Quantitative proteomics identifies brain acid soluble protein 1 (BASP1) as a prognostic biomarker candidate in pancreatic cancer tissue

Analysis of the role of CHPF in colorectal cancer tumorigenesis and immunotherapy based on bioinformatics and experiments

BACKGROUND

Chondroitin polymerizing factor (CHPF) has been found to be involved in the development of numerous cancers and correlated with poor prognosis. However, its role in the tumorigenesis and development of colorectal cancer (CRC) remains unknown.

METHODS

In our research, we explored CHPF expression and clinicopathological characteristics using The Cancer Genome Atlas Program (TCGA), UALCAN, GSE9348, TIMER2.0 and The Human Protein Atlas (HPA) database, in addition, we validated CHPF expression in CRC cell lines by Real-Time Quantitative PCR (qRT-PCR) and Western blot (WB). KM-Plotter, PrognoScan and TCGA were also utilized to verify its prognosis value in CRC. Small-interfer RNA (Si-RNA) was used to perform Cell Counting Kit-8 (CCK8), colony formation, 5-ethynyl-2'-deoxyuridine (EDU), transwell and wound healing assays to testify its function on the tumor progression. Based on TCGA database, we probed potential biological mechanism by which CHPF play its role via clusterProfiler package and GEPIA database and we validated their correlation by WB assay. Moreover, we explored its potential association with the tumor microenvironment (TME), immune infiltrated cells, immune checkpoints, tumor mutation burden (TMB) as well as microsatellite instability (MSI), and investigated immunotherapy sensitivity via Tumor Immune Dysfunction and Exclusion (TIDE) algorithm as well as potentially effective therapeutic drugs via pRRophetic algorithm.

RESULTS

CHPF was identified upregulated in CRC tissues and cells, correlated with poor prognosis, and nodal metastasis status, stage and histological subtype. Down-regulation of CHPF inhibited CRC cell proliferation, migration and its expression correlated with wnt pathway key molecules. In addition, high expression of CHPF was positively correlated with TME scores, Regulatory T cells (Tregs) cell infiltration degree, Programmed death-1 (PD-1), MSI-high (MSI-H), and TIDE scores, however, not with TMB. Targeted drug analysis showed that patients with high CHPF expression were more sensitive to telatinib, recaparib, serdemetan, and trametinib.

CONCLUSION

CHPF could promote the proliferation and migration of CRC cells and lead to poor prognosis, possibly through wnt pathways as well as changes in TME. Patients with high expression of CHPF had poor efficacy in immunotherapy, which might be related to Tregs cell infiltration. Above all, it might offer more reliable guidance for future immunotherapy.

Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host-microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives.

Deciphering the tumor immune microenvironment of imatinib-resistance in advanced gastrointestinal stromal tumors at single-cell resolution

The heterogeneous nature of tumors presents a considerable obstacle in addressing imatinib resistance in advanced cases of gastrointestinal stromal tumors (GIST). To address this issue, we conducted single-cell RNA-sequencing in primary tumors as well as peritoneal and liver metastases from patients diagnosed with locally advanced or advanced GIST. Single-cell transcriptomic signatures of tumor microenvironment (TME) were analyzed. Immunohistochemistry and multiplex immunofluorescence staining were used to further validate it. This analysis revealed unique tumor evolutionary patterns, transcriptome features, dynamic cell-state changes, and different metabolic reprogramming. The findings indicate that in imatinib-resistant TME, tumor cells with activated immune and cytokine-mediated immune responses interacted with a higher proportion of Treg cells via the TIGIT-NECTIN2 axis. Future immunotherapeutic strategies targeting Treg may provide new directions for the treatment of imatinib-resistant patients. In addition, IDO1+ dendritic cells (DC) were highly enriched in imatinib-resistant TME, interacting with various myeloid cells via the BTLA-TNFRSF14 axis, while the interaction was not significant in imatinib-sensitive TME. Our study highlights the transcriptional heterogeneity and distinct immunosuppressive microenvironment of advanced GIST, which provides novel therapeutic strategies and innovative immunotherapeutic agents for imatinib resistance.

An integrated study to decipher immunosuppressive cellular communication in the PDAC environment

Pancreatic ductal adenocarcinoma (PDAC) is one the most aggressive cancers and characterized by a highly rigid and immunosuppressive tumor microenvironment (TME). The extensive cellular interactions are known to play key roles in the immune evasion, chemoresistance, and poor prognosis. Here, we used the spatial transcriptomics, scRNA-seq, and bulk RNA-seq datasets to enhance the insights obtained from each to decipher the cellular communication in the TME. The complex crosstalk in PDAC samples was revealed by the single-cell and spatial transcriptomics profiles of the samples. We show that tumor-associated macrophages (TAMs) are the central cell types in the regulation of microenvironment in PDAC. They colocalize with the cancer cells and tumor-suppressor immune cells and take roles to provide an immunosuppressive environment. LGALS9 gene which is upregulated in PDAC tumor samples in comparison to healthy samples was also found to be upregulated in TAMs compared to tumor-suppressor immune cells in cancer samples. Additionally, LGALS9 was found to be the primary component in the crosstalk between TAMs and the other cells. The widespread expression of P4HB gene and its interaction with LGALS9 was also notable. Our findings point to a profound role of TAMs via LGALS9 and its interaction with P4HB that should be considered for further elucidation as target in the combinatory immunotherapies for PDAC.

