MGDB: A Novel Bioinformatics Quality Control Tool for Clinical Next-Generation Sequencing

Next-generation sequencing (NGS) is a powerful platform for identifying cancer mutations. Routine clinical adoption of NGS requires optimized quality control metrics to ensure accurate results. To assess the robustness of our clinical NGS pipeline, we analyzed the results of 304 solid tumor and hematologic malignancy specimens tested simultaneously by NGS and one or more targeted single-gene tests (EGFR, KRAS, BRAF, NPM1, FLT3, and JAK2). For samples that passed our validated tumor percentage and DNA quality and quantity thresholds, there was perfect concordance between NGS and targeted single-gene tests with the exception of two FLT3 internal tandem duplications that fell below the stringent pre-established reporting threshold but were readily detected by manual inspection. In addition, NGS identified clinically significant mutations not covered by single-gene tests. These findings confirm NGS as a reliable platform for routine clinical use when appropriate quality control metrics, such as tumor percentage and DNA quality cutoffs, are in place. Based on our findings, we suggest a simple workflow that should facilitate adoption of clinical oncologic NGS services at other institutions.

Detection of Recurrent Mutations, Immunoglobulin Rearrangements and Copy Number Changes in Cell-Free DNA and Bone Marrow on Patients with Waldenstrom's Macroglobulinemia over a Course of Treatment

Background: Genomic characterization of circulating tumor cells (CTCs) provides insights into cancer genetic changes, and might be utilized for cancer prognosis, diagnosis, as well as monitoring of therapeutic efficacy. Targeted Panel Next Generation Sequencing (NGS) enables analyzing CTC genetic variants of a focused gene panel at a relatively lower cost1. However, CTCs are rare, often resulting in very limited DNA quantities available that require whole genome amplification (WGA). In previous studies, we introduced the Vortex technology, a platform enabling label-free enrichment of CTCs from blood samples of colorectal cancer (CRC) patients and their use for genomic assays downstream2. In this study, we developed a simple and efficient NGS workflow for CTC samples collected by this technology. Method: An optimized workflow using the Qiagen GeneRead DNAseq targeted panel and Illumina MiSeq NGS was first verified on HCT116 CRC cell line before being applied on patient CTCs. For patient blood samples, CTCs were collected with the Vortex technology, immunostained (CK, Vimentin, CD45) and enumerated. Matched white blood cell (WBC) DNA was included to subtract germline background. Fresh frozen liver metastasis tissue was collected and analyzed using the same NGS workflow. DNA from CTCs was extracted and amplified using Qiagen REPLI-g single cell WGA kit. Mutation detection on the WGA amplified DNA was performed using the GeneRead DNAseq CRC targeted panel of 38 genes and MiSeq sequencing. The sequencing data were analyzed by QIAGEN NGS Data Analysis Web Portal and Ingenuity Variant Analysis software. Results: The Vortex technology was validated for the capture of CTCs from CRC patients. REPLI-g performed a uniform, unbiased amplification on fresh rare cells with a coverage of 97.7%, which enabled further targeted panel NGS. Blood from 3 CRC patients (P1, P2, P3) and 2 healthy donors (HD1, HD2) was processed with Vortex platform. Less than 1 CTCs/mL blood were found in HD1 and HD2. P1 and P2 had 66 and 20 CTCs/ mL of blood respectively, with many vimentin positive CTC clusters. P3 had 2 CTCs/mL of blood. No somatic mutation was found in healthy donors. Somatic variants were only detected in the CTCs from patient samples that were not present in matched germline WBCs. For P1, more mutations were found in the CTCs than in the liver metastasis while it was the opposite for P2 and P3. Conclusion: For each patient, variants in CTCs and germline WBCs were analyzed from one blood sample using an optimized targeted NGS workflow and compared to liver mets. Our optimized workflow, using the Qiagen REPLIg and GeneRead DNAseq Targeted Panel NGS enabled the detection of CTC mutations for 38 CRC-focused genes. The inclusion of a germline WBC control in the workflow allowed the detection of mutations from pooled CTC samples collected using the Vortex technology. Altmüller J, et al. (2014). Biol Chem. Kidess-Sigal E, et al. (2016). Oncotarget. Citation Format: Haiyan E. Liu, Melanie Triboulet, Amin Zia, Meghah Vuppalapaty, Evelyn Kidess-Sigal, John Coller, Vanita S. Natu, Vida Shokoohi, James Che, Corinne Renier, Natalie Chan, Violet Hanft, Elodie Sollier-Christen, Stefanie S. Jeffrey. Genomic profiling of Vortex-enriched CTCs using whole genome amplification and multiplex PCR-based targeted next generation sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1724. doi:10.1158/1538-7445.AM2017-1724

