9-Gene Signature Correlated With CD8+ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma

A Pan-Cancer Comparative Analysis of The Cancer Genome Atlas Transcriptomic TIL-Immune Signatures

Efforts to understand the tumor microenvironment (TME) through basic science research and The Cancer Genome Atlas (TCGA) data analysis have led to the creation of unique immune transcriptomic signatures from tumor-infiltrating lymphocytes (TIL). However, no pan-cancer analysis has been conducted to compare the prognostic performance of these signatures using overall survival (OS) or progression-free interval (PFI) as endpoints. We compiled a library of 146 TIL-immune signatures and evaluated gene signature score correlation with OS and PFI for 9,961 available TCGA samples across 33 cancer types. Zhang CD8 TCS demonstrated higher accuracy in prognosticating both OS and PFI across the pan-cancer landscape, however, variability was seen across cancer types and germ cell origin. Cluster analysis compiled a group of six signatures (Oh.Cd8.MAIT, Grog.8KLRB1, Oh.TIL_CD4.GZMK, Grog.CD4.TCF7, Oh.CD8.RPL, Grog.CD4.RPL32) whose association with OS and PFI could potentially be conserved across multiple cancer types.

A myeloid IFN gamma response gene signature correlates with cancer prognosis

BACKGROUND

The IFN-γ cytokine plays a dual role in anti-tumor immunity, enhancing immune defense against cancer cells while promoting tumor survival and progression. Its influence on prognosis and therapeutic responses across cancer types remains unclear.

OBJECTIVE

This study aimed to perform a pan-cancer analysis of IFN-γ response genes to determine their prognostic significance and evaluate their impact on clinical outcomes and anti-PD1 immunotherapy responses.

METHODS

Using multiple datasets, 46 IFN-γ response genes were identified as prognostic for disease-specific survival, and their expression was used to construct the IFN-γ Response Gene Network Signature (IFGRNS) score. The prognostic and therapeutic relevance of the IFGRNS score was assessed across cancer types, considering tumor pathology, genomic alterations, tumor mutation burden, and microenvironment. Single-cell transcriptomic analysis identified cellular contributors, and a murine pancreatic cancer (PAN02) model was used to validate findings with anti-PD1 therapy.

RESULTS

The IFGRNS score emerged as a robust prognostic indicator of survival, with higher scores correlating with worse outcomes in most cancer types. The prognostic significance of the score was influenced by factors such as cancer type, tumor pathology, and the tumor microenvironment. Single-cell analysis revealed that myeloid cells, particularly the M2 macrophage subtype, demonstrated high levels of IFGRNS expression, which was associated with tumor progression. A negative correlation was observed between the IFGRNS score and outcomes to anti-PD1 immunotherapy in urologic cancers, where patients with higher scores showed worse prognosis and lower response rates to therapy. Experimental validation in the PAN02 murine model confirmed that anti-PD1 therapy significantly reduced tumor size and IFGRNS expression in M2 macrophages, supporting the clinical findings.

CONCLUSIONS

The IFGRNS score is a novel prognostic indicator for survival and therapeutic responses in cancer. These findings underline the complexity of IFN-γ signaling and suggest potential applications for the IFGRNS score in cancer diagnosis, prognosis, and immunotherapy. Novelty & impact statements: IFN-γ response genes play a significant role in tumour biology, yet comprehensive analysis across various cancers is limited. This study identifies a novel prognostic biomarker, the IFGRNS score, which is elevated in myeloid lineage cells and correlates with survival across multiple cancers. The IFGRNS score is also associated with tumour pathology, immune microenvironment, and immunotherapy response, highlighting its diagnostic and therapeutic potential in cancer management.

KEY POINTS

IFN-γ cytokine plays a dual role in cancer, aiding immune defense but also promoting tumor progression. A novel IFGRNS score, based on 46 IFN-γ response genes, was identified as a strong prognostic marker for survival across cancer types. Higher IFGRNS scores correlate with worse prognosis and reduced response to anti-PD1 immunotherapy, particularly in urologic cancers. M2 macrophages were identified as key contributors to high IFGRNS scores, associated with tumor progression. Findings were validated in a murine cancer model, highlighting the potential of the IFGRNS score for cancer prognosis and therapy guidance.

Dual role of interferon-gamma in the response of melanoma patients to immunotherapy with immune checkpoint inhibitors

Interferon-gamma (IFN-γ) is a cytokine produced mainly by immune cells and can affect cancer cells by modulating the activity of multiple signaling pathways, including the canonical Janus-activated kinase/signal transducer and activator of transcription (JAK/STAT) cascade. In melanoma, IFN-γ can exert both anticancer effects associated with cell-cycle arrest and cell death induction and protumorigenic activity related to immune evasion leading to melanoma progression. Notably, IFN-γ plays a crucial role in the response of melanoma patients to immunotherapy with immune checkpoint inhibitors (ICIs), which are currently used in the clinic. As these agents target programmed death-1 (PD-1) and its ligand (PD-L1), cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and lymphocyte-activation gene 3 (LAG-3), they are designed to restore the antimelanoma immune response. In this respect, IFN-γ produced by cells in the tumor microenvironment in response to ICIs has a beneficial influence on both immune and melanoma cells by increasing antigen presentation, recruiting additional T-cells to the tumor site, and inducing direct antiproliferative effects and apoptosis in melanoma cells. Therefore, IFN-γ itself and IFN-γ-related gene signatures during the response to ICIs can constitute biomarkers or predictors of the clinical outcome of melanoma patients treated with ICIs. However, owing to its multifaceted roles, IFN-γ can also contribute to developing mechanisms associated with the acquisition of resistance to ICIs. These mechanisms can be associated with either decreased IFN-γ levels in the tumor microenvironment or diminished responsiveness to IFN-γ due to changes in the melanoma phenotypes associated with affected activity of other signaling pathways or genetic alterations e.g., in JAK, which restricts the ability of melanoma cells to respond to IFN-γ. In this respect, the influence of IFN-γ on melanoma-specific regulators of the dynamic plasticity of the cell phenotype, including microphthalmia-associated transcription factor (MITF) and nerve growth factor receptor (NGFR)/CD271 can affect the clinical efficacy of ICIs. This review comprehensively discusses the role of IFN-γ in the response of melanoma patients to ICIs with respect to its positive influence and role in IFN-γ-related mechanisms of resistance to ICIs as well as the potential use of predictive markers on the basis of IFN-γ levels and signatures of IFN-γ-dependent genes.