BASP1 promotes high glucose-induced endothelial apoptosis in diabetes via activation of EGFR signaling

AIMS

Diabetes mellitus is a common chronic disease of glucose metabolism. Endothelial dysfunction is an early event in diabetes complicated by cardiovascular disease. This study aimed to reveal the expression of BASP1 and its biological roles in endothelial cell dysfunction in diabetes complicated by cardiovascular disease.

MATERIALS AND METHODS

By analyzing the databases related to diabetes complicated with coronary heart disease, BASP1 was screened out as an upregulated gene. Human umbilical vein endothelial cells (HUVECs) and primary mouse aortic endothelial cells were treated with high glucose to establish cell models of diabetes-related endothelial dysfunction, and the expression changes of BASP1 were verified by RT-qPCR, western blot, and immunofluorescence. BASP1 was silenced or overexpressed by siRNA or overexpression plasmid, and its effects on cell migration, apoptosis, tube formation, inflammatory response, and ROS were detected. The possible signaling pathway of BASP1 was found and the mechanism of BASP1 on promoting the progression of endothelial dysfunction was explored using the EGFR inhibitor, gefitinib.

RESULTS

Bioinformatics analysis indicated that the expression of BASP1 in patients with diabetes mellitus and concomitant coronary heart disease was increased. High glucose induced the upregulation of BASP1 expression in endothelial cells, and showed a time-dependent relationship. Silencing of BASP1 alleviated the damage of high glucose to endothelial cells. BASP1 regulated EGFR positively. The promoting effect of BASP1 on endothelial cell apoptosis may be achieved by regulating the EGFR pathway.

CONCLUSION

BASP1 promotes endothelial cell injury induced by high glucose in patients with diabetes, which may be activated by activating the EGFR pathway.

BASP1 is a prognostic biomarker associated with immunotherapeutic response in head and neck squamous cell carcinoma

Backgrounds

Immunotherapy is effective in a subset of head and neck squamous cell carcinoma (HNSCC). However, the unfavorable response rate and inadequate biomarkers for stratifying patients have primarily limited its clinical application. Considering transcriptional factors (TFs) play essential roles in regulating immune activity during HNSCC progression, we comprehensively analyzed the expression alterations of TFs and their prognostic values.

Methods

Gene expression datasets and clinical information of HNSCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repository. Then, Brain abundant membrane attached signal protein 1 (BASP1) was screened out of differentially expressed TFs by univariate and multivariate survival analysis. Tumor immune dysfunction and exclusion (TIDE) was applied to analyze the response to immunotherapy of BASP1^high/low patients. Meanwhile, GO, KEGG and GSEA analyses were used to enrich the pathways between the BASP1^high and BASP1^low groups. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT, EPIC and quanTiseq algorithms were applied to explore immune infiltrations. Also, immune cycle analysis was conducted by ssGSEA. Additionally, lipid peroxidation, glutathione and reactive oxygen species were performed to detect the ferroptosis alternations.

Results

BASP1 was upregulated and associated with poor survival in HNSCC patients. BASP1^high patients exhibited better response rates to anti-PD-1 immunotherapy and higher expressions of immune checkpoint inhibitors. GO, KEGG and GSEA analyses indicated that the expression of BASP1 was related to several immune-related pathways and immunogenic ferroptosis signature. The infiltration of activated CD8⁺ T cells was authenticated to be decreased in BASP1^high patients. Furthermore, BASP1 was identified to be positively correlated with T cell dysfunction and immune escape. Moreover, silencing BASP1 triggered ferroptosis in HNSCC cells, representing as increased LDH, lipid peroxidation and ROS levels, and reduced glutathione synthesis.

Conclusions

We demonstrated that BASP1 suppressed immunogenic ferroptosis to induce immunosuppressive tumor microenvironment. BASP1 plays a critical role in immune response, and might be a promising classifier for selecting HNSCC patients who benefit from current immunotherapy.

Surface protein profiling of prostate-derived extracellular vesicles by mass spectrometry and proximity assays

Extracellular vesicles (EVs) are mediators of intercellular communication and a promising class of biomarkers. Surface proteins of EVs play decisive roles in establishing a connection with recipient cells, and they are putative targets for diagnostic assays. Analysis of the surface proteins can thus both illuminate the biological functions of EVs and help identify potential biomarkers. We developed a strategy combining high-resolution mass spectrometry (HRMS) and  proximity ligation assays (PLA) to first identify and then validate surface proteins discovered on EVs. We applied our workflow to investigate surface proteins of small EVs found in seminal fluid (SF-sEV). We identified 1,014 surface proteins and verified the presence of a subset of these on the surface of SF-sEVs. Our work demonstrates a general strategy for deep analysis of EVs' surface proteins across patients and pathological conditions, proceeding from unbiased screening by HRMS to ultra-sensitive targeted analyses via PLA.

