Single-cell RNA-Seq of follicular lymphoma reveals malignant B-cell types and coexpression of T-cell immune checkpoints.

Follicular lymphoma (FL) is a low-grade B-cell malignancy that transforms into a highly aggressive and lethal disease at a rate of 2% per year. Perfect isolation of the malignant B-cell population from a surgical biopsy is a significant challenge, masking important FL biology, such as immune checkpoint coexpression patterns. To resolve the underlying transcriptional networks of follicular B-cell lymphomas, we analyzed the transcriptomes of 34 188 cells derived from 6 primary FL tumors. For each tumor, we identified normal immune subpopulations and malignant B cells, based on gene expression. We used multicolor flow cytometry analysis of the same tumors to confirm our assignments of cellular lineages and validate our predictions of expressed proteins. Comparison of gene expression between matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin (Ig) light chain expression (either Igκ or Igλ), as well the expected upregulation of the BCL2 gene, but also downregulation of the FCER2, CD52, and major histocompatibility complex class II genes. By analyzing thousands of individual cells per patient tumor, we identified the mosaic of malignant B-cell subclones that coexist within a FL and examined the characteristics of tumor-infiltrating T cells. We identified genes coexpressed with immune checkpoint molecules, such as CEBPA and B2M in regulatory T (Treg) cells, providing a better understanding of the gene networks involved in immune regulation. In summary, parallel measurement of single-cell expression in thousands of tumor cells and tumor-infiltrating lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

Identification of large rearrangements in cancer genomes with barcode linked reads.

Large genomic rearrangements involve inversions, deletions and other structural changes that span Megabase segments of the human genome. This category of genetic aberration is the cause of many hereditary genetic disorders and contributes to pathogenesis of diseases like cancer. We developed a new algorithm called ZoomX for analysing barcode-linked sequence reads-these sequences can be traced to individual high molecular weight DNA molecules (>50 kb). To generate barcode linked sequence reads, we employ a library preparation technology (10X Genomics) that uses droplets to partition and barcode DNA molecules. Using linked read data from whole genome sequencing, we identify large genomic rearrangements, typically greater than 200kb, even when they are only present in low allelic fractions. Our algorithm uses a Poisson scan statistic to identify genomic rearrangement junctions, determine counts of junction-spanning molecules and calculate a Fisher's exact test for determining statistical significance for somatic aberrations. Utilizing a well-characterized human genome, we benchmarked this approach to accurately identify large rearrangement. Subsequently, we demonstrated that our algorithm identifies somatic rearrangements when present in lower allelic fractions as occurs in tumors. We characterized a set of complex cancer rearrangements with multiple classes of structural aberrations and with possible roles in oncogenesis.

Chromosome-scale mega-haplotypes enable digital karyotyping of cancer aneuploidy.

Genomic instability is a frequently occurring feature of cancer that involves large-scale structural alterations. These somatic changes in chromosome structure include duplication of entire chromosome arms and aneuploidy where chromosomes are duplicated beyond normal diploid content. However, the accurate determination of aneuploidy events in cancer genomes is a challenge. Recent advances in sequencing technology allow the characterization of haplotypes that extend megabases along the human genome using high molecular weight (HMW) DNA. For this study, we employed a library preparation method in which sequence reads have barcodes linked to single HMW DNA molecules. Barcode-linked reads are used to generate extended haplotypes on the order of megabases. We developed a method that leverages haplotypes to identify chromosomal segmental alterations in cancer and uses this information to join haplotypes together, thus extending the range of phased variants. With this approach, we identified mega-haplotypes that encompass entire chromosome arms. We characterized the chromosomal arm changes and aneuploidy events in a manner that offers similar information as a traditional karyotype but with the benefit of DNA sequence resolution. We applied this approach to characterize aneuploidy and chromosomal alterations from a series of primary colorectal cancers.

Robust Multiplexed Clustering and Denoising of Digital PCR Assays by Data Gridding.