Introduction: High-risk neuroblastoma patients have a survival rate below 50% despite dose-intensive chemoradiotherapy. Treatment using molecularly targeted therapy could more effectively manage patients with less toxicity, but would be best deployed through identification of GAs that suggest responsiveness to such therapies. Recent work from the TARGET initiative (Pugh et al., Nature Genetics 2013) demonstrates a near 10% frequency of ALK GAs in high-risk neuroblastoma patients; such patients could benefit from crizotinib or similar agents targeting the ALK kinase. However, the majority of high-risk neuroblastoma patients still lack identifiable options for targeted therapy. We reviewed the GAs in 17 advanced, high-risk neuroblastoma patients who underwent prospective genomic profiling by clinical NGS to identify actionable alterations that might allow successful trials of targeted therapy. Methods: Diagnostic genomic profiling was performed to characterize all classes of GAs (base substitutions, small insertions/deletions, copy number alterations, and rearrangements) on primary tumors or metastatic specimens, either pre- or post-chemotherapy, of 17 advanced neuroblastoma patients. For each specimen, 3,320 exons of 182 cancer-related genes and selected introns of 14 frequently rearranged genes or 3769 exons of 236 cancer-related genes and selected introns of 19 frequently rearranged genes (earlier and current version of assay, respectively) were sequenced to a minimum coverage depth of 250x in a CLIA-certified, CAP-accredited lab (Foundation Medicine, Cambridge, MA). Actionable GAs were defined as those for which there were FDA-approved agents and/or agents being evaluated in clinical trials. Results: The patient population had a median age of 4.6 yrs (range 2 - 18 yrs), 13 were males, and 16 had Stage 4 disease (one Stage 3). Specimens were sequenced to an average depth of 861x, and GAs were present in 100% (17/17) of cases. These 17 cases harbored 27 GAs (1.6 alterations per tumor; range 1 to 5). Ninety-four percent of cases harbored at least one actionable GA, with a mean of 1.6 actionable GAs per tumor (range 1 to 5). Previously described GAs in neuroblastoma were present in this series, such as GAs in ALK (5 cases; 29%), MYCN (5 cases; 29%), and ATRX (2 cases; 12%), which occurred in a largely mutually exclusive fashion. Alterations in ALK were predominantly base substitutions (80%) and included F1174L and R1275Q at frequencies of 40% and 20%, respectively. One ALK alteration was a novel fusion gene predicted to be active in vivo and potentially responsive to crizotinib. Another recurrent actionable alteration is potentially targetable by FGFR inhibitors, as two neuroblastoma cases contained the activating base substitution N546K in FGFR1. Conclusions: Profiling the tumor genomes of 17 high-risk neuroblastoma patients led to the identification of actionable GAs in a high proportion of patients including alterations previously unseen in neuroblastoma. Specifically, novel fusions of ALK and activating alterations in FGFR1 would not be detected by current molecular diagnostic assays employed in neuroblastoma but offer possible immediate benefit from targeted treatment. Such findings suggest the value of rebiopsying progressive or recurrent high-risk neuroblastoma to identify unforeseen avenues for treatment with targeted therapy. Citation Format: Siraj M. Ali, Matthew J. Hawryluk, Kai Wang, Juliann Chmielecki, Gary A. Palmer, Lazaro Garcia, Emily White, Roman Yelensky, Philip J. Stephens, Jeffrey S. Ross, John M. Maris, Vince A. Miller. Clinical next-generation sequencing (NGS) reveals genomic alterations (GAs) to guide targeted therapy in advanced neuroblastoma patients. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A28.

