bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 1380: Clinical relevance of cell-free DNA analysis for bile juice assessed through amplicon-based deep sequencing in bile duct and pancreatic cancer patients with obstructive jaundice
Authors: Muramatsu Marie , Muramatsu Marie , Ito Hiromichi , Zembutsu Hitoshi 
Published: August 2019

Abstract
Personalized treatment for patients with pancreatic or bile duct cancer is limited because cancer cells could not be detected in some patient. Cell-free DNA (cfDNA) sequencing is expected to enable a precision oncology approach for these patients. The development of gene panel for cfDNA covering hundreds of mutation hotspots is important for the establishment of clinically practical cfDNA detection system. We enrolled 40 patients with bile duct or pancreatic cancer which caused obstructive jaundice. Amplicon-based genomic profiling of 14 genes, which are commonly mutated in digestive cancer, in preoperative bile juice by next-generation sequencing (NGS) was carried out to evaluate the feasibility of this assay, and was compared with their clinical parameters. One or more somatic mutation(s) of the 14 genes in bile cfDNA were detected in 25 patients (62.5%) with bile duct or pancreatic cancer. Mutations in TP53, KRAS and APC genes were detected in 19 (47.5%), 11 (27.5%) and 4 (10.0%) patients, respectively. Mutant allele frequencies in plasma were not associated with CEA nor CA19-9. Of the 40 patients with bile duct or pancreatic cancer, the cancer cells could be detected by cytology in 18 patients (45.0%). On the other hand, mutant alleles from cancer cells could be detected in 14 patients who showed negative cytology. Hence, 32 patients (80.0%) could be diagnosed as cancer before surgical operation by using the information from liquid biopsy (cfDNA analysis using bile juice) in addition to that from cytology. Our data confirmed that mutant allele in bile cfDNA could be sensitively detected by amplicon-based NGS system. These results suggest that the detection of cfDNA in bile juice using high-sensitive deep sequencing system could be a novel diagnostic tool, and these technologies could increase the ratio of definitive diagnosis of refractory cancer such as bile duct or pancreatic cancer.
Citation Format: Marie Muramatsu, Marie Muramatsu, Hiromichi Ito, Hitoshi Zembutsu. Clinical relevance of cell-free DNA analysis for bile juice assessed through amplicon-based deep sequencing in bile duct and pancreatic cancer patients with obstructive jaundice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1380.
Abstract 1393: Automated adeno/squamous-cell NSCLC classification from diagnostic slide images: A deep-learning framework utilizing cell-density maps
Authors: Jaber Mustafa I. , Beziaeva Liudmila , Szeto Christopher W. , Elshimali John , Rabizadeh Shahrooz , Song Bing 
Published: August 2019

Abstract
Background: The most common form of lung cancer, non-small cell lung cancer (NSCLC), is further categorized into two major histopathological subtypes: ~40% Adenocarcinoma (LUAD), and ~30% squamous cell carcinoma (LUSC). Classifying patients accurately is important for prognosis and therapy decisions, but requires costly pathologist review. Here we present an automated algorithm to differentiate LUAD and LUSC diagnostic whole slide images (WSIs).
Methods: 488 subtyped NSCLC high-resolution diagnostic WSIs were obtained from TCGA sources. Adjacent normal regions were identified and excluded from analysis. Cancer cell-density maps were created based on cell counts within discrete patches. These maps were then binned into ten ranges of cell counts (20-30 cells per patch, 30-40, etc. up to &gt;110 cells per patch). 2D color patches were transformed into 1D descriptive vectors using the inception v3 deep learning framework. Samples were randomly split into 70% training and 30% testing sets. Ten LUAD/LUSC linear SVM classifiers (one for each cell-density bin) were trained on such transformed data. Subtype prediction in unseen testing samples was achieved by averaging subtype predictions from the 10 subsequent models.
Results: 338 TCGA diagnostic WSIs (164 LUAD and 174 LUSC) were used to train, and 150 (71 LUAD and 79 LUSC) were used to test. The proposed system achieved an AUC of 0.9068 in test samples, corresponding to a classification accuracy of 83.33%. The (heretofore excluded) adjacent normal regions were classified correctly almost as accurately as tumor regions (74.7%).
Conclusions: This fully-automated histopathology subtyping method generates maps of regions-of-interest within WSIs, providing novel spatial information on tumoral organization. For example, our results on test data show tumor patches of size 100 square microns with 60 to 100 cells distinguish LUAD from LUSC better than other cell-density ranges. Moreover, adjacent normal tissue may provide additional insights into tumorigenesis mechanisms.
Citation Format: Mustafa I. Jaber, Liudmila Beziaeva, Christopher W. Szeto, John Elshimali, Shahrooz Rabizadeh, Bing Song. Automated adeno/squamous-cell NSCLC classification from diagnostic slide images: A deep-learning framework utilizing cell-density maps [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1393.
Abstract 1395: Residual convolutional neural network for predicting response of transarterial chemoembolizationin hepatocellular carcinomafrom CT imaging
Authors: Peng Jie 
Published: August 2019

