Systematic identification of single amino acid variants in glioma stem-cell-derived chromosome 19 proteins

Glioma and post-translational modifications: A complex relationship

Post-translational modifications (PTMs) are common covalent processes in biochemical pathways that alter protein function and activity. These modifications occur through proteolytic cleavage or attachment of modifying groups, such as phosphoryl, methyl, glycosyl, or acetyl groups, with one or more amino acid residues of a single protein. Some PTMs also present crosstalk abilities that affect both protein functionality and structure, creating new proteoforms. Any alteration in organism homeostasis may be a cancer hallmark. Cataloging PTMs and consequently, emerging proteoforms, present new therapeutic targets, approaches, and opportunities to discover additional discriminatory biomarkers in disease diagnostics. In this review, we focus on experimentally confirmed PTMs and their potential crosstalk in glioma research to introduce new opportunities for this tumor type, which emerge within the PTMomics area.

Mass spectrometry-based targeted proteomics for analysis of protein mutations

Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.

Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection

Discovery of variant peptides such as a single amino acid variant (SAAV) in shotgun proteomics data is essential for personalized proteomics. Both the resolution of shotgun proteomics methods and the search engines have improved dramatically, allowing for confident identification of SAAV peptides. However, it is not yet known if these methods are truly successful in accurately identifying SAAV peptides without prior genomic information in the search database. We studied this in unprecedented detail by exploiting publicly available long-read RNA sequences and shotgun proteomics data from the gold standard reference cell line NA12878. Searching spectra from this cell line with the state-of-the-art open modification search engine ionbot against carefully curated search databases resulted in 96.7% false-positive SAAVs and an 85% lower true positive rate than searching with peptide search databases that incorporate prior genetic information. While adding genetic variants to the search database remains indispensable for correct peptide identification, inclusion of long-read RNA sequences in the search database contributes only 0.3% new peptide identifications. These findings reveal the differences in SAAV detection that result from various approaches, providing guidance to researchers studying SAAV peptides and developers of peptide spectrum identification tools.

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

Detecting single amino acids and small peptides by combining isobaric tags and peptidomics

Single amino acids and small endogenous peptides play important roles in maintaining a properly functioning organism. These molecules are however currently only routinely identified in targeted approaches. In a small proof-of-concept mass spectrometry experiment, we found that by combining isobaric tags and peptidomics, and by targeting singly charged molecules, we were able to identify a significant amount of single amino acids and small endogenous peptides using a basic mass-based identification approach. While there is still room for improvement, our simple test indicates that a limited amount of extra work when setting up the mass spectrometry experiment could potentially lead to a wealth of additional information.

Single Amino Acid Variant Discovery in Small Numbers of Cells

We have performed deep proteomic profiling down to as few as 9 Panc-1 cells using sample fractionation, TMT multiplexing, and a carrier/reference strategy. Off line fractionation of the TMT-labeled sample pooled with TMT-labeled carrier Panc-1 whole cell proteome was achieved using alkaline reversed phase spin columns. The fractionation in conjunction with the carrier/reference (C/R) proteome allowed us to detect 47 414 unique peptides derived from 6261 proteins, which provided a sufficient coverage to search for single amino acid variants (SAAVs) related to cancer. This high sample coverage is essential in order to detect a significant number of SAAVs. In order to verify genuine SAAVs versus false SAAVs, we used the SAVControl pipeline and found a total of 79 SAAVs from the 9-cell Panc-1 sample and 174 SAAVs from the 5000-cell Panc-1 C/R proteome. The SAAVs as sorted into high confidence and low confidence SAAVs were checked manually. All the high confidence SAAVs were found to be genuine SAAVs, while half of the low confidence SAAVs were found to be false SAAVs mainly related to PTMs. We identified several cancer-related SAAVs including KRAS, which is an important oncoprotein in pancreatic cancer. In addition, we were able to detect sites involved in loss or gain of glycosylation due to the enhanced coverage available in these experiments where we can detect both sites of loss and gain of glycosylation.

Multistage Ultraviolet Photodissociation Mass Spectrometry To Characterize Single Amino Acid Variants of Human Mitochondrial BCAT2

Unraveling disease mechanisms requires a comprehensive understanding of how the interplay between higher-order structure and protein-ligand interactions impacts the function of a given protein. Recent advances in native mass spectrometry (MS) involving multimodal or higher-energy activation methods have allowed direct interrogation of intact protein complexes in the gas phase, allowing analysis of both composition and subunit connectivity. We report a multistage approach combining collisional activation and 193 nm ultraviolet photodissociation (UVPD) to characterize single amino acid variants of the human mitochondrial enzyme branched-chain amino acid transferase 2 (BCAT2), a protein implicated in chemotherapeutic resistance in glioblastoma tumors. Native electrospray ionization confirms that both proteins exist as homodimers. Front-end collisional activation disassembles the dimers into monomeric subunits that are further interrogated using UVPD to yield high sequence coverage of the mutated region. Additionally, holo (ligand-bound) fragment ions resulting from photodissociation reveal that the mutation causes destabilization of the interactions with a bound cofactor. This study demonstrates the unique advantages of implementing UVPD in a multistage MS approach for analyzing intact protein assemblies.

