tbuckley/cabot-search huggingface dataset:
Precision oncology for the treatment of salivary gland tumors.
Authors: Damian Tobias Rieke, Mario Lamping, Serge Leyvraz, Theo Daniel Kim, Lutz Brinkmann, Antje Tessmer, Lars Fischer, Antonia Busse, Peter Horak, Andreas Mock, Inge Tinhofer, Clemens Messerschmidt, Eric Blanc, Dieter Beule, Frederick Klauschen, Konrad Friedrich Klinghammer, Stefan Froehling, Sebastian Ochsenreither, Ulrich Keilholz
Journal: Journal of Clinical Oncology (2019)

e17577 Background: Salivary gland tumors (SGT) represent a rare and heterogeneous group of malignancies. No standard treatment exists in the advanced situation and the prognosis is poor. We here report characteristics and clinical outcomes of patients with SGT discussed at the Charité molecular tumor board (MTB). Methods: Patients with advanced cancer and no curative treatment option were discussed at the Charité MTB. Eligible patients underwent fresh tissue sampling and subsequent whole exome (WES) and RNA sequencing (RNA-seq) and immunohistochemical analyses (EGFR, HER2, AR as well as validation tests) or panel sequencing. Results from molecular testing were discussed at the MTB and patients were followed-up after recommendations were made. Results: 24 patients (median age 56 years, 13 male, 11 female) with advanced SGT were presented at the MTB between 2016 and 2019 (9 adenoidcystic carcinomas, 5 adenocarcinomas, 3 mucoepidermoid, 2 carcinosarcoma, 5 miscellaneous). WES/RNA sequencing was performed on tumor tissue from 16 patients. 2 patients were not included in the sequencing program and WES/RNA-Seq was ongoing for another 4 patients at the time of analysis. For another 2 patients, panel sequencing and IHC analysis, respectively was done. Results from analyses were discussed and a median of 2 recommendations, ranked by priority according to prespecified evidence levels, were made for 17 patients, each. Most commonly proposed treatment options by the MTB were FGFR inhibitors in 6 patients, mTOR or PARP inhibitors in 5 each, EGFR, HDAC inhibitors or antiandrogen therapy in 4, each. Treatments following MTB recommendations were initiated in 8 patients, 1 of which received a second recommended therapy after progression (antiandrogen therapy in 4, EGFR inhibitor in 2, a PDGFR, mTOR and PARP inhibitor in 1, each). A clinical benefit (CR = 1; Mixed Response = 1, SD = 3) was achieved in 5 patients, including a complete response in a patient with a metastatic adenocarcinoma of the parotid gland, treated with antiandrogen therapy. Conclusions: Precision oncology represents a feasible treatment strategy in patients with advanced SGT and shows early evidence of activity in a subset of patients. These results suggest further exploration of personalized therapy in these hard-to-treat tumors.
Repeated centralized MDT resectability assessment during first-line treatment in 1086 Finnish metastatic colorectal cancer (mCRC) patients nationwide (prospective RAXO study).
Authors: Pia J. Osterlund, Raija Sinikka Kallio, Ilmo Kellokumpu, Leena-Maija Soveri, Annika Ålgars, Tapio Salminen, Maija-Leena Murashev, Annamarja Lamminmaki, Päivi Halonen, Raija Ristamäki, Eila Lantto, Ali Ovissi, Arno Nordin, Laura Aroviita, Antti Pekka Jekunen, Renee Lindvall-Andersson, Paul Nyandoto, Juha Teppo Kononen, Tuija Poussa, Helena Isoniemi
Journal: Journal of Clinical Oncology (2019)

