Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. Issue 1 (December 2016)
- Record Type:
- Journal Article
- Title:
- Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. Issue 1 (December 2016)
- Main Title:
- Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set
- Authors:
- Roszik, Jason
Haydu, Lauren
Hess, Kenneth
Oba, Junna
Joon, Aron
Siroy, Alan
Karpinets, Tatiana
Stingo, Francesco
Baladandayuthapani, Veera
Tetzlaff, Michael
Wargo, Jennifer
Chen, Ken
Forget, Marie-Andrée
Haymaker, Cara
Chen, Jie
Meric-Bernstam, Funda
Eterovic, Agda
Shaw, Kenna
Mills, Gordon
Gershenwald, Jeffrey
Radvanyi, Laszlo
Hwu, Patrick
Futreal, P.
Gibbons, Don
Lazar, Alexander
Bernatchez, Chantale
Davies, Michael
Woodman, Scott - Abstract:
- Abstract Background While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements. Methods We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan–Meier method. Results PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R2 = 0.73 and R2 = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rankP value < 0.05 in all cohorts). Conclusions The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer.
- Is Part Of:
- BMC medicine. Volume 14:Issue 1(2016)
- Journal:
- BMC medicine
- Issue:
- Volume 14:Issue 1(2016)
- Issue Display:
- Volume 14, Issue 1 (2016)
- Year:
- 2016
- Volume:
- 14
- Issue:
- 1
- Issue Sort Value:
- 2016-0014-0001-0000
- Page Start:
- 1
- Page End:
- 8
- Publication Date:
- 2016-12
- Subjects:
- Melanoma -- Lung cancer -- Total mutation load -- CTLA-4 -- PD-1 -- Immunotherapy
Medicine -- Periodicals
610.5 - Journal URLs:
- http://www.biomedcentral.com/bmcmed/ ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=216 ↗
http://link.springer.com/ ↗ - DOI:
- 10.1186/s12916-016-0705-4 ↗
- Languages:
- English
- ISSNs:
- 1741-7015
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 9959.xml