Digital PCR (dPCR) relies on the analysis of individual partitions to accurately quantify nucleic acid species. The most widely used analysis method requires manual clustering through individual visual inspection. Some automated analysis methods have emerged but do not robustly account for multiplexed targets, low target concentration, and assay noise. In this study, we describe an open source analysis software called Calico that uses "data gridding" to increase the sensitivity of clustering toward small clusters. Our workflow also generates quality score metrics in order to gauge and filter individual assay partitions by how well they were classified. We applied our analysis algorithm to multiplexed droplet-based digital PCR data sets in both EvaGreen and probes-based schemes, and targeted the oncogenic BRAF V600E and KRAS G12D mutations. We demonstrate an automated clustering sensitivity of down to 0.1% mutant fraction and filtering of artifactual assay partitions from low quality DNA samples. Overall, we demonstrate a vastly improved approach to analyzing ddPCR data that can be applied to clinical use, where automation and reproducibility are critical.

Therapeutic Monitoring of Circulating DNA Mutations in Metastatic Cancer with Personalized Digital PCR.

As a high-performance solution for longitudinal monitoring of patients being treated for metastatic cancer, a single-color digital PCR (dPCR) assay that detects and quantifies specific cancer mutations present in circulating tumor DNA (ctDNA) was developed. This customizable assay has a high sensitivity of detection. One can detect a mutation allelic fraction of 0.1%, equivalent to three mutation-bearing DNA molecules among 3000 genome equivalents. The objective of this study was to validate the use of personalized dPCR mutation assays to monitor patients with metastatic cancer. The dPCR results were compared with serum biomarkers indicating disease progression or response. Patients had metastatic colorectal, biliary, breast, lung, and melanoma cancers. Mutations occurred in essential cancer drivers such as BRAF, KRAS, and PIK3CA. Patients were monitored over multiple cycles of treatment for up to a year. All patients had detectable ctDNA mutations. The results correlated with serum markers of metastatic cancer burden, including carcinoembryonic antigen, CA-19-9, and CA-15-3, and qualitatively corresponding to imaging studies. Corresponding trends were observed among these patients receiving active treatment with chemotherapy or targeted agents. For example, in one patient under active treatment, increasing quantities of ctDNA molecules were detected over time, indicating recurrence of tumor. This study demonstrates that personalized dPCR enables longitudinal monitoring of patients with metastatic cancer and may be a useful indicator for treatment response.

Whole genome analysis identifies the association of TP53 genomic deletions with lower survival in Stage III colorectal cancer.

DNA copy number aberrations (CNA) are frequently observed in colorectal cancers (CRC). There is an urgent need for CNA-based biomarkers in clinics,. n For Stage III CRC, if combined with imaging or pathologic evidence, these markers promise more precise care. We conducted this Stage III specific biomarker discovery with a cohort of 134 CRCs, and with a newly developed high-efficiency CNA profiling protocol. Specifically, we developed the profiling protocol for tumor-normal matched tissue samples based on low-coverage clinical whole-genome sequencing (WGS). We demonstrated the protocol's accuracy and robustness by a systematic benchmark with microarray, high-coverage whole-exome and -genome approaches, where the low-coverage WGS-derived CNA segments were highly accordant (PCC >0.95) with those derived from microarray, and they were substantially less variable if compared to exome-derived segments. A lasso-based model and multivariate cox regression analysis identified a chromosome 17p loss, containing the TP53 tumor suppressor gene, that was significantly associated with reduced survival (P = 0.0139, HR = 1.688, 95% CI = [1.112-2.562]), which was validated by an independent cohort of 187 Stage III CRCs. In summary, this low-coverage WGS protocol has high sensitivity, high resolution and low cost and the identified 17p-loss is an effective poor prognosis marker for Stage III patients.

Single-cell transcriptome analysis identifies distinct cell types and niche signaling in a primary gastric organoid model.

