Cost Of Next-generation Sequencing Research Articles

Evaluating the significance of next-generation sequencing (NGS) testing in Indian patients with advanced malignancies: An observational study on clinical outcomes and treatment costs.

e15091 Background: The widespread use of Next-Generation Sequencing (NGS) panels to guide targeted therapy in advanced malignancies has raised questions regarding their real-world impact on clinical outcomes and affordability. Methods: This observational study included 126 patients, conducted between January 2022 and December 2023 aimed to assess the utility of NGS testing in both the initial and subsequent lines of treatment for Indian patients facing advanced malignancies. Results: In the first-line setting, NGS was extensively employed for patients with metastatic Colorectal Cancer (mCRC) and Non-Small Cell Lung Cancer (NSCLC). Analysis of RAS and BRAF mutations in mCRC patients (n=21) informed the choice between EGFR and VEGFR-directed therapy, resulting in a median Progression-Free Survival (PFS) of 7.5 months. In NSCLC patients (n=37), the NGS identified targetable mutations in 30 cases, leading to significantly improved mPFS (12 months vs 6 mo with chemotherapy alone). NGS was also employed for HRR, HRD and BRCA testing in advanced breast (n=45) and ovarian carcinoma (n=11), which helps in determining prognosis, role of targeted therapy and genetics. No adverse events noted till date. For patients undergoing subsequent lines of treatment (n=12), NGS detected targetable mutations in 9 cases. NGS revealed actionable mutations (ERBB2, CD74/NRG1fusion and KRAS12C mutation) in metastatic NSCLC patients (n=3), leading to appropriate treatment and PFS of 4-6 months. In metastatic NSCLC patients, T790M mutation was detected in 1 patient confering PFS of 6 months with change to Osimertinib and EGFR exon 20 insertion mutation detected in another, survival didn't improve with addition of amivantamab due to poor general condition. Alpelisib was started for PIK3CA mutation in metastatic Ca Breast (HR+,HEr2-), which was discontinued due to poor tolerance after 3 months. In Metastatic Neuroendocrine Carcinoma (NEC) Lung, detection of EGFR l858R mutation did not confer a PFS benefit despite the addition of Geftinib to chemotherapy. Due to financial constraints, targeted therapy couldn't be started for 2 patients with pathogenic target detected. Conclusions: The study's findings suggest that NGS testing offers tangible clinical benefits in both initial and subsequent lines of treatment for advanced malignancies in the Indian population. Despite the varying costs of NGS in India (ranging from 240 to 1800 USD), the data implies an overall affordability, making it a viable option for patients with advanced malignancies. However, NGS didn't improve outcomes in patients with rapidly progressing disease, poor general condition and financial constraints.

Abstract A007: Picturing progression: A new role of whole slide imaging in comprehensive clinical genomic datasets

Abstract Introduction: Real world data is needed to understand cancer evolution based on changing standards of care. While Next Generation Sequencing (NGS) is the preferred standard for confirmatory testing of mutational status, its use varies tremendously across settings and countries, with the most influential variable being cost. In this research, we examined the utility of Whole Slide Images (WSI) as a discrete data type to predict mutational and other statuses to inform assessments of clinical progression. This could include initial mutational status or the evolution of resistance to a specific treatment and the emergence of a new driver mutation. Experimental Procedures: We have curated datasets from 4000 NSCLC and 2000 CRC patients with clinically tested WES, WTS and WSI tumors with deeply curated longitudinal clinical electronic medical records were compiled through a partnership between ConcertAI and Caris Life Science. This de-identified clinical dataset is drawn from a diverse range of U.S. community and academic oncology practices. The practice patterns reflect the real-world variability of treatment and utilization of molecular testing. Additional stratification was performed based on lines of therapy and evidence of clinical progression for patients with information available. Results: Features from whole slide H&E images were extracted and compared between subcohorts of interest. We demonstrated the correlation of the WSI features with TMB, MSI-H, molecular variants, differential gene expression and PD-L1 IHC of these cohorts within the context human interpretable features (HIFs) of whole slide images. Conclusion: The availability of whole slide images (WSI) is a dimensionality requirement for real world longitudinal comprehensive clinical datasets. Digital images should be considered as a key deliverable of clinical genomic datasets and have the potential to inform treatment selection and outcomes. In settings where NGS is not the standard of care, WSI could be used to predict the value of a test for treatment decisions or determination of prospective clinical trial eligibility. Where the cost of NGS is fundamentally prohibitive, such as less developed economies, WSI is a much lower cost modality that could have very high utility in guiding treatment decisions with better predicted outcomes. In all cases WSI imaging could be used to assess potential status or acquired resistance and the evolution of a new driver mutation. All critical in the decision to continue or discontinue a specific treatment. Citation Format: Elizabeth G. Sweeney, Yawei J. Wang, Jacob Picard, Jim Abraham, Eghbal Amidi, Michael R. Rossi, Sergey Klimov, Claudio D'Ambrosio, Ming Chen, Jeff Elton, George Sledge. Picturing progression: A new role of whole slide imaging in comprehensive clinical genomic datasets [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A007.