STAM binding protein regulated by hsa_circ_0007334 exerts oncogenic potential in pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a highly aggressive and metastatic malignancy. The molecular events related to PC have not yet been fully elucidated. The STAM binding protein (STAMBP), a deubiquitinase, contributes to carcinogenesis in several types of cancer. Our study aims to investigate the function of STAMBP in the progression of PC.

METHODS

Fifteen pairs of tumor and tumor-adjacent tissues were obtained from PC patients. Human pancreatic cancer cell lines, SW 1990 and BxPC-3, were transfected with short hairpin RNA targeting STAMBP or/and vectors overexpressing wild-type STAMBP or STAMBP D348A mutants (inactive mutants of STAMBP). SW 1990 cells were co-transfected with vectors overexpressing STAMBP and small interfering RNA targeting hsa_circ_0007334.

RESULTS

STAMBP was overexpressed in the tumor tissues as compared with the tumor-adjacent tissues from PC patients. Higher STAMBP expression in the tumor tissues showed worse prognosis. Loss/gain-of-function experiments revealed that STAMBP promoted the malignant behaviors of PC cells in vitro and xenograft tumor growth in vivo. Activation of NF-κB in PC cells was triggered by STAMBP. However, inactive mutants of STAMBP lost these biological functions in PC. hsa_circ_0007334, an oncogene in PC progression, was found to up-regulate STAMBP expression in PC cells. STAMBP up-regulation reversed the effects of hsa_circ_0007334 silencing on cell mobility.

CONCLUSIONS

These results indicated that STAMBP depended on its deubiquitinase activities to induce the malignant behaviors of PC cells and was involved in the regulatory mechanism of hsa_circ_0007334 on PC cell mobility. Our findings provide a novel insight into the molecular mechanism of PC.

Policosanol suppresses tumor progression in a gastric cancer xenograft model

Gastric cancer (GC) is the most common cancer worldwide and the third leading cause of cancer death, with the fifth highest incidence. The development of effective chemotherapeutic agents is needed to decrease GC mortality. Policosanol (PC) extracted from Cuban sugar cane wax is a healthy functional food ingredient that helps improve blood cholesterol levels and blood pressure. Its various physiological activities, such as antioxidant, anti-inflammatory, and anticancer activities, have been reported recently. Nevertheless, the therapeutic efficacy of PC in gastric xenograft models is unclear. We aimed to investigate the anticancer effect of PC on human GC SNU-16 cells and a xenograft mouse model. PC significantly inhibited GC cell viability and delayed tumor growth without toxicity in the SNU-16-derived xenograft model. Therefore, we investigated protein expression levels in tumor tissues; the expression levels of Ki-67, a proliferation marker, and cdc2 were decreased. In addition, we performed proteomic analysis and found thirteen differentially expressed proteins. Our results suggested that PC inhibited GC progression via cdc2 suppression and extracellular matrix protein regulation. Notably, our findings might contribute to the development of novel and effective therapeutic strategies for GC.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

ITGBL1 transcriptionally inhibited by JDP2 promotes the development of pancreatic cancer through the TGF-beta/Smad pathway

Pancreatic cancer (PC) is one of the malignant tumors with the worst prognosis worldwide because of a lack of early diagnostic markers and efficient therapies. Integrin, beta-like 1 (ITGBL1) is a β-integrin-related extracellular matrix protein and is reported to promote progression of some types of cancer. Nevertheless, the function of ITGBL1 in PC is still not clear. Herein, we found that ITGBL1 was highly expressed in PC tissues compared to normal tissues (P<0.05) and PC patients with higher TGBL1 expression showed worse prognosis. PANC-1 and AsPC-1 cells were used for gain/loss-of-function experiments. We found that ITGBL1-silenced cells exhibited decreased proliferation, migration, and invasion abilities and delayed cell cycle, whereas ITGBL1 overexpression reversed these malignant behaviors. ITGBL1 was also demonstrated to activate the TGF-β/Smad pathway, a key signaling pathway in PC progression. Additionally, ITGBL1 expression was found to be suppressed by a suppressor of PC progression, c-Jun dimerization protein 2 (JDP2). Results of dual-luciferase assay indicated that transcription factor JDP2 could inhibit TGBL1 promoter activity. ITGBL1 overexpression inversed the effects of JDP2 up-regulation on cell function. Collectively, we concluded that ITGBL1 may be transcriptionally suppressed by JDP2 and promote PC progression through the TGF-β/Smad pathway, indicating that ITGBL1 may have therapeutic potential for the treatment of PC.

