Proteomic Characterisation of Patient Samples Diagnosed with Haematological Malignancies

Multiple myeloma (MM) is the second most commonly diagnosed lymphoid cancer worldwide, after non-Hodgkin’s lymphoma, and is characterised by the uninhibited proliferation of terminally differentiated B-lymphocytes. The proliferation of these mutated plasma cells leads to the secretion of monoclonal proteins, resulting in mutated heavy/light chain immunoglobulin formation. Characterised by serum albumin levels, serum beta-2-microglobulin levels and hypercalcemia, renal impairment, anaemia, bone lesions (CRAB criteria), MM is diagnosed as stage Ⅰ, Ⅱ or Ⅲ. Even with a multitude of new, novel treatments developed for MM, although OS has increased significantly, MM is considered an incurable disease as the vast majority of patients go into relapse. With the use of label-free liquid chromatography mass spectrometry, proteomic analysis was carried out on MM patient samples with varying drug resistance. Vinculin, talin-1, filamin A and integrin β3 were identified as having an increased abundance in drug resistance in 4 of the 6 drugs tested. Activated RNA polymerase II transcriptional coactivator p15 118 phosphoserine and heat shock protein 27 phosphoserine 78 were identified as having a changed abundance between sensitive and resistant patients. Fatty acid binding protein 5 was detected in saliva as having a significant increase in abundance throughout disease progression of MM. Macrophage inflammatory protein 1α is predicted to play a significant role in the development of adverse side effects, after Rsq-VD treatment, with an observed increased abundance in all patients who developed toxicity throughout the clinical trial. CD44 is also predicted to have potential as a biomarker for poor outcome after Rsq-VD treatment. Multiple proteins were identified as differentially abundant in Group 1 (favourable) to Group 3 (Adverse) in acute myeloid leukaemia (AML), stromal derived growth factor 1 being of particular interest in this study. Overall this work shows proteomic techniques can be used to identify potential biomarkers for haematological malignancies

Identification of Protein Biomarker Signatures for Acute Myeloid Leukemia (AML) Using Both Nontargeted and Targeted Approaches

Acute myeloid leukemia (AML) is characterized by an increasing number of clonal myeloid blast cells which are incapable of differentiating into mature leukocytes. AML risk stratification is based on genetic background, which also serves as a means to identify the optimal treatment of individual patients. However, constant refinements are needed, and the inclusion of significant measurements, based on the various omics approaches that are currently available to researchers/clinicians, have the potential to increase overall accuracy with respect to patient management. Using both nontargeted (label-free mass spectrometry) and targeted (multiplex immunoassays) proteomics, a range of proteins were found to be significantly changed in AML patients with different genetic backgrounds. The inclusion of validated proteomic biomarker panels could be an important factor in the prognostic classification of AML patients. The ability to measure both cellular and secreted analytes, at diagnosis and during the course of treatment, has advantages in identifying transforming biological mechanisms in patients, assisting important clinical management decisions.Peer reviewe

S100 Calcium Binding Protein Family Members Associate With Poor Patient Outcome and Response to Proteasome Inhibition in Multiple Myeloma

Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients’ survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.Peer reviewe

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.Peer reviewe

Proteomic Characterisation of Patient Samples Diagnosed with Haematological Malignancies

Multiple myeloma (MM) is the second most commonly diagnosed lymphoid cancer worldwide, after non-Hodgkin’s lymphoma, and is characterised by the uninhibited proliferation of terminally differentiated B-lymphocytes. The proliferation of these mutated plasma cells leads to the secretion of monoclonal proteins, resulting in mutated heavy/light chain immunoglobulin formation. Characterised by serum albumin levels, serum beta-2-microglobulin levels and hypercalcemia, renal impairment, anaemia, bone lesions (CRAB criteria), MM is diagnosed as stage Ⅰ, Ⅱ or Ⅲ. Even with a multitude of new, novel treatments developed for MM, although OS has increased significantly, MM is considered an incurable disease as the vast majority of patients go into relapse. With the use of label-free liquid chromatography mass spectrometry, proteomic analysis was carried out on MM patient samples with varying drug resistance. Vinculin, talin-1, filamin A and integrin β3 were identified as having an increased abundance in drug resistance in 4 of the 6 drugs tested. Activated RNA polymerase II transcriptional coactivator p15 118 phosphoserine and heat shock protein 27 phosphoserine 78 were identified as having a changed abundance between sensitive and resistant patients. Fatty acid binding protein 5 was detected in saliva as having a significant increase in abundance throughout disease progression of MM. Macrophage inflammatory protein 1α is predicted to play a significant role in the development of adverse side effects, after Rsq-VD treatment, with an observed increased abundance in all patients who developed toxicity throughout the clinical trial. CD44 is also predicted to have potential as a biomarker for poor outcome after Rsq-VD treatment. Multiple proteins were identified as differentially abundant in Group 1 (favourable) to Group 3 (Adverse) in acute myeloid leukaemia (AML), stromal derived growth factor 1 being of particular interest in this study. Overall this work shows proteomic techniques can be used to identify potential biomarkers for haematological malignancies

Proteomic Characterisation of Patient Samples Diagnosed with Haematological Malignancies

