Evidence map›Paper›PMID 30704460›Full record

ArticleBMC medical genomics2019

Integration of genomic copy number variations and chemotherapy-response biomarkers in pediatric sarcoma.

Lijun Cheng, Pankita H Pandya, Enze Liu, Pooja Chandra, Limei Wang, Mary E Murray, Jacquelyn Carter, Michael Ferguson, Mohammad Reza Saadatzadeh, Khadijeh Bijangi-Visheshsaraei and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 55 citations in OpenAlex.

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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

14 authors at 3 institutions in 1 country.

Lijun ChengDepartment of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, 43210, USA.
Pankita H PandyaHerman B Wells Center for Pediatric Research, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Enze LiuDepartment of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, 43210, USA.
Pooja ChandraCenter for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Limei WangDepartment of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, 43210, USA.
Mary E MurrayDivision of Hematology/Oncology, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Jacquelyn CarterDivision of Hematology/Oncology, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Michael FergusonDivision of Hematology/Oncology, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Mohammad Reza SaadatzadehHerman B Wells Center for Pediatric Research, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Khadijeh Bijangi-VisheshsaraeiHerman B Wells Center for Pediatric Research, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Mark MarshallDivision of Hematology/Oncology, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
Lang LiDepartment of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, 43210, USA. Lang.Li@osumc.edu.
Karen E PollokHerman B Wells Center for Pediatric Research, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA. kpollok@iu.edu.
Jamie L RenbargerHerman B Wells Center for Pediatric Research, Department of Pediatrics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA. jarenbar@iu.edu.
Indiana University IndianapolisIndiana University – Purdue University Indianapolis · USThe Ohio State University · US

Funding

Tumor Microenvironment and Metastasis ProgramP30CA082709 · NCI · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI Sara K Quinney · 1999 to 2026
$59.3M
Drug-Drug Interactions Involving Antidiabetic AgentsR01DK102694 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI HENNESSY, SEAN, LI, LANG · 2014 to 2017
$2.4M
Project 2: Biomarkers of endothelial dysfunction in pediatric patients receiving high intensity chemotherapy/irradiationU54HD090215 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI PACZESNY, SOPHIE · 2016 to 2018
$2.3M
Evidence-based Drug-Interaction Discovery: In-Vivo, In-Vitro and ClinicalR01LM011945 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI LI, LANG, ROCHA, LUIS M · 2014 to 2017
$1.8M
Project 2: Biomarkers of endothelial dysfunction in pediatric patients receiving high intensity chemotherapy/irradiationP50HD090215 · NICHD · INDIANA UNIVERSITY INDIANAPOLIS · PI RENBARGER, JAMIE L · 2019 to 2020
$1.4M
NCI NIH HHS P30 CA082709NICHD NIH HHS P50 HD090215NICHD NIH HHS U54 HD090215NIDDK NIH HHS R01 DK102694NLM NIH HHS R01 LM011945
6 · The paper itself

Abstract

backgroundWhile most pediatric sarcomas respond to front-line therapy, some bone sarcomas do not show radiographic response like soft-tissue sarcomas (rhabdomyosarccomas) but do show 90% necrosis. Though, new therapies are urgently needed to improve survival and quality of life in pediatric patients with sarcomas. Complex chromosomal aberrations such as amplifications and deletions of DNA sequences are frequently observed in pediatric sarcomas. Evaluation of copy number variations (CNVs) associated with pediatric sarcoma patients at the time of diagnosis or following therapy offers an opportunity to assess dysregulated molecular targets and signaling pathways that may drive sarcoma development, progression, or relapse. The objective of this study was to utilize publicly available data sets to identify potential predictive biomarkers of chemotherapeutic response in pediatric Osteosarcoma (OS), Rhabdomyosarcoma (RMS) and Ewing's Sarcoma Family of Tumors (ESFTs) based on CNVs following chemotherapy (OS n = 117, RMS n = 64, ESFTs n = 25 tumor biopsies).

methodsThere were 206 CNV profiles derived from pediatric sarcoma biopsies collected from the public databases TARGET and NCBI-Gene Expression Omnibus (GEO). Through our comparative genomic analyses of OS, RMS, and ESFTs and 22,255 healthy individuals called from the Database of Genomic Variants (DGV), we identified CNVs (amplifications and deletions) pattern of genomic instability in these pediatric sarcomas. By integrating CNVs of Cancer Cell Line Encyclopedia (CCLE) identified in the pool of genes with drug-response data from sarcoma cell lines (n = 27) from Cancer Therapeutics Response Portal (CTRP) Version 2, potential predictive biomarkers of therapeutic response were identified.

resultsGenes associated with survival and/recurrence of these sarcomas with statistical significance were found on long arm of chromosome 8 and smaller aberrations were also identified at chromosomes 1q, 12q and x in OS, RMS, and ESFTs. A pool of 63 genes that harbored amplifications and/or deletions were frequently associated with recurrence across OS, RMS, and ESFTs. Correlation analysis of CNVs from CCLE with drug-response data of CTRP in 27 sarcoma cell lines, 33 CNVs out of 63 genes correlated with either sensitivity or resistance to 17 chemotherapies from which actionable CNV signatures such as IGF1R, MYC, MAPK1, ATF1, and MDM2 were identified. These CNV signatures could potentially be used to delineate patient populations that will respond versus those that will not respond to a particular chemotherapy.

conclusionsThe large-scale analyses of CNV-drug screening provides a platform to evaluate genetic alterations across aggressive pediatric sarcomas. Additionally, this study provides novel insights into the potential utilization of CNVs as not only prognostic but also as predictive biomarkers of therapeutic response. Information obtained in this study may help guide and prioritize patient-specific therapeutic options in pediatric bone and soft-tissue sarcomas.

Indexed as

DNA Copy Number VariationsGenomicsAdolescentBiomarkers, TumorCell Line, TumorChildChild, PreschoolFemaleGenome, HumanHumansInfantMalePrognosisSarcomaYoung AdultBiomarkers, TumorComparative genomic hybridization-arrayCopy number variationPediatric sarcomasPrecision medicinePrognostic biomarkers

Identifiers

PMID30704460
PMCPMC6357363
OpenAlexW2912456485

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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.