Salivary Proteome, Inflammatory, and NETosis Biomarkers in Older Adult Practitioners and Nonpractitioners of Physical Exercise

Since aging has been associated with increased production of inflammatory biomarkers, the ability to monitor older adults repeatedly is highly desirable, and saliva is an interesting biofluid for the search of biomarkers, as it is easily accessible in a noninvasive manner. However, given the incipient knowledge of salivary biomarkers in aging and its relationship to physical exercise, the present study is aimed at evaluating the protein expression and the levels of inflammatory and NETosis biomarkers in the saliva of practitioners (PE) and nonpractitioners (NPE) of physical exercise older adults. Six (6) practitioner and 4 nonpractitioner older adults were enrolled in this study. Unstimulated whole saliva was collected for analysis of the proteome by label-free mass spectrometry, as well as of the inflammatory status by evaluation of C-reactive protein (CRP), vascular endothelial growth factor (VEGF), and cytokines (TNF-α, interleukin- (IL-) 1β, and IL-8), while NETosis was assessed by myeloperoxidase (MPO) and neutrophil elastase. Regarding oral health, the decayed, missing, and filled teeth (DMF-T) index, bleeding on probing, suppuration, and probing depth measurement (mm) were evaluated. In addition, functional capacity was investigated using the General Physical Fitness Index (GPFI). In relation to the proteome analysis, 93 and 143 proteins were found exclusively in the PE and NPE groups, respectively; 224 proteins were common to both groups. Among these proteins, 10 proteins showed statistical difference ( $p<0.05$ ) between the groups: alpha-2-macroglobulin, component 3 of the complement, serotransferrin, and protein soluble in brain acid 1 were less expressed, while lactotransferrin, alpha-amylase 1, S100-A8, S100-A9, lactoperoxidase, and galectin-3 binding protein were more expressed in the PE group. No differences between groups were observed in the analysis of inflammatory and NETosis biomarkers. This study shows the potential utility of saliva for detecting protein biomarkers in a noninvasive biological sample of the elderly population.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

An Electrochemical and Raman Scattering Dual Detection Biosensor for Rapid Screening and Biomolecular Profiling of Cancer Biomarkers

Detecting circulating biomarkers sensitively and quantitatively is paramount for cancer screening, diagnosis, and treatment selection. Particularly, screening of a panel of circulating protein biomarkers followed by mapping of individual biomarkers could assist better diagnosis and understanding of the cancer progression mechanisms. Herein, we present a miniaturized biosensing platform with dual readout schemes (electrochemical and Surface enhanced Raman scattering (SERS)) for rapid cancer screening and specific biomarker expressional profiling to support cancer management. Our approach utilizes a controlled nanomixing phenomena under alternative current electrohydrodynamic condition to improve the isolation of cancer-associated circulating proteins (i.e., Epidermal growth factor receptor (EGFR), BRAF, Programmed death-ligand 1 (PD-L1)) with antibody functionalized sensor surface for rapid and efficient isolation of the targets and subsequent labelling with SERS nanotags. The method employs Differential Pulse Voltammetry (DPV) for rapidly screening for the presence of the circulating proteins on biosensor surface irrespective of their type. Upon positive DPV detection, SERS is applied for sensitive read-out of individual biomarkers biomarker levels. In a proof-of-concept study, we demonstrate the dual detection biosensor for analysing circulating BRAF, EGFR and PDL-1 proteins and successfully screened both ensemble and individual biomarker expressional levels as low as 10 pg (1 ng/mL). Our findings clearly indicate the potential of the proposed method for cancer biomarker analysis which may drive the translation of this dual sensing concept in clinical settings.

Identification of COPA as a potential prognostic biomarker and pharmacological intervention target of cervical cancer by quantitative proteomics and experimental verification

BACKGROUND

Cervical cancer is the most fatal gynecological carcinoma in the world. It is urgent to explore novel prognostic biomarkers and intervention targets for cervical cancer.

METHODS

Through integrated quantitative proteomic strategy, we investigated the protein expression profiles of cervical cancer; 28 fresh frozen tissue samples (11 adenocarcinoma (AC), 12 squamous cell carcinoma (SCC) and 5 normal cervixes (HC)) were included in discover cohort; 45 fresh frozen tissue samples (19 AC, 18 SCC and 8 HC) were included in verification cohort; 140 paraffin-embedded tissues samples of cervical cancer (85 AC and 55 SCC) were used for immunohistochemical evaluation (IHC) of coatomer protein subunit alpha (COPA) as a prognostic biomarker for cervical cancer; how deficiency of COPA affects cell viability and tumorigenic ability of cervical cancer cells (SiHa cells and HeLa cells) were evaluated by cell counting kit-8 and clone formation in vitro.

RESULTS

We identified COPA is a potential prognostic biomarker for cervical cancer in quantitative proteomics analysis. By retrospective IHC analysis, we additionally verified the proteomics results and demonstrated moderate or strong IHC staining for COPA is an unfavourable independent prognostic factor for cervical cancer. We also identified COPA is a potential pharmacological intervention target of cervical cancer by a series of in vitro experiments.

