Proximity Extension Assay Research Articles

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p<0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Proximity extension assay in cerebrospinal fluid identifies neurofilament light chain as biomarker of neurodegeneration in sporadic cerebral amyloid angiopathy

BackgroundSporadic cerebral amyloid angiopathy (sCAA) is a disease characterised by the progressive deposition of the amyloid beta (Aβ) in the cerebral vasculature, capable of causing a variety of symptoms, from (mild) cognitive impairment, to micro- and major haemorrhagic lesions. Modern diagnosis of sCAA relies on radiological detection of late-stage hallmarks of disease, complicating early diagnosis and potential interventions in disease progression. Our goal in this study was to identify and validate novel biomarkers for sCAA.MethodsWe performed a proximity extension assay (PEA) on cerebrospinal fluid (CSF) samples of sCAA/control participants (n = 34/51). Additionally, we attempted to validate the top candidate biomarker in CSF and serum samples (n = 38/26) in a largely overlapping validation cohort, through analysis with a targeted immunoassay.ResultsThirteen proteins were differentially expressed through PEA, with top candidate NFL significantly increased in CSF of sCAA patients (p < 0.0001). Validation analyses using immunoassays revealed increased CSF and serum NFL levels in sCAA patients (both p < 0.0001) with good discrimination between sCAA and controls (AUC: 0.85; AUC: 0.79 respectively). Additionally, the CSF: serum NFL ratio was significantly elevated in sCAA (p = 0.002).DiscussionLarge-scale targeted proteomics screening of CSF of sCAA patients and controls identified thirteen biomarker candidates for sCAA. Orthogonal validation of NFL identified NFL in CSF and serum as biomarker, capable of differentiating between sCAA patients and controls.

Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation

BackgroundAtrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology. ObjectivesTo determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS). MethodsProteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used. ResultsOlder age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = −0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration. ConclusionProteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.

Proteomics screening after pediatric allogenic hematopoietic stem cell transplantation reveals an association between increased expression of inhibitory receptor FCRL6 on γδ Tcells and cytomegalovirus reactivation.

We studied the associations between inflammation-related proteins in circulation and complications after pediatric allogenic hematopoietic stem cell transplantation (HSCT), to reveal proteomic signatures or individual soluble proteins associated with specific complications after HSCT. We used a proteomics method called Proximity Extension Assay to repeatedly measure 180 different proteins together with clinical variables, cellular immune reconstitution and blood viral copy numbers in 27 children (1-18 years of age) during a 2-year follow-up after allogenic HSCT. Protein profile analysis was performed using unsupervised hierarchical clustering and a regression-based method, while the Bonferroni-corrected Mann-Whitney U-test was used for time point-specific comparison of individual proteins against outcome. At 6 months after allogenic HSCT, we could identify a protein profile pattern associated with occurrence of the complications such as chronic graft-versus-host disease, viral infections, relapse and death. When protein markers were analyzed separately, the plasma concentration of the inhibitory and cytotoxic T-cell surface protein FCRL6 (Fc receptor-like 6) was higher in patients with cytomegalovirus (CMV) viremia [log2-fold change 1.5 (P = 0.00099), 2.5 (P = 0.00035) and 2.2 (P = 0.045) at time points 6, 12 and 24 months]. Flow cytometry confirmed that FCRL6 expression was higher in innate-like γδ Tcells, indicating that these cells are involved in controlling CMV reactivation in HSCT recipients. In conclusion, the potentially druggable FCRL6 receptor on cytotoxic Tcells appears to have a role in controlling CMV viremia after HSCT. Furthermore, our results suggest that system-level analysis is a useful addition to the studying of single biomarkers in allogenic HSCT.

Proteomic mapping identifies serum marker signatures associated with MIS-C specific hyperinflammation and cardiovascular manifestation

Multisystem inflammatory syndrome in children (MIS-C) shares several clinical and immunological features with Kawasaki Disease (KD) and pediatric hyperinflammation, but the immuno-phenotypic overlap among these clinical mimics is still incompletely understood. Here we analyzed serum samples from treatment-naïve patients with MIS-C (n = 31) and KD (n = 11), pediatric hyperinflammation (n = 13) and healthy controls (HC, n = 10) by proximity extension assay (PEA) to profile 184 blood biomarkers. Collectively, immunophenotypic overlap between MIS-C and hyperinflammation exceeds overlap with KD. Overexpression of IL-17A in MIS-C and KD could best separate these conditions from hyperinflammatory conditions, while those were hallmarked by overabundance of adenosin deaminase and IL-18. Depletion in serum TNF-related subfamily member 9 (TNFRSF9) and apoptosis inducing ligand (TRAIL) linked with cardiovascular manifestations and myocarditis in MIS-C. Altogether, our analysis highlights important differences in molecular marker signatures also across different MIS-C and KD cohorts and suggests several previously unidentified molecular associations in context of cardiovascular inflammation.

