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pmid:33841428

PNOC Expressed by B Cells in Cholangiocarcinoma Was Survival Related and LAIR2 Could Be a T Cell Exhaustion Biomarker in Tumor Microenvironment: Characterization of Immune Microenvironment Combining Single-Cell and Bulk Sequencing Technology.

Zheng Chen · Mincheng Yu · Jiuliang Yan · Lei Guo · Bo Zhang · Shuang Liu · Jin Lei · Wentao Zhang · Binghai Zhou · Jie Gao · Zhangfu Yang · Xiaoqiang Li · Jian Zhou · Jia Fan · Qinghai Ye · Hui Li · Yongfeng Xu · Yongsheng Xiao

Frontiers in immunology · 2021 doi:10.3389/fimmu.2021.647209

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title
PNOC Expressed by B Cells in Cholangiocarcinoma Was Survival Related and LAIR2 Could Be a T Cell Exhaustion Biomarker in Tumor Microenvironment: Characterization of Immune Microenvironment Combining Single-Cell and Bulk Sequencing Technology.
doi
10.3389/fimmu.2021.647209
pmid
33841428
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[0]
Zheng Chen
[1]
Mincheng Yu
[2]
Jiuliang Yan
[3]
Lei Guo
[4]
Bo Zhang
[5]
Shuang Liu
[6]
Jin Lei
[7]
Wentao Zhang
[8]
Binghai Zhou
[9]
Jie Gao
[10]
Zhangfu Yang
[11]
Xiaoqiang Li
[12]
Jian Zhou
[13]
Jia Fan
[14]
Qinghai Ye
[15]
Hui Li
[16]
Yongfeng Xu
[17]
Yongsheng Xiao
journal
Frontiers in immunology
year
2021
abstract
Background: Cholangiocarcinoma was a highly malignant liver cancer with poor prognosis, and immune infiltration status was considered an important factor in response to immunotherapy. In this investigation, we tried to locate immune infiltration related genes of cholangiocarcinoma through combination of bulk-sequencing and single-cell sequencing technology. Methods: Single sample gene set enrichment analysis was used to annotate immune infiltration status in datasets of TCGA CHOL, GSE32225, and GSE26566. Differentially expressed genes between high- and low-infiltrated groups in TCGA dataset were yielded and further compressed in other two datasets through backward stepwise regression in R environment. Single-cell sequencing data of GSE138709 was loaded by Seurat software and was used to examined the expression of infiltration-related gene set. Pathway changes in malignant cell populations were analyzed through scTPA web tool. Results: There were 43 genes differentially expressed between high- and low-immune infiltrated patients, and after further compression, PNOC and LAIR2 were significantly correlated with high immune infiltration status in cholangiocarcinoma. Through analysis of single-cell sequencing data, PNOC was mainly expressed by infiltrated B cells in tumor microenvironment, while LAIR2 was expressed by Treg cells and partial GZMB+ CD8 T cells, which were survival related and increased in tumor tissues. High B cell infiltration levels were related to better overall survival. Also, malignant cell populations demonstrated functionally different roles in tumor progression. Conclusion: PNOC and LAIR2 were biomarkers for immune infiltration evaluation in cholangiocarcinoma. PNOC, expressed by B cells, could predict better survival of patients, while LAIR2 was a potential marker for exhaustive T cell populations, correlating with worse survival of patients.
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Publicly available datasets were analyzed in this study. This data can be found here: CHOL and LIHC in TCGA database: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga: GSE32225: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32225, GSE26566: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26566, GSE138709: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709.
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Stepwise Regression Model for Compression of Immune Infiltration Related Genes.
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PMC8024580
section_index
16
section_title
Several Genes Were Associated With Immune Infiltration Status by Stepwise Regression Model
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Table 1
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Stepwise Regression Model for Compression of Immune Infiltration Related Genes.
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[2]
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[4]
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[1]
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[3]
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[4]
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[5]
2.28E-06
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[1]
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0.00016571
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Publicly available datasets were analyzed in this study. This data can be found here: CHOL and LIHC in TCGA database: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga: GSE32225: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32225, GSE26566: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26566, GSE138709: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709.