DNA immunotherapy for recurrent respiratory papillomatosis (RRP): phase 1/2 study assessing efficacy, safety, and immunogenicity of INO-3107

Recurrent respiratory papillomatosis (RRP) is a chronic airway disease caused by Human Papillomavirus (HPV). INO-3107, DNA immunotherapy designed to elicit T-cells against HPV-6 and HPV-11, was evaluated in a 52-week Phase 1/2 study for efficacy, safety, and immunogenicity (NCT04398433). Thirty-two eligible adults with HPV-6 and/or HPV-11 RRP, requiring ≥2 surgical interventions in the year preceding dosing were enrolled between October 2020 and November 2021 and administered 4 INO-3107 doses by intramuscular injection followed by electroporation. The primary endpoint was safety and tolerability, as assessed by treatment-emergent adverse events (TEAEs). Secondary endpoints included surgical intervention frequency and change in RRP Severity Score (modified) post-INO-3107 and assessment of immune responses. 81% (26/32) of patients experienced surgery reduction following INO-3107 compared with the year prior to treatment. Blood assessments revealed HPV-6 and HPV-11 antigen-specific T-cell induction. RNA sequencing identified an inflammatory response in papillomas, inclusive of cytolytic CD8 + T-cell signatures. T-cell receptor sequencing revealed emergent T-cell clones in blood and confirmed trafficking to papillomas. Treatment-related adverse events (AEs) were reported in 13/32 (41%) patients, all low-grade. INO-3107 provides clinical benefit to HPV-6 and/or HPV-11-associated RRP adults and is well-tolerated. Importantly, treatment-induced peripheral T-cell responses traffic to airway tissue and are associated with clinical response.

Analysis of Variants Induced by Combined Ex Vivo Irradiation and In Vivo Tumorigenesis Suggests a Role for the ZNF831 p.R1393Q Variant in Cutaneous Melanoma Development

UVR is known to be the most important environmental carcinogen for cutaneous melanoma. Whereas genomic analyses of melanoma tumors implicate a high rate of UV damage, the experimental induction and recovery of bona fide UV-signature changes have not been directly observed. To replicate recurrent UV variants from The Cancer Genome Atlas_SKCM specimens, we UV irradiated cultured immortalized human melanocytes and subjected them to in vivo tumorigenesis assays. Exome sequencing of the xenografted tumors revealed an increase in UV-signature mutations within the tumors and identified 48 induced variants that overlap with The Cancer Genome Atlas skin cutaneous melanoma UV-hotspot mutations. A UV-induced mutation, ZNF831 p.R1393Q, was correlated with a decreased survival (hazard ratio = 5.44, 95% confidence interval = 1.92-15.47, P = .0015) and was preferentially observed in melanomas compared with that in all The Cancer Genome Atlas tumors (P = 4.42 × 10-7). In addition, ZNF831 mRNA expression loss was strongly associated with decreased patient survival (hazard ratio = 2.14, 95% confidence interval = 1.62-2.83, P = 7.91 × 10-8), although the transcripts may arise from multiple cell types, including T cells. In multiple melanoma lines, overexpression of wild-type ZNF831 reduced spheroid growth, heightened apoptosis, and increased cell motility, with the ZNF831 p.R1393Q variant partially or wholly abolishing these functional phenotypes. We thus experimentally recovered a "functional UV-hotspot mutation" in ZNF831 that is altered in human melanoma specimens.

Physiologically Achievable Concentration of 2-Deoxy-D-Glucose Stimulates IFN-γ Secretion in Activated T Cells In Vitro

2-deoxy-D-glucose (2DG) is a glycolysis and protein N-glycosylation inhibitor with promising anti-tumor and immunomodulatory effects. However, 2DG can also suppress T cell function, including IFN-γ secretion. Few human T cell studies have studied low-dose 2DG, which can increase IFN-γ in a Jurkat clone. We therefore investigated 2DG's effect on IFN-γ in activated human T cells from PBMCs, with 2DG treatment commenced either concurrently with activation or 48 h after activation. Concurrent 2DG treatment decreased IFN-γ secretion in a dose-dependent manner. However, 2DG treatment of pre-activated T cells had a hormetic effect on IFN-γ, with 0.15-0.6 mM 2DG (achievable in vivo) increasing and >2.4 mM 2DG reducing its secretion. In contrast, IL-2 levels declined monotonously with increasing 2DG concentration. Lower 2DG concentrations reduced PD-1 and increased CD69 expression regardless of treatment timing. The absence of increased T-bet or Eomes expression or IFNG transcription suggests another downstream mechanism. 2DG dose-dependently induced the unfolded protein response, suggesting a possible role in increased IFN-γ secretion, possibly by increasing the ER folding capacity for IFN-γ via increased chaperone expression. Overall, low-dose, short-term 2DG exposure could potentially improve the T cell anti-tumor response.

