Joyce A. Tai

Clusters of tumor cells are often observed in the blood of cancer patients. These structures have been described as malignant entities for more than 50 years, although their comprehensive characterization is lacking. Contrary to current consensus, we demonstrate that a discrete population of circulating cell clusters isolated from the blood of colorectal cancer patients are not cancerous but consist of tumor-derived endothelial cells. These clusters express both epithelial and mesenchymal markers, consistent with previous reports on circulating tumor cell (CTC) phenotyping. However, unlike CTCs, they do not mirror the genetic variations of matched tumors. Transcriptomic analysis of single clusters revealed that these structures exhibit an endothelial phenotype and can be traced back to the tumor endothelium. Further results show that tumor-derived endothelial clusters do not form by coagulation or by outgrowth of single circulating endothelial cells, supporting a direct release of clusters from the tumor vasculature. The isolation and enumeration of these benign clusters distinguished healthy volunteers from treatment-naïve as well as pathological early-stage (≤IIA) colorectal cancer patients with high accuracy, suggesting that tumor-derived circulating endothelial cell clusters could be used as a means of noninvasive screening for colorectal cancer. In contrast to CTCs, tumor-derived endothelial cell clusters may also provide important information about the underlying tumor vasculature at the time of diagnosis, during treatment, and throughout the course of the disease.

Abstract BACKGROUND The comeasurement of both genomic and transcriptomic signatures in single cells is of fundamental importance to accurately assess how the genetic information correlates with the transcriptomic phenotype. However, existing technologies have low throughput and laborious work flows. METHODS We developed a new method for concurrent sequencing of the transcriptome and targeted genomic regions (CORTAD-seq) within the same single cell on an automated microfluidic platform. The method was compatible with the downstream library preparation, allowing easy integration into existing next-generation sequencing work flows. We incorporated a single-cell bioinformatics pipeline for transcriptome and mutation analysis. RESULTS As proof of principle, we applied CORTAD-seq to lung cancer cell lines to dissect the cellular consequences of mutations that result in resistance to targeted therapy. We obtained a mean detection of 6000 expressed genes and an exonic rate of 50%. The targeted DNA-sequencing data achieved a 97.8% detection rate for mutations and allowed for the identification of copy number variations and haplotype construction. We detected expression signatures of tyrosine kinase inhibitor (TKI) resistance, epidermal growth factor receptor (EGFR) amplification, and expansion of the T790M mutation among resistant cells. We also identified characteristics for TKI resistance that were independent of EGFR T790M, indicating that other alterations are required for resistance in this context. CONCLUSIONS CORTAD-seq allows assessment of the interconnection between genetic and transcriptomic changes in single cells. It is operated on an automated, commercially available single-cell isolation platform, making its implementation straightforward.

INTRODUCTION: Circulating tumor cells (CTCs) and cell-free tumor DNA (ctDNA) are tumor components present in circulation. Due to the limited access to both CTC enrichment platforms and ctDNA sequencing in most laboratories, they are rarely analyzed together. METHODS: DropCell platform. We performed targeted amplicon sequencing to evaluate the genomic heterogeneity of CTCs and ctDNA in lung cancer and breast cancer patients. RESULTS: Higher degrees of genomic heterogeneity were observed in CTCs as compared to ctDNA. Several shared alterations present in CTCs and ctDNA were undetected in the primary tumor, highlighting the intra-tumoral heterogeneity of tumor components that were shed into systemic circulation. Accordingly, CTCs and ctDNA displayed higher degree of concordance with the metastatic tumor than the primary tumor. The alterations detected in circulation correlated with worse survival outcome for both lung and breast cancer patients emphasizing the impact of the metastatic phenotype. Notably, evolving genetic signatures were detected in the CTCs and ctDNA samples during the course of treatment and disease progression. CONCLUSIONS: A standardized sample processing and data analysis workflow for concurrent analysis of CTCs and ctDNA successfully dissected the heterogeneity of metastatic tumor in circulation as well as the progressive genomic changes that may potentially guide the selection of appropriate therapy against evolving tumor clonality.