basis
The paper names GSE32225, GSE26566, GSE138709 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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data:geo:GSE138709
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GEO GSE138709
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urvival analysis, combining genomics data of microarray with clinical information (33). Cholangiocar
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33841428", "kind": "science-record", "revision": 7, "content_hash": "sha256:4435179a089d17eb5e5000aac54138ae44990b1ea799751aa9f6743639019712", "created_at": "2026-11-01T15:41:32Z", "updated_at": "2026-11-01T22:03:31Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "PNOC Expressed by B Cells in Cholangiocarcinoma Was Survival Related and LAIR2 Could Be a T Cell Exhaustion Biomarker in Tumor Microenvironment: Characterization of Immune Microenvironment Combining Single-Cell and Bulk Sequencing Technology.", "doi": "10.3389/fimmu.2021.647209", "pmid": "33841428", "authors": ["Zheng Chen", "Mincheng Yu", "Jiuliang Yan", "Lei Guo", "Bo Zhang", "Shuang Liu", "Jin Lei", "Wentao Zhang", "Binghai Zhou", "Jie Gao", "Zhangfu Yang", "Xiaoqiang Li", "Jian Zhou", "Jia Fan", "Qinghai Ye", "Hui Li", "Yongfeng Xu", "Yongsheng Xiao"], "journal": "Frontiers in immunology", "year": 2021, "abstract": "Background: Cholangiocarcinoma was a highly malignant liver cancer with poor prognosis, and immune infiltration status was considered an important factor in response to immunotherapy. In this investigation, we tried to locate immune infiltration related genes of cholangiocarcinoma through combination of bulk-sequencing and single-cell sequencing technology.\nMethods: Single sample gene set enrichment analysis was used to annotate immune infiltration status in datasets of TCGA CHOL, GSE32225, and GSE26566. Differentially expressed genes between high- and low-infiltrated groups in TCGA dataset were yielded and further compressed in other two datasets through backward stepwise regression in R environment. Single-cell sequencing data of GSE138709 was loaded by Seurat software and was used to examined the expression of infiltration-related gene set. Pathway changes in malignant cell populations were analyzed through scTPA web tool.\nResults: There were 43 genes differentially expressed between high- and low-immune infiltrated patients, and after further compression, PNOC and LAIR2 were significantly correlated with high immune infiltration status in cholangiocarcinoma. Through analysis of single-cell sequencing data, PNOC was mainly expressed by infiltrated B cells in tumor microenvironment, while LAIR2 was expressed by Treg cells and partial GZMB+ CD8 T cells, which were survival related and increased in tumor tissues. High B cell infiltration levels were related to better overall survival. Also, malignant cell populations demonstrated functionally different roles in tumor progression.\nConclusion: PNOC and LAIR2 were biomarkers for immune infiltration evaluation in cholangiocarcinoma. PNOC, expressed by B cells, could predict better survival of patients, while LAIR2 was a potential marker for exhaustive T cell populations, correlating with worse survival of patients.", "claims": [{"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: CHOL and LIHC in TCGA database: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga: GSE32225: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32225, GSE26566: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26566, GSE138709: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33841428", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: CHOL and LIHC in TCGA database: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga: GSE32225: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32225, GSE26566: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26566, GSE138709: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33841428"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE138709"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE138709"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33841428", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2021.647209", "sha256": "sha256:5c2ae12f0390f6d8f6ebfee1ff09bad4275feacbee36552d8febea9fe1d7c6c9", "bytes": 50389, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2021.647209", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8024580", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE138709", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE138709", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: CHOL and LIHC in TCGA database: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga: GSE32225: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32225, GSE26566: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26566, GSE138709: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138709.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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