Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue

In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates, n = 27) from control tissues (reactive lymph node lysates, n = 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (n = 26) and healthy controls (n = 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini–Hochberg’s false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all p ≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance.

Plasma Proteome Fingerprints Reveal Distinctiveness and Clinical Outcome of SARS-CoV-2 Infection

Background: We evaluated how plasma proteomic signatures in patients with suspected COVID-19 can unravel the pathophysiology, and determine kinetics and clinical outcome of the infection. Methods: Plasma samples from patients presenting to the emergency department (ED) with symptoms of COVID-19 were stratified into: (1) patients with suspected COVID-19 that was not confirmed (n = 44); (2) non-hospitalized patients with confirmed COVID-19 (n = 44); (3) hospitalized patients with confirmed COVID-19 (n = 53) with variable outcome; and (4) patients presenting to the ED with minor diseases unrelated to SARS-CoV-2 infection (n = 20). Besides standard of care diagnostics, 177 circulating proteins related to inflammation and cardiovascular disease were analyzed using proximity extension assay (PEA, Olink) technology. Results: Comparative proteome analysis revealed 14 distinct proteins as highly associated with SARS-CoV-2 infection and 12 proteins with subsequent hospitalization (p < 0.001). ADM, IL-6, MCP-3, TRAIL-R2, and PD-L1 were each predictive for death (AUROC curve 0.80–0.87). The consistent increase of these markers, from hospital admission to intensive care and fatality, supported the concept that these proteins are of major clinical relevance. Conclusions: We identified distinct plasma proteins linked to the presence and course of COVID-19. These plasma proteomic findings may translate to a protein fingerprint, helping to assist clinical management decisions.

Differential chemokine alteration in the variants of primary progressive aphasia—a role for neuroinflammation

Background The primary progressive aphasias (PPA) represent a group of usually sporadic neurodegenerative disorders with three main variants: the nonfluent or agrammatic variant (nfvPPA), the semantic variant (svPPA), and the logopenic variant (lvPPA). They are usually associated with a specific underlying pathology: nfvPPA with a primary tauopathy, svPPA with a TDP-43 proteinopathy, and lvPPA with underlying Alzheimer’s disease (AD). Little is known about their cause or pathophysiology, but prior studies in both AD and svPPA have suggested a role for neuroinflammation. In this study, we set out to investigate the role of chemokines across the PPA spectrum, with a primary focus on central changes in cerebrospinal fluid (CSF) Methods Thirty-six participants with sporadic PPA (11 svPPA, 13 nfvPPA, and 12 lvPPA) as well as 19 healthy controls were recruited to the study and donated CSF and plasma samples. All patients with lvPPA had a tau/Aβ42 biomarker profile consistent with AD, whilst this was normal in the other PPA groups and controls. We assessed twenty chemokines in CSF and plasma using Proximity Extension Assay technology: CCL2 (MCP-1), CCL3 (MIP-1a), CCL4 (MIP-1β), CCL7 (MCP-3), CCL8 (MCP-2), CCL11 (eotaxin), CCL13 (MCP-4), CCL19, CCL20, CCL23, CCL25, CCL28, CX3CL1 (fractalkine), CXCL1, CXCL5, CXCL6, CXCL8 (IL-8), CXCL9, CXCL10, and CXCL11. Results In CSF, CCL19 and CXCL6 were decreased in both svPPA and nfvPPA compared with controls whilst CXCL5 was decreased in the nfvPPA group with a borderline significant decrease in the svPPA group. In contrast, CCL2, CCL3 and CX3CL1 were increased in lvPPA compared with controls and nfvPPA (and greater than svPPA for CX3CL1). CXCL1 was also increased in lvPPA compared with nfvPPA but not the other groups. CX3CL1 was significantly correlated with CSF total tau concentrations in the controls and each of the PPA groups. Fewer significant differences were seen between groups in plasma, although in general, results were in the opposite direction to CSF, i.e. decreased in lvPPA compared with controls (CCL3 and CCL19), and increased in svPPA (CCL8) and nfvPPA (CCL13). Conclusion Differential alteration of chemokines across the PPA variants is seen in both CSF and plasma. Importantly, these results suggest a role for neuroinflammation in these poorly understood sporadic disorders, and therefore also a potential future therapeutic target.

