Synthetic Internal Standard Research Articles

Abstract 7024: Development of quality control methods for reliable NGS measurement of methylation in cfDNA

Abstract Background and Purpose: Reliable measurement of circulating free genomic DNA (cfDNA) methylation patterns promises a means for cancer early detection as well as treatment response. Use of Next Generation Sequencing (NGS) methods to measure the cfDNA methylome across a large number of potentially methylated CpG sites may enable earlier detection by overcoming stochastic sampling associated with the small specimens obtainable by a blood draw. Wide-spread adoption of these methods for clinical diagnostic applications will be facilitated through improved quality controls that increase reliability. The goal of this study is to assess the performance of the SNAQ-SEQ™ method as a means to establish a limit of detection (LOD) for measurement of methylation at each targeted CpG site. For this purpose, we used test materials that were developed by the National Institute for Standards and Technology (NIST) to mimic methylated cfDNA. Methods: NIST test materials were formulated by physically shearing cell line gDNA then subjecting it to size separation to mimic a size distribution similar to that observed in cfDNA, then mixing sheared DNA in its “native” state of methylation with sheared DNA that was in vitro methylated. Non-sheared NIST test materials also were assessed in these studies. Synthetic spike-in internal standards (IS) were combined with NIST test materials and the combined samples were bisulfite converted, then subjected to PCR-amplicon library preparation. Libraries were sequenced on an Illumina MiSeq instrument and bioinformatic analysis was conducted using the Qiagen CLC Workbench. Results and Conclusions: In initial testing of an off-the-shelf IS for a region of the SOX2 gene, average methylation (preserved C) across 14 targeted CpG sites was 16.4% (0.5%-50%) in the “native” NIST non-sheared sample. This was consistent with the 11.6% methylation across all of SOX2 measured by the NIST. In contrast, in IS corresponding to the targeted SOX2 region the average preserved C was 0.32% (0.03%-0.5%). Use of synthetic internal standards enabled determination of LOD for each individual methylated site, controlling for all known sources of technical error, including inefficient bisulfite conversion, nucleotide substitution error, and alignment error. Studies are now underway that use the NIST test materials to measure methylation at five targets known to be altered in cfDNA from lung cancer subjects, SOX2, CDO1, TAC1, SOX17, and HOXA7. Citation Format: James C. Willey, Erin L. Crawford, Daniel J. Craig, Thomas M. Morrison, Hua-Jun He, James G. Herman. Development of quality control methods for reliable NGS measurement of methylation in cfDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7024.

A quantitative sequencing method using synthetic internal standards including functional and phylogenetic marker genes.

The method of spiking synthetic internal standard genes (ISGs) to samples for amplicon sequencing, generating sequences and converting absolute gene numbers from read counts has been used only for phylogenetic markers and has not been applied to functional markers. In this study, we developed ISGs, including gene sequences of the 16S rRNA, pmoA, encoding a subunit of particulate methane monooxygenase and amoA, encoding a subunit of ammonia monooxygenase. We added ISGs to the samples, amplified the target genes and performed amplicon sequencing. For the mock community, the copy numbers converted from read counts using ISGs were equivalent to those obtained by the quantitative real-time polymerase chain reaction (4.0 × 104 versus 4.1 × 104 and 3.0 × 103 versus 4.0 × 103 copies μL-DNA-1 for 16S rRNA and pmoA genes, respectively), but we also identified underestimation, possibly due to primer coverage (7.8 × 102 versus 3.7 × 103 μL-DNA-1 for amoA gene). We then applied this method to environmental samples and analysed phylogeny, functional diversity and absolute quantities. One Methylocystis population was most abundant in the sludge samples [16S rRNA gene (3.8 × 109 copies g-1 ) and the pmoA gene (2.3 × 109 copies g-1 )] and were potentially interrelated. This study demonstrates that ISG spiking is useful for evaluating sequencing data processing and quantifying functional markers.

A standardized quantitative analysis strategy for stable isotope probing metagenomics.

