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Patients with liver cirrhosis are recommended ultrasonography screening for early detection of hepatocellular carcinoma to increase the chances of curative treatment. However, ultrasonography alone lacks in sensitivity. Adding plasma biomarkers may increase the detection rate. We performed a broad exploratory analysis to find new plasma proteins with potential applicability for HCC screening in patients with cirrhosis. In a protein discovery cohort of 172 patients with cirrhosis or HCC, we screened for 481 proteins with suspension bead array or proximity extension assay. From these, 24 proteins were selected for further analysis in a protein verification cohort (n = 160), using ELISA, Luminex or an electrochemiluminescence platform. A cut-off model and a stepwise logistic regression model were used to find combinations of proteins with the best discriminatory performance between HCC and cirrhosis. Stepwise logistic regression revealed alpha-fetoprotein (AFP), decarboxy-prothrombin (DCP), thioredoxin reductase 1 (TXNRD1), and fibroblast growth factor 21 (FGF21) as the proteins with the best discriminatory performance between HCC and cirrhosis. Adding TXNRD1 to DCP and AFP increased the AUC from 0.844 to 0.878, and combining AFP, DCP and TXNRD1 with age and sex resulted in an AUC of 0.920. FGF21, however, did not further increase the performance when including age and sex. In the present study, TXNRD1 improves the sensitivity and specificity of AFP and DCP as HCC screening tools in patients with cirrhosis. We suggest that TXNRD1 should be validated in prospective settings as a new complementary HCC biomarker together with AFP and DCP. [ABSTRACT FROM AUTHOR]

Simple Summary: A mass spectrometry (MS) proteomics and molecular pathway study was applied to serum samples of patients with ovarian serous carcinoma administered the FOLFOX-4 drug combination protocol, before the second cycle of therapy. This exploratory study aimed at identifying a protein panel that could be significantly modulated during two different collection time intervals and associated with patient response to therapy. The label-free differential MS proteomic analysis of 14 serum samples was conducted and identified 291 shared expressed proteins; 12 proteins resulted in being significantly associated with response to treatment and time of sample collection. The network enrichment analysis performed through STRING and other bioinformatic tools provided a metadata validation of the panel in which the identified proteins were related to resistant ovarian cancers at the molecular level. We concluded that the discovered protein panel that guided the identification of the associated molecular pathways could be further explored in a higher number of patients. Considering the lack of biomarkers that can guide the selection of further therapeutic approaches after drug resistance appearance, our study may suggest a new direction in the discovery and validation of a protein panel as biomarkers for future clinical application. Ovarian cancer is a highly lethal gynecological malignancy. Drug resistance rapidly occurs, and different therapeutic approaches are needed. So far, no biomarkers have been discovered to predict early response to therapies in the case of multi-treated ovarian cancer patients. The aim of our investigation was to identify a protein panel and the molecular pathways involved in chemotherapy response through a combination of studying proteomics and network enrichment analysis by considering a subset of samples from a clinical setting. Differential mass spectrometry studies were performed on 14 serum samples from patients with heavily pretreated platinum-resistant ovarian cancer who received the FOLFOX-4 regimen as a salvage therapy. The serum was analyzed at baseline time (T0) before FOLFOX-4 treatment, and before the second cycle of treatment (T1), with the aim of understanding if it was possible, after a first treatment cycle, to detect significant proteome changes that could be associated with patients responses to therapy. A total of 291 shared expressed proteins was identified and 12 proteins were finally selected between patients who attained partial response or no-response to chemotherapy when both response to therapy and time dependence (T0, T1) were considered in the statistical analysis. The protein panel included APOL1, GSN, GFI1, LCATL, MNA, LYVE1, ROR1, SHBG, SOD3, TEC, VPS18, and ZNF573. Using a bioinformatics network enrichment approach and metanalysis study, relationships between serum and cellular proteins were identified. An analysis of protein networks was conducted and identified at least three biological processes with functional and therapeutic significance in ovarian cancer, including lipoproteins metabolic process, structural component modulation in relation to cellular apoptosis and autophagy, and cellular oxidative stress response. Five proteins were almost independent from the network (LYVE1, ROR1, TEC, GFI1, and ZNF573). All proteins were associated with response to drug-resistant ovarian cancer resistant and were mechanistically connected to the pathways associated with cancer arrest. These results can be the basis for extending a biomarker discovery process to a clinical trial, as an early predictive tool of chemo-response to FOLFOX-4 of heavily treated ovarian cancer patients and for supporting the oncologist to continue or to interrupt the therapy. [ABSTRACT FROM AUTHOR]

Abstract Background Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors. Methods In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses. Results Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor. Conclusions The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort. Trial registration Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.