Comparison of two multiplexed technologies for profiling >1,000 serum proteins that may associate with tumor burden

Background: In this pilot study, we perform a preliminary comparison of two targeted multiplex proteomics technologies for discerning serum protein concentration changes that may correlate to tumor burden in ovarian cancer (OC) patients. Methods: Using the proximity extension assay (PEA) and Quantibody® Kiloplex Array (QKA), we measured >1,000 proteins in the pre-surgical and post-surgical serum from nine OC patients (N=18 samples). We expect that proteins that have decreased significantly in the post-surgical serum concentration may correlate to tumor burden in each patient. Duplicate sera from two healthy individuals were used as controls (N=4 samples). We employed in-house ELISAs to measure five proteins with large serum concentration changes in pre- and post-surgical sera, from four of the original nine patients and the two original controls. Results: Both platforms showed a weak correlation with clinical cancer antigen 125 (CA125) data. The two multiplexed platforms showed a significant correlation with each other for >400 overlapping proteins. PEA uncovered 15 proteins, while QKA revealed 11 proteins, with more than a two-fold post-surgical decrease in at least six of the nine patients. Validation using single enzyme-linked immunosorbent assays (ELISAs) showed at least a two-fold post-surgical decrease in serum concentration of the same patients, as indicated by the two multiplex assays. Conclusion: Both methods identified proteins that had significantly decreased in post-surgical serum concentration, as well as recognizing proteins that had been implicated in OC patients. Our findings from a limited sample size suggest that novel targeted proteomics platforms are promising tools for identifying candidate serological tumor-related proteins. However further studies are essential for the improvement of accuracy and avoidance of false results.

Evaluation of a 92 multiplex protein panel in detection of colorectal cancer and high-risk adenoma in 784 symptomatic individuals

BACKGROUND: Blood-based protein biomarkers for detection of colorectal cancer (CRC) have been submitted to intense research to improve the full potential in screening for CRC. OBJECTIVE: The aim was to explore the diagnostic performance of 92 proteins related to inflammation and carcinogenesis in detection of CRC or precancerous lesions. METHODS: Blood-samples were collected from 4,698 individuals undergoing colonoscopy. An explorative unmatched case-control study was designed with 294 cases (individuals with CRC or high-risk colorectal adenoma) and 490 controls (individuals with low-risk colorectal adenoma, non-malignant findings or clean colorectum at colonoscopy). Protein profiling was performed by multiplex proximity extension assay. Statistical analyses were performed as univariate and multivariate logistic regression analyses. RESULTS: Univariably, CSF-1, MMP12 and IL8 demonstrated superior performance in discrimination of individuals with CRC. Recurrently, IL8 was included as contributor in majority of multivariate models discriminating individuals with CRC. The multivariate evaluation in discrimination of individuals with CRC demonstrated AUC=ROC 0.82, sensitivity = 0.39 at specificity = 0.80. Discrimination of individuals with late stage CRC from individuals with clean colorectum demonstrated AUC=ROC 0.90, sensitivity = 0.58 at specificity = 0.80. CONCLUSIONS: A subset of biomarker candidates, specifically IL8, investigated in the present study suggest a potential as blood-based biomarkers in screening of CRC.

Differential Chemokine Alteration in the Variants of Primary Progressive Aphasia – A Role for Neuroinflammation

