Francis, Princy

Abstract Background: Breast tumors exhibit intratumor heterogeneity resulting in targeted therapy resistance and other challenges in disease management. To address the sources of heterogeneity, we performed a unique, in-depth analysis of clonal architecture in primary chemoradiation-naïve breast cancers. We combined DNA content-based flow cytometry and ploidy analysis with aCGH and whole exome next-generation sequencing (NGS) in multiple biopsies from the tumors and involved lymph nodes (LNs). Material and methods: We sorted nuclei from distinct populations of diploid, tetraploid, and aneuploid cells in surgical tumor samples from three chemoradiation-naïve patients. Each sorted tumor cell population was interrogated with aCGH and whole exome NGS. In Patient #1, we sorted and interrogated the genomes of tumor populations from 12 fresh frozen sections morphologically mapped from within a HER2+, ER+, PR- primary invasive ductal carcinoma (IDC) of histological grade 3 with LN involvement and 2-3 sections from 2 out of 5 LNs. In Patient #2, 11 morphologically mapped fresh frozen sections were analyzed from a grade 2, ER+, PR+, HER2+, BRCA2 mutant LN- IDC. In parallel, matching samples were processed for IHC assays. In Patient #3 biopsies from a grade 2 ER+, PR+ primary tumor were profiled. Results: The 18 primary and LN biopsies from Patient #1 fell into 6 distinct ploidy groups albeit with aberrant but homogenous aCGH profiles, characterized by SARC amplification and homozygous deletions in ROBO1 and ROBO2. In contrast a dominant ploidy was identified throughout 10 biopsies in Patient #2 but with heterogeneous aCGH profiles. Patient #3 had a clonal homozygous deletion in Numb in each of 4 tumor biopsies. Mutation profiles obtained through exome sequencing further confirmed that ploidy was the main driver in Patient #1 whereas copy number aberrations played the key role in Patient #2 with the BRCA2 mutation (R3129X). A dendrogram based on exome variant calls of the aneuploid populations in Patient #1 strongly correlated with ploidy group and further revealed the specific clonal population characterized by a 5N ploidy and homozygous mutations in TP53 and PIK3CA as the progenitor to the ploidies present in the distant LNs. Strikingly, patients #1 and #2 were HER2 wild type across their clonal populations, contradicting IHC staining in a single core biopsy. Conclusions:Rather than inferring the presence of distinct tumor cell populations, our flow-sorting based approach of first identifying clonal populations and then interrogating their genomes, provides an objective method of exploring the sources and clinical significance of tumor heterogeneity. Our approach of clonal analysis has broad implications in the study of tumor heterogeneity and the identification of drivers in breast and other solid tumors that can advance more effective treatment and clinical management of patients with this disease. Citation Format: MARIACARLA ANDREOZZI, Princy Francis, Elizabeth Lenkiewicz, Mia Champion, Brady Laughlin, Karen Anderson, Heather Cunliffe, Ann E. McCullough, Michael T. Barrett, Barbara Pockaj. Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in breast cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-175. doi:10.1158/1538-7445.AM2015-LB-175

