Evidence map›Paper›PMID 35121865›Full record

ReviewNature cancer2021

Moving pan-cancer studies from basic research toward the clinic.

Feng Chen, Michael C Wendl, Matthew A Wyczalkowski, Matthew H Bailey, Yize Li, Li Ding

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

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  12. Self-Normalizing Multi-Omics Neural Network for Pan-Cancer Prognostication.International journal of molecular sciences · 2025
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4 more citing papers are in PubMed but not listed here.

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

6 authors.

Feng ChenDepartment of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
Michael C WendlDepartment of Genetics, Washington University in St. Louis, St. Louis, MO, USA.
Matthew A WyczalkowskiDepartment of Medicine, Washington University in St. Louis, St. Louis, MO, USA.ORCID http://orcid.org/0000-0003-4197-551X
Matthew H BaileyHuntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Yize LiDepartment of Medicine, Washington University in St. Louis, St. Louis, MO, USA.ORCID http://orcid.org/0000-0003-1074-281X
Li DingDepartment of Medicine, Washington University in St. Louis, St. Louis, MO, USA. lding@wustl.edu.ORCID http://orcid.org/0000-0003-1517-2975

Funding

Training Program in Genomic MedicineT32HG008962 · NHGRI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Lynn Jorde, Aaron R Quinlan · 2016 to 2026
$3.0M
NHGRI NIH HHS T32 HG008962
6 · The paper itself

Abstract

Although all cancers share common hallmarks, we have long realized that there is no silver-bullet treatment for the disease. Many clinical oncologists specialize in a single cancer type, based predominantly on the tissue of origin. With advances brought by genetics and cancer genomic research, we now know that cancers are profoundly different, both in origins and in genetic alterations. At the same time, commonalities such as key driver mutations, altered pathways, mutational, immune and microbial signatures and other areas (many revealed by pan-cancer studies) point to the intriguing possibility of targeting common traits across diverse cancer types with the same therapeutic strategies. Studies designed to delineate differences and similarities across cancer types are thus critical in discerning the basic dynamics of oncogenesis, as well as informing diagnoses, prognoses and therapies. We anticipate growing emphases on the development and application of therapies targeting underlying commonalities of different cancer types, while tailoring to the unique tissue environment and intrinsic molecular fingerprints of each cancer type and subtype. Here we summarize the facets of pan-cancer research and how they are pushing progress toward personalized medicine.

Indexed as

NeoplasmsCarcinogenesisGenomicsHumansMutationPrecision Medicine

Identifiers

What OpenQuestion holds

Textmetadata
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.