A Leukocyte Infiltration Score Defined by a Gene Signature Predicts Melanoma Patient Prognosis

Abstract

Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)-Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine. This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.

Melanoma Stem Cell-Like Phenotype and Significant Suppression of Immune Response within a Tumor Are Regulated by TRIM28 Protein

“…Next, we compared the level of transcriptome-based immune-related scores ( Table S5 ), namely, the Immune Score (calculated as previously reported in [ 31 ]) and the Leukocyte Infiltration Score (LIS; calculated as previously reported in [ 32 ]) in TRIM28 NORM and TRIM28 HIGH melanoma samples and observed significantly lower level of both scores in TRIM28 HIGH samples ( p < 0.0001; Figure 4 B,C). Furthermore, the GSEA confirmed significant depletion of the Immune Score-associated signature in the TRIM28 HIGH phenotype (NES = −3.210, p < 0.0001, FDR < 0.0001); ( Figure 4 D).…”

“…The Immune Scores were estimated based on the transcriptome profiles of each sample, as previously reported [ 31 ]. The Leukocyte Infiltration Scores (LIS) were calculated based on the expression level of 25 genes, as previously reported [ 32 ]. All immune-associated scores used in this study are shown in Table S4 .…”

“…( B ) Tukey box plots of the Immune Score (ESTIMATE [ 31 ]) in TRIM28 NORM and TRIM28 HIGH melanomas. ( C ) Tukey box plots of the Leukocyte Infiltration Score (LIS [ 32 ]) in TRIM28 NORM and TRIM28 HIGH melanomas. ( D ) The GSEA with all DEGs in TRIM28 HIGH vs. TRIM28 NORM ( n = 9165) revealed significant depletion of the Immune Score signature (only genes positively associated with the Immune Score signature were used as a reference).…”

<p>Decreasing Microtubule Actin Cross-Linking Factor 1 Inhibits Melanoma Metastasis by Decreasing Epithelial to Mesenchymal Transition</p>

“…As a result, the five-year survival of patients is low, and malignant melanoma will become a formidable disease once cancer cells colonize other tissues. 3,4 Immunotherapy with immune checkpoint inhibitors (inhibitory monoclonal antibodies against the cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed death 1 (PD-1/ PDL1) and targeted therapy (Vemurafenib and nivolumab) acted as a certain efficiency on metastatic melanoma; unfortunately, these immune-based therapies are not fully responsive in some advanced stage melanoma. 5,6 In this regard, it is desirable to adopt an efficient therapeutic strategy to overcome the shortage in successful treatment of metastatic melanoma based on immune checkpoint inhibitors and targeted therapy.…”

Combining texture features of whole slide images improves prognostic prediction of recurrence-free survival for cutaneous melanoma patients

“…Many previous studies had attempted to develop prognostic models using different types of variables including clinicopathologic, mutation, mRNA, microRNA, and methylation variables. Zhao et al (6) identi ed a 25-gene signature that can effectively estimate the level of immune cell in ltration in melanoma, providing a robust biomarker signi cantly related to survival outcome (disease-speci c survival, post-recurrence survival, or overall survival). Multidimensional omics data were also utilized to provide more accurate prediction.…”