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Systematic analysis of more than 5,900 human tumor exomes yields a new genomic classifier of microsatellite instability and insight into its prevalence and biological implications. Microsatellite instability (MSI), the spontaneous loss or gain of nucleotides from repetitive DNA tracts, is a diagnostic phenotype for gastrointestinal, endometrial, and colorectal tumors, yet the landscape of instability events across a wider variety of cancer types remains poorly understood. To explore MSI across malignancies, we examined 5,930 cancer exomes from 18 cancer types at more than 200,000 microsatellite loci and constructed a genomic classifier for MSI. We identified MSI-positive tumors in 14 of the 18 cancer types. We also identified loci that were more likely to be unstable in particular cancer types, resulting in specific instability signatures that involved cancer-associated genes, suggesting that instability patterns reflect selective pressures and can potentially identify novel cancer drivers. We also observed a correlation between survival outcomes and the overall burden of unstable microsatellites, suggesting that MSI may be a continuous, rather than discrete, phenotype that is informative across cancer types. These analyses offer insight into conserved and cancer-specific properties of MSI and reveal opportunities for improved methods of clinical MSI diagnosis and cancer gene discovery.

Key Points MicroRNAs (miRNAs) are small RNAs (∼22 nucleotides long) that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms. miRNA expression profiling is useful for identifying miRNAs that are important in the regulation of a range of processes, including organismal development, tissue differentiation and disease pathology. miRNAs show promise as biomarkers for various diseases. miRNAs are more stable than mRNAs in many specimen types and are more readily measured than proteins. However, sample type, processing and RNA extraction methods can have a substantial impact on the results of miRNA profiling, and therefore quality and quantity assessment is recommended. Biogenesis of miRNAs occurs through multiple steps and includes the intermediate primary miRNA and precursor miRNA forms, as well as post-transcriptional nucleotide additions and deletions, leading to 'isomiRs'. Choice of platform and analysis in miRNA profiling should include consideration of the need to distinguish between different forms of miRNAs. Three main approaches are currently well established for miRNA profiling: quantitative reverse transcription PCR (qRT-PCR), hybridization-based methods (for example, DNA microarrays) and high-throughput sequencing (that is, RNA sequencing). The optimal choice of platform depends on the specific experimental goals. Analysis of miRNA-profiling data typically includes data processing, data quality assessment, data normalization and calculation of differential expression. The optimal approach to data analysis depends on the platform selected and the nature of the experiment. Owing to the important role of microRNAs in gene regulation, profiling repertoires of expressed microRNAs can be informative in basic research and clinical settings. This Review describes the methods that are available for microRNA profiling and considerations for choosing among analytical options. MicroRNAs (miRNAs) are small RNAs that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms in both normal physiological contexts and in disease contexts. miRNA expression profiling is gaining popularity because miRNAs, as key regulators in gene expression networks, can influence many biological processes and also show promise as biomarkers for disease. Technological advances have spawned a multitude of platforms for miRNA profiling, and an understanding of the strengths and pitfalls of different approaches can aid in their effective use. Here, we review the major considerations for carrying out and interpreting results of miRNA-profiling studies.

Heterogeneity in the genomic landscape of metastatic prostate cancer has become apparent through several comprehensive profiling efforts, but little is known about the impact of this heterogeneity on clinical outcome. Here, we report comprehensive genomic and transcriptomic analysis of 429 patients with metastatic castration-resistant prostate cancer (mCRPC) linked with longitudinal clinical outcomes, integrating findings from whole-exome, transcriptome, and histologic analysis. For 128 patients treated with a first-line next-generation androgen receptor signaling inhibitor (ARSI; abiraterone or enzalutamide), we examined the association of 18 recurrent DNA- and RNA-based genomic alterations, including androgen receptor (AR) variant expression, AR transcriptional output, and neuroendocrine expression signatures, with clinical outcomes. Of these, only RB1 alteration was significantly associated with poor survival, whereas alterations in RB1, AR, and TP53 were associated with shorter time on treatment with an ARSI. This large analysis integrating mCRPC genomics with histology and clinical outcomes identifies RB1 genomic alteration as a potent predictor of poor outcome, and is a community resource for further interrogation of clinical and molecular associations.

Circulating, cell-free microRNAs (miRNAs) are promising candidate biomarkers, but optimal conditions for processing blood specimens for miRNA measurement remain to be established. Our previous work showed that the majority of plasma miRNAs are likely blood cell-derived. In the course of profiling lung cancer cases versus healthy controls, we observed a broad increase in circulating miRNA levels in cases compared to controls and that higher miRNA expression correlated with higher platelet and particle counts. We therefore hypothesized that the quantity of residual platelets and microparticles remaining after plasma processing might impact miRNA measurements. To systematically investigate this, we subjected matched plasma from healthy individuals to stepwise processing with differential centrifugation and 0.22 µm filtration and performed miRNA profiling. We found a major effect on circulating miRNAs, with the majority (72%) of detectable miRNAs substantially affected by processing alone. Specifically, 10% of miRNAs showed 4-30x variation, 46% showed 30-1,000x variation, and 15% showed >1,000x variation in expression solely from processing. This was predominantly due to platelet contamination, which persisted despite using standard laboratory protocols. Importantly, we show that platelet contamination in archived samples could largely be eliminated by additional centrifugation, even in frozen samples stored for six years. To minimize confounding effects in microRNA biomarker studies, additional steps to limit platelet contamination for circulating miRNA biomarker studies are necessary. We provide specific practical recommendations to help minimize confounding variation attributable to plasma processing and platelet contamination.

Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped. We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci. We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing. NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

MicroRNAs (miRNAs) circulate in the bloodstream in a highly stable, extracellular form and are being developed as blood-based biomarkers for cancer and other diseases. However, the mechanism underlying their remarkable stability in the RNase-rich environment of blood is not well understood. The current model in the literature posits that circulating miRNAs are protected by encapsulation in membrane-bound vesicles such as exosomes, but this has not been systematically studied. We used differential centrifugation and size-exclusion chromatography as orthogonal approaches to characterize circulating miRNA complexes in human plasma and serum. We found, surprisingly, that the majority of circulating miRNAs cofractionated with protein complexes rather than with vesicles. miRNAs were also sensitive to protease treatment of plasma, indicating that protein complexes protect circulating miRNAs from plasma RNases. Further characterization revealed that Argonaute2 (Ago2), the key effector protein of miRNA-mediated silencing, was present in human plasma and eluted with plasma miRNAs in size-exclusion chromatography. Furthermore, immunoprecipitation of Ago2 from plasma readily recovered non-vesicle-associated plasma miRNAs. The majority of miRNAs studied copurified with the Ago2 ribonucleoprotein complex, but a minority of specific miRNAs associated predominantly with vesicles. Our results reveal two populations of circulating miRNAs and suggest that circulating Ago2 complexes are a mechanism responsible for the stability of plasma miRNAs. Our study has important implications for the development of biomarker approaches based on capture and analysis of circulating miRNAs. In addition, identification of extracellular Ago2-miRNA complexes in plasma raises the possibility that cells release a functional miRNA-induced silencing complex into the circulation.

A hypermutated subtype of advanced prostate cancer was recently described, but prevalence and mechanisms have not been well-characterized. Here we find that 12% (7 of 60) of advanced prostate cancers are hypermutated, and that all hypermutated cancers have mismatch repair gene mutations and microsatellite instability (MSI). Mutations are frequently complex MSH2 or MSH6 structural rearrangements rather than MLH1 epigenetic silencing. Our findings identify parallels and differences in the mechanisms of hypermutation in prostate cancer compared with other MSI-associated cancers. Several patients with metastatic prostate cancer have been shown to harbour tumours with markedly high mutation rates. Here, the authors characterise hypermutation in advanced prostate cancer samples and show that these samples have somatic mismatch repair gene mutations and microsatellite instability.

The U.S. Food and Drug Administration (FDA) recently approved pembrolizumab, an anti- programmed cell death protein 1 cancer immunotherapeutic, for use in advanced solid tumors in patients with the microsatellite-high/DNA mismatch repair-deficient biomarker. This is the first example of a tissue-agnostic FDA approval of a treatment based on a patient’s tumor biomarker status, rather than on tumor histology. Here we discuss key issues and implications arising from the biomarker-based disease classification implied by this historic approval.

Universal screening for Lynch syndrome in colorectal cancer is recommended, and immunohistochemistry for the mismatch repair proteins is commonly used. To reduce cost, some screen using only MSH6 and PMS2, with reflex to the partner stain if either are absent (two-stain method). An expression pattern revealing absent MSH2 and intact MSH6 is not expected, but could result in failed Lynch syndrome detection. We analyzed tumors with absent MSH2 but any degree of MSH6 expression to determine if the two-stain method could miss MSH2 mutations. One-thousand seven-hundred thirty colorectal cancer patients from the Ohio Colorectal Cancer Prevention Initiative underwent tumor screening using microsatellite instability and immunohistochemistry. The two-stain method was used for 1235 cases; staining for all four proteins was completed for 495 cases. The proportion of positive cells and staining intensity were reviewed for MSH6, as well as MSH2 when available. Patients with mismatch repair deficiency underwent next-generation sequencing of germline DNA for mismatch repair genes. If negative, tumor next-generation sequencing was performed to assess for somatic mutations. Overall, thirty-three (1.9%, 33/1730) MSH2-absent cases were identified. Of those, fourteen had no MSH6 expression but eight (0.5%, 8/1730) had ambiguous and eleven (0.6%, 11/1730) had convincing MSH6 expression that could have been interpreted as intact. Germline next-generation sequencing identified MSH2 mutations in 11/14 cases with absence of both stains, 7/8 cases with ambiguous MSH6 expression, and 9/11 cases with convincing MSH6 expression. All remaining cases, except one, had double somatic mutations. The two-stain method fails to detect some patients with Lynch syndrome: (1) significant staining weaker than the control may be incorrectly interpreted as intact MSH6, or (2) Weak or focal/patchy MSH6 can be retained with the absence of MSH2. Accordingly, we recommend the four-stain method be used for optimal Lynch syndrome screening detection.