Immunotherapy in melanoma: advances, pitfalls, and future perspectives

Cutaneous melanoma is the deadliest and most aggressive form of skin cancer owing to its high capacity for metastasis. Over the past few decades, the management of this type of malignancy has undergone a significant revolution with the advent of both targeted therapies and immunotherapy, which have greatly improved patient quality of life and survival. Nevertheless, the response rates are still unsatisfactory for the presence of side effects and development of resistance mechanisms. In this context, tumor microenvironment has emerged as a factor affecting the responsiveness and efficacy of immunotherapy, and the study of its interplay with the immune system has offered new promising clinical strategies. This review provides a brief overview of the currently available immunotherapeutic strategies for melanoma treatment by analyzing both the positive aspects and those that require further improvement. Indeed, a better understanding of the mechanisms involved in the immune evasion of melanoma cells, with particular attention on the role of the tumor microenvironment, could provide the basis for improving current therapies and identifying new predictive biomarkers.

Extracellular vesicle-derived non-coding RNAs in remodeling melanoma

Melanoma is one of the most lethal cutaneous malignancies. Despite great advances in radiotherapy, chemotherapy, and immunotherapy, the survival rate and prognosis of patients with melanoma remain poor. The abundant and sophisticated reciprocal communication network between melanoma cells and non-tumor cells contributes to the high heterogeneity of the melanoma microenvironment and is intimately related to varying treatment responses and clinical courses. Extracellular vesicles (EVs) are membrane structures generated by nearly all cell types. EVs contain biologically active molecules, mainly comprising proteins, lipids, and RNAs, and undoubtedly play multifaceted roles in numerous diseases, represented by melanoma. Non-coding RNAs (ncRNAs) mainly encompass long non-coding RNAs, microRNAs, and circular RNAs and constitute the majority of the human transcriptome. Multiple ncRNAs encapsulated in EVs coordinate various pathophysiological processes in melanoma. This review summarizes the mechanisms by which EV-ncRNAs modulate biological behaviors and immunity, and their potential diagnostic and therapeutic applications in melanoma. Undoubtedly, further insight into EV-ncRNAs and their functions in melanoma will contribute to the clinical treatment of melanoma and the implementation of precision medicine.

The predictive efficacy of programmed cell death in immunotherapy of melanoma: A comprehensive analysis of gene expression data for programmed cell death biomarker and therapeutic target discovery

In this study, genes linked to prognosis in skin cutaneous melanoma (SKCM) involved in programmed cell death (PCD) were identified and confirmed and prognostic models based on these genes were constructed. Acquisition and analysis of clinical data and RNA sequencing information from The Cancer Genome Atlas-SKCM (TCGA-SKCM) and Sangerbox databases, gene expression data for 477 tumor samples and 2 normal samples were successfully gathered. The patients were separated into two clusters based on consensus clustering of PCD-related genes, with Cluster A having greater tumor purity, ESTIMATE score, immune score, and matrix score, and Cluster B having a significantly distinct pattern of immune cell infiltration. The use of gene set enrichment analysis and weighted correlation network analysis showed significant associations between certain genes and factors such as tumor mutation burden, age, stage, grade, and tumor subtype. Finally, based on the 12 genes selected by Least Absolute Shrinkage and Selection Operator regression analysis (STAT3, IRF2, SLC7A11, ZEB1, LIPT1, PML, GCH1, GYS1, ABCC1, XBP1, TFAP2C, NOX4), a prognostic model of PGD-related genes was constructed. The effectiveness of the model's prognostic value was confirmed through survival analysis, time-dependent receiver operating characteristic curve, single-factor Cox regression analysis, and nomogram. We also verified the relationship between the GCH1 and MKI67 expression by wet experiment. This model has high prediction accuracy in SKCM patients and can provide a reference for clinical treatment.

The role of PKP1 in tumor progression in melanoma: Analysis of a cell adhesion-related model

The incidence rate of melanoma varies across regions, with Europe, the United States, and Australia having 10-25, 20-30, and 50-60 cases per 1 00 000 people. In China, patients with melanoma exhibit different clinical manifestations, pathogenesis, and outcomes. Current treatments include surgery, adjuvant therapy, and immune checkpoint inhibitors. Nonetheless, complications may arise during treatment. Melanoma development is heavily reliant on cell adhesion molecules (CAMs), and studying these molecules could provide new research directions for metastasis and progression. CAMs include the integrin, immunoglobulin, selectin, and cadherin families, and they affect multiple processes, such as maintenance, morphogenesis, and migration of adherens junction. In this study, a cell adhesion-related risk prognostic signature was constructed using bioinformatics methods, and survival analysis was performed. Plakophilin 1 (PKP1) was observed to be crucial to the immune microenvironment and has significant effects on melanoma cell proliferation, migration, invasion, and the cell cycle. This signature demonstrates high reliability and has potential for clinical applications.

The inflammatory response-related robust machine learning signature in endometrial cancer: Based on multi-cohort studies

Uterine corpus endometrial carcinoma (UCEC) is a prevalent form of cancer in women, affecting the inner lining of the uterus. Inflammation plays a crucial role in the progression and prognosis of cancer, making it important to identify inflammatory response-related subtypes in UCEC for targeted therapy and personalized medicine. This study discovered significant variation in immune response within UCEC tumors based on molecular subtypes of inflammatory response-related genes. Subtype A showed a more favorable prognosis and better response to immunotherapies like anti-CTLA4 and anti-PDCD1 therapy. Functional analysis revealed subtype-specific differences in immune response, with subtype A exhibiting higher expression of genes related to cytokine signaling pathways, NK cell-mediated cytotoxicity pathways and inflammatory processes. Subtype A also showed increased sensitivity to three chemotherapeutic agents. A 12-gene inflammatory response-related signature was found to have prognostic value for 1, 2 and 3 year survival in UCEC patients. Additionally, a validated machine learning-based signature demonstrated significant differences in clinical traits between low-risk and high-risk cohorts. Elevated risk scores were associated with higher pathological grading, older age, advanced stage and immune subtype C2. Low-risk groups had higher infiltration of immune cell types such as CD8 + T cells and activated CD4 + cells. However, the abundance of cytotoxic immune cells decreased with increasing risk scores. Finally, PCR was applied to test the different expression in P2PX4. P2RX4 knockdown inhibited the proliferation and proliferation of the endometrial carcinoma Ishikawa cell line. In conclusion, this developed signature can serve as a clinical prediction index and reveal distinct immune expression patterns. Ultimately, this study has the potential to enhance targeted therapy and personalized medicine for UCEC patients.