Exposure-response relationship of guselkumab and the potential of serum proteomics in identifying predictive biomarker candidates in psoriasis.

Response to biologics in psoriasis varies in real-world settings. Serum biomarkers could aid biologic selection and dose modifications to improve patient outcomes while encouraging cost-effective care. To explore the exposure-response relationship for guselkumab (GUS), to define a GUS concentration target for optimal response and to evaluate the potential of serum protein levels as predictive biomarker candidates. This is a prospective, multicentric, cohort study in psoriasis patients treated with GUS. Serum GUS trough concentrations (TCs) collected at multiple timepoints were measured using an in-house immunoassay. Next, proximity extension assay technology (Target 96 Inflammation Panel Olink®) was used to measure serum protein levels in a subcohort including 38 GUS patients (week 0 and week 4), six psoriasis patients naive for systemic treatment and four healthy controls. Seventy-five patients participated and 400 samples were collected. Guselkumab TCs and clinical response were correlated at week 4, week 12 and in steady-state (≥20 weeks). Optimal responders (Psoriasis Area and Severity Index [PASI] ≤ 2) had significantly higher TCs than suboptimal responders from week 4 onwards in treatment. An optimal steady-state TC of 1.6 μg/mL was defined. Although TC and absolute PASI were lower and worse, respectively, in patients weighing ≥90 kg, clinical outcomes referred to desirable to excellent PASI ranges. Therefore, we do not recommend systematically higher GUS doses in obese patients. We could not reveal early differentially expressed proteins to distinguish future optimal from suboptimal responders. We demonstrated an exposure-response relationship for GUS and an optimal steady-state TC of 1.6 μg/mL in real-world psoriasis patients. Hereby, we deliver more evidence that therapeutic drug monitoring poses a promising strategy in optimizing GUS treatment. No biomarker candidates were identified through serum proteomics. We propose protein screening should be repeated in larger cohorts to continue the quest for predictive biomarkers.

THE EFFECT OF TREATMENT ON THE INFLAMMATION PROFILE AMONG PATIENTS WITH PRIMARY ALDOSTERONISM

Objective: Due to direct and indirect effects of aldosterone various pathways of inflammation cascade are activated leading to further end organ damage and higher cardiovascular risk among patients with primary aldosteronism (PA). To what extent the pro-inflammatory effects occur and, more importantly, if they are affected by the PA treatment remain unclear. Therefore, we aimed to analyze the inflammation profile among patients with PA before and after the treatment. Design and method: 46 patients with PA (43% with adrenal adenoma and 57% with bilateral hyperplasia) were included into this study. Patient serum samples were collected at the study entry and 6 months after the treatment of PA was initiated. Demographic, clinical and laboratory data were collected retrospectively. Inflammatory cytokines and proteins were measured in patient’s serum using proximity extension assay (O-link Inflammation panel, Olink Proteomics, Uppsala, Sweden). Results: There were 52% woman and 48% men with a mean age of 50.2±12 years. The median aldosterone-renin-quotient (ARQ) was 96 and the blood pressure values were ranging between 142±17/89±12 mmHg. 6 months following the treatment a significant reduction in blood pressure and ARQ was achieved. Analysis of association between clinical factors and biomarker expression has shown that patients with adrenal adenoma have significantly higher levels of FGF21, whereas female gender was associated with lower expression of pro-inflammatory cytokines such as IL-18, TNFRSF9, CXCL9 and higher expression of protective cytokines such as TWEAK and MCP-4, especially among females with bilateral hyperplasia. According to proteomic analysis at study entry, we have identified 4 patient clusters. Interestingly, young females with adrenal adenoma have composed a separate cluster with significantly higher levels of IL-6, IFN-gamma, MCP-1, MMP1 and FGF21 and robust reduction of these parameters following the treatment. In general, volcano plot analysis of whole study cohort has demonstrated the significant reduction in expression of pro-inflammatory cytokines (EN-RAGE, CCL23, OPG, IL-10, FGF21 etc). Conclusions: The treatment of primary aldosteronism leads to reduced expression of pro-inflammatory proteins. The extent of inflammatory activation as well as response to treatment is highly associated with gender and the cause of aldosterone excess.

Search for cerebrospinal fluid biomarkers in patients with major psychiatric disorders: Multiplex immunoassay findings and proximity extension assay prospects.

Multiplex immunoassays have been developed to detect multiple proteins simultaneously and are used to search for biomarkers, including those present in major psychiatric disorders. This study aimed to review multiplex immunoassay studies on cerebrospinal fluid (CSF) biomarkers in patients with schizophrenia, bipolar disorder (BD), and major depressive disorder (MDD) and examine future research directions using improved proteomic techniques. According to the results of previous multiplex immunoassay studies, increased CSF IFN-β, IL-8, MCP-2, MMP-2, PAI-1, sICAM-1, and sVCAM-1 and decreased CSF ACE, APP, fibrinogen, and GDNF were observed in patients with schizophrenia, while CSF HGF and S100B were positively correlated with psychotic symptom and CSF IL-11, IL-29/IFN-λ1, and TSLP were negatively correlated. Increased CSF IFN-β and IL-1β and decreased CSF Aβ42, APP, IL-6, and NCAM-1 were observed, while CSF S100B was positively correlated with manic symptom in patients with BD. Increased CSF IL-4, MCP-1, MIP-1β, and MMP-2 were observed in patients with MDD, while CSF HGF and MMP-2 were positively correlated with depressive symptom and CSF IL-15 and MCP-1 were negatively correlated. However, signal cross-talk and cross-reactivity problems have been observed in previous studies using multiplex immunoassay. The proximity extension assay can be used to overcome cross-reactivity and enable ultrasensitive multiplexed detection and quantification of more than 1000 target proteins. However, proteomic studies using proximity extension assay technology in patients with schizophrenia, BD, or MDD are still scarce. Therefore, future high-quality proteomic studies are required to identify CSF biomarkers for larger sets of target proteins in patients with major psychiatric disorders.

Multiplex proteomics identifies inflammation-related plasma biomarkers for aging and cardio-metabolic disorders

Abstract Background Cardio-metabolic disorders (CMDs) are common in aging people and are pivotal risk factors for cardiovascular diseases (CVDs). Inflammation is involved in the pathogenesis of CVDs and aging, but the underlying inflammatory molecular phenotypes in CMDs and aging are still unknown. Method We utilized multiple proteomics to detect 368 inflammatory proteins in the plasma of 30 subjects, including healthy young individuals, healthy elderly individuals, and elderly individuals with CMDs, by Proximity Extension Assay technology (PEA, O-link). Protein-protein interaction (PPI) network and functional modules were constructed to explore hub proteins in differentially expressed proteins (DEPs). The correlation between proteins and clinical traits of CMDs was analyzed and diagnostic value for CMDs of proteins was evaluated by ROC curve analysis. Result Our results revealed that there were 161 DEPs (adjusted p &lt; 0.05) in normal aging and EGF was the most differentially expressed hub protein in normal aging. Twenty-eight DEPs were found in elderly individuals with CMDs and MMP1 was the most differentially expressed hub protein in CMDs. After the intersection of DEPs in aging and CMDs, there were 10 overlapping proteins: SHMT1, MVK, EGLN1, SLC39A5, NCF2, CXCL6, IRAK4, REG4, PTPN6, and PRDX5. These proteins were significantly correlated with the level of HDL-C, TG, or FPG in plasma. They were verified to have good diagnostic value for CMDs in aging with an AUC &gt; 0.7. Among these, EGLN1, NCF2, REG4, and SLC39A2 were prominently increased both in normal aging and aging with CMDs. Conclusion Our results could reveal molecular markers for normal aging and CMDs, which need to be further expanded the sample size and to be further investigated to predict their significance for CVDs.

Patient-derived tumoroids and proteomic signatures: tools for early drug discovery.

