Search our Database of Scientific Publications and Authors

I’m looking for a
    Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets.
    Cancer Cell 2017 Aug;32(2):238-252.e9
    Department of Neurosurgery, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, the Netherlands; Brain Tumor Center Amsterdam, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, the Netherlands; Department of Neurology, Massachusetts General Hospital and Neuroscience Program, Harvard Medical School, 149 13(th) Street, Charlestown, MA 02129, USA. Electronic address:
    Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable efficient selection of RNA biomarker panels from platelet RNA-sequencing libraries (n = 779). This resulted in accurate TEP-based detection of early- and late-stage non-small-cell lung cancer (n = 518 late-stage validation cohort, accuracy, 88%; AUC, 0.94; 95% CI, 0.92-0.96; p < 0.001; n = 106 early-stage validation cohort, accuracy, 81%; AUC, 0.89; 95% CI, 0.83-0.95; p < 0.001), independent of age of the individuals, smoking habits, whole-blood storage time, and various inflammatory conditions. PSO enabled selection of gene panels to diagnose cancer from TEPs, suggesting that swarm intelligence may also benefit the optimization of diagnostics readout of other liquid biopsy biosources.

    Similar Publications

    Support vector machine based diagnostic system for breast cancer using swarm intelligence.
    J Med Syst 2012 Aug 3;36(4):2505-19. Epub 2011 May 3.
    College of Computer Science and Technology, Jilin University, Changchun, China.
    Breast cancer is becoming a leading cause of death among women in the whole world, meanwhile, it is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. In this paper, a swarm intelligence technique based support vector machine classifier (PSO_SVM) is proposed for breast cancer diagnosis. In the proposed PSO-SVM, the issue of model selection and feature selection in SVM is simultaneously solved under particle swarm (PSO optimization) framework. Read More
    NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.
    Bioinformatics 2015 Oct 18;31(20):3330-8. Epub 2015 Jun 18.
    Academy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing 10080, China.
    Motivation: In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. Read More
    Identification of ten serum microRNAs from a genome-wide serum microRNA expression profile as novel noninvasive biomarkers for nonsmall cell lung cancer diagnosis.
    Int J Cancer 2012 Apr 3;130(7):1620-8. Epub 2011 Aug 3.
    Jiangsu Engineering Research Center for microRNA Biology and Biotechnology, State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, 22 Hankou Road, Nanjing, Jiangsu, China.
    The detection of nonsmall cell lung cancer (NSCLC) at an early stage presents a daunting challenge due to the lack of a specific noninvasive marker. The discovery of microRNAs (miRNAs), particularly those found in serum, has opened a new avenue for tumor diagnosis. To determine whether the expression profile of serum miRNAs can serve as a NSCLC fingerprint, we performed Taqman probe-based quantitative RT-PCR assay to selected differentially expressed serum miRNAs from a sample set including 400 NSCLC cases and 220 controls, and risk score analysis to evaluate the diagnostic value of the serum miRNA profiling system. Read More
    Blood-based gene expression signatures in non-small cell lung cancer.
    Clin Cancer Res 2011 May 10;17(10):3360-7. Epub 2011 May 10.
    Department I of Internal Medicine, University Hospital Cologne, Cologne, Germany.
    Purpose: Blood-based surrogate markers would be attractive biomarkers for early detection, diagnosis, prognosis, and prediction of therapeutic outcome in cancer. Disease-associated gene expression signatures in peripheral blood mononuclear cells (PBMC) have been described for several cancer types. However, RNA-stabilized whole blood-based technologies would be clinically more applicable and robust. Read More