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

Abstract 529: SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens

Abstract Background: Targeted next generation sequencing (NGS) analysis of circulating tumor (ct) DNA promises to significantly advance targeted therapy and potentially early diagnosis of cancer. However, targeted NGS has poor accuracy for calling known variants with VAF below 0.5%. The goal of this study from the FDA-Sequencing and Quality Control Phase 2 (SEQC2) consortium was to develop and validate bioinformatic and biostatistical methods that enable incorporation of synthetic competitive internal standards (IS) in targeted NGS analysis of actionable tumor mutations. Methods: A synthetic IS spike-in was designed for each actionable mutation target, suitable for use in NGS following targeted PCR or hybrid-capture enrichment and either with unique molecular index (UMI) or non-UMI library preparation. Contrived ctDNA reference samples developed by the SEQC2 consortium containing actionable mutations at known variant allele fraction were used. An aliquot of each sample was mixed with a mixture of IS. Following Illumina TST170 enrichment and library preparation, each library was sequenced, then native template (NT) sequences were separated from IS sequences bioinformatically. In SNAQ-SEQ™ analysis, Poisson Exact Test (PET) analysis was used to calculate the statistical difference between each sample library NT variant VAF and respective IS variant VAF. Analysis was based on NT variant count and position coverage (i.e., copies recovered in library preparation) and IS count and position coverage. PET performed an exact test of a simple null hypothesis about the ratio between two rate parameters in Poisson distribution. Results: Stochastic sampling effect on IS error detection was minimized by ensuring an IS/NT ratio of 2.5 or greater. Under the specified conditions, in which a minimum of two NT variant observations were required for a call, the IS was able to estimate NGS background error for each sample when a minimum IS:NT ratio of 2.5:1 was used. Without use of IS information, the Illumina pipeline called 73% (41/56) of known TP variants in the 0.1% - 0.3% VAF range. In contrast, SNAQ-SEQ™ analysis (PET analysis of IS and NT information) increased TP detection sensitivity to 86% (48/56), for a 13% increase in sensitivity, with no false positives. Conclusion: Following mixture of contrived ctDNA reference samples with IS, PET analysis enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. Using this SNAQ-SEQ™ analysis, true positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity. SNAQ-SEQ™ provides QC that is already standard operating procedure in clinical laboratories for analysis by high pressure liquid chromatography and mass spectrometry. Citation Format: James C. Willey, Erin Crawford, Daniel J. Craig, Joshua Xu, Nathan Haseley, Jennifer Lococo, Tom Morrison. SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 529.

New insight into the molecular mechanism of protein cross-linking induced by cis-2-butene-1,4-dial, the metabolite of furan: Formation of 2-substituted pyrrole cross-links involving the cysteine and lysine residues

Furan is an environmental pollutant also present in heat-treated food. The compound is toxic and carcinogenic to rats, and classified as a possible human carcinogen. Mechanisms laying behind the furan carcinogenicity remain unclear, however scientific data indicate the involvement of bioactivation catalysed by cytochrome P450 2E1. The resulted initial metabolite of furan, cis-2-butene-1,4-dial (BDA) is an extremely reactive conjugated dialdehyde able to damage important cellular components such as glutathione, proteins and nucleic acids. Earlier works showed that BDA induces protein cross-linking leading to the formation of modifications containing substituted pyrrole ring, and that the cysteine and lysine residues are prone to undergo such processes. The resulted cross-linked protein adducts are important for research aimed at exploring biomarkers of furan exposure. Due to furan's high volatility, biomarker-based methods appear to be a reliable approach to measure a level of exposure to this chemical. To date, numerous urinary and hepatocyte metabolites were identified. However, all the metabolites contain 3-substituted pyrrole ring resulted from the 1,4-addition of the cysteine thiol function to BDA followed by the condensation with the lysine free amino group. In this work we provide evidence that also 2-substituted pyrrole cross-links are formed at the physiological pH, when BDA is subjected to the reaction with N-acetylcysteine and Nα-acetyllysine, Nε-acetyllysine or lysine, respectively. The 2-substituted cross-links arise from the initial 1,2-addition of N-acetylcysteine to BDA accomplished by the condensation with lysine or its N-acetylated derivatives. Formation of the 2-substituted pyrroles sheds new light on the reactivity of cis-2-butene-1,4-dial towards amino acids, and contributes to complete characterisation of the compound chemistry. Our studies show that the 2- and 3-substituted cross-links are indistinguishable based on their MS and MS/MS spectra, and that for reliable qualitative and quantitative measurements the use of isotope-substituted synthetic internal standards is necessary. In the light of these facts, our results are important for research into furan exposure biomarkers.

