Challenges in bioinformatics approaches to tumor mutation burden analysis.

Several immune checkpoint inhibitors (ICIs) have already been introduced into clinical practice or are in advanced phases of clinical experimentation. Extensive efforts are being made to identify robust biomarkers to select patients who may benefit from treatment with ICIs. Tumor mutation burden (TMB) may be a relevant biomarker of response to ICIs in different tumor types; however, its clinical use is challenged by the analytical methods required for its evaluation.

Validation of a Targeted Next-Generation Sequencing Panel for Tumor Mutation Burden Analysis: Results from the Onconetwork Immuno-Oncology Consortium.

Tumor mutation burden (TMB) is evaluated as a biomarker of response to immunotherapy. We present the efforts of the Onconetwork Immuno-Oncology Consortium to validate a commercial targeted sequencing test for TMB calculation. A three-phase study was designed to validate the Oncomine Tumor Mutational Load (OTML) assay at nine European laboratories.

The employment gap: the relationship between medical student career choices and the future needs of the New Zealand medical workforce.

Aims: To determine the career decision intentions of graduating doctors, and the relationship between these intentions and the predicted medical workforce needs in New Zealand in 10 years' time.

Methods: A workforce forecasting model developed by the Ministry of Health (MOH) has been used to predict the proportion of doctors required in each medical specialty in 2028 in New Zealand. The future work intentions of recently graduated doctors at the Universities of Auckland and Otago were collected from the Medical Student Outcomes Data (MSOD), and compared with these predicted needs.

Developing New Zealand's medical workforce: realising the potential of longitudinal career tracking.

For over a decade, the Medical Schools Outcomes Database and Longitudinal Tracking Project (MSOD) has collected data from medical students in Australia and New Zealand. This project aims to explore how individual student background or attributes might interact with curriculum or early postgraduate training to affect eventual career choice and location. In New Zealand, over 4,000 students have voluntarily provided information at various time points, and the project is at a stage where some firm conclusions are starting to be drawn.

A scalable solution for tumor mutational burden from formalin-fixed, paraffin-embedded samples using the Oncomine Tumor Mutation Load Assay.

Background: Tumor mutational burden (TMB) is an increasingly important biomarker for immune checkpoint inhibitors. Recent publications have described strong association between high TMB and objective response to mono- and combination immunotherapies in several cancer types. Existing methods to estimate TMB require large amount of input DNA, which may not always be available.

User involvement in digital health: Working together to design smart home health technology.

Background: Public involvement adds value to numerous aspects of health research, yet few studies have attempted to evaluate its impact on research. Evidence of such impact is needed to develop recommendations for best practice and ensure adequate resourcing.

Aim: To evaluate public involvement within a large interdisciplinary Science, Technology, Engineering and Mathematics (STEM) research project that focused on digital health.

Analytical Validation of a Next-Generation Sequencing Assay to Monitor Immune Responses in Solid Tumors.

We have developed a next-generation sequencing assay to quantify biomarkers of the host immune response in formalin-fixed, paraffin-embedded (FFPE) tumor specimens. This assay aims to provide clinicians with a comprehensive characterization of the immunologic tumor microenvironment as a guide for therapeutic decisions on patients with solid tumors. The assay relies on RNA-sequencing (seq) to semiquantitatively measure the levels of 43 transcripts related to anticancer immune responses and 11 transcripts that reflect the relative abundance of tumor-infiltrating lymphocytes, as well as on DNA-seq to estimate mutational burden.

Principles and Recommendations for Standardizing the Use of the Next-Generation Sequencing Variant File in Clinical Settings.

A national workgroup convened by the Centers for Disease Control and Prevention identified principles and made recommendations for standardizing the description of sequence data contained within the variant file generated during the course of clinical next-generation sequence analysis for diagnosing human heritable conditions. The specifications for variant files were initially developed to be flexible with regard to content representation to support a variety of research applications. This flexibility permits variation with regard to how sequence findings are described and this depends, in part, on the conventions used.

Development and validation of a scalable next-generation sequencing system for assessing relevant somatic variants in solid tumors.

Next-generation sequencing (NGS) has enabled genome-wide personalized oncology efforts at centers and companies with the specialty expertise and infrastructure required to identify and prioritize actionable variants. Such approaches are not scalable, preventing widespread adoption. Likewise, most targeted NGS approaches fail to assess key relevant genomic alteration classes.

Characterizing the heterogeneity of triple-negative breast cancers using microdissected normal ductal epithelium and RNA-sequencing.

Triple-negative breast cancers (TNBCs) are a heterogeneous set of tumors defined by an absence of actionable therapeutic targets (ER, PR, and HER-2). Microdissected normal ductal epithelium from healthy volunteers represents a novel comparator to reveal insights into TNBC heterogeneity and to inform drug development. Using RNA-sequencing data from our institution and The Cancer Genome Atlas (TCGA) we compared the transcriptomes of 94 TNBCs, 20 microdissected normal breast tissues from healthy volunteers from the Susan G.

RNA-Seq mapping and detection of gene fusions with a suffix array algorithm.

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions-particularly those expressed with low abundance- is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software.

SNPs for a universal individual identification panel.

An efficient method to uniquely identify every individual would have value in quality control and sample tracking of large collections of cell lines or DNA as is now often the case with whole genome association studies. Such a method would also be useful in forensics. SNPs represent the best markers for such purposes.

Sequence and structural variation in a human genome uncovered by short-read, massively parallel ligation sequencing using two-base encoding.

We describe the genome sequencing of an anonymous individual of African origin using a novel ligation-based sequencing assay that enables a unique form of error correction that improves the raw accuracy of the aligned reads to >99.9%, allowing us to accurately call SNPs with as few as two reads per allele. We collected several billion mate-paired reads yielding approximately 18x haploid coverage of aligned sequence and close to 300x clone coverage.

Validation of the performance of a comprehensive genotyping assay panel of single nucleotide polymorphisms in drug metabolism enzyme genes.

A class of genes, known as drug metabolism enzymes (DMEs) are responsible for the metabolism and transport of drugs and other xenobiotics. Variation in DME genes most likely accounts for a proportion of the variability in drug response in humans, and may contribute to complex diseases such as cancer (Nebert DW, Dieter MZ. Pharmacology 2000;61:124-135).

A second-generation combined linkage physical map of the human genome.

We have completed a second-generation linkage map that incorporates sequence-based positional information. This new map, the Rutgers Map v.2, includes 28,121 polymorphic markers with physical positions corroborated by recombination-based data.

Patterns of linkage disequilibrium between SNPs in a Sardinian population isolate and the selection of markers for association studies.

Objective: In isolated populations, 'background' linkage disequilibrium (LD) has been shown to extend over large genetic distances. This and their reduced environmental and genetic heterogeneity has stimulated interest in their potential for association mapping. We compared LD unit map distances with pair-wise measurements of LD in a dense single nucleotide polymorphism (SNP) set.

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.

Background: DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions.