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The hallmark of human cancer is heterogeneity, reflecting the complexity and variability of the vast array of somatic mutations acquired during oncogenesis. An ability to dissect this heterogeneity, to identify subgroups that represent common mechanisms of disease, will be critical to understanding the complexities of genetic alterations and to provide a framework to develop rational therapeutic strategies. Here, we describe a classification scheme for human breast cancer making use of patterns of pathway activity to build on previous subtype characterizations using intrinsic gene expression signatures, to provide a functional interpretation of the gene expression data that can be linked to therapeutic options. We show that the identified subgroups provide a robust mechanism for classifying independent samples, identifying tumors that share patterns of pathway activity and exhibit similar clinical and biological properties, including distinct patterns of chromosomal alterations that were not evident in the heterogeneous total population of tumors. We propose that this classification scheme provides a basis for understanding the complex mechanisms of oncogenesis that give rise to these tumors and to identify rational opportunities for combination therapies.

The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 cancer-related genes. Independent analyses of clinically and biologically relevant sequence changes across 170 clinical tumor samples using MSK-IMPACT, FoundationOne, and PCR-based methods reveals a positive percent agreement of >97%. We observe high concordance with whole-exome sequencing for evaluation of tumor mutational burden for 307 solid tumors (Pearson r = 0.95) and comparison of the elio tissue complete microsatellite instability detection approach with an independent PCR assay for 223 samples displays a positive percent agreement of 99%. Finally, evaluation of amplifications and translocations against DNA- and RNA-based approaches exhibits >98% negative percent agreement and positive percent agreement of 86% and 82%, respectively. These methods provide an approach for pan-solid tumor comprehensive genomic profiling with high analytical performance. The genomic profiling of tumours has not been widely adopted in the clinic due to technical and practical hurdles. Here, the authors develop PGDx elio tissue complete, a scalable, standardised and FDA-cleared test comprising a targeted gene panel and automated machine-learning analysis, which detects clinically relevant sequence biomarkers in cancer samples.

Abstract Objective The majority of tumor sequencing currently performed on cancer patients does not include a matched normal control, and in cases where germline testing is performed, it is usually run independently of tumor testing. The rates of concordance between variants identified via germline and tumor testing in this context are poorly understood. We compared tumor and germline sequencing results in patients with breast, ovarian, pancreatic, and prostate cancer who were found to harbor alterations in genes associated with homologous recombination deficiency (HRD) and increased hereditary cancer risk. We then evaluated the potential for a computational somatic-germline-zygosity (SGZ) modeling algorithm to predict germline status based on tumor-only comprehensive genomic profiling (CGP) results. Methods A retrospective chart review was performed using an academic cancer center’s databases of somatic and germline sequencing tests, and concordance between tumor and germline results was assessed. SGZ modeling from tumor-only CGP was compared to germline results to assess this method’s accuracy in determining germline mutation status. Results A total of 115 patients with 146 total alterations were identified. Concordance rates between somatic and germline alterations ranged from 0% to 85.7% depending on the gene and variant classification. After correcting for differences in variant classification and filtering practices, SGZ modeling was found to have 97.2% sensitivity and 90.3% specificity for the prediction of somatic versus germline origin. Conclusions Mutations in HRD genes identified by tumor-only sequencing are frequently germline. Providers should be aware that technical differences related to assay design, variant filtering, and variant classification can contribute to discordance between tumor-only and germline sequencing test results. In addition, SGZ modeling had high predictive power to distinguish between mutations of somatic and germline origin without the need for a matched normal control, and could potentially be considered to inform clinical decision-making. This study sought to describe concordance between germline and tumor testing among patients at the investigators' institution and queried whether results from one test type could be used to inform the other. The authors also investigated the potential of a computational modeling algorithm to predict germline status based on tumor-only comprehensive genomic profiling results alone.