Abstract
Purpose: We aimed to develop and validate a model of deep learning for the preoperative prediction of response of patients with intermediate stage hepatocellular carcinoma undergoing transarterial chemoembolization.
Methods: The training and two independent validation CT images were acquired for 540 patients from the Nan Fang Hospital (NFH), 84 patients from Zhu Hai Hospital Affiliated with Jinan University (ZHHAJU) and 136 patients from the Sun Yat-sen University Cancer Center (SYUCC). We built a predictive model from the outputs using transfer learning techniques of a residual convolutional neural network (ResNet50). Then, we revaluated the prediction accuracy for each patch in two independent validation cohorts.
Results: In the training (NFH) set, the deep learning model had a high accuracy of 84.3% and an areas under the receiver operating characteristic curves (AUROC) of 0.97, 0.96, 0.95 and 0.96 for complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD), respectively. In the validation (ZHHAJU) set, the deep learning model had an accuracy of 85.1% and an AUROC of 0.98, 0.96, 0.95 and 0.94 for CR, PR, SD and PD, respectively. In the other validation (SYUCC) set, the deep learning model had an accuracy of 82.8% and an AUROC of 0.97, 0.96, 0.95 and 0.95 for CR, PR, SD and PD, respectively.
Conclusion: The proposed ResNet model showed excellent performance for the individualized and non-invasive estimation of TACE therapy, which may help clinicians to better identify patients with HCC who can benefit from the interventional treatment.
Citation Format: Jie Peng. Residual convolutional neural network for predicting response of transarterial chemoembolizationin hepatocellular carcinomafrom CT imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1395.
Abstract 1399: Ex-vivo targeting of urothelial carcinomas by fluorescent pHLIP imaging agents
Authors: Golijanin Borivoj , Moshnikova Anna , Engelman Donald M. , Andreev Oleg A. , Reshetnyak Yana K. , Amin Ali , Golijanin Dragan 
Published: August 2019

Abstract
Introduction: The detection of urothelial carcinomas of the bladder and upper tract is not satisfactory. Incomplete findings by contemporary imaging modalities provide a challenge in patient care, so there is a definitive need to improve diagnosis and treatment methods for urothelial carcinomas.
Experimental procedures: ICG (indocyanine green) near infrared fluorescent (NIRF) dyes were conjugated with a pH-Low Insertion Peptide (pHLIP®), which senses and targets the acidity at the surfaces of cancer cells. In a few cases IR800 pHLIP® was used. Urinary neoplasm (kidney, ureter and bladder) specimens obtained through radical surgery were irrigated and incubated ex-vivo with ICG pHLIP® followed by fluorescence imaging. Pathology findings were correlated with the ICG pHLIP® NIRF imaging.
Results: In the upper urothelial tract, nine of ten patients with nephroureterectomy had urothelial carcinomas (UTUC). Eighteen (100%) malignant lesions were found in NIRF imaging. Only thirteen (72%) of malignant lesions were found under white light macroscopic examination. ICG pHLIP® NIRF imaging gave a 28% increase in diagnosis of UTUC in ex-vivo specimens. There was no non-specific uptake in the non-tumoral tissue. The ICG pHLIP® imaging agent identified malignant upper tract urothelial lesions with 100% specificity and sensitivity.
In the lower urinary tract, thirty-eight radical cystectomy specimens were incubated with pHLIP® conjugated with one of the NIRF dyes (ICG or IR800). In the thirty-eight bladders, eighty-one lesions were identified using fluorescent pHLIP®(specificity (97%) and sensitivity (100%)). White light cystoscopy did not detect 20.5% of lesions identified under NIRF cystoscopy (p&lt;.001). Normal tissue did not show any uptake by the construct; however, entrapment of the dye in the necrotic tumor bed was noted. All regions showing the NIRF signal of pHLIP® were confirmed by standard pathological analysis.
Conclusions: The ICG pHLIP® NIRF revealed additional lesions not seen with white light ex-vivo cystoscopy or preoperative ureteroscopy. pHLIP® based agents promise to improve diagnostic accuracy for urothelial carcinomas and may enable targeted treatment.
Citation Format: Borivoj Golijanin, Anna Moshnikova, Donald M. Engelman, Oleg A. Andreev, Yana K. Reshetnyak, Ali Amin, Dragan Golijanin. Ex-vivo targeting of urothelial carcinomas by fluorescent pHLIP imaging agents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1399.
Abstract 14: A new orally available drug for the treatment of metastatic cancers
Authors: Zhou Kun , Cheong Jae Eun , Zaffagni Michaela , Xu Yingjie , Sun Lijun , Zetter Bruce 
Published: August 2019

