tbuckley/cabot-search huggingface dataset:
Correspondence on ‘Immunogenicity and safety of anti-SARS-CoV-2 mRNA vaccines in patients with chronic inflammatory conditions and immunosuppressive therapy in a monocentric cohort’
Authors: Jesse Veenstra, Jie Wang, Kathleen McKinnon-Maksimowicz, Tingting Liu, Bobby Zuniga, Iltefat Hamzavi, Li Zhou, Qing-Sheng Mi
Journal: Annals of the Rheumatic Diseases (2021)

<h3>Background and Objectives.</h3> Tramadol and metoclopramide have a local anesthetic effect similar to lidocaine following intradermal injection. When metoclopramide was retained in the venous system for 1 minute, it was found to be as effective as lidocaine in reducing propofol injection pain. Using this metoclopramide model, the effects of tramadol in reducing pain on propofol injection was investigated. <h3>Methods.</h3> One hundred five patients were randomly allocated to receive 50 mg tramadol (group T), 60 mg lidocaine (group L), or normal saline (group NS) as pretreatment to reduce pain on propofol injection. Following venous occlusion with a tourniquet (70 mm Hg), one of the drugs was intravenously administered. Venous retention of the drug was maintained for 1 minute. Immediately after the tourniquet release, intravenous injection of 100 mg propofol (10 mL) at a rate of 0.5 mL/s followed. Pain assessment was made after each injection. <h3>Results.</h3> Transient minor injection pain and local skin reactions were significantly greater with tramadol than with lidocaine (<i>P</i> &lt; .05). Both tramadol and lidocaine significantly reduced the incidence and intensity of propofol injection pain when compared with normal saline (<i>P</i> &lt; .05). <h3>Conclusions.</h3> Using 1-minute retention in veins, both tramadol and lidocaine significantly reduced propofol injection pain. A local anesthetic activity is postulated.
Endothelial Cell-Selective Adhesion Molecule (ESAM) Plays Important Roles in the Adult-Type Hemoglobin Synthesis during Fetal Erythropoiesis
Authors: Tomoaki Ueda, Takafumi Yokota, Yasuhiro Shingai, Yukiko Doi, Tomohiko Ishibashi, Takao Sudo, Akira Tanimura, Michiko Ichii, Sachiko Ezoe, Hirohiko Shibayama, Kenji Oritani, Yuzuru Kanakura
Journal: Blood (2017)
Long-term follow-up of recovered MPN patients with COVID-19
Authors: Tiziano Barbui, Alessandra Iurlo, Arianna Masciulli, Alessandra Carobbio, Arianna Ghirardi, Giuseppe Rossi, Claire Harrison, Alberto Alvarez-Larran, Elena Maria Elli, Jean-Jaques Kiladjian, Mercedes Gasior Kabat, Alberto Marin Sanchez, Francesca Palandri, Marcio Miguel Andrade-Campos, Alessandro Maria Vannucchi, Gonzalo Carreno-Tarragona, Petros Papadopoulos, Keina Quiroz Cervantes, Maria Angeles Foncillas, Maria Laura Fox, Miguel Sagues Serrano, Elisa Rumi, Santiago Osorio, Giulia Benevolo, Andrea Patriarca, Begona Navas Elorza, Valentin Garcia-Gutierrez, Elena Magro Mazo, Francesca Lunghi, Massimiliano Bonifacio, Valerio De Stefano, Juan Carlos Hernandez-Boluda, Emma Lopez Abadia, Anna Angona, Blanca Xicoy Cirici, Marco Ruggeri, Steffen Koschmieder, Marta Anna Sobas, Beatriz Cuevas, Daniele Cattaneo, Rosa Daffini, Marta Bellini, Natalia Curto-Garcia, Marta Garrote, Fabrizio Cavalca, Lina Benajiba, Beatriz Bellosillo, Paola Guglielmelli, Oscar Borsani, Silvia Betti, Silvia Salmoiraghi, Alessandro Rambaldi
Journal: Blood Cancer Journal (2021)
EMBR-01. CLASS I HDAC INHIBITORS AND PLK1 INHIBITORS SYNERGIZE IN <i>MYC</i>-AMPLIFIED MEDULLOBLASTOMA
Authors: Gintvile Valinciute, Jonas Ecker, Florian Selt, Thomas Hielscher, Christin Schmidt, Romain Sigaud, Johannes Ridinger, Charlotte Gatzweiler, Daniel Picard, Sina Oppermann, Mirjam Blattner-Johnson, David T W Jones, Ina Oehme, Marcel Kool, Marc Remke, Stefan M Pfister, Olaf Witt, Till Milde
Journal: Neuro-Oncology (2021)