Variant detection protocols for clinical next-generation sequencing (NGS) need application-specific optimization. Our aim was to analyze the performance of single nucleotide variant (SNV) and copy number (CNV) detection programs on an NGS panel for a rare disease. Thirty genes were sequenced in 83 patients with hereditary spastic paraplegia. The variant calls obtained with LifeScope, GATK UnifiedGenotyper and GATK HaplotypeCaller were compared with Sanger sequencing. The calling efficiency was evaluated for 187 (56 unique) SNVs and indels. Five multiexon deletions detected by multiple ligation probe assay were assessed from the NGS panel data with ExomeDepth, panelcn.MOPS and CNVPanelizer software. There were 48/51 (94%) SNVs and 1/5 (20%) indels consistently detected by all the calling algorithms. Two SNVs were not detected by any of the callers because of a rare reference allele, and one SNV in a low coverage region was only detected by two algorithms. Regarding CNVs, ExomeDepth detected 5/5 multi-exon deletions, panelcn.MOPs 4/5 and only 3/5 deletions were accurately detected by CNVPanelizer. The calling efficiency of NGS algorithms for SNVs is influenced by variant type and coverage. NGS protocols need to account for the presence of rare variants in the reference sequence as well as for ambiguities in indel calling. CNV detection algorithms can be used to identify large deletions from NGS panel data for diagnostic applications; however, sensitivity depends on coverage, selection of the reference set and deletion size. We recommend the incorporation of several variant callers in the NGS pipeline to maximize variant detection efficiency.

P002 Standard duo typing of 1196 specimens revealed a strategy to use next generation sequencing as a standalone HLA typing method in clinical laboratory

Targeting appropriate driver genes is crucial in cancer precision medicine. To find oncogenic drivers, targeted next-generation sequencing is becoming widely used in the clinical field. Using targeted next-generation sequencing, we aimed to detect targetable genetic alterations and characterize mutational profiles of breast cancer. We analyzed breast cancer biopsy specimens using customized 50-gene panel. In total, 196 patients of primary operable breast cancer patients were selected from single institution in South Korea. Among the 196 patients, 22 kinds of genes were significantly mutated or amplified. They comprised 161 nonsynonymous missense mutations, 54 frameshift mutations, 29 missense mutations and 5 small indels; 64 gene amplifications and 2 deletions. The most frequently mutated gene was PIK3CA (n=81/196; 41.3%), followed by TP53 (n=62; 31.6%), AKT1 (n=21; 10.7%), GATA3 (n=17; 8.7%) and PTEN (n=14; 7.1%). The most frequently amplified gene was ERBB2 (n=25/196; 12.8%), followed by FGFR1 (n=11; 5.6%), MYC (n=9; 4.6%), FGFR2 (n=3; 1.5%) and FGFR3 (n=3; 1.5%). Targeted next-generation sequencing can be readily performed in daily clinical practice. The most commonly found targetable genetic alterations were mutations of PI3K/AKT/mTOR pathway genes and FGFR family gene amplifications. Despite the limited number of available targeted agents, our study shows the feasible application of precision medicine in breast cancer. Citation Format: Jung Ho Park, Seung Yeon Ko, Sang Hwa Kim, Ho Young Kim, Sung Hoon Ko, Lee Su Kim. Molecular genetic characterization of primary breast cancer via clinical next-generation sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 198.