Onco-virotherapy is an emergent treatment for cancer based on viral vectors. The therapeutic activity is based on two different mechanisms including tumor-specific oncolysis and immunostimulatory properties. In this study, we evaluated onco-virotherapy in vitro responses on immunocompetent non-small cell lung cancer (NSCLC) patient-derived tumoroids (PDTs) and healthy organoids. PDTs are accurate tools to predict patient's clinical responses at the in vitro stage. We showed that onco-virotherapy could exert specific antitumoral effects by producing a higher number of viral particles in PDTs than in healthy organoids. In the present work, we used multiplex protein screening, based on proximity extension assay to highlight different response profiles. Our results pointed to the increase of proteins implied in T cell activation, such as IFN-γ following onco-virotherapy treatment. Based on our observation, oncolytic viruses-based therapy responders are dependent on several factors: a high PD-L1 expression, which is a biomarker of greater immune response under immunotherapies, and the number of viral particles present in tumor tissue, which is dependent to the metabolic state of tumoral cells. Herein, we highlight the use of PDTs as an alternative in vitro model to assess patient-specific responses to onco-virotherapy at the early stage of the preclinical phases.

The plasma proteome differentiates the multisystem inflammatory syndrome in children (MIS-C) from children with SARS-CoV-2 negative sepsis

BackgroundThe Multi-System Inflammatory Syndrome in Children (MIS-C) can develop several weeks after SARS-CoV-2 infection and requires a distinct treatment protocol. Distinguishing MIS-C from SARS-CoV-2 negative sepsis (SCNS) patients is important to quickly institute the correct therapies. We performed targeted proteomics and machine learning analysis to identify novel plasma proteins of MIS-C for early disease recognition.MethodsA case-control study comparing the expression of 2,870 unique blood proteins in MIS-C versus SCNS patients, measured using proximity extension assays. The 2,870 proteins were reduced in number with either feature selection alone or with a prior COMBAT-Seq batch effect adjustment. The leading proteins were correlated with demographic and clinical variables. Organ system and cell type expression patterns were analyzed with Natural Language Processing (NLP).ResultsThe cohorts were well-balanced for age and sex. Of the 2,870 unique blood proteins, 58 proteins were identified with feature selection (FDR-adjusted P < 0.005, P < 0.0001; accuracy = 0.96, AUC = 1.00, F1 = 0.95), and 15 proteins were identified with a COMBAT-Seq batch effect adjusted feature selection (FDR-adjusted P < 0.05, P < 0.0001; accuracy = 0.92, AUC = 1.00, F1 = 0.89). All of the latter 15 proteins were present in the former 58-protein model. Several proteins were correlated with illness severity scores, length of stay, and interventions (LTA4H, PTN, PPBP, and EGF; P < 0.001). NLP analysis highlighted the multi-system nature of MIS-C, with the 58-protein set expressed in all organ systems; the highest levels of expression were found in the digestive system. The cell types most involved included leukocytes not yet determined, lymphocytes, macrophages, and platelets.ConclusionsThe plasma proteome of MIS-C patients was distinct from that of SCNS. The key proteins demonstrated expression in all organ systems and most cell types. The unique proteomic signature identified in MIS-C patients could aid future diagnostic and therapeutic advancements, as well as predict hospital length of stays, interventions, and mortality risks.

Contactin 5 and Apolipoproteins Interplay in Alzheimer's Disease.

Apolipoproteins and contactin 5 are proteins associated with Alzheimer's disease (AD) pathophysiology. Apolipoproteins act on transport and clearance of cholesterol and phospholipids during synaptic turnover and terminal proliferation. Contactin 5 is a neuronal membrane protein involved in key processes of neurodevelopment. To investigate the interactions between contactin 5 and apolipoproteins in AD, and the role of these proteins in response to neuronal damage. Apolipoproteins (measured by Luminex), contactin 5 (measured by Olink's proximity extension assay), and cholesterol (measured by liquid chromatography mass spectrometry) were assessed in the cerebrospinal fluid (CSF) and plasma of cognitively unimpaired participants (n = 93). Gene expression was measured using polymerase chain reaction in the frontal cortex of autopsied-confirmed AD (n = 57) and control subjects (n = 31) and in the hippocampi of mice following entorhinal cortex lesions. Contactin 5 positively correlated with apolipoproteins B (p = 5.4×10-8), D (p = 1.86×10-4), E (p = 2.92×10-9), J (p = 2.65×10-9), and with cholesterol (p = 0.0096) in the CSF, and with cholesterol (p = 0.02), HDL (p = 0.0143), and LDL (p = 0.0121) in the plasma. Negative correlations were seen between CNTN5, APOB (p = 0.034) and APOE (p = 0.015) mRNA levels in the brains of control subjects. In the mouse model, apoe and apoj gene expression increased during the reinnervation phase (p < 0.05), while apob (p = 0.023) and apod (p = 0.006) increased in the deafferentation stage. Extensive interactions were observed between contactin 5 and apolipoproteins and cholesterol, possibly due to neuronal damage. The alterations in gene expression of apolipoproteins suggest a role in axonal, terminal, and synaptic remodeling in response to entorhinal cortex damage.

