Evidence map›Paper›PMID 35442775›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

A preclinical platform for assessing antitumor effects and systemic toxicities of cancer drug targets.

Xiang Li, Chun-Hao Huang, Francisco J Sánchez-Rivera, Margaret C Kennedy, Darjus F Tschaharganeh, John P Morris, Antonella Montinaro, Kevin P O'Rourke, Ana Banito, John E Wilkinson and 10 more

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 14 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 3 institutions in 4 countries.

Xiang LiCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.ORCID 0000-0001-7422-251X
Chun-Hao HuangCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Francisco J Sánchez-RiveraCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.ORCID 0000-0002-8466-8563
Margaret C KennedyCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.ORCID 0000-0001-9106-1906
Darjus F TschaharganehCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
John P MorrisCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Antonella MontinaroCentre for Cell Death, Cancer, and Inflammation, UCL Cancer Institute, University College London, London WC1E 6DD, United Kingdom.
Kevin P O'RourkeCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Ana BanitoCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
John E WilkinsonDepartment of Pathology, University of Michigan School of Medicine, Ann Arbor, MI 48109.
Chi-Chao ChenCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Yu-Jui HoCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.ORCID 0000-0002-7540-024X
Lukas E DowCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Sha TianCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Wei LuanCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Elisa de StanchinaCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.
Tinghu ZhangInnovative Medicines Accelerator, Stanford Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA 94305.
Nathanael S GrayInnovative Medicines Accelerator, Stanford Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA 94305.
Henning WalczakCentre for Cell Death, Cancer, and Inflammation, UCL Cancer Institute, University College London, London WC1E 6DD, United Kingdom.
Scott W LoweCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute, New York, NY 10065.ORCID 0000-0002-5284-9650
Memorial Sloan Kettering Cancer Center · USHarvard University · USSpanish National Cancer Research Centre · ES

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
COMPUTATIONAL AND FUNCTIONAL APPROACHES TO VALIDATING CANCER GENOME TARGETSU01CA168409 · NCI · COLD SPRING HARBOR LABORATORY · PI POWERS, SCOTT · 2012 to 2016
$7.3M
Translational Research in Oncology Training ProgramT32CA160001 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI SAWYERS, CHARLES L. · 2011 to 2020
$2.0M
A scalable platform for target validation in GEMM models of gastrointestinal malignancies.R01CA195787 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI LOWE, SCOTT W. · 2015 to 2017
$2.0M
Cancer Research UK 27323Cancer Research UK A27323Howard Hughes Medical InstituteMedical Research Council MR/S00811X/1NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA195787NCI NIH HHS T32 CA160001NCI NIH HHS U01 CA168409Wellcome Trust 214342Wellcome Trust 214342/Z/18/Z
6 · The paper itself

Abstract

Anticancer drug development campaigns often fail due to an incomplete understanding of the therapeutic index differentiating the efficacy of the agent against the cancer and its on-target toxicities to the host. To address this issue, we established a versatile preclinical platform in which genetically defined cancers are produced using somatic tissue engineering in transgenic mice harboring a doxycycline-inducible short hairpin RNA against the target of interest. In this system, target inhibition is achieved by the addition of doxycycline, enabling simultaneous assessment of efficacy and toxicity in the same animal. As proof of concept, we focused on CDK9—a cancer target whose clinical development has been hampered by compounds with poorly understood target specificity and unacceptable toxicities. We systematically compared phenotypes produced by genetic Cdk9 inhibition to those achieved using a recently developed highly specific small molecule CDK9 inhibitor and found that both perturbations led to robust antitumor responses. Remarkably, nontoxic levels of CDK9 inhibition could achieve significant treatment efficacy, and dose-dependent toxicities produced by prolonged CDK9 suppression were largely reversible upon Cdk9 restoration or drug withdrawal. Overall, these results establish a versatile in vivo target validation platform that can be employed for rapid triaging of therapeutic targets and lend support to efforts aimed at advancing CDK9 inhibitors for cancer therapy.

Indexed as

Antineoplastic AgentsNeoplasmsAnimalsCell Line, TumorCyclin-Dependent Kinase 9MiceRNA InterferenceAntineoplastic AgentsCdk9 protein, mouseCyclin-Dependent Kinase 9CDK9hepatocellular carcinomamouse modelpreclinical platform

Identifiers

PMID35442775
PMCPMC9169916
OpenAlexW4224251122

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.