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1. A Deep Learning-Based Approach to Estimate Paneth Cell Granule Area in Celiac Disease

Author

Alharbi, Ebtihal, Rajaram, Ajay, Tech, M., Cote, Kevin, Farag, Mina, Maleki, Farhad, Gao, Zu-Hua, Maedler-Kron, Chelsea, Marcus, Victoria, and Fiset, Pierre Olivier

Subjects
Celiac disease -- Models -- Development and progression, Intestine, Small -- Physiological aspects -- Health aspects, Machine learning -- Usage -- Health aspects, Epithelial cells -- Physiological aspects -- Health aspects, Health
Abstract

* Context.--Changes in Paneth cell numbers can be associated with chronic inflammatory diseases of the gastrointestinal tract. So far, no consensus has been achieved on the number of Paneth cells and their relevance to celiac disease (CD). Objectives.--To compare crypt and Paneth cell granule areas between patients with CD and those without CD (non-CD) using an artificial intelligence-based solution. Design.--Hematoxylin-eosin-stained sections of duodenal biopsies from 349 patients at the McGill University Health Centre were analyzed. Of these, 185 had a history of CD and 164 were controls. Slides were digitized, and NoCodeSeg, a code-free workflow using open-source software (QuPath, DeepMIB), was implemented to train deep learning models to segment crypts and Paneth cell granules. The total area of the entire analyzed tissue, epithelium, crypts, and Paneth cell granules was documented for all slides, and comparisons were performed. Results.--A mean intersection-over-union score of 88.76% and 91.30% was achieved for crypt areas and Paneth cell granule segmentations, respectively. On normalization to total tissue area, the crypt to total tissue area in CD was increased and the Paneth cell granule area to total tissue area decreased when compared to non-CD controls. Conclusions.--Crypt hyperplasia was confirmed in CD compared to non-CD controls. The area of Paneth cell granules, an indirect measure of Paneth cell function, decreased with increasing severity of CD. More importantly, our study analyzed complete hematoxylin-eosin slide sections using an efficient and easy to use coding-free artificial intelligence workflow. doi: 10.5858/arpa.2023-0074-OA), Paneth cells were first described by Paneth in 1888. (1) They are normally found in the small intestine, right colon, and appendix. They are usually located at the base of [...]

Published
2024
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2. Machine Intelligence-Driven Classification of Cancer Patients-Derived Extracellular Vesicles using Fluorescence Correlation Spectroscopy: Results from a Pilot Study

Author

Uthamacumaran, Abicumaran, Abdouh, Mohamed, Sengupta, Kinshuk, Gao, Zu-hua, Forte, Stefano, Tsering, Thupten, Burnier, Julia V, and Arena, Goffredo

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Quantitative Biology - Biomolecules
Abstract

Patient-derived extracellular vesicles (EVs) that contains a complex biological cargo is a valuable source of liquid biopsy diagnostics to aid in early detection, cancer screening, and precision nanotherapeutics. In this study, we predicted that coupling cancer patient blood-derived EVs to time-resolved spectroscopy and artificial intelligence (AI) could provide a robust cancer screening and follow-up tools. Methods: Fluorescence correlation spectroscopy (FCS) measurements were performed on 24 blood samples-derived EVs. Blood samples were obtained from 15 cancer patients (presenting 5 different types of cancers), and 9 healthy controls (including patients with benign lesions). The obtained FCS autocorrelation spectra were processed into power spectra using the Fast-Fourier Transform algorithm and subjected to various machine learning algorithms to distinguish cancer spectra from healthy control spectra. Results and Applications: The performance of AdaBoost Random Forest (RF) classifier, support vector machine, and multilayer perceptron, were tested on selected frequencies in the N=118 power spectra. The RF classifier exhibited a 90% classification accuracy and high sensitivity and specificity in distinguishing the FCS power spectra of cancer patients from those of healthy controls. Further, an image convolutional neural network (CNN), ResNet network, and a quantum CNN were assessed on the power spectral images as additional validation tools. All image-based CNNs exhibited a nearly equal classification performance with an accuracy of roughly 82% and reasonably high sensitivity and specificity scores. Our pilot study demonstrates that AI-algorithms coupled to time-resolved FCS power spectra can accurately and differentially classify the complex patient-derived EVs from different cancer samples of distinct tissue subtypes., Comment: 23 pages, 6 figures