// Say Li Kong 1 , Xingliang Liu 1 , Nur-Afidah Mohamed Suhaimi 2 , Kenneth Jia Hao Koh 1 , Min Hu 2 , Daniel Yoke San Lee 2 , Igor Cima 2, 3, 4 , Wai Min Phyo 2, 5 , Esther Xing Wei Lee 2 , Joyce A. Tai 1 , Yu Miin Foong 2 , Jess Honganh Vo 2, 5 , Poh Koon Koh 2, 6 , Tong Zhang 1 , Jackie Y. Ying 2 , Bing Lim 1 , Min-Han Tan 2, 5, 6 and Axel M. Hillmer 1, 7 1 Genome Institute of Singapore, Singapore 138672, Singapore 2 Institute of Bioengineering and Nanotechnology, Singapore 138669, Singapore 3 German Cancer Consortium (DKTK), Essen/Düsseldorf, Heidelberg 69120, Germany 4 German Cancer Research Center (DKFZ), Heidelberg 69120, Germany 5 Lucence Diagnostics Pte Ltd, Singapore 159555, Singapore 6 Concord Cancer Hospital Singapore, Singapore 289891, Singapore 7 TRON-Translational Oncology at the University Medical Center of The Johannes Gutenberg University gGmbH, Mainz 55131, Germany Correspondence to: Say Li Kong, email: kongsl@gis.a-star.edu.sg Axel M. Hillmer, email: hillmer@gis.a-star.edu.sg Keywords: circulating tumor cells, colorectal cancer, targeted sequencing, druggable mutation, mutation signatures Received: October 12, 2016     Accepted: June 02, 2017     Published: July 10, 2017 ABSTRACT Studies on circulating tumor cells (CTCs) have largely focused on platform development and CTC enumeration rather than on the genomic characterization of CTCs. To address this, we performed targeted sequencing of CTCs of colorectal cancer patients and compared the mutations with the matched primary tumors. We collected preoperative blood and matched primary tumor samples from 48 colorectal cancer patients. CTCs were isolated using a label-free microfiltration device on a silicon microsieve. Upon whole genome amplification, we performed amplicon-based targeted sequencing on a panel of 39 druggable and frequently mutated genes on both CTCs and fresh-frozen tumor samples. We developed an analysis pipeline to minimize false-positive detection of somatic mutations in amplified DNA. In 60% of the CTC-enriched blood samples, we detected primary tumor matching mutations. We found a significant positive correlation between the allele frequencies of somatic mutations detected in CTCs and abnormal CEA serum level. Strikingly, we found driver mutations and amplifications in cancer and druggable genes such as APC, KRAS, TP53, ERBB3 , FBXW7 and ERBB2 . In addition, we found that CTCs carried mutation signatures that resembled the signatures of their primary tumors. Cumulatively, our study defined genetic signatures and somatic mutation frequency of colorectal CTCs. The identification of druggable mutations in CTCs of preoperative colorectal cancer patients could lead to more timely and focused therapeutic interventions.

Single cell genomics offers an unprecedented resolution to interrogate genetic heterogeneity in a patient's tumour at the intercellular level. However, the DNA yield per cell is insufficient for today's sequencing library preparation protocols. This necessitates DNA amplification which is a key source of experimental noise. We provide an evaluation of two protocols using micro-fluidics based amplification for whole exome sequencing, which is an experimental scenario commonly used in single cell genomics. The results highlight their respective biases and relative strengths in identification of single nucleotide variations. Towards this end, we introduce a workflow SoVaTSiC, which allows for quality evaluation and somatic variant identification of single cell data. As proof of concept, the framework was applied to study a lung adenocarcinoma tumour. The analysis provides insights into tumour phylogeny by identifying key mutational events in lung adenocarcinoma evolution. The consequence of this inference is supported by the histology of the tumour and demonstrates usefulness of the approach.