Abstract Background Medulloblastoma (MB) is one of the most common malignant pediatric CNS tumors. Patients with Group 3 MBs harboring MYC amplification exhibit low survival rates. Surviving patients suffer from therapy-induced sequelae, which calls for new targeted therapy strategies. We and others have previously shown the sensitivity of MYC-amplified MB to class I histone deacetylase (HDAC) inhibition. After demonstrating that the MYC target gene PLK1 is significantly downregulated upon class I HDACi treatment, we hypothesized that inhibition of both HDACs and PLK1 could have synergistic effects. Methods Cell metabolic activity changes upon HDAC and PLK1 inhibitor treatment were measured in MYC-amplified and non-amplified MB cell lines, as well as in an additional MYC-inducible cell line. The interaction effect of both inhibitors was determined by computation of the combination index (CI) using the Chou-Talalay method. Results were validated assessing cell viability, cell cycle, and apoptosis induction. Transcription profile changes after combination treatment were evaluated. Results MYC-amplified MB cell lines were more sensitive than non-amplified cell lines to PLK1i treatment, showing IC50 in clinically achievable concentration ranges. Inhibition of class I HDACs and PLK1 synergistically reduced cell metabolic activity in lower concentrations in MYC-amplified compared to non-amplified MB cell lines. We also observed a significant loss of viability and cells in G1 phase, as well as induction of apoptosis after combination treatment in MYC-amplified cells. MYC target gene sets were significantly downregulated in the MYC-amplified cell line HD-MB03 after treatment with combination. We demonstrated reduction of MYC protein levels upon PLK1i treatment. In vivo evaluation of combination treatment using orthotopic Group 3 MYC-amplified MB PDX models is ongoing. Conclusion Our data suggest that MYC-amplification is a predictive marker for PLK1i treatment in MB. The combination of HDACi and PLKi could be a candidate therapy for future clinical trials for MYC-amplified group 3 MB.
A phase 3, double-blind, randomized study of pamiparib versus placebo as maintenance therapy in patients with inoperable, locally advanced, or metastatic gastric cancer that responded to platinum-based first-line chemotherapy - Trial in progress
Authors: F. Ciardiello, Y. Bang, J. Bendell, A. Cervantes, R. Brachmann, Y. Zhang, M. Raponi, H. Farin, L. Shen
Journal: Annals of Oncology (2018)

Introduction: Gastric cancer is the fifth most common cancer and is the third leading cause of cancer deaths worldwide. A subset of gastric cancers exhibit platinum sensitivity and genomic instability that is characteristic of homologous recombination deficiency (HRD). Poly(ADP-ribose) polymerase proteins 1 and 2 (PARP1/2) are involved in DNA damage repair, and their inhibition is cytotoxic for cells with HRD. Pamiparib (previously known as BGB-290) is a selective PARP1/2 inhibitor that crosses the blood-brain barrier, has shown potent DNA–PARP trapping, and has demonstrated robust antitumor activity in preclinical models. In early phase clinical studies (NCT02361723; NCT03333915), pamiparib was generally well tolerated and showed promising antitumor activity. These studies also established 60 mg orally twice daily as the recommended pivotal dose. Methods: The purpose of this double-blind, placebo-controlled, randomized, multicenter Phase 3 study (NCT03427814) conducted in Asia, Australia, Europe, and North America is to compare the efficacy, safety, and tolerability of pamiparib with placebo as maintenance therapy in ∼540 patients with advanced gastric cancer who have responded to first-line, platinum-based chemotherapy. Patients who are ≤8 weeks after their last platinum dose of first-line chemotherapy will be randomized 1:1 to receive either pamiparib 60 mg twice daily or placebo in 28-day cycles. Patient randomization will be stratified by genomic loss of heterozygosity status (ie, high versus low), region, and ECOG status. Radiologic assessments will be centrally evaluated per RECIST every 8 weeks after first dose. Safety will be assessed on Day 1 of each cycle, and Day 15 of Cycles 1 and 2, and as needed. Blood samples will be collected at various time points to determine the pharmacokinetics of pamiparib in inoperable, locally advanced gastric cancer patients. The primary endpoint is progression-free survival; key secondary endpoints include safety/tolerability, overall survival, objective response rates, time and duration of response, and time to second subsequent treatment. Correlative biomarker analyses in tumor tissues and blood will be performed.
Classification of molecular subtypes of high-grade serous ovarian cancer by MALDI-Imaging.
Authors: Wanja Nikolai Kassuhn, Oliver Klein, Silvia Darb-Esfahani, Hedwig Lammert, Sylwia Handzik, Eliane T Taube, Wolfgang D Schmitt, Oliver Dorigo, David Horst, Carlotta Keunecke, Felix Dreher, Joshy George, David Bowtell, Michael Hummel, Jalid Sehouli, Nils Blüthgen, Hagen Kulbe, Elena Ioana Braicu
Journal: Journal of Clinical Oncology (2021)