3517 Background: Resection of oligometastatic mCRC is curable in up to half and is probably underused in real-life oncology practice. In 2011, a prospective nationwide centralized evaluation of resectability was initiated to assess upfront and conversion to resectability. Methods: The RAXO-study included 1086 mCRCs referred for oncological treatments at all 21 Finnish oncology units (40% of eligible mCRCs in Finland). The MDT at Helsinki tertiary referral center (TRC) assessed resectability of liver, lung and other metastases upfront and twice during first-line therapy. Resectability evaluation was provided online and resections were performed according to clinical praxis, with major resections at TRCs. Results: Median age was 66.5 (range 24-90) yrs, 60% males, ECOG was 0 in 295 (27%), 1 in 600 (55%) and 2-3 in 191 (18%). Tumor was right-sided in 310 (29%), left in 769 (72%) and multiple in 7 (.6%). In the MDT assessment, 435 (40%) were considered resectable, 28% upfront and 12% after conversion. Resections or local ablative therapy were performed in 396 (91% of resectable, R0-1 in 74% and R2 in 17%), with 368 liver-, 91 lung- and 96 other operations. One metastatic site (n = 407), 2 (n = 369) and 3-6 (n = 310) were or became resectable in 65, 33 and 15%, respectively, and R0-1 resected in 54, 30 and 6%, respectively (P &lt; 0.001). In multivariate analysis age &lt; 66.5 (OR 1.51), ECOG 0 (OR 2.40); left-sided primary (OR 1.55), metachronous metastases (OR 1.49), 1-2 metastatic sites (OR 1.86) increased R0-1 resection rates; whereas primary/relapse in situ (OR 0.49), metastases in lung (OR 0.22), peritoneum (OR 0.30) or lymph nodes (OR 0.23) decreased R0-1 rates (P &lt; 0.05). In univariate analyses BRAF wt (OR 0.34), normal CEA (OR 0.31) or normal Ca19-9 (OR 0.45) associated with R0-1 rates. Median OS was 2.4 yrs (CI95% 2.3-2.6) in all, 6.7 yrs in R0-1 (HR 0.15; CI95% 0.11-0.19), 2.8 yrs in R2 (0.50; 0.36-0.68) and 1.7 yrs in non-resected (reference group). Median PFS was 1.1 yrs (1.0-1.1) in all patients, 2.4 yrs in R0-1 (0.24; 0.20-0.28), 1.4 yrs in R2 (0.55; 0.42-0.71) and 0.8 yrs in non-resected patients. P &lt; 0.001 for all comparisons. Conclusions: Repeated centralized MDTs in real-life mCRC patients show high resectability (40%) and resection rates (36%), even if multiple metastatic sites are present. Curative resection associates with good survival. Clinical trial information: NCT01531621.
Report of four cases of pulmonary malignant tumors treated with SBRT using BODYFIX plus 4D-CBCT image guidance technique.
Authors: Lei Wu, Tao Li, Qifeng Wang
Journal: Journal of Clinical Oncology (2019)

e20050 Background: To monitor the range of motion in SBRT treatment of lung tumors by using BODYFIX combined with four-dimensional cone beam CT (4D-CBCT), and provide evidence for delineating the reasonable internal target area (ITV) of lung cancer, and observe the short-term outcom of treatment and treatment of complications. Methods: 4D-CT was used to locate CT scan, delineate the GTV of the tumor, make a simple radiation treatment planning, determine the treatment center point, and then use line accelerator 4D-CBCT to perform pre-SBRT treatment on 4 patients with lung malignant tumor. The system automatically reconstructs the image and matches the CT image of the treatment plan to obtain the placement error of the patient in the head and foot (SI), left and right (LR), and front and rear (AP) directions. The double registration technique is used to correct the correction first. Positioning error, the 4D-CBCT dynamic image is again registered with the target area, the range of motion within the tumor is observed, and the time-weighted 4D-CBCT image is transmitted back to the Monaco planning system to delineate the target area to accurately determine the range of the ITV. According to this target area, a radiation treatment planning was developed, GTV 20Gy/f, 1 to 3 fractions, and then 4D-CBCT scan was performed in each SBRT treatment to observe the range of tumor motion in real time. Results: 3 of the 4 patients the lung tumors were CR at 3 months after treatment, and 1 patient was SD. No serious complications occurred during the treatment or within 3 months after radiotherapy. Conclusions: The BODYFIX plus 4D-CBCT image can more accurately outline the ITV range of lung cancer. The patient is well tolerated and the short-term outcom is good.
Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
Authors: Francesca Finotello, Clemens Mayer, Christina Plattner, Gerhard Laschober, Dietmar Rieder, Hubert Hackl, Anne Krogsdam, Zuzana Loncova, Wilfried Posch, Doris Wilflingseder, Sieghart Sopper, Marieke Ijsselsteijn, Thomas P. Brouwer, Douglas Johnson, Yaomin Xu, Yu Wang, Melinda E. Sanders, Monica V. Estrada, Paula Ericsson-Gonzalez, Pornpimol Charoentong, Justin Balko, Noel Filipe da Cunha Carvalho de Miranda, Zlatko Trajanoski
Journal: Genome Medicine (2019)

