Development of parallel reaction monitoring (PRM)-based quantitative proteomics applied to HER2-Positive breast cancer

Tandem mass tagging combined with liquid chromatography-tandem mass spectrometry technique to detect protein markers in gastroesophageal junction adenocarcinoma

BACKGROUND

Gastroesophageal junction adenocarcinoma (GEJA) is a malignant tumor located at the junction of the esophagus and stomach, the incidence of which is increasing year by year, while screening for early biomarkers is limited. Tandem mass tagging (TMT) coupled with liquid chromatography-tandem mass spectrometry (LC/MS/MS) has been used to screen for differential proteins in various cancers.

METHODS

Differential proteins in GEJA and precancerous lesions were screened using TMT-LC/MS/MS, and then proteins that met expectations were selected for trend clustering analysis, combined with GO and KEGG analysis for functional annotation of differential proteins in GEJA. Then, parallel reaction monitoring and immunohistochemistry techniques were used to validate the accuracy of the proteomics data.

RESULTS

Our group screened the differential proteins during GEJA progression using proteomics technology, analyzed the expression trends and functional regions involved in the differential proteins during carcinogenesis, and validated the accuracy of the experimental results.

CONCLUSIONS

The screening of differential proteins in GEJA carcinogenesis based on TMT-LC/MS/MS technology provides detailed information for the elucidation of GEJA progression process, pathogenesis, early screening and screening of candidate markers.

The addition of FAIMS increases targeted proteomics sensitivity from FFPE tumor biopsies

Mass spectrometry-based targeted proteomics allows objective protein quantitation of clinical biomarkers from a single section of formalin-fixed, paraffin-embedded (FFPE) tumor tissue biopsies. We combined high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) to increase assay sensitivity. The modular nature of the FAIMS source allowed direct comparison of the performance of FAIMS-PRM to PRM. Limits of quantitation were determined by spiking synthetic peptides into a human spleen matrix. In addition, 20 clinical samples were analyzed using FAIMS-PRM and the quantitation of HER2 was compared with that obtained with the Ventana immunohistochemistry assay. FAIMS-PRM improved the overall signal-to-noise ratio over that from PRM and increased assay sensitivity in FFPE tissue analysis for four (HER2, EGFR, cMET, and KRAS) of five proteins of clinical interest. FAIMS-PRM enabled sensitive quantitation of basal HER2 expression in breast cancer samples classified as HER2 negative by immunohistochemistry. Furthermore, we determined the degree of FAIMS-dependent background reduction and showed that this correlated with an improved lower limit of quantitation with FAIMS. FAIMS-PRM is anticipated to benefit clinical trials in which multiple biomarker questions must be addressed and the availability of tumor biopsy samples is limited.

Transcriptome profiling and proteomic validation reveals targets of the androgen receptor signaling in the BT-474 breast cancer cell line

BACKGROUND

Accumulating evidence suggests that the androgen receptor (AR) and its endogenous ligands influence disease progression in breast cancer (BCa). However, AR-mediated changes in BCa differ among the various BCa subtypes according to their hormone receptor profile [i.e., presence/absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2, (HER2)]. Thus, we explored the androgen-regulated transcriptomic changes in the ER⁺PR⁺HER2⁺ BCa cell line, BT-474, and compared them with PR-mediated changes.

METHODS

We performed RNA sequencing analysis in treated BT-474 cells with dihydrotestosterone (DHT) and progesterone. Validation of the top ten differentially androgen-regulated genes and a number of other genes found in enriched signaling pathways was performed by qRT-PCR in BT-474 and other BCa cell lines. In addition, a parallel reaction monitoring targeted proteomic approach was developed to verify selected transcripts at the protein level.

RESULTS

In total 19,450 transcripts were detected, of which 224 were differentially regulated after DHT treatment. The increased expression of two well-known androgen-regulated genes, KLK2 (p < 0.05) and KLK3 (p < 0.001), confirmed the successful androgen stimulation in BT-474 cells. The transcription factor, ZBTB16, was the most highly upregulated gene, with ~ 1000-fold change (p < 0.001). Pathway enrichment analysis revealed downregulation of the DNA replication processes (p < 0.05) and upregulation of the androgen signaling and fatty acid metabolism pathways (p < 0.05). Changes related to progesterone treatment showed opposite effects in gene expression than DHT treatment. Similar expression profiles were observed among other BCa cell lines expressing high levels of AR (ZR75.1 and MBA-MB-453). The parallel reaction monitoring targeted proteomic analysis further confirmed that altered protein expression (KLK3, ALOX15B) in the supernatant and cell lysate of DHT-treated BT-474 cells, compared to control cells.