CONCLUSION

This study is the first to demonstrate that COPA may contribute to progression of cervical cancer. It can serve as a potential prognostic biomarker and promising intervention target for cervical cancer.

BASP1 is up-regulated in tongue squamous cell carcinoma and associated with a poor prognosis

OBJECTIVE

To study the relationship between expression of brain acid soluble protein 1 (BASP1) in tongue squamous cell carcinoma (TSCC) tissue and the clinicopathological characteristics and prognosis of patients with TSCC.

METHODS

Western blotting was performed to detect BASP1 expression in fresh-frozen specimens of tumor tissue and adjacent normal tissue obtained from 6 patients with TSCC. Immunohistochemical methods were used to detect BASP1 expression in 100 paraffin-embedded specimens of TSCC tissue. The chi-square test was used to analyze the association between BASP1 expression and a variety of clinicopathological parameters. A Kaplan-Meier analysis and the Cox proportional hazard model were used to further evaluate the impact of BASP1 on patient survival.

RESULTS

The Oncomine database showed that BASP1 expression was increased in TSCC tissues. The PrognoScan and GEPIA databases suggested that a high level of BASP1 expression is related to a poor prognosis for patients with head and neck cancer. Experimental results showed that when compared to normal tissues adjacent to a cancer, BASP1 was more highly expressed in the TSCC tissues. Univariate and multivariate Cox regression analyses showed that BASP1 expression and the tumor's stage may be independent risk factors that affect the growth and prognosis of TSCC. A survival analysis showed that patients with a low level of BASP1 expression had a higher survival rate.

CONCLUSION

Overexpression of BASP1 was found to be associated with distant node metastasis and a poor prognosis among patents with TSCC. BASP1 could possibly serve as a molecular marker for diagnosing and treating the disease.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

High BASP1 Expression is Associated with Poor Prognosis and Promotes Tumor Progression in Human Lung Adenocarcinoma

BASP1 is involved in signal transduction and cytoskeleton formation and plays a tumor-promoting or tumor-suppressing role in cancers. We found BASP1 was overexpressed in lung adenocarcinoma tissues and promoted the proliferation and migration of lung adenocarcinoma cells. The mechanism may be related to inhibition of cell apoptosis and abnormal activation of the Wnt/β-catenin pathway and epithelial-mesenchymal transformation. BASP1 is associated with poor prognosis in lung adenocarcinoma.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

WT1 activates transcription of the splice factor kinase SRPK1 gene in PC3 and K562 cancer cells in the absence of corepressor BASP1

Dysregulated alternative splicing plays a prominent role in all hallmarks of cancer. The splice factor kinase SRPK1 drives the activity of oncogenic splice factors such as SRSF1. SRSF1 in turn promotes the expression of splice isoforms that favour tumour growth, including proangiogenic VEGF. Knockdown (with siRNA) or chemical inhibition (using SPHINX) of SRPK1 in K562 leukemia and PC3 prostate cancer cell lines reduced cell proliferation, invasion and migration. In glomerular podocytes, the Wilms tumour suppressor zinc-finger transcription factor WT1 represses SRPK1 transcription. Here we show that in cancer cells WT1 activates SRPK1 transcription, unless a canonical WT1 binding site adjacent to the transcription start site is mutated. The ability of WT1 to activate SRPK1 transcription was reversed by the transcriptional corepressor BASP1, and both WT1 and BASP1 co-precipitated with the SRPK1 promoter. BASP1 significantly increased the expression of the antiangiogenic VEGF₁₆₅b splice isoform. We propose that by upregulating SRPK1 transcription WT1 can direct an alternative splicing landscape that facilitates tumour growth.

Molecular characterization of organoids derived from pancreatic intraductal papillary mucinous neoplasms

Intraductal papillary mucinous neoplasms (IPMNs) are commonly identified non-invasive cyst-forming pancreatic neoplasms with the potential to progress into invasive pancreatic adenocarcinoma. There are few in vitro models with which to study the biology of IPMNs and their progression to invasive carcinoma. Therefore, we generated a living biobank of organoids from seven normal pancreatic ducts and ten IPMNs. We characterized eight IPMN organoid samples using whole genome sequencing and characterized five IPMN organoids and seven normal pancreatic duct organoids using transcriptome sequencing. We identified an average of 11,344 somatic mutations in the genomes of organoids derived from IPMNs, with one sample harboring 61,537 somatic mutations enriched for T→C transitions and T→A transversions. Recurrent coding somatic mutations were identified in 15 genes, including KRAS, GNAS, RNF43, PHF3, and RBM10. The most frequently mutated genes were KRAS, GNAS, and RNF43, with somatic mutations identified in six (75%), four (50%), and three (37.5%) IPMN organoid samples, respectively. On average, we identified 36 structural variants in IPMN derived organoids, and none had an unstable phenotype (> 200 structural variants). Transcriptome sequencing identified 28 genes differentially expressed between normal pancreatic duct organoid and IPMN organoid samples. The most significantly upregulated and downregulated genes were CLDN18 and FOXA1. Immunohistochemical analysis of FOXA1 expression in 112 IPMNs, 113 mucinous cystic neoplasms, and 145 pancreatic ductal adenocarcinomas demonstrated statistically significant loss of expression in low-grade IPMNs (p < 0.0016), mucinous cystic neoplasms (p < 0.0001), and pancreatic ductal adenocarcinoma of any histologic grade (p < 0.0001) compared to normal pancreatic ducts. These data indicate that FOXA1 loss of expression occurs early in pancreatic tumorigenesis. Our study highlights the utility of organoid culture to study the genetics and biology of normal pancreatic duct and IPMNs. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Transcriptome Profiling of Acquired Gefitinib Resistant Lung Cancer Cells Reveals Dramatically Changed Transcription Programs and New Treatment Targets

