Zenka, Roman M.

Abstract Background Sphingolipids play a crucial role in cellular functions and are essential components of cell membranes, signaling molecules, and lipid metabolism. In particular, ceramide is a key intermediate in sphingolipid metabolism and defects in ceramide metabolism can lead to various inborn errors of metabolism, making ceramides important targets for clinical screening and diagnosis. Detecting altered concentration patterns of sphingolipids is desirable for distinguishing related inborn errors of metabolism for diagnosis and treatment monitoring. Methods We developed a liquid chromatography-tandem mass spectrometry method with a pathway-oriented approach to focus on sphingolipids involved in ceramide metabolism. A total of 47 sphingolipids bearing different head groups and side chains were targeted. Precision/reproducibility, linearity, and spike recovery extraction efficiency tests were performed on plasma and serum samples from confirmed cases of sphingolipidosis. Results Linearity of the method showed the coefficient of determination (r2) for all standards to be >0.99 with a slope of 1.00 ± 0.01. Intra- and interday reproducibility of standards spiked into plasma and serum revealed a coefficient of variation <20%. Spike and recovery assessment showed recovery values of 80%–120% for all standards. Altered levels of sphingolipids from patients with hereditary sensory and autonomic neuropathy caused by pathogenic variants in SPTLC2 and hypomyelinating leukodystrophy related to variants in DEGS1 were detected, in agreement with trends reported in earlier studies confirming the utility of this pathway-centric method. Conclusions This method can serve as a useful tool to simultaneously monitor sphingolipids, enabling screening and diagnosis of inborn errors of ceramide metabolism.

Abstract Although the functions of tyrosine phosphatases in T‐cell biology have been extensively studied, our knowledge on the contribution of serine/threonine phosphatases in T cells remains poor. Protein phosphatase 2A (PP2A) is one of the most abundantly expressed serine/threonine phosphatases. It is important in thymocyte development and CD4 + T‐cell differentiation. Utilizing a genetic model in which its catalytic subunit alpha isoform (PP2A Cα) is deleted in T cells, we investigated its contribution to CD8 + T‐cell homeostasis and effector functions. Our results demonstrate that T‐cell intrinsic PP2A Cα is critically required for CD8 + T‐cell homeostasis in secondary lymphoid organs and intestinal mucosal site. Importantly, PP2A Cα–deficient CD8 + T cells exhibit reduced proliferation and survival. CD8 + T‐cell antibacterial response is strictly dependent on PP2A Cα. Expression of Bcl2 transgene rescues CD8 + T‐cell homeostasis in spleens, but not in intestinal mucosal site, nor does it restore defective antibacterial responses. Finally, proteomics and phosphoproteomics analyses reveal potential targets dependent on PP2A Cα, including mTORC1 and AKT. Thus, PP2A Cα is a key modulator of CD8 + T‐cell homeostasis and effector functions.

Abstract A quadrupole time‐of‐flight mass spectrometer coupled with a trapped ion mobility spectrometry (timsTOF) operated in parallel accumulation‐serial fragmentation (PASEF) mode has recently emerged as a platform capable of providing four‐dimensional (4D) features comprising of elution time, collision cross section (CCS), mass‐to‐charge ratio, and intensity of peptides. The PASEF mode provides ∼100% ion sampling efficiency both in data‐dependent acquisition (DDA) and data‐independent acquisition (DIA) modes without sacrificing sensitivity. In addition, targeted measurements using PASEF integrated parallel reaction monitoring (PRM) mode have also been described. However, only limited number of studies have used timsTOF for analysis of clinical samples. Although Orbitrap mass spectrometers have been used for biomarker discovery from cerebrospinal fluid (CSF) in a variety of neurological diseases, these Orbitrap‐derived datasets cannot readily be applied for driving experiments on timsTOF mass spectrometers. We generated a catalog of peptides and proteins in human CSF in DDA mode on a timsTOF mass spectrometer and used these data to build a spectral library. This strategy allowed us to use elution times and ion mobility values from the spectral library to design PRM experiments for quantifying previously discovered biomarkers from CSF samples in Alzheimer's disease. When the same samples were analyzed using a DIA approach combined with a spectral library search, a higher number of proteins were identified than in a library‐free approach. Overall, we have established a spectral library of CSF as a resource and demonstrated its utility for PRM and DIA studies, which should facilitate studies of neurological disorders.

AbstractTRIT1 defect is a rare, autosomal‐recessive disorder of transcription, initially described as a condition with developmental delay, myoclonic seizures, and abnormal mitochondrial function. Currently, only 13 patients have been reported. We reviewed the genetic, clinical, and metabolic aspects of the disease in all known patients, including two novel, unrelated TRIT1 cases with abnormalities in oxidative phosphorylation complexes I and IV in fibroblasts. Taken together the features of all 15 patients, TRIT1 defect could be identified as a potentially recognizable syndrome including myoclonic epilepsy, speech delay, strabismus, progressive spasticity, and variable microcephaly, with normal lactate levels. Half of the patients had oxidative phosphorylation complex measurements and had multiple complex abnormalities.

Abstract Motivation Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms. Materials and methods P2T2 presents diverse data and annotation types in a unified protein-centric view, facilitating the interpretation of coding variants and hypothesis generation. Information from primary sequence, domain, motif, and structural levels are presented and also organized into the first Paralog Annotation Analysis across the human proteome. Results Our tool assists research efforts to interpret genomic variation by aggregating diverse, relevant, and proteome-wide information into a unified interactive web-based interface. Additionally, we provide a REST API enabling automated data queries, or repurposing data for other studies. Conclusion The unified protein-centric interface presented in P2T2 will help researchers interpret novel variants identified through next-generation sequencing. Code and server link available at github.com/GenomicInterpretation/p2t2.

AbstractObjectiveAcute myeloid leukemia (AML) can be subtyped based on recurrent cytogenetic and molecular genetic abnormalities with diagnostic and prognostic significance. Although cytogenetic characterization classically involves conventional chromosome and/or fluorescence in situ hybridization (FISH) assays, limitations of these techniques include poor resolution and the inability to precisely identify breakpoints.MethodWe evaluated whether an NGS‐based methodology that detects structural abnormalities and copy number changes using mate pair sequencing (MPseq) can enhance the diagnostic yield for patients with AML.ResultsUsing 68 known abnormal and 20 karyotypically normal AML samples, each recurrent primary AML‐specific abnormality previously identified in the abnormal samples was confirmed using MPseq. Importantly, in eight cases with abnormalities that could not be resolved by conventional cytogenetic studies, MPseq was utilized to molecularly define eight recurrent AML‐fusion events. In addition, MPseq uncovered two cryptic abnormalities that were missed by conventional cytogenetic studies. Thus, MPseq improved the diagnostic yield in the detection of AML‐specific structural rearrangements in 10/88 (11%) of cases analyzed.ConclusionUtilization of MPseq represents a precise, molecular‐based technique that can be used as an alternative to conventional cytogenetic studies for newly diagnosed AML patients with the potential to revolutionize the diagnosis of hematologic malignancies.

AbstractCopy number variation (CNV) is a common form of structural variation detected in human genomes, occurring as both constitutional and somatic events. Cytogenetic techniques like chromosomal microarray (CMA) are widely used in analyzing CNVs. However, CMA techniques cannot resolve the full nature of these structural variations (i.e. the orientation and location of associated breakpoint junctions) and must be combined with other cytogenetic techniques, such as karyotyping or FISH, to do so. This makes the development of a next‐generation sequencing (NGS) approach capable of resolving both CNVs and breakpoint junctions desirable. Mate‐pair sequencing (MPseq) is a NGS technology designed to find large structural rearrangements across the entire genome. Here we present an algorithm capable of performing copy number analysis from mate‐pair sequencing data. The algorithm uses a step‐wise procedure involving normalization, segmentation, and classification of the sequencing data. The segmentation technique combines both read depth and discordant mate‐pair reads to increase the sensitivity and resolution of CNV calls. The method is particularly suited to MPseq, which is designed to detect breakpoint junctions at high resolution. This allows for the classification step to accurately calculate copy number levels at the relatively low read depth of MPseq. Here we compare results for a series of hematological cancer samples that were tested with CMA and MPseq. We demonstrate comparable sensitivity to the state‐of‐the‐art CMA technology, with the benefit of improved breakpoint resolution. The algorithm provides a powerful analytical tool for the analysis of MPseq results in cancer.

