tbuckley/cabot-search huggingface dataset:
Pharmacokinetics of ciclopirox prodrug, a novel agent for the treatment of bladder cancer, in animals and humans.
Authors: Scott James Weir, Robyn Wood, Michael Jay Baltezor, Greg Reed, Amanda E Brinker, Tammy Ham, Karl Schorno, Paul Toren, Prabhu Ramamoorthy, Valentina Zhukova-Harrill, Michael Dalton, William McCulloch, Manish R. Patel, Susanna Varkey Ulahannan, Howard A. Burris, Gerald Steven Falchook, Roy A. Jensen, Shrikant Anant, John Arthur Taylor
Journal: Journal of Clinical Oncology (2019)

e14705 Background: Ciclopirox Prodrug (CPX-POM) is a novel anticancer agent currently being evaluated in patients with advanced solid tumors participating in a First-in-Human, Phase 1 safety, dose tolerance, pharmacokinetics (PK) and pharmacodynamics trial at four US sites. In vitro and in vivo preclinical proof of principle was established in high grade human urothelial cancer cell lines as well as a mouse model of bladder cancer.Methods: A series of in vivo PK studies were conducted in mice, rats and dogs to characterize the absolute bioavailability of CPX following intravenous (IV), subcutaneous (SC) and oral administration of CPX-POM. The single dose and steady-state plasma and urine pharmacokinetics of CPX-POM are also currently being characterized in patients participating in the ongoing Phase 1 trial. Plasma and urine concentrations of the prodrug and metabolites were determined by LC-MS/MS validated in each specie and matrix. Non-parametric pharmacokinetic parameters were generated from resultant plasma and urine drug and metabolite concentration-time data. Results: CPX-POM is rapidly and completely metabolized to CPX in blood via circulating phosphatases in animals and humans. CPX is completely bioavailable following IV CPX-POM administration in mice, rats and dogs. CPX and its major inactive glucuronide metabolite (CPX-G) are extensively eliminated in urine in all animal species. SC administration of CPX-POM demonstrated excellent bioavailability in rats and dogs. Following IV administration of 30-900 mg/m 2 CPX-POM to patients, the apparent elimination half-life of CPX ranged from 2 to 8 hours, CPX systemic exposure was dose-proportional and time-independent in cancer patients, and a major portion of the dose was eliminated as CPX-G. Conclusions: IV CPX-POM achieves plasma and urine CPX exposures that exceed in vitro IC50 values several-fold at well tolerated doses in animals and humans. CPX pharmacokinetics observed in animals were predictive of human systemic clearance based on allometric scaling. Clinical trial information: NCT03348514.
Relapse-free survival (RFS) after surgical resection to predict survival after relapse (SAR) and overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDA).
Authors: Jesus Rodriguez-Pascual, Rafael Alvarez-Gallego, Cesar Munoz, Lisardo Ugidos, Enrique Sanz, Lucia Ceniceros, Maria Rivas, Esther Torres, Jose M Cardenas, Antonio Cubillo Gracián
Journal: Journal of Clinical Oncology (2019)

e15735 Background: We aimed to evaluate the clinical relevance of RFS after local PDA resection as a prognostic factor in terms of SAR and OS. Methods: Patients diagnosed with local PDA who had undergone surgical resection in 4 hospitals from Spain were identified. Disease location, demographic, pathologic, treatment during recurrence and mortality information was retrospectively collected. RFS was measured from date of surgery until recurrence and censored at death or last follow-up. SAR was measured from relapse, until death or last follow-up. We defined patients presenting an RFS value of 6 months or more, or less than 6 months as High-RFS and Low-RFS respectively. Results: Of 93 patients with resected PDA, 51 (54.8%) were male and 42 (45.2%) female. The median age was 65.2 years. 62 (66.7%) tumors were localized in the head. There were 5 (5.4%), 17 (18.3%) and 69 (74.1%) stage I, II and III respectively. 53 (57%) patients had undergone cephalic (Whipple), 20 (21.5%) distal and 20 (21,5%) total pancreatectomy. 48 (51.6%) patients received radiotherapy and 86 (92.5%) received chemotherapy in the neoadjuvant and/or adjuvant setting. Median RFS was 12.3 months. In the metastatic setting, the most frequent chemotherapy combination was gemcitabine plus nab-paclitaxel. 43(46,2%) of patients received second line chemotherapy. Median OS and median SAR were 25,9 and 10,1 months respectively. Kaplan-Meier survival analysis showed that PDA cancer patients with Low-RFS have a poorer clinical outcome than those with High-RFS (median OS 48.26 months, CI 95% 39,3-57,1 for High-RFS; 19.2 months CI 95% 15.7-22-8 for Low-RFS; p = 0.0001). On multivariate Cox regression analysis, age, initial stage I-II, adjuvant chemotherapy utilization and High-RFS were independent prognostic factors for OS and SAR rate. Conclusions: RFS was strongly correlated and discriminated PDA patients with better SAR and OS from the poorer prognosis patients in the ulterior metastatic setting. Prospective studies are needed to confirm this finding.
Mapping the activation landscape of the MAPK\ERK pathway for variants of unknown significance (VUS) using convolutional neural networks (CNN).
Authors: Gabi Tarcic, Lior Zimmerman, Arie Aizenman, Zohar Barbash, Ori Zelichov, Michael Vidne
Journal: Journal of Clinical Oncology (2019)