Published
2022
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4. Machine Learning Characterization of Cancer Patients-Derived Extracellular Vesicles using Vibrational Spectroscopies

Author

Uthamacumaran, Abicumaran, Elouatik, Samir, Abdouh, Mohamed, Berteau-Rainville, Michael, Gao, Zu-hua, and Arena, Goffredo

Subjects
Quantitative Biology - Other Quantitative Biology, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Physics - Biological Physics
Abstract

The early detection of cancer is a challenging problem in medicine. The blood sera of cancer patients are enriched with heterogeneous secretory lipid bound extracellular vesicles (EVs), which present a complex repertoire of information and biomarkers, representing their cell of origin, that are being currently studied in the field of liquid biopsy and cancer screening. Vibrational spectroscopies provide non-invasive approaches for the assessment of structural and biophysical properties in complex biological samples. In this pilot study, multiple Raman spectroscopy measurements were performed on the EVs extracted from the blood sera of 9 patients consisting of four different cancer subtypes (colorectal cancer, hepatocellular carcinoma, breast cancer and pancreatic cancer) and five healthy patients (controls). FTIR (Fourier Transform Infrared) spectroscopy measurements were performed as a complementary approach to Raman analysis, on two of the four cancer subtypes. The AdaBoost Random Forest Classifier, Decision Trees, and Support Vector Machines (SVM) distinguished the baseline corrected Raman spectra of cancer EVs from those of healthy controls (18 spectra) with a classification accuracy of above 90 percent when reduced to a spectral frequency range of 1800 to 1940 inverse cm and subjected to a 50:50 training: testing split. FTIR classification accuracy on 14 spectra showed an 80 percent classification accuracy. Our findings demonstrate that basic machine learning algorithms are powerful applied intelligence tools to distinguish the complex vibrational spectra of cancer patient EVs from those of healthy patients. These experimental methods hold promise as valid and efficient liquid biopsy for artificial intelligence-assisted early cancer screening., Comment: 41 pages

Published
2021
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5. PCSK7: A novel regulator of apolipoprotein B and a potential target against non-alcoholic fatty liver disease

Author

Sachan, Vatsal, Le Dévéhat, Maïlys, Roubtsova, Anna, Essalmani, Rachid, Laurendeau, Jean-Francois, Garçon, Damien, Susan-Resiga, Delia, Duval, Stéphanie, Mikaeeli, Sahar, Hamelin, Josée, Evagelidis, Alexandra, Chong, Michael, Paré, Guillaume, Chernetsova, Elizabeta, Gao, Zu-Hua, Robillard, Isabelle, Ruiz, Matthieu, Trinh, Vincent Quoc-Huy, Estall, Jennifer L., Faraj, May, Austin, Richard C., Sauvageau, Martin, Prat, Annik, Kiss, Robert S., and Seidah, Nabil G.

Published
2024
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7. Smooth muscle tumors of the gastrointestinal tract: an analysis of prognostic features in 407 cases