Plasma proteomics of diabetic kidney disease among Asians with younger-onset type 2 diabetes.

Patients with younger onset of type 2 diabetes (YT2D) have increased risk for kidney failure compared to those with late onset. However, the mechanism of diabetic kidney disease (DKD) progression in this high-risk group is poorly understood. To identify novel biomarkers and potential causal proteins associated with DKD progression in patients with YT2D. Among YT2D (T2D onset age ≤ 40 years), 144 DKD progressors (cases) were matched for T2D onset age, sex, and ethnicity with 292 non-progressors (controls) and divided into discovery and validation sets. DKD progression was defined as decline of estimated glomerular filtration rate (eGFR) of 3ml/min/1.73m2 or greater or 40% decline in eGFR from baseline. 1472 plasma proteins were measured through a multiplex immunoassay that uses a proximity extension assay technology. Multivariable logistic regression was used to identify proteins associated with DKD progression. Mendelian randomization (MR) was used to evaluate causal relationship between plasma proteins and DKD progression. 42 plasma proteins were associated with DKD progression, independent of traditional cardio-renal risk factors, baseline eGFR and urine albumin-to-creatinine ratio (uACR). The proteins identified were related to inflammatory and remodelling biological processes. Our findings suggested angiogenin as one of the top signals (odds ratio =5.29, 95% CI 2.39-11.73, P = 4.03 × 10-5). Furthermore, genetically determined plasma angiogenin level was associated with increased odds of DKD progression. Large-scale proteomic analysis identified novel proteomic biomarkers for DKD progression in YT2D. Genetic evidence suggest a causal role of plasma angiogenin in DKD progression.

Targeted plasma proteomic analysis uncovers a high-performance biomarker panel for early diagnosis of gastric cancer

BackgroundGastric cancer (GC) is characterized by high morbidity, high mortality and low early diagnosis rate. Early diagnosis plays a crucial role in radically treating GC. The aim of this study was to identify plasma biomarkers for GC and early GC diagnosis. MethodsWe quantified 369 protein levels with plasma samples from discovery cohort (n = 88) and validation cohort (n = 50) via high-throughput proximity extension assay (PEA) utilizing the Olink-Explore-384-Cardiometabolic panel. The multi-protein signatures were derived from LASSO and Ridge regression models. ResultsIn the discovery cohort, 13 proteins (GDF15, ITIH3, BOC, DPP7, EGFR, AMY2A, CCDC80, CD163, GPNMB, LTBP2, CTSZ, CCL18 and NECTIN2) were identified to distinguish GC (Stage I-IV) and early GC (HGIN-I) groups from control group with AUC of 0.994 and AUC of 0.998, severally. The validation cohort yielded AUC of 0.930 and AUC of 0.818 for GC and early GC, respectively. ConclusionsThis study identified a multi-protein signature with the potential to benefit clinical GC diagnosis, especially for Asian and early GC patients, which may contribute to the development of a less-invasive, convenient, and efficient early screening tool, promoting early diagnosis and treatment of GC and ultimately improving patient survival.

