Citriquinolinones A and B: Rare Isoquinolinone-Embedded Citrinin Analogues and Related Metabolites from the Deep-Sea-Derived Aspergillus versicolor 170217.

A systematic chemical investigation of the deep-sea-derived fungus Aspergillus versicolor 170217 resulted in the isolation of six new (1-6) and 45 known (7-51) compounds. The structures of the new compounds were established on the basis of exhaustive analysis of their spectroscopic data and theoretical-statistical approaches including GIAO-NMR, TDDFT-ECD/ORD calculations, DP4+ probability analysis, and biogenetic consideration. Citriquinolinones A (1) and B (2) feature a unique isoquinolinone-embedded citrinin scaffold, representing the first exemplars of a citrinin-isoquinolinone hybrid. Dicitrinones K-L (3-4) are two new dimeric citrinin analogues with a rare CH-CH3 bridge. Biologically, frangula-emodin (32) and diorcinol (17) displayed remarkable anti-food allergic activity with IC50 values of 7.9 ± 3.0 µM and 13.4 ± 1.2 µM, respectively, while diorcinol (17) and penicitrinol A (20) exhibited weak inhibitory activity against Vibrio parahemolyticus, with MIC values ranging from 128 to 256 µM.

Cladosporium sphaerospermum extract inhibits quorum sensing associated virulence factors of Serratia marcescens.

Serratia marcescens is now becoming a propensity for its highly antimicrobial-resistant clinical infections. Currently, it provides a novel strategy to prevent and control microbial infection by regulating S. marcescens quorum sensing (QS). Deep-sea-derived fungi are rich in QS bioactive constituents. In this work, the extracts from Cladosporium sphaerospermum SCSGAF0054 showed potent QS-related virulence factors and biofilm-inhibiting activities against S. marcescens NJ01. The swimming motility and multiple virulence factors such as prodigiosin, exopolysaccharide (EPS), lipase, protease and hemolysin were moderately inhibited by the extracts at varied concentrations. The confocal laser scanning microscope (CLSM) and scanning electron microscope (SEM) images revealed that C. sphaerospermum extracts moderately arrested biofilm formation and cell viability. Further, real-time quantitative PCR (RT-qPCR) analysis revealed that expressions of genes associated with virulence factors, flhD, fimA, fimC, bsmA, bsmB, pigA, pigC, and shlA, were significantly down-regulated compared with control. In addition, the extracts combined with imipenem inhibited the QS system of S. marcescens NJ01, disrupted its preformed biofilm, released the intra-biofilm bacteria and killed the bacteria gradually. Therefore, the extracts combined with imipenem can partially restore bacterial drug sensitivity. These results suggest that the extracts from SCSGAF0054 effectively interfere with the QS system to treat S. marcescens infection alone or combining with classical antimicrobial drugs.

Conditional concordance-assisted learning under matched case-control design for combining biomarkers for population screening.

Incorporating promising biomarkers into cancer screening practices for early-detection is increasingly appealing because of the unsatisfactory performance of current cancer screening strategies. The matched case-control design is commonly adopted in biomarker development studies to evaluate the discriminative power of biomarker candidates, with an intention to eliminate confounding effects. Data from matched case-control studies have been routinely analyzed by the conditional logistic regression, although the assumed logit link between biomarker combinations and disease risk may not always hold. We propose a conditional concordance-assisted learning method, which is distribution-free, for identifying an optimal combination of biomarkers to discriminate cases and controls. We are particularly interested in combinations with a clinically and practically meaningful specificity to prevent disease-free subjects from unnecessary and possibly intrusive diagnostic procedures, which is a top priority for cancer population screening. We establish asymptotic properties for the derived combination and confirm its favorable finite sample performance in simulations. We apply the proposed method to the prostate cancer data from the carotene and retinol efficacy trial (CARET).

Disruption of stem cell niche-confined R-spondin 3 expression leads to impaired hematopoiesis.

Self-renewal and differentiation of stem and progenitor cells are tightly regulated to ensure tissue homeostasis. This regulation is enabled both remotely by systemic circulating cues, such as cytokines and hormones, and locally by various niche-confined factors. R-spondin 3 (RSPO3) is one of the most potent enhancers of Wnt signaling, and its expression is usually restricted to the stem cell niche where it provides localized enhancement of Wnt signaling to regulate stem cell expansion and differentiation. Disruption of this niche-confined expression can disturb proper tissue organization and lead to cancers. Here, we investigate the consequences of disrupting the niche-restricted expression of RSPO3 in various tissues, including the hematopoietic system. We show that normal Rspo3 expression is confined to the perivascular niche in the bone marrow. Induction of increased systemic levels of circulating RSPO3 outside of the niche results in prominent loss of early B-cell progenitors and anemia but surprisingly has no effect on hematopoietic stem cells. Using molecular, pharmacologic, and genetic approaches, we show that these RSPO3-induced hematopoietic phenotypes are Wnt and RSPO3 dependent and mediated through noncanonical Wnt signaling. Our study highlights a distinct role for a Wnt/RSPO3 signaling axis in the regulation of hematopoiesis, as well as possible challenges related to therapeutic use of RSPOs for regenerative medicine.

Chemical Constituents of the Deep-Sea-Derived Fungus Cladosporium oxysporum 170103 and Their Antibacterial Effects.

The Cladosporium fungi, one of the largest genera of dematiaceous hyphomycetes, could produce various bioactive secondary metabolites. From the AcOEt-soluble extract of Cladosporium oxysporum 170103, three new secopatulolides (1-3) and thirteen known compounds (4-16) were obtained. Their structures were established by detailed analysis of the NMR and HR-ESI-MS data. All sixteen compounds were tested for antibacterial activity against Vibrio parahemolyticus, ergosterol (10) presented moderate effect with the minimum inhibitory concentration (MIC) of 32 µM. It can destruct the membrane integrity of Vibrio parahemolyticus to change the cell shape.

Cladosporioles A and B, Two New Indole Derivatives from the Deep-Sea-Derived Fungus Cladosporium cladosporioides 170056.

Two new (cladosporioles A and B, 1 and 2) and fourteen known (3-16) compounds were isolated from the deep-sea-derived fungus Cladosporium cladosporioides 170056. The relative structures of the new compounds were elucidated mainly by detailed analysis of their NMR and HR-ESI-MS spectroscopic data. Their absolute configurations were determined by comparison of the experimental and calculated electronic circular dichroism (ECD) spectra. All isolates were tested for antimicrobial activity against Vibrio parahaemolyticus. Compound 15 exhibited weak effect with the MIC value of 156.25 µg/mL.

Anti-Food Allergic Alkaloids from the Lotus Seed Pot.

Lotus seed pod (LSP) has been used as traditional herbal cuisine to modulate immunity. From the AcOEt-soluble extract of LSP, one new aporphine alkaloid, N-[2-(2H-phenanthro[3,4-d][1,3]dioxol-5-yl)ethyl]acetamide (nelunucine A, 1) was obtained along with 19 known ones. Their structures were established by detailed analysis of the 1D-, 2D-NMR, and HR-ESI-MS data. N-Nornuciferine (9) and lirinidine (10) showed potent in vitro anti-food allergic activity with IC50 values of 40.0 and 55.4 µM, respectively, compared to 91.4 µM for loratadine, the positive control.

Chemical Constituents of the Marine Fungus Penicillium sp. MCCC 3A00228.

One new (d-arabinitol-anofinicate, 1) and fourteen known (2-15) compounds were isolated from the marine Penicillium sp. MCCC 3A00228. The structure of the new compound was established mainly by extensive spectroscopic analyses. Compound 1 exhibited weak transcriptional effect on Nur77. While compound 13 showed moderate in vitro anti-proliferative effect against QGY7701, H1299, and HCT116 tumor cells with IC50 values of 21.2 µM, 18.2 µM, and 17.6 µM, respectively.

Total Synthesis and Anti-Inflammatory Bioactivity of (-)-Majusculoic Acid and Its Derivatives.

