Search

Your search keyword '"Lim, Kian Huat"' showing total 5 results
Start Over Author "Lim, Kian Huat" Journal nature communications
5 results on '"Lim, Kian Huat"'

1. Combined KRAS-MAPK pathway inhibitors and HER2-directed drug conjugate is efficacious in pancreatic cancer

Author

Bulle, Ashenafi, Liu, Peng, Seehra, Kuljeet, Bansod, Sapana, Chen, Yali, Zahra, Kiran, Somani, Vikas, Khawar, Iftikhar Ali, Chen, Hung-Po, Dodhiawala, Paarth B., Li, Lin, Geng, Yutong, Mo, Chia-Kuei, Mahsl, Jay, Ding, Li, Govindan, Ramaswamy, Davies, Sherri, Mudd, Jacqueline, Hawkins, William G., Fields, Ryan C., DeNardo, David G., Knoerzer, Deborah, Held, Jason M., Grierson, Patrick M., Wang-Gillam, Andrea, Ruzinova, Marianna B., and Lim, Kian-Huat

Published
2024
Full Text
View/download PDF

2. Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

Author

Sun, Hua, Cao, Song, Mashl, R Jay, Mo, Chia-Kuei, Zaccaria, Simone, Wendl, Michael C, Davies, Sherri R, Bailey, Matthew H, Primeau, Tina M, Hoog, Jeremy, Mudd, Jacqueline L, Dean, Dennis A, Patidar, Rajesh, Chen, Li, Wyczalkowski, Matthew A, Jayasinghe, Reyka G, Rodrigues, Fernanda Martins, Terekhanova, Nadezhda V, Li, Yize, Lim, Kian-Huat, Wang-Gillam, Andrea, Van Tine, Brian A, Ma, Cynthia X, Aft, Rebecca, Fuh, Katherine C, Schwarz, Julie K, Zevallos, Jose P, Puram, Sidharth V, Dipersio, John F, Davis-Dusenbery, Brandi, Ellis, Matthew J, Lewis, Michael T, Davies, Michael A, Herlyn, Meenhard, Fang, Bingliang, Roth, Jack A, Welm, Alana L, Welm, Bryan E, Meric-Bernstam, Funda, Chen, Feng, Fields, Ryan C, Li, Shunqiang, Govindan, Ramaswamy, Doroshow, James H, Moscow, Jeffrey A, Evrard, Yvonne A, Chuang, Jeffrey H, Raphael, Benjamin J, and Ding, Li

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Cancer, Human Genome, Biotechnology, Cancer Genomics, Good Health and Well Being, Animals, Disease Models, Animal, Female, Gene Expression Regulation, Neoplastic, Genome, Genomics, Heterografts, Humans, Male, Mice, Models, Biological, Mutation, Neoplasms, Transcriptome, Xenograft Model Antitumor Assays, NCI PDXNet Consortium
Abstract

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.

Published
2021

3. Author Correction: Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

Author

Sun, Hua, Cao, Song, Mashl, R. Jay, Mo, Chia-Kuei, Zaccaria, Simone, Wendl, Michael C., Davies, Sherri R., Bailey, Matthew H., Primeau, Tina M., Hoog, Jeremy, Mudd, Jacqueline L., Dean, II, Dennis A., Patidar, Rajesh, Chen, Li, Wyczalkowski, Matthew A., Jayasinghe, Reyka G., Rodrigues, Fernanda Martins, Terekhanova, Nadezhda V., Li, Yize, Lim, Kian-Huat, Wang-Gillam, Andrea, Van Tine, Brian A., Ma, Cynthia X., Aft, Rebecca, Fuh, Katherine C., Schwarz, Julie K., Zevallos, Jose P., Puram, Sidharth V., Dipersio, John F., Davis-Dusenbery, Brandi, Ellis, Matthew J., Lewis, Michael T., Davies, Michael A., Herlyn, Meenhard, Fang, Bingliang, Roth, Jack A., Welm, Alana L., Welm, Bryan E., Meric-Bernstam, Funda, Chen, Feng, Fields, Ryan C., Li, Shunqiang, Govindan, Ramaswamy, Doroshow, James H., Moscow, Jeffrey A., Evrard, Yvonne A., Chuang, Jeffrey H., Raphael, Benjamin J., and Ding, Li

Published
2022
Full Text
View/download PDF

5. Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment.

Author

Sun, Hua, Cao, Song, Mashl, R. Jay, Mo, Chia-Kuei, Zaccaria, Simone, Wendl, Michael C., Davies, Sherri R., Bailey, Matthew H., Primeau, Tina M., Hoog, Jeremy, Mudd, Jacqueline L., Dean II, Dennis A., Patidar, Rajesh, Chen, Li, Wyczalkowski, Matthew A., Jayasinghe, Reyka G., Rodrigues, Fernanda Martins, Terekhanova, Nadezhda V., Li, Yize, and Lim, Kian-Huat

Subjects
WEB portals, PHARMACOGENOMICS, TRANSCRIPTOMES, SOURCE code, SCIENTIFIC community, TUMOR markers, CANCER treatment
Abstract

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors. Patient-derived xenograft models (PDX) have been extensively used to study the molecular and clinical features of cancers. Here the authors present a cohort of 536 PDX models from 25 cancers, as well as their genomic and evolutionary profiles and their suitability for clinical trials. [ABSTRACT FROM AUTHOR]

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results