Evidence map›Paper›PMID 35475239›Full record

ArticleCell reports methods2021

A pan-cancer survey of cell line tumor similarity by feature-weighted molecular profiles.

Rileen Sinha, Augustin Luna, Nikolaus Schultz, Chris Sander

Abstract read
In one paragraph

Article in Cell reports methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Learning Patient Similarity from Genomics for Precision Oncology.medRxiv : the preprint server for health sciences · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Stem cell modeling of nervous system tumors.Disease models & mechanisms · 2024
    Review
  14. Characterization of tumor suppressors and oncogenes evaluated from TCGA cancers.American journal of clinical and experimental immunology · 2024
    Article
  15. Article
  16. Review
  17. Article
  18. Frontiers in pharmacology · 2023
    Article
  19. CNpare: matching DNA copy number profiles.Bioinformatics (Oxford, England) · 2022
    Article
  20. Review
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

4 authors.

Rileen SinhaDepartment of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Augustin LunaDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Nikolaus SchultzComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
Chris SanderDepartment of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
MSKCC Center for Translational Cancer Genomic AnalysisU24CA143840 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI LADANYI, MARC, SANDER, CHRIS · 2009 to 2016
$11.5M
A Computational Platform for Analyzing and Visualizing Integrated TCGA Data in thR21CA135870 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI SANDER, CHRIS · 2008 to 2009
$522k
Chemogenomic Analysis of the NCI Therapeutic Compound DatabaseF32CA192901 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI LUNA, AUGUSTIN · 2015 to 2017
$165k
NCI NIH HHS F32 CA192901NCI NIH HHS P30 CA008748NCI NIH HHS R21 CA135870NCI NIH HHS U24 CA143840NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

Patient-derived cell lines are often used in pre-clinical cancer research, but some cell lines are too different from tumors to be good models. Comparison of genomic and expression profiles can guide the choice of pre-clinical models, but typically not all features are equally relevant. We present TumorComparer, a computational method for comparing cellular profiles with higher weights on functional features of interest. In this pan-cancer application, we compare ∼600 cell lines and ∼8,000 tumor samples of 24 cancer types, using weights to emphasize known oncogenic alterations. We characterize the similarity of cell lines and tumors within and across cancers by using multiple datum types and rank cell lines by their inferred quality as representative models. Beyond the assessment of cell lines, the weighted similarity approach is adaptable to patient stratification in clinical trials and personalized medicine.

Indexed as

GenomicsNeoplasmsCell Line, TumorHumanscancer genomicscancer therapyCCLPcell linesdecision supportoncogenic alterationspatient stratificationTCGAweb applicationweighted similarity

Identifiers

PMID35475239
PMCPMC9017219

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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.