Peroxisome proliferator-activated receptors signature reveal the head and neck squamous cell carcinoma energy metabolism phenotype and clinical outcome

BACKGROUND

Peroxisome proliferator activating receptors (PPARs) are important regulators of nuclear hormone receptor function, and they play a key role in biological processes such as lipid metabolism, inflammation and cell proliferation. However, their role in head and neck squamous cell carcinoma (HNSC) is unclear.

METHODS

We used multiple datasets, including TCGA-HNSC, GSE41613, GSE139324, PRJEB23709 and IMVigor, to perform a comprehensive analysis of PPAR-related genes in HNSC. Single-cell sequencing data were preprocessed using Seurat packets, and intercellular communication was analyzed using CellChat packets. Functional enrichment analysis of PPAR-related genes was performed using ClusterProfile and GSEA. Prognostic models were constructed using LASSO and Cox regression models, and immunohistochemical analyses were performed using human protein mapping (The Human Protein Atlas).

RESULTS

Our single-cell RNA sequencing analysis revealed distinct cell populations in HNSC, with T cells having the most significant transcriptome differences between tumors and normal tissues. The PPAR features were higher in most cell types in tumor tissues compared with normal tissues. We identified 17 PPAR-associated differentially expressed genes between tumors and normal tissues. A prognostic model based on seven PPAR-associated genes was constructed with high accuracy in predicting 1, 2 and 3 year survival in patients with HNSC. In addition, patients with a low risk score had a higher immune score and a higher proportion of T cells, CD8+ T cells and cytotoxic lymphocytes. They also showed higher immune checkpoint gene expression, suggesting that they might benefit from immunotherapy. PPAR-related genes were found to be closely related to energy metabolism.

CONCLUSIONS

Our study provides a comprehensive understanding of the role of PPAR related genes in HNSC. The identified PPAR features and constructed prognostic models may serve as potential biomarkers for HNSC prognosis and treatment response. In addition, our study found that PPAR-related genes can differentiate energy metabolism and distinguish energy metabolic heterogeneity in HNSC, providing new insights into the molecular mechanisms of HNSC progression and therapeutic response.

Exploration of the prognostic effect of costimulatory genes in bladder cancer

BACKGROUND

A prognostic model of bladder cancer was constructed based on costimulatory molecules, and its stability and accuracy were verified in different datasets.

METHOD

The expression profile of bladder cancer RNA and the corresponding clinical data in The Cancer Genome Atlas (TCGA) database were analyzed employing computational biology, and a prognostic model was constructed for costimulating molecule-related genes. The model was applied in GSE160693, GSE176307, Xiangya_Cohort, GSE13507, GSE19423, GSE31684, GSE32894, GSE48075, GSE69795 and GSE70691 in TCGA dataset and Gene Expression Omnibus database. The role of costimulating molecules in bladder cancer tumor subtypes was also explored. By consistent cluster analysis, bladder cancer in the TCGA dataset was categorized into two subtypes: C1 and C2. The C1 subtype exhibited a poor prognosis, high levels of immune cell infiltration and significant enrichment of natural killer cells, T cells and dendritic cells in the C1 subtype. In addition, the ImmuneScore calculated by the ESTIMATE algorithm differed greatly between the two subtypes, and the ImmuneScore of the C1 subtype was greater than the C2 subtype in a significant manner.

RESULTS

This study also assessed the relationship between costimulating molecules and immunotherapy response. The high-risk group responded poorly to immunotherapy, with significant differences in the amount of most immune cells between the two groups. Further, three indices of the ESTIMATE algorithm and 22 immune cells of the CIBERSORT algorithm were significantly correlated with risk values. These findings suggest the potential value of costimulating molecules in predicting immunotherapy response.

CONCLUSION

A costimulatory molecule-based prognostic model for bladder cancer was established and validated across multiple datasets. This model introduces a novel mode for tailoring treatments to each individual with bladder cancer, and offers valuable insights for informed clinical choices. Simultaneously, this research also delved into the significance of costimulating molecules within distinct bladder cancer subtypes, shedding novel insights into improving immunotherapy strategies for the treatment of bladder cancer.

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Fatty Acid Metabolism-Related lncRNAs are Potential Biomarkers for Predicting Prognoses and Immune Responses in Patients with Skin Cutaneous Melanoma

Introduction

Skin cutaneous melanoma is becoming more dangerous since it has a poor prognosis and is resistant to treatment. Previous research has shown that lncRNAs and fatty acid metabolism are essential for numerous biological activities. There are no studies on the relationship between fatty acid metabolism-Related lncRNAs and skin cutaneous melanoma.

Methods and Results

In order to better understand the prognosis and survival of SKCM patients, we investigated the significance of lncRNAs related to fatty acid metabolism. In this work, we looked at the fatty acid metabolism genes and lncRNAs expression patterns. On the basis of lncRNAs associated with fatty acid metabolism, a nomogram and a prognosis prediction model were created. Based on the profile of lncRNAs associated with fatty acid metabolism, functional and pharmacological sensitivity investigations were also carried out. We also looked at the connection between immunotherapy and the immune response. The findings demonstrated that a risk score model based on 11 essential lncRNAs for fatty acid metabolism may discriminate between the clinical condition of SKCM and more accurately predict prognosis and survival. We conducted quantitative reverse transcription polymerase-chain reaction (RT-PCR) to verify the model.

