tbuckley/cabot-search huggingface dataset:
Cancer history is an independent risk factor for mortality in hospitalized COVID-19 patients: a propensity score-matched analysis
Authors: Yifan Meng, Wanrong Lu, Ensong Guo, Jia Liu, Bin Yang, Ping Wu, Shitong Lin, Ting Peng, Yu Fu, Fuxia Li, Zizhuo Wang, Yuan Li, Rourou Xiao, Chen Liu, Yuhan Huang, Funian Lu, Xue Wu, Lixin You, Ding Ma, Chaoyang Sun, Peng Wu, Gang Chen
Journal: Journal of Hematology & Oncology (2020)

Although research on the effects of comorbidities on coronavirus disease 2019 (COVID-19) patients is increasing, the risk of cancer history has not been evaluated for the mortality of patients with COVID-19.In this retrospective study, we included 3232 patients with pathogen-confirmed COVID-19 who were hospitalized between January 18th and March 27th, 2020, at Tongji Hospital in Wuhan, China. Propensity score matching was used to minimize selection bias.In total, 2665 patients with complete clinical outcomes were analyzed. The impacts of age, sex, and comorbidities were evaluated separately using binary logistic regression analysis. The results showed that age, sex, and cancer history are independent risk factors for mortality in hospitalized COVID-19 patients. COVID-19 patients with cancer exhibited a significant increase in mortality rate (29.4% vs. 10.2%, P < 0.0001). Furthermore, the clinical outcomes of patients with hematological malignancies were worse, with a mortality rate twice that of patients with solid tumors (50% vs. 26.1%). Importantly, cancer patients with complications had a significantly higher risk of poor outcomes. One hundred nine cancer patients were matched to noncancer controls in a 1:3 ratio by propensity score matching. After propensity score matching, the cancer patients still had a higher risk of mortality than the matched noncancer patients (odds ratio (OR) 2.98, 95% confidence interval (95% CI) 1.76-5.06). Additionally, elevations in ferritin, high-sensitivity C-reactive protein, erythrocyte sedimentation rate, procalcitonin, prothrombin time, interleukin-2 (IL-2) receptor, and interleukin-6 (IL-6) were observed in cancer patients.We evaluated prognostic factors with epidemiological analysis and highlighted a higher risk of mortality for cancer patients with COVID-19. Importantly, cancer history was the only independent risk factor for COVID-19 among common comorbidities, while other comorbidities may act through other factors. Moreover, several laboratory parameters were significantly different between cancer patients and matched noncancer patients, which may indicate specific immune and inflammatory reactions in COVID-19 patients with cancer.
NAFLD — sounding the alarm on a silent epidemic
Authors: Jeffrey V. Lazarus, Massimo Colombo, Helena Cortez-Pinto, Terry T. -K. Huang, Veronica Miller, Michael Ninburg, Jörn M. Schattenberg, Lynn Seim, Vincent W. S. Wong, Shira Zelber-Sagi
Journal: Nature Reviews Gastroenterology & Hepatology (2020)
SAT0011 COMBINED INHIBITION OF AUTOPHAGY AND GLUTAMINE METABOLISM SUPPRESSES CELL GROWTH OF RA SYNOVIOCYTES AND AMELIORATES ARTHRITIS IN SKG MICE
Authors: I. Naka, J. Saegusa, K. Uto, Y. Yamamoto, Y. Ichise, H. Yamada, K. Akashi, Y. Ueda, A. Onishi, T. Okano, S. Takahashi, S. Sendo, A. Morinobu
Journal: Annals of the Rheumatic Diseases (2020)

Background: Immunometabolism is now recognaized to be crucial in the pathogenesis of rheumatoid arthritis (RA). We have recently shown that the expression of glutaminase 1 (GLS1), a key enzyme in glutaminolysis, is upregulated in fibroblast-like synoviocytes from RA patients (RA-FLS) and that GLS1 inhibition suppresses RA-FLS proliferation (1). However, glutaminolysis has been known to suppress autophagy by activating mTORC1 or counteracting ROS production (2). Given the possibility of autophagy upregulation following glutamiolysis inhibition, therapies targeting both autophagy and glutaminolysis may be more effective in suppressing cell growth of RA-FLS, yet the relation between glutaminolysis and autophagy in RA-FLS has not been investigated. Objectives: To examine the effects of inhibiting both glutaminolysis and autophagy on RA-FLS and autoimmune arthritis in SKG mice. Methods: GLS1 inhibitor, compound 968 (C968), was used to suppress glutaminolysis, and Chloroquine (CQ) was used to inhibit autophagy. To detect autophagy, the expression of ATG5 and LC3B was measured by real-time PCR and the production of LC3-II was analyzed by Western blotting. The formation of autophagic vacuoles was identified by immunfluorescense. Cell growth was evaluated by BrdU assay. Apoptosis was analyzed by flow cytometry staining with Annexin V-FITC and PI. C968 and CQ were administered subcutaneously to Zymosan A-injected SKG mice. Results: C968 upregulated the expression of ATG5 and LC3B, and increased the protein level of LC3-II in RA-FLS. C968 also facilitated autophagosome formation. These results suggested that inhibition of glutaminolysis promoted autophagy in RA-FLS. The combined treatment with C968 and CQ significantly suppressed cell proliferation of RA-FLS more strongly than did C968 or CQ alone. In addition, C968 combined with CQ increased the apoptosis rate, whereas either C968 or CQ alone did not. Furthermore, combination of C968 and CQ significantly attenuated the degree of arthritis in SKG mice, while C968 or CQ monotherapy did not (Figure). Conclusion: The GLS1 inhibitor C968 promotes autophagy in RA-FLS. C968 in combination with CQ reduces proliferation and enhances apoptosis in RA-FLS, and ameliorates the arthritis in SKG mice. Suppressing C968-induced autophagy may be a promising therapy for arthritis. References: [1] Takahashi S., et al. Arthritis Res Ther. 2017 Apr 11;19(1):76. [2] Villar VH., et al. Autophagy. 2015;11(8):1198-208. Acknowledgments : None Disclosure of Interests: None declared
Abstract PR09: A systematic approach to create patient-derived models of rare tumors
Authors: Yuen-Yi Tseng, Paula Keskula, Rebecca Deasy, Andrew Hong, Priya Chatterji, Francisca Vazquez, Adam Bass, Barbara Van Hare, David Sandak, Keith Ligon, Jesse Boehm
Journal: Cancer Research (2020)

Abstract Precision cancer medicine is based on the ability to predict the dependencies of a given tumor from its molecular makeup. Despite successes in multiple common cancers, such prediction remains challenging for the majority of rare and understudied tumors, given the absence of laboratory model systems in which to discover and/or validate therapeutic hypotheses. Here, we describe our efforts to address this challenge systematically with the ultimate goal of making it possible to learn how to predict ex vivo growth requirements for cancer samples based on technical, clinical, and genomic properties of the starting tumor material. Over the last 5 years, we have processed nearly 2,000 tumor biospecimens and created over 375 genomically confirmed patient-derived cell lines, organoids, and neurosphere cultures, with &amp;gt;10% of these representing rare cancers. To make this possible, we have implemented three key workflows including (1) direct-to-patient sample sourcing, (2) a tissue cryopreservation and genomic credentialing system to ensure quality prior to model creation, and (3) a systematic empirical approach to screening rich media and variations on organoid technologies ex vivo (HYBRID). We have begun performing genome-wide CRISPR viability screens in these cultures as part of our larger activities to generate a systematic laboratory-based functional map of cancer dependencies (a “Cancer Dependency Map”). The novel organoid, spheroid, and cell line models created as part of this effort are being made publicly available to the scientific community. Looking ahead, as the barriers to culturing rare tumors are overcome, we expect that preclinical functional genomics data will be useful for difficult-to-treat tumors without existing molecularly guided standard-of-care regimens. This abstract is also being presented as Poster A06. Citation Format: Yuen-Yi Tseng, Paula Keskula, Rebecca Deasy, Andrew Hong, Priya Chatterji, Francisca Vazquez, Adam Bass, Barbara Van Hare, David Sandak, Keith Ligon, Jesse Boehm. A systematic approach to create patient-derived models of rare tumors [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR09.
Reply to Epelbaum: Standards and Stereotypes in COVID-19
Authors: David R. Ziehr, Jehan Alladina, Camille R. Petri, Jason H. Maley, Ari Moskowitz, Benjamin D. Medoff, Kathryn A. Hibbert, B. Taylor Thompson, C. Corey Hardin
Journal: American Journal of Respiratory and Critical Care Medicine (2020)
Perirectal Infections in Acute Leukemia
Authors: Scott G. Barnes, Fred R. Sattler, James O. Ballard
Journal: Annals of Internal Medicine (2020)

