From: Advances in single-cell RNA sequencing and its applications in cancer research
Tumor | Year | Species | Protocol | Accession number (custom database if available) | Key findings | References |
---|---|---|---|---|---|---|
Lung cancer | 2020 | Human | 10 × Genomics | EGAD00001005054 | Identified a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage, and revealed potential diagnostic and therapeutic targets in cancer-microenvironment interactions | [156] |
 | 2020 | Human | Smart-seq2 | NCBI BioProject #PRJNA591860 | Identified that individual tumors and cancer cells exhibit substantial molecular diversity and that tumor microenvironment cells exhibit marked therapy-induced plasticity | [157] |
 | 2022 | Human | STRT-seq | HRA000270 | Provided novel insights into the tumor heterogeneity of NSCLC in terms of the identification of prevalent mixed-lineage subpopulations of cancer cells with combined SCC, ADC, and NET signatures and offered clues for potential treatment strategies in these patients | [158] |
Gastric cancer | 2020 | Human | 10 × Genomics | PRJEB40416 | Highlighted response heterogeneity within MSI-H gastric cancer treated with pembrolizumab monotherapy; supported the potential of extended baseline and early on-treatment biomarker analyses to identify responders | [95] |
 | 2021 | Human | 10 × Genomics | EGAS00001004443 | The links between tumor cell lineage/state and ITH were illustrated at the transcriptome, genotype, molecular, and phenotype levels | [72] |
 | 2021 | Human | 10 × Genomics | HRA000051 | A panel of differentiation-related genes revealed large differences in differentiation degree within and between tumors | [80] |
Liver cancer | 2022 | Human | Seq-Well S3 | GSE186975 | Identified five hepatoblastoma tumor signatures that may account for the tumor heterogeneity observed in this disease, and used patient-derived hepatoblastoma spheroid cultures to predict differential responses to treatment based on the transcriptomic signature of each tumor | [237] |
Esophageal cancer | 2022 | Human | 10 × Genomics | GSE196756 | Revealed intratumoral and intertumoral epithelium heterogeneity and tremendous differences between the tumor and normal epithelium. Epithelium cells and myeloid cells had more frequent cell‒cell communication than epithelium cells and T cells | [238] |
 | 2021 | Human | 10 × Genomics | PRJNA777911 | Uncovered heterogeneity in most cell types of the ESCC stroma, particularly in the fibroblast and immune cell compartments | [86] |
Melanoma | 2016 | Human | Smart-seq2 | DUOS-000002; GSE72056 | Malignant cells within the same tumor displayed heterogeneity in the transcription of proteins related to the cell cycle, spatial context, and drug resistance program | [239] |
 | 2020 | Human | 10 × Genomics | GSE139829 | Analysis of tumor cells revealed previously unappreciated subclonal genomic complexity and transcriptional states | [94] |
 | 2021 | Human | 10 × Genomics | GSE138665 | Uncovered intratumoral heterogeneity at the genome and transcriptome level | [81] |
Acute lymphoblastic leukemia | 2020 | Human | 10 × Genomics | GSE132509 | The predicted developmental states of cancer cells were inversely correlated with the expression levels of ribosomal protein, which could be a common contributor to intraindividual heterogeneity in childhood ALL patients | [240] |
Diffuse large B cell lymphoma | 2022 | Human | 10 × Genomics | CNGBdb: CNP0001940 | High intratumor and intertumor heterogeneity was identified in DLBCL | [216] |
 | 2022 | Human | 10 × Genomics | Provided an in-depth dissection of the transcriptional features of malignant B cells and the TME in DLBCL and new insights into DLBCL heterogeneity | [229] | |
Primary central nervous system lymphoma | 2021 | Human | 10 × Genomics | GEO: GSE181304 | Different subtypes of T cells and DCs showed significant heterogeneity | [85] |
B-cell lymphoma | 2020 | Human | 10 × Genomics | Malignant subpopulations from the same patient responded strikingly differently to anticancer drugs ex vivo, highlighting the relevance of intratumor heterogeneity for personalized cancer therapy | [241] | |
Cutaneous T cell lymphoma | 2018 | Human | BD Precise assay | Correspondence with authors | Patients with SS displayed a high degree of single-cell heterogeneity within the malignant T-cell population, and the distinct subpopulation of malignant T cells exhibited HDACi resistance | [76] |
 | 2019 | Human | 10 × Genomics | GSE128531 | Provided an unprecedented view of lymphocyte heterogeneity and identifying tumor-specific molecular signatures, with important implications for diagnosis and personalized disease treatment | [77] |
 | 2021 | Human | 10 × Genomics | GSE171811 | Striking subclonal molecular heterogeneity was observed within clonal malignant T-cell populations in the skin and blood of patients with leukemic CTCL. The tissue microenvironment influenced the transcriptional state of malignant T cells, likely contributing to the evolution of malignant clones | [242] |
 | 2022 | Human | 10 × Genomics | GSA-Human: HRA000166 | Revealed the intratumor and interlesion diversity of CTCL patients, proposed a multistep tumor evolution model that further established a novel subtype, the TCyEM group with a cytotoxic effector memory T-cell phenotype, and identified increased M2 macrophage infiltration | [78] |
Subcutaneous panniculitis-like T cell lymphoma | 2021 | Human | 10 × Genomics | GSA-Human: HRA000370 | Provided insights into the heterogeneity of subcutaneous panniculitis-like T-cell lymphoma, as well as a better understanding of the transcription characteristics and immune microenvironment of this rare tumor | [208] |