Author

Alpert, Lindsay, Al-Sabti, Ram, Graham, Rondell P, Pai, Rish K, Gonzalez, Raul S, Zhang, Xuefeng, Smith, Vanessa, Wang, Hanlin L, Westbrook, Lindsey, Goldblum, John R, Bakhshwin, Ahmed, Shetty, Sindhu, Klimstra, David S, Shia, Jinru, Askan, Gokce, Robert, Marie E, Thomas, Courtney, Frankel, Wendy L, Alsomali, Mohammed, Hagen, Catherine, Mostafa, Mohamed E, Feely, Michael M, Assarzadegan, Naziheh, Misdraji, Joseph, Shih, Angela R, Agostini-Vulaj, Diana, Meis, Jeanne M, Tang, Sherry, Chatterjee, Deyali, Kang, Liang-I, Hart, John, Lee, Sang Mee, Smith, Theresa, Yantiss, Rhonda K, Hissong, Erika M, Gao, Zu-hua, Wu, JingBo, Resnick, Murray B, Wu, Elizabeth Yiru, Pai, Reet K, Zhao, Lei, Doyle, Leona A, Chopra, Shefali, Panarelli, Nicole C, Hu, Shaomin, Longacre, Teri A, Raghavan, Shyam Sampath, Lauwers, Gregory Y, Ghayouri, Masoumeh, Cooper, Harry S, Nagarathinam, Rajeswari, Bellizzi, Andrew M, Kakar, Sanjay, Hosseini, Mojgan, Rong, Juan, Greenson, Joel K, Lamps, Laura W, Dong, Zachary, and Bronner, Mary P

Subjects
Cancer, Rare Diseases, Digestive Diseases, Adult, Aged, Aged, 80 and over, Disease Progression, Female, Gastrointestinal Neoplasms, Humans, Male, Middle Aged, Prognosis, Progression-Free Survival, Smooth Muscle Tumor, Medical and Health Sciences, Pathology
Abstract

Smooth muscle tumors represent the second most common mural mesenchymal neoplasm in the gastrointestinal tract, but established criteria for prognostic assessment of these tumors are lacking. A large cohort of surgically resected intramural gastrointestinal smooth muscle tumors from 31 institutions was analyzed to identify potential prognostic features. Pathologic features were assessed by expert gastrointestinal and/or soft tissue pathologists at each center. Immunohistochemical confirmation was required. A total of 407 cases from the esophagus (n = 97, 24%), stomach (n = 180, 44%), small bowel (n = 74, 18%), and colorectum (n = 56, 14%) were identified. Patients ranged in age from 19 to 92 years (mean 55 years), with a slight female predominance (57%). Mean tumor size was 5.4 cm, with the largest tumor measuring 29 cm. Disease progression following surgery, defined as local recurrence, metastasis, or disease-related death, occurred in 56 patients (14%). Colorectal tumors were most likely to progress, followed by small bowel and gastric tumors. None of the esophageal tumors in this series progressed. Receiver operator characteristic analysis identified optimal cutoffs of 9.8 cm and 3 mitoses/5 mm2 for discriminating between progressive and non-progressive tumors. Histologic features strongly associated with progression by univariate analysis included moderate-to-severe atypia, high cellularity, abnormal differentiation (defined as differentiation not closely resembling that of normal smooth muscle), tumor necrosis, mucosal ulceration, lamina propria involvement, and serosal involvement (P 10 cm and/or showing ≥3 mitoses/5 mm2 may behave aggressively, and therefore close clinical follow-up is recommended in these cases.

Published
2020

11. Gastrointestinal stromal tumors (GISTs) arising in uncommon locations: clinicopathologic features and risk assessment of esophageal, colonic, and appendiceal GISTs

