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CiTSA: a comprehensive platform provides experimentally supported signatures of cancer immunotherapy and analysis tools based on bulk and scRNA-seq data

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Abstract

Immunotherapy has greatly changed the status of cancer treatment, and many patients do not respond or develop acquired resistance. The related research is blocked by lacking of comprehensive resources for researchers to discovery and analysis signatures, then further exploring the mechanisms. Here, we first offered a benchmarking dataset of experimentally supported signatures of cancer immunotherapy by manually curated from published literature works and provided an overview. We then developed CiTSA (http://bio-bigdata.hrbmu.edu.cn/CiTSA/) which stores 878 entries of experimentally supported associations between 412 signatures such as genes, cells, and immunotherapy across 30 cancer types. CiTSA also provides flexible online tools to identify and visualize molecular/cell feature and interaction, to perform function, correlation, and survival analysis, and to execute cell clustering, cluster activity, and cell–cell communication analysis based on single cell and bulk datasets of cancer immunotherapy. In summary, we provided an overview of experimentally supported cancer immunotherapy signatures and developed CiTSA which is a comprehensive and high-quality resource and is helpful for understanding the mechanism of cancer immunity and immunotherapy, developing novel therapeutic targets and promoting precision immunotherapy for cancer.

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Data availability

The datasets generated and/or used during the current study are available in the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/), The Cancer Genome Atlas (https://portal.gdc.cancer.gov/), and we also develop database, CiTSA (http://bio-bigdata.hrbmu.edu.cn/CiTSA/).

Abbreviations

BRCA:

Breast cancer

CAN:

Copy number alteration

COCA:

Colon cancer

FC:

Fold change

GBM:

Glioma

HNSC:

Head and neck cancer

LUCA:

Lung cancer

MM:

Myeloma

NSCLC:

Non-small cell lung cancer

OS:

Overall survival

R/NR:

Immunotherapy response/no response

SKCM:

Skin melanoma

STAD:

Gastric cancer

T/NT:

Immunotherapy treatment/no treatment

TCGA:

The Cancer Genome Atlas

TMB:

Tumor mutation burden

TME:

Tumor microenvironment

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Funding

This work was supported by the National Natural Science Foundation of China (Grant Nos. 62101164, 62172131 and 32070622), the National Key R&D Program of China (2018YFC2000100), the China Brain Project (2021ZD0202403), the China Postdoctoral Science Special Foundation (Grant No. 2020T130162), the Heilongjiang Touyan Innovation Team Program, Heilongjiang Province Natural Science Foundation Joint guidance Project (Grant No. LH2022F042), the China Postdoctoral Science Foundation (Grant No. 2019M661295), and the Doctor Green Seedlings Breaking Ground Project of Harbin Medical University (Grant No. QMPT-2010).

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Author notes

  1. Feng Li, Kejing Dong, Chunlong Zhang, Jingwen Wang have contributed equally.

Authors and Affiliations

  1. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China

    Feng Li, Kejing Dong, Chunlong Zhang, Jingwen Wang, Yongjuan Tang, Ke Xue, Xuan Zheng, Kaiyue Song, Xiaomeng Zhang, Mengyue Li, Rui Zhao, Xiaoling Zhong, Yanjun Xu, Yunpeng Zhang & Xia Li

Authors
  1. Feng Li
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  2. Kejing Dong
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Contributions

YJX, XL, and YPZ contributed to conceptualization; FL, KJD, and JWW contributed to single cell and bulk data curation; FL, KJD, and CLZ performed formal analysis; KJD, JWW, YJT, KX, XZ, and XMZ contributed to the experimentally supported data curation; FL, YJX, and CLZ contributed to interpreting the results; KYS, MYL, RZ, and XLZ contributed to organization and visualization of diagrams; FL and KJD contributed to platform development; FL, YJX, CLZ, and JWW contributed to writing the manuscript. All the authors commented on the manuscript.

Corresponding authors

Correspondence to Yanjun Xu, Yunpeng Zhang or Xia Li.

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Li, F., Dong, K., Zhang, C. et al. CiTSA: a comprehensive platform provides experimentally supported signatures of cancer immunotherapy and analysis tools based on bulk and scRNA-seq data. Cancer Immunol Immunother 72, 2319–2330 (2023). https://doi.org/10.1007/s00262-023-03414-6

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