Evidence map›Paper›PMID 24297535›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2014

Integrative analysis of two cell lines derived from a non-small-lung cancer patient--a panomics approach.

Oleg Mayba, Florian Gnad, Michael Peyton, Fan Zhang, Kimberly Walter, Pan Du, Melanie A Huntley, Zhaoshi Jiang, Jinfeng Liu, Peter M Haverty and 6 more

Open access · greenAbstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 7 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

16 authors at 4 institutions in 2 countries.

Oleg MaybaDepartments of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, CA 94080, USA.
Florian Gnad
Michael Peyton
Fan Zhang
Kimberly Walter
Pan Du
Melanie A Huntley
Zhaoshi Jiang
Jinfeng Liu
Peter M Haverty
Robert C Gentleman
Ruiqiang Li
John D Minna
Yingrui Li
David S Shames
Zemin Zhang
BGI Group (China) · CNSouthwestern Medical Center · USThe University of Texas Southwestern Medical Center · USUniversity of California, Davis · US

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
NCI NIH HHS P50 CA070907
6 · The paper itself

Abstract

Cancer cells derived from different stages of tumor progression may exhibit distinct biological properties, as exemplified by the paired lung cancer cell lines H1993 and H2073. While H1993 was derived from chemo-naive metastasized tumor, H2073 originated from the chemo-resistant primary tumor from the same patient and exhibits strikingly different drug response profile. To understand the underlying genetic and epigenetic bases for their biological properties, we investigated these cells using a wide range of large-scale methods including whole genome sequencing, RNA sequencing, SNP array, DNA methylation array, and de novo genome assembly. We conducted an integrative analysis of both cell lines to distinguish between potential driver and passenger alterations. Although many genes are mutated in these cell lines, the combination of DNA- and RNA-based variant information strongly implicates a small number of genes including TP53 and STK11 as likely drivers. Likewise, we found a diverse set of genes differentially expressed between these cell lines, but only a fraction can be attributed to changes in DNA copy number or methylation. This set included the ABC transporter ABCC4, implicated in drug resistance, and the metastasis associated MET oncogene. While the rich data content allowed us to reduce the space of hypotheses that could explain most of the observed biological properties, we also caution there is a lack of statistical power and inherent limitations in such single patient case studies.

Indexed as

Carcinoma, Non-Small-Cell LungCell Line, TumorComputational BiologyDNA MethylationDrug Resistance, NeoplasmEpigenesis, GeneticGene DosageGene Expression ProfilingGenomicsHumansLung NeoplasmsModels, GeneticMutation

Identifiers

PMID24297535
PMCPMC3940063
OpenAlexW59725086

What OpenQuestion holds

Textmetadata
LicenceTDM
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.