Identification of 15 lncRNAs Signature for Predicting Survival Benefit of Advanced Melanoma Patients Treated with Anti-PD-1 Monotherapy.


Journal

Cells
ISSN: 2073-4409
Titre abrégé: Cells
Pays: Switzerland
ID NLM: 101600052

Informations de publication

Date de publication:
22 04 2021
Historique:
received: 01 03 2021
revised: 14 04 2021
accepted: 17 04 2021
entrez: 30 4 2021
pubmed: 1 5 2021
medline: 9 11 2021
Statut: epublish

Résumé

The blockade of programmed cell death protein 1 (PD-1) as monotherapy has been widely used in melanoma, but to identify melanoma patients with survival benefit from anti-PD-1 monotherapy is still a big challenge. There is an urgent need for prognostic signatures improving the prediction of immunotherapy responses of these patients. We analyzed transcriptomic data of pre-treatment tumor biopsies and clinical profiles in advanced melanoma patients receiving only anti-PD-1 monotherapy (nivolumab or pembrolizumab) from the PRJNA356761 and PRJEB23709 data sets as the training and validation cohort, respectively. Weighted gene co-expression network analysis was used to identify the key module, then least absolute shrinkage and selection operator was conducted to determine prognostic-related long noncoding RNAs (lncRNAs). Subsequently, the differentially expressed genes between different clusters were identified, and their function and pathway annotation were performed. In this investigation, 92 melanoma patients with complete survival information (51 from training cohort and 41 from validation cohort) were included in our analyses. We initiallyidentified the key module (skyblue) by weighted gene co-expression network analysis, and then identified a 15 predictive lncRNAs (AC010904.2, LINC01126, AC012360.1, AC024933.1, AL442128.2, AC022211.4, AC022211.2, AC127496.5, NARF-AS1, AP000919.3, AP005329.2, AC023983.1, AC023983.2, AC139100.1, and AC012615.4) signature in melanoma patients treated with anti-PD-1 monotherapy by least absolute shrinkage and selection operator in the training cohort. These results were then validated in the validation cohort. Finally, enrichment analysis showed that the functions of differentially expressed genes between two consensus clusters were mainly related to the immune process and treatment. In summary, the 15 lncRNAs signature is a novel effective predictor for prognosis in advanced melanoma patients treated with anti-PD-1 monotherapy.

Identifiants

pubmed: 33922038
pii: cells10050977
doi: 10.3390/cells10050977
pmc: PMC8143567
pii:
doi:

Substances chimiques

Antibodies, Monoclonal, Humanized 0
Antineoplastic Agents, Immunological 0
Biomarkers, Tumor 0
PDCD1 protein, human 0
Programmed Cell Death 1 Receptor 0
RNA, Long Noncoding 0
pembrolizumab DPT0O3T46P

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Research Programs of Science and Technology Commission Foundation of Zunyi City
ID : HZ2019-11, HZ2019-07
Organisme : National Natural Science Foundation of China
ID : 81660512
Organisme : Research Programs of Health Commission Foundation of Guizhou Province
ID : gzwjkj2019-1-073, gzwjkj2019-1-172
Organisme : European Commission
ID : MSCA-ITN-ETN; HYPERBOOST; 955625

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Auteurs

Jian-Guo Zhou (JG)

Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China.
Department of Radiation Oncology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN, 91054 Erlangen, Germany.

Bo Liang (B)

Nanjing University of Chinese Medicine, Nanjing 210029, China.

Jian-Guo Liu (JG)

Special Key Laboratory of Oral Diseases Research, Stomatological Hospital Affiliated to Zunyi Medical University, Zunyi 563000, China.

Su-Han Jin (SH)

Special Key Laboratory of Oral Diseases Research, Stomatological Hospital Affiliated to Zunyi Medical University, Zunyi 563000, China.

Si-Si He (SS)

Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China.

Benjamin Frey (B)

Department of Radiation Oncology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN, 91054 Erlangen, Germany.

Ning Gu (N)

Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing 210029, China.

Rainer Fietkau (R)

Department of Radiation Oncology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN, 91054 Erlangen, Germany.

Markus Hecht (M)

Department of Radiation Oncology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN, 91054 Erlangen, Germany.

Hu Ma (H)

Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China.

Udo S Gaipl (US)

Department of Radiation Oncology, Universitätsklinikum Erlangen, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN, 91054 Erlangen, Germany.

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Classifications MeSH