Evidence map›Paper›PMID 27832547›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

Transcriptional Analysis-Based Integrative Genomics Approach to Identify Tumor-Promoting Metabolic Genes.

Romi Gupta, Narendra Wajapeyee

Open access · greenAbstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 72% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Romi GuptaDepartment of Pathology, Yale University School of Medicine, 310 Cedar Street, 208023, New Haven, CT, 06518, USA.
Narendra WajapeyeeDepartment of Pathology, Yale University School of Medicine, 310 Cedar Street, 208023, New Haven, CT, 06518, USA. Narendra.Wajapeyee@yale.edu.
Yale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
A NOVEL DRUGGABLE GENETIC VULNERABILITY PATHWAY IN MELANOMAR01CA200919 · NCI · YALE UNIVERSITY · PI WAJAPEYEE, NARENDRA · 2016 to 2020
$1.8M
Nucleoporin NUP205-driven Novel Pathway in Melanoma Tumor Growth and MetastasisR01CA196566 · NCI · YALE UNIVERSITY · PI WAJAPEYEE, NARENDRA · 2016 to 2020
$1.8M
Metabolic Drivers of Melanoma Initiation, Progression and Therapy ResponseR21CA191364 · NCI · YALE UNIVERSITY · PI WAJAPEYEE, NARENDRA · 2015 to 2016
$398k
METABOLIC DRIVERS OF LUNG CANCER INITIATION, PROGRESSION AND THERAPY RESPONSER21CA197758 · NCI · YALE UNIVERSITY · PI WAJAPEYEE, NARENDRA · 2015 to 2016
$398k
ANOIKIS EFFECTORS AS DRIVERS OF METASTATIC MELANOMAR21CA195077 · NCI · YALE UNIVERSITY · PI WAJAPEYEE, NARENDRA · 2016 to 2016
$218k
NCATS NIH HHS UL1 TR001863NCI NIH HHS R01 CA196566NCI NIH HHS R01 CA200919NCI NIH HHS R21 CA191364NCI NIH HHS R21 CA195077NCI NIH HHS R21 CA197758
6 · The paper itself

Abstract

Metabolic regulation can play key role in normal and pathological states. In particular in cancer cells, alterations in metabolic pathways can drive the growth and survival of cancer cells. Among these alterations, many occur at the transcriptional level leading to the overexpression of metabolic genes. However, not every metabolically upregulated genes may be necessary for tumor growth. Therefore, functional validation approaches are required to distinguish metabolically overexpressed genes that are necessary for tumor growth versus the ones that are not. One of the experimental approaches to do this is to use the approach of RNA interference to systematically survey the transcriptionally upregulated metabolic genes for their requirement in tumor growth. Here, we describe an integrative genomics approach to identify metabolic genes that are necessary for tumor growth. The approach we describe is a general integrative genomics approach that combines bioinformatics-based identification of overexpressed metabolic genes in cancer patient samples and then uses RNAi-based knockdown approach to identify genes that are necessary for tumor growth.

Indexed as

Gene Expression ProfilingGenes, NeoplasmAnimalsCarcinogenesisCell Line, TumorGene Expression Regulation, NeoplasticGenomicsHumansMice, NudeNeoplasm TransplantationRNA InterferenceTranscriptomeUp-RegulationGene expression analysisMetabolism alterationRNA interference

Identifiers

PMID27832547
PMCPMC5340287
OpenAlexW2554123688

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Registered trials

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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.