We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, and immunohistochemistry data.quanTIseq analysis of 8000 tumor samples revealed that cytotoxic T cell infiltration is more strongly associated with the activation of the CXCR3/CXCL9 axis than with mutational load and that deconvolution-based cell scores have prognostic value in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture and to reveal immune-cell types that underlie differential patients' responses to checkpoint blockers.Availability: quanTIseq is available at http://icbi.at/quantiseq .
Impact of Electronically Accessible Pathways (EAPathways) on clinical trial enrollment at a large multisite cancer center.
Authors: Jeryl Jean Villadolid, Elizabeth Jandrisevits, Donald Moore, Jai Narendra Patel, Kathryn Finch Mileham, Edward S. Kim
Journal: Journal of Clinical Oncology (2019)

6517 Background: Clinical pathways streamline evidence-based treatment decisions and provide consistent, high-quality, value-based care. A high-quality clinical pathway should enhance screening and access to clinical trials. Our healthcare system utilizes EAPathways to allow providers to select treatment regimens vetted by section experts, inquire about clinical trials, and refer to relevant programs (e.g. palliative medicine) or testing (e.g. genomics) at a main cancer center and 22 regional sites. With over 400 clinical trials, our goal is to provide access regardless of where a patient lives or receives treatment. We aim to explore the impact of EAPathways on clinical trial enrollment at our healthcare system. Methods: This study is a retrospective review to compare clinical trial inquiries through EAPathways and clinical trial enrollment using Oncore between 1/1/2017 and 7/31/2018. The primary outcome is the success rate reported as the total number of inquiries that resulted in clinical trial enrollment. Other outcomes include a comparison of inquiries and enrollments for hematology and solid tumor oncology, cancer treatment and non-treatment (e.g. specimen collection), and our main cancer center and regional sites. The number of and reason for opting out of treatments or trials was also analyzed. Results: A total of 29.1% (740/2539) of clinical trial inquiries through EAPathways resulted in clinical trial enrollment. Success rates for the following settings were reported: 39.5% (223/564) in hematology, 26.2% (517/1975) in solid tumor oncology, 27.0% (594/2203) in treatment trials, and 43.5% (146/336) in non-treatment clinical trials. Sixty-three percent of enrollments were at our main cancer center compared to regional sites. A total of 39.7% (3356/8453) of patients were enrolled into an opt-out pathway due to reasons such as performance status, organ dysfunction, or hospice. Conclusions: Clinical pathways can provide access to clinical trial enrollment in multiple settings. These baseline metrics will help assess process improvement needs to increase clinical trial enrollment success rates and address reasons for opt-out.
EMR documentation of genetics evaluations in patients with ovarian cancer.
Authors: Payal Deepak Shah, Heather Symecko, Melissa Batson, Stacy Pundock, Neil Rustgi, Ashley Ford Haggerty, Emily Meichun Ko, Lainie P. Martin, Katherine Nathanson, Susan M. Domchek
Journal: Journal of Clinical Oncology (2019)

