ArticleFrontiers in genetics2019
Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Antitumor Effects of Apatinib on Tongue Cancer in Patient-Derived Xenograft Models.Iranian journal of medical sciences · 2026Article
- Long non-coding RNA MIR4435-2HG promotes pancreatic cancer progression by regulating ABHD17C through sponging miR-128-3p.Translational cancer research · 2024Article
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- Development and characterization of a patient‑derived orthotopic xenograft of therapy‑resistant breast cancer.Oncology reports · 2023Article
- Rat Mammary carcinoma susceptibility 3 (Mcs3) pleiotropy, socioenvironmental interaction, and comparative genomics with orthologous human 15q25.1-25.2.G3 (Bethesda, Md.) · 2023Article
- Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.European radiology · 2020Article
- Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies.Frontiers in physiology · 2020Article
- The Methylation Pattern for Knee and Hip Osteoarthritis.Frontiers in cell and developmental biology · 2020Article
- The Functional Effects of Key Driver KRAS Mutations on Gene Expression in Lung Cancer.Frontiers in genetics · 2020Article
- The Serum MicroRNA Signatures for Pancreatic Cancer Detection and Operability Evaluation.Frontiers in bioengineering and biotechnology · 2020Article
- Identifying Methylation Pattern and Genes Associated with Breast Cancer Subtypes.International journal of molecular sciences · 2019Article
- Identifying Microbiota Signature and Functional Rules Associated With Bacterial Subtypes in Human Intestine.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example,
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