scCT-DB, an omnibus for cancer patient-derived paired pre- and post-treatment single-cell transcriptomes to reveal drug perturbation and drug resistance mechanisms

Drug resistance continues to be a major challenge in cancer treatment. Understanding cellular and molecular dynamics after treatment is crucial for elucidating resistance mechanisms. Single-cell RNA sequencing (scRNA-seq) of paired pre- and post-treatment patient samples enables high-resolution exploration of such dynamics, but rapidly accumulated relevant data bring challenges for easy data access, integration, and reuse. Therefore, we present the Cancer Treatment-related Single-Cell transcriptome DataBase (scCT-DB, http://scctdb.ncpsb.org.cn). scCT-DB has comprehensively collected 266 patient-derived paired pre- and post-treatment scRNA-seq datasets processed by a uniform pipeline and with detailed and structured metadata, most of which simultaneously include information on primary/acquired drug response. scCT-DB includes 6.19 million cells from 1142 original patient samples, 27 major cancer types, 96 therapeutic regimens, and 102 drugs (involving chemotherapy, immunotherapy, hormone therapy, and targeted therapy). scCT-DB also provides 48 dataset pairs with opposite primary response groupings and 41 longitudinal datasets with ≥3 sampling timepoints. Besides data browsing, download, and search, scCT-DB also supports single-dataset analysis (including cell abundance, gene, cell state, and intercellular communication perturbation analyses), dataset comparative and re-combination analyses, providing insights into drug perturbation mechanisms and their heterogeneity in patients, drug resistance mechanisms, and discovery of biomarkers predictive of treatment response, etc.

Authors

Institutions

Publication Details

Journal
Nucleic Acids Research
Published
2025-10-23
DOI
https://doi.org/10.1093/nar/gkaf1065
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

scCT-DB, an omnibus for cancer patient-derived paired pre- and post-treatment single-cell transcriptomes to reveal drug perturbation and drug resistance mechanisms

Zhongyang Liu, Ruiyu Zhang, Shurui Ma, Tingting Zhao et al.
1 citations
Nucleic Acids Research
Single-cell and spatial transcriptomics
0.81
article

scCT-DB, an omnibus for cancer patient-derived paired pre- and post-treatment single-cell transcriptomes to reveal drug perturbation and drug resistance mechanisms

Zhongyang Liu, Ruiyu Zhang, Shurui Ma, Tingting Zhao, Jianzhou Jiang, Li Zuo, Peng Liu, Dong Li, Xiang‐Dong Li, Anxin Gu, Dan Li, Mu Hong, Xinyi Ren
article en
1 citations

Abstract

Drug resistance continues to be a major challenge in cancer treatment. Understanding cellular and molecular dynamics after treatment is crucial for elucidating resistance mechanisms. Single-cell RNA sequencing (scRNA-seq) of paired pre- and post-treatment patient samples enables high-resolution exploration of such dynamics, but rapidly accumulated relevant data bring challenges for easy data access, integration, and reuse. Therefore, we present the Cancer Treatment-related Single-Cell transcriptome DataBase (scCT-DB, http://scctdb.ncpsb.org.cn). scCT-DB has comprehensively collected 266 patient-derived paired pre- and post-treatment scRNA-seq datasets processed by a uniform pipeline and with detailed and structured metadata, most of which simultaneously include information on primary/acquired drug response. scCT-DB includes 6.19 million cells from 1142 original patient samples, 27 major cancer types, 96 therapeutic regimens, and 102 drugs (involving chemotherapy, immunotherapy, hormone therapy, and targeted therapy). scCT-DB also provides 48 dataset pairs with opposite primary response groupings and 41 longitudinal datasets with ≥3 sampling timepoints. Besides data browsing, download, and search, scCT-DB also supports single-dataset analysis (including cell abundance, gene, cell state, and intercellular communication perturbation analyses), dataset comparative and re-combination analyses, providing insights into drug perturbation mechanisms and their heterogeneity in patients, drug resistance mechanisms, and discovery of biomarkers predictive of treatment response, etc.

Nucleic Acids ResearchVol. 54(D1)
Harbin Medical University (CN), Anhui Medical University (CN), Academy of Military Medical Sciences (CN), Beijing Tian Tan Hospital (CN), Third Affiliated Hospital of Harbin Medical University (CN), Hebei University (CN)
Openalex Percentile: Top 22%
Single-cell and spatial transcriptomics
0.81
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.