e13156 Background: Genetic testing for hereditary cancer predisposition has become increasingly complex yet impactful. Provider knowledge of test results influences risk management, implications for family members, and therapeutics. Currently, it’s unknown if genetic test (GT) results are appropriately recorded and accessible within the electronic medical record (EMR). Methods: We conducted a single-institution retrospective chart review to examine clinical diagnoses, family history of cancer, genetics referrals, and genetics services received at University of Pennsylvania’s Cancer Risk Evaluation Program (CREP) or elsewhere. The study cohort included new and prevalent cases of ovarian cancer (OC) seen by either a gynecologic or medical oncologist at the University of Pennsylvania in 2016. Analyses were conducted using SAS 9.4. Results: 667 women (83% white, 9% black, 4% Asian; mean age 61) with OC were included. 58% had a documented family history of breast, ovarian, prostate or pancreas cancer. 48% had documentation of referral to genetic testing and an additional 26% had documentation of testing outside of CREP. 26% had no documentation of referral or testing. Of those referred to CREP, 75% had genetic testing: in total 62% of the cohort had documented testing. 94% of those tested had a result documented in a provider note, and 64% had a scanned testing report uploaded into the EMR, including 74.3% of those tested through CREP and 25.7% of those tested outside. Among the 118 pathogenic mutations, 70% were documented on the EMR “problem list.” Conclusions: In this study, most, though not all, OC patients had documentation of a GT referral or testing in the EMR. Although GT results were routinely included in progress notes, these reports were less commonly scanned into the EMR (particularly for those tested outside Penn) or included in the EMR “problem list” which is both searchable and immediately visible. Capturing genetic data in a uniform and easily accessible manner within the EMR is necessary to maximize clinical utility of this information and should be a focus for EMR module development.
Identification of a gene expression signature predictive of clinical benefit in patients with advanced mucosal melanoma (MCM) treated with immune checkpoint blockade.
Authors: Suthee Rapisuwon, Alexander Noor Shoushtari, Lee S. Gottesdiener, Douglas Buckner Johnson, Daniel Ying Wang, Garrett Thomas Graham, David Goerlitz, Deborah Berry, Michael B. Atkins
Journal: Journal of Clinical Oncology (2019)

9546 Background: MCM is a rare melanoma subtype (only 1% of melanomas in the US). MCM has a lower tumor mutational burden than cutaneous melanoma (CM). While some patients (pts) with MCM respond to immune checkpoint inhibitor (ICI) therapy, predictive markers of response have not been established. We analyzed a cohort of MCM from pts treated with ICI to identify gene expression signatures associated with tumor response and clinical outcome. Methods: Fifty-eight MCM specimens were collected from 3 institutions. RNA was extracted from FFPE tissue slides and analyzed by NanoString 770 Immune Profiling Panel. Gene expression profiles were linked to anatomical location and disease outcome after ICI therapy: response as defined by RECIST v1.1 and median overall survival (mOS). Results: Fifty-one pts were treated with ICI - anti-CTLA-4 (n = 9), anti-PD1 (n = 38), or both (n = 5) ) and had tumor response evaluation. Three were without response data, 2 were without disease recurrence after surgery, 2 did not receive ICI. Among 51 pts with response data, seven were without long-term follow-up (1CR, 2PR, 3SD). The overall response rate (ORR) was 40.3%, similar to the prior study (Shoushtari et al, Cancer 2016). A signature involving differential expression of 87 immunoregulatory genes correlated with tumor response: ORR: 75% (12/16) signature high vs. 33.3% (7/21) signature low (p = 0.02, high vs. low) vs. 14.3% (2/14) signature average (p &lt; 0.01; high vs. average). mOS for the whole population was 12.4 months. Pts with increased gene signature expression had superior mOS: signature-high: Not reached, signature-low: 8.2 months, (HR: 0.2; 95%CI: 0.07-0.55, p &lt; 0.01). Transcript pathway analysis of the gene signature showed association with chemokine receptors, interleukin-10 signaling, and Treg development. Conclusions: We have identified a gene expression signature that involves chemokine receptors, IL-10 signaling, and Treg development gene sets, that appears to predict for tumor response and mOS in pts with advanced MCM treated with ICI. Further validation of these gene signatures is underway.
Simple minimally-invasive automatic antidote delivery device (A2D2) towards closed-loop reversal of opioid overdose
Authors: Bahar Dhowan, Jongcheon Lim, Michael D. MacLean, Alycia G. Berman, Min Ku Kim, Qi Yang, Jacqueline Linnes, Chi Hwan Lee, Craig J. Goergen, Hyowon Lee
Journal: Journal of Controlled Release (2019)
Exploring the Association of Sex Differences and Exposure to Maternal Smoking With Low Fetal Growth
Authors: Henri-Jean Aubin, Ivan Berlin, Mikael Ekblad
Journal: JAMA Psychiatry (2019)

