Estimating the probability of clonal relatedness of pairs of tumors in cancer patients Journal Article

   


Authors: Mauguen, A.; Seshan, V. E.; Ostrovnaya, I.; Begg, C. B.
Article Title: Estimating the probability of clonal relatedness of pairs of tumors in cancer patients
Abstract: Next generation sequencing panels are being used increasingly in cancer research to study tumor evolution. A specific statistical challenge is to compare the mutational profiles in different tumors from a patient to determine the strength of evidence that the tumors are clonally related, that is, derived from a single, founder clonal cell. The presence of identical mutations in each tumor provides evidence of clonal relatedness, although the strength of evidence from a match is related to how commonly the mutation is seen in the tumor type under investigation. This evidence must be weighed against the evidence in favor of independent tumors from non-matching mutations. In this article, we frame this challenge in the context of diagnosis using a novel random effects model. In this way, by analyzing a set of tumor pairs, we can estimate the proportion of cases that are clonally related in the sample as well as the individual diagnostic probabilities for each case. The method is illustrated using data from a study to determine the clonal relationship of lobular carcinoma in situ with subsequent invasive breast cancers, where each tumor in the pair was subjected to whole exome sequencing. The statistical properties of the method are evaluated using simulations, demonstrating that the key model parameters are estimated with only modest bias in small samples in most configurations. © 2017, The International Biometric Society
Keywords: conditional likelihood; random effects; clonal relatedness; mutational testing; diagnostic probability
Journal Title: Biometrics
Volume: 74
Issue: 1
ISSN: 0006-341X
Publisher: Wiley Blackwell  
Date Published: 2018-03-01
Start Page: 321
End Page: 330
Language: English
DOI: 10.1111/biom.12710
PROVIDER: scopus
PMCID: PMC5677588
PUBMED: 28482133
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019012005&doi=10.1111%2fbiom.12710&partnerID=40&md5=10d71ba3482a6d718f33e67f4d722d65
Notes: Article -- Export Date: 2 April 2018 -- Source: Scopus
Altmetric
What is Altmetric?
Citation Impact
What is Dimensions Citation Badge?
BMJ Impact Analytics
MSK Authors
  1. Venkatraman Ennapadam Seshan
    385 Seshan
  2. Irina Ostrovnaya
    200 Ostrovnaya
  3. Colin B Begg
    306 Begg
  4. Audrey Mauguen
    157 Mauguen
Related MSK Work