Author

Hu, Shaomin, Alpert, Lindsay, Cates, Justin M.M., Gonzalez, Raul S., Graham, Rondell, Goldblum, John R., Bakhshwin, Ahmed, Shetty, Sindhu, Wang, Hanlin L., Lollie, Trang, Ma, Changqing, Siddique, Ayesha, Karamchandani, Dipti M., Chen, Fengming, Yantiss, Rhonda K., Hissong, Erika, Chatterjee, Deyali, Chopra, Shefali, Chen, Wei, Vazzano, Jennifer, Wang, Wei-Lien, Ai, Di, Lin, Jingmei, Zheng, Lan, Davis, Jessica L., Brinkerhoff, Brian, Breitbarth, Amanda, Yang, Michelle, Madahian, Sepideh, Panarelli, Nicole, Kuan, Kevin, Pomper, Jonathan, Longacre, Teri, Raghavan, Shyam, Misdraji, Joseph, Cui, Min, Yang, Zhaohai, Savant, Deepika, Harpaz, Noam, Chen, Xiuxu, Resnick, Murray, Wu, Elizabeth Yiru, Klimstra, David, Shia, Jinru, Vyas, Monika, Kakar, Sanjay, Choi, Won-Tak, Robert, Marie E., Li, Hongjie, Lee, Michael, Clark, Ian, Li, Yongchao, Cao, Wenqing, Chang, Qing, Bronner, Mary P., Dong, Zachary, Zhang, Wei, Buehler, Darya, Swanson, Paul E., Mantilla, Jose G., Bellizzi, Andrew M., Feely, Michael, Cooper, Harry S., Nagarathinam, Rajeswari, Pai, Rish, Hammer, Suntrea, Hosseini, Mojgan, Hu, JingJing, Westerhoff, Maria, Cheng, Jerome, Agostini-Vulaj, Diana, Lauwers, Gregory, Ghayouri, Masoumeh, Pezhouh, Maryam K., Zeng, Jianying, Xia, Rong, Yin, Feng, Zhang, Tao, Gao, Zu-hua, Demko, Nadine, Chen, Hannah H., Yu, Sanhong, and Hart, John

Published
2022
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12. Bioinspired Printable Tough Adhesives with In Situ Benignly Triggered Mechanical Enhancements.

Author

Ma, Zhenwei, Huo, Ran, Nottegar, Alexander, Chung‐Tze‐Cheong, Christopher, Gao, Qiman, Lan, Xiaoyi, Gao, Zu‐hua, and Li, Jianyu

Subjects
TISSUES, SALINE solutions, CONNECTIVE tissues, HUMAN body, THREE-dimensional printing
Abstract

Adhesives can intimately connect humans to machines, seamlessly bond diverse tissues in the human body, and manage various diseases. However, the precise spatial control of wet and tough adhesion of biocompatible hydrogels on biological tissues remains a major challenge. Inspired by the bioglue secreted by sandcastle worms, the design of printable tough adhesives (PTAs) is proposed, a supramolecular hydrogel that can be printed into defined structures, in situ mechanically reinforced into a tough matrix with physiologically relevant benign triggers, and strongly adhere to diverse substrates. With carefully selected polymer components and ratios, it is discovered that the 3D printed PTAs can achieve a marked increase in toughness, tensile strength, and stiffness after being immersed in water/saline solution or attached to biological tissues. To assess the robust toughening mechanism triggered by the supramolecular interactions, the effects of polymer content and pH on the mechanical performance of PTAs and the kinetics of their triggered reinforcement are thoroughly investigated. The potential of PTAs is further demonstrated for manufacturing tough connective tissue mimetics, controlling patterned bioadhesion, and designing programmable 4D soft robotics. The bioinspired, printable, benignly triggerable, and adhesive supramolecular PTAs are expected to find broad applications in engineering and medicine. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Histopathological Growth Patterns Determine the Outcomes of Colorectal Cancer Liver Metastasis Following Liver Resection.

Author

Krzywoń, Lucyna, Lazaris, Anthoula, Petrillo, Stephanie K., Zlotnik, Oran, Gao, Zu-Hua, and Metrakos, Peter

Subjects
LIVER tumors, ACADEMIC medical centers, CANCER invasiveness, CANCER relapse, COLORECTAL cancer, DECISION making in clinical medicine, TREATMENT effectiveness, DESCRIPTIVE statistics, RETROSPECTIVE studies, MULTIVARIATE analysis, METASTASIS, HEPATECTOMY, GENETIC mutation, COMPARATIVE studies, OVERALL survival
Abstract

