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Gene expression profiling makes it possible to conduct many biological studies in a variety of fields due to its thorough characterization of cellular states under various experimental conditions. Despite recent advances in high-throughput technology, profiling an entire set of genomes is still difficult and expensive. Due to the high correlation between expression patterns of different genes, the aforementioned problem can be solved with a cost-effective approach that collects only a small subset of genes, called landmark genes, representing the entire set of genes, and infer the remaining genes, called target genes, using a computational model. There are several shallow and deep regression models in literature to estimate the expressions of target genes from the landmark genes. However, the shallow mostly have limited capacity in learning the nonlinear and complex gene expression data and are prone to underfitting, and the deep models generally do not take advantage of correlation among target genes in the learning process and suffer from overfitting. Considering the gene expression inference as a multitask learning problem, we propose a new deep multitask learning algorithm to tackle these issues. Our learning framework automatically learns the correlation between target genes and uses this knowledge to improve its generalization. Specifically, we utilize a subnetwork with low-dimensional latent variables to discover the relationships between target genes and enforce a seamless and easy to implement regularization to our deep regression model. Unlike the existing multitask learning methods that can only deal with dozens or hundreds of tasks, our algorithm is able to efficiently learn the relationships between ∼10,000 target genes and, thus, is scalable to a large number of tasks. Our proposed method outperforms the shallow and deep regression models for gene expression inference and alternative multitask learning algorithms on two large-scale datasets regardless of the network architecture.

Current sequencing-based methods for profiling microbial communities rely on marker gene (e.g., 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present an approach based on a single-primer extension reaction using a highly multiplexed oligonucleotide probe pool. This approach, termed MA-GenTA (microbial abundances from genome tagged analysis), enables quantitative, straightforward, cost-effective microbiome profiling that combines desirable features of both 16S rRNA and mWGS strategies. The use of multiple probes per target genome and rigorous probe design criteria enabled robust determination of relative abundance. To test the utility of the MA-GenTA assay, probes were designed for 830 genome sequences representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, nonmetric multidimensional scaling (NMDS) clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS, and 16S rRNA data sets. MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes. IMPORTANCE New methods for profiling the microbial communities can create new approaches to understanding the composition and function of those communities. In this study, we combined bacterial genome-specific probe design with a highly multiplexed single primer extension reaction as a new method to profile microbial communities, using stool from various mouse strains as a test case. This method, termed MA-GenTA, was benchmarked against 16S rRNA gene sequencing and metagenome sequencing methods and delivered similar relative abundance and clustering data. Since the probes were generated from reference genomes, MA-GenTA was also able to provide functional pathway data for the stool microbiome in the assayed samples. The method is more informative than 16S rRNA analysis while being less costly than metagenome shotgun sequencing., (Copyright © 2021 Benjamino et al.)

Background: Prior studies have established that broader incorporation of active surveillance, guided by additional prognostic tools, may mitigate the growing economic burden of localized prostate cancer in the USA. This study sought to further explore the potential of a particular gene expression-based prognostic tool to address this unmet need. Materials & methods: A deterministic, decision-analytic model was developed to estimate the economic impact of the Prolaris ® test on a US commercial health plan. Results & conclusion: When adopted in patients classified by the American Urological Association as low or intermediate risk, the assay was projected to reduce costs by $1894 and $2129 per patient over 3 and 10 years, respectively, largely through the increased use of active surveillance.

Background: Our objective was to investigate why early studies regarding adoption of the 21-gene recurrence score (RS) assay did not show an initial reduction in the number of patients with breast cancer receiving real-world chemotherapy., Materials and Methods: We addressed 2 sources of confounding suspected in previous studies: (1) the early time frame during the initial adoption phase of the RS assay, and (2) suspected selective, increased administration to patients more likely to have been chemotherapy candidates. To address selective use during initial adoption, we used updated SEER-Medicare data from 2004 and 2011. To address individual selection bias, we examined whether RS test utilization was negatively associated with rates of local chemotherapy use assessed at the hospital referral region level using conventional ordinary least squares and instrumental variable approaches to adjust for selection bias., Results: A total of 26,009 patients met inclusion criteria. Assay use was associated with a decrease in absolute percentage use of chemotherapy of 4.5% (95% confidence interval [CI], 3.2%-5.7%), which was even more pronounced in sensitivity analyses limited to later study years (2008-2011), with a decrease of 6.8% (95% CI, 5.3%-8.3%). Instrumental variable models yielded similar point estimates but were insufficiently powered to draw conclusions., Conclusion: Receipt of the 21-gene assay was associated with decreased utilization of chemotherapy by 2008., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Multiparametric assays for risk stratification are widely used in the management of breast cancer, with applications being developed for a number of other cancer settings. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. There is an increasing need for robust methods to support cost effective comparisons of test performance in multiple settings. The derivation of similar risk classifications using genes comprising the following multi-parametric tests Oncotype DX® (Genomic Health.), Prosigna™ (NanoString Technologies, Inc.), MammaPrint® (Agendia Inc.) was performed using different computational approaches. Results were compared to the actual test results. Two widely used approaches were applied, firstly computational "modelling" of test results using published algorithms and secondly a "training" approach which used reference results from the commercially supplied tests. We demonstrate the potential for errors to arise when using a "modelling" approach without reference to real world test results. Simultaneously we show that a "training" approach can provide a highly cost-effective solution to the development of real-world comparisons between different multigene signatures. Comparisons between existing multiparametric tests is challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. We present an approach, modelled in breast cancer, which can provide health care providers and researchers with the potential to perform robust and meaningful comparisons between multigene tests in a cost-effective manner. We demonstrate that whilst viable estimates of gene signatures can be derived from modelling approaches, in our study using a training approach allowed a close approximation to true signature results., Competing Interests: JMSB reports consultancies from Insight Genetics, BioNTech AG, Biotheranostics, Pfizer, RNA Diagnostics and oncoXchange, honoraria from NanoString Technologies, Oncology Education and Biotheranostics, travel and accommodation expenses from Biotheranostics and NanoString Technologies, research funding from Thermo Fisher Scientific, Genoptix, Agendia, NanoString Technoloiges, Stratifyer GmbH and Biotheranostics, a disclosure “A Molecular Classifier for Personalized Risk Stratification for Patients with Prostate Cancer” (Aug 2019), and applied for patents, including: “Methods and Devices for Predicting Anthracycline Treatment Efficacy”, US utility – 15/325,472; EPO – 15822898.1; Canada – not yet assigned (Jan 2017); “Systems, Devices and Methods for Constructing and Using a Biomarker”, US utility – 15/328,108; EPO –15824751.0; Canada – not yet assigned (Jan 2017); “Histone gene module predicts anthracycline benefit”, PCT/CA2016/000247 (Oct 2016); “Immune Gene Signature Predicts Anthracycline Benefit”, PCT/CA2016/000305 (Dec 2016). JMSB, JB, CQY and PCB are co-inventors on the applied for patent: “95-Gene Signature of Residual Risk Following Endocrine Treatment”, PCT/CA2016/000304 (Dec 2016). PD is an employee and shareholder of NanoString Technologies. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials. The remaining authors do not declare any other competing interests.

