The defining feature of cancer is metastasis, the ability of tumors to colonize distant sites of the body. However, independent (second primary) cancers also occur frequently. The ability to distinguish a second primary from a metastasis is often of great clinical relevance, as it can affect the appropriateness of local (surgical) versus systemic (medical) treatment. Historically pathologists have distinguished these on the basis of gross and microscopic pathologic criteria. In recent years cancer investigators have begun to compare the molecular profiles of pairs of tumors with a view to distinguishing independent cancers from those that share a clonal origin (e.g. metastases) at the molecular level. These studies involve the side-by-side comparison of pairs of tumors (from the same patient) on the basis of patterns of somatic mutations, such as allelic gains or losses, or point mutations in genes that frequently experience somatic mutations in tumors. Statistical methods for classifying the tumors as independent versus clonal in this field have only recently begun to be developed and evaluated for validity. Building on research on methods for comparing sets of candidate markers of loss of heterozygosity that we have recently developed, we now plan to develop formal procedures for comparing array CGH profiles from two tumors to determine if they are of clonal (metastatic) or independent origin. Our strategy involves a global evaluation of the correlation of apparent allelic losses and gains on the tumors, and a much more precise comparison of individual, potentially clonal somatic events within chromosome arms. Based on the results of the research we will develop software t provide investigators with the computational tools to arrive at these molecular diagnoses.

Public Health Relevance

Cancers can be cured by surgery or they may spread subsequently to other parts of the body. This latter process is known as metastasis. It is also possible for a patient who has been cured to develop a new, independent occurrence of cancer. When a new tumor develops pathologists examine the tumor to determine if it is a metastasis or a new primary cancer. However, in some circumstances it is difficult for the pathologist to distinguish a new primary cancer from a metastasis, and yet this diagnosis may be very important for deciding upon the appropriate course of treatment. We believe that the pathologist's dilemma in these circumstances can be resolved by comparing the "genetic fingerprints" of the two tumors. Our proposed research involves developing statistical techniques for examining the information in these genetic fingerprints, representing the mutations that have occurred during the development of the tumors, in order to provide accurate pathological diagnoses.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA124504-03
Application #
7993113
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Li, Jerry
Project Start
2008-12-01
Project End
2013-04-30
Budget Start
2010-12-01
Budget End
2013-04-30
Support Year
3
Fiscal Year
2011
Total Cost
$343,456
Indirect Cost
Name
Sloan-Kettering Institute for Cancer Research
Department
Type
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10065
Ostrovnaya, Irina; Seshan, Venkatraman E; Begg, Colin B (2015) USING SOMATIC MUTATION DATA TO TEST TUMORS FOR CLONAL RELATEDNESS. Ann Appl Stat 9:1533-1548
Andrade, Victor P; Ostrovnaya, Irina; Seshan, Venkatraman E et al. (2012) Clonal relatedness between lobular carcinoma in situ and synchronous malignant lesions. Breast Cancer Res 14:R103
Ostrovnaya, Irina (2012) Testing clonality of three and more tumors using their loss of heterozygosity profiles. Stat Appl Genet Mol Biol 11:
Begg, Colin B (2011) A strategy for distinguishing optimal cancer subtypes. Int J Cancer 129:931-7
Olshen, Adam B; Bengtsson, Henrik; Neuvial, Pierre et al. (2011) Parent-specific copy number in paired tumor-normal studies using circular binary segmentation. Bioinformatics 27:2038-46
Ostrovnaya, Irina; Seshan, Venkatraman E; Olshen, Adam B et al. (2011) Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles. Bioinformatics 27:1698-9
Ostrovnaya, Irina; Nanjangud, Gouri; Olshen, Adam B (2010) A classification model for distinguishing copy number variants from cancer-related alterations. BMC Bioinformatics 11:297
Ostrovnaya, Irina; Begg, Colin B (2010) Testing clonal relatedness of tumors using array comparative genomic hybridization: a statistical challenge. Clin Cancer Res 16:1358-67
Ostrovnaya, Irina; Olshen, Adam B; Seshan, Venkatraman E et al. (2010) A metastasis or a second independent cancer? Evaluating the clonal origin of tumors using array copy number data. Stat Med 29:1608-21
Kuligina, Ekatherina; Reiner, Anne; Imyanitov, Evgeny N et al. (2010) Evaluating cancer epidemiologic risk factors using multiple primary malignancies. Epidemiology 21:366-72

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