Abstract During a 6-year period, 16 (7.9%) of 202 patients with acute leukemia of both the lymphocytic and nonlymphocytic types developed perirectal infections. All patients were febrile and severe...
Tuberculosis in the time of COVID-19: quality of life and digital innovation
Authors: Dina Visca, Simon Tiberi, Emanuele Pontali, Antonio Spanevello, Giovanni Battista Migliori
Journal: European Respiratory Journal (2020)

<b>COVID-19 affects healthy individuals, patients and healthcare professionals, as well as tuberculosis services. The importance of digital technologies and the impact on quality of life are discussed.</b>https://bit.ly/2U8nA0h
Impact of Splenomegaly on Outcomes of Fully Matched Sibling Bone Marrow Transplant Among Children with Low Risk Thalassemia
Authors: Stalin Ramprakash, Rajat Agarwal, Rakesh Dhanya, Priya Marwah, Rajpreet Soni, Naila Yaqub, Fatima Itrat, Lallindra Gooneratne, Senani Williams, Sadaf Khalid, Santanu Sen, Lawrence Faulkner
Journal: Blood (2017)
Abstract A05: Nomograms based on the SEER database for predicting the prognosis of pulmonary large-cell neuroendocrine carcinoma: A population-based STROBE cohort study
Authors: Hong-fen Wu
Journal: Cancer Research (2020)

Abstract Background: This work aimed at the development and validation of nomograms for predicting patient survival cancer-specific survival (CSS) and overall survival (OS) in the context of pulmonary large-cell neuroendocrine carcinoma (LCNEC). Material and Methods: Based on the SEER database, patients were selected who received diagnosis between the period 2004 and 2014, through the Surveillance, Epidemiology, and End Results (SEER) database. Variables were subjected to univariate and multivariate studies, performed through Cox’s Proportional Hazards Regression model. The 3- and 5-year CSS and OS were predicted based on a nomogram constructed from prognostic factors that were independent. The accuracy of the nomogram was evaluated using discrimination and calibration plots. Results: From 1,837 eligible patients based on the SEER database, assignment of 1,276 patients was done to the training set, while that of 561 patients was done to the validation set. Multivariate analyses revealed that age, laterality, tumor size, N stage, M stage, surgery, and chemotherapy were significant prognostic factors for CSS, while those of OS were age, laterality, tumor size, surgery, N and M stages, chemotherapy, and radiation. The concordance index (C-index) for CSS was 0.781 (95% CI: 0.766-0.796) and 0.754 (95% CI: 0.730-0.778) for the internal and external validations, respectively. The values for OS were 0.791 (95%CI: 0.776-0.806) and 0.775 (95% CI: 0.751-0.799), respectively. For the training and the validation sets, discrimination in terms of prediction of OS and CSS was better in the nomograms against the SEER summary stage as well as AJCC TNM staging systems (6th edition) (P&amp;lt;0.001). The CSS and OS predicted by the nomograms closely corresponded to actual observation as shown by calibration plots. Conclusion: Prediction of the 3- and 5-year CSS and OS of patients with pulmonary LCNEC by nomograms with higher accuracy than existing staging models was demonstrated. Note: This abstract was not presented at the conference. Citation Format: Hong-fen Wu. Nomograms based on the SEER database for predicting the prognosis of pulmonary large-cell neuroendocrine carcinoma: A population-based STROBE cohort study [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A05.
Better Biomarkers for Surgeons Treating Cancer
Authors: David L. Bartlett
Journal: JAMA Surgery (2020)

Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA Surgery HomeNew OnlineCurrent IssueFor Authors Podcast Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA Surgery journal
Neither black nor white: do altered intestinal microbiota reflect chronic liver disease severity?
Authors: Felix Goeser, Philipp Münch, Till Robin Lesker, Philipp Ludwig Lutz, Benjamin Krämer, Dominik J Kaczmarek, Claudia Finnemann, Hans Dieter Nischalke, Robert Geffers, Marijo Parcina, Alice McHardy, Christian Strassburg, Achim Hoerauf, Jacob Nattermann, Isabelle Bekeredjian-Ding, Ulrich Spengler
Journal: Gut (2020)

In their outstanding study, Wei et al 1 compared the intestinal microbiota (IM) of well-defined autoimmune hepatitis (AIH) patients to healthy controls. They reported significantly reduced IM alpha diversity and disparate IM compositional heterogeneity (beta diversity) with enrichment of Streptococcus , Veillonella , Klebsiella and Lactobacillus in AIH. The excellent achievement of this study is to have characterised the IM of untreated patients with AIH. However, differentiation between IM changes caused by AIH in particular and by chronic liver disease (CLD) in general was not possible because this study lacked a control group with CLD other than AIH.

