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3. A Genomically and Clinically Annotated Patient-Derived Xenograft (PDX) Resource for Preclinical Research in Non-Small Cell Lung Cancer

Author

Woo, Xing Yi, Srivastava, Anuj, Mack, Philip C, Graber, Joel H, Sanderson, Brian J, Lloyd, Michael W, Chen, Mandy, Domanskyi, Sergii, Gandour-Edwards, Regina, Tsai, Rebekah A, Keck, James, Cheng, Mingshan, Bundy, Margaret, Jocoy, Emily L, Riess, Jonathan W, Holland, William, Grubb, Stephen C, Peterson, James G, Stafford, Grace A, Paisie, Carolyn, Neuhauser, Steven B, Karuturi, R Krishna Murthy, George, Joshy, Simons, Allen K, Chavaree, Margaret, Tepper, Clifford G, Goodwin, Neal, Airhart, Susan D, Lara, Primo N, Openshaw, Thomas H, Liu, Edison T, Gandara, David R, and Bult, Carol J

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Orphan Drug, Lung Cancer, Biotechnology, Genetics, Human Genome, Rare Diseases, Cancer, Lung, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, Good Health and Well Being, Humans, Animals, Carcinoma, Non-Small-Cell Lung, Lung Neoplasms, Heterografts, Xenograft Model Antitumor Assays, Adenocarcinoma of Lung, Disease Models, Animal, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research.SignificancePatient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

Published
2022

6. Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer

Author

Ravanmehr, Vida, Blau, Hannah, Cappelletti, Luca, Fontana, Tommaso, Carmody, Leigh, Coleman, Ben, George, Joshy, Reese, Justin, Joachimiak, Marcin, Bocci, Giovanni, Hansen, Peter, Bult, Carol, Rueter, Jens, Casiraghi, Elena, Valentini, Giorgio, Mungall, Christopher, Oprea, Tudor I, and Robinson, Peter N

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Cancer, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Bioinformatics and computational biology
Abstract

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.

Published
2021

7. Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

Author

Talhouk, Aline, George, Joshy, Wang, Chen, Budden, Timothy, Tan, Tuan Zea, Chiu, Derek S, Kommoss, Stefan, San Leong, Huei, Chen, Stephanie, Intermaggio, Maria P, Gilks, Blake, Nazeran, Tayyebeh M, Volchek, Mila, Elatre, Wafaa, Bentley, Rex C, Senz, Janine, Lum, Amy, Chow, Veronica, Sudderuddin, Hanwei, Mackenzie, Robertson, Leong, Samuel CY, Liu, Geyi, Johnson, Dustin, Chen, Billy, Group, AOCS, Alsop, Jennifer, Banerjee, Susana N, Behrens, Sabine, Bodelon, Clara, Brand, Alison H, Brinton, Louise, Carney, Michael E, Chiew, Yoke-Eng, Cushing-Haugen, Kara L, Cybulski, Cezary, Ennis, Darren, Fereday, Sian, Fortner, Renée T, García-Donas, Jesús, Gentry-Maharaj, Aleksandra, Glasspool, Rosalind, Goranova, Teodora, Greene, Casey S, Haluska, Paul, Harris, Holly R, Hendley, Joy, Hernandez, Brenda Y, Herpel, Esther, Jimenez-Linan, Mercedes, Karpinskyj, Chloe, Kaufmann, Scott H, Keeney, Gary L, Kennedy, Catherine J, Köbel, Martin, Koziak, Jennifer M, Larson, Melissa C, Lester, Jenny, Lewsley, Liz-Anne, Lissowska, Jolanta, Lubiński, Jan, Luk, Hugh, Macintyre, Geoff, Mahner, Sven, McNeish, Iain A, Menkiszak, Janusz, Nevins, Nikilyn, Osorio, Ana, Oszurek, Oleg, Palacios, José, Hinsley, Samantha, Pearce, Celeste L, Pike, Malcolm C, Piskorz, Anna M, Ray-Coquard, Isabelle, Rhenius, Valerie, Rodriguez-Antona, Cristina, Sharma, Raghwa, Sherman, Mark E, De Silva, Dilrini, Singh, Naveena, Sinn, Peter, Slamon, Dennis, Song, Honglin, Steed, Helen, Stronach, Euan A, Thompson, Pamela J, Tołoczko, Aleksandra, Trabert, Britton, Traficante, Nadia, Tseng, Chiu-Chen, Widschwendter, Martin, Wilkens, Lynne R, Winham, Stacey J, Winterhoff, Boris, Beeghly-Fadiel, Alicia, Benitez, Javier, Berchuck, Andrew, Brenton, James D, Brown, Robert, and Chang-Claude, Jenny

