Addressing drug resistance is a core challenge in cancer research, but the degree of heterogeneity in resistance mechanisms in cancer is unclear. In this study, we conducted next-generation sequencing (NGS) of circulating tumor cells (CTC) from patients with advanced cancer to assess mechanisms of resistance to targeted therapy and reveal opportunities for precision medicine. Comparison of the genomic landscapes of CTCs and tissue metastases is complicated by challenges in comprehensive CTC genomic profiling and paired tissue acquisition, particularly in patients who progress after targeted therapy. Thus, we assessed by NGS somatic mutations and copy number alterations (CNA) in archived CTCs isolated from patients with metastatic breast cancer who were enrolled in concurrent clinical trials that collected and analyzed CTCs and metastatic tissues. In 76 individual and pooled informative CTCs from 12 patients, we observed 85% concordance in at least one or more prioritized somatic mutations and CNA between paired CTCs and tissue metastases. Potentially actionable genomic alterations were identified in tissue but not CTCs, and vice versa. CTC profiling identified diverse intra- and interpatient molecular mechanisms of endocrine therapy resistance, including loss of heterozygosity in individual CTCs. For example, in one patient, we observed CTCs that were either wild type for ( = 5/32), harbored the known activating p.Y537S mutation ( = 26/32), or harbored a novel p.A569S ( = 1/32). p.A569S was modestly activating, consistent with its presence as a minority circulating subclone. Our results demonstrate the feasibility and potential clinical utility of comprehensive profiling of archived fixed CTCs. Tissue and CTC genomic assessment are complementary, and precise combination therapies will likely be required for effective targeting in advanced breast cancer patients. These findings demonstrate the complementary nature of genomic profiling from paired tissue metastasis and circulating tumor cells from patients with metastatic breast cancer. .

Precision medicine in oncology requires an accurate characterization of a tumor molecular profile for patient stratification. Though targeted deep sequencing is an effective tool to detect the presence of somatic sequence variants, a significant number of patient specimens do not meet the requirements needed for routine clinical application. Analysis is hindered by contamination of normal cells and inherent tumor heterogeneity, compounded with challenges of dealing with minute amounts of tissue and DNA damages common in formalin-fixed paraffin-embedded (FFPE) specimens. Here we present an innovative workflow using DEPArray™ system, a microchip-based digital sorter to achieve 100%-pure, homogenous subpopulations of cells from FFPE samples. Cells are distinguished by fluorescently labeled antibodies and DNA content. The ability to address tumor heterogeneity enables unambiguous determination of true-positive sequence variants, loss-of-heterozygosity as well as copy number variants. The proposed strategy overcomes the inherent trade-offs made between sensitivity and specificity in detecting genetic variants from a mixed population, thus rescuing for analysis even the smaller clinical samples with low tumor cellularity.

Background: Aurora kinases are key regulators of cell cycle and represent new promising therapeutic targets in several human tumours.

PLK1 can be proposed as a new candidate target for OS. Targeting PLK1 in OS with NMS-P937 in association with conventional chemotherapeutic drugs may be a new interesting therapeutic option, since this approach has proved to be active against drug resistant cells.

