PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery

Soner Koc; Michael W. Lloyd; Jeffrey W. Grover; Nan Xiao; Sara Seepo; Sai Lakshmi Subramanian; Manisha Ray; Christian Frech; John Digiovanna; Phillip Webster; Steven Neuhauser; Anuj Srivastava; Xing Yi Woo; Brian J. Sanderson; Brian White; Paul Lott; Lacey E. Dobrolecki; Heidi Dowst; Yvonne A. Evrard; Tiffany A. Wallace; Jeffrey A. Moscow; James H. Doroshow; Nicholas Mitsiades; Salma Kaochar; Chong Xian Pan; Moon S. Chen; Luis Carvajal-Carmona; Alana L. Welm; Bryan E. Welm; Michael T. Lewis; Ramaswamy Govindan; Li Ding; Shunqiang Li; Meenhard Herlyn; Michael A. Davies; Jack Roth; Funda Meric-Bernstam; Peter N. Robinson; Carol J. Bult; Brandi Davis-Dusenbery; Dennis A. Dean; Jeffrey H. Chuang

doi:10.1093/narcan/zcac014

PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery

Soner Koc, Michael W. Lloyd, Jeffrey W. Grover, Nan Xiao, Sara Seepo, Sai Lakshmi Subramanian, Manisha Ray, Christian Frech, John Digiovanna, Phillip Webster, Steven Neuhauser, Anuj Srivastava, Xing Yi Woo, Brian J. Sanderson, Brian White, Paul Lott, Lacey E. Dobrolecki, Heidi Dowst, Yvonne A. Evrard, Tiffany A. WallaceJeffrey A. Moscow, James H. Doroshow, Nicholas Mitsiades, Salma Kaochar, Chong Xian Pan, Moon S. Chen, Luis Carvajal-Carmona, Alana L. Welm, Bryan E. Welm, Michael T. Lewis, Ramaswamy Govindan, Li Ding, Shunqiang Li, Meenhard Herlyn, Michael A. Davies, Jack Roth, Funda Meric-Bernstam, Peter N. Robinson, Carol J. Bult, Brandi Davis-Dusenbery, Dennis A. Dean, Jeffrey H. Chuang

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

Original language	English (US)
Article number	zcac014
Journal	NAR Cancer
Volume	4
Issue number	2
DOIs	https://doi.org/10.1093/narcan/zcac014
State	Published - Jun 1 2022

ASJC Scopus subject areas

Oncology
Cancer Research

MD Anderson CCSG core facilities

Clinical and Translational Research Center

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10.1093/narcan/zcac014

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Koc, S., Lloyd, M. W., Grover, J. W., Xiao, N., Seepo, S., Subramanian, S. L., Ray, M., Frech, C., Digiovanna, J., Webster, P., Neuhauser, S., Srivastava, A., Woo, X. Y., Sanderson, B. J., White, B., Lott, P., Dobrolecki, L. E., Dowst, H., Evrard, Y. A., ... Chuang, J. H. (2022). PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery. NAR Cancer, 4(2), Article zcac014. https://doi.org/10.1093/narcan/zcac014

Koc, S, Lloyd, MW, Grover, JW, Xiao, N, Seepo, S, Subramanian, SL, Ray, M, Frech, C, Digiovanna, J, Webster, P, Neuhauser, S, Srivastava, A, Woo, XY, Sanderson, BJ, White, B, Lott, P, Dobrolecki, LE, Dowst, H, Evrard, YA, Wallace, TA, Moscow, JA, Doroshow, JH, Mitsiades, N, Kaochar, S, Pan, CX, Chen, MS, Carvajal-Carmona, L, Welm, AL, Welm, BE, Lewis, MT, Govindan, R, Ding, L, Li, S, Herlyn, M, Davies, MA, Roth, J, Meric-Bernstam, F, Robinson, PN, Bult, CJ, Davis-Dusenbery, B, Dean, DA & Chuang, JH 2022, 'PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery', NAR Cancer, vol. 4, no. 2, zcac014. https://doi.org/10.1093/narcan/zcac014

@article{5bf91d0934ef4b4595f7f668c1db2dd1,

title = "PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery",

abstract = "We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.",

author = "Soner Koc and Lloyd, {Michael W.} and Grover, {Jeffrey W.} and Nan Xiao and Sara Seepo and Subramanian, {Sai Lakshmi} and Manisha Ray and Christian Frech and John Digiovanna and Phillip Webster and Steven Neuhauser and Anuj Srivastava and Woo, {Xing Yi} and Sanderson, {Brian J.} and Brian White and Paul Lott and Dobrolecki, {Lacey E.} and Heidi Dowst and Evrard, {Yvonne A.} and Wallace, {Tiffany A.} and Moscow, {Jeffrey A.} and Doroshow, {James H.} and Nicholas Mitsiades and Salma Kaochar and Pan, {Chong Xian} and Chen, {Moon S.} and Luis Carvajal-Carmona and Welm, {Alana L.} and Welm, {Bryan E.} and Lewis, {Michael T.} and Ramaswamy Govindan and Li Ding and Shunqiang Li and Meenhard Herlyn and Davies, {Michael A.} and Jack Roth and Funda Meric-Bernstam and Robinson, {Peter N.} and Bult, {Carol J.} and Brandi Davis-Dusenbery and Dean, {Dennis A.} and Chuang, {Jeffrey H.}",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s) 2022. Published by Oxford University Press on behalf of NAR Cancer.",

year = "2022",

month = jun,

day = "1",

doi = "10.1093/narcan/zcac014",

language = "English (US)",

volume = "4",

journal = "NAR Cancer",

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T1 - PDXNet portal

T2 - patient-derived Xenograft model, data, workflow and tool discovery

AU - Koc, Soner

AU - Lloyd, Michael W.

AU - Grover, Jeffrey W.

AU - Xiao, Nan

AU - Seepo, Sara

AU - Subramanian, Sai Lakshmi

AU - Ray, Manisha

AU - Frech, Christian

AU - Digiovanna, John

AU - Webster, Phillip

AU - Neuhauser, Steven

AU - Srivastava, Anuj

AU - Woo, Xing Yi

AU - Sanderson, Brian J.

AU - White, Brian

AU - Lott, Paul

AU - Dobrolecki, Lacey E.

AU - Dowst, Heidi

AU - Evrard, Yvonne A.

AU - Wallace, Tiffany A.

AU - Moscow, Jeffrey A.

AU - Doroshow, James H.

AU - Mitsiades, Nicholas

AU - Kaochar, Salma

AU - Pan, Chong Xian

AU - Chen, Moon S.

AU - Carvajal-Carmona, Luis

AU - Welm, Alana L.

AU - Welm, Bryan E.

AU - Lewis, Michael T.

AU - Govindan, Ramaswamy

AU - Ding, Li

AU - Li, Shunqiang

AU - Herlyn, Meenhard

AU - Davies, Michael A.

AU - Roth, Jack

AU - Meric-Bernstam, Funda

AU - Robinson, Peter N.

AU - Bult, Carol J.

AU - Davis-Dusenbery, Brandi

AU - Dean, Dennis A.

AU - Chuang, Jeffrey H.

PY - 2022/6/1

Y1 - 2022/6/1

N2 - We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

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PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery

Abstract

ASJC Scopus subject areas

MD Anderson CCSG core facilities

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