Abstract
Metastatic cancers account for the great majority of cancer deaths. We conducted a screen to indetify known drugs that selectively inhibit the viability of metastatic tumor cells. Results of the screen identified members of the FDA-approved benzimidazole methylcarbamate family (e.g. mebendazole (MBZ) and albendazole (ALB)) as potential therapies for metastatic disease. Earlier work also supports a role for this chemical family in the potential treatment of activity in multiple cancers, but progress has been stalled by their poor water solubility and poor bioavailability for systemic delivery to disseminated tumors. We therefore synthesized a novel compound (OBD9) containing the scaffold of MBZ coupled to an oxetane group to enhance aqueous solubility to 361 μM. OBD9 demonstrates significant cytotoxicity toward a variety of cancer cell types including colon, lung, and prostate cancers (IC50: 0.9-2 μM). In a mouse xenograft model of human A549 lung cancer cell line OBD9 dramatically inhibited the growth of established tumors at 30 or 90 μM without noticeable toxicity. In a mouse xenograft model using highly aggressive PCMLN3 prostate cancer cells, oral administration of OBD9 at 30 mg/kg also significantly repressed growth of established tumors with no visible toxicity.
We have studied the working mechanisms behind OBD9 and found that the Wnt signaling pathway is suppressed by OBD9 treatment. Both qPCR and Western blot data suggest that the beta-catenin/TCF complex in the Wnt signaling pathway are inhibited by OBD9. Among the downstream targets of Wnt signaling pathway, the oncogene cMyc is also significantly decreased in different cancers including colon, lung and prostate cancer. Overall, our in vitro and in vivo data suggest that OBD9 potentially represents a novel therapeutic option for multiple cancers especially metastatic cancer through targeting Wnt signaling pathway and the downstream oncogene cMyc.
Citation Format: Kun Zhou, Jae Eun Cheong, Michaela Zaffagni, Yingjie Xu, Lijun Sun, Bruce Zetter. A new orally available drug for the treatment of metastatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 14.
Abstract 140: Comprehensive analysis of immune evasion in breast cancer by single-cell RNA-seq
Authors: Yin Jianhua , Zhou Hanlin , Yan Chen , lv Ruqian , Wang Ting , He Chenyang , Huang Chen , Hou Yong , Zhu Shida , Wang Ling , Dean Michael , Wu Kui , Hu Hong , Li Guibo 
Published: August 2019

Abstract
The tumor microenvironment is composed of numerous cell types, including tumor, immune and stromal cells. Cancer cells interact with the tumor microenvironment to suppress anticancer immunity. In this study, we molecularly dissected the tumor microenvironment of breast cancer by single-cell RNA-seq. The breast tumor microenvironment was profiled by analyzing the single-cell transcriptomes of 52,163 cells from the tumor tissues of 15 breast cancer patients. The tumor cells and immune cells from individual patients were analyzed simultaneously at the single-cell level. Among more than 40,000 tumor cells, we identified distinct cell clusters with different molecular subtypes and gene signatures in the same tumor, which revealed intra-tumor heterogeneity in breast cancer. We comprehensively profiled the functional state of T cells, macrophages, B cells, CAFs in breast cancer tumor microenvironment, which highlight the immune cell and CAF diversity in the breast cancer TME. Moreover, we analyzed intercellular communication in the breast cancer TME using a dataset of human ligand receptor pairs, which showed distinct cell interaction models across tumors. The evolution of the tumor microenvironment during clinical treatment was dissected by comparing tumor microenvironment of breast cancer pre- and post-chemotherapy. This study investigated the diversity of the cell types in the tumor microenvironment and provided information on the mechanisms of escape from clearance by immune cells in breast cancer, which could be a beneficial resource for immunotherapy development.
Citation Format: Jianhua Yin, Hanlin Zhou, Chen Yan, Ruqian lv, Ting Wang, Chenyang He, Chen Huang, Yong Hou, Shida Zhu, Ling Wang, Michael Dean, Kui Wu, Hong Hu, Guibo Li. Comprehensive analysis of immune evasion in breast cancer by single-cell RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 140.
Abstract 1408: Diffuse optical spectroscopic imaging reveals regimen-dependent changes in breast tumors throughout neoadjuvant chemotherapy
Authors: Tank Anup , Peterson Hannah , Pera Vivian , Tabassum Syeda , Ko Naomi , Leproux Anais , Tromberg Bruce , Roblyer Darren 
Published: August 2019

