaneous Melanoma—Persistent Updating

The incidence of melanoma, a very aggressive skin cancer, has increased over the past few decades. Although there are well-established clinical, dermoscopic and histopathological criteria, the diagnosis is often performed late, which has important implications on the patient’s clinical outcome. Unfortunately, melanoma is one of the most challenging tumors to diagnose because it is a heterogeneous neoplasm at the clinical, histopathological, and molecular level. The use of reliable biomarkers for the diagnosis and monitoring of disease progression is becoming a standard of care in modern medicine. In this review, we discuss the latest studies, which highlight findings from the genomics, epitranscriptomics, proteomics and metabolomics areas, pointing out different genes, molecules and cells as potential diagnostic and prognostic biomarkers in cutaneous melanoma.

Pancancer analysis of a potential gene mutation model in the prediction of immunotherapy outcomes

Background: Immune checkpoint blockade (ICB) represents a promising treatment for cancer, but predictive biomarkers are needed. We aimed to develop a cost-effective signature to predict immunotherapy benefits across cancers.

Methods: We proposed a study framework to construct the signature. Specifically, we built a multivariate Cox proportional hazards regression model with LASSO using 80% of an ICB-treated cohort (n = 1661) from MSKCC. The desired signature named SIGP was the risk score of the model and was validated in the remaining 20% of patients and an external ICB-treated cohort (n = 249) from DFCI.

Results: SIGP was based on 18 candidate genes (NOTCH3, CREBBP, RNF43, PTPRD, FAM46C, SETD2, PTPRT, TERT, TET1, ROS1, NTRK3, PAK7, BRAF, LATS1, IL7R, VHL, TP53, and STK11), and we classified patients into SIGP high (SIGP-H), SIGP low (SIGP-L) and SIGP wild type (SIGP-WT) groups according to the SIGP score. A multicohort validation demonstrated that patients in SIGP-L had significantly longer overall survival (OS) in the context of ICB therapy than those in SIGP-WT and SIGP-H (44.00 months versus 13.00 months and 14.00 months, p < 0.001 in the test set). The survival of patients grouped by SIGP in non-ICB-treated cohorts was different, and SIGP-WT performed better than the other groups. In addition, SIGP-L + TMB-L (approximately 15% of patients) had similar survivals to TMB-H, and patients with both SIGP-L and TMB-H had better survival. Further analysis on tumor-infiltrating lymphocytes demonstrated that the SIGP-L group had significantly increased abundances of CD8+ T cells.

Conclusion: Our proposed model of the SIGP signature based on 18-gene mutations has good predictive value for the clinical benefit of ICB in pancancer patients. Additional patients without TMB-H were identified by SIGP as potential candidates for ICB, and the combination of both signatures showed better performance than the single signature.

TIMM13 as a prognostic biomarker and associated with immune infiltration in skin cutaneous melanoma (SKCM)

Objective

Providing protection against aggregation and guiding hydrophobic precursors through the mitochondria’s intermembrane space, this protein functions as a chaperone-like protein. SLC25A12 is imported by TIMM8 as a result of its interaction with TIMM13. In spite of this, it is still unknown how TIMM13 interacts with skin cutaneous melanoma (SKCM) and tumor-infiltrating lymphocytes (TILs).

Methods

Aberrant expression of TIMM13 in SKCM and its clinical outcome was evaluated with the help of multiple databases, including the Xiantao tool (https://www.xiantao.love/), HPA, and UALCAN. TISIDB and Tumor Immune Estimation Resources (TIMER) databases were applied to explore the association between TIMM13 and tumor infiltration immune cells. OS nomogram was constructed, and model performance was examined. Finally, TIMM13 protein expression was validated by immunohistochemistry (IHC).

Results

TIMM13 expression was higher in SKCM samples than in peritumor samples. TIMM13 was strongly associated with sample type, subgroup, cancer stage, lymph node stage, and worse survival. Further, upregulation of TIMM13 was significantly associated with immunoregulators, and chemokines, as well as T cells, B cells, monocytes, neutrophils, macrophages, and T-cell regulators. An analysis of bioinformatic data uncovered that TIMM13 expression was strongly associated with PD1 (T-cell exhaustion marker). The nomogram showed good predictive performance based on calibration plot. TIMM13 was highly expressed in melanoma tissue samples than in normal samples.

Conclusion

In brief, TIMM13 may be a prognostic biomarker for SKCM. It might modulate the tumor immune microenvironment and lead to a poorer prognosis. In addition, it is necessary to study the targeted therapy of TIMM13.

Identification, function, and biological relevance of POGLUT2 and POGLUT3

O-glycosylation of Epidermal Growth Factor-like (EGF) repeats plays crucial roles in protein folding, trafficking and function. The Notch extracellular domain has been used as a model to study these mechanisms due to its many O-glycosylated EGF repeats. Three enzymes were previously known to O-glycosylate Notch EGF repeats: Protein O-Glucosyltransferase 1 (POGLUT1), Protein O-Fucosyltransferase 1 (POFUT1), and EGF Domain Specific O-Linked N-Acetylglucosamine Transferase (EOGT). All of these modifications affect Notch activity. Recently, POGLUT2 and POGLUT3 were identified as two novel O-glucosyltransferases that modify a few Notch EGF repeats at sites distinct from those modified by POGLUT1. Comparison of these modification sites revealed a putative consensus sequence which predicted modification of many extracellular matrix proteins including fibrillins (FBNs) and Latent TGFβ-binding proteins (LTBPs). Glycoproteomic analysis revealed that approximately half of the 47 EGF repeats in FBN1 and FBN2, and half of the 18 EGF repeats in LTBP1, are modified by POGLUT2 and/or POGLUT3. Cellular assays showed that loss of modifications by POGLUT2 and/or POGLUT3 significantly reduces FBN1 secretion. There is precedent for EGF modifications to affect protein-protein interactions, as has been demonstrated by research of POGLUT1 and POFUT1 modifications on Notch. Here we discuss the identification and characterization of POGLUT2 and POGLUT3 and the ongoing research that continues to elucidate the biological significance of these novel enzymes.

Lung Adenocarcinoma Cells Promote Self-Migration and Self-Invasion by Activating Neutrophils to Upregulate Notch3 Expression of Cancer Cells

Background: Invasion and migration of cancer cells play a key role in lung cancer progression and metastasis. Tumor-associated neutrophils (TANs) are related to poor prognosis in many types of cancer. However, the role of TANs in lung cancer is controversial. In this study, we investigated the effect of TANs on the invasion and migration of lung adenocarcinoma.

Methods: Immunohistochemistry was performed to detect the density of infiltrating TANs and the expression of Notch3 in 100 lung adenocarcinoma tissues. Flow cytometry was used to observe the viability of neutrophils, which were isolated from healthy peripheral blood and then exposed to the supernatant of cultured lung adenocarcinoma cell lines. After treating with tumor-associated neutrophils culture supernatant, NeuCS (supernatant of cultured neutrophils), tumor cells culture supernatant, Medium (serum-free medium), respectively, the migration and invasion of the lung cancer cells before and after transfected by si-Notch3 were detected by transwell assay and wound healing assay. Kaplan-Meier plotter (http://kmplot.com/analysis/index.php?p) was used to analyze the prognostic role of the density of TANs on lung adenocarcinoma and TIMER ((http://cistrome.dfci.harvard.edu/TIMER/) was used to detect the expression of Notch3 on lung adenocarcinoma.

Results: The infiltration of TANs was observed in the parenchyma and stroma of the lung adenocarcinoma, the density of TANs was positively related to the TNM stage and negatively related to the differentiation and prognosis. Notch3 expression of cancer cells was negatively related to the tumor differentiation and prognosis. Compared to quiescent neutrophils, the viability of TCCS-activated neutrophils was enhanced. Both migration and invasion of A549 and PC9 cells were significantly promoted by TANs, while after knocking down Notch3, the migration and invasion of the cancer cells were not affected by TANs. Bioinformatics analysis showed that the density of TANs and the expression of Notch3 were related to the poor prognosis.

Conclusion: The results indicated that lung adenocarcinoma cells promote self-invasion and self-migration by activating neutrophils to upregulate the Notch3 expression of cancer cells. The density of infiltrating TANs may be a novel marker for the poor prognosis of lung adenocarcinoma. Targeting TANs might be a potential therapeutic strategy for lung cancer treatment.

The TRPA1 Channel Amplifies the Oxidative Stress Signal in Melanoma

Macrophages (MΦs) and reactive oxygen species (ROS) are implicated in carcinogenesis. The oxidative stress sensor, transient receptor potential ankyrin 1 (TRPA1), activated by ROS, appears to contribute to lung and breast cancer progression. Although TRPA1 expression has been reported in melanoma cell lines, and oxidative stress has been associated with melanocytic transformation, their role in melanoma remains poorly known. Here, we localized MΦs, the final end-product of oxidative stress, 4-hydroxynonenal (4-HNE), and TRPA1 in tissue samples of human common dermal melanocytic nevi, dysplastic nevi, and thin (pT1) and thick (pT4) cutaneous melanomas. The number (amount) of intratumoral and peritumoral M2 MΦs and 4-HNE staining progressively increased with tumor severity, while TRPA1 expression was similar in all samples. Hydrogen peroxide (H₂O₂) evoked a TRPA1-dependent calcium response in two distinct melanoma cell lines (SK-MEL-28 and WM266-4). Furthermore, H₂O₂ induced a TRPA1-dependent H₂O₂ release that was prevented by the TRPA1 antagonist, A967079, or Trpa1 gene silencing (siRNA). ROS release from infiltrating M2 MΦs may target TRPA1-expressing melanoma cells to amplify the oxidative stress signal that affects tumor cell survival and proliferation.

Development and Validation of a CD8+ T Cell Infiltration-Related Signature for Melanoma Patients

Aim

Immunotherapy shows efficacy in only a subset of melanoma patients. Here, we intended to construct a risk score model to predict melanoma patients’ sensitivity to immunotherapy.

Methods

Integration analyses were performed on melanoma patients from high-dimensional public datasets. The CD8+ T cell infiltration related genes (TIRGs) were selected via TIMER and CIBERSORT algorithm. LASSO Cox regression was performed to screen for the crucial TIRGs. Single sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithm were used to evaluate the immune activity. The prognostic value of the risk score was determined by univariate and multivariate Cox regression analysis.

Results

184 candidate TIRGs were identified in melanoma patients. Based on the candidate TIRGs, melanoma patients were classified into three clusters which were characterized by different immune activity. Six signature genes were further screened out of 184 TIRGs and a representative risk score for patient survival was constructed based on these six signature genes. The risk score served as an indicator for the level of CD8+ T cell infiltration and acted as an independent prognostic factor for the survival of melanoma patients. By using the risk score, we achieved a good predicting result for the response of cancer patients to immunotherapy. Moreover, pan-cancer analysis revealed the risk score could be used in a wide range of non-hematologic tumors.

Conclusions

Our results showed the potential of using signature gene-based risk score as an indicator to predict melanoma patients’ sensitivity to immunotherapy.