Tumor Genomics and Their Application in Early-Stage Lung Cancer

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Despite complete surgical resection of stage I, II, or III non-small cell lung cancer (NSCLC), the disease will eventually recur in up to 49 percent of patients.1 After recurrence, survival is poor, with five-year rates as low as 30 percent.1 The current rationale for recommending adjuvant therapy relies solely on TNM (tumor, node, and metastasis) classification and is agnostic to clinicopathologic and tumor genomic factors. As a result, the survival benefits are modest at best when using the TNM model to select patients for adjuvant therapy. With the recent explosion of next-generation sequencing and robust genomic data, our lab is rigorously investigating associations between tumor genomics and recurrence and disease-free survival (DFS) in people with early-stage lung adenocarcinoma (LUAD). In addition to a gene-centric approach, we are performing specific pathway analyses2 to ascertain if these analyses can supplement existing TNM indicators for prognosis and prediction of recurrence, as well as begin to explore the organotropism of lung cancer metastases. We have also focused on the prognostic abilities of tumor mutation burden as well as the fraction of genome altered — another genomic biomarker; it measures the percentage of the genome affected by gains or losses in the copy number — and their association with recurrence. We were the first to use OncoCast,3 a novel computational machine-learning model that integrates genomic and clinicopathologic factors, to predict DFS in our MSK LUAD cohort (see figures below). We believe that continued investigation of tumor genomics in early-stage lung cancer has the possibility of moving the field toward use of this information to guide therapeutic decisions. We actively collaborate with the Marie-Josée and Henry R. Kravis Center for Molecular Oncology at MSK, as well use MSK OncoKB, MSK-IMPACT™, and related bioinformatics platforms.

  1. Brandt WS, Bouabdallah I, Tan KS, et al. Factors associated with distant recurrence following R0 lobectomy for pN0 lung adenocarcinoma. J Thorac Cardiovasc Surg. 2018 Mar; 155(3): 1212–1224.e3.

  2. Sanchez-Vega F, Mina M, Armenia J, et al. Oncogenic signaling pathways in The Cancer Genome Atlas. Cell. 2018 Apr 5;173(2):321-337.e10.

  3. Shen R, Martin A, Ni A, et al. Harnessing clinical sequencing data for survival stratification of patients with metastatic lung adenocarcinomas. JCO Precision Oncology. Published online March 28, 2019. doi: 10.1200/PO.18.00307.

tumor genomics models

Figure A: The percentage of alteration in the most frequently altered genes, grouped by biological relevance, comparing primary tumors from stages I through III to stage IV lung adenocarcinoma (LUAD). Figure B: The OncoCast predictive model for disease-free survival for a specific scenario: a 58-year-old patient with a two centimeter LUAD tumor with an SUVmax of 12. Following lobectomy and lymph node dissection, pathology revealed a pT1bN0M0 solid histologic subtype with lymphovascular invasion. Genomic analysis showed a tumor mutation burden of 6.5 and TP53 and SMARCA4 mutations (OncoCast, blue line). The comparison is to all pT1bN0M0 patients in the stage I through III cohort (n=136) (TNM, red line).