Conclusion

These important lncRNAs further showed a strong association with the tumor immune system, and these important lncRNAs also showed a connection between SKCM and chemotherapeutic treatment sensitivity. Our research strives to provide fresh viewpoints and innovative approaches to the treatment and administration of SKCM.

LY6/PLAUR domain containing 3 (LYPD3) maintains melanoma cell stemness and mediates an immunosuppressive microenvironment

BACKGROUND

Malignant melanoma is a highly heterogeneous skin cancer with the highest mortality rate among dermatological cancers. Catenins form functional networks in the nucleus to regulate gene expression and determine cell fate. Dysregulation of catenin expression correlates with the malignant characteristics of the tumor. We aimed to investigate the regulatory mechanisms of catenins in melanoma and to further define the function of catenin-related molecular signaling in the tumor microenvironment.

METHODS

In this study, a bioinformatics approach combined with experimental validation was used to explore the potential tumor biology mechanisms of catenin-related signaling.

RESULTS

Melanoma patients can be divided into two catenin clusters. Patients defined by high Junction Plakoglobin (JUP), Plakophilin 1 (PKP1), Plakophilin 3 (PKP3) levels (C2) had shorter survival time than other patients (C1). We demonstrated that JUP regulates Anterior Gradient 2 (AGR2)/LY6/PLAUR Domain Containing 3 (LYPD3) to maintain melanoma stemness and promotes glycolysis. We also found that LYPD3 was co-expressed with S100A9 and associated with immunosuppressive tumor microenvironment (TME).

CONCLUSION

The JUP/AGR2/LYPD3 signaling axis plays an important role in the malignant features of melanoma. Targeting the JUP/AGR2/LYPD3 signaling axis can help develop promising drugs.

Immune gene signatures as prognostic criteria for cancer patients

Recently, the possibility of using immune gene signatures (IGSs) has been considered as a novel prognostic tool for numerous cancer types. State-of-the-art methods of genomic, transcriptomic, and protein analysis have allowed the identification of a number of immune signatures correlated to disease outcome. The major adaptive and innate immune components are the T lymphocytes and macrophages, respectively. Herein, we collected essential data on IGSs consisting of subsets of T cells and tumor-associated macrophages and indicating cancer patient outcomes. We discuss factors that can introduce errors in the recognition of immune cell types and explain why the significance of immune signatures can be interpreted with uncertainty. The unidirectional functions of cell types should be entirely addressed in the signatures constructed by the combination of innate and adaptive immune cells. The state of the antitumor immune response is the key basis for IGSs and should be considered in gene signature construction. We also analyzed immune signatures for the prediction of immunotherapy response. Finally, we attempted to explain the present-day limitations in the use of immune signatures as robust criteria for prognosis.

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas

Background

Recent studies have suggested that long non-coding RNAs (lncRNAs) may play crucial role in low-grade glioma; however, the underlying mechanisms linking them to epigenetic methylation remain unclear.

Methods

We downloaded expression level data for regulators associated with N1 methyladenosine (m1A), 5-methyladenine (m5C), and N6 methyladenosine (m6A) (M1A/M5C/M6A) methylation from the Cancer Genome Atlas-low-grade glioma (TCGA-LGG) database. We identified the expression patterns of lncRNAs, and selected methylation-related lncRNAs using Pearson correlation coefficient>0.4. Non-negative matrix dimensionality reduction was then used to determine the expression patterns of the methylation-associated lncRNAs. We constructed a weighted gene co-expression network analysis (WGCNA) network to explore the co-expression networks between the two expression patterns. Functional enrichment of the co-expression network was performed to identify biological differences between the expression patterns of different lncRNAs. We also constructed prognostic networks based on the methylation presence in lncRNAs in low-grade gliomas.

Results

We identified 44 regulators by literature review. Using a correlation coefficient greater than 0.4, we identified 2330 lncRNAs, among which 108 lncRNAs with independent prognostic values were further screened using univariate Cox regression at P< 0.05. Functional enrichment of the co-expression networks revealed that regulation of trans-synaptic signaling, modulation of chemical synaptic transmission, calmodulin binding, and SNARE binding were mostly enriched in the blue module. The calcium and CA2 signaling pathways were associated with different methylation-related long non-coding chains. Using the Least Absolute Shrinkage Selector Operator (LASSO) regression analysis, we analyzed a prognostic model containing four lncRNAs. The model's risk score was 1.12 *AC012063 + 0.74 * AC022382 + 0.32 * AL049712 + 0.16 * GSEC. Gene set variation analysis (GSVA) revealed significant differences in mismatch repair, cell cycle, WNT signaling pathway, NOTCH signaling pathway, Complement and Cascades, and cancer pathways at different GSEC expression levels. Thus, these results suggest that GSEC may be involved in the proliferation and invasion of low-grade glioma, making it a prognostic risk factor for low-grade glioma.

Conclusion

Our analysis identified methylation-related lncRNAs in low-grade gliomas, providing a foundation for further research on lncRNA methylation. We found that GSEC could serve as a candidate methylation marker and a prognostic risk factor for overall survival in low-grade glioma patients. These findings shed light on the underlying mechanisms of low-grade glioma development and may facilitate the development of new treatment strategies.

Tumor-targeted superantigens produce curative tumor immunity with induction of memory and demonstrated antigen spreading

BACKGROUND

Despite remarkable progress, the immunotherapies currently used in the clinic, such as immune checkpoint blockade (ICB) therapy, still have limited efficacy against many types of solid tumors. One major barrier to effective treatment is the lack of a durable long-term response. Tumor-targeted superantigen (TTS) therapy may overcome this barrier to enhance therapeutic efficacy. TTS proteins, such as the clinical-stage molecule naptumomab estafenatox (NAP), increase tumor recognition and killing by both coating tumor cells with bacterial-derived superantigens (SAgs) and selectively expanding T-cell lineages that can recognize them. The present study investigated the efficacy and mechanism of action of repeated TTS (C215Fab-SEA) treatments leading to a long-term antitumor immune response as monotherapy or in combination with PD-1/PD-L1 inhibitors in murine tumor models.

METHODS

We used syngeneic murine tumor models expressing the human EpCAM target (C215 antigen) to assess the efficacy and mechanism of action of repeated treatment with TTS C215Fab-SEA alone or with anti-PD-1/PD-L1 monoclonal antibodies. Tumor draining lymph nodes (TDLNs) and tumor tissues were processed and analyzed by immunophenotyping and immunohistochemistry. Isolated RNA from tumors was used to analyze gene expression and the TCR repertoire. Tumor rechallenge and T-cell transfer studies were conducted to test the long-term antitumor memory response.

RESULTS

TTS therapy inhibited tumor growth and achieved complete tumor rejection, leading to a T-cell-dependent long-term memory response against the tumor. The antitumor effect was derived from inflammatory responses converting the immunosuppressive TME into a proinflammatory state with an increase in T-cell infiltration, activation and high T-cell diversity. The combination of TTS with ICB therapy was significantly more effective than the monotherapies and resulted in higher tumor-free rates.

CONCLUSIONS

These new results indicate that TTSs not only can turn a "cold" tumor into a "hot" tumor but also can enable epitope spreading and memory response, which makes TTSs ideal candidates for combination with ICB agents and other anticancer agents.

Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma

Background

The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition.

Methods

We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2).

Results

Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells.

Conclusion

We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.

Cell signaling activation and extracellular matrix remodeling underpin glioma tumor microenvironment heterogeneity and organization

PURPOSE

Tumor cells thrive by adapting to the signals in their microenvironment. To adapt, cancer cells activate signaling and transcriptional programs and migrate to establish micro-niches, in response to signals from neighboring cells and non-cellular stromal factors. Understanding how the tumor microenvironment evolves during disease progression is crucial to deciphering the mechanisms underlying the functional behavior of cancer cells.

METHODS

Multiplex immunohistochemistry, spatial analysis and histological dyes were used to identify and measure immune cell infiltration, cell signal activation and extracellular matrix deposition in low-grade, high-grade astrocytoma and glioblastoma.

RESULTS

We show that lower grade astrocytoma tissue is largely devoid of infiltrating immune cells and extracellular matrix proteins, while high-grade astrocytoma exhibits abundant immune cell infiltration, activation, and extensive tissue remodeling. Spatial analysis shows that most T-cells are restricted to perivascular regions, but bone marrow-derived macrophages penetrate deep into neoplastic cell-rich regions. The tumor microenvironment is characterized by heterogeneous PI3K, MAPK and CREB signaling, with specific signaling profiles correlating with distinct pathological hallmarks, including angiogenesis, tumor cell density and regions where neoplastic cells border the extracellular matrix. Our results also show that tissue remodeling is important in regulating the architecture of the tumor microenvironment during tumor progression.

CONCLUSION

The tumor microenvironment in malignant astrocytoma, exhibits changes in cell composition, cell signaling activation and extracellular matrix deposition during disease development and that targeting the extracellular matrix, as well as cell signaling activation will be critical to designing personalized therapy.

Integrated analysis from multi-center studies identities m7G-derived modification pattern and risk stratification system in skin cutaneous melanoma

The m7G modification has been proven to play an important role in RNA post-transcriptional modification and protein translation. However, the potential role of m7G modification patterns in assessing the prognosis of Skin cutaneous melanoma (SKCM) and tumor microenvironment (TME) has not been well studied. In this study, we investigated and finally identified 21 available m7G-related genes. We used hierarchical clustering (K-means) to classify 743 SKCM patients into three m7G-modified subtypes named m7G/gene cluster-A, B, C. We found that both m7G cluster B and gene cluster B exhibited higher prognosis and higher immune cell infiltration in TME compared to other subtypes. EIF4E3 and IFIT5, two m7G related genes, were both markedly elevated in Cluster B. Then, we constructed an m7G score system utilizing principal component analysis (PCA) in order to evaluate the patients' prognosis. High m7G score subtype was associated with better survival prognosis and active immune response. Overall, this article revealed that m7G modification patterns were involved in the development of the tumor microenvironment. Evaluating patients' m7G modification patterns will enhance our understanding of TME characteristics and help to guide personal treatment in clinics in the future.

Multi-omic Characterization of Pancreatic Ductal Adenocarcinoma Relates CXCR4 mRNA Expression Levels to Potential Clinical Targets

PURPOSE

Chemokines are essential for immune cell trafficking and are considered to have a major impact on the composition of the tumor microenvironment. CX-chemokine receptor 4 (CXCR4) is associated with poor differentiation, metastasis, and prognosis in pancreatic ductal adenocarcinoma (PDAC). This study provides a comprehensive molecular portrait of PDAC according to CXCR4 mRNA expression levels.

EXPERIMENTAL DESIGN

The Cancer Genome Atlas database was used to explore molecular and immunologic features associated with CXCR4 mRNA expression in PDAC. A large real-word dataset (n = 3,647) served for validation and further exploratory analyses. Single-cell RNA analyses on a publicly available dataset and in-house multiplex immunofluorescence (mIF) experiments were performed to elaborate cellular localization of CXCR4.

