Your browser doesn't support javascript.
loading
Use of comprehensive genomic profiling for biomarker discovery for the management of non-small cell lung cancer brain metastases.
Abdulhaleem, Mohammed; Hunting, John C; Wang, Yuezhu; Smith, Margaret R; Agostino, Ralph D' Jr; Lycan, Thomas; Farris, Michael K; Ververs, James; Lo, Hui-Wen; Watabe, Kounosuke; Topaloglu, Umit; Li, Wencheng; Whitlow, Christopher; Su, Jing; Wang, Ge; Chan, Michael D; Xing, Fei; Ruiz, Jimmy.
Affiliation
  • Abdulhaleem M; Department of Internal Medicine (Hematology & Oncology), Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Hunting JC; Department of Internal Medicine (Hematology & Oncology), Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Wang Y; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Smith MR; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Agostino RJ; Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Lycan T; Department of Internal Medicine (Hematology & Oncology), Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Farris MK; Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Ververs J; Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Lo HW; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Watabe K; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Topaloglu U; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Li W; Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Whitlow C; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Su J; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.
  • Wang G; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States.
  • Chan MD; Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Xing F; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States.
  • Ruiz J; Department of Internal Medicine (Hematology & Oncology), Wake Forest School of Medicine, Winston-Salem, NC, United States.
Front Oncol ; 13: 1214126, 2023.
Article in En | MEDLINE | ID: mdl-38023147
ABSTRACT

Background:

Clinical biomarkers for brain metastases remain elusive. Increased availability of genomic profiling has brought discovery of these biomarkers to the forefront of research interests.

Method:

In this single institution retrospective series, 130 patients presenting with brain metastasis secondary to Non-Small Cell Lung Cancer (NSCLC) underwent comprehensive genomic profiling conducted using next generation circulating tumor deoxyribonucleic acid (DNA) (Guardant Health, Redwood City, CA). A total of 77 genetic mutation identified and correlated with nine clinical outcomes using appropriate statistical tests (general linear models, Mantel-Haenzel Chi Square test, and Cox proportional hazard regression models). For each outcome, a genetic signature composite score was created by summing the total genes wherein genes predictive of a clinically unfavorable outcome assigned a positive score, and genes with favorable clinical outcome assigned negative score.

Results:

Seventy-two genes appeared in at least one gene signature including 14 genes had only unfavorable associations, 36 genes had only favorable associations, and 22 genes had mixed effects. Statistically significant associated signatures were found for the clinical endpoints of brain metastasis velocity, time to distant brain failure, lowest radiosurgery dose, extent of extracranial metastatic disease, concurrent diagnosis of brain metastasis and NSCLC, number of brain metastases at diagnosis as well as distant brain failure. Some genes were solely associated with multiple favorable or unfavorable outcomes.

Conclusion:

Genetic signatures were derived that showed strong associations with different clinical outcomes in NSCLC brain metastases patients. While these data remain to be validated, they may have prognostic and/or therapeutic impact in the future. Statement of translation relevance Using Liquid biopsy in NSCLC brain metastases patients, the genetic signatures identified in this series are associated with multiple clinical outcomes particularly these ones that lead to early or more numerous metastases. These findings can be reverse-translated in laboratory studies to determine if they are part of the genetic pathway leading to brain metastasis formation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Oncol Year: 2023 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Oncol Year: 2023 Document type: Article Affiliation country: