MMP9 Processing of HSPB1 Regulates Tumor Progression

Matrix metalloproteinases regulate pathophysiological events by processing matrix proteins and secreted proteins. Previously, we demonstrated that soluble heat shock protein B1 (HSPB1) is released primarily from endothelial cells (ECs) and regulates angiogenesis via direct interaction with vascular endothelial growth factor (VEGF). Here we report that MMP9 can cleave HSPB1 and release anti-angiogenic fragments, which play a key role in tumorprogression. We mapped the cleavage sites and explored their physiological relevance during these processing events. HSPB1 cleavage by MMP9 inhibited VEGF-induced ECs activation and the C-terminal HSPB1 fragment exhibited more interaction with VEGF than did full-length HSPB1. HSPB1 cleavage occurs during B16F10 lung progression in wild-type mice. Also, intact HSPB1 was more detected on tumor endothelium of MMP9 null mice than wild type mice. Finally, we confirmed that secretion of C-terminal HSPB1 fragment was significantly inhibited lung and liver tumor progression of B16F10 melanoma cells and lung tumor progression of CT26 colon carcinoma cells, compared to full-length HSPB1. These data suggest that in vivo MMP9-mediated processing of HSPB1 acts to regulate VEGF-induced ECs activation for tumor progression, releasing anti-angiogenic HSPB1 fragments. Moreover, these findings potentially explain an anti-target effect for the failure of MMP inhibitors in clinical trials, suggesting that MMP inhibitors may have pro-tumorigenic effects by reducing HSPB1 fragmentation

Prognostic Factors and Clinical Outcomes of High-Dose Chemotherapy followed by Autologous Stem Cell Transplantation in Patients with Peripheral T Cell Lymphoma, Unspecified: Complete Remission at Transplantation and the Prognostic Index of Peripheral T Cell Lymphoma Are the Major Factors Predictive of Outcome

AbstractHigh-dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT) offers a rescue option for T cell lymphoma patients with poor prognosis. However, the effectiveness of HDT/ASCT in patients with various peripheral T cell subtypes, optimal transplant timing, and the prognostic factors that predict better outcomes, have not been identified. We retrospectively investigated the clinical outcomes and prognostic factors for HDT/ASCT in 64 Korean patients with peripheral T cell lymphoma, unspecified (PTCL-U) between March 1995 and February 2007. The median age at transplantation was 44 years (range: 15-63 years). According to the age-adjusted International Prognostic Index (a-IPI) and the prognostic index of PTCL (PIT), 8 patients (12.5%) were in the high-risk group and 16 (26.6%) had the 2-3 PIT factors, respectively. After a median follow-up of 29.7 months, the 3-year overall survival (OS) and progression-free survival (PFS) rates were 53.0% ± 7.5% and 44.3% ± 7.0%, respectively. Univariate analysis showed that poor performance status, high lactate dehydrogenase (LDH) levels, high a-IPI score, high PIT classes, failure to achieve complete response (CR) at transplantation, and nonfrontline transplantation were associated with poor OS. Multivariate analysis showed that failure to achieve CR at transplantation (hazard ratio [HR] 2.23; 95% confidence interval [CI] 1.78-7.93) and 2-3 PIT factors (HR 3.76; 95% CI 1.02-5.42) were independent prognostic factors for OS. Failure to achieve CR at transplantation and high PIT are negative predictable factors for survival following HDT/ASCT in patients with PTCL-U

KAI1 suppresses HIF-1α and VEGF expression by blocking CDCP1-enhanced Src activation in prostate cancer

<p>Abstract</p> <p>Background</p> <p>KAI1 was initially identified as a metastasis-suppressor gene in prostate cancer. It is a member of the tetraspan transmembrane superfamily (TM4SF) of membrane glycoproteins. As part of a tetraspanin-enriched microdomain (TEM), KAI1 inhibits tumor metastasis by negative regulation of Src. However, the underlying regulatory mechanism has not yet been fully elucidated. CUB-domain-containing protein 1 (CDCP1), which was previously known as tetraspanin-interacting protein in TEM, promoted metastasis via enhancement of Src activity. To better understand how KAI1 is involved in the negative regulation of Src, we here examined the function of KAI1 in CDCP1-mediated Src kinase activation and the consequences of this process, focusing on HIF-1 α and VEGF expression.</p> <p>Methods</p> <p>We used the human prostate cancer cell line PC3 which was devoid of KAI1 expression. Vector-transfected cells (PC3-GFP clone #8) and KAI1-expressing PC3 clones (PC3-KAI1 clone #5 and #6) were picked after stable transfection with KAI1 cDNA and selection in 800 <it>μ</it>g/ml G418. Protein levels were assessed by immunoblotting and VEGF reporter gene activity was measured by assaying luciferase activitiy. We followed tumor growth <it>in vivo </it>and immunohistochemistry was performed for detection of HIF-1, CDCP1, and VHL protein level.</p> <p>Results</p> <p>We demonstrated that Hypoxia-inducible factor 1α (HIF-1α) and VEGF expression were significantly inhibited by restoration of KAI1 in PC3 cells. In response to KAI1 expression, CDCP1-enhanced Src activation was down-regulated and the level of von Hippel-Lindau (VHL) protein was significantly increased. In an <it>in vivo </it>xenograft model, KAI1 inhibited the expression of CDCP1 and HIF-1α.</p> <p>Conclusions</p> <p>These novel observations may indicate that KAI1 exerts profound metastasis-suppressor activity in the tumor malignancy process via inhibition of CDCP1-mediated Src activation, followed by VHL-induced HIF-1α degradation and, ultimately, decreased VEGF expression.</p

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level.Comment: 24 pages, 5 figure

Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M&gt;70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0&lt;e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM