Integrated pan-cancer gene expression and drug sensitivity analysis reveals SLFN11 mRNA as a solid tumor biomarker predictive of sensitivity to DNA-damaging chemotherapy.
Antineoplastic Agents
/ pharmacology
Biomarkers, Tumor
/ genetics
Cell Line, Tumor
DNA Damage
/ drug effects
Datasets as Topic
Drug Resistance, Neoplasm
/ genetics
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Neoplasms
/ drug therapy
Nuclear Proteins
/ genetics
Precision Medicine
/ methods
Predictive Value of Tests
Prognosis
Progression-Free Survival
RNA, Messenger
/ metabolism
Survival Analysis
Time Factors
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2019
2019
Historique:
received:
30
06
2019
accepted:
09
10
2019
entrez:
5
11
2019
pubmed:
5
11
2019
medline:
3
4
2020
Statut:
epublish
Résumé
Precision oncology seeks to integrate multiple layers of data from a patient's cancer to effectively tailor therapy. Conventional chemotherapies are sometimes effective but accompanied by adverse events, warranting the identification of a biomarker of chemosensitivity. Identify an mRNA biomarker that predicts chemosensitivity across solid tumor subtypes. We performed a pan-solid tumor analysis integrating gene expression and drug sensitivity profiles from 3 cancer cell line datasets to identify transcripts correlated with sensitivity to a panel of chemotherapeutics. We then tested the ability of an mRNA biomarker to predictive clinical outcomes in cohorts of patients with breast, lung, or ovarian cancer. Expression levels of several mRNA transcripts were significantly correlated with sensitivity or resistance chemotherapeutics in cancer cell line datasets. The only mRNA transcript significantly correlated with sensitization to multiple classes of DNA-damaging chemotherapeutics in all 3 cell line datasets was encoded by Schlafen Family Member 11 (SLFN11). Analyses of multiple breast, lung, and ovarian cancer patient cohorts treated with chemotherapy confirmed SLFN11 mRNA expression as a predictive biomarker of longer overall survival and improved tumor response. Tumor SLFN11 mRNA expression is a biomarker of sensitivity to an array of DNA-damaging chemotherapeutics across solid tumor subtypes.
Sections du résumé
BACKGROUND
Precision oncology seeks to integrate multiple layers of data from a patient's cancer to effectively tailor therapy. Conventional chemotherapies are sometimes effective but accompanied by adverse events, warranting the identification of a biomarker of chemosensitivity.
OBJECTIVE
Identify an mRNA biomarker that predicts chemosensitivity across solid tumor subtypes.
METHODS
We performed a pan-solid tumor analysis integrating gene expression and drug sensitivity profiles from 3 cancer cell line datasets to identify transcripts correlated with sensitivity to a panel of chemotherapeutics. We then tested the ability of an mRNA biomarker to predictive clinical outcomes in cohorts of patients with breast, lung, or ovarian cancer.
RESULTS
Expression levels of several mRNA transcripts were significantly correlated with sensitivity or resistance chemotherapeutics in cancer cell line datasets. The only mRNA transcript significantly correlated with sensitization to multiple classes of DNA-damaging chemotherapeutics in all 3 cell line datasets was encoded by Schlafen Family Member 11 (SLFN11). Analyses of multiple breast, lung, and ovarian cancer patient cohorts treated with chemotherapy confirmed SLFN11 mRNA expression as a predictive biomarker of longer overall survival and improved tumor response.
CONCLUSIONS
Tumor SLFN11 mRNA expression is a biomarker of sensitivity to an array of DNA-damaging chemotherapeutics across solid tumor subtypes.
Identifiants
pubmed: 31682620
doi: 10.1371/journal.pone.0224267
pii: PONE-D-19-18449
pmc: PMC6827986
doi:
Substances chimiques
Antineoplastic Agents
0
Biomarkers, Tumor
0
Nuclear Proteins
0
RNA, Messenger
0
SLFN11 protein, human
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0224267Subventions
Organisme : NCI NIH HHS
ID : F30 CA216966
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA023108
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA200994
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA211869
Pays : United States
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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