Many stage II/III colorectal cancer (CRC) patients may relapse after routine treatments. Aberrant phosphorylation can regulate pathophysiological processes of tumors, and finding characteristic protein phosphorylation is an efficient approach for the prediction of CRC relapse. We compared the tissue proteome and phosphoproteome of stage II/III CRC patients between the relapsed group (n = 5) and the non-relapsed group (n = 5). Phosphopeptides were enriched with Ti4+-IMAC material. We utilized label-free quantification-based proteomics to screen differentially expressed proteins and phosphopeptides between the two groups. Gene Ontology (GO) analysis and Ingenuity Pathway Analysis (IPA) were used for bioinformatics analysis. The immune response of the relapsed group (Z-score −2.229) was relatively poorer than that of the non-relapsed group (Z-score 1.982), while viability of tumor was more activated (Z-score 2.895) in the relapsed group, which might cause increased relapse risk. The phosphorylation degrees of three phosphosites (phosphosite 1362 of TP53BP1, phosphosite 809 of VCL and phosphosite 438 of STK10) might be reliable prognostic biomarkers. Some promising proteins and phosphopeptides were discovered to predict the relapse risk in postoperative follow-ups. [ABSTRACT FROM AUTHOR]

Abstract Aims Hypertension is the leading cause for the development of heart failure (HF). Here, we aimed to identify cardiomyocyte stretch‐induced circulating biomarkers for predicting hypertension‐associated HF. Methods and results Circulating levels of 149 proteins were measured by proximity extension assay at baseline examination in 4742 individuals from the Malmö Diet and Cancer study. Protein levels were compared with stretch‐activated gene expression changes in cultured neonatal rat ventricular myocytes (NRVMs) in response to 1–48 h of mechanical stretch. We also studied the association between protein levels and hypertension and HF incidence using respectively binary logistic and Cox regressions. Levels of 35 proteins were differentially expressed after Bonferroni correction in incident HF vs. control (P

Background: Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors.Methods: In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses.Results: Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor.Conclusions: The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort.Trial Registration: Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013. [ABSTRACT FROM AUTHOR]

Aims: Hypertension is the leading cause for the development of heart failure (HF). Here, we aimed to identify cardiomyocyte stretch‐induced circulating biomarkers for predicting hypertension‐associated HF. Methods and results: Circulating levels of 149 proteins were measured by proximity extension assay at baseline examination in 4742 individuals from the Malmö Diet and Cancer study. Protein levels were compared with stretch‐activated gene expression changes in cultured neonatal rat ventricular myocytes (NRVMs) in response to 1–48 h of mechanical stretch. We also studied the association between protein levels and hypertension and HF incidence using respectively binary logistic and Cox regressions. Levels of 35 proteins were differentially expressed after Bonferroni correction in incident HF vs. control (P < 3.4E−4). Growth differentiation factor‐15 (GDF‐15), interleukin‐6 (IL‐6), IL‐1 receptor type 1, and urokinase plasminogen activator surface receptor had corresponding mRNA levels up‐regulated by stretch in NRVMs at all time points (P < 0.05). These four proteins were individually associated with increased risk of HF after age and sex adjustment [hazard ratio (HR) per standard deviation: 1.19 ≤ HR ≤ 1.49, P ≤ 4.90E−3]. GDF‐15 and IL‐6 were associated with HF independently of each other (1.22 ≤ HR ≤ 1.33, P ≤ 0.001). In subjects with hypertension, these associations remained significant after further adjustment for N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP) levels (1.23 ≤ HR ≤ 1.45, P ≤ 0.001). A higher fasting value of a GDF‐15, IL‐6 score aggregate was associated with increased risk of hypertensive HF after adjustment for all traditional risk factors for HF and NT‐proBNP (HR = 1.31, P = 2.19E−4). Conclusions: Cardiomyocyte mRNA levels of GDF‐15 and IL‐6 are consistently up‐regulated by stretch, and their circulating protein levels predict HF in hypertensive subjects independently of NT‐proBNP during long‐term follow‐up. Our results encourage further studies on lower blood pressure goals in hypertensive subjects with high GDF‐15 and IL‐6, and interventions targeted at stretch‐induced cardiomyocyte expressed biomarkers. [ABSTRACT FROM AUTHOR]