e17544 Background: High-grade serous ovarian cancer (HGSOC) can be separated by gene expression profiling into four molecular subtypes with clear correlation of the clinical outcome. However, these gene signatures have not been implemented in clinical practice to stratify patients for targeted therapy. This is mainly due to a lack of easy, cost-effective and reproducible methods, as well as the high heterogeneity of HGSOC. Hence, we aimed to examine the potential of unsupervised matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients, which might benefit from targeted therapeutic strategies. Methods: Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS, a novel technology to identify distinct mass profiles on the same paraffin-embedded tissue sections paired with machine learning algorithms to identify HGSOC subtypes by proteomic signature. Finally, we devised a novel strategy to annotate spectra of stromal origin. Results: We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma associated spectra provides tangible improvements to classification quality (AUC = 0.988). False discovery rates (FDR) were reduced from 10.2% to 8.0%. Finally, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999, FDR &lt; 1.0%). Conclusions: Here, we present a concept integrating MALDI-IMS with machine learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for targeted therapies.
Correction: Quantifying Potential Tradeoffs in COVID-19 Vaccine Deployment
Journal: Annals of Internal Medicine (2021)

Corrections20 April 2021Correction: Quantifying Potential Tradeoffs in COVID-19 Vaccine DeploymentFREEThis correction concerns the following article:LettersApr 2021Speed Versus Efficacy: Quantifying Potential Tradeoffs in COVID-19 Vaccine DeploymentFREEA. David Paltiel, PhD, Amy Zheng, BA, and Jason L. Schwartz, PhDA. David Paltiel, PhDYale School of Public Health, New Haven, Connecticut, Amy Zheng, BAHarvard Medical School, Boston, Massachusetts, and Jason L. Schwartz, PhDYale School of Public Health, New Haven, ConnecticutAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L21-0233 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail The April 2021 print edition of Annals contains a publisher error. An article in the issue, which was published online on 5 January 2021 (1), inadvertently included an individual in the author byline who was not an author. The error solely appears in the print version of the article. The online version is correct.Reference1. Paltiel AD, Zheng A, Schwartz JL. Speed versus efficacy: quantifying potential tradeoffs in COVID-19 vaccine deployment. Ann Intern Med. 2021;174:568-570. [PMID: 33395345] doi:10.7326/M20-7866 LinkGoogle Scholar Comments 0 Comments Sign In to Submit A Comment Author, Article, and Disclosure InformationThis article was published at Annals.org on 20 April 2021. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoSpeed Versus Efficacy: Quantifying Potential Tradeoffs in COVID-19 Vaccine Deployment A. David Paltiel , Amy Zheng , and Jason L. Schwartz Metrics May 2021Volume 174, Issue 5 Page: 736 ePublished: 20 April 2021 Issue Published: May 2021 Copyright & PermissionsCopyright © 2021 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Phase 2 study of retifanlimab (INCMGA00012) in patients (pts) with selected solid tumors (POD1UM-203).
Authors: Michele Maio, Michael Schenker, Jacques Medioni, Slawomir Mandziuk, Margarita Majem, Gwenaelle Gravis, Mark J. Cornfeld, Sulabha Ranganathan, Yubing Yao, Howard Su-Hau Yeh, Tibor Csőszi
Journal: Journal of Clinical Oncology (2021)