The success of targeted therapy in non-small cell lung cancer (NSCLC) hinges on the precise identification of driver alterations, including mutations, gene fusions, and amplifications. Next-generation sequencing (NGS) has emerged as a comprehensive molecular diagnostic tool, capable of detecting both known and novel genomic aberrations, providing critical support for personalized NSCLC treatment. However, NGS remains a complex and technically challenging method. Despite its widespread adoption, NGS still faces some challenges, including technical complexity and prolonged turnaround times. Here, the ISO15189-certified NGS workflow implemented in the clinical laboratory is introduced. The standardized protocol encompassed tumor cellularity assessment (≥20 %), DNA extraction from formalin-fixed paraffin-embedded (FFPE) tissues (DNA input ≥ 50 ng), automated library preparation, and bioinformatics analysis. By integrating stringent quality control (QC) measures at each step, the workflow ensures high data reliability. Besides, the key innovation in workflow was the automation of NGS library construction. The automated system of NGS library construction included end repair, A-tailing, adapter ligation, hybridization capture, and purification, effectively minimizing human error, enhancing experimental reproducibility, reducing hands-on time, and thus improving efficiency. Together, experience demonstrates that rigorous QC and automated library preparation are essential for maintaining accuracy and scalability in clinical NGS testing. This optimized approach not only ensures compliance with ISO15189 standards but also supports the growing demand for precision oncology in NSCLC management.

The aim of this study was to provide an efficient tool: reliable, able to increase the molecular diagnosis performance, to facilitate the detection of copy number variants (CNV), to assess genetic risk scores (wGRS) and to offer the opportunity to explore candidate genes. Custom SeqCap EZ libraries, NextSeq500 sequencing and a homemade pipeline enable the analysis of 311 dyslipidemia-related genes. In the training group (48 DNA from patients with a well-established molecular diagnosis), this next-generation sequencing (NGS) workflow showed an analytical sensitivity >99% (n = 532 variants) without any false negative including a partial deletion of one exon. In the prospective group, from 25 DNA from patients without prior molecular analyses, 18 rare variants were identified in the first intention panel genes, allowing the diagnosis of monogenic dyslipidemia in 11 patients. In six other patients, the analysis of minor genes and wGRS determination provided a hypothesis to explain the dyslipidemia. Remaining data from the whole NGS workflow identified four patients with potentially deleterious variants. This NGS process gives a major opportunity to accede to an enhanced understanding of the genetic of dyslipidemia by simultaneous assessment of multiple genetic determinants.

Accurate Detection of Clinically Actionable Copy Number Variants in Diverse Hematological Neoplasms By Routine Targeted Sequencing: A Comparative Performance Study

Background: Comprehensive tumor molecular profiling using next-generation sequencing (NGS) enables personalized cancer treatment and is standard of care in the management of advanced solid malignancies. Given challenges with efficient implementation of NGS testing in safety-net health care settings, we evaluated the tissue NGS workflow at our facility and investigated the impact of a targeted specimen courier service intervention. Methods: We constructed a NGS workflow process map to identify key stakeholders and potential sources of delays. 26 clinicians were surveyed regarding time spent placing orders, reliance on a process guide sheet, and adherence to key steps in the ordering process. Utilization and process data from 2019-2022 was obtained from our NGS vendor. Time from order placement to result report [Turn Around Time; (TAT)] was the primary process measure; secondary measures were time from order placement to specimen receipt by the vendor [Order to Specimen (OTS)] and time from specimen receipt to reporting of results [Specimen to Report (STR)]. Medians for TAT, OTS, and STR were compared over 3-month intervals, and pre- and post-courier service implementation. A Root Cause Analysis was conducted to identify additional delays and opportunities for further optimization. Results: Between 2019 and 2022 median TAT was 22 days, with a downward trend in median TAT to 18.5 days at the end of 2022. Median OTS and TAT were significantly improved following courier service introduction (13 vs 7 days and 23 vs. 18.5 days, respectively). STR remained stable throughout the periods of interest. Only 63.6%-72.7% of clinicians reported correctly completing key steps of the ordering workflow possibly contributing to delays in OTS and TAT. Conclusions: We assessed the complex effort of optimizing the NGS testing workflow at a large safety-net health system. Courier service implementation improved OTS and overall TAT. Surveys identified inefficiencies in the provider side of the ordering process. Future opportunities to improve TAT include NGS order integration with electronic medical systems.