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Orphan Drug, Genetics, Ovarian Cancer, Women's Health, Cancer Genomics, Precision Medicine, Cancer, Human Genome, 4.2 Evaluation of markers and technologies, Good Health and Well Being, Aged, Algorithms, Cystadenoma, Serous, Female, Gene Expression Regulation, Neoplastic, Humans, Lymphocytes, Tumor-Infiltrating, Middle Aged, Neoplasm Grading, Neoplasm Proteins, Neoplasm, Residual, Ovarian Neoplasms, Transcriptome, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

PurposeGene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features.Experimental designAdopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting.ResultsGene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations.ConclusionsWe validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

Published
2020

10. Single-cell analysis of human glioma and immune cells identifies S100A4 as an immunotherapy target

Author

Abdelfattah, Nourhan, Kumar, Parveen, Wang, Caiyi, Leu, Jia-Shiun, Flynn, William F., Gao, Ruli, Baskin, David S., Pichumani, Kumar, Ijare, Omkar B., Wood, Stephanie L., Powell, Suzanne Z., Haviland, David L., Parker Kerrigan, Brittany C., Lang, Frederick F., Prabhu, Sujit S., Huntoon, Kristin M., Jiang, Wen, Kim, Betty Y. S., George, Joshy, and Yun, Kyuson

Published
2022
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12. Predominance of genetically diverse ESBL Escherichia coli identified in resistance mapping of Vembanad Lake, the largest fresh-cum-brackishwater lake of India

Author

Vaiyapuri, Murugadas, Sebastian, Anna SherinPulithara, George, Iris, Variem, Sandhya Soolamkandath, Vasudevan, Radhakrishnan Nair, George, Joshy Chalil, Badireddy, Madhusudana Rao, Sivam, Visnuvinayagam, Peeralil, Shaheer, Sanjeev, Devi, Thandapani, Muthulakshmi, Moses, Sheela Albert, Nagarajarao, Ravishankar Chandragiri, and Mothadaka, Mukteswar Prasad

Published
2021
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16. Computational inference of a genomic pluripotency signature in human and mouse stem cells

Author

Kurum, Esra, Benayoun, Bérénice A, Malhotra, Ankit, George, Joshy, and Ucar, Duygu

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Stem Cell Research, Stem Cell Research - Nonembryonic - Human, Stem Cell Research - Nonembryonic - Non-Human, Biotechnology, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Animals, Cell Line, Computational Biology, Embryonic Stem Cells, Epigenesis, Genetic, Genome, High-Throughput Nucleotide Sequencing, Humans, Mice, Pluripotent Stem Cells, Pluripotency, Epigenomics, Computational biology, Least absolute shrinkage and selection operator, Embryonic stem cells, Medical and Health Sciences, Bioinformatics, Biological sciences
Abstract