In a pilot study, we analysed the IM of patients with CLD of mixed aetiology in comparison to healthy controls to clarify alterations across different stages of CLD (table 1 and online supplementary data). In contrast to the study by Wei et al , patients with recent intake of antibiotics were excluded. Additionally, only patients on proton pump inhibitors (PPIs), which are frequently taken by patients with CLD, were included to avoid a bias due to mixed PPI use, because PPI can alter the IM, in particular, the abundance of Veillonellaceae and Streptococcaceae.2 Based on investigations of normalised relative reads (n-RR) per IM taxon as well as IM alpha-diversity and beta-diversity analyses, we detected Veillonella …
Abstract PR10: A versatile ES cell-based melanoma mouse modeling platform
Authors: Florian A. Karreth
Journal: Cancer Research (2020)

Abstract The cumbersome and time-consuming process of generating new mouse strains and multiallelic experimental animals often hinders the use of genetically engineered mouse models (GEMM) in cancer research. Here, we describe the development and validation of an embryonic stem cell (ESC)-GEMM platform for rapid modeling of melanoma in mice. The platform incorporates twelve clinically relevant genotypes composed of combinations of four driver alleles (LSL-BrafV600E, LSL-NrasQ61R, PtenFlox, Cdkn2aFlox) and regulatory alleles to spatiotemporally control the perturbation of genes of interest. The ESCs produce high-contribution chimeras, which recapitulate the melanoma phenotypes of conventionally bred mice. Using the ESC-GEMM platform to modulate Pten expression in melanocytes in vivo, we highlighted the utility and advantages of gene depletion by CRISPR-Cas9, RNAi, or conditional knockout for melanoma modeling. Moreover, complementary genetic methods demonstrated the impact of Pten restoration on the prevention and maintenance of Pten-deficient melanomas. Finally, we showed that chimera-derived melanoma cell lines retain regulatory allele competency and are a powerful resource to complement ESC-GEMM chimera experiments in vitro and in syngeneic grafts in vivo. Thus, when combined with sophisticated genetic tools, the ESC-GEMM platform enables rapid, high-throughput, and versatile studies aimed at addressing outstanding questions in melanoma biology. This abstract is also being presented as Poster B45. Citation Format: Florian A. Karreth. A versatile ES cell-based melanoma mouse modeling platform [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR10.
Abstract A29: Dissecting the mechanisms of senescence immune surveillance in liver cancer
Authors: Hsuan-An Chen, Direna Alonso-Curbelo, Yu-Jui Ho, John P. Morris, Shauna Houlihan, Ryan Smolkin, Wei Luan, Ronald C. Hendrickson, Scott W. Lowe
Journal: Cancer Research (2020)

Abstract Senescence is a cell cycle arrest program that limits the expansion of damaged cells and can trigger antitumor immunity that leads to their elimination in vivo, serving as a potent barrier to tumorigenesis. However, during tumor initiation, the effective clearance of senescent cells is compromised, warranting a deeper mechanistic understanding of this process. To define the critical immunomodulatory factors mediating senescence immune surveillance and how these mechanisms are bypassed during cancer development and progression, we exploited a genetic approach in which liver tumor cells can be triggered to senesce by restoration of tumor suppressor p53. p53 reactivation triggers cytostatic response in vitro, yet it drives robust regression of established liver tumors in immunocompetent mice. Profiling of the immune landscape upon senescence induction revealed that there is an accumulation of CD8 and CD4 T cells in the tumor microenvironment. Consistently, immune cell blockade through depleting antibodies blunts tumor regression, indicating a key role of adaptive immunity in this process. To gain mechanistic insight into how senescent cells are recognized by the immune system, RNA-seq and mass spectrometry were conducted on both proliferating and senescent tumor cells and revealed several senescence-enriched cell surface factors related to epithelial-immune cell interactions and MHC-I presentation. Ongoing work aims to functionally interrogate the role of these senescence-induced factors as novel senescence surveillance effectors. Our research will increase the current knowledge of the strategies to trigger senescence in advanced cancers that can restore immune surveillance programs lost during the course of tumor evolution. Citation Format: Hsuan-An Chen, Direna Alonso-Curbelo, Yu-Jui Ho, John P. Morris IV, Shauna Houlihan, Ryan Smolkin, Wei Luan, Ronald C. Hendrickson, Scott W. Lowe. Dissecting the mechanisms of senescence immune surveillance in liver cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A29.
Abstract A08: Modeling melanomagenesis
Authors: Hyeongsun Moon, Leanne Donahue, Andrew C. White
Journal: Cancer Research (2020)

