Evidence map›Paper›PMID 31672976›Full record

ArticleScientific data2019

A multi-modal data resource for investigating topographic heterogeneity in patient-derived xenograft tumors.

Satwik Rajaram, Maike A Roth, Julia Malato, Scott VandenBerg, Byron Hann, Chloe E Atreya, Steven J Altschuler, Lani F Wu

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
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

8 authors.

Satwik RajaramDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA. Satwik.Rajaram@utsouthwestern.edu.ORCID http://orcid.org/0000-0001-8242-4402
Maike A RothDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA.ORCID http://orcid.org/0000-0003-1003-7002
Julia MalatoHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.
Scott VandenBergDepartment of Pathology, University of California San Francisco, San Francisco, CA, USA.
Byron HannHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.
Chloe E AtreyaHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.
Steven J AltschulerDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA. AltschulerAndWu@gmail.com.ORCID http://orcid.org/0000-0001-9142-0796
Lani F WuDepartment of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, USA. AltschulerAndWu@gmail.com.

Funding

Maximizing the predictive power of high-throughput, microscopy-based phenotypic screensR01CA184984 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WU, LANI F · 2014 to 2025
$4.7M
Kinome-guided Targeting of Cooperative Dependencies in BRAF Mutated Colorectal CancerR01CA229447 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Chloe E. Atreya, Jean-Philippe Francois Marie Coppe · 2019 to 2026
$4.1M
(PQD1) An Iterative Approach for Overcoming Evolving Targeted Therapy ResistanceR01CA185404 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WU, LANI F · 2014 to 2017
$1.3M
Systems-level role of GSK3 in colonic epithelium homeostasis and drug resistanceR01GM112690 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALTSCHULER, STEVEN J · 2015 to 2018
$1.3M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS R01 CA184984NCI NIH HHS R01 CA185404NCI NIH HHS R01 CA229447NIGMS NIH HHS R01 GM112690
6 · The paper itself

Abstract

Patient-derived xenografts (PDXs) are an essential pre-clinical resource for investigating tumor biology. However, cellular heterogeneity within and across PDX tumors can strongly impact the interpretation of PDX studies. Here, we generated a multi-modal, large-scale dataset to investigate PDX heterogeneity in metastatic colorectal cancer (CRC) across tumor models, spatial scales and genomic, transcriptomic, proteomic and imaging assay modalities. To showcase this dataset, we present analysis to assess sources of PDX variation, including anatomical orientation within the implanted tumor, mouse contribution, and differences between replicate PDX tumors. A unique aspect of our dataset is deep characterization of intra-tumor heterogeneity via immunofluorescence imaging, which enables investigation of variation across multiple spatial scales, from subcellular to whole tumor levels. Our study provides a benchmark data resource to investigate PDX models of metastatic CRC and serves as a template for future, quantitative investigations of spatial heterogeneity within and across PDX tumor models.

Indexed as

Disease Models, AnimalAnimalsColonic NeoplasmsGenomicsHeterograftsHumansMiceNeoplasm MetastasisProteomicsTranscriptome

Identifiers

PMID31672976
PMCPMC6823477

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.