Purpose: Adjuvant treatment decisions in early breast cancer (eBC) have traditionally been driven by risk stratification based on clinical and pathological risk factors. The 21-gene Oncotype DX® assay has been validated as a predictive test for benefit from adjuvant chemotherapy (CT), hence assessing its impact in clinical decisions is of high interest. The objective of this study was to estimate the rate of adjuvant treatment decision modification impacted by the Recurrence Score® result, and the consequent budget impact., Methods: The study was a multicentre, prospective, real-life experience in Lombardy (Italy) including consecutive patients with T1-T3, N0-N1a, and ER+/HER2-eBC with clinical-pathologic "intermediate risk" of relapse. The change in treatment recommendations was assessed before and after availability of Recurrence Score result. A budget model evaluated the implications of 21-gene testing in the study population., Results: The overall proportion of CT recommendations was reduced from 24.6% to 15.2% after 21-gene testing, with a major impact in patients initially considered for CT plus hormone therapy (CHT). In these patients, the total budget was reduced, leading to a net saving of -€81,017. The greater the physician propensity to prescribe CHT, the higher the potential savings for the health system from sparing CT in most tested patients., Conclusions: Our real-life experience suggests that all intermediate-risk ER+/HER2-eBC patients who are initially deemed candidates for CHT should be tested with the 21-gene test. The potential to spare CT in at least half of them offers relevant advantages for patients and national health services., Competing Interests: Declaration of competing interest Alberto Zambelli and Carlo Tondini: Genomic Health (RF/CA); Giorgio Colombo: Genomic Health (H). The other authors indicated no financial relationships. (C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment (ET); Expert testimony; (H) Honoraria received (OI); Ownership interests; (IP) Intellectual property rights/inventor/patent holder (SAB); Scientific advisory board., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Importance: Use of tumor molecular profiling (MP) is entering routine clinical practice; however, little is known about how much and why patients value MP., Objective: To examine the perceived value of MP to patients with advanced cancer and factors associated with perceived value., Design, Setting, and Participants: A cross-sectional survey that included willingness-to-pay trade-off scenarios was administered to participants after consent and before MP. A total of 777 participants (94% response rate) were recruited from the Molecular Screening and Therapeutics Program. Eligible patients had advanced solid cancers of any histologic type, were receiving or had completed their last line of effective therapy, had an Eastern Cooperative Oncology Group Performance Status 0 to 3, and had sufficient accessible tissue for MP. The participants were recruited between October 24, 2017, and March 12, 2019, and data analysis was conducted from March 13 to April 14, 2019., Main Outcomes and Measures: Willingness to pay for MP was assessed via hypothetical trade-off scenarios varying in the actionable return rate (1%, 20%, or 40%) and cost (A$0, A$300 [US$210], A$1000 [US $700], A$3000 [US $2100], or A$10 000 [US $7000]). Ordinal regressions were used to explore factors associated with willingness to have and pay for MP., Results: Of 777 participants (405 women [52%]; mean [SD] age, 55.47 [14.26] years), 689 patients (89%) would have MP for as little as a 1% actionable return rate. Fifty-six patients (7%) would require at least a 20% return rate and 11 patients (1%) would require at least a 40% return rate. Fifteen patients (2%) consistently chose not to have the test; 6 participants (0.8%) had missing values on this item. Participants were willing to pay a median of A$1000 if the actionable return rate was 1% and A$3000 for an actionable return rate of 20% to 40%. Of 762 individuals who agreed to testing, 482 patients (64%) were consistently unwilling to pay A$10 000, regardless of the actionable return rate. Patients born in Australia or New Zealand were more likely to want MP (eg, participants born in South Asia had an ordered odds for the tipping point of 7.74 [95% CI, 1.67-36.05; P = .009] times higher than Australian- and/or New Zealand-born participants). Patients born in Australia or New Zealand were also more willing to pay A$1000 or A$3000 (eg, participants born in Western Europe had an ordered odds for the tipping point for paying A$1000 of 1.74 [95% CI, 1.01-3.00; P = .048] times higher than Australian- and/or New Zealand-born participants). People with a medical- or science-related occupation and with more negative attitudes toward uncertainty were more likely to pay A$10 000 (eg, A$10 000 tipping point-ordered odds of participants with a medical- or science-related occupation was 0.49 [95% CI, 0.7-0.87; P = .02] times that of participants without a medical- or science-related occupation)., Conclusions and Relevance: This study found apparent high interest in but lower willingness to pay for MP among patients with advanced cancer. Ability to pay may limit access to MP. Ongoing societal debate is required to establish the value of MP and whether subsidization is needed to ensure equity of access.

Introduction: The aim of this study is to evaluate the cost-effectiveness and impact of gene-expression assays (GEAs) on treatment decisions in a real-world setting of early-stage breast cancer (ESBC) patients., Methods: This is a regional, prospective study promoted by the Council Health Authorities in Madrid. Enrolment was offered to women with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, node-negative or micrometastatic, stage I or II breast cancer from 21 hospitals in Madrid. Treatment recommendations were recorded before and after knowledge of tests results. An economic model compared the cost-effectiveness of treatment, guided by GEAs or by common prognostic factors., Results: 907 tests (440 Oncotype DX ® and 467 MammaPrint ® ) were performed between February 2012 and November 2014. Treatment recommendation changed in 42.6% of patients. The shift was predominantly from chemohormonal (CHT) to hormonal therapy (HT) alone, in 30.5% of patients. GEAs increased patients' confidence in treatment decision making. Tumor grade, progesterone receptor positivity and Ki67 expression were associated with the likelihood of change from CHT to HT (P < 0.001) and from HT to CHT (P < 0.001). Compared with current clinical practice genomic testing increased quality-adjusted life years by 0.00787 per patient and was cost-saving from a national health care system (by 13.867€ per patient) and from a societal perspective (by 32.678€ per patient)., Conclusion: Using GEAs to guide adjuvant therapy in ESBC is cost-effective in Spain and has a significant impact on treatment decisions.

