Humoral immunoprofiling identifies novel biomarkers and an immune suppressive autoantibody phenotype at the site of disease in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous cancer, with minimal response to therapeutic intervention and with 85% of cases diagnosed at an advanced stage due to lack of early symptoms, highlighting the importance of understanding PDAC immunology in greater detail. Here, we applied an immunoproteomic approach to investigate autoantibody responses against cancer-testis and tumor-associated antigens in PDAC using a high-throughput multiplexed protein microarray platform, comparing humoral immune responses in serum and at the site of disease in order to shed new light on immune responses in the tumor microenvironment. We simultaneously quantified serum or tissue IgG and IgA antibody isotypes and subclasses in a cohort of PDAC, disease control and healthy patients, observing inter alia that subclass utilization in tumor tissue samples was predominantly immune suppressive IgG4 and inflammatory IgA2, contrasting with predominant IgG3 and IgA1 subclass utilization in matched sera and implying local autoantibody production at the site of disease in an immune-tolerant environment. By comparison, serum autoantibody subclass profiling for the disease controls identified IgG4, IgG1, and IgA1 as the abundant subclasses. Combinatorial analysis of serum autoantibody responses identified panels of candidate biomarkers. The top IgG panel included ACVR2B, GAGE1, LEMD1, MAGEB1 and PAGE1 (sensitivity, specificity and AUC values of 0.933, 0.767 and 0.906). Conversely, the top IgA panel included AURKA, GAGE1, MAGEA10, PLEKHA5 and XAGE3aV1 (sensitivity, specificity, and AUC values of 1.000, 0.800, and 0.954). Assessment of antigen-specific serum autoantibody glycoforms revealed abundant sialylation on IgA in PDAC, consistent with an immune suppressive IgA response to disease.

MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets.

BACKGROUND: Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. RESULTS: We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. CONCLUSIONS: By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.

A mass spectrometry-based approach for the identification of Kpnß1 binding partners in cancer cells.

Karyopherin beta 1 (Kpnß1) is the principal nuclear importer of cargo proteins and plays a role in many cellular processes. Its expression is upregulated in cancer and essential for cancer cell viability, thus the identification of its binding partners might help in the discovery of anti-cancer therapeutic targets and cancer biomarkers. Herein, we applied immunoprecipitation coupled to mass spectrometry (IP-MS) to identify Kpnß1 binding partners in normal and cancer cells. IP-MS identified 100 potential Kpnß1 binding partners in non-cancer hTERT-RPE1, 179 in HeLa cervical cancer, 147 in WHCO5 oesophageal cancer and 176 in KYSE30 oesophageal cancer cells, including expected and novel interaction partners. 38 binding proteins were identified in all cell lines, with the majority involved in RNA metabolism. 18 binding proteins were unique to the cancer cells, with many involved in protein translation. Western blot analysis validated the interaction of known and novel binding partners with Kpnß1 and revealed enriched interactions between Kpnß1 and select proteins in cancer cells, including proteins involved in cancer development, such as Kpnα2, Ran, CRM1, CCAR1 and FUBP1. Together, this study shows that Kpnß1 interacts with numerous proteins, and its enhanced interaction with certain proteins in cancer cells likely contributes to the cancer state.

Mechanistic implications of altered protein expression in rheumatic heart disease.

Rheumatic heart disease (RHD) is a major cause of cardiovascular morbidity and mortality in low- and middle-income countries, where living conditions promote spread of group A ß-haemolytic streptococcus. Autoimmune reactions due to molecular mimicry of bacterial epitopes by host proteins cause acute rheumatic fever (ARF) and subsequent disease progression to RHD. Despite knowledge of the factors that predispose to ARF and RHD, determinants of the progression to valvular damage and the molecular events involved remain incompletely characterised. This review focuses on altered protein expression in heart valves, myocardial tissue and plasma of patients with RHD and pathogenic consequences on RHD. Proteins mainly involved in structural organization of the valve matrix, blood homeostasis and immune response were altered due to RHD pathogenesis. Study of secreted forms of these proteins may aid the development of non-invasive biomarkers for early diagnosis and monitoring outcomes in RHD. Valve replacement surgery, the single evidence-based strategy to improve outcomes in severe RHD, is costly, largely unavailable in low- and middle-income countries (LMIC) and requires specialised facilities. When diagnosed early, penicillin prophylaxis may be used to delay progression to severe valvular damage. Echocardiography and cardiovascular magnetic resonance and the standard imaging tools recommended to confirm early diagnosis remain largely unavailable and inaccessible in most LMIC and both require expensive equipment and highly skilled persons for manipulation as well as interpretation of results. Changes in protein expression in heart valves and myocardium are associated with progressive valvular deformation in RHD. Understanding these protein changes should shed more light on the mechanisms of pathogenicity, while secreted forms of these proteins may provide leads towards a biomarker for non-invasive early detection of RHD.

