ArticlePloS one2011
Transcriptome profiling of whole blood cells identifies PLEK2 and C1QB in human melanoma.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 51 citations in OpenAlex.
- Whole-blood RNA transcript-based models can predict clinical response in two large independent clinical studies of patients with advanced melanoma treated with the checkpoint inhibitor, tremelimumab.Journal for immunotherapy of cancer · 2017Trial
- A promising frontier of circulating messenger RNA in liquid biopsy: From mechanisms to clinical applications.International journal of cancer · 2025Review
- An attention-based mRNA transformer network for accurate prediction of melanoma response to immune checkpoint inhibitors.Scientific reports · 2025Article
- PLEK2 promotes migration and invasion in pancreatic ductal adenocarcinoma by MMP1 through IL-17 pathway.Molecular and cellular biochemistry · 2025Article
- PLEK2: a potential biomarker for metastasis and prognostic evaluation in uveal melanoma.Frontiers in medicine · 2024Article
- 5-mRNA-based prognostic signature of survival in lung adenocarcinoma.World journal of clinical oncology · 2023Article
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- Antimelanoma Effects of Concomitant Inhibition of SIRT1 and SIRT3 in BrafThe Journal of investigative dermatology · 2022Article
- Prognostic and immune-related value of complement C1Q (C1QA, C1QB, and C1QC) in skin cutaneous melanoma.Frontiers in genetics · 2022Article
- Analyzing Prognostic Hub Genes in the Microenvironment of Cutaneous Melanoma by Computer Integrated Bioinformatics.Computational intelligence and neuroscience · 2022Article
- IRF4-activated TEX41 promotes the malignant behaviors of melanoma cells by targeting miR-103a-3p/C1QB axis.BMC cancer · 2021Article
- Pleckstrin 2 is a potential drug target for colorectal carcinoma with activation of APC/β‑catenin.Molecular medicine reports · 2021Article
- TGF-β-induced PLEK2 promotes metastasis and chemoresistance in oesophageal squamous cell carcinoma by regulating LCN2.Cell death & disease · 2021Article
- Identification of TYROBP and FCER1G as Key Genes with Prognostic Value in Clear Cell Renal Cell Carcinoma by Bioinformatics Analysis.Biochemical genetics · 2021Article
- Eight-year longitudinal study of whole blood gene expression profiles in individuals undergoing long-term medical follow-up.Scientific reports · 2021Article
- PLEK2 promotes osteosarcoma tumorigenesis and metastasis by activating the PI3K/AKT signaling pathway.Oncology letters · 2021Article
- Pancreatic cancer is marked by complement-high blood monocytes and tumor-associated macrophages.Life science alliance · 2021Article
- Pleckstrin-2 as a Prognostic Factor and Mediator of Gastric Cancer Progression.Gastroenterology research and practice · 2021Article
- Identification of Hub Genes to Regulate Breast Cancer Spinal Metastases by Bioinformatics Analyses.Computational and mathematical methods in medicine · 2021Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundDeveloping analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells. METHODOLOGY/PRINCIPAL
findingsWe conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively. CONCLUSIONS/SIGNIFICANCE: The current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease.
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