INTEGRATION OF SINGLE-CELL DATA TO CORRELATE TUMOR-ASSOCIATED MACROPHAGES SIGNATURES AND CLINICAL OUTCOME IN MELANOMA
Vol 1, 2020 - 131602
Especialização/Aperfeiçoamento
Abstract
INTRODUCTION AND OBJECTIVES: Melanoma is a very aggressive and highly lethal disease, being responsible for the majority of skin cancer-related deaths worldwide. The melanoma cells are surrounded by a heterogeneous tumor microenvironment (TME), comprising stromal, and immune cells. The tumor-associated macrophages (TAM) are particularly abundant in the TME and the TAM subpopulation-specific signatures have been associated with distinct clinical outcomes. The identification of new gene expression profiles of TAM subpopulations through the integration of melanoma data and normal skin at single-cell resolution can unveil TAM heterogeneity in melanoma TME and its impact on tumor clinical outcomes. MATERIAL AND METHODS: Pre-processed single-cell RNA-seq data from melanoma and healthy skin samples were obtained from the public repository Gene Expression Omnibus (GEO). Data analysis was performed with Seurat (v.3.1.1) in R (v.4.0). Myeloid cells were extracted from each study using the differential expression of myeloid cells canonical markers (LYZ, CD68, and AIF1), which have been used in at least 3 different previous studies. We combined the myeloid data from each study and performed data normalization and scaling for downstream analysis. Dimensionality reduction and clustering were performed. TAM subpopulation-specific signatures were assessed from the differential expression analysis and each signature was used as reference data for deconvolution methods to assess the association between patients’ clinical/pathological data and the presence of TAM subpopulations in TCGA melanoma patients. RESULTS AND CONCLUSION: The data integration of normal and tumor samples resulted in 4,219 cells segregated into 12 clusters of myeloid cells with distinct expression profiles. By comparing previously reported TAM profiles across different studies, our thorough analysis allowed the identification of well-established and also new TAM signatures. Skin resident subpopulations were also found. We identified a new specific TAM subpopulation signature significantly impacting the patient's overall survival. Our work contributes to the characterization of well-established TAM subpopulations and the discovery of new ones, paving the way for the development of new immunotherapies.
Institutions
- 1 Bioinformatics and Computational Biology Lab, Brazilian National Cancer Institute, Rio de Janeiro, RJ
- 2 Laboratory of Immunometabolism, Department of Genetics, Evolution, Microbiology, and Immunology, Institute of Biology, University of Campinas, Campinas, SP;
- 3 Laboratory of Aging Biology (LABE), Department of Biochemistry and Tissue Biology, University of Campinas, Campinas, SP, Brazil
Track
- Bioinformatics
Keywords
Melanoma
Tumor-Associated Macrophages
Single-Cell RNA-Seq
Tumor microenvironment
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Palloma Almeida
Boa tarde, Edward! Obrigada pelo seu comentário e pelos elogios. Ainda não estou no doutorado, mas estou em processo de preparação sob orientação da Dra. Boroni! A seguir, pretendemos utilizar machine learning para selecionar genes codificadores de proteínas de membrana que melhor distinguem cada cluster, e assim separá-los por Fluorescence-activated cell sorting (FACS). Desse modo, análises subsequentes como ensaio de Acessibilidade da Cromatina por Transposase com sequenciamento de alto rendimento (ATAC-seq), permitem uma melhor caracterização das subpopulações com impacto no desfecho clínico dos pacientes com melanoma metastático
Uma leitura bacana é: Ludwig et al., 2019, Cell Reports. https://doi.org/10.1016/j.celrep.2019.05.046
Não é diretamente relacionado ao trabalho, mas aborda as técnicas que mencionei e pode facilitar o entendimento.
Edward Helal Neto
Olá Paloma, bem impressionante vc ter feito esse trabalho todo sem nem estar no doutorado.
O seu grupo também trabalha com o uso de reagentes, como medicamentos, para tentar modular esses subgrupos?
Bom saber que a situação atual do país não te desanimou. Espero que vc consiga entrar no DO para dar continuidade a esse projeto. Nos momentos de crise é q precisamos ser mais fortes. Boa sorte e sucesso com a pesquisa.
Palloma Almeida
Edward, muito obrigada, mas eu represento otrabalho de uma bela equipe, que me motiva inclusive nos momentos de desânimo em que vivemos no país como um todo!
Nosso grupo ainda nao trabalha com reagentes, pois o trabalho ainda está na sua fase in silico, mas é algo que está no nosso planejamento, justamente quando formos para o FACS e ATAC-seq e, até mesmo, single-cell RNAseq com nossos próprios dados!
Boa sorte e sucesso para você e sua pesquisa também!