UnlabelledRecent analyses of next-generation sequencing datasets have shown that cell-specific regulatory elements in stem cells are marked with distinguishable patterns of transcription factor (TF) binding and epigenetic marks. For example, we recently demonstrated that promoters of cell-specific genes are covered with expanded trimethylation of histone H3 at lysine 4 (H3K4me3) marks (i.e., broad H3K4me3 domains). Moreover, binding of specific TFs, such as OCT4, NANOG, and SOX2, have been shown to play a critical role in maintaining the pluripotency of stem cells. Despite these observations, a systematic exploration of genomic and epigenomic features of stem-cell-specific gene promoters has not been conducted. Advanced machine-learning models can capture distinguishable genomic and epigenomic characteristics of stem-cell-specific promoters by taking advantage of the wealth of publicly available datasets. Here, we propose a three-step framework to discover novel data characteristics of high-throughput next generation sequencing datasets that distinguish pluripotency genes in human and mouse embryonic stem cells (ESCs). Our framework involves: i) feature extraction to identify novel features of genomic datasets; ii) feature selection using a logistic regression model combined with the Least Absolute Shrinkage and Selection Operator (LASSO) method to find the most critical datasets and features; and iii) cross validation with features selected using LASSO method to assess the predictive power of selected data features in distinguishing pluripotency genes. We show that specific epigenetic marks, and specific features of these marks, are enriched at pluripotency gene promoters. Moreover, we also assess both the individual and combined effect of TF binding, epigenetic mark deposition, gene expression datasets for marking pluripotency genes. Our findings are consistent with the existence of a conserved, complex and integrative genomic signature in ESCs that can be exploited to flag important candidate pluripotency genes. They also validate our computational framework for fostering a deeper understanding of genomic datasets in stem cells, in the future, could be extended to study cell-type-specific genomic landscapes in other cell types.ReviewersThis article was reviewed by Zoltan Gaspari and Piotr Zielenkiewicz.

Published
2016

22. ABCA transporter gene expression and poor outcome in epithelial ovarian cancer.

Author

Hedditch, Ellen L, Gao, Bo, Russell, Amanda J, Lu, Yi, Emmanuel, Catherine, Beesley, Jonathan, Johnatty, Sharon E, Chen, Xiaoqing, Harnett, Paul, George, Joshy, Australian Ovarian Cancer Study Group, Williams, Rebekka T, Flemming, Claudia, Lambrechts, Diether, Despierre, Evelyn, Lambrechts, Sandrina, Vergote, Ignace, Karlan, Beth, Lester, Jenny, Orsulic, Sandra, Walsh, Christine, Fasching, Peter, Beckmann, Matthias W, Ekici, Arif B, Hein, Alexander, Matsuo, Keitaro, Hosono, Satoyo, Nakanishi, Toru, Yatabe, Yasushi, Pejovic, Tanja, Bean, Yukie, Heitz, Florian, Harter, Philipp, du Bois, Andreas, Schwaab, Ira, Hogdall, Estrid, Kjaer, Susan K, Jensen, Allan, Hogdall, Claus, Lundvall, Lene, Engelholm, Svend Aage, Brown, Bob, Flanagan, James, Metcalf, Michelle D, Siddiqui, Nadeem, Sellers, Thomas, Fridley, Brooke, Cunningham, Julie, Schildkraut, Joellen, Iversen, Ed, Weber, Rachel P, Berchuck, Andrew, Goode, Ellen, Bowtell, David D, Chenevix-Trench, Georgia, deFazio, Anna, Norris, Murray D, MacGregor, Stuart, Haber, Michelle, and Henderson, Michelle J

Subjects
Australian Ovarian Cancer Study Group, Humans, Neoplasms, Glandular and Epithelial, Cystadenocarcinoma, Serous, Ovarian Neoplasms, ATP-Binding Cassette Transporters, RNA, Messenger, Cell Movement, Gene Expression Regulation, Neoplastic, Polymorphism, Single Nucleotide, Female, Neoplastic Stem Cells, Genome-Wide Association Study, Kaplan-Meier Estimate, Real-Time Polymerase Chain Reaction, Neoplasm Grading, ATP Binding Cassette Transporter 1, Carcinoma, Ovarian Epithelial, Ovarian Cancer, Rare Diseases, Biotechnology, Genetics, Cancer, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