A highly predictive autoantibody-based biomarker panel for prognosis in early-stage NSCLC with potential therapeutic implications.

BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide. Surgical resection remains the definitive curative treatment for early-stage disease offering an overall 5-year survival rate of 62%. Despite careful case selection, a significant proportion of early-stage cancers relapse aggressively within the first year post-operatively. Identification of these patients is key to accurate prognostication and understanding the biology that drives early relapse might open up potential novel adjuvant therapies. METHODS: We performed an unsupervised interrogation of >1600 serum-based autoantibody biomarkers using an iterative machine-learning algorithm. RESULTS: We identified a 13 biomarker signature that was highly predictive for survivorship in post-operative early-stage lung cancer; this outperforms currently used autoantibody biomarkers in solid cancers. Our results demonstrate significantly poor survivorship in high expressers of this biomarker signature with an overall 5-year survival rate of 7.6%. CONCLUSIONS: We anticipate that the data will lead to the development of an off-the-shelf prognostic panel and further that the oncogenic relevance of the proteins recognised in the panel may be a starting point for a new adjuvant therapy.

Immunogenicity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection and Ad26.CoV2.S Vaccination in People Living With Human Immunodeficiency Virus (HIV).

BACKGROUND: People living with HIV (PLWH) have been reported to have a higher risk of more severe COVID-19 disease and death. We assessed the ability of the Ad26.CoV2.S vaccine to elicit neutralizing activity against the Delta variant in PLWH relative to HIV-negative individuals. We also examined effects of HIV status and suppression on Delta neutralization response in SARS-CoV-2-infected unvaccinated participants. METHODS: We enrolled participants who were vaccinated through the SISONKE South African clinical trial of the Ad26.CoV2.S vaccine in healthcare workers (HCWs). PLWH in this group had well-controlled HIV infection. We also enrolled unvaccinated participants previously infected with SARS-CoV-2. Neutralization capacity was assessed by a live virus neutralization assay of the Delta variant. RESULTS: Most Ad26.CoV2.S vaccinated HCWs were previously infected with SARS-CoV-2. In this group, Delta variant neutralization was 9-fold higher compared with the infected-only group and 26-fold higher relative to the vaccinated-only group. No decrease in Delta variant neutralization was observed in PLWH relative to HIV-negative participants. In contrast, SARS-CoV-2-infected, unvaccinated PLWH showed 7-fold lower neutralization and a higher frequency of nonresponders, with the highest frequency of nonresponders in people with HIV viremia. Vaccinated-only participants showed low neutralization capacity. CONCLUSIONS: The neutralization response of the Delta variant following Ad26.CoV2.S vaccination in PLWH with well-controlled HIV was not inferior to HIV-negative participants, irrespective of past SARS-CoV-2 infection. In SARS-CoV-2-infected and nonvaccinated participants, HIV infection reduced the neutralization response to SARS-CoV-2, with the strongest reduction in HIV viremic individuals.

Nuclear transport proteins are secreted by cancer cells and identified as potential novel cancer biomarkers.