e14615 Background: The MAPK\ERK signaling pathway is a major determinant in the control of diverse cellular processes. This pathway is often up-regulated in human tumors and as such has been an attractive target for the development of anticancer drugs. Mapping the activation landscape of MAPK\ERK is a necessary step in understanding tumor progression and determining the significance of a mutation as well as the relevance of available treatments. Here we present a CNN model, combined with an in-vitro system to investigate the activation landscape of various members of the MAPK\ERK pathway Methods: A novel multi-resolution multi-channel deep neural network was trained to classify images of cells that were transfected with known activating mutated forms of MAPK activating proteins versus WT forms of the proteins. The cells were also transfected with a fluorescently tagged ERK2 expression construct that was one of the three channels imaged by a fluorescent microscopy system. The trained network was subsequently tested on its ability to score images of cells that were transfected with VUS forms of the proteins, or images of cells that were transfected with VUS forms of MAPK proteins and were incubated with the relevant targeted therapies Results: We analyzed 6 proteins activating MAPK\ERK carrying over 100 unique VUS as well as many known oncogenic mutations and determined the pathogenicity score outputted by the network. Analysis of the performance of our model showed that our predictions exceed 95% accuracy and AUC &gt; 0.95. Interestingly, analysis of deeper layers of the network revealed that each gene and mutation exhibit a unique ERK2 activation signal which is considerably different between active and non-active mutations as well as the ability to recognize what mutated gene was transfected, which means that each mutated gene induces different phenological attributes to the cells Conclusions: The use of deep-learning algorithms is providing increasing clinical relevance in several medical fields, most notably pathology. We show that using a cell-based assay combined with high throughput microscopy and CNN based analysis can be used to determine the activity of a wide set of mutations and potentially assist the prediction of targeted therapy outcome. Our results highlight the role of functional interpretation of molecular profiles, enabling more accurate prediction of oncogenic mutations.
Computer-aided classification of lung nodules on CT scans via 3D CNNs.
Authors: Xiaohua Liu, Ligang Luo, Haiying Yang, Xiaoxiang Jie, Peiyu Li, Ding Ma, Yue Kang, Guangming Gao, Xiangfeng Luo, Yuli She, Jinchen Li, Yuzhe Liu, Weihao Xie, Shijie Lu, Zhongjie Hu, Tianze Zhang
Journal: Journal of Clinical Oncology (2019)

e18047 Background: Computer-aided diagnosis based on deep learning methodologies has demonstrated great potential to assist disease diagnosis with accuracy and efficiency. Specifically, the quantitative and qualitative analysis on lung nodules has proven to be important for the early-detection of lung cancer as well as its treatment in clinical practice. This study developed a 3D CNN model to facilitate the classification of pulmonary nodules. Methods: We collected 3956 lung CT scans (slice thickness≤3mm) with multiple lung nodules from 15 Class-A hospitals in China, 1155 lung CTs from Luna 16 dataset and Data Science Bowl 2017. There were 30 senior radiologists responsible for annotation and each CT scan was annotated by two of them randomly. Another 4 senior associate chief physicians were divided into two groups, each group was responsible for arbitration when conflicts occurred between the annotation doctors. All the annotated CTs were randomly selected and split to construct training, validation and test sets. We pre-processed the CTs and utilized 3D CNNs to classify these nodules as solid, partial-solid, ground glass opacity, calcified, pleural solid and pleural calcified. ROC analysis was used, and the classification capability was assessed by classification accuracy and the AUC score. Results: Table shows the overall results. The proposed model yielded an AUC score of 0.97 for the ground glass opacity and 0.90 for calcified nodules in the training set, while the AUC of them were 0.93 and 0.93 respectively in the validation set. For the test set, we got an AUC score of 0.94 for the ground glass opacity. The average classification time for each nodule was less than 0.005 sec. Conclusions: Our model may assist clinical diagnosis of lung cancer and increase its objectivity and accuracy, and the fast processing speed proves its feasibility to be applied in real clinical practice. In the future, we will enrich the dataset with clinical and genetic information, thus improving our model to boost its performance. [Table: see text]
Breast Cancer Cases in a Surveillance Program: Report from the Hereditary Department at South General Hospital, Sweden.
Authors: Anna-Maria Karumo, Linda Thorén, Anna Von Wachenfeldt Väppling
Journal: Journal of Clinical Oncology (2019)