Moving liquid biopsies to the Front-line of lung cancer treatment decisions

Liquid biopsies have evolved as a promising non-invasive technology for cancer diagnosis and treatment, as they provide a comprehensive analysis of tumor-derived biomarkers. Prospective multicenter studies have shown the efficacy of liquid biopsies, including circulating tumoral DNA (ctDNA) and more recently cfRNA analysis, in identifying biomarkers for targeted therapies in patients with non-small cell lung cancer (NSCLC). In addition, studies have demonstrated a reduced time to treatment initiation when liquid biopsies are used in conjunction with or in lieu of tissue genotyping. Although liquid biopsies hold excellent potential, there are several obstacles to overcome, including technical limitations, standardization of methodologies, and cost-effectiveness. However, ongoing research and technological advances are conquering these obstacles, resulting in enhanced performance and dependability of liquid biopsy assays. To maximize the clinical utility of liquid biopsies, it is necessary to continue research, validation studies, and standardization initiatives. The incorporation of liquid biopsies into standard clinical practice has the potential to revolutionize the diagnosis and treatment of cancer. These noninvasive tests not only are a great tool for diagnosis but also allow real-time monitoring, guide treatment decisions, and enhance patient outcomes. As the costs of next-generation sequencing (NGS) declines, global access to liquid biopsies is anticipated to increase. Liquid biopsies arrived in the clinical practice after we were familiar with the analysis of genetic aberrations in tissue by next generation sequencing (NGS) that is considered the standard of care in new patients with the diagnosis of metastatic non-small cell lung cancer (NSCLC) and sometimes are used now as complement of tissue analysis or only when there is not enough tissue available. We already have done enough studies that show the non-inferiority and equivalence of liquid biopsies with molecular tissue testing. This article explores recent studies that demonstrate the clinical utility and potential of liquid biopsies in oncology including the possibility to use them at the same time of tissue analysis and the comparison of both with the advantage for the patient to get an earlier result due to the shorter turnaround time of liquid biopsies.

Cost-Effectiveness of Next-Generation Sequencing Versus Single-Gene Testing for the Molecular Diagnosis of Patients With Metastatic Non-Small-Cell Lung Cancer From the Perspective of Spanish Reference Centers.

The aim of this study was to assess the cost-effectiveness of using next-generation sequencing (NGS) versus single-gene testing (SgT) for the detection of genetic molecular subtypes and oncogenic markers in patients with advanced non-small-cell lung cancer (NSCLC) in the setting of Spanish reference centers. A joint model combining decision tree with partitioned survival models was developed. A two-round consensus panel was performed to describe clinical practice of Spanish reference centers, providing data on testing rate, prevalence of alterations, turnaround times, and treatment pathways. Treatment efficacy data and utility values were obtained from the literature. Only direct costs (euros, 2022), obtained from Spanish databases, were included. A lifetime horizon was considered, so a 3% discount rate for future costs and outcomes was considered. Both deterministic and probabilistic sensitivity analyses were performed to assess uncertainty. A target population of 9,734 patients with advanced NSCLC was estimated. If NGS was used instead of SgT, 1,873 more alterations would be detected and 82 more patients could potentially be enrolled in clinical trials. In the long term, using NGS would provide 1,188 additional quality-adjusted life-years (QALYs) in the target population compared with SgT. On the other hand, the incremental cost of NGS versus SgT in the target population was €21,048,580 euros for a lifetime horizon (€1,333,288 for diagnosis phase only). The obtained incremental cost-utility ratios were €25,895 per QALY gained, below the standard cost-effectiveness thresholds. Using NGS in Spanish reference centers for the molecular diagnosis of patients with metastatic NSCLC would be a cost-effective strategy over SgT.