Background: Breast cancer is a disease in which cells in the breast grow out of control. They often form a tumour that may be seen on an x-ray or felt as a lump.Gene expression profiling (GEP) tests are intended to help predict the risk of metastasis (spread of the cancer to other parts of the body) and to identify people who will most likely benefit from chemotherapy. We conducted a health technology assessment of four GEP tests (EndoPredict, MammaPrint, Oncotype DX, and Prosigna) for people with early-stage invasive breast cancer, which included an evaluation of effectiveness, safety, cost effectiveness, the budget impact of publicly funding GEP tests, and patient preferences and values., Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using either the Cochrane Risk of Bias tool, Prediction model Risk Of Bias ASsessment Tool (PROBAST), or Risk of Bias Assessment tool for Non-randomized Studies (RoBANS), depending on the type of study and outcome of interest, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also performed a literature survey of the quantitative evidence of preferences and values of patients and providers for GEP tests.We performed an economic evidence review to identify published studies assessing the cost-effectiveness of each of the four GEP tests compared with usual care or with one another for people with early-stage invasive breast cancer. We adapted a decision-analytic model to compare the costs and outcomes of care that includes a GEP test with usual care without a GEP test over a lifetime horizon. We also estimated the budget impact of publicly funding GEP tests to be conducted in Ontario, compared with funding tests conducted through the out-of-country program and compared with no funding of tests in any location.To contextualize the potential value of GEP tests, we spoke with people who have been diagnosed with early-stage invasive breast cancer., Results: We included 68 studies in the clinical evidence review. Within the lymph-node-negative (LN-) population, GEP tests can prognosticate the risk of distant recurrence (GRADE: Moderate) and may predict chemotherapy benefit (GRADE: Low). The evidence for prognostic and predictive ability (ability to indicate the risk of an outcome and ability to predict who will benefit from chemotherapy, respectively) was lower for the lymph-node-positive (LN+) population (GRADE: Very Low to Low). GEP tests may also lead to changes in treatment (GRADE: Low) and generally may increase physician confidence in treatment recommendations (GRADE: Low).Our economic evidence review showed that GEP tests are generally cost-effective compared with usual care.Our primary economic evaluation showed that all GEP test strategies were more effective (led to more quality-adjusted life-years [QALYs]) than usual care and can be considered cost-effective below a willingness-to-pay of $20,000 per QALY gained. There was some uncertainty in our results. At a willingness-to-pay of $50,000 per QALY gained, the probability of each test being cost-effective compared to usual care was 63.0%, 89.2%, 89.2%, and 100% for EndoPredict, MammaPrint, Oncotype DX, and Prosigna, respectively.Sensitivity analyses showed our results were robust to variation in subgroups considered (i.e., LN+ and premenopausal), discount rates, age, and utilities. However, cost parameter assumptions did influence our results. Our scenario analysis comparing tests showed Oncotype DX was likely cost-effective compared with MammaPrint, and Prosigna was likely cost-effective compared with EndoPredict. When the GEP tests were compared with a clinical tool, the cost-effectiveness of the tests varied. Assuming a higher uptake of GEP tests, we estimated the budget impact to publicly fund GEP tests in Ontario would be between $1.29 million (Year 1) and $2.22 million (Year 5) compared to the current scenario of publicly funded GEP tests through the out-of-country program.Gene expression profiling tests are valued by patients and physicians for the additional information they provide for treatment decision-making. Patients are satisfied with what they learn from GEP tests and feel GEP tests can help reduce decisional uncertainty and anxiety., Conclusions: Gene expression profiling tests can likely prognosticate the risk of distant recurrence and some tests may also predict chemotherapy benefit. In people with breast cancer that is ER+, LN-, and human epidermal growth factor receptor 2 (HER2)-negative, GEP tests are likely cost-effective compared with no testing. The GEP tests are also likely cost-effective in LN+ and premenopausal people. Compared with funding GEP tests through the out-of-country program, publicly funding GEP tests in Ontario would cost an additional $1 million to $2 million annually, assuming a higher uptake of tests. GEP tests are valued by both patients and physicians for chemotherapy treatment decision-making., (Copyright © Queen's Printer for Ontario, 2020.)

Bacterial RNA sequencing (RNA-seq) is a powerful approach for quantitatively delineating the global transcriptional profiles of microbes in order to gain deeper understanding of their physiology and function. Cost-effective bacterial RNA-seq requires efficient physical removal of ribosomal RNA (rRNA), which otherwise dominates transcriptomic reads. However, current methods to effectively deplete rRNA of diverse non-model bacterial species are lacking. Here, we describe a probe and ribonuclease based strategy for bacterial rRNA removal. We implemented the method using either chemically synthesized oligonucleotides or amplicon-based single-stranded DNA probes and validated the technique on three novel gut microbiota isolates from three distinct phyla. We further showed that different probe sets can be used on closely related species. We provide a detailed methods protocol, probe sets for >5000 common microbes from RefSeq, and an online tool to generate custom probe libraries. This approach lays the groundwork for large-scale and cost-effective bacterial transcriptomics studies., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Gene expression profiling (GEP) testing using 12-gene recurrence score (RS) assay (EndoPredict®), 58-gene RS assay (Prosigna®), and 21-gene RS assay (Oncotype DX®) is available to aid in chemotherapy decision-making when traditional clinicopathological predictors are insufficient to accurately determine recurrence risk in women with axillary lymph node-negative, hormone receptor-positive, and human epidermal growth factor-receptor 2-negative early-stage breast cancer. We examined the cost-effectiveness of incorporating these assays into standard practice. A decision model was built to project lifetime clinical and economic consequences of different adjuvant treatment-guiding strategies. The model was parameterized using follow-up data from a secondary analysis of the Anastrozole or Tamoxifen Alone or Combined randomized trial, cost data (2017 Canadian dollars) from the London Regional Cancer Program (Canada) and secondary Canadian sources. The 12-gene, 58-gene, and 21-gene RS assays were associated with cost-effectiveness ratios of $36,274, $48,525, and $74,911/quality-adjusted life year (QALY) gained and resulted in total gains of 379, 284.3, and 189.5 QALYs/year and total budgets of $12.9, $14.2, and $16.6 million/year, respectively. The total expected-value of perfect information about GEP assays' utility was $10.4 million/year. GEP testing using any of these assays is likely clinically and economically attractive. The 12-gene and 58-gene RS assays may improve the cost-effectiveness of GEP testing and offer higher value for money, although prospective evidence is still needed. Comparative field evaluations of GEP assays in real-world practice are associated with a large societal benefit and warranted to determine the optimal and most cost-effective assay for routine use.

Introduction: Indiscriminate ordering of Oncotype DX (ODX) is expensive and of poor value to patients, physicians, and health care providers. The 3 Magee equations, Gage Algorithm, and University of Tennessee predictive algorithm all use standard clinicopathologic data to provide surrogate ODX scores. In this hypothesis-generating study, we evaluated whether these prognostic scores could be used to identify patients unlikely to benefit from additional ODX testing., Patients and Methods: Retrospective data was collected from 302 patients with invasive ductal breast cancer and available ODX scores. Additional data was available for: Magee equations 1 (212 patients), 2 (299 patients), 3 (212 patients), Gage Algorithm (299 patients), and University of Tennessee predictive algorithm (286 patients). ODX scores were banded according to the TAILORx results., Results: Correlation with ODX scores was between 0.7 and 0.8 (Gage), 0.8 and 0.9 (Magee 2, University of Tennessee predictive algorithm), and > 0.9 (Magee 1 and 3). Magee 3 was the most robust and is proposed as a screening tool: for patients aged ≤ 50 years, ODX testing would be not required if the Magee 3 score was < 14 or ≥ 20; for those aged > 50 years, ODX would not be required if the Magee 3 score was < 18 or ≥ 26. Using these cut-offs, 110 (51.9%) of 212 patients would be deemed as not requiring ODX testing, and 109 (99.1%) of110 patients would be appropriately managed., Conclusions: Use of all formulae, and the Magee 3 equation in particular, are proposed as possible screening tools for ODX testing, resulting in significantly reduced frequency of ODX testing. This requires validation in other populations., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Bronchoscopy is the safest procedure for lung cancer diagnosis when an invasive evaluation is required after imaging procedures. However, its sensitivity is relatively low, especially for small and peripheral lesions. We assessed benefits and costs of introducing a bronchial gene-expression classifier (BGC) to improve the performance of bronchoscopy and the overall diagnostic process for early detection of lung cancer. We used discrete-event simulation to compare clinical and economic outcomes of two different strategies with the standard practice in former and current smokers with indeterminate nodules: (i) location-based strategy-integrated the BGC to the bronchoscopy indication; (ii) simplified strategy-extended use of bronchoscopy plus BGC also on small and peripheral lesions. Outcomes modeled were rate of invasive procedures, quality-adjusted-life-years (QALYs), costs and incremental cost-effectiveness ratios. Compared to the standard practice, the location-based strategy (i) reduced absolute rate of invasive procedures by 3.3% without increasing costs at the current BGC market price. It resulted in savings when the BGC price was less than $3,000. The simplified strategy (ii) reduced absolute rate of invasive procedures by 10% and improved quality-adjusted life expectancy, producing an incremental cost-effectiveness ratio of $10,109 per QALY. In patients with indeterminate nodules, both BGC strategies reduced unnecessary invasive procedures at high risk of adverse events. Moreover, compared to the standard practice, the simplified use of BGC for central and peripheral lesions resulted in larger QALYs gains at acceptable cost. The location-based is cost-saving if the price of classifier declines., (© 2019 UICC.)

As sequencing read length has increased, researchers have quickly adopted longer reads for their experiments. Here, we examine 14 pathogen or host-pathogen differential gene expression data sets to assess whether using longer reads is warranted. A variety of data sets was used to assess what genomic attributes might affect the outcome of differential gene expression analysis including: gene density, operons, gene length, number of introns/exons and intron length. No genome attribute was found to influence the data in principal components analysis, hierarchical clustering with bootstrap support, or regression analyses of pairwise comparisons that were undertaken on the same reads, looking at all combinations of paired and unpaired reads trimmed to 36, 54, 72 and 101 bp. Read pairing had the greatest effect when there was little variation in the samples from different conditions or in their replicates (e.g. little differential gene expression). But overall, 54 and 72 bp reads were typically most similar. Given differences in costs and mapping percentages, we recommend 54 bp reads for organisms with no or few introns and 72 bp reads for all others. In a third of the data sets, read pairing had absolutely no effect, despite paired reads having twice as much data. Therefore, single-end reads seem robust for differential-expression analyses, but in eukaryotes paired-end reads are likely desired to analyse splice variants and should be preferred for data sets that are acquired with the intent to be community resources that might be used in secondary data analyses.

Simultaneous profiling of transcriptome and chromatin accessibility within single cells is a powerful approach to dissect gene regulatory programs in complex tissues. However, current tools are limited by modest throughput. We now describe an ultra high-throughput method, Paired-seq, for parallel analysis of transcriptome and accessible chromatin in millions of single cells. We demonstrate the utility of Paired-seq for analyzing the dynamic and cell-type-specific gene regulatory programs in complex tissues by applying it to mouse adult cerebral cortex and fetal forebrain. The joint profiles of a large number of single cells allowed us to deconvolute the transcriptome and open chromatin landscapes in the major cell types within these brain tissues, infer putative target genes of candidate enhancers, and reconstruct the trajectory of cellular lineages within the developing forebrain.

We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/β-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.

Aims: Broad molecular profiling of patients with advanced non-small cell lung cancer (NSCLC) is strongly advised to optimize genomic matching with available targeted treatment options or investigational agents. Unlike conventional molecular diagnostic testing, or smaller hotspot panels, comprehensive genomic profiling (CGP) identifies genomic alterations across hundreds of clinically relevant cancer genes from a single tissue specimen. The present study sought to estimate the budget impact of increased use of CGP using a 324-gene panel (FoundationOne) vs non-CGP (represented by a mix of conventional molecular diagnostic testing and smaller NGS hotspot panels) and the number needed to test with CGP to gain 1 life year., Materials and Methods: A decision analytic model was developed to assess the budget impact of increased CGP in advanced NSCLC from a US private payer perspective. Model inputs were based on published literature (epidemiology and treatment outcomes), real-world data (testing and rates, medical service costs), list prices for CGP and anti-cancer drugs, and assumptions for clinical trial participation., Results: Among 2 million covered lives, 532 had advanced NSCLC; 266 underwent molecular diagnostic testing. An increase in CGP among those tested, from 2% to 10%, was associated with $0.02 per member per month budget impact, of which $0.013 was attributable to costs of prolonged drug treatment and survival and $0.005 to testing cost. Approximately 12 patients would need to be tested with CGP to add 1 life year., Limitations: The model incorporated certain assumptions to account for inputs with a limited evidence profile and simplify the possible post-CGP treatments., Conclusions: An increase in CGP utilization from 2% to 10% among patients with advanced NSCLC undergoing molecular diagnostic testing was associated with a modest budget impact, most of which was attributable to increased use of more effective treatments and prolonged survival.

Background: The transcriptional regulation that occurs in malaria parasites during the erythrocytic stages of infection can be studied in vivo with rodent malaria parasites propagated in mice. Time-series transcriptome profiling commonly involves the euthanasia of groups of mice at specific time points followed by the extraction of parasite RNA from whole blood samples. Current methodologies for parasite RNA extraction involve several steps and when multiple time points are profiled, these protocols are laborious, time-consuming, and require the euthanization of large cohorts of mice., Results: A simplified protocol has been designed for parasite RNA extraction from blood volumes as low as 20 μL (microsamples), serially bled from mice via tail snips and directly lysed with TRIzol reagent. Gene expression data derived from microsampling using RNA-seq were closely matched to those derived from larger volumes of leucocyte-depleted and saponin-treated blood obtained from euthanized mice with high reproducibility between biological replicates. Transcriptome profiling of microsamples taken at different time points during the intra-erythrocytic developmental cycle of the rodent malaria parasite Plasmodium vinckei revealed the transcriptional cascade commonly observed in malaria parasites., Conclusions: Microsampling is a quick, robust and cost-efficient approach to sample collection for in vivo time-series transcriptomic studies in rodent malaria parasites.

Since its establishment in 2009, single-cell RNA sequencing (RNA-seq) has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. Although most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, with the same cell line and bioinformatics pipeline, we developed directly comparable datasets for each of three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. Although each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Drop-Seq is a low-cost, high-throughput platform to profile thousands of cells by encapsualting them into individual droplets. Uniquely barcoded mRNA capture microparticles and cells are coconfined through a microfluidic device within the droplets where they undergo cell lysis and RNA hybridiztion. After breaking the droplets and pooling the hybridized particles, reverse transcription, PCR, and sequencing in single reactions allow to generate data from thousands of single-cell transcriptomes while maintaining information on the cellular origin of each transcript.

The number of breast cancer (BC) cases is growing worldwide, being most frequently diagnosed in the early-setting. Mammaprint™ is a 70-gene-expression signature, originally designed for selecting early BC patients with low risk of developing metastasis, so that they could be spared adjuvant chemotherapy. Its use as a prognostic biomarker has been extensively validated, both retrospectively and prospectively. However, its value as a predictive tool and as a clinically useful tool remains controversial. This review will describe how the test works, its application in the clinic and its limitations. Cost-effectiveness studies will be summarized. Finally, we will provide a perspective on the use of Mammaprint in the near future, as a valuable tool for personalizing the treatment of early BC patients.

Seq-Well is a low-cost picowell platform that can be used to simultaneously profile the transcriptomes of thousands of cells from diverse, low input clinical samples. In Seq-Well, uniquely barcoded mRNA capture beads and cells are co-confined in picowells that are sealed using a semipermeable membrane, enabling efficient cell lysis and mRNA capture. The beads are subsequently removed and processed in parallel for sequencing, with each transcript's cell of origin determined via the unique barcodes. Due to its simplicity and portability, Seq-Well can be performed almost anywhere.

Examining transcriptomics of populations at the single-cell level allows for higher resolution when studying functionality in development, differentiation, and physiology. Real-time quantitative PCR (qPCR) enables a sensitive detection of specific gene expression; however, processing a large number of samples for single-cell research involves a time-consuming process and high reagent costs. Here we describe a protocol for single-cell qPCR using nanofluidic chips. This method reduces the number of handling steps and volumes per reaction, allowing for more samples and genes to be measured.

Single-cell RNA sequencing has revolutionized the way we look at cell populations. Of the methods available, CEL-Seq was the first to use linear RNA amplification. With early barcoding and 3' sequencing, it is sensitive, cost-effective and easy to perform. Here we describe a protocol for performing CEL-Seq2 on sorted cells, which can be performed without any special equipment.

Objectives: Industry-supported decision impact studies demonstrate that Oncotype Dx (ODX) changes treatment recommendations (TR) in 24-40% of hormone receptor+/HER2- patients. ODX is not reimbursed by third-party payers in Australia, potentially resulting in more selective use. We sought to evaluate the impact of self-funded ODX on TRs., Methods: Data collected included demographics, tumor characteristics, indication for ODX and pre- and post-recurrence score (RS) TR. Primary endpoint was frequency of TR change and associations with TR change were sought., Results: Eighteen physicians contributed 382 patients (median age 54). A total of 232 (61%) of tumors were T1 and were grade 1, 2 and 3 in 49 (13%), 252 (66%) and 79 (21%). A total of 257 (67%) were node negative. Assay indications were: confirm need for chemotherapy (CT) (36%), confirm omission of CT (40%) and genuine equipoise (24%). RS was low (≤17) in 55%, intermediate (18-31) in 36% and high (≥32) in 9%. Thirty-eight percent of patients had TR change post-ODX. Sixty-five percent of patients recommended CT pre-ODX changed to hormone therapy alone (HT)-more likely if lower grade and if ER and/or PR > 10%. Fourteen percent of patients with pre-ODX TR for HT added CT-more likely if ER and/or PR ≤10% and if Ki67 > 15% Overall, TR for CT decreased from 47% to 24%., Conclusion: Patient-funded ODX changed TRs in 38% of patients, de-escalating 65% from CT to HT and adding CT to 14% of those recommended HT. These changes were greater than an industry-funded study suggesting that physicians can identify situations where the assay may influence decisions., (© 2018 John Wiley & Sons Australia, Ltd.)

Background: It is unclear whether testing for novel risk factors, such as a cardiovascular genetic risk score (cGRS), improves clinical decision making or health outcomes when used for targeting statin initiation in the primary prevention of atherosclerotic cardiovascular disease (ASCVD). Our objective was to estimate the cost-effectiveness of cGRS testing to inform clinical decision making about statin initiation in individuals with low-to-intermediate (2.5%-7.5%) 10-year predicted risk of ASCVD., Methods and Results: We evaluated the cost-effectiveness of testing for a 27-single-nucleotide polymorphism cGRS comparing 4 test/treat strategies: treat all, treat none, test/treat if cGRS is high, and test/treat if cGRS is intermediate or high. We tested a set of clinical scenarios of men and women, aged 45 to 65 years, with 10-year ASCVD risks between 2.5% and 7.5%. Our primary outcome measure was cost per quality-adjusted life-year gained. Under base case assumptions for statin disutility and cost, the preferred strategy is to treat all patients with ASCVD risk >2.5% without cGRS testing. For certain clinical scenarios, such as a 57-year-old man with a 10-year ASCVD risk of 7.5%, cGRS testing can be cost-effective under a limited set of assumptions; for example, when statins cost $15 per month and statin disutility is 0.013 (ie, willing to trade 3 months of life in perfect health to avoid 20 years of statin therapy), the preferred strategy (using a willingness-to-pay threshold of $50 000 per quality-adjusted life-year gained) is to test and treat if cGRS is intermediate or high. Overall, the results were not sensitive to assumptions about statin efficacy and harms., Conclusions: Testing for a 27-single-nucleotide polymorphism cGRS is generally not a cost-effective approach for targeting statin therapy in the primary prevention of ASCVD for low- to intermediate-risk patients., (© 2018 American Heart Association, Inc.)

Objectives: Many women with early-stage, hormone receptor-positive breast cancer may not benefit from adjuvant chemotherapy. Gene expression tests can reduce chemotherapy over- and undertreatment by providing prognostic information on the likelihood of recurrence and, with Oncotype DX, predictive information on chemotherapy benefit. These tests are currently not reimbursed by German healthcare payers. An analysis was conducted to evaluate the budget impact of gene expression tests in Germany., Materials and Methods: Costs of gene expression tests and medical and non-medical costs associated with treatment were assessed from healthcare payer and societal perspectives. Costs were estimated from data collected at a university hospital and were combined with decision impact data for Oncotype DX, MammaPrint, Prosigna and EndoPredict (EPclin). Changes in chemotherapy use and budget impact were evaluated over 1 year for 20,000 women., Results: Chemotherapy was associated with substantial annual costs of EUR 19,003 and EUR 84,412 per therapy from the healthcare payer and societal perspective, respectively. Compared with standard care, only Oncotype DX was associated with cost savings to healthcare payers and society (EUR 5.9 million and EUR 253 million, respectively). Scenario analysis showed that both women at high clinical but low genomic risk and low clinical but high genomic risk were important contributors to costs., Conclusions: Oncotype DX was the only gene expression test that was estimated to reduce costs versus standard care in Germany. The reimbursement of Oncotype DX testing in standard clinical practice in Germany should be considered., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Purpose The 21-gene assay Oncotype Dx (Genomic Health, Redwood City, CA) test is used to aid the decision about chemotherapy in patients with hormone receptor-positive breast cancer who received endocrine therapy. Economic studies to support test adoption used decision-analytic models with assumptions and data derived from disparate sources. The objective was to evaluate whether the 21-gene assay test resulted in an overall cost expense or saving to the health system. Patients and Methods One thousand participants enrolled in a field evaluation study, were linked to population-level health system administrative databases, and were observed for 20 months. The cost for the cohort, which included the cost of the test, subsequent treatments received, and health care encounters, was determined. The cost in the absence of the test was compared with the pretest recommendation about chemotherapy from the field study for a base case and under scenarios that reflected different adjuvant chemotherapy use. Overall health system costs and incremental costs were calculated. Results The 21-gene assay resulted in a net decrease in chemotherapy use of 23%. For the base case incremental analysis, the actual overall health system cost of this cohort, including the cost of 21-gene assay, was $29.2 million compared with $26.2 million in the absence of the test-an increase of $3.1 million. For three of the four scenario analyses, the actual overall cost to the health system exceeded the estimated cost in the absence of the test. Results showed that, when at least half of the population received adjuvant chemotherapy, the cost increased to $30.2 million. Conclusion The use of real-world administrative data showed that, despite lower rates of chemotherapy use, the 21-gene assay test results in an overall incremental cost to the health care system in the short-term under most assumptions.

Gene expression profiles with prognostic capacities have shown good performance in multiple clinical trials. However, with multiple assays available and numerous types of validation studies performed, the added value for daily clinical practice is still unclear. In Europe, the MammaPrint, OncotypeDX, PAM50/Prosigna and Endopredict assays are commercially available. In this systematic review, we aim to assess these assays on four important criteria: Assay development and methodology, clinical validation, clinical utility and economic value. We performed a literature search covering PubMed, Embase, Web of Science and Cochrane, for studies related to one or more of the four selected assays. We identified 147 papers for inclusion in this review. MammaPrint and OncotypeDX both have evidence available, including level IA clinical trial results for both assays. Both assays provide prognostic information. Predictive value has only been shown for OncotypeDX. In the clinical utility studies, a higher reduction in chemotherapy was achieved by OncotypeDX, although the number of available studies differ considerably between tests. On average, economic evaluations estimate that genomic testing results in a moderate increase in total costs, but that these costs are acceptable in relation to the expected improved patient outcome. PAM50/prosigna and EndoPredict showed comparable prognostic capacities, but with less economical and clinical utility studies. Furthermore, for these assays no level IA trial data are available yet. In summary, all assays have shown excellent prognostic capacities. The differences in the quantity and quality of evidence are discussed. Future studies shall focus on the selection of appropriate subgroups for testing and long-term outcome of validation trials, in order to determine the place of these assays in daily clinical practice., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Value-based payment reforms shift cost-containment responsibilities to the physician. Although gene expression profiling (GEP) utilizing a 21-gene panel among patients with early-stage, axillary lymph node-negative, hormone receptor-positive, HER2/neu oncogene-negative breast cancer is able to identify a cohort that may achieve excellent outcomes without adjuvant chemotherapy, high up-front costs (list price, $4175) could dissuade usage., Study Design: Retrospective review of consecutive patients with breast cancer treated at a single cancer center., Methods: Chart review of 227 patients 70 years or younger with outpatient costs (ie, drug average sales price, reagent costs, physician charges) during first 6 months of treatment., Results: Of these patients, 68% underwent GEP, with 52%, 43%, and 5% having low, intermediate, and high recurrence risk scores, respectively. Adjuvant chemotherapy was utilized less in genomically profiled cohorts (19% vs 29%; P = .08) and was consistent with recommendations of the recurrence scores. The mean 6-month outpatient costs were $24,955 with adjuvant chemotherapy and $2654 with hormonal therapy. Patients with stage II cancer undergoing GEP received adjuvant chemotherapy at a lower frequency (28.6% vs 86.7%), but patients with stage I cancer who underwent testing were slightly more likely to receive chemotherapy (15.8% vs 14%) because the test identified patients with higher-risk tumors. Universal GEP testing of patients with stage II cancer would have resulted in net savings of $11,494 per patient inclusive of test cost; stage I testing would have increased costs by $4505. Similar trends for grade 2/3 tumors (-$2394) and grade 1 tumors (+$6047) were noted., Conclusions: Universal GEP testing of women 70 years or younger with stage II or grade 2/3 lymph node-negative breast cancers would result in lower outpatient costs, inclusive of the diagnostic test, within the first 6-month episode of care.

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The Oncotype DX breast cancer assay (Genomic Health, Redwood City, CA) is increasingly being used to guide treatment decisions for patients with early stage, hormone-positive, Her-2-negative breast cancer. The utility of the Oncotype DX in decision making for treatment of invasive lobular carcinoma (ILC) has not been investigated as the results reported by Genomic Health are largely in a population with invasive ductal carcinoma (IDC). The authors hypothesized that the Oncotype DX recurrence score (RS) distribution for ILC is different than that for IDC. We performed a retrospective analysis of early stage breast cancer patients treated at Penn State Cancer Institute from 2001 to 2011 and identified 102 patients with ILC. We also pulled RS data from our institution's prospective registry of consecutive patients with early stage IDC treated during the same time period. Median follow-up was 55 months. We found that the RS distribution for ILC differed significantly from that of IDC (p = 0.024). We also found a statistically significant difference in the RS distribution between the pure ILC and pleomorphic ILC subtypes (p = 0.027). The Oncotype DX RS distribution in ILC is unique, differing significantly from that in ductal carcinoma. Consequently, the clinical usefulness and cost-effectiveness of the Oncotype DX in guiding treatment for ILC should be further investigated., (© 2017 Wiley Periodicals, Inc.)

Objective To predict the cost-effectiveness of implementing routine gene expression classifier testing for thyroid nodules with indeterminate fine-needle aspiration cytology, by utilizing a real cohort of patients as a comparator. Study Design Cost-effectiveness analysis of a retrospective cohort compared with a simulated cohort. Setting Tertiary academic medical center. Subjects and Methods We reviewed the records of all patients who underwent ultrasound-guided fine-needle aspiration from 2010 to 2014 at a tertiary academic medical center. All patients with Bethesda class III or IV cytopathology had the details of their management catalogued over the subsequent 2 years of care. These patients were assigned to the standard-of-care arm of the study. We compared the third-party payer costs of care and the proportion of patients who underwent surgery with a simulated cohort who underwent gene expression classifier testing after an initial indeterminate fine-needle aspiration (molecular test arm). Results The cost of managing 1 nodule over 2 years was $2399 higher (range, $397-$4399) for the molecular test group than the standard of care group. The molecular test group had a 13.1% decrease (base parameters; range, 0.73%-45.09%) in the number of patients undergoing surgery. Conclusion When applied to a real cohort of patients, routine gene expression classifier is predicted to reduce the number of patients undergoing surgery but will increase cost of care. Cost-effectiveness is heavily dependent on prevalence of malignancy and gene expression classifier specificity.

MicroRNAs (miRNAs) are ~22-nucleotide-long small non-coding RNAs that regulate the expression of protein-coding genes by base pairing to partially complementary target sites, preferentially located in the 3´ untranslated region (UTR) of target mRNAs. The expression and function of miRNAs have been extensively studied in human disease, as well as the possibility of using these molecules as biomarkers for prognostication and treatment guidance. To identify and validate miRNAs as biomarkers, their expression must be screened in large collections of patient samples. Here, we develop a scalable protocol for the rapid and economical preparation of a large number of small RNA sequencing libraries using dual indexing for multiplexing. Combined with the use of off-the-shelf reagents, more samples can be sequenced simultaneously on large-scale sequencing platforms at a considerably lower cost per sample. Sample preparation is simplified by pooling libraries prior to gel purification, which allows for the selection of a narrow size range while minimizing sample variation. A comparison with publicly available data from benchmarking of miRNA analysis platforms showed that this method captures absolute and differential expression as effectively as commercially available alternatives.

We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

Background: The National Institute for Health and Clinical Excellence (NICE) recommended the Oncotype DX ® Breast Recurrence Score ® (RS) assay as an option for informing adjuvant chemotherapy decisions in node-negative, oestrogen receptor (ER)+, human epidermal growth factor receptor 2 (HER2)-negative early breast cancer assessed to be at intermediate risk of recurrence based on clinicopathological factors. We evaluated the impact of RS testing on adjuvant chemotherapy decision-making in routine clinical practice in a UK Cancer Network., Methods: RS testing was performed in 201 females with newly diagnosed, ER+, HER2-negative, invasive breast cancer who underwent breast surgery with curative intent, were calculated to have a >3% overall survival benefit at 10 years from adjuvant chemotherapy based on PREDICT, and were considered for adjuvant chemotherapy. The impact of RS testing on adjuvant treatment decisions/associated cost was assessed., Results: In all patients, the multi-disciplinary team recommended chemotherapy but the RS result allowed 127/201 patients (63.2%) to avoid unnecessary adjuvant chemotherapy. Amongst ER+, HER2-negative, node-negative patients (eligible for Oncotype DX testing in UK guidelines), 60.3% were spared chemotherapy. In node-positive patients, the assay reduced the use of chemotherapy by 69.2%. The use of RS testing to guide treatment in these 201 patients was associated with significant cost saving (when considering the cost of RS testing for all patients plus chemotherapy and its associated cost for 74 patients)., Conclusions: Incorporating RS testing into routine clinical practice for selected node-negative and node-positive breast cancer patients significantly reduces the use of chemotherapy (p < 0.001) with its associated morbidity and costs., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Low-input RNA-seq is powerful to represent the gene expression profiles with limited number of cells, especially when single-cell variations are not the aim. However, pre-amplification-based and molecule index-based library construction methods boost bias or require higher throughput. Here we demonstrate a simple, low-cost, low-bias and low-input RNA-seq with ion torrent semiconductor sequencing (LIEA RNA-seq). We also developed highly accurate and error-tolerant spliced mapping algorithm FANSe2splice to accurately map the single-ended reads to the reference genome with better experimental verifiability than the previous spliced mappers. Combining the experimental and computational advancements, our solution is comparable with the bulk mRNA-seq in quantification, reliably detects splice junctions and minimizes the bias with much less mappable reads.

Single cell RNA sequencing approaches are instrumental in studies of cell-to-cell variability. 5΄ selective transcriptome profiling approaches allow simultaneous definition of the transcription start size and have advantages over 3΄ selective approaches which just provide internal sequences close to the 3΄ end. The only currently existing 5΄ selective approach requires costly and labor intensive fragmentation and cell barcoding after cDNA amplification. We developed an optimized 5΄ selective workflow where all the cell indexing is done prior to fragmentation. With our protocol, cell indexing can be performed in the Fluidigm C1 microfluidic device, resulting in a significant reduction of cost and labor. We also designed optimized unique molecular identifiers that show less sequence bias and vulnerability towards sequencing errors resulting in an improved accuracy of molecule counting. We provide comprehensive experimental workflows for Illumina and Ion Proton sequencers that allow single cell sequencing in a cost range comparable to qPCR assays., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: The National Comprehensive Cancer Network recommends that women who carry gene variants that confer substantial risk for breast cancer consider risk-reduction strategies, that is, enhanced surveillance (breast magnetic resonance imaging and mammography) or prophylactic surgery. Pathogenic variants can be detected in women with a family history of breast or ovarian cancer syndromes by multigene panel testing., Objectives: To investigate whether using a seven-gene test to identify women who should consider risk-reduction strategies could cost-effectively increase life expectancy., Methods: We estimated effectiveness and lifetime costs from a payer perspective for two strategies in two hypothetical cohorts of women (40-year-old and 50-year-old cohorts) who meet the National Comprehensive Cancer Network-defined family history criteria for multigene testing. The two strategies were the usual test strategy for variants in BRCA1 and BRCA2 and the seven-gene test strategy for variants in BRCA1, BRCA2, TP53, PTEN, CDH1, STK11, and PALB2. Women found to have a pathogenic variant were assumed to undergo either prophylactic surgery or enhanced surveillance., Results: The incremental cost-effectiveness ratio for the seven-gene test strategy compared with the BRCA1/2 test strategy was $42,067 per life-year gained or $69,920 per quality-adjusted life-year gained for the 50-year-old cohort and $23,734 per life-year gained or $48,328 per quality-adjusted life-year gained for the 40-year-old cohort. In probabilistic sensitivity analysis, the seven-gene test strategy cost less than $100,000 per life-year gained in 95.7% of the trials for the 50-year-old cohort., Conclusions: Testing seven breast cancer-associated genes, followed by risk-reduction management, could cost-effectively improve life expectancy for women at risk of hereditary breast cancer., (Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

RNAseq is a relatively new tool for ecological genetics that offers researchers insight into changes in gene expression in response to a myriad of natural or experimental conditions. However, standard RNAseq methods (e.g., Illumina TruSeq ® or NEBNext ® ) can be cost prohibitive, especially when study designs require large sample sizes. Consequently, RNAseq is often underused as a method, or is applied to small sample sizes that confer poor statistical power. Low cost RNAseq methods could therefore enable far greater and more powerful applications of transcriptomics in ecological genetics and beyond. Standard mRNAseq is costly partly because one sequences portions of the full length of all transcripts. Such whole-mRNA data are redundant for estimates of relative gene expression. TagSeq is an alternative method that focuses sequencing effort on mRNAs' 3' end, reducing the necessary sequencing depth per sample, and thus cost. We present a revised TagSeq library construction procedure, and compare its performance against NEBNext ® , the 'gold-standard' whole mRNAseq method. We built both TagSeq and NEBNext ® libraries from the same biological samples, each spiked with control RNAs. We found that TagSeq measured the control RNA distribution more accurately than NEBNext ® , for a fraction of the cost per sample (~10%). The higher accuracy of TagSeq was particularly apparent for transcripts of moderate to low abundance. Technical replicates of TagSeq libraries are highly correlated, and were correlated with NEBNext ® results. Overall, we show that our modified TagSeq protocol is an efficient alternative to traditional whole mRNAseq, offering researchers comparable data at greatly reduced cost., (© 2016 John Wiley & Sons Ltd.)

Background: Profiling the somatic mutations of genes which may inform about tumor evolution, prognostics and treatment is becoming a standard tool in clinical oncology. Commercially available cancer gene panels rely on manually gathered cancer-related genes, in a "one-size-fits-many" solution. The design of new panels requires laborious search of literature and cancer genomics resources, with their performance on cohorts of patients difficult to estimate., Results: We present OncoPaD, to our knowledge the first tool aimed at the rational design of cancer gene panels. OncoPaD estimates the cost-effectiveness of the designed panel on a cohort of tumors and provides reports on the importance of individual mutations for tumorigenesis or therapy. With a friendly interface and intuitive input, OncoPaD suggests researchers relevant sets of genes to be included in the panel, because prior knowledge or analyses indicate that their mutations either drive tumorigenesis or function as biomarkers of drug response. OncoPaD also provides reports on the importance of individual mutations for tumorigenesis or therapy that support the interpretation of the results obtained with the designed panel. We demonstrate in silico that OncoPaD designed panels are more cost-effective-i.e. detect a maximum fraction of tumors in the cohort by sequencing a minimum quantity of DNA-than available panels., Conclusions: With its unique features, OncoPaD will help clinicians and researchers design tailored next-generating sequencing (NGS) panels to detect circulating tumor DNA or biopsy specimens, thereby facilitating early and accurate detection of tumors, genomics informed therapeutic decisions, patient follow-up and timely identification of resistance mechanisms to targeted agents. OncoPaD may be accessed through http://www.intogen.org/oncopad.

Several multi-gene assays have been developed to predict the risk of recurrence in patients with estrogen receptor-positive early breast cancer and in whom endocrine therapy is planned. The 21-gene assay is widely used and its prognostic value has been retrospectively validated, showing significant differences in the risk of distant recurrence for patients at high versus low risk. Its role in predicting chemotherapy benefit has also been established, showing a clear benefit for high-risk patients and minimal benefit in those at low risk. These findings have been prospectively investigated in TAILORx (Trial Assigning Individualized Options for Treatment), where available data from the low-risk cohort confirms the prognostic value of this diagnostic test. The prognostic utility of the 21-gene assay increases when combined with clinicopathologic variables, and data from integrated models suggest that its use should be limited to patients with tumor characteristics suggestive of potential chemotherapy benefit. Furthermore, the 21-gene assay has been shown to impact clinical decision making in a cost-effective manner, although direct evidence of benefit from modified treatment recommendations is yet to be proven. The prognostic value of this test has also been shown in populations with node-positive or locally advanced disease treated with neoadjuvant chemotherapy, and ongoing trials aim to prospectively validate these findings.

Purpose of Review: Precision cancer medicine, the use of genomic profiling of patient tumors at the point-of-care to inform treatment decisions, is rapidly changing treatment strategies across cancer types. Precision medicine for advanced prostate cancer may identify new treatment strategies and change clinical practice. In this review, we discuss the potential and challenges of precision medicine in advanced prostate cancer., Recent Findings: Although primary prostate cancers do not harbor highly recurrent targetable genomic alterations, recent reports on the genomics of metastatic castration-resistant prostate cancer has shown multiple targetable alterations in castration-resistant prostate cancer metastatic biopsies. Therapeutic implications include targeting prevalent DNA repair pathway alterations with PARP-1 inhibition in genomically defined subsets of patients, among other genomically stratified targets. In addition, multiple recent efforts have demonstrated the promise of liquid tumor profiling (e.g., profiling circulating tumor cells or cell-free tumor DNA) and highlighted the necessary steps to scale these approaches in prostate cancer., Summary: Although still in the initial phase of precision medicine for prostate cancer, there is extraordinary potential for clinical impact. Efforts to overcome current scientific and clinical barriers will enable widespread use of precision medicine approaches for advanced prostate cancer patients.

Purpose: Oncotype DX (ODX) is a tumor gene-profiling test that aids in adjuvant chemotherapy decision-making. ODX has the potential to improve quality of care; however, if not equally accessible across racial groups, disparities in cancer care quality may persist or worsen. We examined racial disparities in ODX testing uptake., Methods: We used data from the Carolina Breast Cancer Study, phase III, a longitudinal, population-based study of 2,998 North Carolina women who received a diagnosis of breast cancer between 2008 and 2014. Our primary analysis used modified Poisson regression to determine the association between race and whether ODX testing was ordered among two strata: node-negative and node-positive breast cancer., Results: A total of 1,468 women with estrogen receptor-positive, human epidermal growth factor receptor-2-negative, stage I or II breast cancer met inclusion criteria. Black patients had higher-grade and larger tumors, more comorbidities, younger age at diagnosis, and lower socioeconomic status than non-black women. Overall, 42% of women had ODX test results in their pathology reports. Compared with those who did not receive ODX testing, women who received ODX testing tended to be younger and have medium tumor size and grade. Our regression analyses indicated no racial disparities in ODX uptake among node-negative patients. However, racial differences were detected among node-positive patients, with black patients being 46% less likely to receive ODX testing than non-black women (adjusted relative risk, 0.54; 95% CI, 0.35 to 0.84; P = .006)., Conclusion: We did not find racial disparities in ODX testing for node-negative patients for whom ODX testing is guideline recommended and widely covered by insurers. However, our findings suggest that a newer, non-guideline-concordant application of ODX testing for node-positive breast cancer was accessed less by black women than by non-black women, reflecting more guideline concordant care among black women., (© 2015 by American Society of Clinical Oncology.)

Transcriptional profiling is a powerful tool to study biological mechanisms during stem cell differentiation and reprogramming. Genome-wide methods like microarrays or next generation sequencing are expensive, time consuming, and require special equipment and bioinformatics expertise. Quantitative RT-PCR remains one of today's most widely accepted and used methods for analyzing gene expression in biological samples. However, limitations in the amount of starting materials often hinder the quantity and quality of information that could be obtained from a given sample. Here, we present a fast 4-step workflow allowing direct, column-free RNA isolation from limited human pluripotent stem cell (hPSC) cultures that is directly compatible with subsequent reverse transcription, target specific multiplex pre-amplification, and standard SYBR-Green quantitative PCR (qPCR) analysis. The workflow delivers excellent correlations in normalized gene-expression data obtained from different samples of hPSCs over a wide range of cell numbers (500-50,000 cells). We demonstrate accurate and unbiased target gene quantification in limiting stem cell cultures which allows for monitoring embryoid body differentiation and induced pluripotent stem cell (iPSC) reprogramming. This method highlights a rapid and cost effective screening process, allowing reduction of culture formats and increase of processing throughputs for various stem cell applications.

Background: The value of gene expression classifier (GEC) testing for cytologically indeterminate thyroid nodules lies in its negative predictive value, which is influenced by the prevalence of malignancy. We incorporated actual GEC test performance data from a tertiary referral center into a cost-effectiveness analysis of GEC testing., Methods: We evaluated consecutive patients who underwent GEC testing for Bethesda category III and IV nodules from 2012 to 2014. Routine GEC testing was compared with conventional management by the use of a decision tree model. Additional model variables were determined via literature review. A cost-effectiveness threshold of $100,000 per quality-adjusted life-year (QALY) was used., Results: The prevalence of malignancy was 24.3% (52/214). Sensitivity and specificity of GEC testing were 96% and 60%. Conventional management cost $11,119 and yielded 22.15 QALYs. Routine GEC testing was more effective and more costly, with an incremental cost-effectiveness ratio of $119,700/QALY, making it not cost-effective. At malignancy rates of 15, 25, or 35%, routine GEC testing became cost-effective when the cost of GEC testing fell below $3,167, $2,595, or $2,023., Conclusion: The cost-effectiveness of routine GEC testing varies inversely with the underlying prevalence of malignancy in the tested population. The value of routine GEC testing should be assessed within the context of institution-specific malignancy rates., (Copyright © 2016 Elsevier Inc. All rights reserved.)