e13068 Background: Women with a doubled, or greater, lifetime risk of developing breast cancer are according to Swedish guidelines offered intensified surveillance with one or more of the following modalities; mammography (MG), ultrasound (US) and magnetic resonance imaging (MRI). MRI is primarily recommended for mutation carriers &lt; 55 years of age. From 2014 mutation carriers undergo annual surveillance, alternating MRI and MG/US every 6 months. Aim: To evaluate which modality was able to detect the tumor, tumor stage and characteristics in women who developed breast cancer under surveillance at the Hereditary Department, South General Hospital, Stockholm. Methods: Data on women in the surveillance program diagnosed with breast cancer 2003 - 2018 was collected from patient notes. Results: Fifty-five women were diagnosed with breast cancer. Twenty-five women underwent MRI, in 22 cases the tumor was visible. Forty percent of the women aged 55 or older had tumors only visible on MRI. Fifty-three women underwent US, in 38 cases the tumor was visible. Thirty two of 49 tumors were detected by MG. In 35 cases the tumor was not palpable. Fourteen women were diagnosed with DCIS. These cases, combined with patients with T1 N0 tumors, constituted 69% of the 55 women. Eleven women were node positive. Twelve women were diagnosed in between screening rounds, ie interval cancers. Three of these were small tumors found only at the pathology examination after prophylactic mastectomy. The proportion of interval cancers decreased from 31% to 14% after 2014. Twenty-four women were identified as mutation carriers in BRCA1, BRCA2 or PALB2. Seven of these mutations were detected after the patient´s cancer diagnosis. Nine mutation carriers were diagnosed with interval cancers, four were node positive. Conclusions: All women were diagnosed at a potentially curable stage and most were node negative. Mutation carriers constituted the largest portion of women with interval cancers. This study indicates that MRI may be of benefit in the surveillance of mutation carriers after 55 years of age. The transition from annual to biannual examinations with MG/US and MRI appears to decrease the incidence of interval cancers.
Case 50-1987
Authors: Richard C. Cabot, Robert E. Scully, Eugene J. Mark, William F. McNeely, Betty U. McNeely, Caryn A. Libbey, Michael L. Talbert
Journal: New England Journal of Medicine (1987)

Presentation of CaseA 43-year-old woman was admitted to the hospital because of abdominal pain, vomiting, and impaired hepatic function.There was a history of hypertension and progressive renal dysfunction since the age of 25 years. Twenty-one months before entry extracorporeal hemodialysis was begun. Seventeen months before admission bilateral nephrectomy was performed, and a cadaveric renal allograft was transplanted. Microscopical examination of the native kidneys showed prominent interstitial deposition of amorphous eosinophilic material around vessels and between tubules, especially in the renal medulla; the tubules were atrophic; scattered obsolescent glomeruli were seen, but the glomeruli were otherwise uninvolved; there was . . .
Erratum: Unexplored therapeutic opportunities in the human genome
Authors: Tudor I. Oprea, Cristian G. Bologa, Søren Brunak, Allen Campbell, Gregory N. Gan, Anna Gaulton, Shawn M. Gomez, Rajarshi Guha, Anne Hersey, Jayme Holmes, Ajit Jadhav, Lars Juhl Jensen, Gary L. Johnson, Anneli Karlson, Andrew R. Leach, Avi Ma'ayan, Anna Malovannaya, Subramani Mani, Steven L. Mathias, Michael T. McManus, Terrence F. Meehan, Christian von Mering, Daniel Muthas, Dac-Trung Nguyen, John P. Overington, George Papadatos, Jun Qin, Christian Reich, Bryan L. Roth, Stephan C. Schürer, Anton Simeonov, Larry A. Sklar, Noel Southall, Susumu Tomita, Ilinca Tudose, Oleg Ursu, Dušica Vidovic´, Anna Waller, David Westergaard, Jeremy J. Yang, Gergely Zahoránszky-Köhalmi
Journal: Nature Reviews Drug Discovery (2018)
Decision making in surveillance of high-grade gliomas using perfusion MRI as adjunct to conventional MRI and artificial intelligence.
Authors: Sotirios Bisdas, Loizos Shakallis, Andy McEvoy, Anna Miserocchi, George Samandouras, Sebastian Brandner, Jeremy Rees, Naomi Ferscht, Jorge M Cardoso, Jasmina Panovska-Griffiths, Carole Sudre, Faiq Shaikh, Diana Roettger
Journal: Journal of Clinical Oncology (2019)