Abstract
Diffuse Optical Spectroscopic Imaging (DOSI) is a non-invasive near-infrared imaging modality than can provide label-free functional and metabolic information about breast tumors, probing depths up to several centimeters. Previous work has shown that DOSI has prognostic value for pathological response at key timepoints during neoadjuvant (presurgical) chemotherapy (NAC), including baseline, 24 hours after the first infusion, week 1, and at the midpoint of therapy. To date there have been almost no reports on how specific NAC regimens affect the prognostic capability of DOSI. Here we present a large multi-center DOSI dataset consisting of 54 breast tumors and 313 unique measurements taken across three timepoints during NAC: Baseline, week 1, and midpoint of treatment. We will show for the first time that the manifestation of DOSI response parameters (oxyhemoglobin, de-oxyhemoglobin, water, and lipid) is highly dependent on the specific NAC regimen used. Subjects were treated with either a Maximum Tolerated Dose (MTD) regimen, in which a higher dose is administered less frequently, or a Metronomic (MET) regimen, in which a smaller dose is given more frequently. MTD regimen of cytotoxic agents has traditionally been the most effective method to treat breast cancer as it aims to kill the maximum amount of tumor cells before regrowth. MET administration of cytotoxic therapies has shown antiangiogenic properties aiming to limit toxic side effects and drug resistance, while potentially inducing tumor dormancy and immunomodulation. Subjects treated with MTD regimen and also responding to this treatment exhibited an oxyhemoglobin flare in the first day of NAC. In contrast, subjects treated with MET presented only small fluctuations in oxyhemoglobin throughout the first week of NAC. The oxyhemoglobin flare has been theorized to be induced by an inflammatory effect significant for cell death, which could be in response to specifically the MTD regimen and its higher dosing. This study indicates that the specific regimen must be considered when using DOSI for NAC monitoring. It also suggests DOSI may provide biological insight into the regimen-specific mechanisms of action.
Citation Format: Anup Tank, Hannah Peterson, Vivian Pera, Syeda Tabassum, Naomi Ko, Anais Leproux, Bruce Tromberg, Darren Roblyer. Diffuse optical spectroscopic imaging reveals regimen-dependent changes in breast tumors throughout neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1408.
Abstract 1411: Semi-quantitative mapping of oncological therapies with mass spectrometry imaging
Authors: Baluya Dodge , Shrestha Bindesh , Cressman Erik N. 
Published: August 2019

Abstract
Hepatocellular carcinoma (HCC) is one of the challenging cancers to treat with occurrence steadily rising in the United States. While surgical resection is considered curative, it is not available to patients who have underlying liver problems, such as chronic liver disease. Liver transplantation may be considered in these cases but recurrence is a possibility, and transplantation occurs for &lt;5% of all HCC cases. Doxorubicin (DXR), a drug derived from a natural product extracted from several wild strains of Streptomyces, is used to treat different types of cancer, particularly liver cancer such as HCC. While DXR use for treatment shows positive efficacy, the side effects such as cardiomyopathy and typhlitis, are easily triggered when the systemic concentration dose reaches a particular threshold. Also, there is no confirmation that the drug reaches the target area with a viable therapeutic concentration. In this work, we use mass spectrometry imaging (MSI) platform on Waters SYNAPT G2-Si MALDI to gather spatial information and quantity of the DXR to determine the delivery efficacy. To generate a calibration curve that is suitable for MSI, a phantom tissue template was created. Livers were extracted from pig and homogenized using a Qiagen Tissuelyzer with a 30% w/v in deionized water, and created DXR tissue homogenate solutions (20, 10, 5, 2, 1µM) using serial dilution. The resulting solutions were pipetted into a gelatin mold before it was frozen using liquid nitrogen and stored at -80 °C until needed. For the ‘unknown’ samples, the liver was explanted from a pig that was treated with doxorubicin, then flash-frozen using liquid nitrogen and kept at -80 °C until needed. The tissue was sectioned using a Leica cryotome and mounted on glass microscope slides. For each analysis, two adjacent sections were selected, one was submitted for MSI analysis and the other for IHC staining. A good correlation (R&gt;0.99) of the DXR signal from the tissue homogenates showed that the calibration curve could be used to comparably measure the DXR amount in the similar tissue type. MSI of the explanted liver showed the distribution of DXR towards a particular section. While this experiment showed only the response for DXR, this approach can be applied to other drug therapies to show the localization and concentration, thereby helping the effectivity assessment of the therapy complementary with the other evaluation tools for a successful treatment.
Citation Format: Dodge Baluya, Bindesh Shrestha, Erik N. Cressman. Semi-quantitative mapping of oncological therapies with mass spectrometry imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1411.