Simple Summary: The survival of patients with colorectal cancer liver metastasis can be prognosticated based on the presence or absence of desmoplastic histopathologic growth patterns. Patient survival is improved if the liver tumor has at least a 50% desmoplastic histopathologic growth pattern. Determing the patients tumor histopathological features is essential to prognosis outcomes and treatment management. Introduction: Colorectal cancer liver metastasis (CRCLM) remains a lethal diagnosis, with an overall 5-year survival rate of 5–10%. Two distinct histopathological growth patterns (HGPs) of CRCLM are known to have significantly differing rates of patient survival and response to treatment. We set out to review the results of 275 patients who underwent liver resection for CRCLM at the McGill University Health Center (MUHC) and analyze their clinical outcome, mutational burden, and pattern of cancer progression in light of their HGPs, and to consider their potential effect on surgical decision making. Methods: We performed a retrospective multivariate analysis on clinical data from patients with CRCLM (n = 275) who underwent liver resection at the McGill University Health Center (MUHC). All tumors were scored using international consensus guidelines by pathologists trained in HGP scoring. Results: A total of 109 patients (42.2%) were classified as desmoplastic and angiogenic, whereas 149 patients (57.7%) were non-desmoplastic and vessel co-opting. The 5-year survival rates for angiogenic patients compared with vessel co-opting patients were 47.1% and 13%, respectively (p < 0.0001). Multivariate analysis showed patients with vessel co-opting CRCLM had a higher incidence of extrahepatic metastatic disease (p = 0.0215) compared with angiogenic CRCLM. Additionally, KRAS mutation status was a marker of increased likelihood of disease recurrence (p = 0.0434), as was increased number of liver tumors (p = 0.0071) and multiple sites of extrahepatic metastatic disease (p < 0.0001). Conclusions: Multivariate analysis identified key clinical prognostic and molecular features correlating with the two HGPs. Determining liver tumor HGPs is essential for patient prognostication and treatment optimization. [ABSTRACT FROM AUTHOR]

Published
2024
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14. A Deep Learning-Based Pipeline for Celiac Disease Diagnosis Using Histopathological Images

Author

Maleki, Farhad, Cote, Kevin, Najafian, Keyhan, Ovens, Katie, Miao, Yan, Zakarian, Rita, Reinhold, Caroline, Forghani, Reza, Savadjiev, Peter, Gao, Zu-hua, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tsapatsoulis, Nicolas, editor, Panayides, Andreas, editor, Theocharides, Theo, editor, Lanitis, Andreas, editor, Pattichis, Constantinos, editor, and Vento, Mario, editor

Published
2021
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18. Tough Adhesive Puncture Sealing Sutures with Swelling Triggered Bioadhesion for Enhanced Wound Closure.

Author

Ma, Zhenwei, Nguyen, Alex, Chung‐Tze‐Cheong, Christopher, Mazy, David, Ghezelbash, Farshid, Yang, Zhen, Liu, Yin, Liu, Shiyu, Lamer, Stéphanie, Gao, Zu‐hua, Obuseh, Favour, Freedman, Benjamin R., Nault, Marie‐Lyne, and Li, Jianyu

Subjects
SURGICAL equipment, BIOMEDICAL adhesives, SUTURES, SURGICAL site infections, SUTURING, BIOLOGICAL interfaces
Abstract

Surgical sutures are gold‐standard wound closure devices. However, they are unable to form a tight seal with surrounding tissues, raising the risks of body fluid leakage and surgical site infection. Additionally, the use of sutures can result in cracking at suture roots, damage and micro‐trauma to soft tissues due to the slicing and compression of suture fibers after their placement. Bioadhesives capable of mimicking natural biological interfaces are appealing alternatives, but they cannot achieve the same level of strength as conventional surgical sutures. Here, a tough adhesive puncture sealing (TAPS) suture, featuring swelling‐triggered bioadhesion to mend the gap between the suture and the surrounding tissues with a soft yet tough adhesive interface is reported. This unique design principle of TAPS sutures is applicable to diverse soft tissues of various defect sizes and can be controlled by modulating the hydrogel swelling kinetics. The advantages of the TAPS sutures for meniscal tear repair and intestine tissue sealing ex vivo, corroborates their favorable applications in managing mechanically active musculoskeletal and gastrointestinal tissues are demonstrated. The design and performance of the TAPS sutures offer extensive possibilities for redesigning surgical tools and developing next‐generation medical devices for wound management and tissue repair. [ABSTRACT FROM AUTHOR]