Targeted DNA-based comprehensive genomic profiling (CGP) to detect clinically significant alterations is increasingly becoming standard for patients with advanced or recurrent cancer. RNA-based sequencing, however, may improve performance of fusion detection. We developed a robust targeted RNA sequencing assay (FoundationOne®RNA) and evaluated its analytic performance. FoundationOne®RNA is a hybrid-capture based targeted RNA sequencing test designed to optimally detect fusions (318 genes) and measure gene expression (1521 genes). Analytical validation studies were performed in College of American Pathologists (CAP)-accredited and Clinical Laboratory Improvement Amendments (CLIA)-certified lab to assess fusion call accuracy, assay reproducibility, limit of detection (LoD) and gene expression in 189 clinical solid tumor specimens. In the accuracy study, 160 out of 189 biopsy samples which were previously profiled using large-panel DNA- or RNA-based next-generation sequencing (NGS) passed quality control metrics and were studied using the FoundationOne®RNA assay. Analysis of all diagnostic fusions showed a positive percent agreement (PPA) of 98.28%, as well as a negative percent agreement (NPA) of 99.89% when compared to orthogonal assays. The FoundationOne®RNA assay was able to identify a low level BRAF fusion missed by orthogonal whole transcriptome RNA sequencing and was confirmed by fluorescence in situ hybridization (FISH). The range for the minimum RNA input and LoD was determined based on dilutions from 5 fusion-positive cell lines. It spans from 1.5ng (0.5% input) to 30ng (10% input) for RNA input and from 21 to 85 supporting reads for LoD. In the precision study, 10 out of 10 pre-defined target fusions had 100% reproducibility. In our gene expression analysis, multiple gene expression signatures were detected in fusion positive samples. FoundationOne®RNA assay successfully detected oncogenic fusions with high concordance to orthogonal NGS based tests, high reproducibility, and low limit of detection. This study demonstrated the robustness of FoundationOne®RNA and supports its use as a supplement to tissue DNA comprehensive genomic profiling (CGP) in routine clinical practice. Additional work is required to clarify optimal clinical scenarios for fusion detection and enable gene expression biomarkers for clinical use.

We implemented universal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing of patients undergoing surgical procedures as a means to conserve personal protective equipment (PPE). The rate of asymptomatic coronavirus disease 2019 (COVID-19) was <0.5%, which suggests that early local public health interventions were successful. Although our protocol was resource intensive, it prevented exposures to healthcare team members.

Background: Comprehensive genomic profiling (CGP) is frequently adopted to direct the clinical care of myeloid neoplasms and solid tumors, but its utility in the care of lymphoid and histiocytic cancers is less well defined. Methods: In this study, we aimed to evaluate the frequency at which mutations identified by CGP altered management in non-myeloid hematologic malignancies. We retrospectively examined the CGP results of 105 samples from 101 patients with non-myeloid hematologic malignancies treated at an academic medical center who had CGP testing between 2014 and 2021. Results: CGP revealed one or more pathogenic or likely pathogenic variant in 92 (88%) of samples and 73 (72%) of tested patients had one or more mutations with diagnostic, prognostic, or therapeutic significance. The identification of a resistance variant resulted in the suspension of the active treatment or affected subsequent treatment choice in 9 (69%) out of 13 patients. However, the presence of a therapy sensitizing variant only led to consideration of a biomarker-directed therapy in 6 (10%) out of 61 patients. Conclusions: Overall, CGP of non-myeloid hematologic malignancies identified clinically significant variants in 72% of patients and resulted in a change in management in 22% of patients.

