Evidence map›Paper›PMID 37021816›Full record

ArticleCancer medicine2023

Integrative single-cell sequencing analysis distinguishes survival-associated cells from the breast cancer microenvironment.

Ling Huang, Shijie Qin, Lingling Xia, Fei Ma, Liming Chen

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 3 countries.

Ling HuangDepartment of Biochemistry, School of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, 210023, China.
Shijie QinLaboratory for Comparative Genomics and Bioinformatics, College of Life Science, Nanjing Normal University, Nanjing, Jiangsu, 210046, China.
Lingling XiaDepartment of Biochemistry, School of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, 210023, China.
Fei MaLaboratory for Comparative Genomics and Bioinformatics, College of Life Science, Nanjing Normal University, Nanjing, Jiangsu, 210046, China.
Liming ChenDepartment of Biochemistry, School of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu, 210023, China.ORCID 0000-0002-7782-9824
Nanjing Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBreast cancer shows a highly complex tumor microenvironment by containing various cell types. Identifying prognostic cell populations in the tumor microenvironment will improve the mechanistical understanding of breast cancer and facilitate the development of new breast cancer therapies by targeting the tumor microenvironment. The development of single-cell sequencing reveals various cell types, states, and lineages within the context of heterogenous breast tumors, but identifying phenotype-associated subpopulations is challenging.

resultsHere, we applied Scissor (single-cell identification of subpopulations with bulk Sample phenotype correlation) to integrate single cell and bulk data of breast cancer, and found that MHC-deficient tumor cells, FABP5+ macrophages, and COL1A1+ cancer-associated fibroblasts (CAFs) were detrimental to patient survival, while T cells and dendritic cells were the main protective cells. MHC-deficient tumor cells show strong downregulation of MHC expression for immune evasion by downregulating interferon and JAK-STATs signaling. FABP5+ macrophages show low antigen-presenting activity via associating with lipid metabolism. Our data suggest that COL1A1+ CAFs may block T-cell immune infiltration through cell interaction in breast tumor microenvironment.

conclusionTaken together, our study reveals survival-associated subpopulations in breast tumor microenvironment. Importantly, subpopulations related to immune evasion of breast cancer is uncovered.

Indexed as

Cancer-Associated FibroblastsNeoplasmsFatty Acid-Binding ProteinsHumansMacrophagesPrognosisTumor MicroenvironmentFABP5 protein, humanFatty Acid-Binding Proteinsbreast cancerimmune evasionprognostic cellsingle-cell sequencingtumor microenvironment

Identifiers

PMID37021816
PMCPMC10278529
OpenAlexW4362657594

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.