2054 Background: Surveillance of High-Grade Gliomas (HGGs) remains a major challenge in clinical neurooncology. Histopathological validation is not an option during the course of disease and imaging surveillance suffers from ambiguous features of both disease progression and treatment related changes. This study aimed to differentiate between Pseudoprogression (PsP) and Progressive Disease (PD) using an artificial intelligence (support vector machine - SVM) classification algorithm. Methods: Two groups of patients with histologically proven HGGs were analysed, a group with a single time point DSC perfusion MRI (45 patients) and a group with multiple time point DSC perfusion MRI (19 patients). Both groups included conventional MRI studies prior and after each perfusion MRI. This study design aimed to replicate decision making in clinical practice including multiple previous studies for each patient. SVM training was performed with all available MRI studies for each group and classification was based on different feature datasets from a single or multiple (subtracted features) time points. Classification accuracy comparisons were performed by calculating prediction error rates for different feature datasets and different time point analyses. Results: Our results indicate that the addition of multiple time point perfusion MRI combined with structural (conventional with gadolinium-enhanced sequences) MRI features results in optimal classification performance (median error rate: 0.016, lowest value dispersion). Subtracted feature datasets improved classification performance, more prominently when the final and first perfusion studies were included in the analysis. On the contrary, in the single time point group analysis, structural feature-based classification performed best (median error rate: 0.012). Conclusions: Validation of our results with a larger patient cohort may have significant clinical importance in optimising imaging surveillance and clinical decision making for patients with HGG.
The efficacy of ado-trastuzumab emtansine in patients with HER-2-aberrant non-small cell lung cancer.
Authors: Yang Xia, Xiu Huang, Rui Jin, Wen Li, Huahao Shen
Journal: Journal of Clinical Oncology (2019)

e20584 Background: HER-2 aberrations, including gene mutation, gene amplification and protein overexpression, have been considered as oncogenic driver alteration in non-small cell lung cancer. However, the therapeutic effect of Ado-trastuzumab emtansine (T-DM1) is varied in HER-2 altered lung cancer. Thus, we aim to elucidate the efficacy of T-DM1 in treating different subtypes of HER-2 aberrations by integrating and reanalyzing the data from current available literatures. Methods: We sought published articles, case reports and ongoing studies that reported efficacy of T-DM1 in lung cancer with HER-2 aberration. Seven studies met the systematic review criteria. The main outcomes were the overall response rate (ORR). Results: 93 patients with various HER-2 aberrations were identified in 7 studies. HER-2 upregulation was prone to occurred in the patients with smoking history and adenocarcinoma, without gender difference, while HER-2 mutations were more common in female non-smoker with adenocarcinoma. The overall ORR of HER-2 aberration was 19.35%. Subgroup analysis showed the ORR was 35.00% for sole HER-2 mutation, 42.86% for HER-2 gene amplification, 2.78% for HER-2 protein overexpression, respectively. Of note, ORR was only 8.33% for HER-2 upregulation (protein overexpression and/or gene amplification), while ORR was significantly increased to 46.15% upon concomitant HER-2 upregulation and mutation. Furthermore, ORR was 25.00% for overexpression plus mutation, but ORR was up to 80.00% for gene amplification plus overexpression and mutation. Conclusions: T-DM1 is a promising agent targeting to HER-2 mutant or amplified lung cancers and the therapeutic efficiency might be more pronounced upon HER-2 mutation alone with amplification. Additional studies of this agent are warranted.
Doxorubicin response prediction in neoadjuvant breast cancer therapy.
Authors: Anna Sofie Kappel Buhl, Ib Jarle Christensen, Steen Knudsen, Peter Buhl Jensen
Journal: Journal of Clinical Oncology (2019)

e12119 Background: Neoadjuvant treatment for breast cancer (BC) is an important remedy if the tumors are responding adequately. Still, there is no biomarker guidance resulting in many patients receiving chemotherapy with no efficient antitumor effect. We study a multigene mRNA-based technology for drug response prediction (DRP). DRP has been thoroughly validated in other settings, latest in prediction of epirubicin efficacy in advanced BC [1]. Here are the results of the DRP method in the prediction of response to neoadjuvant doxorubicin in early BC. Methods: The DRP correlates sensitivity of the applicable drug in cell lines with background mRNA. This is combined with gene expression patterns from &gt;2.000 tumors of different origin to ensure clinically usefulness. The higher DRP score, the higher likelihood of response. Blinded predictions of doxorubicin DRP scores were compared to response data which originated from a phase II trial [2], where the study population received neoadjuvant doxorubicin and cyclophosphamide (N=279). The patients had histologically confirmed primary invasive breast adenocarcinoma (T2-3, N0-3, M0, tumor size ≥ 2.0 cm, ER+/- and HER2+/-). Statistical analysis was done using logistic regression. Results: Table shows the distribution of response and DRP scores, showing higher DRPs are correlated to better clinical outcome. This is demonstrated by logistic regression ( p=0.002), odds ratio for response 2.2 (95% CI:1.3-3.4). Multivariate analysis showed that the DRP was independent of other covariates. Conclusions: The DRP can predict which patients will be high likelihood responders to neoadjuvant doxorubicin. Modern multigene technologies may help assist clinicians in choosing between upfront surgery or neoadjuvant chemotherapy. Complete response (CR), Partial response (PR), Stable disease (SD), Progression of Disease (PD). 1. Buhl ASK, et al. (2018): Predicting efficacy of epirubicin by a multigene assay in advanced breast cancer within a Danish Breast Cancer Cooperative Group (DBCG) cohort: a retrospective-prospective blinded study. Breast cancer research and treatment. doi: 10.1007/s10549-018-4918-4. 2. Horak CE et al. (2013): Biomarker analysis of neoadjuvant doxorubicin/cyclophosphamide followed by ixabepilone or Paclitaxel in early-stage breast cancer. Clinical cancer research. doi: 10.1158/1078-0432.ccr-12-1359.[Table: see text]
FRI0091 UNEMPLOYED FEMALE RHEUMATOID ARTHRITIS PATIENTS ARE LESS ADHERENT TO THE BIOLOGIC DMARD TREATMENT
Authors: FRISO LARA, Francesca Ometto, Davide Astorri, Bernd Raffeiner, Costantino Botsios, Danila Azzolina, Marta Favero, Dario Gregori, John Done, Andrea Doria
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background:</h3> The 5-item Compliance Questionnaire for Rheumatology (CQR5) allows the identification of patients likely to be high adherers (HAs) to anti-rheumatic treatment (i.e. taking ≥80% of their medications correctly), or "low" adherers (LAs). An Italian version of the questionnaire was validated (I-CQR5) [1]. <h3>Objectives:</h3> The objective was to investigate what factors are associated with high treatment adherence according to I-CQR5 in RA patients treated with biologic DMARDs (bDMARDs). <h3>Methods:</h3> RA patients (with disease duration &gt;1 year, undergoing treatment with ≥1 self-administered biological disease-modifying anti-rheumatic drug (bDMARD), willing and capable of completing the questionnaire unaided) were enrolled in the study. I-CQR5 were anonymous and clinical data were collected from the local database. Factors included were demographic, social characteristics of the patients, clinical and treatment variables. Factors achieving a p&lt;0.10 in univariate analysis were included in a multivariate regression analysis. <h3>Results:</h3> Among 604 RA patients, 193 patients were included in the validation analysis. Median age of the patients was 57 years (46-65), 142 (73.4%) were females, median disease duration was 15 years (9-21); 82 (42.7%) patients were treated with low dose bDMARDs; 174 (91.1%) patients were in low disease activity or remission (Fig.1). HAs were 40.9% (79/193) of patients: 100% (193/193) of patients treated with bDMARDs and 22.4% (57/193) of those treated with bDMARDs in combination with conventional synthetic DMARDs. Female gender, no employment, lower education level, positive Rheumatoid Factor and/or Anti-Citrullinated Peptides Antibodies, low bDMARD dose, higher patient-VAS were significantly more frequent in LAs compared with HAs. In the multivariate analysis, employment was also positively and significantly associated with high adherence: OR 2.89 (1.3-6.44), p=0.009 (Tab.1). <h3>Conclusion:</h3> As previously reported only one third of RA patients treated with bDMARDs were found to be HAs to treatment according to the I-CQR5. Employment status was the major determinant, increasing by almost 3-fold the likelihood of being adherent. Education level and female gender might be also taken into account as factors influencing treatment adherence. <h3>Reference:</h3> [1] Ometto F., et al. Treatment adherence in rheumatoid arthritis italian patients using a validated version of the 5-item compliance questionnaire for rheumatology (I-CQR5). EULAR18-4294. <h3>Disclosure of Interests:</h3> None declared