In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 1552-1552
Abstract:
Background: We provide a solution of pressing needs in preparation of FFPE samples for genomic analysis: small sample size, unwanted admixture of normal cells, analysis of tumor rare-cell subpopulations present at low percentages in the tumor fraction. Methods: We disaggregated into cell suspensions archival FFPE samples from 12 ovarian, pancreatic and lung cancer patients, staining for Vimentin, Keratin and DNA. We sorted by DEPArray™ precise numbers (mean = 107, median 58, range = 5-600) of pure homogenous cells from the major population of tumor cells, the contaminant diploid stromal cells, and other minority tumor cell types indicative of epithelial-to-mesenchymal transition (EMT). Using IonTorrent AmpliSeq CHPv2, we generated sequencing libraries, after lysis of the pure cells recovered by DEPArray™ (n = 54), or unsorted samples (either QIAmp DNA columns or disaggregated cells). Libraries were sequenced with IonTorrent PGM (mean depth & gt;2,000x), and analyzed using IonTorrent software. Results: On several loci, we detected somatic mutations with 100% variant frequency, only observable as heterozygous in the unsorted samples and as wild-type in stromal cells of same patient, confirming 100% purity of sorted cells. Moreover, in the EMT-phenotype subpopulations we identified clear somatic mutations, different from tumor cells majority and undetectable in unsorted samples. Frequently, for loci harboring germ-line heterozygous SNPs with variant frequency around 50% for pure stromal cells, we readily detected loss-of-heterozygosis in tumor cells subpopulations as binary (0%/100%) variants. Quantitative traits such as copy number gains and losses were also reproducibly identified in tumor cell replicates as deviations from the 50% variant frequency of germline SNPs of pure stromal cells. Furthermore, we observed an excellent coverage uniformity (mean = 96%) for recoveries (n = 27) in the range of 81-600 cells, even higher than the uniformity obtained with (n = 2) QIAmp-purified DNA (92%). Mean uniformity gradually decreased to 89% for cell recoveries (n = 13) in the range 21-80, and further decreased to 70% for lower cell numbers (n = 14). Highlights: Sorting tumor rare-cell subpopulations reveals their genetic characteristics, undetectable in unsorted samples. Analyzing homogenous cell subpopulations boosts signal-to-noise ratio working around inherent sensitivity/specifitiy trade-offs of rare-variant calls. The proposed workflow further enables reliable detection of quantitative traits such as CNVs. Sorting pure stromal cells yields internal controls for archival samples. Citation Format: Chiara Bolognesi, Anna Doffini, Genny Buson, Rossana Lanzellotto, Giulio Signorini, Valeria Sero, Alex Calanca, Francesca Fontana, Rita Romano, Stefano Gianni, Giulia Bregola, Gianni Medoro, Raimo Tanzi, Giuseppe Giorgini, Hans Morreau, Massimo Barberis, Willem E. Corver, Nicolo Manaresi. Image-based microchip sorting of pure, immuno-phenotypically defined subpopulations of tumor cells from tiny formalin-fixed paraffin embedded (FFPE) samples reveals their distinct genetic features. [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 1552. doi:10.1158/1538-7445.AM2015-1552
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2015-1552
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2015
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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