Abstract Despite recent advances in therapy, cutaneous melanoma remains a deadly form of skin cancer. Ultraviolet radiation is a known risk factor that can be reduced by the use of sunscreen; nevertheless, melanoma incidence continues to rise. Determining how a cell that contains all the mutations required for cancer resists forming a tumor could suggest novel means of prevention. Conversely, understanding an identical cancer cell of origin that has switched to a proliferative expansion state can provide invaluable insight into tumor initiation. We have generated a method of inducing melanoma from melanocyte stem cells in a spatially specific manner by altering the exterior environment, in the context of a previously established genetically engineered mouse model of melanoma. Specifically, exposure to ultraviolet radiation B can provide a proinflammatory microenvironment that stimulates this switch from a quiescent cancer cell of origin to a proliferative cancer cell. Moreover, this model shows tumor development from the interfollicular epidermis, similar to human melanoma initiation and progression. This represents an evolution from previous mouse models of melanoma and presents a new method that can be exploited for stage-specific precision targeting for both initiation prevention and progression intervention. Citation Format: Hyeongsun Moon, Leanne Donahue, Andrew C. White. Modeling melanomagenesis [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A08.
A study of the prevalence and type of anemia in lymphoid malignancies
Authors: J. Ghosh, L. Kumar, R. Saxena, V. Raina, A. Sharma, R. Gupta, S. Vivekanandhan, V. Sreenivas, R. Verma
Journal: Journal of Clinical Oncology (2009)

e19556 Background: Anemia is a common and serious problem in patients with lymphoid malignancy. Hence there was need to analyze the prevalence of anemia in our patient population and evaluate its cause for optimal management. Methods: Newly diagnosed patients of lymphoid malignancy- non Hodgkins lymphoma (NHL), Hodgkins lymphoma (HL), and chronic lymphocytic leukemia (CLL) aged more than 15 years without renal failure and who had not received blood transfusion, iron, folic acid or vitamin B complex in the last 2 weeks were analyzed. 316 patients were screened for the prevalence of anemia. Of the anemic patients (hemoglobin &lt;11gm/dl), 46 were studied for the type of anemia. These patients underwent the following investigations -complete hemogram with RBC indices, hematocrit, reticulocyte count, peripheral blood smear (PBS) examination, direct Coombs test (DCT), bone marrow (BM) aspiration and biopsy, S. iron (SI), S. ferritin (SF), total iron binding capacity (TIBC), percentage saturation (psat), S. Vitamin B12 and Folic acid levels. Anemia was categorized as due to either autoimmune hemolytic anemia (AIHA)-DCT positive with evidence of hemolysis on PBS, B12 and folate deficiency (&lt;200 pgm/ml and &lt; 4ngm/ml respectively), iron deficiency anemia (IDA)- psat &lt;20% and SF315μgm/dl, anemia of chronic disease (ACD)-psat200μgm/L, a combination of IDA and ACD -psat &lt;20%, SF -30–200 with TIBC ≤315 μgm/dl. Results: The prevalence of anemia in patients with lymphoid malignancy was 42.41% (134 /316, 95% CI-36.96% -47.85%). It was multifactorial in 39.13% (18/46) patients. ACD was the most common cause of anemia present in 71.74% (33/46) patients. This was followed by nutritional anemia (iron,B12 and folate deficiency) in 47.83% (22/46) and AIHA in 10.87% (5/46) of patients. Conclusions: Although anemia of chronic disease is the most common cause of anemia in patients with lymphoid malignancy, it is multifactorial in a large number of patients and hence it is important to rule out other causes of anemia like nutritional and AIHA in these patients. No significant financial relationships to disclose.