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Diabetes mellitus: An adverse prognosis in cancer patients—Study of a cohort treated at Instituto Oncológico Henry Moore (IOHM).
Authors: Ernesto Gil Deza, Julio Cesar Bragagnolo, Eduardo L. Morgenfeld, Marta Dragosky, Natasha Gercovich, Monica Montiel, Dario Niewiadomski, Pamela Perez, Silvina Laura Musini, Edgardo G. J. Rivarola, Felipe G. Gercovich
Journal: Journal of Clinical Oncology (2019)

e18212 Background: Numerous studies have evaluated the unfavorable impact of diabetes mellitus (DM) on cancer evolution. The objective of this paper is to study the coexistence of DM and cancer diagnosis; and its influence on the evolution of a cohort followed at IOHM. Methods: Between 9/26/2012 and 11/28/2018 all new patients (Pt) admitted to IOHM filled out a Past Medical History Form (PMHF) (ASCO 2013 ABST. e17539) with their preexisting clinical conditions.The database was locked and anonymized. Those with a history of DM or who were taking insulin and/ or oral antidiabetics were selected (Group A). The stage and evolution of their tumors were compared with those of non-diabetic patients (Group B). Results: Out of 15,617 Pt, 1,829 Pt (11,7%) had DM (Group A); 1,087 Pt were being treated with oral hypoglycemics (59%); 178 Pt with insulin (10%) and 564 Pt (31%) were not on antidiabetics drugs. They were compared to 13,788 Pt without DM (Group B). Oncological treatment was similar in both groups. Mortality was greaterin DM Patients adjusted by sex, age, PS, BMI, Dx and stage; Multivariate Cox Regression (p = 0.0001). The results are presented in the chart below. Conclusions: 1) In a cohort of 15,617 cancer Pt, 11,7% had DM. 2) DM Pt's tumors were more advanced. 3) Under similar treatments, DM Pt presented higher mortality. 4) Based on this, we advocate for DM in oncological Pt to be considered as an independent adverse factor.[Table: see text]
Automated prostate lesion detection and PI-RADS assessment with deep learning.
Authors: Choongheon Yoon, Jasper Van, Michelle Bardis, Param Bhatter, Alexander Ushinsky, Justin Glavis-Bloom, Chanon Chantaduly, Daniel S. Chow, Roozbeh Houshyar, Peter Chang
Journal: Journal of Clinical Oncology (2019)

e16605 Background: Prostate Cancer is the most commonly diagnosed male cancer in the U.S. Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for both prostate cancer evaluation and biopsy guidance. The PI-RADS v2 scoring paradigm was developed to stratify prostate lesions on MRI and to predict lesion grade. Prostate organ and lesion segmentation is an essential step in pre-biopsy surgical planning. Deep learning convolutional neural networks (CNN) for image recognition are becoming a more common method of machine learning. In this study, we develop a comprehensive deep learning pipeline of 3D/2D CNN based on U-Net architecture for automatic localization and segmentation of prostates, detection of prostate lesions and PI-RADS v2 lesion scoring of mpMRIs. Methods: This IRB approved retrospective review included a total of 303 prostate nodules from 217 patients who had a prostate mpMRI between September 2014 and December 2016 and an MR-guided transrectal biopsy. For each T2 weighted image, a board-certified abdominal radiologist manually segmented the prostate and each prostate lesion. The T2 weighted and ADC series were co-registered and each lesion was assigned an overall PI-RADS score, T2 weighted PI-RADS score, and ADC PI-RADS score. After a U-Net neural network segmented the prostate organ, a mask regional convolutional neural network (R-CNN) was applied. The mask R-CNN is composed of three neural networks: feature pyramid network, region proposal network, and head network. The mask R-CNN detected the prostate lesion, segmented it, and estimated its PI-RADS score. Instead, the mask R-CNN was implemented to regress along dimensions of the PI-RADS criteria. The mask R-CNN performance was assessed with AUC, Sørensen–Dice coefficient, and Cohen’s Kappa for PI-RADS scoring agreement. Results: The AUC for prostate nodule detection was 0.79. By varying detection thresholds, sensitivity/PPV were 0.94/.54 and 0.60/0.87 at either ends of the spectrum. For detected nodules, the segmentation Sørensen–Dice coefficient was 0.76 (0.72 – 0.80). Weighted Cohen’s Kappa for PI-RADS scoring agreement was 0.63, 0.71, and 0.51 for composite, T2 weighted, and ADC respectively. Conclusions: These results demonstrate the feasibility of implementing a comprehensive 3D/2D CNN-based deep learning pipeline for evaluation of prostate mpMRI. This method is highly accurate for organ segmentation. The results for lesion detection and categorization are modest; however, the PI-RADS v2 score accuracy is comparable to previously published human interobserver agreement.