Additional file 2 of Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma

Additional file 2: Supplemental Figures_S1_to_S17.PDF. Fig. S1. Tumor purity in EPICA methylation subsets and validation of methylation classes in Firehose Legacy TCGA primary and metastatic melanoma cohorts. Fig. S2. Oncoplot displaying common somatic nonsynonymous alterations in the Stage III/IV EPICA MM cohort, divided by methylation groups. Fig. S3. Promoter methylation vs. gene expression analysis. Fig. S4. IPA core analysis for differentially expressed genes in the DEM, LOW, INT and CIMP EPICA classes. Fig. S5. Expression and prognostic significance of the IFNG, TREX1, IRGM, and IL1RN target genes in EPICA methylation classes. Fig. S6. Top master molecules activated in CIMP MM classes are negative regulators of target genes with prognostic significance. Fig. S7. Expression of ICB predictive signatures in methylation-defined classes of the TCGA MM cohort. Fig. S8. Assessment of immune-related gene signatures in the EPICA methylation-defined clusters. Fig. S9. LOW lesions are enriched for intra-tumor T cells compared to CIMP lesions. Fig. S10. Association of methylation classes and tumor immune contexture with subsequent stage progression in EPICA cohort. Fig. S11. Analysis strategy for identification of CD8+ subsets characterized by differential expression of TCF-1, PD-1 and TIM-3 in EPICA melanoma lesions by multiple immunofluorescence (mIF). Fig. S12. Correlation analysis in EPICA and TCGA MM cohorts of genes in the HLA Class I APM pathway and clinical significance of the HLA Class I APM signature. Fig. S13. Expression of HLA Class I antigens on tumor cells in representative lesions belonging to the DEM, LOW, INT and CIMP classes of the EPICA cohort. Fig. S14. Expression of melanoma differentiation signatures in EPICA methylation subsets. Fig. S15. Guadecitabine treatment promotes melanoma de-differentiation. Fig. S16. Guadecitabine promotes de-differentiation of the differentiated melanoma clone 2_59. Fig. S17. Guadecitabine treatment of differentiated melanoma lines reverses the activation state of UR identified in CIMP lesions.

Institutions

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.29603203
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Additional file 2 of Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma

Figshare
Cutaneous Melanoma Detection and Management
article

Additional file 2 of Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma

article en

Abstract

Additional file 2: Supplemental Figures_S1_to_S17.PDF. Fig. S1. Tumor purity in EPICA methylation subsets and validation of methylation classes in Firehose Legacy TCGA primary and metastatic melanoma cohorts. Fig. S2. Oncoplot displaying common somatic nonsynonymous alterations in the Stage III/IV EPICA MM cohort, divided by methylation groups. Fig. S3. Promoter methylation vs. gene expression analysis. Fig. S4. IPA core analysis for differentially expressed genes in the DEM, LOW, INT and CIMP EPICA classes. Fig. S5. Expression and prognostic significance of the IFNG, TREX1, IRGM, and IL1RN target genes in EPICA methylation classes. Fig. S6. Top master molecules activated in CIMP MM classes are negative regulators of target genes with prognostic significance. Fig. S7. Expression of ICB predictive signatures in methylation-defined classes of the TCGA MM cohort. Fig. S8. Assessment of immune-related gene signatures in the EPICA methylation-defined clusters. Fig. S9. LOW lesions are enriched for intra-tumor T cells compared to CIMP lesions. Fig. S10. Association of methylation classes and tumor immune contexture with subsequent stage progression in EPICA cohort. Fig. S11. Analysis strategy for identification of CD8+ subsets characterized by differential expression of TCF-1, PD-1 and TIM-3 in EPICA melanoma lesions by multiple immunofluorescence (mIF). Fig. S12. Correlation analysis in EPICA and TCGA MM cohorts of genes in the HLA Class I APM pathway and clinical significance of the HLA Class I APM signature. Fig. S13. Expression of HLA Class I antigens on tumor cells in representative lesions belonging to the DEM, LOW, INT and CIMP classes of the EPICA cohort. Fig. S14. Expression of melanoma differentiation signatures in EPICA methylation subsets. Fig. S15. Guadecitabine treatment promotes melanoma de-differentiation. Fig. S16. Guadecitabine promotes de-differentiation of the differentiated melanoma clone 2_59. Fig. S17. Guadecitabine treatment of differentiated melanoma lines reverses the activation state of UR identified in CIMP lesions.

Figshare
University of Siena (IT), University of Miami (US), Biogem (IT), Italian Network for Tumor Biotherapy Foundation (IT), Fondazione IRCCS Istituto Nazionale dei Tumori (IT), University of Florence (IT), New York University (US), University of Naples Federico II (IT)
Openalex Percentile: Top 39%
Cutaneous Melanoma Detection and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.