Evidence map›Paper›PMID 25875127›Full record

ArticlePloS one2015

Tensor GSVD of patient- and platform-matched tumor and normal DNA copy-number profiles uncovers chromosome arm-wide patterns of tumor-exclusive platform-consistent alterations encoding for cell transformation and predicting ovarian cancer survival.

Preethi Sankaranarayanan, Theodore E Schomay, Katherine A Aiello, Orly Alter

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.0field-weighted citation impact, top 16% 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

26 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
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  4. Review
  5. [Research Advances of RAD51AP1 in Tumor Progression and Drug Resistance].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023
    Review
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  9. Scaling concepts in 'omics: Nuclear lamin-B scales with tumor growth and often predicts poor prognosis, unlike fibrosis.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
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  17. Personalized disease signatures through information-theoretic compaction of big cancer data.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  18. Review
  19. Tensor factorization toward precision medicine.Briefings in bioinformatics · 2017
    Article
  20. 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 1 institution in 1 country.

Preethi SankaranarayananScientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, United States of America; Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.
Theodore E SchomayScientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, United States of America; Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.
Katherine A AielloScientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, United States of America; Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America.
Orly AlterScientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, Utah, United States of America; Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America; Department of Human Genetics, University of Utah, Salt Lake City, Utah, United States of America.
University of Utah · US

Funding

Tensor Computations for Modeling Large-Scale Molecular Biological DataR01HG004302 · NHGRI · UNIVERSITY OF UTAH · PI ALTER, ORLY · 2007 to 2011
$1.8M
NHGRI NIH HHS R01 HG-004302NHGRI NIH HHS R01 HG004302
6 · The paper itself

Abstract

The number of large-scale high-dimensional datasets recording different aspects of a single disease is growing, accompanied by a need for frameworks that can create one coherent model from multiple tensors of matched columns, e.g., patients and platforms, but independent rows, e.g., probes. We define and prove the mathematical properties of a novel tensor generalized singular value decomposition (GSVD), which can simultaneously find the similarities and dissimilarities, i.e., patterns of varying relative significance, between any two such tensors. We demonstrate the tensor GSVD in comparative modeling of patient- and platform-matched but probe-independent ovarian serous cystadenocarcinoma (OV) tumor, mostly high-grade, and normal DNA copy-number profiles, across each chromosome arm, and combination of two arms, separately. The modeling uncovers previously unrecognized patterns of tumor-exclusive platform-consistent co-occurring copy-number alterations (CNAs). We find, first, and validate that each of the patterns across only 7p and Xq, and the combination of 6p+12p, is correlated with a patient's prognosis, is independent of the tumor's stage, the best predictor of OV survival to date, and together with stage makes a better predictor than stage alone. Second, these patterns include most known OV-associated CNAs that map to these chromosome arms, as well as several previously unreported, yet frequent focal CNAs. Third, differential mRNA, microRNA, and protein expression consistently map to the DNA CNAs. A coherent picture emerges for each pattern, suggesting roles for the CNAs in OV pathogenesis and personalized therapy. In 6p+12p, deletion of the p21-encoding CDKN1A and p38-encoding MAPK14 and amplification of RAD51AP1 and KRAS encode for human cell transformation, and are correlated with a cell's immortality, and a patient's shorter survival time. In 7p, RPA3 deletion and POLD2 amplification are correlated with DNA stability, and a longer survival. In Xq, PABPC5 deletion and BCAP31 amplification are correlated with a cellular immune response, and a longer survival.

Indexed as

Models, TheoreticalPrognosisCarcinoma, Ovarian EpithelialCell Transformation, NeoplasticChromosome MappingChromosomesCystadenocarcinoma, SerousDNA Copy Number VariationsFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsMutationNeoplasm ProteinsNeoplasms, Glandular and EpithelialOvarian NeoplasmsMicroRNAsNeoplasm ProteinsRNA, Messenger

Identifiers

PMID25875127
PMCPMC4398562
OpenAlexW2031058636

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.