Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.EGA study EGAS00001005242