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Molecular prognostic index may predict survival in early-stage NSCLC
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A nine-gene molecular prognostic index provided accurate risk stratification and may be used to inform adjuvant therapy for patients with early-stage non–small cell lung cancer, according to the results of a retrospective analysis.
“We set out to develop a predictor that could identify which patients with early-stage NSCLC are at highest risk for dying of the disease,” Maximilian Diehn, MD, PhD, assistant professor of radiation oncology at Stanford University School of Medicine, told HemOnc Today. “Such a predictor could potentially help identify patients who would be most likely to benefit from adjuvant therapy after definitive local treatment. We also wanted our predictor to incorporate both gene expression and clinical risk factors in order to take advantage of both types of information.”
Diehn and colleagues designed a nine-gene molecular prognostic index (MPI), which they validated using gene expression profiles from a meta-cohort of 1,106 patients with stage 1 nonsquamous NSCLC. Researchers developed a prognostic score using the MPI and clinical variables from SEER data.
The analysis included training (n = 563) and validation (n = 543) sets balanced for clinical risk.
In the training set, researchers identified 1,012 genes that corresponded with survival (P < .01). Researchers focused on four cluster sets with the most significantly prognostic genes and included four adverse risk genes (MAD2L1, GINS1, SLC2A1 and KRT6A) and five genes associated with favorable outcomes (TNIK, BCAM, KDM6A, GCGRT and FA1M3) in the MPI.
The MPI appeared strongly associated with OS as a continuous score in the validation set. When researchers stratified patients based on high vs. low risk relative to the training cohort, MPI was significantly associated with OS in the validation cohort (HR = 2.42; 95% CI, 1.78-3.29). The prognostic ability of the MPI persisted when evaluating only patients with stage I nonsquamous NSCLC (HR = 2.28; 95% CI, 1.48-3.52), even within stage IA (HR = 2.99; 95% CI, 1.55-5.76).
Researchers also developed the MPI as a quantitative polymerase chain reaction (qPCR) assay that could be readily performed in clinical laboratories, which they validated in an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98).
Using high- and low-risk cutoff values defined in the microarray training set, the MPI qPCR stratified patients across stage I disease, including within stage IA (HR = 3.95; 95% CI, 1.24-12.64).
Prognostic genes expressed themselves in distinct tumor cell subpopulations. Genes implicated in proliferation and stem cells indicated poor outcomes, whereas genes associated with normal lung differentiation and immune infiltration predicted improved survival.
The greatest prognostic power occurred by integrating the MPI assay with clinical factors (HR = 3.43; 95% CI, 2.18-5.39 for stage I patients in the largest microarray cohort; HR = 3.99; 95% CI, 1.67-9.56 for stage I patients in the qPCR cohort).
Researchers noted the MPI conferred prognostic power irrespective of somatic alterations within EGFR, KRAS, TP53 and ALK genes.
The researchers acknowledged the relative heterogeneity of NSCLC tumors and the retrospective nature of the study as limitations of their findings.
“We have developed a clinically implementable assay that incorporates molecular information about the tumor and its microenvironment as well as clinical risk factors into a single risk score that robustly predicts outcome in early-stage NSCLC,” Diehn said. “Our results suggest that patients with high risk scores may benefit from the addition of adjuvant therapy. To prove this, a key next step will be performing a prospective trial that incorporates our risk score.” – by Cameron Kelsall
For more information:
Maximilian Diehn, MD, PhD, can be reached at Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305; email: diehn@stanford.edu.
Disclosure: Please see the full study for a list of all researchers’ relevant financial disclosures.
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