Budget impact of next-generation sequencing for diagnosis of TB drug resistance in Moldova.

BACKGROUND Diagnosing drug resistance is critical for choosing effective TB treatment regimens. Next-generation sequencing (NGS) represents an alternative approach to conventional phenotypic drug susceptibility testing (pDST) for diagnosing TB drug resistance.METHODS We undertook a budget impact analysis estimating the costs of introduction and routine use of NGS in the Moldovan National TB Programme. We conducted an empirical costing study and collated price and operating characteristics for NGS platforms. We examined multiple NGS scenarios in comparison to the current approach (pDST) for pre-treatment drug resistance testing over 2021-2025.RESULTS Annual testing volume ranged from 912 to 1,926 patients. For the pDST scenario, we estimated total costs of US$362,000 (2021 USD) over the 5-year study period. Total costs for NGS scenarios ranged from US$475,000 to US$1,486,000. Lowest cost NGS options involved targeted sequencing as a replacement for pDST, and excluded individuals diagnosed as RIF-susceptible on Xpert® MTB/RIF. For all NGS scenarios, the majority (55-80%) of costs were devoted to reagent kits. Start-up costs of NGS were small relative to routine costs borne each year.CONCLUSION NGS adoption will require expanded resources compared to conventional pDST. Further work is required to better understand the feasibility of NGS in settings such as Moldova.

Harnessing the potential of bulk segregant analysis sequencing and its related approaches in crop breeding.

Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.

Economic Analysis of Exclusionary EGFR Test Versus Up-Front NGS for Lung Adenocarcinoma in High EGFR Mutation Prevalence Areas.

This study sought to determine whether exclusionary EGFR mutation testing followed by next-generation sequencing (NGS) is a cost-efficient and timely strategy in areas with high prevalence rates of EGFR mutation. We developed a decision tree model to compare exclusionary EGFR testing followed by NGS and up-front NGS. Patients entered the model upon diagnosis of metastatic lung adenocarcinoma. Gene alterations with FDA-approved targeted therapies included EGFR, ALK, ROS1, BRAF, RET, MET, NTRK, and KRAS. Model outcomes were testing-related costs; time-to-test results; monetary loss, taking both costs and time into consideration; and percentage of patients who could be treated by FDA-approved therapies. Stacked 1-way and 3-way sensitivity analyses were performed. Exclusionary EGFR testing incurred testing-related costs of US $1,387 per patient, a savings of US $1,091 compared with the costs of up-front NGS. The time-to-test results for exclusionary EGFR testing and up-front NGS were 13.0 and 13.6 days, respectively. Exclusionary EGFR testing resulted in a savings of US $1,116 in terms of net monetary loss, without a reduction of patients identified with FDA-approved therapies. The EGFR mutation rate and NGS cost had the greatest impact on minimizing monetary loss. Given that the tissue-based NGS turnaround time was shortened to 7 days, up-front NGS testing would become the best strategy if its price could be reduced to US $568 in Taiwan. In areas with high prevalence rates of EGFR mutation, exclusionary EGFR testing followed by NGS, rather than up-front NGS, is currently a cost-efficient strategy for metastatic lung adenocarcinoma.

Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer.

In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC samples at a single institution. Molecular analysis examined 15 genes for hotspot mutation variants, including AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed. 1201 patients (86.1%) had at least one variant identified, most frequently TP53 (47.5%), KRAS (32.2%) or EGFR (24.2%). Among these, 994 patients (71.3%) had clinically relevant variants eligible for treatment with approved therapies or clinical trial enrollment. The incremental cost of NGS beyond single gene testing (EGFR, ALK) was CAD $233 per case. Reflex upfront NGS identified at least one actionable variant in more than 70% of patients with NSCLC, with minimal increase in testing cost. Implementation of NGS panels remains essential as treatment paradigms continue to evolve.

Effectiveness of nationwide insurance coverage for next-generation sequencing in advanced non–small cell lung cancer: A real-world data study.