Published
2024
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21. PCSK7: A novel regulator of apolipoprotein B and a potential target against non-alcoholic fatty liver disease

Author

Sachan, Vatsal, primary, Le Dévéhat, Maïlys, additional, Roubtsova, Anna, additional, Essalmani, Rachid, additional, Laurendeau, Jean-Francois, additional, Garçon, Damien, additional, Susan-Resiga, Delia, additional, Duval, Stéphanie, additional, Mikaeeli, Sahar, additional, Hamelin, Josée, additional, Evagelidis, Alexandra, additional, Chong, Michael, additional, Paré, Guillaume, additional, Chernetsova, Elizabeta, additional, Gao, Zu-Hua, additional, Robillard, Isabelle, additional, Ruiz, Matthieu, additional, Trinh, Vincent Quoc-Huy, additional, Estall, Jennifer L., additional, Faraj, May, additional, Austin, Richard C., additional, Sauvageau, Martin, additional, Prat, Annik, additional, Kiss, Robert S., additional, and Seidah, Nabil G., additional

Published
2023
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23. Claudin-2 promotes colorectal cancer liver metastasis and is a biomarker of the replacement type growth pattern

Author

Tabariès, Sébastien, Annis, Matthew G., Lazaris, Anthoula, Petrillo, Stephanie K., Huxham, Jennifer, Abdellatif, Amri, Palmieri, Vincent, Chabot, Jaclyn, Johnson, Radia M., Van Laere, Steven, Verhoef, Cornelis, Hachem, Yasmina, Yumeen, Sara, Meti, Nicholas, Omeroglu, Atilla, Altinel, Gulbeyaz, Gao, Zu-Hua, Yu, Alan S. L., Grünhagen, Dirk J., Vermeulen, Peter, Metrakos, Peter, and Siegel, Peter M.

Published
2021
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27. Contributors

Author

Aranda, Ana, primary, Belsham, Denise D., additional, Bozon, Véronique, additional, Brandi, Maria Luisa, additional, Brigante, Giulia, additional, Bruneau, Gilles, additional, Camper, Sally A., additional, Casarini, Livio, additional, Castellano, Juan M., additional, Cheung, Leonard Y.M., additional, Cianferotti, Luisella, additional, Clément, Frédérique, additional, Coolen, Lique M., additional, Crépieux, Pascale, additional, Dalvi, Prasad, additional, Dong, Lily Q., additional, Ezzat, Shereen, additional, Fiordelisio, Tatiana, additional, Fowkes, Robert C., additional, Gagniac, Laurine, additional, Gallay, Nathalie, additional, Gao, Zu-hua, additional, Gluckman, Peter D., additional, Gomez-Hernandez, Karen, additional, Goodman, Robert L., additional, Guillou, Florian, additional, Hadley, Jason T., additional, Hanson, Mark A., additional, Hanyaloglu, Aylin C., additional, Ishii, Tomohiro, additional, Janovick, Jo Ann, additional, Jean-Alphonse, Frédéric, additional, Jiménez, José Nicolás, additional, Jurado, Constanza Contreras, additional, Kaddour, Nancy, additional, Lehman, Michael N., additional, Liu, Jun-Li, additional, Liu, Zhenqi, additional, Loganathan, Neruja, additional, Low, Felicia M., additional, Martínez-Iglesias, Olaia, additional, McArdle, Craig A., additional, Mcilwraith, Emma K., additional, Mercado, Moises, additional, De Pascali, Francesco, additional, Pellissier, Lucie P., additional, Pérez Millán, María Inés, additional, Pincas, Hanna, additional, Poupon, Anne, additional, Raynaud, Pauline, additional, Reiter, Eric, additional, Rodríguez-Vázquez, Elvira, additional, Romagnoli, Cecilia, additional, Ruf-Zamojski, Frederique, additional, Ruiz-Llorente, Lidia, additional, Ryu, Jiyoon, additional, Santi, Daniele, additional, Sealfon, Stuart C., additional, Simoni, Manuela, additional, Tahir, Shifa, additional, Tateno, Toru, additional, Tena-Sempere, Manuel, additional, Torres, Nimbe, additional, Tovar, Armando R., additional, Tran, Andy, additional, Tsaneva-Atanasova, Krasimira, additional, Turgeon, Judith L., additional, Ulloa-Aguirre, Alfredo, additional, Vargas-Castillo, Ariana, additional, Vilardaga, Jean-Pierre, additional, Voliotis, Margaritis, additional, White, Alex D., additional, Xega, Viktoria, additional, Yvinec, Romain, additional, and Zariñán, Teresa, additional

