SUPR
Deciphering of the molecular signatures of lung cancer to uncover promising therapeutic RNA candidates
Dnr:

sens2024639

Type:

NAISS SENS

Principal Investigator:

Per Hydbring

Affiliation:

Karolinska Institutet

Start Date:

2024-12-10

End Date:

2026-01-01

Primary Classification:

30599: Other Medical and Health Sciences not elsewhere specified

Allocation

Abstract

We are prospectively collecting NSCLC tumor tissue biopsies from patients treated in clinical routine at the Karolinska University Hospital (estimated inclusion n=100 NSCLC patients/year). In this project, detailed clinical data is correlated with molecular data derived from genomic and transcriptomic profiling. DNA analysis is performed by whole exome sequencing (WES). WES is conducted through NovaSeq paired end 150 sequencing with 12 G of raw data collected for each sample. RNA profiling is conducted through mRNA-seq and small RNA-seq at a sequencing depth of 50 million reads per sample. In this project, we have at this point systematically profiled 100 patients for WES, mRNA-seq and small RNA-seq. The project is ongoing with the aim to analyze the following group comparisons: early stage lung adenocarcinomas (LUAD) vs advanced stage LUAD (stage I-IIIA vs stage IIIB-IV), LUADs treated with immune checkpoint inhibitors vs others, LUADs treated with targeted therapies vs others, LUADs with genetic aberrations in KRAS vs KRAS wt, LUADs with genetic aberrations in EGFR vs EGFR wt, and LUADs with genetic aberrations in ALK vs ALK wt. We also aim to correlate the molecular profiles with response to different therapies, including TKIs and immune checkpoint inhibitors, to be able to identify biomarkers for treatment resistance. We hypothesize, based on previously published results from our research team, that NSCLC with oncogenic drivers will display a distinct RNA-landscape compared to NSCLC without any known oncogenic drivers. The genetic and transcriptomic profiling in Aim 1 will enable us to track the genomic evolution of LUADs as well as to uncover genetic and transcriptomic alterations associated with subgroups of LUADs to decipher both prognostic and predictive markers of LUAD.