ATP-binding cassette (ABC) transporters play various roles in cancer biology and drug resistance, but their association with outcomes in serous epithelial ovarian cancer (EOC) is unknown. The relationship between clinical outcomes and ABC transporter gene expression in two independent cohorts of high-grade serous EOC tumors was assessed with real-time quantitative polymerase chain reaction, analysis of expression microarray data, and immunohistochemistry. Associations between clinical outcomes and ABCA transporter gene single nucleotide polymorphisms were tested in a genome-wide association study. Impact of short interfering RNA-mediated gene suppression was determined by colony forming and migration assays. Association with survival was assessed with Kaplan-Meier analysis and log-rank tests. All statistical tests were two-sided. Associations with outcome were observed with ABC transporters of the "A" subfamily, but not with multidrug transporters. High-level expression of ABCA1, ABCA6, ABCA8, and ABCA9 in primary tumors was statistically significantly associated with reduced survival in serous ovarian cancer patients. Low levels of ABCA5 and the C-allele of rs536009 were associated with shorter overall survival (hazard ratio for death = 1.50; 95% confidence interval [CI] =1.26 to 1.79; P = 6.5e-6). The combined expression pattern of ABCA1, ABCA5, and either ABCA8 or ABCA9 was associated with particularly poor outcome (mean overall survival in group with adverse ABCA1, ABCA5 and ABCA9 gene expression = 33.2 months, 95% CI = 26.4 to 40.1; vs 55.3 months in the group with favorable ABCA gene expression, 95% CI = 49.8 to 60.8; P = .001), independently of tumor stage or surgical debulking status. Suppression of cholesterol transporter ABCA1 inhibited ovarian cancer cell growth and migration in vitro, and statin treatment reduced ovarian cancer cell migration. Expression of ABCA transporters was associated with poor outcome in serous ovarian cancer, implicating lipid trafficking as a potentially important process in EOC.

Published
2014

24. Immunosuppressive tumor microenvironment of osteosarcoma

Author

Taylor, Aaron Michael, primary, Shing Ng, Patrick Kwok, additional, Harder, Jeffrey M., additional, Kumar, Parveen, additional, Dzis, Alissa M., additional, Jillette, Nathaniel L., additional, Goodspeed, Andrew, additional, Bodlak, Avery, additional, Wu, Qian, additional, Isakoff, Michael S., additional, George, Joshy, additional, Grassmann, Jessica D.S., additional, Luo, Diane, additional, Flynn, William F., additional, Courtois, Elise T., additional, Robson, Paul, additional, Hayashi, Masanori, additional, Paolillo, Alini Trujillo, additional, de Toledo, Silvia Regina Caminada, additional, Balarezo, Fabiola Sara, additional, Lindsay, Adam D., additional, Hoang, Bang, additional, and Lau, Ching C., additional

Published
2023
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26. 923 Characterization and clinical significance of the intra and inter-tumor spatial immune heterogeneity using 3-dimensional multiplexed phenotyping in non-small cell lung cancer

Author

Rodas, Miguel Lopez de, primary, Frohock, Zachary, additional, Liu, Xiao, additional, Vilarino, Noelia, additional, Ahumada, Viviana, additional, Gettinger, Scott, additional, Murthy Karuturi, R Krishna, additional, George, Joshy, additional, Li, Yi, additional, and Schalper, Kurt, additional

Published
2023
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32. Genome Informatics

Author

Kesarwani, Anil K., primary, Malhotra, Ankit, additional, Srivastava, Anuj, additional, Ananda, Guruprasad, additional, Ashoor, Haitham, additional, Kumar, Parveen, additional, Kesharwani, Rupesh K., additional, Sarsani, Vishal K., additional, Li, Yi, additional, George, Joshy, additional, and Karuturi, R. Krishna Murty, additional

Published
2019
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33. Supplementary Table 5 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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34. Supplementary Table 7 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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35. Abstract 5871: Pan-cancer myeloid cell analysis at the single cell level reveals the influence of distinct organ sites in myeloid cell phenotypes and support targeting S100A4 to reverse immune suppression

Author

Abdelfattah, Nourhan, primary, Kumar, Parveen, additional, Wang, Caiyi, additional, Leu, Jia-Shiun, additional, Baskin, David, additional, Flynn, William, additional, Gao, Ruli, additional, Pichumani, Kumar, additional, Ijare, Omkar, additional, Wood, Stephanie, additional, Powell, Suzanne, additional, Haviland, David, additional, Kerrigan, Brittany Parker, additional, Lang, Frederick, additional, Prabhu, Sujit, additional, Huntoon, Kristin, additional, Jiang, Wen, additional, Kim, Betty, additional, George, Joshy, additional, and Yun, Kyuson, additional

