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Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle.

ABSTRACT: BACKGROUND:Plasma-derived cell-free tumor DNA (ctDNA) constitutes a potential surrogate for tumor DNA obtained from tissue biopsies. We posit that massively parallel sequencing (MPS) analysis of ctDNA may help define the repertoire of mutations in breast cancer and monitor tumor somatic alterations during the course of targeted therapy. PATIENT AND METHODS:A 66-year-old patient presented with synchronous estrogen receptor-positive/HER2-negative, highly proliferative, grade 2, mixed invasive ductal-lobular carcinoma with bone and liver metastases at diagnosis. DNA extracted from archival tumor material, plasma and peripheral blood leukocytes was subjected to targeted MPS using a platform comprising 300 cancer genes known to harbor actionable mutations. Multiple plasma samples were collected during the fourth line of treatment with an AKT inhibitor. RESULTS:Average read depths of 287x were obtained from the archival primary tumor, 139x from the liver metastasis and between 200x and 900x from ctDNA samples. Sixteen somatic non-synonymous mutations were detected in the liver metastasis, of which 9 (CDKN2A, AKT1, TP53, JAK3, TSC1, NF1, CDH1, MML3 and CTNNB1) were also detected in >5% of the alleles found in the primary tumor sample. Not all mutations identified in the metastasis were reliably identified in the primary tumor (e.g. FLT4). Analysis of ctDNA, nevertheless, captured all mutations present in the primary tumor and/or liver metastasis. In the longitudinal monitoring of the patient, the mutant allele fractions identified in ctDNA samples varied over time and mirrored the pharmacodynamic response to the targeted therapy as assessed by positron emission tomography-computed tomography. CONCLUSIONS:This proof-of-principle study is one of the first to demonstrate that high-depth targeted MPS of plasma-derived ctDNA constitutes a potential tool for de novo mutation identification and monitoring of somatic genetic alterations during the course of targeted therapy, and may be employed to overcome the challenges posed by intra-tumor genetic heterogeneity. REGISTERED CLINICAL TRIAL:www.clinicaltrials.gov, NCT01090960.

SUBMITTER: De Mattos-Arruda L

PROVIDER: S-EPMC6276937 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle.

De Mattos-Arruda L L Weigelt B B Cortes J J Won H H HH Ng C K Y CKY Nuciforo P P Bidard F-C FC Aura C C Saura C C Peg V V Piscuoglio S S Oliveira M M Smolders Y Y Patel P P Norton L L Tabernero J J Berger M F MF Seoane J J Reis-Filho J S JS

Annals of oncology : official journal of the European Society for Medical Oncology 20140709 9

<h4>Background</h4>Plasma-derived cell-free tumor DNA (ctDNA) constitutes a potential surrogate for tumor DNA obtained from tissue biopsies. We posit that massively parallel sequencing (MPS) analysis of ctDNA may help define the repertoire of mutations in breast cancer and monitor tumor somatic alterations during the course of targeted therapy.<h4>Patient and methods</h4>A 66-year-old patient presented with synchronous estrogen receptor-positive/HER2-negative, highly proliferative, grade 2, mixe ...[more]

PMID: 25009010

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Project description:BackgroundGene expression-based subtyping has the potential to form a new paradigm for stratified treatment of colorectal cancer. However, current frameworks are based on the transcriptomic profiles of primary tumors, and metastatic heterogeneity is a challenge. Here we aimed to develop a de novo metastasis-oriented framework.MethodsIn total, 829 transcriptomic profiles from patients with colorectal cancer were analyzed, including primary tumors, liver metastases, and non-malignant liver samples. High-resolution microarray gene expression profiling was performed of 283 liver metastases from 171 patients treated by hepatic resection, including multiregional and/or multi-metastatic samples from each of 47 patients. A single randomly selected liver metastasis sample from each patient was used for unsupervised subtype discovery by nonnegative matrix factorization, and a random forest prediction model was trained to classify multi-metastatic samples, as well as liver metastases from two independent series of 308 additional patients.ResultsInitial comparisons with non-malignant liver samples and primary colorectal tumors showed a highly variable degree of influence from the liver microenvironment in metastases, which contributed to inter-metastatic transcriptomic heterogeneity, but did not define subtype distinctions. The de novo liver metastasis subtype (LMS) framework recapitulated the main distinction between epithelial-like and mesenchymal-like tumors, with a strong immune and stromal component only in the latter. We also identified biologically distinct epithelial-like subtypes originating from different progenitor cell types. LMS1 metastases had several transcriptomic features of cancer aggressiveness, including secretory progenitor cell origin, oncogenic addictions, and microsatellite instability in a microsatellite stable background, as well as frequent RAS/TP53 co-mutations. The poor-prognostic association of LMS1 metastases was independent of mutation status, clinicopathological variables, and current subtyping frameworks (consensus molecular subtypes and colorectal cancer intrinsic subtypes). LMS1 was also the least heterogeneous subtype in comparisons of multiple metastases per patient, and tumor heterogeneity did not confound the prognostic value of LMS1.ConclusionsWe report the first large study of multi-metastatic gene expression profiling of colorectal cancer. The new metastasis-oriented subtyping framework showed potential for clinically relevant transcriptomic classification in the context of metastatic heterogeneity, and an LMS1 mini-classifier was constructed to facilitate prognostic stratification and further clinical testing.

Project description:Colorectal cancer arises in part from the cumulative effects of multiple gene lesions. Recent studies in selected cancer types have revealed significant intra-tumor genetic heterogeneity and highlighted its potential role in disease progression and resistance to therapy. We hypothesized the existence of significant intra-tumor genetic heterogeneity in rectal cancers involving variations in localized somatic mutations and copy number abnormalities. Two or three spatially disparate regions from each of six rectal tumors were dissected and subjected to the next-generation whole-exome DNA sequencing, Oncoscan SNP arrays, and targeted confirmatory sequencing and analysis. The resulting data were integrated to define subclones using SciClone. Mutant-allele tumor heterogeneity (MATH) scores, mutant allele frequency correlation, and mutation percent concordance were calculated, and copy number analysis including measurement of correlation between samples was performed. Somatic mutations profiles in individual cancers were similar to prior studies, with some variants found in previously reported significantly mutated genes and many patient-specific mutations in each tumor. Significant intra-tumor heterogeneity was identified in the spatially disparate regions of individual cancers. All tumors had some heterogeneity but the degree of heterogeneity was quite variable in the samples studied. We found that 67-97% of exonic somatic mutations were shared among all regions of an individual's tumor. The SciClone computational method identified 2-8 shared and unshared subclones in the spatially disparate areas in each tumor. MATH scores ranged from 7 to 41. Allele frequency correlation scores ranged from R(2)=0.69-0.96. Measurements of correlation between samples for copy number changes varied from R(2)=0.74-0.93. All tumors had some heterogeneity, but the degree was highly variable in the samples studied. The occurrence of significant intra-tumor heterogeneity may allow selected tumors to have a genetic reservoir to draw from in their evolutionary response to therapy and other challenges.

Dataset Information

Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle.

Publications

Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle.

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