9134 Background: Next-generation sequencing (NGS) has been covered by Korean national health insurance since March 2017 for patients with advanced non-small cell lung cancer (NSCLC). We explored the clinical and socioeconomic impact of NGS compared with that of a single gene test (SGT) alone. Methods: From the nationwide database, we identified patients who 1) are diagnosed with advanced NSCLC classified as a distant disease using Summary Stage between March 1, 2017, and December 31, 2018; 2) had NGS or SGT within 2 months after diagnosis of advanced NSCLC. Patients with squamous cell carcinoma were excluded. We conducted multivariate logistic regression to identify factors (e.g., age, sex, Charlson comorbidity index, insurance type, year of diagnosis, and region and type of hospital with the initial diagnosis) affecting the performance of NGS. Further, we divided the cohort into subgroups based on whether patients received treatment targeting epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutations (group A) or not (group B). We conducted 1:5 propensity score matching for each group to minimize the impact of confounding factors. The median overall survival and the adjusted hazard ratio (aHR) for death were estimated using the Kaplan-Meier method and the Cox proportional hazard model, respectively. We calculated the total medical cost, and per patient per year (PPPY) cost adjusted for the survival period. Results: Among 10,247 patients with advanced NSCLC, 768 patients were identified as group A and 1,596 as group B after matching. Old age, low household income, and rural region were factors negatively impacting on having NGS tests. In Group A, we did not find a significant difference in survival outcome between the NGS cohort and the SGT cohort (median survival 31.6 vs. 27.5 months, P =.331; aHR 0.80, P =.204). In contrast, significantly favorable survival was observed for the NGS group in Group B (median survival 14.1 vs. 9.5 months, P =.023; aHR 0.80, P =.009). Although the total medical cost was higher in the NGS group ($39,145) than the SGT group ($36,207) for Group B, the PPPY cost was lower in the NGS group ($57,502 and $63,293, respectively). Conclusions: Socioeconomic factors hampering the implementation of NGS were identified. Lowering the barrier by covering the NGS cost publicly in a specific clinical setting may have survival and cost-benefit in patients with advanced NSCLC.

Clinical and Economic Impact of Upfront Next-Generation Sequencing for Metastatic NSCLC in East Asia

IntroductionUpfront next-generation sequencing (NGS) in patients with metastatic NSCLC has been associated with cost savings and shorter time-to-test results in the United States. Nevertheless, this may not apply in jurisdictions where the prevalence of patients with actionable mutations, cost of health care, and reimbursement models differ. MethodsA decision analytical model was built to compare sequential, panel, exclusionary, and upfront NGS testing in patients with metastatic NSCLC in Hong Kong. In sequential and panel testing, patients were tested for genomic alterations (GAs) with treatment followed by sequential or NGS. In exclusionary testing, EGFR and ALK were tested first, followed by NGS. For each modality, the mutation identified, time to receive testing results, and costs (2020 U.S. dollars) were estimated. ResultsExclusionary testing required the shortest time-to-results (1.6 wk) and was most cost saving. In the scenario where all patients used exclusionary testing, a cost saving of $4.6 million was expected relative to current practice, with 90.7% of actionable and 46.5% of nonactionable GAs detected; when all patients used NGS, it would be $2.9 million more expensive with a 100% GA detection rate. Results were sensitive to testing costs and the proportion of patients that continued testing. ConclusionsExclusionary testing is the best option in terms of cost and time-to-results in Hong Kong. This finding may be applicable for other Asian countries; however, exclusionary testing does not capture all possible GAs. As more GAs become actionable and the cost of NGS declines, NGS may become a cost-saving option.

665. Clinical and Financial Impact of Next Generation Sequencing (NGS) in addition to Conventional Microbiology Testing in our Urban Referral Health Center

