Abstract P5-01-10: Next generation sequencing-based gene variant-oriented characterization in metastatic breast cancer: An innovative analysis using ctDNA

Abstract

Abstract Introduction: Novel high throughput genomic technologies are enhancing the ability to dynamically characterize cancer on a granular level. Although Next Generation Sequencing (NGS) is becoming part of the common practice, little is known on the role of a characterization on a gene variant level. Large heterochromatic regions or blocks are a characteristic feature in the autosomes 1, 9, 16 and the blocks contain about 10% of the human genome. The heterochromatic regions consist of highly repetitive DNA of the classes Sat I to IV. Thus, these specific regions are preferential positions for genome instability. The aim of this study was to explore the feasibility of a gene variant-oriented characterization for variants interplay discovery and to explore the role of chromosome stability in gene variants incidence. Methods: This study analyzed a pilot cohort of 35 metastatic breast cancer (MBC) patients (pts) treated and characterized for CTCs and circulating tumor DNA (ctDNA) at Northwestern University (Chicago, IL). ctDNA was analyzed using the PredicinePLUS™ NGS 180-gene panel (Predicine Inc, CA). Associations between gene variants and clinico-molecular characteristics were tested through Fisher’s exact test. Chromosomes 1, 9, 16 where defined as instable (instable_chr) based on the presence of highly repeated sequences. Results: An overall set of 35 samples was analyzed, and the main variants were detected in the ARID1A (40%), ATM (20%), DNMT3A (37%), ESR1 (20%), PIK3CA (26%), and TP53 (49%) genes. A total of 448 gene variants were detected through the NGS panel and across them, ARID1A accounted for 5.13%, ATM 2.23%, DNMT3A 4.91%, ESR1 4.02%, PIK3CA 2.23%, and TP53 for 6.03%. Among the genes mutated, the DNMT3A:c.2644C>T, DNMT3A:c.2645G>A, ESR1:c.1138G>C,ESR1:c.1609T>A, ESR1:c.1610A>C, ESR1:c.1613A>G, PIK3CA:c.1624G>A were the most detected. Thirty-eight copy number variations (CNV) and 3 splicing variants were observed. Notably, 55.6% of detected variants were found in instable_chr. No significant differences were observed between instable_chr variants and MBC subtype. Interestingly, ARID1Aaberrations were significantly linked to ATM, ESR1 (P=0.006) and PIK3CA with ESR1 (P= 0.019). Consistently with literature, ATM and TP53 variants were mutually exclusive (P<0.0001). Intriguingly, both ATM and TP53 were associated with a higher incidence of variants affecting genes in instable_chr. Conclusions: MBC is often described as a non-gene-addicted disease, rendering the onset of gene variants a multi-factor phenomenon. The present results suggest a role for both chromosomal intrinsic instability and DNA repair impairment in this process, with a potential down-stream selection mediated by treatment resistance. Future studies are warranted to further validate this proof of concept approach. Citation Format: Lorenzo Gerratana, Qiang Zhang, Ami N Shah, Alessandra Franzoni, Jianjun Yu, Shidong Jia, Andrew A Davis, Youbin Zhang, Firas Wehbe, Amir Behdad, Leonidas C Platanias, William J Gradishar, Massimo Cristofanilli. Next generation sequencing-based gene variant-oriented characterization in metastatic breast cancer: An innovative analysis using ctDNA [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-01-10.