Large Scale Identification of Variant Proteins in Glioma Stem Cells

Glioblastoma (GBM), the most malignant of primary brain tumors, is a devastating and deadly disease, with a median survival of 14 months from diagnosis, despite standard regimens of radical brain tumor surgery, maximal safe radiation, and concomitant chemotherapy. GBM tumors nearly always re-emerge after initial treatment and frequently display resistance to current treatments. One theory that may explain GBM re-emergence is the existence of glioma stemlike cells (GSCs). We sought to identify variant protein features expressed in low passage GSCs derived from patient tumors. To this end, we developed a proteomic database that reflected variant and nonvariant sequences in the human proteome, and applied a novel retrograde proteomic workflow, to identify and validate the expression of 126 protein variants in 33 glioma stem cell strains. These newly identified proteins may harbor a subset of novel protein targets for future development of GBM therapy.

Combined Proteomic-Molecular Epidemiology Approach to Identify Precision Targets in Brain Cancer

Primary brain tumors are predominantly malignant gliomas. Grade IV astrocytomas (glioblastomas, GBM) are among the most deadly of all tumors; most patients will succumb to their disease within 2 years of diagnosis despite standard of care. The grim outlook for brain tumor patients indicates that novel precision therapeutic targets must be identified. Our hypothesis is that the cancer proteomes of glioma tumors may contain protein variants that are linked to the aggressive pathology of the disease. To this end, we devised a novel workflow that combined variant proteomics with molecular epidemiological mining of public cancer data sets to identify 10 previously unrecognized variants linked to the risk of death in low grade glioma or GBM. We hypothesize that a subset of the protein variants may be successfully developed in the future as novel targets for malignant gliomas.

Intact Protein Analysis at 21 Tesla and X-Ray Crystallography Define Structural Differences in Single Amino Acid Variants of Human Mitochondrial Branched-Chain Amino Acid Aminotransferase 2 (BCAT2)

Structural technologies are an essential component in the design of precision therapeutics. Precision medicine entails the development of therapeutics directed toward a designated target protein, with the goal to deliver the right drug to the right patient at the right time. In the field of oncology, protein structural variants are often associated with oncogenic potential. In a previous proteogenomic screen of patient-derived glioblastoma (GBM) tumor materials, we identified a sequence variant of human mitochondrial branched-chain amino acid aminotransferase 2 as a putative factor of resistance of GBM to standard-of-care-treatments. The enzyme generates glutamate, which is neurotoxic. To elucidate structural coordinates that may confer altered substrate binding or activity of the variant BCAT2 T186R, a ~45 kDa protein, we applied combined ETD and CID top-down mass spectrometry in a LC-FT-ICR MS at 21 T, and X-Ray crystallography in the study of both the variant and non-variant intact proteins. The combined ETD/CID fragmentation pattern allowed for not only extensive sequence coverage but also confident localization of the amino acid variant to its position in the sequence. The crystallographic experiments confirmed the hypothesis generated by in silico structural homology modeling, that the Lys59 side-chain of BCAT2 may repulse the Arg186 in the variant protein (PDB code: 5MPR), leading to destabilization of the protein dimer and altered enzyme kinetics. Taken together, the MS and novel 3D structural data give us reason to further pursue BCAT2 T186R as a precision drug target in GBM. Graphical Abstract ᅟ.

Single Amino Acid Variant Profiles of Subpopulations in the MCF-7 Breast Cancer Cell Line

Cancers are initiated and developed from a small population of stem-like cells termed cancer stem cells (CSCs). There is heterogeneity among this CSC population that leads to multiple subpopulations with their own distinct biological features and protein expression. The protein expression and function may be impacted by amino acid variants that can occur largely due to single nucleotide changes. We have thus performed proteomic analysis of breast CSC subpopulations by mass spectrometry to study the presence of single amino acid variants (SAAVs) and their relation to breast cancer. We have used CSC markers to isolate pure breast CSC subpopulation fractions (ALDH+ and CD44+/CD24- cell populations) and the mature luminal cells (CD49f-EpCAM+) from the MCF-7 breast cancer cell line. By searching the Swiss-CanSAAVs database, 374 unique SAAVs were identified in total, where 27 are cancer-related SAAVs. 135 unique SAAVs were found in the CSC population compared with the mature luminal cells. The distribution of SAAVs detected in MCF-7 cells was compared with those predicted from the Swiss-CanSAAVs database, where we found distinct differences in the numbers of SAAVs detected relative to that expected from the Swiss-CanSAAVs database for several of the amino acids.