RESULTS

High CXCR4 mRNA expression (CXCR4high) was associated with increased infiltration of regulatory T cells, CD8+ T cells, and macrophages, and upregulation of several immune-related genes, including immune checkpoint transcripts (e.g., TIGIT, CD274, PDCD1). Analysis of the validation cohort confirmed the CXCR4-dependent immunologic TME composition in PDAC irrespective of microsatellite instability-high/mismatch repair-deficient or tumor mutational burden. Single-cell RNA analysis and mIF revealed that CXCR4 was mainly expressed by macrophages and T-cell subsets. Clinical relevance of our finding is supported by an improved survival of CXCR4high PDAC.

CONCLUSIONS

High intratumoral CXCR4 mRNA expression is linked to a T cell- and macrophage-rich PDAC phenotype with high expression of inhibitory immune checkpoints. Thus, our findings might serve as a rationale to investigate CXCR4 as a predictive biomarker in patients with PDAC undergoing immune checkpoint inhibition.

speedingCARs: accelerating the engineering of CAR T cells by signaling domain shuffling and single-cell sequencing

Chimeric antigen receptors (CARs) consist of an antigen-binding region fused to intracellular signaling domains, enabling customized T cell responses against targets. Despite their major role in T cell activation, effector function and persistence, only a small set of immune signaling domains have been explored. Here we present speedingCARs, an integrated method for engineering CAR T cells via signaling domain shuffling and pooled functional screening. Leveraging the inherent modularity of natural signaling domains, we generate a library of 180 unique CAR variants genomically integrated into primary human T cells by CRISPR-Cas9. In vitro tumor cell co-culture, followed by single-cell RNA sequencing (scRNA-seq) and single-cell CAR sequencing (scCAR-seq), enables high-throughput screening for identifying several variants with tumor killing properties and T cell phenotypes markedly different from standard CARs. Mapping of the CAR scRNA-seq data onto that of tumor infiltrating lymphocytes further helps guide the selection of variants. These results thus help expand the CAR signaling domain combination space, and supports speedingCARs as a tool for the engineering of CARs for potential therapeutic development.

The lncRNA-miRNA-integrin alpha V ceRNA network can affect the occurrence and prognosis of gastric cancer

OBJECTIVES

The aim of this study was to explore the role of integrin alpha V (ITGAV) and the related long noncoding RNA-microRNA-messenger RNA competing endogenous RNA (lncRNA-miRNA-mRNA ceRNA) network in the development and prognosis of cancers, especially gastric cancer (GC), through bioinformatic analysis.

METHODS

Pan-cancer and GC data were collected from the UCSC Xena website, and validation datasets were obtained from the Gene Expression Omnibus (GEO). R (version 3.6.3), GraphPad Prism 8, and SPSS 23.0 software were used to analyze data and prepare figures.

RESULTS

The expression of ITGAV in tumor tissues was higher than that of normal tissues in ten cancer types. A lower expression of ITGAV in five tumors (CESC, LGG, LIHC, MESO, and STAD) predicted better patient prognosis. In GC, the mRNA and protein expression of ITGAV in tumor tissues was higher than that of normal tissues. Patients with high ITGAV expression had poor prognosis and clinical characteristics, including worse grades and more advanced stages. Patients with higher ITGAV expression had higher immune and stromal scores and lower purity (P<0.05). In addition, seven miRNAs were found that were negatively correlated with ITGAV expression through the website; high expression of these miRNAs indicated a better prognosis. Using this correlation, the authors built the lncRNA-miRNA-ITGAV ceRNA network, to predict the prognosis of GC.

CONCLUSIONS

This study showed that ITGAV could be considered a prognostic factor for GC, and an lncRNA-miRNA-ITGAV ceRNA network was built to promote the exploration of the mechanism and prognosis of GC.

Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma

Yutao Wang, China Medical University, ChinaThe tumor microenvironment (TME) has been shown to impact the prognosis of tumors in patients including cutaneous melanoma (CM); however, not all components of TME are important. Given the aforementioned situation, the functional immune cell contents correlated with CM patient prognosis are needed to optimize present predictive models and reflect the overall situation of TME. We developed a novel risk score named core tumor-infiltrating immune cell score (cTICscore), which showed certain advantages over existing biomarkers or TME-related signatures in predicting the prognosis of CM patients. Furthermore, we explored a new gene signature named cTILscore−related module gene score (cTMGs), based on four identified TME-associated genes (GCH1, GZMA, PSMB8, and PLAAT4) showing a close correlation with the cTICscore, which was generated by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis to facilitate clinical application. Patients with low cTMGs had significantly better overall survival (OS, P = 0.002,< 0.001, = 0.002, and = 0.03, respectively) in the training and validating CM datasets. In addition, the area under the curve values used to predict the immune response in four CM cohorts were 0.723, 0.723, 0.754, and 0.792, respectively, and that in one gastric cohort was 0.764. Therefore, the four-gene signature, based on cTICscore, might improve prognostic information, serving as a predictive tool for CM patients receiving immunotherapy.cutaneous melanoma, tumor microenvironment, prognosis, immunotherapy, cTICscore

A combined aging and immune prognostic signature predict prognosis and responsiveness to immunotherapy in melanoma

Background: Melanoma is the most lethal, and one of the most aggressive forms of cutaneous malignancies, which poor response to treatment has always puzzled clinicians. As is known to all, aging and immune microenvironment are two crucial factors impacting melanoma biological progress through the tumor microenvironment (TME). However, reliable biomarkers for predicting melanoma prognosis based on aging and immune microenvironment and therapeutic efficacy of immune checkpoints remain to be determined.

Methods: The aging-related genes (ARGs) were obtained from the Human Ageing Genomic Resources and immune-related genes (IRGs) were downloaded from the Immunology database as well as Analysis Portal (ImmPort) database. Next, we initially performed LASSO regression and multivariate Cox regression to identify prognostic ARGs and IRGs in the TCGA and GSE65904 datasets, and firstly constructed a novel comprehensive index of aging and immune (CIAI) signature. Finally, in vitro molecular biology experiments were performed to assess the regulatory role of CNTFR in melanoma cell lines proliferation and migration, macrophage recruitment, and M2 polarization.