IntroductionTo evaluate a next-generation sequencing (NGS) workflow in the screening and diagnosis of thalassemia.MethodsIn this prospective study, blood samples were obtained from people undergoing genetic screening for thalassemia at our centre in Guangzhou, China. Genomic DNA was polymerase chain reaction (PCR)-amplified and sequenced using the Ion Torrent system and results compared with traditional genetic analyses.ResultsOf the 359 subjects, 148 (41%) were confirmed to have thalassemia. Variant detection identified 35 different types including the most common. Identification of the mutational sites by NGS were consistent with those identified by Sanger sequencing and Gap-PCR. The sensitivity and specificities of the Ion Torrent NGS were 100%. In a separate test of 16 samples, results were consistent when repeated ten times.ConclusionOur NGS workflow based on the Ion Torrent sequencer was successful in the detection of large deletions and non-deletional defects in thalassemia with high accuracy and repeatability.

The rapid advancement in technology for next-generation sequencing (NGS) continues to make NGS more affordable, and in turn, there is a high influx of sequencing data. While NGS is relatively fast and efficient compared to previous sequencing technologies, there are a multitude of steps in the NGS workflow in which sequencing errors can be introduced. Such sequencing errors are known as artifacts, and if not careful, they can be mistaken for true variants. It's especially important to distinguish artifacts in cancer biopsies, specifically liquid biopsies, a noninvasive method for sample collection. Somatic mutations occur at low frequencies, and a liquid biopsy adds another challenge for detection if not enough cancer cells are collected in the sample. Thus, the distinction between low-frequency mutations and low-frequency artifacts becomes more difficult. In this study, machine learning methods will be used to model sequencing artifacts in NGS cancer data. The Genome in a Bottle (GIAB) genomes and BAMSurgeon will be used as "truth-sets" to distinguish true variants from low-frequency sequencing artifacts.

Simple SummaryCo-mutations may affect EGFR-TKIs efficacy in advanced EGFR mutated NSCLC and could be associated with worse prognosis. Using a clinical next-generation sequencing (NGS) panel we retrospectively assessed the impact of co-alterations in 106 consecutive patients treated with front-line EGFR-TKIs. Clinical and molecular data were retrieved. According to our data, co-mutations do not seem to have any predictive nor prognostic role. Co-mutations are associated with younger age at diagnosis and lymph nodes metastases at baseline. No association with PD-L1 expression level was observed.Background: Tyrosine kinase inhibitors (TKIs) show variable efficacy in epidermal growth factor receptor mutation-positive (EGFR+) NSCLC patients, even in patients harbouring the same mutation. Co-alterations may predict different outcomes to TKIs. Methods: We retrospectively analysed all consecutive EGFR+ advanced NSCLC treated with first-line TKIs at our Institutions. NGS with a 22 genes clinical panel was performed on diagnostic specimens. PD-L1 expression was also evaluated. Results: Of the 106 analysed specimens, 59 showed concomitant pathogenic mutations. No differences in OS (mOS 22.8 vs. 29.5 months; p = 0.088), PFS (mPFS 10.9 vs. 11.2 months; p = 0.415) and ORR (55.9% vs. 68.1%; p = 0.202) were observed comparing patients without and with co-alterations. Subgroup analysis by EGFR mutation type and TKIs generation (1st/2nd vs. 3rd) did not show any difference too. No correlations of PD-L1 expression levels by co-mutational status were found. Significant associations with presence of co-alterations and younger age (p = 0.018) and baseline lymph nodes metastases (p = 0.032) were observed. Patients without concomitant alterations had a significant higher risk of bone progression (26.5% vs. 3.3%, p = 0.011). Conclusions: Pathogenic co-alterations does not seem to predict survival nor efficacy of EGFR TKIs in previously untreated advanced NSCLC.

Newly Diagnosed AML Patient Samples Demonstrate High Degree of Concordance in Identification of Pathogenic Mutations By Next Generation Sequencing (NGS) Performed at Enrolling Institutions Compared to Central Laboratory Results in the Beat AML Master Trial