BackgroundClinical microbiology traditionally relies on culture methodology and serological testing, that have inherent limitations. Newer diagnostic techniques such as Next Generation Sequencing (NGS) have shown promise to improve microbial identification. In select scenarios, we send clinical specimens to reference laboratories for NGS testing in addition to current standard of care (SOC) diagnostics. We wanted to determine how this diagnostic approach has impacted patient care. We also wanted to review the financial burden through cost-benefit analysis for these ‘send-out’ tests.MethodsWe performed a retrospective chart review of all cases over a 3-year period in which NGS was submitted. Data, including demographics, comorbidities, antimicrobial use, and diagnosis (by SOC and NGS) were gathered. We delineated how often there was concordance or discordance between SOC and NGS. We also obtained information on financial cost (direct and indirect) and turnaround time (TAT) for NGS results. ResultsA total of 33 clinical specimens from 25 patients were sent for NGS. The majority of specimens comprised joint tissue/fluid, organ tissue and CSF.Concordance occurred between SOC and NGS testing in 75.8% (25/33) of samples; of those, 88% excluded infection. NGS identified a pathogen in 20% (5/25) patients in which concomitant SOC testing was negative. A subsequent change in antimicrobial management occurred in 16% (4/25) of patients. The mean TAT was 14 days and average cost per specimen was &821.52 (range: &573-&1590).Table 1. Pathogens identified by NGS with negative traditional microbiological test results Figure 1. Distribution of specimen site (in %) sent for NGS ConclusionNGS can provide additional diagnostic sensitivity in infectious diseases, which at our institution identified a new pathogen in 20% and a resultant treatment change in 16% of our patients. This testing may also allow physicians to reaffirm the absence of an infection diagnosis. A larger NGS testing population may reveal more significant benefits. While the attributable cost of NGS was substantial, it should be measured against the costs of administration of unnecessary antibiotics, inaccurate diagnosis, and adverse patient outcomes that may result from SOC testing alone. Considering its financial cost and extended TAT, in-house NGS testing may be warranted to facilitate a higher volume of testing.Disclosures All Authors: No reported disclosures

Assessment of metrics in next-generation sequencing experiments for use in core-genome multilocus sequence type.

With the reduction in the cost of next-generation sequencing, whole-genome sequencing (WGS)–based methods such as core-genome multilocus sequence type (cgMLST) have been widely used. However, gene-based methods are required to assemble raw reads to contigs, thus possibly introducing errors into assemblies. Because the robustness of cgMLST depends on the quality of assemblies, the results of WGS should be assessed (from sequencing to assembly). In this study, we investigated the robustness of different read lengths, read depths, and assemblers in recovering genes from reference genomes. Different combinations of read lengths and read depths were simulated from the complete genomes of three common food-borne pathogens: Escherichia coli, Listeria monocytogenes, and Salmonella enterica. We found that the quality of assemblies was mainly affected by read depth, irrespective of the assembler used. In addition, we suggest several cutoff values for future cgMLST experiments. Furthermore, we recommend the combinations of read lengths, read depths, and assemblers that can result in a higher cost/performance ratio for cgMLST.

Rapid Genomic Diagnosis of Fungal Infections in the Age of Next-Generation Sequencing.

Next-generation sequencing (NGS) technologies have recently developed beyond the research realm and started to mature into clinical applications. Here, we review the current use of NGS for laboratory diagnosis of fungal infections. Since the first reported case in 2014, >300 cases of fungal infections diagnosed by NGS were described. Pneumocystis jirovecii is the predominant fungus reported, constituting ~25% of the fungi detected. In ~12.5% of the cases, more than one fungus was detected by NGS. For P. jirovecii infections diagnosed by NGS, all 91 patients suffered from pneumonia and only 1 was HIV-positive. This is very different from the general epidemiology of P. jirovecii infections, of which HIV infection is the most important risk factor. The epidemiology of Talaromyces marneffei infection diagnosed by NGS is also different from its general epidemiology, in that only 3/11 patients were HIV-positive. The major advantage of using NGS for laboratory diagnosis is that it can pick up all pathogens, particularly when initial microbiological investigations are unfruitful. When the cost of NGS is further reduced, expertise more widely available and other obstacles overcome, NGS would be a useful tool for laboratory diagnosis of fungal infections, particularly for difficult-to-grow fungi and cases with low fungal loads.