Towards the Molecular Foundations of Glutamatergic-targeted Antidepressants

BACKGROUND

Depression affects over 120 million individuals of all ages and is the leading cause of disability worldwide. The lack of objective diagnostic criteria, together with the heterogeneity of the depressive disorder itself, makes it challenging to develop effective therapies. The accumulation of preclinical data over the past 20 years derived from a multitude of models using many divergent approaches, has fueled the resurgence of interest in targeting glutamatergic neurotransmission for the treatment of major depression.

OBJECTIVE

The emergence of mechanistic studies are advancing our understanding of the molecular underpinnings of depression. While clearly far from complete and conclusive, they offer the potential to lead to the rational design of more specific therapeutic strategies and the development of safer and more effective rapid acting, long lasting antidepressants.

METHODS

The development of comprehensive omics-based approaches to the dysregulation of synaptic transmission and plasticity that underlies the core pathophysiology of MDD are reviewed to illustrate the fundamental elements.

RESULTS

This review frames the rationale for the conceptualization of depression as a "pathway disease". As such, it culminates in the call for the development of novel state-of-the-art "-omics approaches" and neurosystems biological techniques necessary to advance our understanding of spatiotemporal interactions associated with targeting glutamatergic-triggered signaling in the CNS.

CONCLUSION

These technologies will enable the development of novel psychiatric medications specifically targeted to impact specific, critical intracellular networks in a more focused manner and have the potential to offer new dimensions in the area of translational neuropsychiatry.

Association of chromosome 19 to lung cancer genotypes and phenotypes

The Chromosome 19 Consortium, a part of the Chromosome-Centric Human Proteome Project (C-HPP, http://www.C-HPP.org ), is tasked with the understanding chromosome 19 functions at the gene and protein levels, as well as their roles in lung oncogenesis. Comparative genomic hybridization (CGH) studies revealed chromosome aberration in lung cancer subtypes, including ADC, SCC, LCC, and SCLC. The most common abnormality is 19p loss and 19q gain. Sixty-four aberrant genes identified in previous genomic studies and their encoded protein functions were further validated in the neXtProt database ( http://www.nextprot.org/ ). Among those, the loss of tumor suppressor genes STK11, MUM1, KISS1R (19p13.3), and BRG1 (19p13.13) is associated with lung oncogenesis or remote metastasis. Gene aberrations include translocation t(15, 19) (q13, p13.1) fusion oncogene BRD4-NUT, DNA repair genes (ERCC1, ERCC2, XRCC1), TGFβ1 pathway activation genes (TGFB1, LTBP4), Dyrk1B, and potential oncogenesis protector genes such as NFkB pathway inhibition genes (NFKBIB, PPP1R13L) and EGLN2. In conclusion, neXtProt is an effective resource for the validation of gene aberrations identified in genomic studies. It promises to enhance our understanding of lung cancer oncogenesis.

Mutant Proteogenomics

Identification of mutant proteins in biological samples is one of the emerging areas of proteogenomics. Despite the fact that only a limited number of studies have been published up to now, it has the potential to recognize novel disease biomarkers that have unique structure and desirably high specificity. Such properties would identify mutant proteoforms related to diseases as optimal drug targets useful for future therapeutic strategies. While mass spectrometry has demonstrated its outstanding analytical power in proteomics, the most frequently applied bottom-up strategy is not suitable for the detection of mutant proteins if only databases with consensus sequences are searched. It is likely that many unassigned tandem mass spectra of tryptic peptides originate from single amino acid variants (SAAVs). To address this problem, a couple of protein databases have been constructed that include canonical and SAAV sequences, allowing for the observation of mutant proteoforms in mass spectral data for the first time. Since the resulting large search space may compromise the probability of identifications, a novel concept was proposed that included identification as well as verification strategies. Together with transcriptome based approaches, targeted proteomics appears to be a suitable method for the verification of initial identifications in databases and can also provide quantitative insights to expression profiles, which often reflect disease progression. Important applications in the field of mutant proteoform identification have already highlighted novel biomarkers in large-scale investigations.

Reconciling proteomics with next generation sequencing

Both genomics and proteomics technologies have matured in the last decade to a level where they are able to deliver system-wide data on the qualitative and quantitative abundance of their respective molecular entities, that is DNA/RNA and proteins. A next logical step is the collective use of these technologies, ideally gathering data on matching samples. The first large scale so-called proteogenomics studies are emerging, and display the benefits each of these layers of analysis has on the other layers to together generate more meaningful insight into the connection between the phenotype/physiology and genotype of the system under study. Here we review a selected number of these studies, highlighting what they can uniquely deliver. We also discuss the future potential and remaining challenges, from a somewhat proteome biased perspective.