Elucidating the Predictive Capacity of Gene Expression in Lung Carcinogenesis

Lung cancer remains the leading cause of cancer-related mortality globally, with the highest incidence rates reported worldwide. This pervasive disease is significantly influenced by factors such as smoking, air pollution, and occupational exposure, with varying incidence rates across different regions and demographics. Advances in genomic technology have ushered in a new era of high-throughput gene analysis, enhancing our understanding of lung cancer's molecular underpinnings. This study focuses on the gene expression profiles of 551 patients, employing techniques such as volcano plots and binary regression analysis to identify key genetic markers associated with lung cancer. Our findings highlight five critical genes: CLDN18, GKN2, LYVE-1, GPIHBP1, and CLIC5, which not only play significant roles in the early detection of lung cancer but also hold potential as targets for future therapeutic interventions. By leveraging gene expression for early screening, this research contributes to improving lung cancer prognosis and paves the way for developing targeted treatment strategies, thereby underscoring the importance of integrating molecular genetics into clinical practice for personalized medicine approaches in lung cancer management.

Authors

Institutions

Publication Details

Journal
Highlights in Science Engineering and Technology
Published
2024-12-24
DOI
https://doi.org/10.54097/d85nq124
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Elucidating the Predictive Capacity of Gene Expression in Lung Carcinogenesis

Xiu-Juan Yan
Highlights in Science Engineering and Technology
Gene expression and cancer classification
article

Elucidating the Predictive Capacity of Gene Expression in Lung Carcinogenesis

Xiu-Juan Yan
article en

Abstract

Lung cancer remains the leading cause of cancer-related mortality globally, with the highest incidence rates reported worldwide. This pervasive disease is significantly influenced by factors such as smoking, air pollution, and occupational exposure, with varying incidence rates across different regions and demographics. Advances in genomic technology have ushered in a new era of high-throughput gene analysis, enhancing our understanding of lung cancer's molecular underpinnings. This study focuses on the gene expression profiles of 551 patients, employing techniques such as volcano plots and binary regression analysis to identify key genetic markers associated with lung cancer. Our findings highlight five critical genes: CLDN18, GKN2, LYVE-1, GPIHBP1, and CLIC5, which not only play significant roles in the early detection of lung cancer but also hold potential as targets for future therapeutic interventions. By leveraging gene expression for early screening, this research contributes to improving lung cancer prognosis and paves the way for developing targeted treatment strategies, thereby underscoring the importance of integrating molecular genetics into clinical practice for personalized medicine approaches in lung cancer management.

Highlights in Science Engineering and TechnologyVol. 123
Nanjing University of Chinese Medicine (CN)
Good health and well-being
Openalex Percentile: Top 79%
Gene expression and cancer classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.