Abstract 2525: Low frequency TP53 mutations in airway epithelial cells serve as lung cancer risk biomarker

Abstract Background: Lung cancer is the leading cause of cancer-related death in men and women in the United States. Based on evidence from controlled trials in the United States and Europe that low dose CT (LDCT) screening significantly reduces lung cancer mortality, the United States Preventative Services Tasks Force (USPSTF) recommends LDCT screening for individuals with high demographic risk based on age and smoking history. However, a large fraction of lung cancers occur in individuals who do not meet LDCT screening threshold criteria. Thus, there is a need for biomarkers that supplement demographic factors to more accurately detect those at highest lung cancer risk and include additional individuals who will benefit from LDCT screening. An initial study from this lab demonstrated that TP53 mutations with 0.05-1.0% variant allele fraction (VAF) were significantly more prevalent (p<0.005) in grossly normal airway epithelial cell (AEC) specimens from lung cancer cases compared to non-cancer controls matched for smoking and age. Here, we present an expanded follow-up study aimed at testing this biomarker according to PRospective-specimen-collection, retrospective-Blinded-Evaluation (PRoBE) design. Methods: AEC specimens were prospectively collected through the National Cancer Institute Early Detection Research Network (EDRN) program from 60 subjects at high demographic risk for lung cancer by bronchoscopic brush biopsy at Vanderbilt University Medical Center. Genomic (g)DNA was extracted from each AEC specimen and stored at -80 degrees Celsius. Subjects matched for age and smoking history who subsequently did or did not develop lung cancer were identified and gDNA specimens, blinded with respect to cancer status, were shipped to the University of Toledo. gDNA specimens were quantified and 50,000 gDNA copies were included in each NGS library preparation. Synthetic DNA internal standards (IS) were prepared for multiple lung cancer driver mutations within the TP53 gene and mixed with each AEC gDNA specimen prior to competitive multiplex PCR NGS library preparation. By controlling for technical error, this approach enables reliable detection of mutations with VAF as low as 5 x 10-4 (0.05%) (Craig et al, BMC Cancer, 2019). Results: Following library preparation and sequencing on Illumina Novaseq, there was sufficient library complexity to detect TP53 VAF <0.05% in >90% of AEC specimens. The data are currently in pipeline analysis. After analysis is complete, VCF files will be sent to Vanderbilt for unblinding and validation of the biomarker. Conclusions: Based on preliminary data, we expect that sufficient AEC gDNA is available from most subjects enrolled in the EDRN program for TP53 low VAF biomarker analysis, and the previously reported method (Craig et al, BMC Cancer, 2019) is reliable and feasible. The current study should provide additional information regarding validity of the biomarker. Citation Format: Daniel J. Craig, Erin L. Crawford, Pierre P. Massion, Thomas Morrison, James C. Willey. Low frequency TP53 mutations in airway epithelial cells serve as lung cancer risk biomarker [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 2525.

Pitfalls in HLA Ligandomics—How to Catch a Li(e)gand

Knowledge about the peptide repertoire presented by human leukocyte antigens (HLA) holds the key to unlock target-specific cancer immunotherapies such as adoptive cell therapies or bispecific T cell engaging receptors. Therefore, comprehensive and accurate characterization of HLA peptidomes by mass spectrometry (immunopeptidomics) across tissues and disease states is essential. With growing numbers of immunopeptidomics datasets and the scope of peptide identification strategies reaching beyond the canonical proteome, the likelihood for erroneous peptide identification as well as false annotation of HLA-independent peptides as HLA ligands is increasing. Such “fake ligands” can lead to selection of nonexistent targets for immunotherapeutic development and need to be recognized as such as early as possible in the preclinical pipeline. Here we present computational and experimental methods that enable the identification of “fake ligands” that might be introduced at different steps of the immunopeptidomics workflow. The statistics presented herein allow discrimination of true HLA ligands from coisolated HLA-independent proteolytic fragments. In addition, we describe necessary steps to ensure system suitability of the chromatographic system. Furthermore, we illustrate an algorithm for detection of source fragmentation events that are introduced by electrospray ionization during mass spectrometry. For confirmation of peptide sequences, we present an experimental pipeline that enables high-throughput sequence verification through similarity of fragmentation pattern and coelution of synthetic isotope-labeled internal standards. Based on these methods, we show the overall high quality of existing datasets but point out limitations and pitfalls critical for individual peptides and how they can be uncovered in order to identify true ligands.

