Timour Baslan

Genome-wide copy number analysis of single cells

Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ∼3 d from flow cytometry to sequence-ready DNA libraries.

Rapid Phenotypic and Genomic Change in Response to Therapeutic Pressure in Prostate Cancer Inferred by High Content Analysis of Single Circulating Tumor Cells

Timely characterization of a cancers evolution is required to predict treatment efficacy and to detect resistance early. High content analysis of single Circulating Tumor Cells (CTCs) enables sequential characterization of genotypic, morphometric and protein expression alterations in real time over the course of cancer treatment. This concept was investigated in a patient with castrate-resistant prostate cancer progressing through both chemotherapy and targeted therapy. In this case study, we integrate across four timepoints 41 genome-wide copy number variation (CNV) profiles plus morphometric parameters and androgen receptor (AR) protein levels. Remarkably, little change was observed in response to standard chemotherapy, evidenced by the fact that a unique clone (A), exhibiting highly rearranged CNV profiles and AR+ phenotype was found circulating before and after treatment. However, clinical response and subsequent progression after targeted therapy was associated with the drastic depletion of clone A, followed by the sequential emergence of two distinct CTC sub-populations that differed in both AR genotype and expression phenotype. While AR- cells with flat or pseudo-diploid CNV profiles (clone B) were identified at the time of response, a new tumor lineage of AR+ cells (clone C) with CNV altered profiles was detected during relapse. We showed that clone C, despite phylogenetically related to clone A, possessed a unique set of somatic CNV alterations, including MYC amplification, an event linked to hormone escape. Interesting, we showed that both clones acquired AR gene amplification by deploying different evolutionary paths. Overall, these data demonstrate the timeframe of tumor evolution in response to therapy and provide a framework for the multi-scale analysis of fluid biopsies to quantify and monitor disease evolution in individual patients.

Interactive analysis and assessment of single-cell copy-number variations.

We present Ginkgo (http://qb.cshl.edu/ginkgo), a user-friendly, open-source web platform for the analysis of single-cell copy-number variations (CNVs). Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells. We validated Ginkgo by reproducing the results of five major studies. After comparing three commonly used single-cell amplification techniques, we concluded that degenerate oligonucleotide-primed PCR is the most consistent for CNV analysis.

Optimizing sparse sequencing of single cells for highly multiplex copy number profiling

Genome-wide analysis at the level of single cells has recently emerged as a powerful tool to dissect genome heterogeneity in cancer, neurobiology, and development. To be truly transformative, single-cell approaches must affordably accommodate large numbers of single cells. This is feasible in the case of copy number variation (CNV), because CNV determination requires only sparse sequence coverage. We have used a combination of bioinformatic and molecular approaches to optimize single-cell DNA amplification and library preparation for highly multiplexed sequencing, yielding a method that can produce genome-wide CNV profiles of up to a hundred individual cells on a single lane of an Illumina HiSeq instrument. We apply the method to human cancer cell lines and biopsied cancer tissue, thereby illustrating its efficiency, reproducibility, and power to reveal underlying genetic heterogeneity and clonal phylogeny. The capacity of the method to facilitate the rapid profiling of hundreds to thousands of single-cell genomes represents a key step in making single-cell profiling an easily accessible tool for studying cell lineage.

Deletions linked to TP53 loss drive cancer through p53-independent mechanisms

Mutations disabling the TP53 tumour suppressor gene represent the most frequent events in human cancer and typically occur through a two-hit mechanism involving a missense mutation in one allele and a ‘loss of heterozygosity’ deletion encompassing the other. While TP53 missense mutations can also contribute gain-of-function activities that impact tumour progression, it remains unclear whether the deletion event, which frequently includes many genes, impacts tumorigenesis beyond TP53 loss alone. Here we show that somatic heterozygous deletion of mouse chromosome 11B3, a 4-megabase region syntenic to human 17p13.1, produces a greater effect on lymphoma and leukaemia development than Trp53 deletion. Mechanistically, the effect of 11B3 loss on tumorigenesis involves co-deleted genes such as Eif5a and Alox15b (also known as Alox8), the suppression of which cooperates with Trp53 loss to produce more aggressive disease. Our results imply that the selective advantage produced by human chromosome 17p deletion reflects the combined impact of TP53 loss and the reduced dosage of linked tumour suppressor genes.