Background: Targeted therapy for lung cancer with epidermal growth factor receptor (EGFR) mutations with tyrosine kinase inhibitors (TKIs) represents one of the major breakthroughs in lung cancer management. However, gradually developed resistance to these drugs prevents sustained clinical benefits and calls for resistant mechanism research and identification of new therapeutic targets. Acquired T790M mutation accounts for the majority of resistance cases, yet transcriptome changes in these cells are less characterized, and it is not known if new treatment targets exist by available drugs.

Methods: Transcriptome profiling was performed for lung cancer cell line PC9 and its resistant line PC9GR after long-term exposure to gefitinib through RNA sequencing. Differentially expressed genes and changed pathways were identified along with existing drugs targeting these upregulated genes. Using 144 lung cancer cell lines with both gene expression and drug response data from the cancer cell line encyclopedia (CCLE) and Cancer Therapeutics Response Portal (CTRP), we screened 549 drugs whose response was correlated with these upregulated genes in PC9GR cells, and top drugs were evaluated for their response in both PC9 and PC9GR cells.

Results: In addition to the acquired T790M mutation, the resistant PC9GR cells had very different transcription programs from the sensitive PC9 cells. Multiple pathways were changed with the top ones including TNFA signaling, androgen/estrogen response, P53 pathway, MTORC1 signaling, hypoxia, and epithelial mesenchymal transition. Thirty-two upregulated genes had available drugs that can potentially be effective in treating the resistant cells. From the response profiles of CCLE, we found 17 drugs whose responses were associated with at least four of these upregulated genes. Among the four drugs evaluated (dasatinib, KPT-185, trametinib, and pluripotin), all except trametinib demonstrated strong inhibitory effects on the resistant PC9GR cells, among which KPT185 was the most potent. KPT-185 suppressed growth, caused apoptosis, and inhibited migration of the PC9GR cells at similar (or better) rates as the sensitive PC9 cells in a dose-dependent manner.

Conclusions: Acquired TKI-resistant lung cancer cells (PC9GR) have dramatically changed transcription and pathway regulation, which expose new treatment targets. Existing drugs may be repurposed to treat those patients with developed resistance to TKIs.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.

PSMD11, PTPRM and PTPRB as novel biomarkers of pancreatic cancer progression

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate of all major cancers. Surgery is the only curative intent therapy, but the majority of patients experience disease relapse. Thus, patients who do not benefit from highly morbid surgical resection needs to be identified and offered palliative chemotherapy instead. In this pilot study, we aimed to identify differentially regulated proteins in plasma and plasma derived microparticles from PDAC patients with poor and good prognosis.

METHODS

Plasma and plasma derived microparticle samples were obtained before surgical resection from PDAC patients. Sequential Windowed Acquisition of all Theoretical fragment ion spectra - Mass Spectrometry (SWATH-MS) proteomic analysis was performed to identify and quantify proteins in these samples. Statistical analysis was performed to identify biomarkers for poor prognosis.

RESULTS

A total of 482 and 1024 proteins were identified from plasma and microparticle samples, respectively, by SWATH-MS analysis. Statistical analysis of the data further identified nine and six differentially (log₂ratio > 1, p < .05) expressed proteins in plasma and microparticles, respectively. Protein tyrosine phosphatases, PTPRM and PTPRB, were decreased in plasma of patients with poor PDAC prognosis, while proteasomal subunit PSMD11 was increased in microparticles of patients with poor prognosis.

CONCLUSION AND GENERAL SIGNIFICANCE

A novel blood-based biomarker signature for PDAC prognosis was identified.