Abstract 4609: TP53, PIK3CA, and BRAF somatic mutations in airway epithelial field of injury associated with lung cancer risk

Abstract Background: Lung cancer is the leading cause of cancer-related death in men and women, and cigarette smoking is the most significant preventable risk factor. Early detection through annual low dose CT screening reduces mortality but has low positive predictive value and specificity, in part due to low lung cancer incidence (<10%) among those who currently meet screening criteria. Thus, there is a need for biomarkers that reliably detect those at highest lung cancer risk, thereby enabling more effectivescreening. The purpose of this study was to test the hypothesis that high risk for lung cancer is characterized by high prevalence of low variant allele frequency (VAF) somatic mutations among known lung cancer driver genes in normal airway epithelial cells (AEC). Methods: Synthetic DNA internal standards (IS) were prepared for each of 11 lung cancer driver genes and mixed with each AEC genomic (g)DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach enabled reliable detection of mutations with VAF as low as 5 x 10-4 (0.05%). This method was then applied in a retrospective case-control study. Specifically, AEC specimens were collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested. Results: TP53 mutations with 0.05-1.0% VAF were more prevalent (p<0.005) and significantly more enriched for tobacco smoke and age-associated mutation signatures in AEC from lung cancer cases compared to non-cancer controls matched for smoking and age. Further, PIK3CA and BRAF mutations in this VAF range were identified in AEC from cases but not controls. Conclusions: Measurement of very low frequency mutations in the 0.05-1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes. Citation Format: Daniel J. Craig, Thomas Morrison, Sadik Khuder, Erin L. Crawford, Leihong Wu, Joshua Xu, Thomas M. Blomquist, James C. Willey. TP53, PIK3CA, and BRAF somatic mutations in airway epithelial field of injury associated with lung cancer risk [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 4609.

Mass-spectrometric MRM analysis of FDA-verified proteins in the blood plasma of healthy volunteers

The proteomic composition of a biological sample serves as the most important feature of a biological object, and it allows discriminating normal and pathological conditions. Targeted mass spectrometric analysis, namely, multiple reaction monitoring (MRM) using synthetic isotopically-labeled internal standard (SIS), is the main alternative to the ELISA method for the analysis of diagnostically significant proteins. Based on the MRM results, a prototype test system has been developed; it employs the targeted mass spectrometric method for multiplex, quantitative analysis of FDA-verified proteins in whole blood plasma. Using this approach, it was possible to measure the content of 42 proteins in 31 samples in a concentration range spanning five orders of magnitude. The interindividual variability for 30 of the 42 registered proteins was less than 40%. The largest scatter was observed for haptoglobin (68%), immunoglobulin heavy constant delta IGHD (90%), angiotensin (72%), sex hormone-binding globulin SHBG (100%) and lipoprotein-(a) (136%). The obtained results on the concentration of proteins correlate with published data (Hortin et al., 2008, Clinical Chemistry, 54, 1608) with R2=0.84. The developed prototype test system based on targeted mass spectrometric analysis of proteins can be considered as an alternative to methods using monoclonal antibodies.

Technical advance in targeted NGS analysis enables identification of lung cancer risk-associated low frequency TP53, PIK3CA, and BRAF mutations in airway epithelial cells

BackgroundStandardized Nucleic Acid Quantification for SEQuencing (SNAQ-SEQ) is a novel method that utilizes synthetic DNA internal standards spiked into each sample prior to next generation sequencing (NGS) library preparation. This method was applied to analysis of normal appearing airway epithelial cells (AEC) obtained by bronchoscopy in an effort to define a somatic mutation field effect associated with lung cancer risk. There is a need for biomarkers that reliably detect those at highest lung cancer risk, thereby enabling more effective screening by annual low dose CT. The purpose of this study was to test the hypothesis that lung cancer risk is characterized by increased prevalence of low variant allele frequency (VAF) somatic mutations in lung cancer driver genes in AEC.MethodsSynthetic DNA internal standards (IS) were prepared for 11 lung cancer driver genes and mixed with each AEC genomic (g) DNA specimen prior to competitive multiplex PCR amplicon NGS library preparation. A custom Perl script was developed to separate IS reads and respective specimen gDNA reads from each target into separate files for parallel variant frequency analysis. This approach identified nucleotide-specific sequencing error and enabled reliable detection of specimen mutations with VAF as low as 5 × 10− 4 (0.05%). This method was applied in a retrospective case-control study of AEC specimens collected by bronchoscopic brush biopsy from the normal airways of 19 subjects, including eleven lung cancer cases and eight non-cancer controls, and the association of lung cancer risk with AEC driver gene mutations was tested.ResultsTP53 mutations with 0.05–1.0% VAF were more prevalent (p < 0.05) and also enriched for tobacco smoke and age-associated mutation signatures in normal AEC from lung cancer cases compared to non-cancer controls matched for smoking and age. Further, PIK3CA and BRAF mutations in this VAF range were identified in AEC from cases but not controls.ConclusionsApplication of SNAQ-SEQ to measure mutations in the 0.05–1.0% VAF range enabled identification of an AEC somatic mutation field of injury associated with lung cancer risk. A biomarker comprising TP53, PIK3CA, and BRAF somatic mutations may better stratify individuals for optimal lung cancer screening and prevention outcomes.

