Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.National Science Foundation (U.S.). Graduate Research FellowshipNational Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051)Janssen Pharmaceutical Ltd.Klarman Family Foundatio

Calibrating genomic and allelic coverage bias in single-cell sequencing

Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1–10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples.National Cancer Institute (U.S.) (Grant P30-CA14051

Single cells from human primary colorectal tumors exhibit polyfunctional heterogeneity in secretions of ELR+ CXC chemokines

Cancer is an inflammatory disease of tissue that is largely influenced by the interactions between multiple cell types, secreted factors, and signal transduction pathways. While single-cell sequencing continues to refine our understanding of the clonotypic heterogeneity within tumors, the complex interplay between genetic variations and non-genetic factors ultimately affects therapeutic outcome. Much has been learned through bulk studies of secreted factors in the tumor microenvironment, but the secretory behavior of single cells has been largely uncharacterized. Here we directly profiled the secretions of ELR+ CXC chemokines from thousands of single colorectal tumor and stromal cells, using an array of subnanoliter wells and a technique called microengraving to characterize both the rates of secretion of several factors at once and the numbers of cells secreting each chemokine. The ELR+ CXC chemokines are highly redundant, pro-angiogenic cytokines that signal via the CXCR1 and CXCR2 receptors, influencing tumor growth and progression. We find that human primary colorectal tumor and stromal cells exhibit polyfunctional heterogeneity in the combinations and magnitudes of secretions for these chemokines. In cell lines, we observe similar variance: phenotypes observed in bulk can be largely absent among the majority of single cells, and discordances exist between secretory states measured and gene expression for these chemokines among single cells. Together, these measures suggest secretory states among tumor cells are complex and can evolve dynamically. Most importantly, this study reveals new insight into the intratumoral phenotypic heterogeneity of human primary tumors.Janssen Pharmaceutical Ltd.National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)National Science Foundation (U.S.). Graduate Research FellowshipSingapore. Agency for Science, Technology and ResearchSwiss National Science Foundation (Fellowship for Advanced Researchers PA00P3 139659

Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic

The Mutational Landscape of Circulating Tumor Cells in Multiple Myeloma

The development of sensitive and non-invasive ‘‘liquid biopsies’’ presents new opportunities for longitudinal monitoring of tumor dissemination and clonal evolution. The number of circulating tumor cells (CTCs) is prognostic in multiple myeloma (MM), but there is little information on their genetic features. Here, we have analyzed the genomic landscape of CTCs from 29 MM patients, including eight cases with matched/paired bone marrow (BM) tumor cells. Our results show that 100% of clonal mutations in patient BM were detected in CTCs and that 99% of clonal mutations in CTCs were present in BM MM. These include typical driver mutations in MM such as in KRAS, NRAS, or BRAF. These data suggest that BM and CTC samples have similar clonal structures, as discordances between the two were restricted to subclonal mutations. Accordingly, our results pave the way for potentially less invasive mutation screening of MM patients through characterization of CTCs

Resistance to checkpoint blockade therapy through inactivation of antigen presentation

Treatment with immune checkpoint blockade (CPB) therapies often leads to prolonged responses in patients with metastatic melanoma, but the common mechanisms of primary and acquired resistance to these agents remain incompletely characterized and have yet to be validated in large cohorts. By analyzing longitudinal tumor biopsies from 17 metastatic melanoma patients treated with CPB therapies, we observed point mutations, deletions or loss of heterozygosity (LOH) in beta-2-microglobulin (B2M), an essential component of MHC class I antigen presentation, in 29.4% of patients with progressing disease. In two independent cohorts of melanoma patients treated with anti-CTLA4 and anti-PD1, respectively, we find that B2M LOH is enriched threefold in non-responders (~30%) compared to responders (~10%) and associated with poorer overall survival. Loss of both copies of B2M is found only in non-responders. B2M loss is likely a common mechanism of resistance to therapies targeting CTLA4 or PD1

Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors

Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing

Toward engineered processes for sequencing-based analysis of single circulating tumor cells

Sequencing-based analysis of single circulating tumor cells (CTCs) has the potential to revolutionize our understanding of metastatic cancer and improve clinical care. Technologies exist to enrich, identify, recover, and sequence single cells, but to enable systematic routine analysis of single CTCs from a range of cancer patients, there is a need to establish processes that efficiently integrate these specific operations. Such engineered processes should address challenges associated with the yield and viability of enriched CTCs, the robust identification of candidate single CTCs with minimal degradation of DNA, the bias in whole-genome amplification, and the efficient handling of candidate single CTCs or their amplified DNA products. Advances in methods for single-cell analysis and nanoscale technologies suggest opportunities to overcome these challenges, and could create integrated platforms that perform several of the unit operations together. Ultimately, technologies should be selected or adapted for optimal performance and compatibility in an integrated process. © 2014 Elsevier Ltd

Technological considerations for genome-guided diagnosis and management of cancer

Abstract Technological, methodological, and analytical advances continue to improve the resolution of our view into the cancer genome, even as we discover ways to carry out analyses at greater distances from the primary tumor sites. These advances are finally making the integration of cancer genomic profiling into clinical practice feasible. Formalin fixation and paraffin embedding, which has long been the default pathological biopsy medium, is now being supplemented with liquid biopsy as a means to profile the cancer genomes of patients. At each stage of the genomic data generation process—sample collection, preservation, storage, extraction, library construction, sequencing, and variant calling—there are variables that impact the sensitivity and specificity of the analytical result and the clinical utility of the test. These variables include sample degradation, low yields of nucleic acid, and low variant allele fractions (proportions of assayed molecules carrying variant allele(s)). We review here the most common pre-analytical and analytical factors relating to routine cancer patient genome profiling, some solutions to common challenges, and the major sample preparation and sequencing technology choices available today

Tumor cells are dislodged into the pulmonary vein during lobectomy

Objective Intraoperative tumor shedding may facilitate tumor dissemination. In earlier studies, shed tumor cells were defined primarily by cytomorphological examination, and normal epithelial cells could not always be distinguished from tumor cells. We sought to accurately identify tumor cells using single-cell sequencing and determine whether these cells were mobilized into the circulation during pulmonary lobectomy. Methods Forty-two blood samples collected from the tumor-draining pulmonary vein at the end of lobectomy procedures were analyzed. Arrays of nanowells were used to enumerate and retrieve single EpCAM[superscript +] cells. Targeted sequencing of 10 to 15 cells and nested polymerase chain reaction of single cells detected somatic mutations in shed epithelial cells consistent with patient-matched tumor but not normal tissue. Results The mean number of EpCAM[superscript +] cells in video-assisted thoracoscopy (VATS) lobectomy (no wedge) specimens (n = 16) was 165 (median, 115; range, 0-509) but sampling cells from 3 patients indicated that only 0% to 38% of the EpCAM[superscript +] cells were tumor cells. The mean number of EpCAM[superscript +] cells in VATS lobectomy (wedge) specimens (n = 12) was 1128 (median, 197; range, 47-9406) and all of the EpCAM[superscript +] cells were normal epithelial cells in 2 patients sampled. The mean number of EpCAM[superscript +] cells in thoracotomy specimens (n = 14) was 238 (median, 22; range, 9-2920) and 0% to 50% of total EpCAM[superscript +] cells were tumor cells based on 4 patients sampled. Conclusions Surgery mobilizes tumor cells into the pulmonary vein, along with many normal epithelial cells. EpCAM alone cannot differentiate between normal and tumor cells. On the other hand, single-cell genetic approaches with patient-matched normal and tumor tissues can accurately quantify the number of shed tumor cells.National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051)Singapore. Agency for Science, Technology and ResearchNational Science Foundation (U.S.). Graduate Research FellowshipJanssen Pharmaceutical Ltd