Concentrations of 46 proteins have been determined in human blood plasma by the method of multiple reaction monitoring (MRM) using the PlasmaDeepDiveTM MRM-panel (Biognosys AG, Switzer land) for quantitative analysis of peptides. 18 of these proteins included into the group of proteins with higher concentrations, were also identified by method of liquid chromatography-tandem mass spectrometry (LS MS/MS) shotgun. Based on literature data it is concluded that the PlasmaDeepDiveTM MRM-panel is appli cable for studies of human plasma samples for determination of potential biomarkers of various nervous sys tem disorders. [ABSTRACT FROM AUTHOR]

BACKGROUND To date, no robust biomarkers have been available in clinical practice that can provide an early diagnostic evaluation of lung cancer. The objective of this study was to identify potential biomarkers for the early detection of lung cancer using bronchial brushing specimens. METHODS Immunocytochemistry was used to investigate the expression of 35 proteins in 880 bronchial brushing specimens from both outpatients and inpatients who had either lung cancer or benign lung lesions. An optimal panel was identified that had high sensitivity and considerable specificity for detecting lung cancer. Associations between protein expression and clinicopathologic parameters were assessed. RESULTS Tumor protein 53 (TP53), TP63, Ki67, epidermal growth factor receptor (EGFR), minichromosome maintenance complex component 6 (MCM6), MCM7, uncharacterized proteins KIAA1522 and KIAA0317, and ubiquitin-protein ligase UHR1 (ICBP90) frequently presented high expression in bronchial brushing specimens from patients who had lung cancer compared with patients who had benign lung lesions. A 6-protein panel consisting of TP53, Ki67, MCM6, MCM7, KIAA1522, and KIAA0317 was identified as the best combination, with sensitivity of 81.1% (309 of 381 specimens) for detecting nonsmall cell lung cancer (NSCLC) and 86.8% (145 of 167 specimens) for detecting small cell lung cancer (SCLC) (specificity, 83.3%; 65 of 78 specimens). The combination of cytology and the protein panel significantly improved the sensitivity of bronchial brushing examination for detecting lung cancer ( P<.00001), which increased from 49.1% to 81% in early stage NSCLC (stage I and II). In combined analyses, the protein panel was positively associated with patient sex ( P=.00033), tumor type ( P<.00001), tumor location ( P<.00001), and lymph node metastasis ( P=.028). CONCLUSIONS The 6-protein panel is a potential biomarker for the early detection of lung cancer in bronchial brushings. Cancer (Cancer Cytopathol) 2014;122:833-841. © 2014 American Cancer Society. [ABSTRACT FROM AUTHOR]

Many stage II/III colorectal cancer (CRC) patients might relapse after routine treatment and there is a great need of reliable biomarkers for predicting its reoccurrence risk. Small extracellular vesicles (sEVs) could regulate many pathophysiological processes of diseases, which are promising source for biomarker discovery. In this study, we implemented a MS-based workflow that utilizes data-dependent acquisition (DDA) for discovery and parallel reaction monitoring (PRM) for validation of high relapse risk related biomarkers. We compared the protein profiling of sEVs from CRC tissues and paired adjacent tissues in relapsed group (n = 5) and non-relapsed group (n = 5). 417 and 1140 proteins were differentially expressed between the tumor tissues and adjacent tissues in relapsed group and non-relapsed group, respectively. Bioinformatics analysis showed that immunity of the relapsed patients (Z -score − 0.69) was relatively poorer than the non-relapsed patients (Z-score 2.59), while chronic inflammatory response was activated (Z-score 3.0), which might enhance the reoccurrence risk. Four proteins (HLA-DPA1, S100P, NUP205, PCNA) showed significant expressions in the adjacent tissues of the relapsed group by PRM validation. ROC analysis of HLA-DPA1 (AUC = 0.96) achieved the best classification accuracy in separating the relapsed group and the non-relapsed group. Our data demonstrate that tissue-derived sEVs harbor prognostic proteomic signatures of CRC. In this research, our proteomics analysis of tissue sEVs revealed that poor immunity as well as chronic inflammatory of the CRC relapsed patient likely lead to poor prognosis and high risk of reoccurrence. The significant expression levels of four proteins (HLA-DPA1, S100P, NUP205, PCNA) in the adjacent tissues of the relapsed group might be used to predict the risk of relapse in postoperative follow-ups. A MS-based workflow that utilizes DDA for discovery and PRM for validation of high relapse risk related biomarkers of CRC. [Display omitted] • Small extracellular vesicles of colorectal cancer tissues are promising source for novel biomarker discovery. • Our proteomics analysis revealed that the CRC relapsed patients have poor immunity and chronic inflammatory. • Four validated proteins can predict high risk of relapse from low risk ones, showing the reliability for prognostic judgment. [ABSTRACT FROM AUTHOR]