The first total synthesis of marine natural product, (-)-majusculoic acid (1) and its seven analogs (9-15), was accomplished in three to ten steps with a yield of 3% to 28%. The strategy featured the application of the conformational controlled establishment of the trans-cyclopropane and stereochemical controlled bromo-olefination or olefination by Horner-Wadsworth-Emmons (HWE) reaction. The potential anti-inflammatory activity of the eight compounds (1 and 9-15) was evaluated by determining the nitric oxide (NO) production in the lipopolysaccharide (LPS)-induced mouse macrophages RAW264.7. (-)-Majusculoic acid (1), methyl majusculoate (9), and (1R,2R)-2-((3E,5Z)-6-bromonona-3,5-dien-1-yl)cyclopropane-1-carboxylic acid (12) showed significant effect with inhibition rates of 33.68%, 35.75%, and 43.01%, respectively. Moreover, they did not show cytotoxicity against RAW264.7 cells, indicating that they might be potential anti-inflammatory agents.

Asperochratides A-J, Ten new polyketides from the deep-sea-derived Aspergillus ochraceus.

Ten new C9 polyketides (asperochratides A-J, 1-10) and 14 known miscellaneous compounds (11-24) were isolated from the deep-sea-derived fungus Aspergillus ochraceus. Structures of the new compounds were elucidated by extensive spectroscopic analyses, modified Mosher's method, Mo2(OAc)4 induced circular dichroism (ICD) experiments, and ECD calculations. Structurally, compounds 1-11 and 16-18 share the same polyketide origin of the skeleton and belong to aspyrone co-metabolites. All isolates were tested for cytotoxic, anti-food allergic, anti-H1N1 virus, anti-microbe, and anti-inflammatory activities in vitro. Results showed that compounds 5-8 and 13-17 exerted significant cytotoxic effects on BV-2 cell line, and compound 16 showed the potential of anti-inflammatory activities.

Ultra-Short Circulating Tumor DNA (usctDNA) in Plasma and Saliva of Non-Small Cell Lung Cancer (NSCLC) Patients.

Mutations identified in the epidermal growth factor receptor (EGFR) predict sensitivity to EGFR-targeted therapy for non-small cell lung carcinoma (NSCLC). We previously reported that Electric Field-Induced Release and Measurement (EFIRM)-based liquid biopsy could detect EGFR ctDNA with >94% concordance with tissue-based genotyping. A side-by-side comparison of concordance of EFIRM and droplet digital PCR (ddPCR) for the detection of the two front-line actionable EFGR mutations was performed with paired plasma and saliva samples from 13 NSCLC patients. Deep sequencing analysis based on single-strand DNA library preparation was employed to determine the size distributions of EGFR L858R ctDNA in plasma and saliva samples. EFIRM detected both EGFR mutations with 100% sensitivity in both plasma and saliva samples, whereas ddPCR detected EGFR mutations with sensitivities of 84.6% and 15.4%, respectively. In saliva samples, the majority of EGFR L858R ctDNA fragments detected were <80 bp. Deep sequencing analysis of ctDNA enriched for the EGFR L858R mutation revealed the significant presence of EGFR L858R ctDNA as ultra-short circulating tumor DNA (usctDNA) with the size of 40-60 bp in patient plasma and saliva. Most of usctDNAs are not amplifiable with the current ddPCR assay. Further examination using cell lines and patient biofluids revealed that the majority of usctDNAs were predominately localized in the exosomal fraction. Our study revealed the abundant existence of EGFR ctDNA in the plasma and saliva of NSCLC patients is usctDNA. usctDNA is a novel type of targets for liquid biopsy that can be efficiently detected by EFIRM technology.

Antiproliferative Sorbicillinoids From the Deep-Sea-Derived Penicillium allii-sativi.

Two new (1-2) and three known (3-5) sorbicillinoids were isolated from the deep-sea-derived fungus Penicillium allii-sativi MCCC 3A00580. Compounds 1 and 2, named sorbicatechols C and D, were two new hybrid dihydrosorbillinoids. Their structures were established mainly by spectroscopic analyses and electronic circular dichroism (ECD) calculations. All five isolates were tested for antiproliferative activities against four tumor cell lines of MCF-7, HT-29, HuH-7, and LNCap. Compounds 2 and 5 inhibited HT-29 cells in a good dose-dependent manner. Mechanism investigation uncovered that they could significantly induce cell cycle G2-M phase arresting by increasing the protein levels of p-H3 and cyclin B1.

Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

Importance: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. Objective: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. Design, Setting, and Participants: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). Main Outcomes and Measures: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). Results: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. Conclusions and Relevance: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.

Combining multiple biomarkers linearly to maximize the partial area under the ROC curve.

It is now common in clinical practice to make clinical decisions based on combinations of multiple biomarkers. In this paper, we propose new approaches for combining multiple biomarkers linearly to maximize the partial area under the receiver operating characteristic curve (pAUC). The parametric and nonparametric methods that have been developed for this purpose have limitations. When the biomarker values for populations with and without a given disease follow a multivariate normal distribution, it is easy to implement our proposed parametric approach, which adopts an alternative analytic expression of the pAUC. When normality assumptions are violated, a kernel-based approach is presented, which handles multiple biomarkers simultaneously. We evaluated the proposed as well as existing methods through simulations and discovered that when the covariance matrices for the disease and nondisease samples are disproportional, traditional methods (such as the logistic regression) are more likely to fail to maximize the pAUC while the proposed methods are more robust. The proposed approaches are illustrated through application to a prostate cancer data set, and a rank-based leave-one-out cross-validation procedure is proposed to obtain a realistic estimate of the pAUC when there is no independent validation set available.

Estimation of smooth ROC curves for biomarkers with limits of detection.

Protein biomarkers found in plasma are commonly used for cancer screening and early detection. Measurements obtained by such markers are often based on different assays that may not support detection of accurate measurements due to a limit of detection. The ROC curve is the most popular statistical tool for the evaluation of a continuous biomarker. However, in situations where limits of detection exist, the empirical ROC curve fails to provide a valid estimate for the whole spectrum of the false positive rate (FPR). Hence, crucial information regarding the performance of the marker in high sensitivity and/or high specificity values is not revealed. In this paper, we address this problem and propose methods for constructing ROC curve estimates for all possible FPR values. We explore flexible parametric methods, transformations to normality, and robust kernel-based and spline-based approaches. We evaluate our methods though simulations and illustrate them in colorectal and pancreatic cancer data.

Epigenome-Wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-Lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer.

PURPOSE: Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential. EXPERIMENTAL DESIGN: Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum. RESULTS: Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P < 0.05) AUC (range, 0.66-0.75) or pAUC (range, 0.007-0.009). The biomarkers that improved discrimination of patients with metastatic-lethal prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P <0.05). CONCLUSIONS: Eight differentially methylated CpGs that distinguish patients with metastatic-lethal from nonrecurrent tumors were validated. These novel epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR.

Quantitative Proteomics Based on Optimized Data-Independent Acquisition in Plasma Analysis.

The advent of high-resolution and frequency mass spectrometry has ushered in an era of data-independent acquisition (DIA). This approach affords enormous multiplexing capacity and is particularly suitable for clinical biomarker studies. However, DIA-based quantification of clinical plasma samples is a daunting task due to the high complexity of clinical plasma samples, the diversity of peptides within the samples, and the high biologic dynamic range of plasma proteins. Here we applied DIA methodology, including a highly reproducible sample preparation and LC-MS/MS analysis, and assessed its utility for clinical plasma biomarker detection. A pancreatic cancer-relevant plasma spectral library was constructed consisting of over 14 000 confidently identified peptides derived from over 2300 plasma proteins. Using a nonhuman protein as the internal standard, various empirical parameters were explored to maximize the reliability and reproducibility of the DIA quantification. The DIA parameters were optimized based on the quantification cycle times and fragmentation profile complexity. Higher analytical and biological reproducibility was recorded for the tryptic peptides without labile residues and missed cleavages. Quantification reliability was developed for the peptides identified within a consistent retention time and signal intensity. Linear analytical dynamic range and the lower limit of quantification were assessed, suggesting the critical role of sample complexity in optimizing DIA settings. Technical validation of the assay using a cohort of clinical plasma indicated the robustness and unique advantage for targeted analysis of clinical plasma samples in the context of biomarker development.

