Evidence map›Paper›PMID 34495981›Full record

ArticlePloS one2021

Glioblastoma signature in the DNA of blood-derived cells.

Siddharth Jain, Bijan Mazaheri, Netanel Raviv, Jehoshua Bruck

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 56% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

4 authors at 2 institutions in 1 country.

Siddharth JainDepartment of Electrical Engineering, California Institute of Technology, Pasadena, CA, United States of America.ORCID 0000-0002-9164-6119
Bijan MazaheriDepartment of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, United States of America.
Netanel RavivDepartment of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, United States of America.
Jehoshua BruckDepartment of Electrical Engineering, California Institute of Technology, Pasadena, CA, United States of America.
California Institute of Technology · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current approach for the detection of cancer is based on identifying genetic mutations typical to tumor cells. This approach is effective only when cancer has already emerged, however, it might be in a stage too advanced for effective treatment. Cancer is caused by the continuous accumulation of mutations; is it possible to measure the time-dependent information of mutation accumulation and predict the emergence of cancer? We hypothesize that the mutation history derived from the tandem repeat regions in blood-derived DNA carries information about the accumulation of the cancer driver mutations in other tissues. To validate our hypothesis, we computed the mutation histories from the tandem repeat regions in blood-derived exomic DNA of 3874 TCGA patients with different cancer types and found a statistically significant signal with specificity ranging from 66% to 93% differentiating Glioblastoma patients from other cancer patients. Our approach and findings offer a new direction for future cancer prediction and early cancer detection based on information derived from blood-derived DNA.

Indexed as

MutationBlood CellsBrain NeoplasmsDatabases, GeneticDNAEarly Detection of CancerExomeGlioblastomaHumansMachine LearningSensitivity and SpecificitySequence AlignmentTandem Repeat SequencesDNA

Identifiers

PMID34495981
PMCPMC8425531
OpenAlexW3197365562

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.