Esophageal squamous cell carcinoma (ESCC) is a highly invasive disease with a poor long-term survival rate. Although there has been progress in understanding the pathogenesis of ESCC, there are currently no molecular biomarkers that are used in routine clinical practices to determine prognosis. Therefore, the aim of this study was to determine a small immunohistochemical panel that could predict the prognosis of patients with ESCC. Phospholipase C epsilon-1 (PLCE1), IKKα, IKBα, p65, and p53 were highly expressed in ESCC tissues. The high expression level of PLCE1, IKBα, and p53 showed a significant positive correlation with a short overall survival (P = .022, .009, and .024, respectively). This 3-biomarker panel (ie, PLCE1, IKBα, and p53) was found to be a predictor of ESCC, with a worse overall survival as each positive marker was added (hazard ratio, 1.553; 95% confidence interval, 1.166-2.067; P = .003). In another cohort (including 1922 esophageal endoscopic biopsy tissues), the lesions of 28 patients were aggravated. Three proteins (PLCE1, 12/28 [42.86%]; IKBα, 16/28 [57.14%]; p53, 16/28 [57.14%]) were immunoreactive in patients with progressive disease. Our study identified and validated that this immunohistochemical biomarker panel of 3 proteins, consisting of PLCE1, IKBα, and p53, is not only independently associated with an unfavorable outcome for ESCC patients but also able to predict disease progression to precancerous lesions., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Concentrations of 46 proteins have been determined in human blood plasma using PlasmaDeepDive™ MRM Panel ("Biognosys AG", Switzerland). 18 of them were included into the group of proteins with higher concentrations, also identified by the shotgun proteomic analysis. Based on literature data it is concluded that the PlasmaDeepDive™ MRM Panel is applicable for studies of human plasma samples for potential biomarkers of various nervous system disorders.

We developed a discovery-validation mass-spectrometry-based pipeline to identify a set of proteins that are regulated in serum of patients with cervical intraepithelial neoplasia (CIN) and squamous cell cervical cancer using iTRAQ, label-free shotgun, and targeted mass-spectrometric quantification. In the discovery stage we used a "pooling" strategy for the comparative analysis of immunodepleted serum and revealed 15 up- and 26 down-regulated proteins in patients with early- (CES) and late-stage (CLS) cervical cancer. The analysis of nondepleted serum samples from patients with CIN, CES, an CLS and healthy controls showed significant changes in abundance of alpha-1-acid glycoprotein 1, alpha-1-antitrypsin, serotransferrin, haptoglobin, alpha-2-HS-glycoprotein, and vitamin D-binding protein. We validated our findings using a fast UHPLC/MRM method in an independent set of serum samples from patients with cervical cancer or CIN and healthy controls as well as serum samples from patients with ovarian cancer (more than 400 samples in total). The panel of six proteins showed 67% sensitivity and 88% specificity for discrimination of patients with CIN from healthy controls, a stage of the disease where current protein-based biomarkers, for example, squamous cell carcinoma antigen (SCCA), fail to show any discrimination. Additionally, combining the six-protein panel with SCCA improves the discrimination of patients with CES and CLS from healthy controls.