The diverse cellular milieu of the gastric tissue microenvironment plays a critical role in normal tissue homeostasis and tumor development. However, few cell culture model can recapitulate the tissue microenvironment and intercellular signaling in vitro. We used a primary tissue culture system to generate a murine p53 null gastric tissue model containing both epithelium and mesenchymal stroma. To characterize the microenvironment and niche signaling, we used single cell RNA sequencing (scRNA-Seq) to determine the transcriptomes of 4,391 individual cells. Based on specific markers, we identified epithelial cells, fibroblasts and macrophages in initial tissue explants during organoid formation. The majority of macrophages were polarized towards wound healing and tumor promotion M2-type. During the course of time, the organoids maintained both epithelial and fibroblast lineages with the features of immature mouse gastric stomach. We detected a subset of cells in both lineages expressing Lgr5, one of the stem cell markers. We examined the lineage-specific Wnt signaling activation, and identified that Rspo3 was specifically expressed in the fibroblast lineage, providing an endogenous source of the R-spondin to activate Wnt signaling. Our studies demonstrate that this primary tissue culture system enables one to study gastric tissue niche signaling and immune response in vitro.

Single Color Multiplexed ddPCR Copy Number Measurements and Single Nucleotide Variant Genotyping.

Droplet digital PCR (ddPCR) allows for accurate quantification of genetic events such as copy number variation and single nucleotide variants. Probe-based assays represent the current "gold-standard" for detection and quantification of these genetic events. Here, we introduce a cost-effective single color ddPCR assay that allows for single genome resolution quantification of copy number and single nucleotide variation.

Single-Color Digital PCR Provides High-Performance Detection of Cancer Mutations from Circulating DNA.

We describe a single-color digital PCR assay that detects and quantifies cancer mutations directly from circulating DNA collected from the plasma of cancer patients. This approach relies on a double-stranded DNA intercalator dye and paired allele-specific DNA primer sets to determine an absolute count of both the mutation and wild-type-bearing DNA molecules present in the sample. The cell-free DNA assay uses an input of 1 ng of nonamplified DNA, approximately 300 genome equivalents, and has a molecular limit of detection of three mutation DNA genome-equivalent molecules per assay reaction. When using more genome equivalents as input, we demonstrated a sensitivity of 0.10% for detecting the BRAF V600E and KRAS G12D mutations. We developed several mutation assays specific to the cancer driver mutations of patients' tumors and detected these same mutations directly from the nonamplified, circulating cell-free DNA. This rapid and high-performance digital PCR assay can be configured to detect specific cancer mutations unique to an individual cancer, making it a potentially valuable method for patient-specific longitudinal monitoring.

Linked read sequencing resolves complex genomic rearrangements in gastric cancer metastases.

BACKGROUND: Genome rearrangements are critical oncogenic driver events in many malignancies. However, the identification and resolution of the structure of cancer genomic rearrangements remain challenging even with whole genome sequencing. METHODS: To identify oncogenic genomic rearrangements and resolve their structure, we analyzed linked read sequencing. This approach relies on a microfluidic droplet technology to produce libraries derived from single, high molecular weight DNA molecules, 50 kb in size or greater. After sequencing, the barcoded sequence reads provide long range genomic information, identify individual high molecular weight DNA molecules, determine the haplotype context of genetic variants that occur across contiguous megabase-length segments of the genome and delineate the structure of complex rearrangements. We applied linked read sequencing of whole genomes to the analysis of a set of synchronous metastatic diffuse gastric cancers that occurred in the same individual. RESULTS: When comparing metastatic sites, our analysis implicated a complex somatic rearrangement that was present in the metastatic tumor. The oncogenic event associated with the identified complex rearrangement resulted in an amplification of the known cancer driver gene FGFR2. With further investigation using these linked read data, the FGFR2 copy number alteration was determined to be a deletion-inversion motif that underwent tandem duplication, with unique breakpoints in each metastasis. Using a three-dimensional organoid tissue model, we functionally validated the metastatic potential of an FGFR2 amplification in gastric cancer. CONCLUSIONS: Our study demonstrates that linked read sequencing is useful in characterizing oncogenic rearrangements in cancer metastasis.