Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach

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Publicado en:BMC Cancer vol. 25 (2025), p. 1
Autor principal: Shu-Hwa, Chen
Otros Autores: Bo-Yi, Yu, Wen-Yu, Kuo, Ya-Bo, Lin, Sheng-Yao, Su, Wei-Hsuan Chuang, I.-Hsuan Lu, Chung-Yen, Lin
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Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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022 |a 1471-2407 
024 7 |a 10.1186/s12885-025-14089-w  |2 doi 
035 |a 3201524541 
045 2 |b d20250101  |b d20251231 
084 |a 58465  |2 nlm 
100 1 |a Shu-Hwa, Chen 
245 1 |a Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach 
260 |b Springer Nature B.V.  |c 2025 
513 |a Journal Article 
520 3 |a Accurately resolving the composition of tumor-infiltrating leukocytes is pivotal for advancing cancer immunotherapy strategies. Despite the success of some clinical trials, applying these strategies remains limited due to the challenges in deciphering the immune microenvironment. In this study, we developed a streamlined, two-step workflow to address the complexity of bioinformatics processes involved in analyzing immune cell composition from transcriptomics data. Our dockerized toolkit, DOCexpress_fastqc, integrates the hisat2-stringtie pipeline with customized scripts within Galaxy/Docker environments, facilitating RNA sequencing (RNA-seq) gene expression profiling. The output from DOCexpress_fastqc is seamlessly formatted with mySORT, a web application that employs a deconvolution algorithm to determine the immune content across 21 cell subclasses. We validated mySORT using synthetic pseudo-bulk data derived from single-cell RNA sequencing (scRNA-seq) datasets. Our predictions exhibit strong concordance with the ground-truth immune cell composition, achieving Pearson’s correlation coefficients of 0.871 in melanoma patients and 0.775 in head and neck cancer patients. Additionally, mySORT outperforms existing methods like CIBERSORT in accuracy and provides a wide range of data visualization features, such as hierarchical clustering and cell complexity plots. The toolkit and web application are freely available for the research community, providing enhanced resolution for conventional bulk RNA sequencing data and facilitating the analysis of immune microenvironment responses in immunotherapy. The mySORT demo website and Docker image are free at https://mysort.iis.sinica.edu.tw and https://hub.docker.com/r/lsbnb/mysort_2022. 
653 |a Cancer 
653 |a Clinical trials 
653 |a Cells 
653 |a Software 
653 |a Head & neck cancer 
653 |a Ribonucleic acid--RNA 
653 |a Gene expression 
653 |a Datasets 
653 |a User experience 
653 |a Bioinformatics 
653 |a Melanoma 
653 |a Quality control 
653 |a Lymphocytes 
653 |a Data processing 
653 |a Leukocytes 
653 |a Flow cytometry 
653 |a Transcriptomics 
653 |a Microenvironments 
653 |a Tumors 
653 |a Online tutorials 
653 |a Cancer immunotherapy 
653 |a Linux 
653 |a Data visualization 
700 1 |a Bo-Yi, Yu 
700 1 |a Wen-Yu, Kuo 
700 1 |a Ya-Bo, Lin 
700 1 |a Sheng-Yao, Su 
700 1 |a Wei-Hsuan Chuang 
700 1 |a I.-Hsuan Lu 
700 1 |a Chung-Yen, Lin 
773 0 |t BMC Cancer  |g vol. 25 (2025), p. 1 
786 0 |d ProQuest  |t Health & Medical Collection 
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856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3201524541/fulltext/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
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