Published
2021
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28. Corrigendum to “PCSK7: A novel regulator of apolipoprotein B and a potential target against non-alcoholic fatty liver disease” [Metabolism Volume 150, January 2024, 155736, PMID: 7967646]

Author

Sachan, Vatsal, LeDévéhat, Maïlys, Roubtsova, Anna, Essalmani, Rachid, Laurendeau, Jean-Francois, Garçon, Damien, Susan-Sesiga, Delia, Duval, Stéphanie, Mikaeeli, Sahar, Hamelin, Josée, Evagelidis, Alexandra, Chong, Michael, Paré, Guillaume, Chernetsova, Elizabeta, Gao, Zu-Hua, Robillard, Isabelle, Ruiz, Matthieu, Trinh, Vincent Quoc-Huy, Estall, Jennifer L., Faraj, May, Austin, Richard C., Sauvageau, Martin, Prat, Annik, Kiss, Robert S., and Seidah, Nabil G.

Published
2024
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32. Supplementary Figure 10 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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33. Supplementary Figure 4 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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34. Supplementary Figure 5 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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35. Supplementary Figure 2 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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36. Supplementary Table 2 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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37. Supplementary Figure 7 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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38. Supplementary Figure 9 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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39. Supplementary Figure 8 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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40. Supplementary Table 3 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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41. Supplementary Figure 3 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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42. Supplementary Table 1 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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43. Supplementary Figure 6 from A Preclinical Trial and Molecularly Annotated Patient Cohort Identify Predictive Biomarkers in Homologous Recombination–deficient Pancreatic Cancer

Author

Wang, Yifan, primary, Park, Jin Yong Patrick, primary, Pacis, Alain, primary, Denroche, Robert E., primary, Jang, Gun Ho, primary, Zhang, Amy, primary, Cuggia, Adeline, primary, Domecq, Celine, primary, Monlong, Jean, primary, Raitses-Gurevich, Maria, primary, Grant, Robert C., primary, Borgida, Ayelet, primary, Holter, Spring, primary, Stossel, Chani, primary, Bu, Simeng, primary, Masoomian, Mehdi, primary, Lungu, Ilinca M., primary, Bartlett, John M.S., primary, Wilson, Julie M., primary, Gao, Zu-Hua, primary, Riazalhosseini, Yasser, primary, Asselah, Jamil, primary, Bouganim, Nathaniel, primary, Cabrera, Tatiana, primary, Boucher, Louis-Martin, primary, Valenti, David, primary, Biagi, James, primary, Greenwood, Celia M.T., primary, Polak, Paz, primary, Foulkes, William D., primary, Golan, Talia, primary, O'Kane, Grainne M., primary, Fischer, Sandra E., primary, Knox, Jennifer J., primary, Gallinger, Steven, primary, and Zogopoulos, George, primary