Proteomic profiling for biomarker discovery in heparin-induced thrombocytopenia

AbstractNew analytical techniques can assess hundreds of proteins simultaneously with high sensitivity, facilitating the observation of their complex interplay and role in disease mechanisms. We hypothesized that proteomic profiling targeting proteins involved in thrombus formation, inflammation, and the immune response would identify potentially new biomarkers for heparin-induced thrombocytopenia (HIT). Four existing panels of the Olink proximity extension assay covering 356 proteins involved in thrombus formation, inflammation, and immune response were applied to randomly selected patients with suspected HIT (confirmed HIT, n = 32; HIT ruled out, n = 38; and positive heparin/platelet factor 4 [H/PF4] antibodies, n = 28). The relative difference in protein concentration was analyzed using a linear regression model adjusted for sex and age. To confirm the test results, soluble P-selectin was determined using enzyme-linked immunosorbent assay (ELISA) in above mentioned patients and an additional second data set (n = 49). HIT was defined as a positive heparin-induced platelet activation assay (washed platelet assay). Among 98 patients of the primary data set, the median 4Ts score was 5 in patients with HIT, 4 in patients with positive H/PF4 antibodies, and 3 in patients without HIT. The median optical density of a polyspecific H/PF4 ELISA were 3.0, 0.9, and 0.3. Soluble P-selectin remained statistically significant after multiple test adjustments. The area under the receiver operating characteristic curve was 0.81 for Olink and 0.8 for ELISA. Future studies shall assess the diagnostic and prognostic value of soluble P-selectin in the management of HIT.

Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival

BackgroundBreast cancers exhibit considerable heterogeneity in their biology, immunology, and prognosis. Currently, no validated, serum protein-based tools are available to evaluate the prognosis of patients with early breast cancer.MethodsThe study population consisted of 521 early-stage breast cancer patients with a median follow-up of 8.9 years. Additionally, 61 patients with breast fibroadenoma or atypical ductal hyperplasia were included as controls. We used a proximity extension assay to measure the preoperative serum levels of 92 proteins associated with inflammatory and immune response processes. The invasive cancers were randomly split into discovery (n = 413) and validation (n = 108) cohorts for the statistical analyses.ResultsUsing LASSO regression, we identified a nine-protein signature (CCL8, CCL23, CCL28, CSCL10, S100A12, IL10, IL10RB, STAMPB2, and TNFβ) that predicted various survival endpoints more accurately than traditional prognostic factors. In the time-dependent analyses, the prognostic power of the model remained rather stable over time. We also developed and validated a 17-protein model with the potential to differentiate benign breast lesions from malignant lesions (Wilcoxon p < 2.2*10− 16; AUC 0.94).ConclusionsInflammation and immunity-related serum proteins have the potential to rise above the classical prognostic factors of early-stage breast cancer. They may also help to distinguish benign from malignant breast lesions.

Abstract LB098: Deep plasma proteome characterization in two independent clinical cohorts identifies clusters of biomarkers separating benign and malign tumors in women with suspicion of ovarian cancer

Abstract Early detection is essential for ovarian cancer survival but today’s biomarkers are not specific enough to clear benign from malignant tumors nor sensitive enough to be used in screening. Here we have used the proximity extension assay (PEA) Olink Explore HT to characterize 5416 plasma proteins. For a subset of the women, we have also characterized the transcriptional landscape in corresponding tumor tissue using total RNA-sequencing on the Illumina NovaSeq 6000 instrument. The plasma samples were from two independent Swedish clinical cohorts (N1 = 171, N2 = 233) and tumor RNA was extracted from 112 of the samples from the second cohort. Each cohort consisted of women who after suspicion of ovarian cancer were surgically diagnosed with either benign or malign tumors. All plasma samples were collected at time of diagnosis, before commencement of treatment. In the plasma protein analyses, the first cohort was used as a discovery and the second as replication. In the discovery cohort, we found a total of 328 plasma proteins differing significantly between women with benign tumors and; early stage (I-II), late stage (III-IV) or any stage(I-IV) malignant tumors. These associations were examined in the replication cohort, and were all found to have similar foldchange between women with benign and malignant tumors. 99.7% (327/328) differed significantly after adjustment for multiple hypothesis testing. The 328 associations corresponded to a total of 192 proteins out of which 26 (13.5%) were found to have a significant correlation with RNA-expression in the corresponding tumor. A correlation network analysis based on the 192 proteins identified 5 major clusters, consisting of 18 to 59 protein-protein couplings. 80% of these clusters contained proteins that are annotated with up to five major KEGG cancer pathways and several of these contained proteins correlating significantly with the tumor RNA-SEQ data. All except one cluster contained one or two proteins that are either currently approved FDA drug targets or listed as druggable in DrugBank by specific compounds. Ovarian cancer has a low 5-year survival and eludes the current treatment regimens if discovered late. By applying high-throughput proteomics in two independent cohorts, we identified a large number of affected proteins out of which only a few have corresponding changes in tumor RNA-expression. We also identified large highly co-regulated networks of proteins, suggesting large downstream systemic effects which could be a contributing factor to the difficulties in finding efficient treatments. Among these proteins, there are several druggable targets, however, not all the associated compounds are currently primarily used as anti-cancer drugs, highlighting the possibility of drug re-purposing for future use against ovarian cancer. Citation Format: Stefan Enroth, Mikaela Moskov, Julia Lindberg Hedlund, Svetlana Popova, Simn K. Forsberg, Klev Diamanti, Maria Lycke, Emma Ivansson, Anna Tolf, Karin Sundfeldt, Karin Stålberg, Ulf Gyllensten. Deep plasma proteome characterization in two independent clinical cohorts identifies clusters of biomarkers separating benign and malign tumors in women with suspicion of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB098.

Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections

BackgroundSelf-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.MethodsOur study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.ResultsOur three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors.ConclusionsProteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.

Anti-IL-6 Receptor Treatment in Giant Cell Arteritis Patients Reduces Levels of IL-1β-Receptor Antagonist but Not IL-1β

This work aimed to investigate a potential link between serum IL-1β levels in patients with giant cell arteritis (GCA) and their responsiveness to combined anti-IL-6 receptor (IL-6R) and glucocorticoid (GC) treatments within the context of two separate clinical trials. IL-1β levels were analyzed in serum samples of two prospective clinical trials investigating tocilizumab in GCA patients using quantitative Polymerase Chain Reaction (qPCR) based Proximity Ligation Assays (PLA). In the phase II randomized controlled trial, serum samples from five patients were quantified at two critical time points: the commencement of the trial (Week 2) and the conclusion of the trial (Week 52). In the GUSTO trial, serum samples from nine patients were similarly analyzed using PLA at Day 0 and Week 52. Furthermore, for the GUSTO trial, serum samples from 18 patients were assessed for IL-1β and IL-1RN at six time points: days 0, 3, and 10, weeks 4, 24, and 52 by a second assay (Proximity Extension Assay, PEA). PLA results from both studies indicated that IL-1β levels were below 1 pg/mL in most of the patients, resulting in notable signal deviations within the same samples. In the analysis of the GUSTO trial, both PLA and PEA exhibited similar trends in IL-1β variations among patients from day 0 to week 52. Notably, the PEA analysis did not show significant variation over time. Furthermore, we did not find a correlation of IL-1β levels with active disease as compared to remission, but interestingly, the measurement of IL-1β receptor antagonist (IL-1RN) revealed a substantial decrease over time. Our study shows that IL-1RN but not IL-1β concentration in serum samples could be directly related to anti-IL-6R treatment in patients diagnosed with GCA.

Biomarkers and Proteomics in Sarcomeric Hypertrophic Cardiomyopathy in the Young-FGF-21 Highly Associated with Overt Disease.

Background: Any difference in biomarkers between genotype-positive individuals with overt hypertrophic cardiomyopathy (HCM), and genotype-positive but phenotype-negative individuals (G+P-) in HCM-associated pathways might shed light on pathophysiological mechanisms. We studied this in young HCM patients. Methods: 29 HCM patients, 17 G+P--individuals, and age- and sex-matched controls were prospectively included. We analyzed 184 cardiovascular disease-associated proteins by two proximity extension assays, categorized into biological pathways, and analyzed with multivariate logistic regression analysis. Significant proteins were dichotomized into groups above/below median concentration in control group. Results: Dichotomized values of significant proteins showed high odds ratio (OR) in overt HCMphenotype for Fibroblast growth factor-21 (FGF-21) 10 (p = 0.001), P-selectin glycoprotein ligand-1 (PSGL-1) OR 8.6 (p = 0.005), and Galectin-9 (Gal-9) OR 5.91 (p = 0.004). For G+P-, however, angiopoietin-1 receptor (TIE2) was notably raised, OR 65.5 (p = 0.004), whereas metalloproteinase inhibitor 4 (TIMP4) involved in proteolysis, in contrast, had reduced OR 0.06 (p = 0.013). Conclusions: This study is one of the first in young HCM patients and G+P- individuals. We found significantly increased OR for HCM in FGF-21 involved in RAS-MAPK pathway, associated with cardiomyocyte hypertrophy. Upregulation of FGF-21 indicates involvement of the RAS-MAPK pathway in HCM regardless of genetic background, which is a novel finding.