2571 Background: Checkpoint inhibitors (CPIs) are an effective treatment (tx) for many tumor types. Retifanlimab, an investigational humanized anti–PD-1 monoclonal antibody, has shown safety, pharmacology, and clinical activity consistent with the class. POD1UM-203 (NCT03679767) assessed efficacy and safety of retifanlimab in pts with selected solid tumors where CPI monotherapy is highly active. Methods: Eligible pts (≥18 y) had tx-naïve metastatic non-small cell lung cancer (NSCLC) with high PD-L1 expression (tumor proportion score ≥50%), cisplatin ineligible locally-advanced/metastatic urothelial cancer (UC) with PD-L1 expression (combined positive score ≥10%), unresectable/metastatic melanoma, or tx-naïve locally advanced/metastatic clear-cell renal cell carcinoma (RCC). Measurable disease (RECIST v1.1) was required. ECOG PS &gt;1 and prior PD-1/PD-L1 directed tx were exclusions. Retifanlimab was administered as an IV infusion at 500 mg every 4 wks over 30 min. Primary endpoint was investigator-assessed objective response rate (ORR). Secondary endpoints were duration of response (DOR), disease control rate (DCR), progression-free survival, overall survival, safety, and pharmacokinetics. Results: A total of 121 pts (35 melanoma, 23 NSCLC, 29 UC, 34 RCC) received ≥1 dose of retifanlimab and were included in the analyses. Median duration of tx was 169 d (range, 1–442). The efficacy cut-off for the primary analysis occurred once all pts had been followed for at least 6 mo from the time of initial tx. Confirmed RECIST v1.1 responses were observed in all tumor types (Table) and were consistent with published ORR for other CPIs; median DOR was not reached for any tumor cohort and tx was ongoing at the time of data cutoff for 17, 11, 9, and 15 pts with melanoma, NSCLC, UC, and RCC, respectively. The most common tx-emergent AEs (TEAEs, &gt;10% incidence) were asthenia (17.4%), arthralgia (14.9%), decreased appetite (14.0%), pruritus (12.4%), rash (10.7%), and urinary tract infection (10.7%); majority of TEAEs were low grade (≤ grade 2) and none led to tx discontinuation. Immune-related AEs occurred in 23 pts (19.0%), most common (&gt;1% incidence) were hypothyroidism (7.4%), rash (4.1%), hyperthyroidism (2.5%), and pruritus (1.7%). Immune-related AEs led to dose delay in 5 pts (4.1%), but none led to tx discontinuation and/or dose interruption. Conclusions: Retifanlimab demonstrated antitumor activity and was generally well-tolerated in pts with melanoma, NSCLC, UC, or RCC comparable with approved CPIs for these tumor types. These results support ongoing further development of retifanlimab. Clinical trial information: NCT03679767. [Table: see text]
Efficacy and safety of zanubrutinib versus rituximab-based chemoimmunotherapy in Waldenström macroglobulinemia (WM): Matching-adjusted indirect comparisons.
Authors: Jorge J. Castillo, Keri Yang, Rongzhe Liu, Yu Wang, Aileen Cohen, Todd M. Zimmerman, Qian Zhao, Xin Gao, Boxiong Tang
Journal: Journal of Clinical Oncology (2021)

7559 Background: Given a lack of WM randomized trials directly comparing zanubrutinib with chemoimmunotherapy, this study aimed to indirectly compare zanubrutinib with bendamustine-rituximab (BR) and with dexamethasone-rituximab-cyclophosphamide (DRC) separately through matching-adjusted indirect comparisons (MAIC). Methods: MAIC were conducted to re-weight the individual data of 102 WM patients (83 relapsed/refractory [R/R] and 19 treatment-naïve [TN]) treated with zanubrutinib in the ASPEN trial (NCT03053440) so that the weighted average baseline characteristics of patients treated with zanubrutinib matched those of 71 R/R patients treated with BR, and 72 TN patients treated with DRC separately. Matching variables for MAIC with BR included age, prior lines of therapy, IgM concentration, International Prognostic Scoring System for WM score, and extramedullary disease (EMD); and for MAIC with DRC included age, platelet count, hemoglobin concentration, and EMD. Kaplan-Meier curves of progression-free survival (PFS) and overall survival (OS) of comparators were digitized to re-create patient-level data. Comparisons of survival and adverse event incidence between treatments were conducted using Cox proportional hazards models and modified Poisson models. Results: Compared to DRC, zanubrutinib was associated with longer PFS (hazard ratio [HR]: 0.39 [95% confidence interval 0.18-0.82] and 0.35 [0.14-0.86] pre- and post-matching, respectively) and longer OS (HR: 0.56 [0.20-1.53] and 0.47 [0.14-1.62] pre- and post-matching, respectively), and insignificantly higher incidences of neutropenia (risk ratio [RR]: 1.63 [0.71-3.77] and 1.47 [0.58-3.74] pre- and post-matching, respectively). Compared to BR, zanubrutinib was associated with longer PFS (HR: 0.32 [0.15-0.69] and 0.37 [0.15-0.91] pre- and post-matching, respectively), longer OS (HR: 0.31 [0.12, 0.80] and 0.29 [0.10-0.85] pre- and post-matching, respectively), lower incidences of neutropenia (RR: 0.45 [0.26-0.78] and 0.50 [0.27-0.91] pre- and post-matching, respectively) and lower incidences of pneumonia (RR: 0.18 [0.02-1.55] and 0.26 [0.03-2.28] pre- and post-matching, respectively). Conclusions: Zanubrutinib demonstrated longer PFS than DRC, and longer PFS and OS than BR in WM, before and after matching adjustment based on patient characteristics. [Table: see text]
Prediction of adenocarcinoma among other subtypes of lung cancer from CT using deep learning.
Authors: Noah Waterfield Price, Sam Janes, Fergus Gleeson, Pierre P. Massion, Jonathan Lehman
Journal: Journal of Clinical Oncology (2021)