Results: This novel CIAI signature consisted of 7 genes, including FOXM1, TP63, ARNTL, KIR2DL4, CCL8, SEMA6A, and CNTFR, in which melanoma patients in the high-CIAI group had shorter OS, DSS, and PFI, indicating CIAI model served as an independent prognostic index. Moreover, we found the CIAI score was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Finally, CNTFR might function as oncogenes in melanoma cell lines and the silencing of CNTFR reduced macrophage recruitment and M2 polarization.

Conclusion: In this study, we have first presented a novel prognostic CIAI model applied to assess immune checkpoint therapy and the efficacy of conventional chemotherapy agents in melanoma patients. Thus providing a new insight for combating melanoma.

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

Background

One of the most common diseases that have a negative impact on women’s health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-γ is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-γ-related genes and long non-coding RNAs in endometrial cancer, however, is unknown.

Methods

The Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-γ were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-γ gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1).

Results

Based on the transcript expression of IFN-γ-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-γ-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories.

Conclusion

Our findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.

Identification of Crucial Gene Modules Related to the Efficiency of Anti-PD-1/PD-L1 Therapy and Comprehensive Analyses of a Novel Signature Based on These Modules

Biomarker development for clinical checkpoint inhibition is still in its early stages. It is critical to determine the cause of the lack of a long-term response in patients after immune checkpoint blockade (ICB) treatment and to develop composite biomarkers or signatures to improve personalized approaches. Three modules that were significantly correlated with the immunotherapeutic response were identified. Stimulatory pathways of cellular immunity, extracellular matrix formation-related pathways, and ATP metabolism-related pathways were enriched. Two distinct transcriptional subtypes were determined. Tumor microenvironment (TME) characteristics were highly correlated with “hot” and “cold” tumors. The ICB score was significantly correlated with clinical characteristics including age, Breslow depth, Clerk level, AJCC stage, and T stage. Meanwhile, a low ICB score is characterized by increased activation of immunity, a higher level of immune infiltration, and immune molecule expression. The ICB score showed a robust ability to predict melanoma prognosis in the discovery, internal validation, and external validation cohorts. In addition, a low ICB score was linked to a higher CR/PR rate in the immunotherapeutic cohort. The ICB score could reflect the pre-existing immune features and the expression pattern of “Cold” versus “Hot” tumors in melanoma patients. Thus, it has the potential to serve as a reliable predictor of melanoma prognosis and response to ICB therapy.

Retinoic Acid Induces an IFN-Driven Inflammatory Tumour Microenvironment, Sensitizing to Immune Checkpoint Therapy

With immune checkpoint therapy (ICT) having reshaped the treatment of many cancers, the next frontier is to identify and develop novel combination therapies to improve efficacy. Previously, we and others identified beneficial immunological effects of the vitamin A derivative tretinoin on anti-tumour immunity. Although it is known that tretinoin preferentially depletes myeloid derived suppressor cells in blood, little is known about the effects of tretinoin on the tumour microenvironment, hampering the rational design of clinical trials using tretinoin in combination with ICT. Here, we aimed to identify how tretinoin changed the tumour microenvironment in mouse tumour models, using flow cytometry and RNAseq, and we sought to use that information to establish optimal dosing and scheduling of tretinoin in combination with several ICT antibodies in multiple cancer models. We found that tretinoin rapidly induced an interferon dominated inflammatory tumour microenvironment, characterised by increased CD8+ T cell infiltration. This phenotype completely overlapped with the phenotype that was induced by ICT itself, and we confirmed that the combination further amplified this inflammatory milieu. The addition of tretinoin significantly improved the efficacy of anti-CTLA4/anti-PD-L1 combination therapy, and staggered scheduling was more efficacious than concomitant scheduling, in a dose-dependent manner. The positive effects of tretinoin could be extended to ICT antibodies targeting OX40, GITR and CTLA4 monotherapy in multiple cancer models. These data show that tretinoin induces an interferon driven, CD8+ T cell tumour microenvironment that is responsive to ICT.

Identification of Therapeutic Targets and Prognostic Biomarkers Among Integrin Subunits in the Skin Cutaneous Melanoma Microenvironment

The roles of different integrin alpha/beta (ITGA/ITGB) subunits in skin cutaneous melanoma (SKCM) and their underlying mechanisms of action remain unclear. Oncomine, UALCAN, GEPIA, STRING, GeneMANIA, cBioPortal, TIMER, TRRUST, and Webgestalt analysis tools were used. The expression levels of ITGA3, ITGA4, ITGA6, ITGA10, ITGB1, ITGB2, ITGB3, ITGB4, and ITGB7 were significantly increased in SKCM tissues. The expression levels of ITGA1, ITGA4, ITGA5, ITGA8, ITGA9, ITGA10, ITGB1, ITGB2, ITGB3, ITGB5, ITGB6 and ITGB7 were closely associated with SKCM metastasis. The expression levels of ITGA1, ITGA4, ITGB1, ITGB2, ITGB6, and ITGB7 were closely associated with the pathological stage of SKCM. The expression levels of ITGA6 and ITGB7 were closely associated with disease-free survival time in SKCM, and the expression levels of ITGA6, ITGA10, ITGB2, ITGB3, ITGB6, ITGB7, and ITGB8 were markedly associated with overall survival in SKCM. We also found significant correlations between the expression of integrin subunits and the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells). Finally, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed, and protein-protein interaction (PPI) networks were constructed. We have identified abnormally-expressed genes and gene regulatory networks associated with SKCM, improving understanding of the underlying pathogenesis of SKCM.