Previous studies have identified increased expression of members of the nuclear transport protein family in cancer cells. Recently, certain nuclear transport proteins have been reported to be secreted by cells and found in the serum. The aims of our study were to investigate the levels of multiple nuclear transport proteins secreted from cancer cells, and to determine their potential as diagnostic markers for cervical and oesophageal cancer. Mass spectrometry identified 10 nuclear transport proteins in the secretome and exosomes of cultured cancer cells, and Western blot analysis confirmed increased secreted levels in cancer cells compared to normal. To investigate their presence in patient serum, enzyme-linked immunosorbent assays were performed and revealed significantly increased levels of KPNß1, CRM1, CAS, IPO5 and TNPO1 in cervical and oesophageal cancer patient serum compared to non-cancer controls. Significantly elevated KPNα2 and RAN levels were also identified in oesophageal cancer serum samples. Logistics regression analyses revealed IPO5 and TNPO1 to be the best performing individual candidate biomarkers in discriminating between cancer cases and controls. The combination of KPNß1, CRM1, KPNα2, CAS, RAN, IPO5 and TNPO1 as a panel of biomarkers had the highest diagnostic capacity with an area under the curve of 0.944 and 0.963, for cervical cancer and oesophageal cancer, and sensitivity of 92.5% at 86.8% specificity and 95.3% sensitivity at 87.5% specificity, respectively. These results suggest that nuclear transport proteins have potential as diagnostic biomarkers for cervical and oesophageal cancers, with a combination of protein family members being the best predictor.

Targeting the oncogenic TBX3:nucleolin complex to treat multiple sarcoma subtypes.

Sarcomas are diverse cancers of mesenchymal origin, with compromised clinical management caused by insufficient diagnostic biomarkers and limited treatment options. The transcription factor TBX3 is upregulated in a diverse range of sarcoma subtypes, where it plays a direct oncogenic role, and it may thus represent a novel therapeutic target. To identify versatile ways to target TBX3, we performed affinity purification coupled by mass spectrometry to identify putative TBX3 protein cofactors that regulate its oncogenic activity in sarcomas. Here we identify and validate the multifunctional phosphoprotein nucleolin as a TBX3 cofactor. We show that nucleolin is co-expressed with TBX3 in several sarcoma subtypes and their expression levels positively correlate in sarcoma patients which are associated with poor prognosis. Furthermore, we demonstrate that nucleolin and TBX3 interact in chondrosarcoma, liposarcoma and rhabdomyosarcoma cells where they act together to enhance proliferation and migration and regulate a common set of tumor suppressor genes. Importantly, the nucleolin targeting aptamer, AS1411, exhibits selective anti-cancer activity in these cells and mislocalizes TBX3 and nucleolin to the cytoplasm which correlates with the re-expression of the TBX3/nucleolin target tumor suppressors CDKN1A (p21CIP1) and CDKN2A (p14ARF). Our findings provide the first evidence that TBX3 requires nucleolin to promote features of sarcomagenesis and that disruption of the oncogenic TBX3-nucleolin interaction by AS1411 may be a novel approach for treating sarcomas.

Ropporin-1 and 1B Are Widely Expressed in Human Melanoma and Evoke Strong Humoral Immune Responses.

Antibodies that block immune regulatory checkpoints (programmed cell death 1, PD-1 and cytotoxic T-lymphocyte-associated antigen 4, CTLA-4) to mobilise immunity have shown unprecedented clinical efficacy against cancer, demonstrating the importance of antigen-specific tumour recognition. Despite this, many patients still fail to benefit from these treatments and additional approaches are being sought. These include mechanisms that boost antigen-specific immunity either by vaccination or adoptive transfer of effector cells. Other than neoantigens, epigenetically regulated and shared antigens such as NY-ESO-1 are attractive targets; however, tissue expression is often heterogeneous and weak. Therefore, peptide-specific therapies combining multiple antigens rationally selected to give additive anti-cancer benefits are necessary to achieve optimal outcomes. Here, we show that Ropporin-1 (ROPN1) and 1B (ROPN1B), cancer restricted antigens, are highly expressed and immunogenic, inducing humoral immunity in patients with advanced metastatic melanoma. By multispectral immunohistochemistry, 88.5% of melanoma patients tested (n = 54/61) showed ROPN1B expression in at least 1 of 2/3 tumour cores in tissue microarrays. Antibody responses against ROPN1A and ROPN1B were detected in 71.2% of melanoma patients tested (n = 74/104), with increased reactivity seen with more advanced disease stages. Thus, ROPN1A and ROPN1B may indeed be viable targets for cancer immunotherapy, alone or in combination with other cancer antigens, and could be combined with additional therapies such as immune checkpoint blockade.