Abstract 549: Genomic characterization and monitoring molecular response to treatment in African American (AA) advanced prostate cancer (PC) patients (pts) via next-generation sequencing (NGS): Real-world experience in a safety net hospital Oncology clinic

Abstract Background: AA men have higher PC incidence and mortality than white men. Healthcare access and other socioeconomic factors contribute to these disparities. The high cost of NGS can become an additional factor for disparity. Indeed, minority and uninsured pts were underrepresented in prior NGS studies and NGS-based Precision Oncology clinical trials. Methods: Ben Taub Hospital (BTH) is a safety net hospital serving a racially/ethnically diverse pt population (91% minorities). We retrospectively analyzed NGS data obtained via Tempus|xT tissue assay (DNA sequencing of 648 genes in tumor tissue at 500x depth) and/or Tempus|xF liquid biopsy assay (ctDNA sequencing of 105 genes at 5,000x depth) for germline and/or somatic mutations detected in 117 BTH pts [61 self-identified AA and 56 white (including white Hispanic)] receiving treatment for locally advanced, biochemically recurrent or metastatic PC. We also analyzed de-identified NGS data from a nationwide cohort of 2090 metastatic PC pts (225 AA) previously sequenced with xT and/or xF by Tempus Labs (Chicago, IL). Results: AA BTH PC pts exhibited high frequencies of BRCA2 (14.8%), SPOP (19.7%), AR (16.4%) and TP53 (49.1%) mutations (respective frequencies in white BTH pts were 9%, 7%, 3.6% and 12.5%). TMPRSS2 fusions were less frequent in AA than white pts. Upon treatment with active therapy (hormonal or taxane), the allele frequency of PC-derived ctDNA mutations in the liquid biopsy declined significantly and concordantly to the biochemical (PSA) response. In addition, two out of 61 (3.3%) AA BTH PCs had microsatellite instability [a frequency comparable to that seen in white BTH PC pts (3.6%) and in the nationwide Tempus Labs cohort (3.6% of AA PC pts)], and experienced prompt and durable clinical, biochemical and molecular responses to pembrolizumab, including disappearance of PC-derived mutant ctDNA. On the other hand, four AA PC pts who had progressed on abiraterone or enzalutamide with ctDNA findings of AR mutations previously reported as sensitive in vitro to the newest FDA-approved AR antagonist darolutamide, did not achieve clinical or biochemical response on darolutamide treatment and that was paralleled by lack of molecular (ctDNA fraction) response. Conclusions: The high mutation frequency in key PC drivers in AA pts at our safety net hospital can be attributed to underlying disease biology or the more advanced disease at presentation in AA pts with socioeconomic factors delaying access to healthcare. Wide use of NGS testing is necessary to improve early access of underserved minority populations to novel targeted therapies and to biomarker-based Precision Oncology clinical trials. Liquid biopsy is a minimally invasive tool that allows longitudinal monitoring of response (or lack thereof) to treatment. Citation Format: Tamer Khashab, Salma Kaochar, Alexander D. Le, Samantha Cohen, Attiya B. Noor, Heidi Dowst, Neda Zarrin-Khameh, Michael A. Brooks, Guilherme Godoy, Maria A. Berezina, Anna E. Schwarzbach, Michael E. Scheurer, Martha P. Mims, Nicholas Mitsiades. Genomic characterization and monitoring molecular response to treatment in African American (AA) advanced prostate cancer (PC) patients (pts) via next-generation sequencing (NGS): Real-world experience in a safety net hospital Oncology clinic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 549.

Pancreatic cancer prognosis is predicted by an ATAC-array technology for assessing chromatin accessibility

Unlike other malignancies, therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. Here we report tumor-cell-intrinsic chromatin accessibility patterns of treatment-naïve surgically resected PDAC tumors that were subsequently treated with (Gem)/Abraxane adjuvant chemotherapy. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we show here the discovery of a signature of 1092 chromatin loci displaying differential accessibility between patients with disease free survival (DFS) < 1 year and patients with DFS > 1 year. Analyzing transcription factor (TF) binding motifs within these loci, we identify two TFs (ZKSCAN1 and HNF1b) displaying differential nuclear localization between patients with short vs. long DFS. We further develop a chromatin accessibility microarray methodology termed “ATAC-array”, an easy-to-use platform obviating the time and cost of next generation sequencing. Applying this methodology to the original ATAC-seq libraries as well as independent libraries generated from patient-derived organoids, we validate ATAC-array technology in both the original ATAC-seq cohort as well as in an independent validation cohort. We conclude that PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

Real-world trends in costs of next generation sequencing (NGS) testing in U.S. setting.