Published
2023
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36. Supplementary Table 8 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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37. Supplementary Table 9 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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38. Supplementary Figures and Tables 1-2 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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39. Supplementary Table 4 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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40. Supplementary Table 6 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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41. Supplementary Table 3 from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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42. Data from Cancer Stem Cells, not Bulk Tumor Cells, Determine Mechanisms of Resistance to SMO Inhibitors

Author

George, Joshy, primary, Chen, Yaohui, primary, Abdelfattah, Nourhan, primary, Yamamoto, Keiko, primary, Gallup, Thomas D., primary, Adamson, Scott I., primary, Rybinski, Brad, primary, Srivastava, Anuj, primary, Kumar, Parveen, primary, Lee, Min Gyu, primary, Baskin, David S., primary, Jiang, Wen, primary, Choi, Jong Min, primary, Flavahan, William, primary, Chuang, Jeffrey H., primary, Kim, Betty Y.S., primary, Xu, Jiaqiong, primary, Jung, Sung Yun, primary, and Yun, Kyuson, primary

Published
2023
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43. Data from Enhanced GAB2 Expression Is Associated with Improved Survival in High-Grade Serous Ovarian Cancer and Sensitivity to PI3K Inhibition

Author

Davis, Sally J., primary, Sheppard, Karen E., primary, Anglesio, Michael S., primary, George, Joshy, primary, Traficante, Nadia, primary, Fereday, Sian, primary, Intermaggio, Maria P., primary, Menon, Usha, primary, Gentry-Maharaj, Aleksandra, primary, Lubinski, Jan, primary, Gronwald, Jacek, primary, Pearce, Celeste Leigh, primary, Pike, Malcolm C., primary, Wu, Anna, primary, Kommoss, Stefan, primary, Pfisterer, Jacobus, primary, du Bois, Andreas, primary, Hilpert, Felix, primary, Ramus, Susan J., primary, Bowtell, David D.L., primary, Huntsman, David G., primary, Pearson, Richard B., primary, Simpson, Kaylene J., primary, Campbell, Ian G., primary, and Gorringe, Kylie L., primary

Published
2023
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44. Supplementary Table 1 from Enhanced GAB2 Expression Is Associated with Improved Survival in High-Grade Serous Ovarian Cancer and Sensitivity to PI3K Inhibition

Author

Davis, Sally J., primary, Sheppard, Karen E., primary, Anglesio, Michael S., primary, George, Joshy, primary, Traficante, Nadia, primary, Fereday, Sian, primary, Intermaggio, Maria P., primary, Menon, Usha, primary, Gentry-Maharaj, Aleksandra, primary, Lubinski, Jan, primary, Gronwald, Jacek, primary, Pearce, Celeste Leigh, primary, Pike, Malcolm C., primary, Wu, Anna, primary, Kommoss, Stefan, primary, Pfisterer, Jacobus, primary, du Bois, Andreas, primary, Hilpert, Felix, primary, Ramus, Susan J., primary, Bowtell, David D.L., primary, Huntsman, David G., primary, Pearson, Richard B., primary, Simpson, Kaylene J., primary, Campbell, Ian G., primary, and Gorringe, Kylie L., primary

Published
2023
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45. Data from Mutation of ERBB2 Provides a Novel Alternative Mechanism for the Ubiquitous Activation of RAS-MAPK in Ovarian Serous Low Malignant Potential Tumors

Author

Anglesio, Michael S., primary, Arnold, Jeremy M., primary, George, Joshy, primary, Tinker, Anna V., primary, Tothill, Richard, primary, Waddell, Nic, primary, Simms, Lisa, primary, Locandro, Bianca, primary, Fereday, Sian, primary, Traficante, Nadia, primary, Russell, Peter, primary, Sharma, Raghwa, primary, Birrer, Michael J., primary, deFazio, Anna, primary, Chenevix-Trench, Georgia, primary, and Bowtell, David D.L., primary