Multiple myeloma (MM) is the second most commonly diagnosed lymphoid cancer worldwide, after non-Hodgkin’s lymphoma, and is characterised by the uninhibited proliferation of terminally differentiated B-lymphocytes. The proliferation of these mutated plasma cells leads to the secretion of monoclonal proteins, resulting in mutated heavy/light chain immunoglobulin formation. Characterised by serum albumin levels, serum beta-2-microglobulin levels and hypercalcemia, renal impairment, anaemia, bone lesions (CRAB criteria), MM is diagnosed as stage Ⅰ, Ⅱ or Ⅲ. Even with a multitude of new, novel treatments developed for MM, although OS has increased significantly, MM is considered an incurable disease as the vast majority of patients go into relapse. With the use of label-free liquid chromatography mass spectrometry, proteomic analysis was carried out on MM patient samples with varying drug resistance. Vinculin, talin-1, filamin A and integrin β3 were identified as having an increased abundance in drug resistance in 4 of the 6 drugs tested. Activated RNA polymerase II transcriptional coactivator p15 118 phosphoserine and heat shock protein 27 phosphoserine 78 were identified as having a changed abundance between sensitive and resistant patients. Fatty acid binding protein 5 was detected in saliva as having a significant increase in abundance throughout disease progression of MM. Macrophage inflammatory protein 1α is predicted to play a significant role in the development of adverse side effects, after Rsq-VD treatment, with an observed increased abundance in all patients who developed toxicity throughout the clinical trial. CD44 is also predicted to have potential as a biomarker for poor outcome after Rsq-VD treatment. Multiple proteins were identified as differentially abundant in Group 1 (favourable) to Group 3 (Adverse) in acute myeloid leukaemia (AML), stromal derived growth factor 1 being of particular interest in this study. Overall this work shows proteomic techniques can be used to identify potential biomarkers for haematological malignancies

Saliva-omics in plasma cell disorders- Proof of concept and potential as a non-invasive tool for monitoring disease burden

Multiple Myeloma (MM), the second most common lymphoid cancer worldwide, is characterised by the uninhibited proliferation of terminally differentiated Blymphocytes. Leading to The diagnosis typically requires the presence of a monoclonal protein (M protein) and the demonstration of CRAB features (hypercalcemia, renal impairment, anaemia and bone lesions). MM is considered incurable as, due to serial clonal evolution, the vast majority of patients succumb to treatment refractory disease. MGUS (Monoclonal Gammopathy of Unknown Uncertain Significance) is the pre-malignant form of MM and, although 93% of MM patients exhibit M protein production associated with MGUS before diagnosis, little is known about the switch from pre-malignant to malignant disease. To explore this disease transition further, LC-MS/MS analysis was carried out to identify potential salivary biomarkers to monitor disease burden. FABP5 was detected in saliva as having a significant increase in abundance when MGUS was compared to symptomatic MM. The levels of FABP5 decreased after treatment indicating correlation with tumour burden. This finding was validated using western blot analysis and ELISA analysis. Significance: The field of biomarker discovery has focused largely on serum as a biofluid. Saliva is a readily available biofluid that, as a biomarker resource, has been relatively un-explored. The identification of changes in saliva indicating disease progression underlines the utility of saliva as a non-invasive source of informative biomarkers reflecting disease burden and progression

Potential biomarkers of acute ischemic stroke etiology revealed by mass spectrometry based proteomic characterization of formalin-fixed paraffin-embedded blood clots

Background and Aims: Besides the crucial role in the treatment of acute ischemic stroke (AIS), mechanical thrombectomy represents a unique opportunity for researchers to study the retrieved clots, with the possibility of unveiling biological patterns linked to stroke pathophysiology and etiology. We aimed to develop a shotgun proteomic approach to study and compare the proteome of formalin-fixed paraffin-embedded (FFPE) cardioembolic and large artery atherosclerotic (LAA) clots. Methods: We used 16 cardioembolic and 15 LAA FFPE thrombi from 31 AIS patients. The thrombus proteome was analyzed by label-free quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant v1.5.2.8 and Perseus v.1.6.15.0 were used for bioinformatics analysis. Protein classes were identified using the PANTHER database and the STRING database was used to predict protein interactions. Results: We identified 1,581 protein groups as part of the AIS thrombus proteome. Fourteen significantly differentially abundant proteins across the two etiologies were identified. Four proteins involved in the ubiquitin-proteasome pathway, blood coagulation or plasminogen activating cascade were identified as significantly abundant in LAA clots. Ten proteins involved in the ubiquitin proteasome-pathway, cytoskeletal remodeling of platelets, platelet adhesion or blood coagulation were identified as significantly abundant in cardioembolic clots. Conclusion: Our results outlined a set of 14 proteins for a proof-of-principle characterization of cardioembolic and LAA FFPE clots, advancing the proteome profile of AIS human thrombi and understanding the pathophysiology of ischemic stroke.This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant No. 13/RC/2073_2. Furthermore, the authors declare that this study received funding from Cerenovus. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication.peer-reviewe

Priority III

The Priority III Priority Setting Partnership identified priorities for future research around how we plan, do and share the results of rapid reviews in the context of healthcare using a modified JLA approac