Protocols for Preparation and Mass Spectrometry Analysis of Clinical Urine Samples to Identify Candidate Biomarkers of Schistosoma-Associated Bladder Cancer.

Advances in mass spectrometry instrumentation have revolutionized analytical capability in clinical proteomics. In parallel, various sample preparation methods have been developed to try to address the inherent complexity and dynamic range of clinical samples, typically involving a combination of depletion of abundant proteins followed by extensive prefractionation. However, the depth of coverage routinely achieved in discovery proteomics experiments on peripheral fluids such as serum, still leaves something to be desired, especially if no depletion or prefractionation is done in order to increase the throughput of clinical samples. Remarkably, despite being an easily accessible, typically sterile and diagnostically rich clinical sample, urine is often overlooked and as such has received less development effort. As an ultrafiltrate of blood, urine contains proteins and protein fragments originating from all parts of the body which may have diagnostic or prognostic potential if accurately and reproducibly quantified. Here, we describe an efficient and simple method for the concentration of urine samples by methanol-chloroform precipitation and subsequent in-solution tryptic digestion prior to discovery or targeted mass spectrometry analysis. We exemplify this method by reference to the discovery of novel candidate urinary biomarkers of schistosomiasis. Importantly, the methods described here have been used to identify >1900 protein groups in human urine by label-free discovery proteomics, without requiring any prior depletion or prefractionation, making this approach amenable to high throughput clinical biomarker studies in many diseases.

Protein array-based companion diagnostics in precision medicine.

INTRODUCTION: The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities. AREA COVERED: This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests. EXPERT OPINION: Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Associating H2O2-and NO-related changes in the proteome of Mycobacterium smegmatis with enhanced survival in macrophage.

Mycobacterium manages to evade the host cell immune system, partially owing to its ability to survive redox stress after macrophage engulfment. Exposure to redox stress has been linked to later replication, persistence, and latent infection. In this work, mass spectrometry was used to elucidate the cell-wide changes that occur in response to sublethal doses of hydrogen peroxide and nitric oxide over time, with Mycobacterium smegmatis being used as a model organism. A total of 3135 proteins were confidently assigned, of which 1713, 1674, and 1713 were identified under NO, H2O2, and control conditions, respectively. Both treatment conditions resulted in changes of protein expression from the DosR regulon as well as those related to lipid metabolism. Complementary to the changes in the proteome, sublethal exposure to NO and H2O2 improved the survival of the bacteria after macrophage infection. Our data indicate that pre-exposure to sublethal doses of these redox stressors causes an alteration in the expression of proteins related to lipid metabolism, suggesting a link between altered lipid metabolism and enhanced survival in macrophages.

The Role of Tumor Microenvironment in Chemoresistance: 3D Extracellular Matrices as Accomplices.

BACKGROUND: The functional interplay between tumor cells and their adjacent stroma has been suggested to play crucial roles in the initiation and progression of tumors and the effectiveness of chemotherapy. The extracellular matrix (ECM), a complex network of extracellular proteins, provides both physical and chemicals cues necessary for cell proliferation, survival, and migration. Understanding how ECM composition and biomechanical properties affect cancer progression and response to chemotherapeutic drugs is vital to the development of targeted treatments. METHODS: 3D cell-derived-ECMs and esophageal cancer cell lines were used as a model to investigate the effect of ECM proteins on esophageal cancer cell lines response to chemotherapeutics. Immunohistochemical and qRT-PCR evaluation of ECM proteins and integrin gene expression was done on clinical esophageal squamous cell carcinoma biopsies. Esophageal cancer cell lines (WHCO1, WHCO5, WHCO6, KYSE180, KYSE 450 and KYSE 520) were cultured on decellularised ECMs (fibroblasts-derived ECM; cancer cell-derived ECM; combinatorial-ECM) and treated with 0.1% Dimethyl sulfoxide (DMSO), 4.2 µM cisplatin, 3.5 µM 5-fluorouracil and 2.5 µM epirubicin for 24 h. Cell proliferation, cell cycle progression, colony formation, apoptosis, migration and activation of signaling pathways were used as our study endpoints. RESULTS: The expression of collagens, fibronectin and laminins was significantly increased in esophageal squamous cell carcinomas (ESCC) tumor samples compared to the corresponding normal tissue. Decellularised ECMs abrogated the effect of drugs on cancer cell cycling, proliferation and reduced drug induced apoptosis by 20⁻60% that of those plated on plastic. The mitogen-activated protein kinase-extracellular signal-regulated kinase (MEK-ERK) and phosphoinositide 3-kinase-protein kinase B (PI3K/Akt) signaling pathways were upregulated in the presence of the ECMs. Furthermore, our data show that concomitant addition of chemotherapeutic drugs and the use of collagen- and fibronectin-deficient ECMs through siRNA inhibition synergistically increased cancer cell sensitivity to drugs by 30⁻50%, and reduced colony formation and cancer cell migration. CONCLUSION: Our study shows that ECM proteins play a key role in the response of cancer cells to chemotherapy and suggest that targeting ECM proteins can be an effective therapeutic strategy against chemoresistant tumors.

