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SORC: an integrated spatial omics resource in cancer.
Zhou, Weiwei; Su, Minghai; Jiang, Tiantongfei; Yang, Qingyi; Sun, Qisen; Xu, Kang; Shi, Jingyi; Yang, Changbo; Ding, Na; Li, Yongsheng; Xu, Juan.
Afiliação
  • Zhou W; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Su M; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Jiang T; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Yang Q; School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Sun Q; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Xu K; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Shi J; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Yang C; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Ding N; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Li Y; School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
  • Xu J; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, Heilongjiang Province, China.
Nucleic Acids Res ; 52(D1): D1429-D1437, 2024 Jan 05.
Article em En | MEDLINE | ID: mdl-37811897
ABSTRACT
The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http//bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Genéticas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bases de Dados Genéticas / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Nucleic Acids Res Ano de publicação: 2024 Tipo de documento: Article