2H-Azirine-Based Reagents for Chemoselective Bioconjugation at Carboxyl Residues Inside Live Cells

Protein modification by chemical reagents has played an essential role in the treatment of human diseases. However, the reagents currently used are limited to the covalent modification of cysteine and lysine residues. It is thus desirable to develop novel methods that can covalently modify other residues. Despite the fact that the carboxyl residues are crucial for maintaining the protein function, few selective labeling reactions are currently available. Here, we describe a novel reactive probe, 3-phenyl-2H-azirine, that enables chemoselective modification of carboxyl groups in proteins under both in vitro and in situ conditions with excellent efficiency. Furthermore, proteome-wide profiling of reactive carboxyl residues was performed with a quantitative chemoproteomic platform.

Label-free detection of biomarker alpha fetoprotein in serum by ssDNA aptamer functionalized magnetic nanoparticles

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the clinic, with the characteristics of occult onset, rapid progression, and high degree of malignancy. Alpha fetoprotein (AFP) is the most important biomarker of HCC, which is widely used in early screening, diagnosis, and prognosis observation. A series of immunoassays have been developed and frequently used in the detection of AFP based on antibodies. Unfortunately, the shortcomings of antibodies, such as thermal unstable and fluctuant activity by batches, lead to the inaccuracy in the detection of AFP. In this study, aptamers instead of antibodies were adopted as the specific recognition element for AFP, aiming to seek an alternative strategy to immunoassays. An AFP-specific ssDNA aptamer was grafted to magnetic nanoparticles (Fe₃O₄@SiO₂) via avidin-biotin interaction, and the resultant aptamer functionalized magnetic nanoparticles (Ap-MNPs) were adequately characterized and tested. The Ap-MNPs in solution exhibited a fast response to the outer magnetic field, and can be completely separated in several minutes. It was found that Ap-MNPs have good specificity to the target AFP, as the recovery of AFP (87.0%) was much higher than the competitive proteins IgG (38.9%), HSA (18.5%), and FIB (11.4%). A convenient and efficient label-free detection method of AFP in serum was developed based on Ap-MNPs in combination with high-performance liquid chromatography. The linearity of this method was over a range of 1-50 μg ml^-1 with a correlation coefficient of 0.9999, and the limit of detection was 0.27 μg ml^-1. This study indicated that aptamers are an ideal tool for the recognition and detection of biomarkers, and thus will find wide applications in clinical practice.

YAP1 is an independent prognostic marker in pancreatic cancer and associated with extracellular matrix remodeling

Background

Pancreatic cancer is a major cause of cancer-related mortality. The identification of effective biomarkers is essential in order to improve management of the disease. Yes-associated protein 1 (YAP1) is a downstream effector of the Hippo pathway, a signal transduction system implicated in tissue repair and regeneration, as well as tumorigenesis. Here we evaluate the biomarker potential of YAP1 in pancreatic cancer tissue.

Methods

YAP1 was selected as a possible biomarker for pancreatic cancer from global protein sequencing of fresh frozen pancreatic cancer tissue samples and normal pancreas controls. The prognostic utility of YAP1 was evaluated using mRNA expression data from 176 pancreatic cancer patients in The Cancer Genome Atlas (TCGA), as well as protein expression data from immunohistochemistry analysis of a local tissue microarray (TMA) cohort comprising 140 pancreatic cancer patients. Ingenuity Pathway Analysis was applied to outline the interaction network for YAP1 in connection to the pancreatic tumor microenvironment. The expression of YAP1 target gene products was evaluated after treatment of the pancreatic cancer cell line Panc-1 with three substances interrupting YAP–TEAD interaction, including Super-TDU, Verteporfin and CA3.

Results

Mass spectrometry based proteomics showed that YAP1 is the top upregulated protein in pancreatic cancer tissue when compared to normal controls (log2 fold change 6.4; p = 5E−06). Prognostic analysis of YAP1 demonstrated a significant correlation between mRNA expression level data and reduced overall survival (p = 0.001). In addition, TMA and immunohistochemistry analysis suggested that YAP1 protein expression is an independent predictor of poor overall survival [hazard ratio (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, p = 0.004], as well as reduced disease-free survival (HR 1.950, 95% CI 1.299–2.927, p = 0.001). Bioinformatic analyses coupled with in vitro assays indicated that YAP1 is involved in the transcriptional control of target genes, associated with extracellular matrix remodeling, which could be modified by selected substances disrupting the YAP1-TEAD interaction.

Conclusions

Our findings indicate that YAP1 is an important prognostic biomarker for pancreatic cancer and may play a regulatory role in the remodeling of the extracellular matrix.

