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White Papers and Videos

Single-Cell DNA Sequencing Resolves the Genetic Complexity Underlying Chronic Lymphocytic Leukemia Progression

White Paper

High-count monoclonal B-cell lymphocytosis (MBL) is an asymptomatic state that can evolve into chronic lymphocytic leukemia (CLL) when B-cells gain a cancer-inducing combination of driver mutations. In a recently published study, MBL patient samples were analyzed using bulk targeted deep sequencing. The researchers found that in a subset of cases, there were a significant number of mutations — in many cases, affecting the same genes.

To further gain insights into these MBL patient samples, single-cell DNA sequencing was performed on them using the Mission Bio Tapestri Platform and a 33-gene CLL amplicon panel. This application note shows that previously generated data from bulk sequencing were highly correlative to the newly generated single-cell data. The researchers unambiguously resolved co-occurrence and zygosity of all detected mutations to track clonal evolution and population expansion over time. These results show that single-cell DNA sequencing is a powerful tool for resolving clonal heterogeneity.

Single-Cell DNA Analysis With the Tapestri Platform and Nuclei From Metastatic Melanoma Tissue

White Paper

Recent advancements in genomic analysis of tumors have revealed that cancer disease evolves by a reiterative process of somatic variation, clonal expansion, and selection. Therefore, intra- and inter-tumor genomic heterogeneity has become a major area of investigation. While bulk next-generation sequencing methods have significantly contributed to our understanding of cancer biology and genomics, they overlook the genetic heterogeneity of a tumor at the level of the individual cell.

Here, the use of the Mission Bio Tapestri Platform demonstrates the power of single-cell, targeted DNA sequencing in characterizing solid tumor tissue samples and understanding disease evolution. Single-cell targeted DNA analysis was performed with the Tapestri Platform using sectioned melanoma metastatic tissues and normal liver tissue. An analysis of samples from separate metastatic sites in a single subject revealed unique genomic signatures in each sample.

Single-Cell DNA Analysis of Myelodysplastic Syndrome Using the Tapestri Single-Cell DNA AML Panel

White Paper

Myelodysplastic syndrome (MDS) is brought on by an accumulation of somatic mutations in hematopoietic stem cells resulting in ineffective hematopoiesis. Distinguishing mutational status at the single-cell level offers precision in diagnosis and informs treatment options, and clonal lineage reconstruction provides a comprehensive picture of the disease progression. MDS and acute myeloid leukemia (AML) are both myeloid disorders and can share overlapping molecular signatures.

In this technical note, the Tapestri Single-cell DNA AML Panel was used to analyze the mutational landscape of two patients with myelodysplastic syndrome (MDS). The results showed high sensitivity, clonal resolution, and concordance of variant allele frequency between single-cell and bulk next-generation sequencing data. Additionally, clonal variant co-occurrence was resolved, allowing for clonal lineage reconstruction and a more comprehensive picture of the patients’ disease.

Copy Number Variants and Single Nucleotide Variants Simultaneously Detected in Single Cells

White Paper

Cancer begins with mutations in the DNA of a single cell. These mutations are often caused by single nucleotide variants (SNVs) and gene copy number variants (CNVs). Differences in SNVs and CNVs contribute to cancer heterogeneity, making some clonal populations more virulent and drug-resistant than others. Accurately defining clonal populations and reconstructing clonal phylogenies can only be achieved through single-cell analysis and is critical for informed clinical research. This application note describes a study demonstrating the ability of the Tapestri Platform to detect CNVs and SNVs simultaneously in single cells from cancer cell lines.

Tapestri Platform Resolves Clonality of Heterogeneous Mouse Organoid Cancer Model Through Single-Cell DNA Sequencing of Lentiviral Barcodes

White Paper

Bladder cancer exhibits high genomic heterogeneity, with an average of five mutations or more in the same tumor. Studying diverse higher-order genetic interactions that drive bladder cancer is difficult with current models of tumorigenesis, and it is limited by bulk sequencing which fails to directly discern clonality and resolve mutational co-occurrence patterns.

Dr. John Lee, of Fred Hutchinson Cancer Center, sought to better understand which combinations of mutations were critical by leveraging a mouse model, organoids, and gene-editing approaches. Using single-cell DNA sequencing, the Lee lab developed a system for investigating the functional impact of higher-order genetic interactions in cancer.

Optimizing Performance of Whole Transcriptome RNA-Seq Reference Materials

White Paper

Whole-transcriptome RNA-seq is one of the most effective methods for detecting genomic rearrangements in cancer. Enriching RNA samples with messenger RNA (mRNA) is an important step in sample preparation to avoid the muddling effects of less relevant RNAs. Poly-A selection targets the poly-A tails of mRNAs by binding them to oligo-dT sequences, but capture is not always optimal.

This whitepaper describes a study investigating whether extending the poly-A tails of clinically relevant fusion mRNAs in the Seraseq Fusion RNA Mix v4 reference material improves how efficiently they bind to oligo-dT columns during poly-A selection. The researchers found modest improvements in performance of reference materials after increasing the poly-A tail length.

Reference Materials for Tumor Mutational Burden Transcriptome Profiling

White Paper

Tumor mutational burden (TMB) predicts the response of some tumor types to immune checkpoint inhibitor therapy. However, TMB is an imperfect biomarker as some patients respond conversely to expectation. One partial explanation for the observed discrepancies is that some or many of the mutations contributing to TMB are not expressed and do not produce neoantigens.

