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pmid:37063853

An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma.

Xiaochuan Chen · Qin Ding · Ting Lin · Yingming Sun · Zongwei Huang · Ying Li · Wenquan Hong · Xin Chen · Desheng Wang · Sufang Qiu

Frontiers in immunology · 2023 doi:10.3389/fimmu.2023.1109503

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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title
An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma.
doi
10.3389/fimmu.2023.1109503
pmid
37063853
authors array · 10 items
[0]
Xiaochuan Chen
[1]
Qin Ding
[2]
Ting Lin
[3]
Yingming Sun
[4]
Zongwei Huang
[5]
Ying Li
[6]
Wenquan Hong
[7]
Xin Chen
[8]
Desheng Wang
[9]
Sufang Qiu
journal
Frontiers in immunology
year
2023
abstract
Background: The prognosis of nasopharyngeal carcinoma (NPC) has been recognized to improve immensely owing to radiotherapy combined with chemotherapy. However, patients with metastatic NPC have a poor prognosis. Immunotherapy has dramatically prolonged the survival of patients with NPC. Hence, further research on immune-related biomarkers is imperative to establish the prognosis of metastatic NPC. Methods: 10 NPC RNA expression profiles were generated from patients with or without distant metastasis after chemoradiotherapy from the Fujian Cancer Hospital. The differential immune-related genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88). The immune microenvironment and signal pathways were evaluated in multiple dimensions at the transcriptome and single-cell levels. Results: 1328 differential genes were identified, out of which 520 were upregulated and 808 were downregulated. Notably, most of the immune genes and pathways were down-regulated in the metastasis group. A prognostic immune model involving nine hub genes. Patients in low-risk group were characterized by survival advantage, hot immune phenotype and benefit from immunotherapy. Compared with immune cells, malignant cell exhibited the most active levels of risk score by ssGSEA. Accordingly, intercellular communications including LT, CD70, CD40 and SPP1, and the like, between high-risk and low-risk were explored by the R package "Cellchat". Conclusion: We have constructed a model based on immunity of metastatic NPC and determined its prognostic value. The model identified the level of immune cell infiltration, cell-cell communication, along with potential immunotherapy for metastatic NPC.
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Genomic Analysis of Nasopharyngeal Carcinoma Reveals TME-based Subtypes
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Single-cell transcriptomics reveals regulators underlying immune cell diversity and immune subtypes associated with prognosis in nasopharyngeal carcinoma
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lated genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrin
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hospital in 2021 and 2022 were used for the immunohistochemistry to validate CD8 T cell infiltration and immu
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were evaluated in multiple dimensions at the transcriptome and single-cell levels. Results: 1328 differ
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37063853", "kind": "science-record", "revision": 3, "content_hash": "sha256:ca8af5cc920a1c1839b6f3a7755933383658aaa05b6af75359bf75b3555f9e93", "created_at": "2026-11-01T19:01:43Z", "updated_at": "2026-11-01T22:09:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma.", "doi": "10.3389/fimmu.2023.1109503", "pmid": "37063853", "authors": ["Xiaochuan Chen", "Qin Ding", "Ting Lin", "Yingming Sun", "Zongwei Huang", "Ying Li", "Wenquan Hong", "Xin Chen", "Desheng Wang", "Sufang Qiu"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Background: The prognosis of nasopharyngeal carcinoma (NPC) has been recognized to improve immensely owing to radiotherapy combined with chemotherapy. However, patients with metastatic NPC have a poor prognosis. Immunotherapy has dramatically prolonged the survival of patients with NPC. Hence, further research on immune-related biomarkers is imperative to establish the prognosis of metastatic NPC.\nMethods: 10 NPC RNA expression profiles were generated from patients with or without distant metastasis after chemoradiotherapy from the Fujian Cancer Hospital. The differential immune-related genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88). The immune microenvironment and signal pathways were evaluated in multiple dimensions at the transcriptome and single-cell levels.\nResults: 1328 differential genes were identified, out of which 520 were upregulated and 808 were downregulated. Notably, most of the immune genes and pathways were down-regulated in the metastasis group. A prognostic immune model involving nine hub genes. Patients in low-risk group were characterized by survival advantage, hot immune phenotype and benefit from immunotherapy. Compared with immune cells, malignant cell exhibited the most active levels of risk score by ssGSEA. Accordingly, intercellular communications including LT, CD70, CD40 and SPP1, and the like, between high-risk and low-risk were explored by the R package \"Cellchat\".\nConclusion: We have constructed a model based on immunity of metastatic NPC and determined its prognostic value. The model identified the level of immune cell infiltration, cell-cell communication, along with potential immunotherapy for metastatic NPC.", "claims": [{"id": "claim-method", "statement": "Progression-free survival (PFS) was subjected to minimum absolute shrinkage and selection operator (LASSO) Cox regression with 10-fold cross-validation to screen for DEGs with prognostic value on the basis of the univariate Cox analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37063853", "locator": "sections[5] \"Construction and validation of immune-related prognostic model\" paragraph 2", "quote": "Progression-free survival (PFS) was subjected to minimum absolute shrinkage and selection operator (LASSO) Cox regression with 10-fold cross-validation to screen for DEGs with prognostic value on the basis of the univariate Cox analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37063853", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37063853", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88).", "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:37063853"], "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:GSE102349"], "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:GSE102349"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37063853", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2023.1109503", "sha256": "sha256:8e2d9dead8034c22bb8c05b35835aabf875ed870e357b0cc8a2ca5ea13e47140", "bytes": 51273, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2023.1109503", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10102363", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE102349", "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=GSE102349", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE102349", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. 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The method of least absolute shrin", "hospital in 2021 and 2022 were used for the immunohistochemistry to validate CD8 T cell infiltration and immu"], "order_basis": "paper_text_order:704", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["were evaluated in multiple dimensions at the transcriptome and single-cell levels. Results: 1328 differ", "treatment. As an external validation cohort, RNA-seq data of NPC from the GEO database (https://w", "volution algorithms (CIBERSORTx) to the bulk transcriptome data to quantitatively estimate cell-type pr"], "order_basis": "paper_text_order:1010", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Progression-free survival (PFS) was subjected to minimum absolute shrinkage and selection operator (LASSO) Cox regression with 10-fold cross-validation to screen for DEGs with prognostic value on the basis of the univariate Cox analysis."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}