The brain acid-soluble protein 1 (BASP1) interferes with the oncogenic capacity of MYC and its binding to calmodulin

The MYC protein is a transcription factor with oncogenic potential controlling fundamental cellular processes such as cell proliferation, metabolism, differentiation, and apoptosis. The MYC gene is a major cancer driver, and elevated MYC protein levels are a hallmark of most human cancers. We have previously shown that the brain acid-soluble protein 1 gene (BASP1) is specifically downregulated by the v-myc oncogene and that ectopic BASP1 expression inhibits v-myc-induced cell transformation. The 11-amino acid effector domain of the BASP1 protein interacts with the calcium sensor calmodulin (CaM) and is mainly responsible for this inhibitory function. We also reported recently that CaM interacts with all MYC variant proteins and that ectopic CaM increases the transactivation and transformation potential of the v-Myc protein. Here, we show that the presence of excess BASP1 or of a synthetic BASP1 effector domain peptide leads to displacement of v-Myc from CaM. The protein stability of v-Myc is decreased in cells co-expressing v-Myc and BASP1, which may account for the inhibition of v-Myc. Furthermore, suppression of v-Myc-triggered transcriptional activation and cell transformation is compensated by ectopic CaM, suggesting that BASP1-mediated withdrawal of CaM from v-Myc is a crucial event in the inhibition. In view of the tumor-suppressive role of BASP1 which was recently also reported for human cancer, small compounds or peptides based on the BASP1 effector domain could be used in drug development strategies aimed at tumors with high MYC expression.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Alpha-1-acid glycoprotein 1 is upregulated in pancreatic ductal adenocarcinoma and confers a poor prognosis

Pancreatic cancer is an aggressive malignancy that carries a high mortality rate. A major contributor to the poor outcome is the lack of effective molecular markers. The purpose of this study was to develop protein markers for improved prognostication and noninvasive diagnosis. A mass spectrometry (MS)-based discovery approach was applied to pancreatic cancer tissues and healthy pancreas. In the verification phase, extracellular proteins with differential expression were further quantified in targeted mode using parallel reaction monitoring (PRM). Next, a tissue microarray (TMA) cohort including 140 pancreatic cancer resection specimens was constructed, in order to validate protein expression status and investigate potential prognostic implications. The levels of protein candidates were finally assessed in a prospective series of 110 serum samples in an accredited clinical laboratory using the automated Cobas system. Protein sequencing with nanoliquid chromatography tandem MS (nano-LC-MS/MS) and targeted PRM identified alpha-1-acid glycoprotein 1 (AGP1) as an upregulated protein in pancreatic cancer tissue. Using TMA and immunohistochemistry, AGP1 expression was significantly associated with shorter overall survival (HR = 2.22; 95% CI 1.30-3.79, P =  0.004). Multivariable analysis confirmed the results (HR = 1.87; 95% CI 1.08-3.24, P  =  0.026). Circulating levels of AGP1 yielded an area under the curve (AUC) of 0.837 for the discrimination of resectable pancreatic cancer from healthy controls. Combining AGP1 with CA 19-9 enhanced the diagnostic performance, with an AUC of 0.963. This study suggests that AGP1 is a novel prognostic biomarker in pancreatic cancer tissue. Serum AGP1 levels may be useful as part of a biomarker panel for early detection of pancreatic cancer but further studies are needed.

What is Normalization? The Strategies Employed in Top-Down and Bottom-Up Proteome Analysis Workflows

The accurate quantification of changes in the abundance of proteins is one of the main applications of proteomics. The maintenance of accuracy can be affected by bias and error that can occur at many points in the experimental process, and normalization strategies are crucial to attempt to overcome this bias and return the sample to its regular biological condition, or normal state. Much work has been published on performing normalization on data post-acquisition with many algorithms and statistical processes available. However, there are many other sources of bias that can occur during experimental design and sample handling that are currently unaddressed. This article aims to cast light on the potential sources of bias and where normalization could be applied to return the sample to its normal state. Throughout we suggest solutions where possible but, in some cases, solutions are not available. Thus, we see this article as a starting point for discussion of the definition of and the issues surrounding the concept of normalization as it applies to the proteomic analysis of biological samples. Specifically, we discuss a wide range of different normalization techniques that can occur at each stage of the sample preparation and analysis process.

Mining cancer biology through bioinformatic analysis of proteomic data

Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research. Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes. Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

Using the tools of proteomics to understand the pathogenesis of idiopathic inflammatory myopathies

PURPOSE OF REVIEW

One of the most important advances in medical research over the past 20 years has been the emergence of technologies to assess complex biological processes on a global scale. Although a great deal of attention has been given to genome-scale genetics and genomics technologies, the utility of studying the proteome in a comprehensive way is sometimes under-appreciated. In this review, we discuss recent advances in proteomics as applied to dermatomyositis/polymyositis as well as findings from other inflammatory diseases that may enlighten our understanding of dermatomyositis/polymyositis.

RECENT FINDINGS

Proteomic approaches have been used to investigate basic mechanisms contributing to lung and skin disease in dermatomyositis/polymyositis as well as to the muscle disease itself. In addition, proteomic approaches have been used to identify autoantibodies targeting the endothelium in juvenile dermatomyositis. Studies from other inflammatory diseases have shown the promise of using proteomics to characterize the composition of immune complexes and the protein cargoes of exosomes.

SUMMARY

There are many relevant scientific and clinical questions in dermatomyositis/polymyositis that can be addressed using proteomics approaches. Careful attention to both methodology and analytic approaches are required to obtain useful and reproducible data.