e18824 Background: Recent advances in NGS testing have revolutionized the scope for personalized medicine. The goal of this study was to describe historic trends in the average allowed cost for NGS testing. Methods: This was a retrospective database study evaluating biomarker testing claims in patients undergoing tumor and/or germline sequencing tests between 2016-2019. Molecular testing claims data and marketplace data of tests currently sold in the U.S. were analyzed in the proprietary Concert Genetics Medical Claims Data Warehouse. Results: Analysis of data highlighted high variability in utilization rates as well as allowed amounts for NGS testing. The average allowed amounts for NGS Tests varied from $1269 to $2058 per test during the study period. Higher variability in billing codes and price was also observed when analysis was done for subgroups, which included region, age, gender and cancer type. Similar trends were also observed for panels containing NGS-derived tests such as Tumor Mutation Burden (TMB), an upcoming biomarker. Average allowed amounts for NGS tests that included TMB testing varied from $438 to $3700 per test. To gain a better perspective on evolution of coding, utilization and pricing trends, additional analyses were done in hereditary cancer, given longer availability of these tests in the US Market. For Hereditary cancers, the average allowed amounts varied from $1722 to $2249 per test during the study period. Greater consistency in price was observed in hereditary cancer. Utilization is also more consistent over time and price showed a gradual decreasing trend over time. Coding was also less variable per claim for hereditary cancer and showed a converging trend. Conclusions: Understanding and quantifying the trends in cost of NGS testing for novel biomarkers is critical to predict evolution of testing costs and provide insights essential for minimizing barriers to availability and affordability of these tests. NGS testing can play an important role in improving quality of care and making the clinical decision-making process more efficient. Currently, coverage and reimbursement of NGS tests is one of the key policy challenges that needs to be addressed. Hence, development and adoption of policies is needed to ensure efficient integration of NGS testing in the US health care system.

QIIME 2 Automation for Microbiome Analysis: An Opportunity to Reduce Barriers to Entry While Improving Analytic Speed and Reliability

The cost of next-generation sequencing has significantly reduced since its arrival in 2004, allowing metagenomic research to flourish with applications in medicine, genetics, agriculture, and environment. QIIME 2 is an open-source microbiome analysis software package that converts raw sequence data into interpretable visualizations and statistical results. Most common analyses include classifying sequences taxonomically, analyzing alpha and beta diversity, assessing phylogenetic relationship between features, and identifying features with differential abundances in various treatment groups. Third parties can contribute functionality such as longitudinal analysis and machine-learning analysis, making it a robust microbiome tool that is widely used. However, there exist several barriers in using QIIME 2. There is a steep learning curve for users with limited technical computer skill. The high volume of user inputs increases risk for user error and inefficient reproducibility among collaborators. However, these issues with efficiency, accessibility, and consistency can be addressed through automation. Using LINUX shells, we developed a robust QIIME 2 automation pipeline that automates the core functions of QIIME 2 metagenomic analysis. The process covers raw sequence data importing, demultiplexing, and denoising. It also automates data subset filtering, taxonomic classification, and alpha and beta diversity analyses. Files created with standardized nomenclature are organized into a simple folder structure comprising of data, visualizations, and metadata. QIIME 2 parameters are saved into accessible text files for transparency. The pipeline was trialed with 3 novices to both data science and metagenomic research: one PhD principal investigator, one 2nd year medical student and one 1st year medical student. They were given our scripts and tutorial, and they recorded the time and keystrokes to reach 3 endpoints: 1) construct a PCOA plot of an entire dataset, 2) perform ADONIS test on a distance matrix subset, and 3) compare alpha diversity using the Shannon metric on a metadata subset feature table. 2 out of 3 trials were successful in meeting these endpoints within 2 weeks, requiring 7 (PhD) and 9 hours (2nd year medical student) to do so. Using the fewest possible keystrokes, this analysis would have taken 11,594 characters over roughly 40 hours if done manually. Using our QIIME 2 automation, these endpoints were completed with 228 user keystrokes. The limitations of QIIME 2 can be diminished by automation and clarification of steps at decision points within a metagenomic analysis. The goal of this project was to reduce risk of error and time spent, limiting the obstacles facing a new user using QIIME 2. With growing popularity in metagenomic research, our automation tool can help computer novices navigate through the technical barriers of metagenomic analysis.

