ArticleBiology2022
Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.
Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 10 citations in OpenAlex.
- From COPD and asthma to lung cancer: potential candidate genes and their associated biological pathways for the incidence risk of lung cancer.Journal, genetic engineering & biotechnology · 2026Article
- SLPI⁺ AT2-Like Cells Orchestrate Lung Adenocarcinoma Invasion via Wnt Pathway Activation and Stromal Crosstalk in a Spatially Defined Margin Niche.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Long Non-Coding RNA DUXAP10 Promotes Tumorigenesis and Metastasis in Anaplastic Thyroid Cancer.Cancers · 2025Article
- Chloroplast Functionality at the Interface of Growth, Defense, and Genetic Innovation: A Multi-Omics and Technological Perspective.Plants (Basel, Switzerland) · 2025Review
- Global transcriptomic network analysis of the crosstalk between microbiota and cancer-related cells in the oral-gut-lung axis.Frontiers in cellular and infection microbiology · 2024Article
- Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis.International journal of molecular sciences · 2023Review
- Preliminary results from the EMoLung clinical study showing early lung cancer detection by the LC score.Discover oncology · 2023Article
- Article
- LC-MS/MS Based Volatile Organic Compound Biomarkers Analysis for Early Detection of Lung Cancer.Cancers · 2023Article
- Lung Cancer Gene Regulatory Network of Transcription Factors Related to the Hallmarks of Cancer.Current issues in molecular biology · 2023Article
- Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells.Biomedicines · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID's tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan-Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.