Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma.

doi:10.1016/j.ebiom.2024.105048

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Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma.

EBioMedicine - 1 Apr 2024

Patiño-García Ana, Guruceaga Elizabeth, Andueza Maria Pilar, Ocón Marimar, Fodop Sokoudjou Jafait Junior, de Villalonga Zornoza Nicolás, Alkorta-Aranburu Gorka, Uria Ibon Tamayo, Gurpide Alfonso, Camps Carlos, Jantus-Lewintre Eloísa, Navamuel-Andueza Maria, Sanmamed Miguel F, Melero Ignacio, Elgendy Mohamed, Fusco Juan Pablo, Zulueta Javier J, de-Torres Juan P, Bastarrika Gorka, Seijo Luis, Pio Ruben, Montuenga Luis M, Hernáez Mikel, Ochoa Idoia, Perez-Gracia Jose Luis

Abstract excerpt

BACKGROUND: Tobacco is the main risk factor for developing lung cancer. Yet, while some heavy smokers develop lung cancer at a young age, other heavy smokers never develop it, even at an advanced age, suggesting a remarkable variability in the individual susceptibility to the carcinogenic effects of tobacco. We characterized the germline profile of subjects presenting these extreme phenotypes with Whole Exome...

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Whole exome sequencing and machine learning germline analysis of individuals presenting with extreme phenotypes of high and low risk of developing tobacco-associated lung adenocarcinoma.

Abstract excerpt

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