Nearly all estrogen receptor (ER)‐positive (POS) metastatic breast cancers become refractory to endocrine (ET) and other therapies, leading to lethal disease presumably due to evolving genomic alterations. Timely monitoring of the molecular events associated with response/progression by serial tissue biopsies is logistically difficult. Use of liquid biopsies, including circulating tumor cells (CTC) and circulating tumor DNA (ctDNA), might provide highly informative, yet easily obtainable, evidence for better precision oncology care. Although ctDNA profiling has been well investigated, the CTC precision oncology genomic landscape and the advantages it may offer over ctDNA in ER‐POS breast cancer remain largely unexplored. Whole‐blood (WB) specimens were collected at serial time points from patients with advanced ER‐POS/HER2‐negative (NEG) advanced breast cancer in a phase I trial of AZD9496, an oral selective ER degrader (SERD) ET. Individual CTC were isolated from WB using tandem CellSearch®/DEPArray™ technologies and genomically profiled by targeted single‐cell DNA next‐generation sequencing (scNGS). High‐quality CTC (n = 123) from 12 patients profiled by scNGS showed 100% concordance with ctDNA detection of driver estrogen receptor α (ESR1) mutations. We developed a novel CTC‐based framework for precision medicine actionability reporting (MI‐CTCseq) that incorporates novel features, such as clonal predominance and zygosity of targetable alterations, both unambiguously identifiable in CTC compared to ctDNA. Thus, we nominated opportunities for targeted therapies in 73% of patients, directed at alterations in phosphatidylinositol‐4,5‐bisphosphate 3‐kinase catalytic subunit alpha (PIK3CA), fibroblast growth factor receptor 2 (FGFR2), and KIT proto‐oncogene, receptor tyrosine kinase (KIT). Intrapatient, inter‐CTC genomic heterogeneity was observed, at times between time points, in subclonal alterations. Our analysis suggests that serial monitoring of the CTC genome is feasible and should enable real‐time tracking of tumor evolution during progression, permitting more combination precision medicine interventions.

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>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

• Somatic copy number alterations (CNAs) were detected at a single CTC level that are absent from germline WBC genomes from same patients. • Single non-conventional (large CK-) CTCs were identified as tumor originating based on CNA profiles.

Fluorescent in Situ Hybridization (FISH) is commonly used for assessment of chromosomal alterations. Guidelines for determining FISH-based classification of clinical biomarkers exist but are based on pre-analytical factors, including fixation/sectioning/thickness/age, that can greatly influence biomarker status determination. Here, we use single-cell image-based cell sorting by DEPArrayTM for the separation and recovery of pure distinct cell populations prior to FISH. Methods: A multi-center study to evaluate HER2-FISH based analysis on FFPE with and without DEPArrayTM pre-processing was conducted using breast tumors classified as infiltrating ductal carcinoma (n=12), metastatic (n=1) and ductal carcinoma (n=1). From each block, four 50-micron thick curls were sectioned. One curl from each sample was sent to each of four centers (3 US; 1 EU). Each site performed disassociation of curls to generate a single cell suspension. Cells were then stained and sorted using the DEPArrayTM platform for recovery of tumor (cytokeratin+/vimentin-/DAPI+) and stromal (cytokeratin-/vimentin+/DAPI+) cells. Dual-probe FISH for HER2 and centromere 17 was performed on the sorted cells and compared with conventional tissue section FISH. Results: Overall, ≥ 90% concordance between the sorted tumor cells and the conventional HER2 FISH result was observed. Among the 7 HER2+ cases, HER2 ratio scores for the sorted tumor cells ranged slightly higher, from 2.60 to 8.95, as compared to the conventional method (from 2.10 to 5.14). In all cases in which stromal cells were also recovered, an expected normal ratio was observed, thus verifying that the populations were efficiently separated. Discordance can be attributed to intra-tumoral heterogeneity and the fact that conventional FISH on FFPE requires only a 4-micron section for analysis. Conclusion: Today, a percentage of patients are likely misclassified for the biomarker of interest as result of pre-analytical factors. We demonstrate here the ability to overcome these pre-analytic factors and ultimately improve the accuracy in determining biomarker status using the DEPArrayTM Note: This abstract was not presented at the meeting. Citation Format: Amanda Gerber, Aditi Khurana, Lisa Koenig, Lindsay Strotoman, Lori Millner, Valeria Sero, Chiara Bolognesi, Sabine Kasimir-bauer, Gianni Medoro, Matthew Moore, Philip Cotter, Nicolo Manaresi, Farideh Bischoff. Image-based single cell-sorting to separate and recover distinct cell populations from complex heterogeneous mixed tissue: precise sample preparation upstream of FISH [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2730. doi:10.1158/1538-7445.AM2017-2730