On university campuses and in similar congregate environments, surveillance testing of asymptomatic persons is a critical strategy (1,2) for preventing transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). All students at Duke University, a private research university in Durham, North Carolina, signed the Duke Compact (3), agreeing to observe mandatory masking, social distancing, and participation in entry and surveillance testing. The university implemented a five-to-one pooled testing program for SARS-CoV-2 using a quantitative, in-house, laboratory-developed, real-time reverse transcription-polymerase chain reaction (RT-PCR) test (4,5). Pooling of specimens to enable large-scale testing while minimizing use of reagents was pioneered during the human immunodeficiency virus pandemic (6). A similar methodology was adapted for Duke University's asymptomatic testing program. The baseline SARS-CoV-2 testing plan was to distribute tests geospatially and temporally across on- and off-campus student populations. By September 20, 2020, asymptomatic testing was scaled up to testing targets, which include testing for residential undergraduates twice weekly, off-campus undergraduates one to two times per week, and graduate students approximately once weekly. In addition, in response to newly identified positive test results, testing was focused in locations or within cohorts where data suggested an increased risk for transmission. Scale-up over 4 weeks entailed redeploying staff members to prepare 15 campus testing sites for specimen collection, developing information management tools, and repurposing laboratory automation to establish an asymptomatic surveillance system. During August 2-October 11, 68,913 specimens from 10,265 graduate and undergraduate students were tested. Eighty-four specimens were positive for SARS-CoV-2, and 51% were among persons with no symptoms. Testing as a result of contact tracing identified 27.4% of infections. A combination of risk-reduction strategies and frequent surveillance testing likely contributed to a prolonged period of low transmission on campus. These findings highlight the importance of combined testing and contact tracing strategies beyond symptomatic testing, in association with other preventive measures. Pooled testing balances resource availability with supply-chain disruptions, high throughput with high sensitivity, and rapid turnaround with an acceptable workload.

Purpose: The purpose of this study was to analyze laboratory performance on proficiency testing surveys offered jointly by the College of American Pathologists/American College of Medical Genetics and Genomics biannually for the three common Ashkenazi Jewish founder mutations in the BRCA1 and BRCA2 genes. Methods: Survey responses were analyzed for accuracy of genotype determination and the associated clinical interpretation. Data on an individual laboratory’s participation over time, number of samples tested, turnaround time, and test methodology were also reviewed. Results: Between 2003 and 2012, 23 US laboratories and 39 international laboratories participated. There were six genotyping errors, with a corresponding analytical sensitivity of 99.0% (479/484 challenges; 95% confidence interval: 97.6–99.7%) and an analytic specificity of 99.9% (870/871; 95% confidence interval: 99.4–99.9%). Among the 1,325 clinical interpretations, 92.5% (1,226/1,325; 95% confidence interval: 91.0–93.9%) matched the intended response. Most of the 99 discrepancies—81% (80/99)—incorrectly interpreted the risk for a negative test result as having a lifetime risk of breast cancer “that is the same as that in the general population” instead of “that cannot be determined without BRCA mutation testing of the affected relative.” Conclusion: Clinical laboratories demonstrated excellent analytical sensitivity and specificity. The clinical interpretation requires additional education, focusing on the clinical interpretation of negative test results for these three mutations. Genet Med advance online publication 19 June 2014

This diagnostic study describes an online tool created with actual severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus copy number data to help policy makers understand how pooled testing compares with single-sample testing in different populations.

Smad3 and Smad4 are sequence-specific DNA-binding factors that bind to their consensus DNA-binding sites in response to transforming growth factor β (TGFβ) and activate transcription. Recent evidence implicates Smad3 and Smad4 in the transcriptional activation of consensus AP-1 DNA-binding sites that do not interact with Smads directly. Here, we report that Smad3 and Smad4 can physically interact with AP-1 family members. In vitro binding studies demonstrate that both Smad3 and Smad4 bind all three Jun family members: JunB, cJun, and JunD. The Smad interacting region of JunB maps to a C-terminal 20-amino acid sequence that is partially conserved in cJun and JunD. We show that Smad3 and Smad4 also associate with an endogenous form of cJun that is rapidly phosphorylated in response to TGFβ . Providing evidence for the importance of this interaction between Smad and Jun proteins, we demonstrate that Smad3 is required for the activation of concatamerized AP-1 sites in a reporter construct that has previously been characterized as unable to bind Smad proteins directly. Together, these data suggest that TGFβ -mediated transcriptional activation through AP-1 sites may involve a regulated interaction between Smads and AP-1 transcription factors.