Published
2023
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44. Data from TNF Receptor-2 Facilitates an Immunosuppressive Microenvironment in the Liver to Promote the Colonization and Growth of Hepatic Metastases

Author

Ham, Boram, primary, Wang, Ni, primary, D'Costa, Zarina, primary, Fernandez, Maria Celia, primary, Bourdeau, France, primary, Auguste, Patrick, primary, Illemann, Martin, primary, Eefsen, Rikke Loevendahl, primary, Høyer-Hansen, Gunilla, primary, Vainer, Ben, primary, Evrard, Maximilien, primary, Gao, Zu-Hua, primary, and Brodt, Pnina, primary

Published
2023
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45. Supplementary Figures from TNF Receptor-2 Facilitates an Immunosuppressive Microenvironment in the Liver to Promote the Colonization and Growth of Hepatic Metastases

Author

Ham, Boram, primary, Wang, Ni, primary, D'Costa, Zarina, primary, Fernandez, Maria Celia, primary, Bourdeau, France, primary, Auguste, Patrick, primary, Illemann, Martin, primary, Eefsen, Rikke Loevendahl, primary, Høyer-Hansen, Gunilla, primary, Vainer, Ben, primary, Evrard, Maximilien, primary, Gao, Zu-Hua, primary, and Brodt, Pnina, primary

Published
2023
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46. Supplementary Figure legends from TNF Receptor-2 Facilitates an Immunosuppressive Microenvironment in the Liver to Promote the Colonization and Growth of Hepatic Metastases

Author

Ham, Boram, primary, Wang, Ni, primary, D'Costa, Zarina, primary, Fernandez, Maria Celia, primary, Bourdeau, France, primary, Auguste, Patrick, primary, Illemann, Martin, primary, Eefsen, Rikke Loevendahl, primary, Høyer-Hansen, Gunilla, primary, Vainer, Ben, primary, Evrard, Maximilien, primary, Gao, Zu-Hua, primary, and Brodt, Pnina, primary

Published
2023
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47. Supplementary tables from TNF Receptor-2 Facilitates an Immunosuppressive Microenvironment in the Liver to Promote the Colonization and Growth of Hepatic Metastases

Author

Ham, Boram, primary, Wang, Ni, primary, D'Costa, Zarina, primary, Fernandez, Maria Celia, primary, Bourdeau, France, primary, Auguste, Patrick, primary, Illemann, Martin, primary, Eefsen, Rikke Loevendahl, primary, Høyer-Hansen, Gunilla, primary, Vainer, Ben, primary, Evrard, Maximilien, primary, Gao, Zu-Hua, primary, and Brodt, Pnina, primary

Published
2023
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48. PCSK7: a Novel Regulator of Apolipoprotein B and a Potential Target Against Non-Alcoholic Fatty Liver Disease

Author

Seidah, Nabil, primary, Sachan, Vatsal, additional, Dévéhat, Mailys Le, additional, Roubtsova, Anna, additional, Essalmani, Rachid, additional, Garçon, Damien, additional, Susan-Resiga, Delia, additional, Duval, Stéphanie, additional, Mikaeeli, Sahar, additional, Hamelin, Josée, additional, Evagelidis, Alexandra, additional, Chong, Michael, additional, Pare, Guillaume, additional, Chernetsova, Elizabeta, additional, Gao, Zu-hua, additional, Robillard, Isabelle, additional, Ruiz, Matthieu, additional, Trinh, Vincent Quoc-Huy, additional, Estall, Jennifer, additional, Faraj, May, additional, Laurendeau, Jean-Francois, additional, Austin, Richard, additional, Sauvageau, Martin, additional, Prat, Annik, additional, and Kiss, Robert Scott, additional

Published
2023
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