11 Background: Currently there are no serum markers of response to AA. We performed a proteome based analysis of serum from prostate cancer patients, followed by mapping of candidate markers to networks based on known molecular interactions in Ingenuity Knowledge Base (IKB). Methods: Isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) was performed in serum of 3 non-localized prostate cancer cohorts. The first cohort included 15 paired untreated hormone-sensitive “pre AA” and 3-month “post AA” specimens; the second included 10 “early AA failure” (median failure time: 11 months) and the third included 10 “late AA failure” specimens (median failure time: 95 months). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post AA proteomes and (ii) post AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. To facilitate biological interpretation of multiple candidates identified in the comparisons, IPA was used. Candidate markers implicated in IPA networks with statistical significance were pursued in a second, independent patient cohort for association with time to AA failure using univariate Cox regression analysis. Results: Median PSA for pre/post AA first cohort were 3.15 and 0.29 ng/ml. Median PSA for the second and third cohorts were 27.3 and 4.3 ng/ml. Between post AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. Network enrichment analysis of the 47 proteins by IPA identified four interaction networks (p<0.01), one of which highlighted a role for 17-β-estradiol (E1). Gas chromatography used for measuring 3-month post AA initiation serum E1, estrone (E2) and testosterone levels (N=38) detected high E1, E2 levels associated with longer time to AA failure (P=0.07 for E1; P=0.08 for E2) in the independent cohort. Conclusions: A global proteomic analysis identified post AA initiation serum E1, E2 levels as potential response markers, which needs validation.

104 Background: Currently there are no serum predictive markers of response to AA. We used a proteomic based analytic approach to identify candidates. Methods: Serum from three non-localized prostate cancer cohorts was analyzed. The first included15 paired untreated hormone-sensitive “pre-AA” and 3-month “post-AA” specimens; the second included 10 “early AA failure” (median time to AA failure:11 months) and the third included 10 “late AA failure” specimens (median time to AA failure: 95 months). Proteomic analysis was performed with isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post-AA proteomes and (ii) post-AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. ELISA assays were used to verify candidate markers in a second stored aliquot of first cohort specimens. This cohort was followed for AA failure. Association of post-AA ELISA levels of candidate markers with time to AA failure was performed using Cox proportional hazards regression, summarized as relative risk (RR) for AA failure. Results: Median PSA in pre/post-AA first cohort were 3.15 ng/ml and 0.29 ng/ml. Median PSA in the second and third cohorts were 27.3 and 4.3 ng/ml. Between post-AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. ELISA assays verified expression levels of 2/47 proteins in the first cohort; zinc alpha-2 macroglobulin (ZAG), and Neuropilin-2 (NPL2). Median change in ZAG decreased by 2073.5 ng/ml (post versus pre-AA) while median change in NPL2 levels increased by 2.9 ng/ml. After a median follow-up of 43 months from the post-AA time-point, 4/15 first cohort subjects had failed AA. The RR of AA failure for ZAG levels below the median change was 3.8 (95% CI: 0.4-37) and 3.0 (95% CI: 0.3-29) for NPL2. Conclusions: A global proteomic analysis identified ZAG and NPL2 as candidate serum predictive markers of AA response which needs further validation.

Key Points Mass spectrometry is a high-throughput, low-resource technique that can identify immunoglobulin variable region gene from tissue specimens. IGVL gene usage is restricted and different between systemic and localized AL and only partially explains organ tropism in this disease.