DISCUSSION

Our findings suggest that AR modulates the metabolism of BT-474 cells by affecting the expression of a large number of genes and proteins. Based on further pathway analysis, we suggest that androgen receptor acts as a tumor suppressor in the BT-474 cells.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

Comparative Proteomic Profiling: Cellular Metabolisms Are Mainly Affected in Senecavirus A-Inoculated Cells at an Early Stage of Infection

Senecavirus A (SVA), also known as Seneca Valley virus, belongs to the genus Senecavirus in the family Picornaviridae. SVA can cause vesicular disease and epidemic transient neonatal losses in pigs. This virus efficiently propagates in some non-pig-derived cells, like the baby hamster kidney (BHK) cell line and its derivate (BSR-T7/5). Conventionally, a few proteins or only one protein is selected for exploiting a given mechanism concerning cellular regulation after SVA infection in vitro. Proteomics plays a vital role in the analysis of protein profiling, protein-protein interactions, and protein-directed metabolisms, among others. Tandem mass tag-labeled liquid chromatography-tandem mass spectrometry combined with the parallel reaction monitoring technique is increasingly used for proteomic research. In this study, this combined method was used to uncover separately proteomic profiles of SVA- and non-infected BSR-T7/5 cells. Furthermore, both proteomic profiles were compared with each other. The proteomic profiling showed that a total of 361 differentially expressed proteins were identified, out of which, 305 and 56 were upregulated and downregulated in SVA-infected cells at 12 h post-inoculation, respectively. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses showed that cellular metabolisms were affected mainly in SVA-inoculated cells at an early stage of infection. Therefore, an integrated metabolic atlas remains to be explored via metabolomic methods.

A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. METHODS: In this study we have compiled a list of 636 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV).

RESULTS

Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639-peptide possibilities to 87 peptides that were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Through stringent p-value cutoff combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively.

CONCLUSION

We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from patient samples. We also contend that samples harvested from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.

A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)

The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. In this study we have compiled a list of 639 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV). Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639 peptide possibilities to 87 peptides which were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Applying stringent statistical scoring thresholds, combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively. We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from a variety of sample types. We also contend that samples taken from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.

Identification of proteins related with pemetrexed resistance by iTRAQ and PRM-based comparative proteomic analysis and exploration of IGF2BP2 and FOLR1 functions in non-small cell lung cancer cells

Pemetrexed (PEM), a multi-target folate antagonist, has been extensively used for the treatment of non-small cell lung cancer (NSCLC). However, the therapeutic efficacy of PEM is limited by tumor resistance. In this project, iTRAQ and parallel reaction monitoring (PRM)-based LC-MS/MS comparative proteomic analysis was performed to identify protein determinants of PEM resistance in A549/PEM cells versus A549 parental cells. A total of 567 differentially expressed proteins (DEPs) were identified by iTRAQ analysis. The function and classification of DEPs were analyzed through GO and KEGG Pathway databases. Moreover, PRM analysis further validated the expression changes of 14 DEPs identified by iTRAQ analysis. Moreover, insulin-like growth factor (IGF) 2 mRNA-binding protein 2 (IGF2BP2) or folate receptor alpha (FOLR1) knockdown weakened PEM resistance, reduced cell viability and promoted cell apoptosis in A549/PEM cells. IGF2BP2 depletion inhibited cell migration, invasion and epithelial-mesenchymal transition (EMT), while FOLR1 loss had no much effect on cell migration, invasion and EMT in A549/PEM cells. Our study can provide a deep insight into molecular mechanisms of PEM resistance in NSCLC and contribute to the development of more effective therapeutic schedules. SIGNIFICANCE: Our study can provide deeper insight into molecular mechanisms of PEM resistance in NSCLC and contribute to the development of more effective therapeutic schedules.

Cataloguing the phosphorylation sites of tristetraprolin (TTP): Functional implications for inflammatory diseases

Tristetraprolin (TTP) is a destabilizing mRNA binding protein known to regulate gene expression of a wide variety of targets, including those that control inflammation. TTP expression, regulation and function is controlled by phosphorylation. While the importance of key serine (S) sites (S⁵² and S¹⁷⁸ in mice and S¹⁸⁶ in humans) has been recognized, other sites on the hyperphosphorylated TTP protein have more recently emerged as playing an important role in regulating cellular signalling and downstream functions of TTP. In order to propel investigation of TTP and fully exploit its potential as a drug target in inflammatory disease, this review will catalogue TTP phosphorylation sites in both the murine and human TTP protein, the known and unknown roles and functions of these sites, the kinases and phosphatases that act upon TTP and overview methodological approaches to increase our knowledge of this important protein regulated by phosphorylation.