INFLAMMATORY BOWEL DISEASE CLASSIFICATION USING THE GUT MICROBIOME: A BENCHMARK OF MICROBIAL DATA ANALYSIS METHODS

Abstract The prevalence of inflammatory bowel disease (IBD) is increasing throughout the developed world. For the newly diagnosed, the time between the appearance of symptoms and diagnosis can take months, involving invasive procedures. There is an urgent need to develop a simple, low cost, accurate and non-invasive diagnostic test. With decreasing costs of next-generation sequencing, many studies have compared IBD gut microbiomes to healthy controls, successfully identifying bacterial biomarkers for IBD. Unfortunately, a majority of these studies utilize machine learning and statistical methods on either single or low-sample size datasets. This results in the creation of disease classification models that have a high level of overfitting and therefore minimal clinical application to new patient cohorts. There are several data preprocessing methods available for data normalization and reduction of cohort specific signals (batch reduction) which can address this lack of cross-dataset performance. With an abundance of potential methods, there is a need to benchmark the performance and generalizability of various machine learning pipelines (combination of data preprocessing and model) for microbiome-based IBD diagnostic tools. We used a collection of 12 IBD-associated North American microbiome datasets (~4000 samples) to benchmark several machine learning pipelines. Raw sequencing data was processed, collapsed at the OTU or Genus level and merged using QIIME2. Datasets were then normalized using either sum-scaling or log based methods and batch reduction was performed using either zero-centering or Empirical Bayes’ approaches. Performance of pipelines was evaluated using binary accuracy, AUC, F1 metric and MCC score. Generalizability of pipelines was evaluated using leave one out cross validation, where data from one study was left out of the training set and tested upon. The best performing and most generalizable pipeline included a Random Forest model paired with centered log ratio based normalization and batch reduction via an Empirical Bayes’ based approach. This combination, along with others, showed equivalent or higher performance to that of more complex models involving deep neural networks (DNNs). In addition to benchmarking our pipelines, we also explore their limitations, such as the tendency of zero-centered batch reduction to rely on balanced data as input or the tendency of Empirical Bayes’ based methods to introduce artificial signals into data, evidencing certain methods as poor tools for clinical use. To our knowledge, this is the first comprehensive benchmark of data preprocessing and machine learning methods for microbiome-based disease classification of IBD. These findings will help improve the generalizability of machine learning models as we move towards non-invasive diagnostic and disease management tools for patients with IBD.

DPCR application in liquid biopsies: divide and conquer

ABSTRACT Introduction: Precision medicine is already a reality in oncology, since biomarker-driven therapies have clearly improved patient survival. Furthermore, a new, minimally invasive strategy termed ‘liquid biopsy’ (LB) has revolutionized the field by allowing comprehensive cancer genomic profiling through the analysis of circulating tumor DNA (ctDNA). However, its detection requires extremely sensitive and efficient technologies. A powerful molecular tool based on the principle of ‘divide and conquer’ has emerged to solve this problem. Thus, digital PCR (dPCR) allows absolute and accurate quantification of target molecules. Areas covered: In this review we will discuss the fundamentals of dPCR and the most common approaches used for partition of samples and quantification. The advantages and limitations of dPCR will be mentioned in the context of LB in oncology. Expert opinion: In our opinion, dPCR has proven to be one of the most sensitive methods available for LB analysis, albeit some aspects such as its capacity of multiplexing and protocol standardization still require further improvements. Furthermore, the increasing sensitivities and lower costs of next generation sequencing (NGS) methods position dPCR as a confirmatory and complementary technique for NGS results which will likely prove to be very useful for treatment monitoring and assessing minimal residual disease.

Atypical insects: molecular mechanisms of unusual life history strategies.

Metamorphosis undeniably shaped the evolutionary success of winged insects. So far, what we know about the hormonal regulation and molecular mechanisms controlling insect metamorphosis lies on the understanding of complete and incomplete metamorphosis. Rarer types of metamorphosis are overlooked, yet they could provide important insights as they represent deviations in life history strategies that are associated with unique ecological traits. The molecular mechanisms of these atypical metamorphoses are still poorly understood. With the rise of next-generation sequencing, and increasing interest in emerging organismal systems, it is now possible to start exploring the molecular mechanisms underlying atypical metamorphoses in insects. By focusing on neometaboly and paedomorphosis, we discuss how exploring their molecular mechanisms can complete our understanding on the evolution of insects and impact applied research areas. Continued decrease in next-generation sequencing costs and progress in genome editing will help decipher the proximate mechanisms of unusual life history strategies in insects.