TY - JOUR
T1 - Prognostic Indicators for Precision Treatment of Non-Small Cell Lung Carcinoma
AU - Ghosh, Damayanti Das
AU - McDonald, Hannah
AU - Dutta, Rajeswari
AU - Krishnan, Keerthana
AU - Thilakan, Jaya
AU - Paul, Manash K.
AU - Arya, Neha
AU - Rao, Mahadev
AU - Rangnekar, Vivek M.
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/11
Y1 - 2024/11
N2 - Non-small cell lung cancer (NSCLC) has established predictive biomarkers that enable decisions on treatment regimens for many patients. However, resistance to therapy is widespread. It is therefore essential to have a panel of molecular biomarkers that may help overcome therapy resistance and prevent adverse effects of treatment. We performed in silico analysis of NSCLC prognostic indicators, separately for adenocarcinomas and squamous carcinomas, by using The Cancer Genome Atlas (TCGA) and non-TCGA data sources in cBioPortal as well as UALCAN. This review describes lung cancer biology, elaborating on the key genetic alterations and specific genes responsible for resistance to conventional treatments. Importantly, we examined the mechanisms associated with resistance to immune checkpoint inhibitors. Our analysis indicated that a robust prognostic biomarker was lacking for NSCLC, especially for squamous cell carcinomas. In this work, our screening uncovered previously unidentified prognostic gene expression indicators, namely, MYO1E, FAM83 homologs, and DKK1 for adenocarcinoma, and FGA and TRIB1 for squamous cell carcinoma. It was further observed that overexpression of these genes was associated with poor prognosis. Additionally, FAM83 homolog and TRIB1 unexpectedly harbored copy number amplifications. In conclusion, this study elucidated novel prognostic indicators for NSCLC that may serve as targets to overcome therapy resistance toward improved patient outcomes.
AB - Non-small cell lung cancer (NSCLC) has established predictive biomarkers that enable decisions on treatment regimens for many patients. However, resistance to therapy is widespread. It is therefore essential to have a panel of molecular biomarkers that may help overcome therapy resistance and prevent adverse effects of treatment. We performed in silico analysis of NSCLC prognostic indicators, separately for adenocarcinomas and squamous carcinomas, by using The Cancer Genome Atlas (TCGA) and non-TCGA data sources in cBioPortal as well as UALCAN. This review describes lung cancer biology, elaborating on the key genetic alterations and specific genes responsible for resistance to conventional treatments. Importantly, we examined the mechanisms associated with resistance to immune checkpoint inhibitors. Our analysis indicated that a robust prognostic biomarker was lacking for NSCLC, especially for squamous cell carcinomas. In this work, our screening uncovered previously unidentified prognostic gene expression indicators, namely, MYO1E, FAM83 homologs, and DKK1 for adenocarcinoma, and FGA and TRIB1 for squamous cell carcinoma. It was further observed that overexpression of these genes was associated with poor prognosis. Additionally, FAM83 homolog and TRIB1 unexpectedly harbored copy number amplifications. In conclusion, this study elucidated novel prognostic indicators for NSCLC that may serve as targets to overcome therapy resistance toward improved patient outcomes.
KW - lung cancer
KW - precision medicine
KW - prognostic marker
KW - therapy resistance
UR - http://www.scopus.com/inward/record.url?scp=85208493445&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85208493445&partnerID=8YFLogxK
U2 - 10.3390/cells13211785
DO - 10.3390/cells13211785
M3 - Review article
C2 - 39513892
AN - SCOPUS:85208493445
VL - 13
JO - Cells
JF - Cells
IS - 21
M1 - 1785
ER -