Phosphorylation Ratio Determination in Fresh-Frozen and Formalin-Fixed Paraffin-Embedded Tissue with Targeted Mass Spectrometry

Formalin-fixed paraffin-embedded (FFPE) tissues are routinely prepared and collected for diagnostics in pathology departments. These are, therefore, the most accessible research sources in pathology archives. In this study we investigated whether we can apply a targeted and quantitative parallel reaction monitoring (PRM) method for FFPE tissue samples in a sensitive and reproducible way. The feasibility of this technical approach was demonstrated for normal brain and glioblastoma multiforme tissues. Two methods were used: PRM measurement of a tryptic digest without phosphopeptide enrichment (Direct-PRM) and after Fe-NTA phosphopeptide enrichment (Fe-NTA-PRM). With these two methods, the phosphorylation ratio could be determined for four selected peptide pairs that originate from neuroblast differentiation-associated protein (AHNAK S5448-p), calcium/calmodulin-dependent protein kinase type II subunit delta (CAMK2D T337-p), eukaryotic translation initiation factor 4B (EIF4B S93-p), and epidermal growth factor receptor (EGFR S1166-p). In normal brain FFPE tissues, the Fe-NTA-PRM method enabled the quantification of targeted phosphorylated peptides with high reproducibility (CV < 14%). Our results indicate that formalin fixation does not impede relative quantification of a phospho-site and its phosphorylation ratio in FFPE tissues. The developed workflow combining these methods opens ways to study archival FFPE tissues for phosphorylation ratio determination in proteins.

The status of proteomics as we enter the 2020s: Towards personalised/precision medicine

The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.

Investigation of cancer drug resistance mechanisms by phosphoproteomics

Cancer cell mutations can be identified by genomic and transcriptomic techniques. However, they are not sufficient to understand the full complexity of cancer heterogeneity. Analyses of proteins expressed in cancers and their modification profiles show how these mutations could be translated at the functional level. Protein phosphorylation is a major post-translational modification critical for regulating several cellular functions. The covalent addition of phosphate groups to serine, threonine, and tyrosine is catalyzed by protein kinases. Over the past years, kinases were strongly associated with cancer, thus inhibition of protein kinases emanated as novel cancer treatment. However, cancers frequently develop drug resistance. Therefore, a better understanding of drug effects on tumors is urgently needed. In this perspective, phosphoproteomics arose as advanced tool to monitor cancer therapies and to discover novel drugs. This review highlights the role of phosphoproteomics in predicting sensitivity or resistance of cancers towards tyrosine kinase inhibitors and cytotoxic drugs. It also shows the importance of phosphoproteomics in identifying biomarkers that could be applied in clinical diagnostics to predict responses to drugs.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Protein spectrum changes in exosomes after therapeutic plasma exchange in patients with neuromyelitis optica

INTRODUCTION

Neuromyelitis optica (NMO) is an autoimmune disease with a high rate of blindness and positive for the detection of aquaporin-4 antibody (AQP4) in most patients. NMO acute attacks are managed by high-doses of intravenous methylprednisolone followed by oral taper, and if symptoms fail to resolve, therapeutic plasma exchange (TPE) is added. TPE can remove pathological antibodies and inflammatory factors leading to clinical improvement.

METHODS

A total of 40 TPE fluid collections from the first to fifth TPE treatments were obtained from eight patients. Exosomes were isolated by ultracentrifugation. Mass spectrometry analyses were used to compare protein change in TPE fluid collection exosomes after the first to the fifth TPE treatments in these patients.

RESULTS

We detected 647 exosome proteins through data-independent acquisition analysis. It was found that some unknown functional antibody fragments and complement pathway proteins decreased after TPE treatment. The results revealed a significant involvement of the following two key pathways: the primary immunodeficiency and systemic lupus erythematosus that may be associated with NMO pathophysiology and TPE treatment efficacy (P < .05). A series of complement proteins may contribute to NMO; in addition, the following proteins increased with plasma exchange: complement factor H-related protein 5, bridging integrator 2, neuroplastin, pigment epithelium-derived factor, ficolin-1, extracellular matrix protein 1, and fatty acid-binding protein 5.

CONCLUSION

Our study may provide a new perspective on the pathogenesis and treatment efficacy of NMO.