Evidence map›Paper›PMID 39507529›Full record

ArticleFrontiers in immunology2024

Comprehensive single-cell and bulk transcriptomic analyses to develop an NK cell-derived gene signature for prognostic assessment and precision medicine in breast cancer.

Qianshan Hou, Chunzhen Li, Yuhui Chong, Haofeng Yin, Yuchen Guo, Lanjie Yang, Tianliang Li, Shulei Yin

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PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Qianshan Hou *National Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Chunzhen Li *National Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Yuhui Chong *School of Pharmacy, Naval Medical University, Shanghai, China.
Haofeng YinNational Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Yuchen GuoNational Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Lanjie YangNational Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Tianliang LiNational Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.
Shulei YinNational Key Laboratory of Immunity & Inflammation, Institute of Immunology, Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Natural killer (NK) cells play crucial roles in mediating anti-cancer activity in breast cancer (BRCA). However, the potential of NK cell-related molecules in predicting BRCA outcomes and guiding personalized therapy remains largely unexplored. This study focused on developing a prognostic and therapeutic prediction model for BRCA by incorporating NK cell-related genes. Methods: The data analyzed primarily originated from the TCGA and GEO databases. The prognostic role of NK cells was evaluated, and marker genes of NK cells were identified via single-cell analysis. Module genes closely associated with immunotherapy resistance were identified by bulk transcriptome-based weighted correlation network analysis (WGCNA). Following taking intersection and LASSO regression, NK-related genes (NKRGs) relevant to BRCA prognosis were screened, and the NK-related prognostic signature was subsequently constructed. Analyses were further expanded to clinicopathological relevance, GSEA, tumor microenvironment (TME) analysis, immune function, immunotherapy responsiveness, and chemotherapeutics. Key NKRGs were screened by machine learning and validated by spatial transcriptomics (ST) and immunohistochemistry (IHC). Results: Tumor-infiltrating NK cells are a favorable prognostic factor in BRCA. By combining scRNA-seq and bulk transcriptomic analyses, we identified 7 NK-related prognostic NKRGs (CCL5, EFHD2, KLRB1, C1S, SOCS3, IRF1, and CCND2) and developed an NK-related risk scoring (NKRS) system. The prognostic reliability of NKRS was verified through survival and clinical relevance analyses across multiple cohorts. NKRS also demonstrated robust predictive power in various aspects, including TME landscape, immune functions, immunotherapy responses, and chemotherapeutic sensitivity. Additionally, KLRB1 and CCND2 emerged as key prognostic NKRGs identified through machine learning and external validation, with their expression correlation with NK cells confirmed in BRCA specimens by ST and IHC. Conclusions: We developed a novel NK-related gene signature that has proven valuable for evaluating prognosis and treatment response in BRCA, expecting to advance precision medicine of BRCA.

Indexed as

Biomarkers, TumorBreast NeoplasmsGene Expression ProfilingKiller Cells, NaturalPrecision MedicineSingle-Cell AnalysisTranscriptomeTumor MicroenvironmentFemaleGene Expression Regulation, NeoplasticHumansLymphocytes, Tumor-InfiltratingMiddle AgedPrognosisBiomarkers, Tumorbreast cancerimmunotherapynatural killer (NK) cellprognostic signaturescRNA-seqtumor microenvironment

Identifiers

PMID39507529
PMCPMC11537931

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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.