Epstein-Barr Virus-Encoded BARF1 Protein is a Decoy Receptor for Macrophage Colony Stimulating Factor and Interferes with Macrophage Differentiation and Activation

Epstein-Barr virus (EBV), like many other persistent herpes viruses, has acquired numerous mechanisms for subverting or evading immune surveillance. This study investigates the role of secreted EBV-encoded BARF1 protein (sBARF1) in creating an immune evasive microenvironment. Wild-type consensus BARF1 was expressed in the human 293 cell line and purified. This native hexameric sBARF1 had inhibitory capacity on macrophage colony stimulating factor (M-CSF)-stimulated, and not on granulocyte macrophage-colony stimulating factor (GM-CSF)-stimulated growth and differentiation of myeloid cells. Antibodies specific to hexameric sBARF1 were able to block this effect. M-CSF was shown to interact with sBARF1 via the protruding N-terminal loops involving Val38 and Ala84. Each BARF1 hexamer was capable of binding three M-CSF dimers. Mutations in the BARF1 loops greatly affected M-CSF interaction, and showed loss of growth inhibition. Analysis of the activation state of the M-CSF receptor c-fms and its downstream kinase pathways showed that sBARF1 prevented M-CSF-induced downstream phosphorylation. Since M-CSF is an important factor in macrophage differentiation, the effect of sBARF1 on the function of monocyte-derived macrophages was evaluated. sBARF1 affected overall survival and morphology and significantly reduced expression of macrophage differentiation surface markers such as CD14, CD11b, CD16, and CD169. Macrophages differentiating in the presence of sBARF1 showed impaired responses to lipopolysaccharide and decreased oxygen radical formation as well as reduced phagocytosis of apoptotic cells. In conclusion, EBV sBARF1 protein is a potent decoy receptor for M-CSF, hampering the function and differentiation of macrophages. These results suggest that sBARF1 contributes to the modulation of immune responses in the microenvironment of EBV-positive carcinoma

Prognostic and predictive value of human equilibrative nucleoside transporter 1 (hENT1) in extrahepatic cholangiocarcinoma: a translational study

Introduction: Effective (neo) adjuvant chemotherapy for cholangiocarcinoma is lacking due to chemoresistance and the absence of predictive biomarkers. Human equilibrative nucleoside transporter 1 (hENT1) has been described as a potential prognostic and predictive biomarker. In this study, the potential of rabbit-derived (SP120) and murine-derived (10D7G2) antibodies to detect hENT1 expression was compared in tissue samples of patients with extrahepatic cholangiocarcinoma (ECC), and the predictive value of hENT1 was investigated in three ECC cell lines. Methods: Tissues of 71 chemonaïve patients with histological confirmation of ECC were selected and stained with SP120 or 10D7G2 to assess the inter-observer variability for both antibodies and the correlation with overall survival. Concomitantly, gemcitabine sensitivity after hENT1 knockdown was assessed in the ECC cell lines EGI-1, TFK-1, and SK-ChA-1 using sulforhodamine B assays. Results: Scoring immunohistochemistry for hENT1 expression with the use of SP120 antibody resulted in the highest interobserver agreement but did not show a prognostic role of hENT1. However, 10D7G2 showed a prognostic role for hENT1, and a potential predictive role for gemcitabine sensitivity in hENT1 in SK-ChA-1 and TFK-1 cells was found. Discussion: These findings prompt further studies for both preclinical validation of the role of hENT1 and histochemical standardization in cholangiocarcinoma patients treated with gemcitabine-based chemotherapy

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000

Detection and localization of early- and late-stage cancers using platelet RNA

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I–IV cancer patients and in half of 352 stage I–III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening

Surveillance strategy for small asymptomatic non-functional pancreatic neuroendocrine tumors – a systematic review and meta-analysis

Background Non-functional pancreatic neuroendocrine tumors (NF-PNET) are rare neoplasms being increasingly diagnosed. Surgical treatment or expectant management are both suggested for small NF-PNETs. The aim of this study was to evaluate the outcome of surveillance strategy for small NF-PNETs. Methods A systematic search was performed up to March 2016 in MEDLINE, EMBASE and the Cochrane Library according to the PRISMA guidelines. Data was pooled using the random-effects model. Results Nine articles including 344 patients with sporadic and 64 patients with MEN1 related NF-PNET were selected. Tumor growth was observed in 22% and 52%, development of metastases were reported on 0% and 9%, and rate of secondary surgical resection was 12% and 25% in patients with sporadic or MEN1 related NF-PNETs, respectively. All metastases (1 distant, 4 nodal) were reported by a single study in patients with MEN1. Reason for secondary surgery was tumor growth in half of patients undergoing surgery. Discussion Expectant management of small asymptomatic, sporadic, NF-PNETs could be a reasonable option in highly selected patients. However, the level of evidence is low and longer follow-up is needed to identify patients could benefit from upfront surgery instead of expectant treatment

MiRNA profiling for diagnosis, prognosis and stratification of cancer treatment in cholangiocarcinoma

Cholangiocarcinoma (CCA) is a lethal malignancy originating from the biliary tract epithelium. Most patients are diagnosed at an advanced stage. Even after resection with curative intent, prognosis remains poor. Previous studies have reported the evolving role of miRNAs as novel biomarkers in cancer diagnosis, prognostication and chemotherapy response. Various miRNAs, such as miR-21, miR-26, miR-122 and miR-150, have been identified as possible blood-based biomarkers for noninvasive diagnosis of CCA. Moreover, epithelial-mesenchymal transition (EMT)- and angiogenesis-associated miRNAs have been implicated in tumor cell dissemination and are able to determine clinical outcome. In fact, miRNAs involved in cell survival might even determine chemotherapy response. This review provides an overview of known miRNAs as CCA-specific biomarkers

Bioinformatic analysis reveals pancreatic cancer molecular subtypes specific to the tumor and the microenvironment

<p>Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by a dense desmoplastic reaction surrounding malignant epithelial cells. Interaction between the epithelial and stromal compartments is suggested to enhance its aggressive nature. Indeed, therapies targeting the stroma, as well as the tumor cells, may improve survival outcomes for patients. The evaluated study by Moffitt <i>et al</i>. used bioinformatic techniques to separate gene expression patterns of normal tissues from PDAC and stroma in a large cohort of samples. The researchers identified two different subtypes of PDAC (‘classical’ and ‘basal-like’) and surrounding stroma (‘normal’ and ‘activated’). The basal-like subtype was associated with worse prognosis and a trend towards better response to adjuvant therapy. Hopefully, the molecular stratification of PDAC will potentially allow more personalized treatment strategies and guide clinical decision making.</p