Background The primary progressive aphasias (PPA) represent a group of usually sporadic neurodegenerative disorders with three main variants: the nonfluent or agrammatic variant (nfvPPA), the semantic variant (svPPA), and the logopenic variant (lvPPA). They are usually associated with a specific underlying pathology: nfvPPA with a primary tauopathy, svPPA with a TDP-43 proteinopathy, and lvPPA with underlying Alzheimer’s disease (AD). Little is known about their cause or pathophysiology but prior studies in both AD and svPPA have suggested a role for neuroinflammation. In this study we set out to investigate the role of chemokines across the PPA spectrum, with a primary focus on central changes in cerebrospinal fluid (CSF) Methods 36 participants with sporadic PPA (11 svPPA, 13 nfvPPA and 12 lvPPA) as well as 19 healthy controls were recruited to the study and donated CSF and plasma samples. All patients with lvPPA had a tau/Aβ42 biomarker profile consistent with AD, whilst this was normal in the other PPA groups and controls. We assessed twenty chemokines in CSF and plasma using Proximity Extension Assay technology: CCL2 (MCP-1), CCL3 (MIP-1a), CCL4 (MIP-1β), CCL7 (MCP-3), CCL8 (MCP-2), CCL11 (eotaxin), CCL13 (MCP-4), CCL19, CCL20, CCL23, CCL25, CCL28, CX3CL1 (fractalkine), CXCL1, CXCL5, CXCL6, CXCL8 (IL-8), CXCL9, CXCL10, and CXCL11. Results In CSF, CCL19 and CXCL6 were decreased in both svPPA and nfvPPA compared with controls whilst CXCL5, was decreased in the nfvPPA group with a borderline significant decrease in the svPPA group. In contrast, CCL2, CCL3 and CX3CL1 were increased in lvPPA compared with controls and nfvPPA (and greater than svPPA for CX3CL1). CXCL1 was also increased in lvPPA compared with nfvPPA but not the other groups. CX3CL1 was significantly correlated with CSF total tau concentrations in the controls and each of the PPA groups. Fewer significant differences were seen between groups in plasma, although in general, results were in the opposite direction to CSF i.e. decreased in lvPPA compared with controls (CCL3 and CCL19), and increased in svPPA (CCL8) and nfvPPA (CCL13). Conclusion Differential alteration of chemokines across the PPA variants is seen in both CSF and plasma. Importantly, these results suggest a role for neuroinflammation in these poorly understood sporadic disorders, and therefore also a potential future therapeutic target.

Abstract P777: Statistical Modeling of Proteomic Signaling During Stroke in Patients Undergoing Thrombectomy

Introduction: The previously published Blood and Clot Thrombectomy Registry and Collaboration (BACTRAC) protocol (clinicaltrials.gov NCT03153683) utilizes mechanical thrombectomy to obtain tissue samples for banking. Peripheral blood proximal to the clot and intracranial blood distal from the clot were isolated. Proteomic and statistical analyses revealed normalized (intracranial-systemic) CCL19 expression was a predictor of infarct volume. Statistical modeling analyses were used determine the CCL19-associated proteomic signaling network occurring during ischemic stroke relating to infarct volume. Methods: Arterial intracranial and systemic blood samples underwent analysis for inflammatory proteins using Proximity Extension Assay (PEA) via Olink (Olink Proteomics, Boston, MA). Systemic expression was used as an internal control to normalize expression in the intracranial blood. Bivariate regression was used to examine the relationship between the intracranial normalized CCL19 expression and infarct volume. A backwards stepwise regression was then used to determine a model of predictability of infarct volume by CCL19 and associated inflammatory proteins. Results: 25 subjects (>18 yrs) with a mean infarct volume of 8,172 ± 82,284 mm 3 and mean infarct time of 513 ± 246 minutes were included in this study. Their median age was 64 (24-91) and 10 (40%) were male. 16 subjects (64%) had hypertension, 15 (60%) had BMI > 25, and 6 (24%) had a previous stroke. The stepwise regression model shows normalized expression of 16 proteins correlated with an increase in infarct volume (p<0.005): CCL20, CXCL1, OSM, CD6, OSMR, TGF-alpha, TRANCE, CXCL10, LIF-R, CCL19, CDCP1, Flt3L, CCL23, CD244, TRAIL, NOTCH1. Conclusions: In our model, the expression of these proteins were consistently changed, though the directionality differed. LIF-R, NOTCH1, TRAIL, CD6, CCL23, TGF-alpha, and CCL20 were positively correlated, while the expressions of Flt3L, OSM, OSMR, TRANCE, CD244, CDCP1, CXCL1, CXCL10, and CCL19 were negatively correlated with infarct volume. This model depicts the proteomic signaling occurring during stroke in relationship to infarct volume, which reveals potential biomarkers and therapeutic targets for the early phase of ischemic stroke.