Abstract 432: Novel method for NGS analysis of actionable mutations in circulating tumor DNA specimens: improved quality control and 20-fold lower sequencing required

Abstract Background: Identification of actionable mutations in circulating tumor DNA (ctDNA) enables gene-targeted therapy of solid tumors based on a simple blood test. NGS methods that attach a unique molecular identifier (UMI) to each DNA molecule reduce variant allele fraction (VAF) limit of detection (LOD) to &amp;lt;0.01% at a cost of 10-20-fold higher sequencing requirement. Importantly, the VAF lower limit of detection (LOD) for analysis of ctDNA specimens does not typically extend below 0.5% due to limits of ctDNA specimen quantity. For example, the average ctDNA specimen is 32 ng (10,000 genome copies) and at 0.1% VAF, 10 mutant molecules would be added to library prep. At this level, signal loss during library prep (typically 70-90%) will be associated with stochastic sampling variation. For example, in the Sequencing Quality Control Consortium (SEQC) 2 study, we measured inter-site and inter-replicate reproducibility of VAF measurement in 50 ng (15,000 genome copies) of synthetic ctDNA reference material. Thus, even using UMI NGS, measurement, reproducibility at VAF &amp;gt;0.5% was &amp;gt;95%, but reproducibility at 0.1-0.5% VAF was about 70%. Given limited value of UMI NGS when size of ctDNA specimen restricted VAF LOD to 0.5%, we tested the hypothesis that synthetic internal standard (IS) spike-in molecules provide reliable alternative quality control while eliminating UMI-imposed sequencing burden. Methods: We synthesized IS for 61 actionable mutations, cloned them into pUC vectors, confirmed each IS to be wild-type sequence, linearized, quantified abundance and combined at a 1:1 genome copy mixture. An aliquot of IS mixture was added to the ctDNA reference material at 1:1 genome copy prior to library prep, followed by Illumina HiSeq sequencing, separation of target from IS reads using custom splitter, then pipeline analysis on Qiagen CLC Genomics Workbench. Results: Analysis of each target relative to IS reliably identified base-substitution sequencing errors at each measured actionable mutation site and determined that VAF for each was &amp;lt;0.2%. Further, although a typical UMI method requires &amp;gt;200,000 reads per target in each sample, with analysis relative to IS spike-ins, 20,000 reads was sufficient (10,000 reads for the specimen and 10,000 reads for the spike-in). Because the IS spike-in molecules were validated to be wild-type, any variants were assumed to be due to technical error. Thus, a z-score comparing sequence count for a) specimen wild-type, b) specimen mutant, c) IS wild-type, and d) IS mutant enabled calculation of confidence level regarding each biological variant call. Conclusion: Preliminary data indicate that IS spike-in mixtures enable reliable analysis of ctDNA mutation fraction to LOD of 0.5% without need for UMI. Disclaimer: The views expressed here are those of the authors only and do not necessarily express the views/policies of the FDA. Citation Format: Daniel J. Craig, Erin L. Crawford, Joshua Xu, Thomas M. Blomquist, Leihong Wu, Thomas Morrison, James C. Willey. Novel method for NGS analysis of actionable mutations in circulating tumor DNA specimens: improved quality control and 20-fold lower sequencing required [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 432.