3057 Background: Determination of histological subtype is a crucial step in the management of patients with lung cancer as it informs prognosis and management. The identification of adenocarcinoma (AC) is particularly important with new targeted treatments becoming available. Although the gold standard for diagnosing histological subtype is pathological analysis of tissue samples, interventions can present a risk of complication. Imaging-based, computational approaches to distinguishing malignant from benign lesions have shown promising results. A similar approach may also be applied to determining histological subtype, which could provide an early, non-invasive alternative or complimentary method to biopsy. Here, we investigate an imaging and machine learning method to predict the subtype of a malignant lung lesion. Methods: A dataset of 1493 primary lung cancer patients was collected, of which 943 were diagnosed with AC. The histological subtypes of the non-AC patients were, squamous-cell carcinoma (158), large-cell carcinoma (69), small-cell carcinoma (33), other subtypes (27), or unreported non-AC subtype (253). This consists of retrospectively collected CT images and demographic data from both screening and clinical settings, across 41 academic and community centres from the USA (35 centres), and Europe (6 centres). All patients included were aged ≥ 18 with no history of cancer in the last 5 years. Each CT was manually curated. Given a CT-image of a lung nodule, a Convolutional Neural Network (CNN) was trained to classify nodules as AC or non-AC, using 8-fold cross-validation. A logistic-regression model based on clinical parameters was also trained using the same data and cross-validation. Classification performance was evaluated using the Area-Under-the-ROC-Curve (AUC), sensitivity, and specificity. Confidence intervals and P values were calculated by nonparametric bootstrapping. Results: The median age of AC patients was 66 yr (non-AC 67 yr) and 62.3% of them were male (non-AC 57.8%). The median pack years for AC patients was 38.4 p.yr (non-AC 50.0 p.yr). For AC tumours, the median diameter was 14.0 mm (non-AC 14.0 mm) and the mean diameter was 15.0 mm (non-AC 16.4 mm). The AC-classification results are tabulated below. The CNN classification performance is significantly better than the logistic-regression baseline across all three measures of performance P &lt;.001. AC classification results. All values are given in % with 95% confidence interval bounds in parentheses. Conclusions: We find that the CNN significantly outperforms a logistic model in identifying AC from other histological subtypes. With further development, this algorithm could prove a useful tool to aid management of lung cancer patients.[Table: see text]
Reduced glucose-induced first-phase insulin release is a danger signal that predicts diabetes
Authors: Gordon C. Weir, Susan Bonner-Weir
Journal: Journal of Clinical Investigation (2021)

During progression to both types 1 and 2 diabetes (T1D, T2D), there is a striking loss of glucose-induced first-phase insulin release (FPIR), which is known to predict the onset of T1D. The contribution of reduced β cell mass to the onset of hyperglycemia remains unclear. In this issue of the JCI, Mezza et al. report on their study of patients with pancreatic neoplasms before and after partial pancreatectomy to evaluate the impact of reduced β cell mass on the development of diabetes. The authors found that reduced FPIR predicted diabetes when 50% of the pancreas was removed. These findings suggest that low or absent FPIR indicates that β cell mass can no longer compensate for increased insulin needs. Notably, clinicians may use reduction of FPIR as a warning that progression to T2D is underway.