Clonality: An R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles

Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Bioinformatics (Impact Factor: 4.98). 06/2011; 27(12):1698-9. DOI: 10.1093/bioinformatics/btr267
Source: PubMed


If a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called 'Clonality'. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results. AVAILABILITY: Bioconductor ( and

9 Reads
  • Source
    • "Quantitative allelic imbalance (LOH) and KRAS point mutations were determined by PCR and subsequent capillary gel electrophoresis (ABI Genetic Analyzer) [23]. For LOH analysis, the normal allelic balance range was determined to be two standard deviations from the average allelic ratio in which the fluorescence derived from the shorter allele copy is divided by that of the longer allele copy [33]. The presence of LOH was determined by those allelic ratios that fell outside the thresholds. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Background This study aimed to better understand the supporting role that mutational profiling (MP) of DNA from microdissected cytology slides and supernatant specimens may play in the diagnosis of malignancy in fine-needle aspirates (FNA) and biliary brushing specimens from patients with pancreaticobiliary masses. Methods Cytology results were examined in a total of 30 patients with associated surgical (10) or clinical (20) outcomes. MP of DNA from microdissected cytology slides and from discarded supernatant fluid was analyzed in 26 patients with atypical, negative or indeterminate cytology. Results Cytology correctly diagnosed aggressive disease in 4 patients. Cytological diagnoses for the remaining 26 were as follows: 16 negative (9 false negative), 9 atypical, 1 indeterminate. MP correctly determined aggressive disease in 1 false negative cytology case and confirmed a negative cytology diagnosis in 7 of 7 cases of non-aggressive disease. Of the 9 atypical cytology cases, MP correctly diagnosed 7 as positive and 1 as negative for aggressive disease. One specimen that was indeterminate by cytology was correctly diagnosed as non-aggressive by MP. When first line malignant (positive) cytology results were combined with positive second line MP results, 12/21 cases of aggressive disease were identified, compared to 4/21 cases identified by positive cytology alone. Conclusions When first line cytology results were uncertain (atypical), questionable (negative), or not possible (non-diagnostic/indeterminate), MP provided additional information regarding the presence of aggressive disease. When used in conjunction with first line cytology, MP increased detection of aggressive disease without compromising specificity in patients that were difficult to diagnose by cytology alone.
    BMC Gastroenterology 08/2014; 14(1):135. DOI:10.1186/1471-230X-14-135 · 2.37 Impact Factor
  • Source
    • "This test uses chromosome arms as the unit of analysis and has its starting point in the multinomial distribution, which requires pre-specification of several tuning parameters , such as the proportion of all identified somatic mutations expected to have occurred in the mother cell. The Likelihood Ratio test assumes that c 5 0.5 (e.g., half of the observed somatic mutations occurred in the mother clone) and calculates the ratio of the likelihoods with c 5 0.5 and c 5 0. The Likelihood Ratio test was run using the " Clonality " R package (Ostrovnaya et al., 2011). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite practical implications we still lack standardized methods for clonality testing of tumor pairs. Each tumor is characterized by a set of chromosomal abnormalities, nonrandom changes preferentially involving specific chromosomes and chromosomal regions. Although tumors accumulate chromosomal abnormalities during their development, the majority of these alterations is specific and characteristic for each individual tumor is not exhibited at the population level. Assumingly, secondary tumors that develop from disseminated cells from the primary tumor inherit not only chromosomal changes specific for the cancerous process but also random chromosomal changes that accumulate during tumor development. Based on this assumption, we adopted an intuitive index for genomic similarities of paired tumors, which ranges between zero (completely different genomic profiles) and one (identical genomic profiles). To test the assumption that two tumors have clonal origins if they share a higher degree of genomic similarity than two randomly paired tumors, we built a permutation-based null-hypothesis procedure. The procedure is demonstrated using two publicly available data sets. The article highlights the complexities of clonality testing and aims to offer an easy to follow blueprint that will allow researchers to test genomic similarities of paired tumors, with the proposed index or any other index that fits their need. © 2013 Wiley Periodicals, Inc.
    Genes Chromosomes and Cancer 11/2013; 52(11). DOI:10.1002/gcc.22096 · 4.04 Impact Factor
  • Source
    • "Tumor pairs are considered clonal if the observed similarity measure lies outside the reference distribution of independent pairs, and is considered suggestive for clonality (equivocal) if the P value is within the range of the reference distribution but more extreme than the 5th percentile (that is, P < 0.05). Further details of the method are described in Ostrovnaya and colleagues [21], and software is available in the Bioconductor package [23]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Introduction Lobular carcinoma in situ (LCIS) has been accepted as a marker of risk for the development of invasive breast cancer, yet modern models of breast carcinogenesis include LCIS as a precursor of low-grade carcinomas. We provide evidence favoring a clonal origin for LCIS and synchronous estrogen receptor-positive malignant lesions of the ductal and lobular phenotype. Methods Patients with prior LCIS undergoing mastectomy were identified preoperatively from 2003 to 2008. Specimens were widely sampled, and frozen blocks were screened for LCIS and co-existing malignant lesions, and were subject to microdissection. Samples from 65 patients were hybridized to the Affymetrix SNP 6.0 array platform. Cases with both an LCIS sample and an associated ductal carcinoma in situ (DCIS) or invasive tumor sample were evaluated for patterns of somatic copy number changes to assess evidence of clonal relatedness. Results LCIS was identified in 44 of the cases, and among these a DCIS and/or invasive lesion was also identified in 21 cases. A total of 17 tumor pairs had adequate DNA/array data for analysis, including nine pairs of LCIS/invasive lobular cancer, four pairs of LCIS/DCIS, and four pairs of LCIS/invasive ductal cancer. Overall, seven pairs (41%) were judged to be clonally related; in five (29%) evidence suggested clonality but was equivocal, and five (29%) were considered independent. Clonal pairs were observed with all matched lesion types and low and high histological grades. We also show anecdotal evidence of clonality between a patient-matched triplet of LCIS, DCIS, and invasive ductal cancer. Conclusion Our results support the role of LCIS as a precursor in the development of both high-grade and low-grade ductal and lobular cancers.
    Breast cancer research: BCR 07/2012; 14(4):R103. DOI:10.1186/bcr3222 · 5.49 Impact Factor
Show more


9 Reads
Available from