Simultaneous quantification of acidic and basic flupirtine metabolites by supercritical fluid chromatography according to European Medicines Agency validation

Supercritical fluid chromatography (SFC) holds the potential to become an orthogonal method to HPLC/UHPLC in xenobiotic metabolism studies, due to its outstanding capacity to simultaneously separate highly similar (as HPLC) and physicochemically different analytes (problematic using HPLC). Paucity of guideline-conform validation, however, has been a major obstacle to clinical application of SFC, even in cases where biotransformation yields chemically dissimilar metabolites that require more than one HPLC method for comprehensive analysis. Here, a method based on supercritical fluid chromatography coupled to single quadrupole MS detection was developed to simultaneously quantify the divisive analgesic flupirtine and its acidic and basic metabolites, represented by 4-fluorohippuric acid (4-FHA) and the active metabolite D-13223 respectively, using custom-made synthetic internal standards. Experimental data on the fundamental retention mechanisms under supercritical conditions, indicating the importance of halogen and π-π-bonding for specific retention on polysaccharide-based stationary-phases, is discussed. Compared to previous HPLC methods, the novel method offers higher versatility in terms of the target metabolite range (addressing both acidic and basic metabolites within a singular method), faster analysis (7.5 min), and compliance with green chemistry principles. Validation was performed according to EMA criteria on bioanalytical method validation, demonstrating selectivity, carry-over, calibration curve parameters (LLOQ, range, and linearity), within- and between-run accuracy and precision, dilution integrity, matrix effect and stability. For proof-of-concept, the SFC method was applied to clinical samples of human urine obtained after single intravenous (100 mg), single oral (100 mg), and repeated oral administration (400 mg). Flupirtine, D-13223, and 4-FHA could be quantified, shedding light on the extent of oxidative flupirtine metabolism in humans in the context of the unresolved biotoxification that has led to the withdrawal of specific neuronal KV7 openers.

Development of Targeted Mass Spectrometry-Based Approaches for Quantitation of Proteins Enriched in the Postsynaptic Density (PSD).

The postsynaptic density (PSD) is a structural, electron-dense region of excitatory glutamatergic synapses, which is involved in a variety of cellular and signaling processes in neurons. The PSD is comprised of a large network of proteins, many of which have been implicated in a wide variety of neuropsychiatric disorders. Biochemical fractionation combined with mass spectrometry analyses have enabled an in-depth understanding of the protein composition of the PSD. However, the PSD composition may change rapidly in response to stimuli, and robust and reproducible methods to thoroughly quantify changes in protein abundance are warranted. Here, we report on the development of two types of targeted mass spectrometry-based assays for quantitation of PSD-enriched proteins. In total, we quantified 50 PSD proteins in a targeted, parallel reaction monitoring (PRM) assay using heavy-labeled, synthetic internal peptide standards and identified and quantified over 2100 proteins through a pre-determined spectral library using a data-independent acquisition (DIA) approach in PSD fractions isolated from mouse cortical brain tissue.

Quantification of Inflammasome Adaptor Protein ASC in Biological Samples by Multiple-Reaction Monitoring Mass Spectrometry.

Inflammation is an integral component of many diseases, including chronic kidney disease (CKD). ASC (apoptosis-associated speck-like protein containing CARD, also PYCARD) is the key inflammasome adaptor protein in the innate immune response. Since ASC specks, a macromolecular condensate of ASC protein, can be released by inflammasome-activated cells into the extracellular space to amplify inflammatory responses, the ASC protein could be an important biomarker in diagnostic applications. Herein, we describe the development and validation of a multiple reaction monitoring mass spectrometry (MRM-MS) assay for the accurate quantification of ASC in human biospecimens. Limits of detection and quantification for the signature DLLLQALR peptide (used as surrogate for the target ASC protein) were determined by the method of standard addition using synthetic isotope-labeled internal standard (SIS) peptide and urine matrix from a healthy donor (LOQ was 8.25pM, with a ~ 1000-fold linear range). We further quantified ASC in the urine of CKD patients (8.4 ± 1.3ng ASC/ml urine, n = 13). ASC was positively correlated with proteinuria and urinary IL-18 in CKD samples but not with urinary creatinine. Unfortunately, the ASC protein is susceptible to degradation, and patient urine that was thawed and refrozen lost 85% of the ASC signal. In summary, the MRM-MS assay provides a robust means to quantify ASC in biological samples, including clinical biospecimens; however, sample collection and storage conditions will have a critical impact on assay reliability.

