Study
Investigate the evolutionary trajectories during invasiveness acquisition in early lung adenocarcinoma
| Study ID | Alternative Stable ID | Type |
|---|---|---|
| EGAS00001004754 | Other |
Study Description
The evolutionary trajectories of early lung adenocarcinoma (LUAD) have not been fully elucidated. We hypothesize that genomic analysis between pre-invasive and invasive components will facilitate the description of LUAD evolutionary patterns. We micro-dissect malignant pulmonary nodules (MPNs) into paired pre-invasive and invasive components for panel-genomic sequencing and recognize three evolutionary trajectories. Evolutionary mode 1 (EM1) demonstrates none of the common driver events between paired components, but another two modes, EM2A and EM2B, exhibit critical private alterations restricted to pre-invasive and invasive components, respectively. When ancestral clones harbor EGFR mutations, truncal mutation abundance significantly decrease after the acquisition of invasiveness, which may be associated with the intratumoral accumulation of infiltrated B cells. Harboring EGFR mutations is critical to the selective pressure and further impacts the prognosis. Our findings extend the understanding of evolutionary trajectories during invasiveness acquisition in early LUAD.
Study Datasets 2 datasets.
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| Dataset ID | Description | Technology | Samples |
|---|---|---|---|
| EGAD00001006457 |
Genomic analysis between pre-invasive and invasive components of malignant pulmonary nodule (MPN) facilitates the description of lung adenocarcinoma (LUAD) evolutionary patterns. We conduct an analysis of gene-panel sequencing on 53 T1 stage LUAD cases, which extend the understanding of evolutionary trajectories during invasiveness acquisition in early LUAD.
|
174 | |
| EGAD00001007587 |
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 ... (Show More)
|
760 |
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