Published
2023
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46. Supplementary Table 5 from Enhanced GAB2 Expression Is Associated with Improved Survival in High-Grade Serous Ovarian Cancer and Sensitivity to PI3K Inhibition

Author

Davis, Sally J., primary, Sheppard, Karen E., primary, Anglesio, Michael S., primary, George, Joshy, primary, Traficante, Nadia, primary, Fereday, Sian, primary, Intermaggio, Maria P., primary, Menon, Usha, primary, Gentry-Maharaj, Aleksandra, primary, Lubinski, Jan, primary, Gronwald, Jacek, primary, Pearce, Celeste Leigh, primary, Pike, Malcolm C., primary, Wu, Anna, primary, Kommoss, Stefan, primary, Pfisterer, Jacobus, primary, du Bois, Andreas, primary, Hilpert, Felix, primary, Ramus, Susan J., primary, Bowtell, David D.L., primary, Huntsman, David G., primary, Pearson, Richard B., primary, Simpson, Kaylene J., primary, Campbell, Ian G., primary, and Gorringe, Kylie L., primary

Published
2023
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47. Supplementary Figures and Tables from Enhanced GAB2 Expression Is Associated with Improved Survival in High-Grade Serous Ovarian Cancer and Sensitivity to PI3K Inhibition

Author

Davis, Sally J., primary, Sheppard, Karen E., primary, Anglesio, Michael S., primary, George, Joshy, primary, Traficante, Nadia, primary, Fereday, Sian, primary, Intermaggio, Maria P., primary, Menon, Usha, primary, Gentry-Maharaj, Aleksandra, primary, Lubinski, Jan, primary, Gronwald, Jacek, primary, Pearce, Celeste Leigh, primary, Pike, Malcolm C., primary, Wu, Anna, primary, Kommoss, Stefan, primary, Pfisterer, Jacobus, primary, du Bois, Andreas, primary, Hilpert, Felix, primary, Ramus, Susan J., primary, Bowtell, David D.L., primary, Huntsman, David G., primary, Pearson, Richard B., primary, Simpson, Kaylene J., primary, Campbell, Ian G., primary, and Gorringe, Kylie L., primary

Published
2023
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48. Supplementary Data from Mutation of ERBB2 Provides a Novel Alternative Mechanism for the Ubiquitous Activation of RAS-MAPK in Ovarian Serous Low Malignant Potential Tumors

Author

Anglesio, Michael S., primary, Arnold, Jeremy M., primary, George, Joshy, primary, Tinker, Anna V., primary, Tothill, Richard, primary, Waddell, Nic, primary, Simms, Lisa, primary, Locandro, Bianca, primary, Fereday, Sian, primary, Traficante, Nadia, primary, Russell, Peter, primary, Sharma, Raghwa, primary, Birrer, Michael J., primary, deFazio, Anna, primary, Chenevix-Trench, Georgia, primary, and Bowtell, David D.L., primary

Published
2023
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50. Supplementary Table from A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non–Small Cell Lung Cancer

Author

Woo, Xing Yi, primary, Srivastava, Anuj, primary, Mack, Philip C., primary, Graber, Joel H., primary, Sanderson, Brian J., primary, Lloyd, Michael W., primary, Chen, Mandy, primary, Domanskyi, Sergii, primary, Gandour-Edwards, Regina, primary, Tsai, Rebekah A., primary, Keck, James, primary, Cheng, Mingshan, primary, Bundy, Margaret, primary, Jocoy, Emily L., primary, Riess, Jonathan W., primary, Holland, William, primary, Grubb, Stephen C., primary, Peterson, James G., primary, Stafford, Grace A., primary, Paisie, Carolyn, primary, Neuhauser, Steven B., primary, Karuturi, R. Krishna Murthy, primary, George, Joshy, primary, Simons, Allen K., primary, Chavaree, Margaret, primary, Tepper, Clifford G., primary, Goodwin, Neal, primary, Airhart, Susan D., primary, Lara, Primo N., primary, Openshaw, Thomas H., primary, Liu, Edison T., primary, Gandara, David R., primary, and Bult, Carol J., primary

Published
2023
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