Control for stochastic sampling variation and qualitative sequencing error in next generation sequencing

BackgroundClinical implementation of Next-Generation Sequencing (NGS) is challenged by poor control for stochastic sampling, library preparation biases and qualitative sequencing error. To address these challenges we developed and tested two hypotheses. MethodsHypothesis 1: Analytical variation in quantification is predicted by stochastic sampling effects at input of (a) amplifiable nucleic acid target molecules into the library preparation, (b) amplicons from library into sequencer, or (c) both. We derived equations using Monte Carlo simulation to predict assay coefficient of variation (CV) based on these three working models and tested them against NGS data from specimens with well characterized molecule inputs and sequence counts prepared using competitive multiplex-PCR amplicon-based NGS library preparation method comprising synthetic internal standards (IS). Hypothesis 2: Frequencies of technically-derived qualitative sequencing errors (i.e., base substitution, insertion and deletion) observed at each base position in each target native template (NT) are concordant with those observed in respective competitive synthetic IS present in the same reaction. We measured error frequencies at each base position within amplicons from each of 30 target NT, then tested whether they correspond to those within the 30 respective IS. ResultsFor hypothesis 1, the Monte Carlo model derived from both sampling events best predicted CV and explained 74% of observed assay variance. For hypothesis 2, observed frequency and type of sequence variation at each base position within each IS was concordant with that observed in respective NTs (R2=0.93). ConclusionIn targeted NGS, synthetic competitive IS control for stochastic sampling at input of both target into library preparation and of target library product into sequencer, and control for qualitative errors generated during library preparation and sequencing. These controls enable accurate clinical diagnostic reporting of confidence limits and limit of detection for copy number measurement, and of frequency for each actionable mutation.

Tandem mass spectrometry assays of palmitoyl protein thioesterase 1 and tripeptidyl peptidase activity in dried blood spots for the detection of neuronal ceroid lipofuscinoses in newborns.

We report new substrates for quantitative enzyme activity measurements of human palmitoyl protein thioesterase (PPT1) and tripeptidyl peptidase (TPP1) in dried blood spots from newborns using tandem mass spectrometry. Deficiencies in these enzyme activities due to inborn errors of metabolism cause neuronal ceroid lipofuscinoses. The assays use synthetic compounds that were designed to mimic the natural substrates. Incubation produces nanomole quantities of enzymatic products per a blood spot that are quantified by tandem mass spectrometry using synthetic internal standards and selected reaction monitoring. The assays utilize a minimum steps for sample workup and can be run in a duplex format for the detection of neuronal ceroid lipofuscinoses or potentially multiplexed with other mass spectrometry-based assays for newborn screening of lysosomal storage disorders.

Quantification of Transferrin in Human Serum Using Both QconCAT and Synthetic Internal Standards

Transferrin, an iron transport protein, is a clinically important biomarker in diseases such as iron-deficiency anemia. Current diagnostic methods for transferrin levels lack quantitative accuracy, suggesting the need for alternative approaches like LC-MS with isotope-labeled peptides as internal standards. Besides solid-phase synthesis, isotope-labeled peptides are also generated by a method called QconCAT where peptides are expressed from DNA in the presence of heavy isotope media. After evaluation of the expressed QconCAT, this study compares transferrin levels obtained by synthetic peptides versus QconCAT peptides as internal standards. Transferrin levels obtained by both internal standards give overlapping, or nearly overlapping, uncertainty values and are near ≈200 mg/dL of transferrin in human serum. Close agreement between the two methods suggests that the quantitative values are reasonable. Using QconCAT and synthetic peptides in parallel gives a refined focus on method development, and the resulting methods should be applicable to other clinically relevant proteins.

Multiple reaction monitoring-based determination of bovine α-lactalbumin in infant formulas and whey protein concentrates by ultra-high performance liquid chromatography–tandem mass spectrometry using tryptic signature peptides and synthetic peptide standards

