ArticleComputational and structural biotechnology journal2019
Radiogenomic Analysis of F-18-Fluorodeoxyglucose Positron Emission Tomography and Gene Expression Data Elucidates the Epidemiological Complexity of Colorectal Cancer Landscape.
Article in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.
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Who cites it
44 citing papers in PubMed, 2 syntheses or guidelines pooled it, 136 citations in OpenAlex.
- Insights into pet-based radiogenomics in oncology: an updated systematic review.European journal of nuclear medicine and molecular imaging · 2025Pooled it
- A novel meta-analysis based on data augmentation and elastic data shared lasso regularization for gene expression.BMC bioinformatics · 2022Pooled it
- Construction of a diagnostic model for colorectal cancer based on exosome-related genes: integration of immune cell differentials and molecular docking.Translational cancer research · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- T-cell receptor clonotypic diversity and specialization in digestive system cancers.NPJ precision oncology · 2026Article
- Mechanistic study of deoxycholic acid in colorectal cancer based on network toxicology and machine learning approaches.BMC pharmacology & toxicology · 2026Article
- Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.Human mutation · 2026Article
- Regulatory role of phosphatidylcholine metabolic reprogramming in colorectal cancer progression and neutrophil interactions.iScience · 2025Article
- Identification and modulation of a PI3K/AKT/mTOR pathway-targeting microRNA in order to increase colorectal cancer cells radiosensitivity in vitro.BMC cancer · 2025Article
- Circulating IL6 is involved in the infiltration of M2 macrophages and CD8+ T cells.Scientific reports · 2025Article
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- A Comprehensive Review: Versatile Imaging Probe Based on Chemical Materials for Biomedical Applications.Applied biochemistry and biotechnology · 2025Review
- BTBD19 promotes colorectal cancer progression and correlates with adverse clinical outcomes.Frontiers in oncology · 2025Article
- Machine Learning-Integrated Analysis of SULF1, CXCL8, and PBLD Expression as Discriminative Biomarkers for Early Detection and Prognosis in Colorectal Cancer.International journal of general medicine · 2025Article
- Integrative network analysis of transcriptomics data reveals potential prognostic biomarkers for colorectal cancer.Cancer medicine · 2024Article
- CEBPB-mediated upregulation of SERPINA1 promotes colorectal cancer progression by enhancing STAT3 signaling.Cell death discovery · 2024Article
- Identification and clinicopathological analysis of potential p73-regulated biomarkers in colorectal cancer via integrative bioinformatics.Scientific reports · 2024Article
- Sparassis latifolia and exercise training as complementary medicine mitigated the 5-fluorouracil potent side effects in mice with colorectal cancer: bioinformatics approaches, novel monitoring pathological metrics, screening signatures, and innovative management tactic.Cancer cell international · 2024Article
- Preclinical Repurposing of Sitagliptin as a Drug Candidate for Colorectal Cancer by TargetingInternational journal of molecular sciences · 2024Article
- Identification of Hub genes with prognostic values in colorectal cancer by integrated bioinformatics analysis.Cancer biomarkers : section A of Disease markers · 2024Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTranscriptomic profiling has enabled the neater genomic characterization of several cancers, among them colorectal cancer (CRC), through the derivation of genes with enhanced causal role and informative gene sets. However, the identification of small-sized gene signatures, which can serve as potential biomarkers in CRC, remains challenging, mainly due to the great genetic heterogeneity of the disease.
methodsWe developed and exploited an analytical framework for the integrative analysis of CRC datasets, encompassing transcriptomic data and positron emission tomography (PET) measurements. Profiling data comprised two microarray datasets, pertaining biopsy specimen from 30 untreated patients with primary CRC, coupled by their F-18-Fluorodeoxyglucose (FDG) PET values, using tracer kinetic analysis measurements. The computational framework incorporates algorithms for semantic processing, multivariate analysis, data mining and dimensionality reduction.
resultsTranscriptomic and PET data feature sets, were evaluated for their discrimination performance between primary colorectal adenocarcinomas and adjacent normal mucosa. A composite signature was derived, pertaining 12 features: 7 genes and 5 PET variables. This compact signature manifests superior performance in classification accuracy, through the integration of gene expression and PET data.
conclusionsThis work represents an effort for the integrative, multilayered, signature-oriented analysis of CRC, in the context of radio-genomics, inferring a composite signature with promising results for patient stratification.
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