Abstract PS2-05: Genetic profiling for circulating tumor cell clusters to unveil molecular drivers of metastasis
Authors: Qiang Zhang, Lorenzo Gerratana, Paolo D'Amico, Andrew A. Davis, Saya Liz Jacob, Xinkun Wang, Zhe Ji, Zheng Cai, Elena Vagia, Wenan Qiang, Ami Shah, Youbin Zhang, Lisa Flaum, Firas Wehbe, Amir Behdad, William Gradishar, Leonidas Platanias, Massimo Cristofanilli
Journal: Cancer Research (2021)

Abstract Introduction: Although CTCs display the same spatial and temporal heterogeneity as the primary tumor, they represent a privileged window to disclose mechanisms of metastases. A portion of CTCs may form clusters that contain two or more CTCs bound together which were reported to have up to 50-fold of potential of forming distant metastasis in MBC as compared to individual CTCs (Aceto N. Cell, 2015). However, genomic characterization of CTCs-clusters compared to single CTCs remain largely unknown. We previously reported single CTC sequencing for HER2+ CTCs (2020 AACR #3120). Herein, we report a new finding of heterogeneity profiling for CTC-clusters compared to single CTCs, which would be helpful to evaluate the MBC metastasis capability and treatment in clinic. Methods: Whole blood sample (7.5ml/each) was collected from stage III/IV MBC patients before therapy. CTC enumeration was performed using the FDA-cleared CellSearch™ System (Menarini) targeting the EpCAM antigen for capturing CTCs which were then stained by Anti-CK-PE, DAPI, anti-CD45-APC and anti-HER2-FITC. The CTC-clusters and single CTCs were isolated using DEPArrayTM System (Menarini). DNA was isolated from CTC-clusters and single CTCs by ArcturusTM PicoPureTM DNA Extraction kit. The initial library was prepared by SMARTer® PicoPLEX® Gold Single Cell DNA-Seq Kit, and the exome capture was performed by Twist Human Core Exome EF Multiplex Complete Kit. The sequencing was prepared by NextSeq 500 mid output V2.5 kit and was performed on the NextSeq 500 (Illumina). It was a paired end run, 75×75 bps run with dual indexing. Results: We identified 107 CTCs by CellSearch™, including 93 single CTCs, 14 CTC-clusters and 145 WBCs. Autologous CTC-clusters (CK+DAPI+CD45-, Group 1), single CTCs (CK+DAPI+CD45-, Group 2), and leukocytes (CK-DAPI+CD45+, Group 3) were sequenced respectively. The sequencing data was processed following the GATK pipeline and annotated using SnpEff. There were 60,638 counts (6.77%) and 70,334 counts (8.20%) for exon variants in CTC-clusters and single CTCs respectively, 507,595 counts (56.69%) and 486,119 counts (56.69%) for intron variants, 194,026 (21.67%) and 175,819 counts (20.51%) for intergenic variants, 54,174 counts (6.05%) and 50,370 counts (5.87%) for downstream genes, 51,716 counts (5.78%) and 45,915 counts (5.36%) for upstream genes, and 3.04% and 3.37% of others variants in CTC-clusters and single CTCs respectively. Meanwhile, there was 0 count for exon and intron variants found in Group 3. There were 60 and 79 gene variants (SNP and Ins-Del) identified to have the highest impact effect (≥20) on CTC-clusters and single CTC exons respectively, which affect significantly on the functional proteins coding. Among the top 50 high impact gene variants in each group, there were 25 gene alteration sites were similar in Group 1 and 2, including XYLB, RAN, QPCT, HPGDS, HDAC8, GABBR2, CYP11B2 and CHKA. Specific to Group 1, there were 25 gene alterations which were primarily related to cellular proliferation and tumor promotion (AMD1), liver drug clearance (CES1), tissue remodeling (CHI3L1), immune cytokine signaling (JAK1) and metabolism (ASRGL1). Meanwhile, there are 25 specific gene alterations in Group 2 compared to Group 1, which were associated with nucleotide-excision repair (DDB1 and FAN1) chromosome positioning (KIF11), cell growth, differentiation, mitotic cycle, oncogenic transformation (PTPN3 and MAPK14), apoptosis (CASP1) and cell growth (CTNNB1). Conclusion: Genomic characterization of CTC-clusters compared to autologous single CTCs and leukocytes elucidated new specific gene alterations in CTC-clusters associated with most aggressive disease metastasis in MBC, which will help to gain new insights on the molecular mechanisms associated with the metastasis and find new molecularly driven therapies for disease metastasis. Citation Format: Qiang Zhang, Lorenzo Gerratana, Paolo D'Amico, Andrew A. Davis, Saya Liz Jacob, Xinkun Wang, Zhe Ji, Zheng Cai, Elena Vagia, Wenan Qiang, Ami Shah, Youbin Zhang, Lisa Flaum, Firas Wehbe, Amir Behdad, William Gradishar, Leonidas Platanias, Massimo Cristofanilli. Genetic profiling for circulating tumor cell clusters to unveil molecular drivers of metastasis [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-05.