B cells and antibody production in melanoma.

Recent developments in the immuno-oncology field strongly support a role for the immune system in both the prevention and progression of melanoma. Melanoma is a highly immunogenic cancer, including its ability to induce tumour antigen-specific B cell and antibody responses through largely unknown mechanisms. This review considers likely hypothetical mechanisms by which anti-tumour surveillance detects pre-cancerous cells and by which immune (including B cell and antibody) responses may be elicited during malignancy. The review further considers potential pro- and anti-tumour functions of B cells and antibodies (including tertiary lymphoid structures) in both the tumour microenvironment and in circulation. Although the vast majority of studies have focused on T cells, recent evidence highlights the important roles of B cells in response to malignancy. B cells and antibodies are also discussed in the context of their potential utility as clinical biomarkers for various applications (as diagnostic, prognostic, therapeutic efficacy, and toxicity proxies), with a particular focus on protein microarray-based antibody detection and quantitation. Although the role of B cells in melanoma is incompletely understood, the measurement of circulating tumour-specific antibodies represents a promising avenue in the search for melanoma-relevant biomarkers.

Autoantibodies May Predict Immune-Related Toxicity: Results from a Phase I Study of Intralesional Bacillus Calmette-Guérin followed by Ipilimumab in Patients with Advanced Metastatic Melanoma.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of advanced melanoma. The first ICI to demonstrate clinical benefit, ipilimumab, targets cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4); however, the long-term overall survival is just 22%. More than 40 years ago intralesional (IL) bacillus Calmette-Guérin (BCG), a living attenuated strain of Mycobacterium bovis, was found to induce tumor regression by stimulating cell-mediated immunity following a localized and self-limiting infection. We evaluated these two immune stimulants in combination with melanoma with the aim of developing a more effective immunotherapy and to assess toxicity. In this phase I study, patients with histologically confirmed stage III/IV metastatic melanoma received IL BCG injection followed by up to four cycles of intravenous ipilimumab (anti-CTLA-4) (ClinicalTrials.gov number NCT01838200). The trial was discontinued following treatment of the first five patients as the two patients receiving the escalation dose of BCG developed high-grade immune-related adverse events (irAEs) typical of ipilimumab monotherapy. These irAEs were characterized in both patients by profound increases in the repertoire of autoantibodies directed against both self- and cancer antigens. Interestingly, the induced autoantibodies were detected at time points that preceded the development of symptomatic toxicity. There was no overlap in the antigen specificity between patients and no evidence of clinical responses. Efforts to increase response rates through the use of novel immunotherapeutic combinations may be associated with higher rates of irAEs, thus the imperative to identify biomarkers of toxicity remains strong. While the small patient numbers in this trial do not allow for any conclusive evidence of predictive biomarkers, the observed changes warrant further examination of autoantibody repertoires in larger patient cohorts at risk of developing irAEs during their course of treatment. In summary, dose escalation of IL BCG followed by ipilimumab therapy was not well tolerated in advanced melanoma patients and showed no evidence of clinical benefit. Measuring autoantibody responses may provide early means for identifying patients at risk from developing severe irAEs during cancer immunotherapy.