Evaluation of a novel saliva-based epidermal growth factor receptor mutation detection for lung cancer: A pilot study.

BACKGROUND: This article describes a pilot study evaluating a novel liquid biopsy system for non-small cell lung cancer (NSCLC) patients. The electric field-induced release and measurement (EFIRM) method utilizes an electrochemical biosensor for detecting oncogenic mutations in biofluids. METHODS: Saliva and plasma of 17 patients were collected from three cancer centers prior to and after surgical resection. The EFIRM method was then applied to the collected samples to assay for exon 19 deletion and p.L858 mutations. EFIRM results were compared with cobas results of exon 19 deletion and p.L858 mutation detection in cancer tissues. RESULTS: The EFIRM method was found to detect exon 19 deletion with an area under the curve (AUC) of 1.0 in both saliva and plasma samples in lung cancer patients. For L858R mutation detection, the AUC of saliva was 1.0, while the AUC of plasma was 0.98. Strong correlations were also found between presurgery and post-surgery samples for both saliva (0.86 for exon 19 and 0.98 for L858R) and plasma (0.73 for exon 19 and 0.94 for L858R). CONCLUSION: Our study demonstrates the feasibility of utilizing EFIRM to rapidly, non-invasively, and conveniently detect epidermal growth factor receptor mutations in the saliva of patients with NSCLC, with results corresponding perfectly with the results of cobas tissue genotyping.

MAPRE1 as a plasma biomarker for early-stage colorectal cancer and adenomas.

Blood-based biomarkers for early detection of colorectal cancer could complement current approaches to colorectal cancer screening. We previously identified the APC-binding protein MAPRE1 as a potential colorectal cancer biomarker. Here, we undertook a case-control validation study to determine the performance of MAPRE1 in detecting early colorectal cancer and colon adenoma and to assess the potential relevance of additional biomarker candidates. We analyzed plasma samples from 60 patients with adenomas, 30 with early colorectal cancer, 30 with advanced colorectal cancer, and 60 healthy controls. MAPRE1 and a set of 21 proteins with potential biomarker utility were assayed using high-density antibody arrays, and carcinoembryonic antigen (CEA) was assayed using ELISA. The biologic significance of the candidate biomarkers was also assessed in colorectal cancer mouse models. Plasma MAPRE1 levels were significantly elevated in both patients with adenomas and patients with colorectal cancer compared with controls (P < 0.0001). MAPRE1 and CEA together yielded an area under the curve of 0.793 and a sensitivity of 0.400 at 95% specificity for differentiating early colorectal cancer from controls. Three other biomarkers (AK1, CLIC1, and SOD1) were significantly increased in both adenoma and early colorectal cancer patient plasma samples and in plasma from colorectal cancer mouse models at preclinical stages compared with controls. The combination of MAPRE1, CEA, and AK1 yielded sensitivities of 0.483 and 0.533 at 90% specificity and sensitivities of 0.350 and 0.467 at 95% specificity for differentiating adenoma and early colorectal cancer, respectively, from healthy controls. These findings suggest that MAPRE1 can contribute to the detection of early-stage colorectal cancer and adenomas together with other biomarkers.

Equivalent input produces different output in the UniFrac significance test.

BACKGROUND: UniFrac is a well-known tool for comparing microbial communities and assessing statistically significant differences between communities. In this paper we identify a discrepancy in the UniFrac methodology that causes semantically equivalent inputs to produce different outputs in tests of statistical significance. RESULTS: The phylogenetic trees that are input into UniFrac may or may not contain abundance counts. An isomorphic transform can be defined that will convert trees between these two formats without altering the semantic meaning of the trees. UniFrac produces different outputs for these equivalent forms of the same input tree. This is illustrated using metagenomics data from a lake sediment study. CONCLUSIONS: Results from the UniFrac tool can vary greatly for the same input depending on the arbitrary choice of input format. Practitioners should be aware of this issue and use the tool with caution to ensure consistency and validity in their analyses. We provide a script to transform inputs between equivalent formats to help researchers achieve this consistency.