The determination of α-lactalbumin in various dairy products attracts wide attention in multidiscipline fields because of its nutritional and biological functions. In the present study, we quantified the bovine α-lactalbumin in various infant formulas and whey protein concentrates using ultra-high performance liquid chromatography coupled to tandem mass spectrometer in multiple reaction monitoring mode. Bovine α-lactalbumin was quantified by employing the synthetic internal standard based on the molar equivalent relationship among the internal standard, bovine α-lactalbumin and their signature peptides. This study especially focused on the recovery rates of the sample preparation procedure and robust quantification of total bovine α-lactalbumin in its native and thermally denatured form with a synthetic internal standard KILDKVGINNYWLAHKALCSE. The observed recovery rates of bovine α-lactalbumin ranged from 95.8 to 100.6% and the reproducibility was excellent (RSD<6%) at different spiking levels. The limit of quantitation is 10mg/100g for infant formulas and whey protein concentrates. In order to validate the applicability of the method, 21 brands of infant formulas were analyzed. The acquired contents of bovine α-lactalbumin were 0.67–1.84g/100g in these infant formulas in agreement with their label claimed values. The experiment of heat treatment time showed that the loss of native α-lactalbumin enhanced with an increasing intensity of heat treatment. Comparing with Ren's previous method by analysis of only native bovine α-lactalbumin, the present method at the peptide level proved to be highly suitable for measuring bovine α-lactalbumin in infant formulas and whey protein concentrates, avoiding forgoing the thermally induced denatured α-lactalbumin caused by the technological processing.

Precision of Heavy–Light Peptide Ratios Measured by MALDI-TOF Mass Spectrometry

We have investigated the precision of peptide quantitation by MALDI-TOF mass spectrometry (MS) using six pairs of proteotypic peptides (light) and same-sequence stable isotope labeled synthetic internal standards (heavy). These were combined in two types of dilution curves spanning 100-fold and 2000-fold ratios. Coefficients of variation (CV; standard deviation divided by mean value) were examined across replicate MALDI spots using a reflector acquisition method requiring 100 000 counts for the most intense peak in each summed spectrum. The CV of light/heavy peptide centroid peak area ratios determined on four replicate spots per sample, averaged across 11 points of a 100-fold dilution curve and over all six peptides, was 2.2% (ranging from 1.5 to 3.7% among peptides) at 55 fmol total (light + heavy) of each peptide applied per spot, and 2.5% at 11 fmol applied. The average CV of measurements at near-equivalence (light = heavy, the center of the dilution curve) for the six peptides was 1.0%, about 17-fold lower CV than that observed when five peptides were ratioed to a sixth peptide (i.e., a different-sequence internal standard). Response curves across the 100-fold range were not completely linear but could be closely modeled by a power law fit giving R(2) values >0.998 for all peptides. The MALDI-TOF MS method was used to determine the endogenous level of a proteotypic peptide (EDQYHYLLDR) of human protein C inhibitor (PCI) in a plasma digest after enrichment by capture on a high affinity antipeptide antibody, a technique called stable isotope standards and capture by anti-peptide antibodies (SISCAPA). The level of PCI was determined to be 770 ng/mL with a replicate measurement CV of 1.5% and a >14 000-fold target enrichment via SISCAPA-MALDI-TOF. These results indicate that MALDI-TOF technology can provide precise quantitation of high-to-medium abundance peptide biomarkers over a 100-fold dynamic range when ratioed to same-sequence labeled internal standards and enriched to near purity by specific antibody capture. The robustness and throughput of MALDI-TOF in comparison to conventional nano-LC-MS technology could enable currently impractical large-scale verification studies of protein biomarkers.

Environmental Effects on Allergen Levels in Commercially Grown Non-Genetically Modified Soybeans: Assessing Variation Across North America

Soybean (Glycine max) is a hugely valuable soft commodity that generates tens of billions of dollars annually. This value is due in part to the balanced composition of the seed which is roughly 1:2:2 oil, starch, and protein by weight. In turn, the seeds have many uses with various derivatives appearing broadly in processed food products. As is true with many edible seeds, soybeans contain proteins that are anti-nutritional factors and allergens. Soybean, along with milk, eggs, fish, crustacean shellfish, tree nuts, peanuts, and wheat, elicit a majority of food allergy reactions in the United States. Soybean seed composition can be affected by breeding, and environmental conditions (e.g., temperature, moisture, insect/pathogen load, and/or soil nutrient levels). The objective of this study was to evaluate the influence of genotype and environment on allergen and anti-nutritional proteins in soybean. To address genetic and environmental effects, four varieties of non-GM soybeans were grown in six geographically distinct regions of North America (Georgia, Iowa, Kansas, Nebraska, Ontario, and Pennsylvania). Absolute quantification of proteins by mass spectrometry can be achieved with a technique called multiple reaction monitoring (MRM), during which signals from an endogenous protein are compared to those from a synthetic heavy-labeled internal standard. Using MRM, eight allergens were absolutely quantified for each variety in each environment. Statistical analyses show that for most allergens, the effects of environment far outweigh the differences between varieties brought about by breeding.