PMA: Protein Microarray Analyser, a user-friendly tool for data processing and normalization.

OBJECTIVE: Protein microarrays provide a high-throughput platform to measure protein interactions and associated functions, and can aid in the discovery of cancer biomarkers. The resulting protein microarray data can however be subject to systematic bias and noise, thus requiring a robust data processing, normalization and analysis pipeline to ensure high quality and robust results. To date, a comprehensive data processing pipeline is yet to be developed. Furthermore, a lack of analysis consistency is evident amongst different research groups, thereby impeding collaborative data consolidation and comparison. Thus, we sought to develop an accessible data processing tool using methods that are generalizable to the protein microarray field and which can be adapted to individual array layouts with minimal software engineering expertise. RESULTS: We developed an improved version of a previously developed pipeline of protein microarray data processing and implemented it as an open source software tool, with particular focus on widening its use and applicability. The Protein Microarray Analyser software presented here includes the following tools: (1) neighbourhood background correction, (2) net intensity correction, (3) user-defined noise threshold, (4) user-defined CV threshold amongst replicates and (5) assay controls, (6) composite 'pin-to-pin' normalization amongst sub-arrays, and (7) 'array-to-array' normalization amongst whole arrays.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

BACKGROUND: Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. METHODOLOGY: A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. RESULTS: A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). CONCLUSION: These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Emerging proteomics biomarkers and prostate cancer burden in Africa.

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

A temporal proteome dynamics study reveals the molecular basis of induced phenotypic resistance in Mycobacterium smegmatis at sub-lethal rifampicin concentrations.

In the last 40 years only one new antitubercular drug has been approved, whilst resistance to current drugs, including rifampicin, is spreading. Here, we used the model organism Mycobacterium smegmatis to study mechanisms of phenotypic mycobacterial resistance, employing quantitative mass spectrometry-based proteomics to investigate the temporal effects of sub-lethal concentrations of rifampicin on the mycobacterial proteome at time-points corresponding to early response, onset of bacteriostasis and early recovery. Across 18 samples, a total of 3,218 proteins were identified from 31,846 distinct peptides averaging 16,250 identified peptides per sample. We found evidence that two component signal transduction systems (e.g. MprA/MprB) play a major role during initial mycobacterial adaptive responses to sub-lethal rifampicin and that, after dampening an initial SOS response, the bacteria supress the DevR (DosR) regulon and also upregulate their transcriptional and translational machineries. Furthermore, we found a co-ordinated dysregulation in haeme and mycobactin synthesis. Finally, gradual upregulation of the M. smegmatis-specific rifampin ADP-ribosyl transferase was observed which, together with upregulation of transcriptional and translational machinery, likely explains recovery of normal growth. Overall, our data indicates that in mycobacteria, sub-lethal rifampicin triggers a concerted phenotypic response that contrasts significantly with that observed at higher antimicrobial doses.

Quantitative proteomic analysis of HIV-1 Tat-induced dysregulation in SH-SY5Y neuroblastoma cells.

Despite affecting up to 70% of HIV-positive patients and being the leading cause of dementia in patients under 40 years, the molecular mechanisms involved in the onset of HIV-associated neurocognitive disorders (HAND) are not well understood. To address this, we performed SILAC-based quantitative proteomic analysis on HIV-Tat treated SH-SY5Y neuroblastoma cells. Isolated protein was fractionated by SDS-PAGE and analyzed by nLC-MS/MS on an Orbitrap Velos. Using MaxQuant, we identified and quantified 3077 unique protein groups, of which 407 were differentially regulated. After applying an additional standard deviation-based cutoff, 29 of these were identified as highly significantly and stably dysregulated. GO term analysis shows dysregulation in both protein translation machinery as well as cytoskeletal regulation that have both been implicated in other dementias. In addition, several key cytoskeletal regulatory proteins such as ARHGEF17, the Rho GTPase, SHROOM3, and CMRP1 are downregulated. Together, these data demonstrate that HIV-Tat can dysregulate neuronal cytoskeletal regulatory proteins that could lead to the major HAND clinical manifestation-synapse loss.