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While next-generation sequencing (NGS) is used to guide therapy in patients with metastatic lung adenocarcinoma (LUAD), use of NGS to determine pathologic LN metastasis prior to surgery has not been assessed. To bridge this knowledge gap, we performed NGS using MSK-IMPACT in 426 treatment-naive patients with clinical N2-negative LUAD. A multivariable logistic regression model that considered preoperative clinical and genomic variables was constructed. Most patients had cN0 disease (85%) with pN0, pN1, and pN2 rates of 80%, 11%, and 9%, respectively. Genes altered at higher rates in pN-positive than in pN-negative tumors were  STK11  ( p  = 0.024),  SMARCA4  ( p  = 0.006), and  SMAD4  ( p  = 0.011). Fraction of genome altered ( p  = 0.037), copy number amplifications ( p  = 0.001), and whole-genome doubling ( p  = 0.028) were higher in pN-positive tumors. Multivariable analysis revealed solid tumor morphology, tumor SUVmax, clinical stage,  SMARCA4  and  SMAD4  alterations were independently associated with pathologic LN metastasis. Incorporation of clinical and tumor genomic features can identify patients at risk of pathologic LN metastasis; this may guide therapy decisions before surgical resection.

Preoperative clinical and tumor genomic features associated with pathologic lymph node metastasis in clinical stage I and II lung adenocarcinoma