This whitepaper from SeraCare compares TMB as measured by whole-exome sequencing with expression of TMB mutations in whole-transcriptome sequences. The study authors compared two library prep techniques, differing mainly in their ribodepletion methods. They found that the resulting whole-transcriptome libraries showed reproducibility within and between methods, and that approximately half of the TMB mutations called by exome sequencing have no or very little expression in the tumor cell lines assessed.

Development and Verification of the HTG EdgeSeq Reveal Immune, Stroma and TME Signatures

White Paper

Immune response to a malignant tumor is a known indicator in predicting patient response to therapy. Historically, tumor immune response has been characterized using immunohistochemistry, but, more recently, gene expression profiling based on next-generation sequencing has emerged as an alternative to classify a tumor’s inflammation status.

This white paper describes the development and verification of three new oncology signatures for classifying a tumor’s inflammation status: the HTG EdgeSeq Reveal Immune, Stroma, and Tumor Microenvironment signatures. These signatures are built upon the HTG EdgeSeq research use only Precision ImmunoOncology Panel. The data presented demonstrate that the HTG EdgeSeq Immune, Stroma, and TME scores offer an accurate and robust method for determining the inflammation and stroma status of tumor FFPE samples.

Drop-off Crystal Digital PCR for NRAS, KRAS, & EGFR Mutations

White Paper

A major advantage of a drop-off digital PCR is the single-assay detection of multiple proximal genetic lesions (including deletions, insertions, and nucleotide substitutions) within a short genomic interval.

This application note describes a study that used Crystal Digital PCR to design and validate three internally controlled drop-off assays for the detection of seven KRAS mutations, four NRAS mutations, and a range of EGFR exon 19 deletions/insertions commonly monitored in clinical practice.

3-Color Crystal Digital PCR Assays for EGFR Mutation Detection

White Paper

In non-small cell lung cancer (NSCLC), EGFR activating mutations, such as L858R, L861Q, and exon 19 deletions, are predictive of disease responsiveness to targeted therapy using tyrosine kinase inhibitors, while the presence of the EGFR T790M mutation is associated with tumor resistance to TKIs.

This application note outlines the development of two multiplex digital PCR assays to detect and quantify these mutations in single tests without sacrificing the precision and reliability of the results. The two 3-color digital PCR panels were evaluated on mutant DNA extracted from NSCLC patients and compared to next generation sequencing measurements. The measured mutant allelic EGFR fractions displayed a strong correlation.

Detection of Hypermethylated Circulating Tumor DNA by Crystal Digital PCR

White Paper

In colorectal cancer, hypermethylation of WNT inhibitory factor 1 (WIF1) and neuropeptide T (NPY) was found in 80 percent and 44.7 percent of metastatic and stage II/III patients, respectively.

This application note describes a study that sought to evaluate whether hypermethylated WIF1 and NPY can be used as a universal colorectal cancer marker and a surrogate to tumor sequence-specific mutations.

The method, which combined bisulfite conversion of unmethylated cytosine to uracil, followed by 3-color Crystal Digital PCR, enabled the reliable detection of down to 25 and 5 copies of hypermethylated WIF1 and NPY DNA, respectively, per 25 µl reaction.

COSMIC: Describing Millions of Somatic Mutations at High Resolution Across Forms of Cancer Underpins Precision Oncology Research

Video

COSMIC, the Catalog of Somatic Mutations in Cancer, is a hand-curated database that details more than 71 million somatic mutation events across almost 1.5 million tumor samples.

In this on-demand webinar, Simon Forbes, head of the COSMIC database at the Wellcome Sanger Institute, provides an overview of the core database, as well as specialized component projects that each present a distinct dataset or view of the data, including a 3D interactive view of cancer mutations.

COSMIC now allows users to search for drugs that target somatic mutations at all stages of drug development, including those still in development, in clinical trials, or that have been repurposed.

Biomarker Discovery Research: Cancer Molecular Profiling

White Paper

Research in the discovery and identification of new, targetable biomarkers is driven by comprehensive tumor profiling using NGS. Converting tissue samples into NGS libraries is often challenging due to the low quantity and quality of DNA in such samples.

This application note presents a workflow for sensitive and accurate detection of low-frequency variants that combines the xGen Prism DNA Library Prep Kit with IDT xGen hybridization capture reagents. 

Combining NGS Technologies for Biomarker Identification and Confirmation Research

White Paper

Biomarker characterization in diseases such as cancer can be achieved by combining targeted next-generation sequencing (NGS) enrichment approaches. These techniques can provide a high level of sensitivity and specificity when detecting low levels of variant allele frequencies (VAF) in somatic cancer detection.

This application note describes two high-performing targeted NGS approaches to maximize the ability to identify and confirm germline and somatic mutations. 

BCR-ABL1 Minor Breakpoint (e1a2) Monitoring Using an Analytically Validated Multiplex Assay

White Paper

BCR-ABL1 e1a2 fusion transcript (minor breakpoint) of t(9;22) quantitation is needed to assess tumor burden in Philadelphia chromosome-positive precursor B-cell acute lymphoblastic leukemia (Ph+ B-ALL) and chronic myeloid leukemia (CML). In this poster, we describe the analytical validation of a multiplex system reporting continuous BCR-ABL1:ABL1 % ratio values via automated analysis, which offers deep sensitivity of >4.5 logs of reduction.