Single cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species
Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into a spectrum of states, which may promote or limit tumor outgrowth, but remain poorly understood. Here, we used single-cell RNA sequencing to map TIMs in non-small cell lung cancer patients. We uncovered 25 TIM states, most of which were reproducibly found across patients. To facilitate translational research o...
Provenance — who produced it, who reused it
Linked to 35 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- High-resolution single-cell atlas reveals diversity and plastici... 2022 · 459 cites
- Emergence of a High-Plasticity Cell State during Lung Cancer Evo... 2020 · 398 cites
- Tumour heterogeneity and intercellular networks of nasopharyngea... 2021 · 290 cites
- Assessing single-cell transcriptomic variability through density... 2021 · 172 cites
- m5C RNA Methylation Regulators Predict Prognosis and Regulate th... 2021 · 134 cites
- De novo analysis of bulk RNA-seq data at spatially resolved sing... 2022 · 95 cites
- An integrated single-cell transcriptomic dataset for non-small c... 2023 · 84 cites
- BIDCell: Biologically-informed self-supervised learning for segm... 2024 · 72 cites
27 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.