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Discriminant Analysis of Lung Cancer Using Nonlinear Clustering of Copy Numbers.

Nezamoddin N Kachouie1, Meshal Shutaywi1, David C Christiani2,3

  • 1Department of Mathematical Sciences, Florida Institute of Technology, Melbourne, Florida, USA.

Cancer Investigation
|January 25, 2020
PubMed
Summary

Early detection of non-small cell lung cancer (NSCLC) is crucial. DNA copy numbers on chromosomes 5, 8, 1, 3, and 19 show high potential for identifying cancer cells, improving patient survival rates.

Keywords:
DNA copy numbersLung cancerclusteringdiscriminant analysiskernel K-meansnormalized mutual information

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Area of Science:

  • Genomics
  • Cancer Research
  • Bioinformatics

Background:

  • Non-small cell lung cancer (NSCLC) has suboptimal patient survival and high recurrence rates, necessitating early detection strategies.
  • Advances in high-throughput genotyping enable genome-wide screening for cancer-associated genetic alterations.
  • DNA copy number variations present a potential biomarker for distinguishing cancerous from normal cells in early cancer detection.

Purpose of the Study:

  • To evaluate the efficacy of DNA copy number analysis for early cancer detection in NSCLC patients.
  • To identify specific chromosomes with high discriminant power for classifying cancer versus normal samples.
  • To apply nonlinear clustering methods for improved sample separation based on genomic profiles.

Main Methods:

  • Utilized kernel K-means, a nonlinear clustering algorithm, to analyze DNA copy number data.
  • Applied the method to 63 paired cancer-blood samples (126 total samples) from NSCLC patients.
  • Evaluated clustering performance using true/false positive/negative rates and normalized mutual information (NMI).

Main Results:

  • Kernel K-means successfully clustered NSCLC samples based on DNA copy numbers for each chromosome.
  • Discriminant power varied significantly across chromosomes in identifying cancer samples.
  • Chromosomes 8, 5, 1, 3, and 19 demonstrated high discriminant power, with chromosome 5 achieving 75% sensitivity.

Conclusions:

  • Specific DNA copy number profiles on chromosomes 8, 5, 1, 3, and 19 are highly effective for NSCLC detection.
  • Chromosomes 9, 6, 4, 13, and 21 exhibited low discriminant power, indicating overlapping copy number profiles between cancer and normal tissues.
  • This study highlights the potential of targeted chromosomal copy number analysis for early NSCLC diagnosis.