The Genomic Landscape of Male Breast Cancers

Purpose: Male breast cancer is rare, and its genomic landscape has yet to be fully characterized. Lacking studies in men, treatment of males with breast cancer is extrapolated from results in females with breast cancer. We sought to define whether male breast cancers harbor somatic genetic alterations in genes frequently altered in female breast cancers. Experimental Design: All male breast cancers were estrogen receptor–positive, and all but two were HER2-negative. Fifty-nine male breast cancers were subtyped by immunohistochemistry, and tumor–normal pairs were microdissected and subjected to massively parallel sequencing targeting all exons of 241 genes frequently mutated in female breast cancers or DNA-repair related. The repertoires of somatic mutations and copy number alterations of male breast cancers were compared with that of subtype-matched female breast cancers. Results: Twenty-nine percent and 71% of male breast cancers were immunohistochemically classified as luminal A–like or luminal B–like, respectively. Male breast cancers displayed a heterogeneous repertoire of somatic genetic alterations that to some extent recapitulated that of estrogen receptor (ER)-positive/HER2-negative female breast cancers, including recurrent mutations affecting PIK3CA (20%) and GATA3 (15%). ER-positive/HER2-negative male breast cancers, however, less frequently harbored 16q losses, and PIK3CA and TP53 mutations than ER-positive/HER2-negative female breast cancers. In addition, male breast cancers were found to be significantly enriched for mutations affecting DNA repair–related genes. Conclusions: Male breast cancers less frequently harbor somatic genetic alterations typical of ER-positive/HER2-negative female breast cancers, such as PIK3CA and TP53 mutations and losses of 16q, suggesting that at least a subset of male breast cancers are driven by a distinct repertoire of somatic changes. Given the genomic differences, caution may be needed in the application of biologic and therapeutic findings from studies of female breast cancers to male breast cancers. Clin Cancer Res; 22(16); 4045–56. ©2016 AACR.

Transplantation of engineered organoids enables rapid generation of metastatic mouse models of colorectal cancer

Colorectal cancer (CRC) is a leading cause of death in the developed world, yet facile preclinical models that mimic the natural stages of CRC progression are lacking. Through the orthotopic engraftment of colon organoids we describe a broadly usable immunocompetent CRC model that recapitulates the entire adenoma–adenocarcinoma–metastasis axis in vivo. The engraftment procedure takes less than 5 minutes, shows efficient tumor engraftment in two-thirds of mice, and can be achieved using organoids derived from genetically engineered mouse models (GEMMs), wild-type organoids engineered ex vivo, or from patient-derived human CRC organoids. In this model, we describe the genotype and time-dependent progression of CRCs from adenocarcinoma (6 weeks), to local disseminated disease (11–12 weeks), and spontaneous metastasis (>20 weeks). Further, we use the system to show that loss of dysregulated Wnt signaling is critical for the progression of disseminated CRCs. Thus, our approach provides a fast and flexible means to produce tailored CRC mouse models for genetic studies and pre-clinical investigation.

An approach to suppress the evolution of resistance in BRAFV600E-mutant cancer

The principles that govern the evolution of tumors exposed to targeted therapy are poorly understood. Here we modeled the selection and propagation of an amplification in the BRAF oncogene (BRAFamp) in patient-derived tumor xenografts (PDXs) that were treated with a direct inhibitor of the kinase ERK, either alone or in combination with other ERK signaling inhibitors. Single-cell sequencing and multiplex fluorescence in situ hybridization analyses mapped the emergence of extra-chromosomal amplification in parallel evolutionary trajectories that arose in the same tumor shortly after treatment. The evolutionary selection of BRAFamp was determined by the fitness threshold, the barrier that subclonal populations need to overcome to regain fitness in the presence of therapy. This differed for inhibitors of ERK signaling, suggesting that sequential monotherapy is ineffective and selects for a progressively higher BRAF copy number. Concurrent targeting of the RAF, MEK and ERK kinases, however, imposed a sufficiently high fitness threshold to prevent the propagation of subclones with high-level BRAFamp. When administered on an intermittent schedule, this treatment inhibited tumor growth in 11/11 PDXs of lung cancer or melanoma without apparent toxicity in mice. Thus, gene amplification can be acquired and expanded through parallel evolution, enabling tumors to adapt while maintaining their intratumoral heterogeneity. Treatments that impose the highest fitness threshold will likely prevent the evolution of resistance-causing alterations and, thus, merit testing in patients.

Whole-genome single-cell copy number profiling from formalin-fixed paraffin-embedded samples

A substantial proportion of tumors consist of genotypically distinct subpopulations of cancer cells. This intratumor genetic heterogeneity poses a substantial challenge for the implementation of precision medicine. Single-cell genomics constitutes a powerful approach to resolve complex mixtures of cancer cells by tracing cell lineages and discovering cryptic genetic variations that would otherwise be obscured in tumor bulk analyses. Because of the chemical alterations that result from formalin fixation, single-cell genomic approaches have largely remained limited to fresh or rapidly frozen specimens. Here we describe the development and validation of a robust and accurate methodology to perform whole-genome copy-number profiling of single nuclei obtained from formalin-fixed paraffin-embedded clinical tumor samples. We applied the single-cell sequencing approach described here to study the progression from in situ to invasive breast cancer, which revealed that ductal carcinomas in situ show intratumor genetic heterogeneity at diagnosis and that these lesions may progress to invasive breast cancer through a variety of evolutionary processes.

Single cell sequencing approaches for complex biological systems.

Biological phenotype is the output of complex interactions between heterogeneous cells within a specified niche. These interactions are tightly governed and regulated by the genetic, epigenetic, and transcriptional states of single cells, with deregulation of these states resulting in disease. As such, genome wide single cell investigations are bound to enhance our knowledge of the underlying principles that govern biological systems. Recent technological advances have enabled such investigations in the form of single-cell sequencing. Here, we review the most recent developments in genome wide profiling of single cells, discuss some of the novel biological observations gleaned by such investigations, and touch upon the promise of single cell sequencing in unraveling biological systems.