Lung Cancer Research Studies

The paper introduces GPAS to analyze gene co-expression modules in NSCLC, identifying lineage plasticity and aggressiveness patterns across different cancer subtypes.

The paper identifies ATOH1 as a pro-metastatic oncogenic driver in SCLC by showing its role in cell survival and metastasis suppression upon depletion.

This study identifies three distinct DDR phenotypes in SCLC associated with chemotherapy response and tumor evolution.

This study identifies KSR1 as a critical regulator of SCLC tumor initiation and cisplatin resistance, showing that its disruption enhances cisplatin toxicity and reduces tumor-initiating cells.

The paper compares transcriptomic and proteomic expression between two NSCLC subtypes to identify potential therapeutic targets and biomarkers.

The paper identifies EZH2 and SOX2 as key genes in LUAD through differential expression analysis and pathway enrichment, suggesting EZH2 as a potential therapeutic target.

This study identifies a prognostic signature involving p16INK4a and related genes in NSCLC, highlighting their potential as diagnostic and therapeutic biomarkers.

This study compares the patho-transcriptomic profiles of invasive mucinous adenocarcinoma (IMA) and adenocarcinoma with signet ring cell features (SRCC), identifying distinct and shared gene expression patterns and potential therapeutic targets.

This study maps the SCLC tumor microenvironment and identifies cancer-associated fibroblasts as key drivers of neuroendocrine state plasticity and poor prognosis.

The paper establishes a database of lung cancer mouse models to improve data comparison and translational relevance by aligning mouse mutations with human lung cancer mutations.

The paper analyzes the structure of SCLC transcription factor networks to identify subtype regulators and transition pathways using graph theory and RNA-seq data.

The paper identifies two LUAD clusters based on Anoikis-related genes, establishes a prognostic risk score, and shows its association with immune status and clinical outcomes using single-cell data.

The paper introduces XTABLE, an open-source tool for analyzing PML transcriptomic data, and uses it to study chromosomal instability as a biomarker for LUSC progression and pathway onset.

This study identifies a 25-gene minimal common region on 3q amplified in 44% of LUSC cases, associated with improved disease-specific survival and progression-free interval.

This study investigates RAD51 expression in non-small cell lung cancer using bioinformatics tools and finds it is highly expressed and associated with poor prognosis.

This study compares neuroendocrine (NE) features in SCLC and NBL, finding similar molecular profiles and shared therapeutic responses but no significant survival association with NE scores.

This study investigates LRFN4 expression and its association with immunity and prognosis in lung adenocarcinoma using bioinformatics analysis and experimental validation.

The paper identifies two understudied selectively essential genes, C11orf53 and COLCA2, as novel transcriptional co-activators in tuft cell-like SCLC, validated through computational ranking and experimental analysis.

This study shows SCLC cells exist in a continuum of plastic states rather than discrete subtypes, with gene expression patterns linked to cancer hallmarks and potential therapeutic targets.

The paper identifies an epigenomic subtype of SCLC-A defined by NKX2-1 and SOX1 super-enhancers and their functional collaboration.

The paper identifies prognostic gene signatures and genomic differences between high-risk and low-risk groups in lung adenocarcinoma and squamous cell carcinoma using TCGA data.

This study performs a meta-analysis of transcriptomic data to identify sex-based differences in functional signatures of non-small-cell lung cancer, finding enrichment in immune response and purinergic signaling in females.

This study examines genomic and TCR repertoire heterogeneity in SCLC, finding that lower TCR heterogeneity and mutational burden correlate with better survival.

The paper identifies AKR1B10 as a gene linked to smoking and lung cancer using transcriptomic data from six studies.

The paper identifies four SCLC subtypes using a systems approach, with NEv2 being a new subtype, and finds master regulators and destabilizers using BooleaBayes.

The paper identifies a conserved gene expression signature linking airway injury and lung cancer using microarray analysis of murine and human samples.