Abstract Background: Next generation sequencing (NGS) has revealed that the genetic profiles of individual tumors are highly heterogeneous due to their subclonal composition. Tumor heterogeneity has profound clinical implications affecting differences in treatment response and therapeutic resistance. Methods: An estrogen receptor positive, Her2 normal breast cancer patient underwent definitive surgical treatment with modified radical mastectomy. Multiple samples were obtained from the primary cancer and metastatic lymph nodes. Flow cytometry based methods were used to isolate and classify distinct cell subpopulations according to their ploidy, and samples were processed for whole exome sequencing (WES). Comparative Genomic Hybridization (CGH) methods were used to identify somatic unique copy-number alterations (CNAs). WES-Single Nucleotide Variations (SNVs) were used to infer subclonal phylogenetic relationships using Maximum Parsimony methods and annotated with variation-cluster-barcodes (vc-barcodes) generated using a variation Bayesian mixture model (VBMM) approach that focuses on copy-number neutral sequence variations for subclone identification (SciClone). Our comparative phylogenetic-VBMM clustering method was used to identify CNA and/or SNV drivers that are key in differentiating subclonal populations at multiple tumor sites. Results: CNA-neutral WES-SNVs from 25 subclonal populations (isolated from 4 distinct sites) clustered into 6 major groups and were used to generate vc-barcodes. A phylogenetic reconstruction of subclonal architecture annotated with vc-barcode information expedited identification of key variations underlying the differentiation of subclones at distinct tumor sites. For example, we identified an amplification event involving the Anaplastic Lymphoma Kinase (ALK) gene that was more frequent in primary biopsy subclones (12/17, ∼71%) in comparison to metastatic subclones (2/6, ∼34%). As the ALK amplification is lost, we find that most of the metastatic subclones also acquire a predicted damaging mutation in this oncogene (4/6, ∼67%). In addition, we identified a potential driver metastatic cell lineage that carries the ALK amplification in the absence of the nonsynonymous mutation. Conclusions: We developed a hybrid clustering methodology and used it to reconstruct the subclonal architecture in primary and metastatic tumors from a single breast cancer patient. Our methods have identified several CNAs and/or SNVs underlying subclonal differentiation, as well as potential biomarkers of disease progression and indicators of emerging resistance. Application of these methods to larger cohorts and types of tumors should be conducted to ascertain more precise estimates of the predictive accuracy of our processes. Citation Format: Mia D. Champion, Princy Francis, Barbara A. Pockaj, Michael T. Barrett. Hybrid clustering methodologies to distinguish CNAs and/or SNVs that drive subclonal differentiation in samples from a breast cancer patient primary tumor and metastatic lymph nodes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4861. doi:10.1158/1538-7445.AM2015-4861

Abstract Background: Breast tumors exhibit intratumor heterogeneity resulting in targeted therapy resistance and other challenges in disease management. To address the sources of heterogeneity, we performed a unique, in-depth analysis of clonal architecture in primary chemoradiation-naïve breast cancers. We combined DNA content-based flow cytometry and ploidy analysis with aCGH and next-generation sequencing (NGS) in multiple biopsies from the tumors and involved lymph nodes (LNs). Material and methods: We used DNA content-based flow sorting to isolate nuclei from distinct populations of diploid and aneuploid tumor cells in surgical tumor samples from two chemoradiation-naïve patients. Each sorted tumor cell population was interrogated with aCGH and exome NGS. In Patient #1, we used 12 fresh frozen sections morphologically mapped from within a HER2+, ER+, PR- primary invasive ductal carcinoma (IDC) of histological grade 3 with LN involvement and 2-3 sections from 2 out of 5 LNs. In Patient #2, 11 morphologically mapped fresh frozen sections were analyzed from a grade 2, ER+, PR+, HER2+, BRCA2 mutant LN- IDC. In parallel, matching samples were processed for IHC assays. Results: We identified multiple co-existing aneuploid populations within the biopsies. The 17 primary and LN biopsies from Patient #1 fell into 6 distinct ploidy groups albeit with aberrant but homogenous aCGH profiles, characterized by SARC amplification and homozygous deletions in ROBO1 and ROBO2. In contrast a dominant ploidy was identified throughout Patient #2 but with heterogeneous aCGH profiles. Mutation profiles obtained through exome sequencing further confirmed that ploidy was the main driver in Patient #1 whereas copy number aberrations played the key role in Patient #2 with the BRCA2 mutation (R3129X). A dendrogram based on exome variant calls of the aneuploid populations in Patient #1 strongly correlated with ploidy group and further revealed the specific clonal population characterized by a 5N ploidy and homozygous mutations in TP53 and PIK3CA as the progenitor to the ploidies present in the distant LNs. Strikngly, both patients had no HER2 amplification or mutation across their clonal populations, contradicting the initial IHC staining in a single core biopsy. Conclusions Rather than inferring the presence of distinct tumor cell populations, our novel flow-sorting based approach of first identifying the clonal populations and then interrogating their genomes, provides an objective method of exploring the sources and clinical significance of tumor heterogeneity. Our approach of clonal analysis has broad implications in the study of tumor heterogeneity and the identification of drivers in breast and other solid tumors that can advance more effective treatment and clinical management of patients with this disease. Citation Format: Princy Francis, Lucretia M Alvarez, Elizabeth Lenkiewicz, Mia Champion, Lisa Evers, Karen L Anderson, Ann E McCullough, Michael T Barrett, Barbara Pockaj. Deep clonal profiling identifies distinct mechanisms of heterogeneity and evolution in breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-03-07.