Evidence map›Paper›PMID 27829362›Full record

ArticleBMC genomics2016

CASTIN: a system for comprehensive analysis of cancer-stromal interactome.

Daisuke Komura, Takayuki Isagawa, Kazuki Kishi, Ryohei Suzuki, Reiko Sato, Mariko Tanaka, Hiroto Katoh, Shogo Yamamoto, Kenji Tatsuno, Masashi Fukayama and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 10 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

12 authors at 3 institutions in 1 country.

Daisuke KomuraDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Takayuki IsagawaDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Kazuki KishiDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Ryohei SuzukiDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Reiko SatoDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Mariko TanakaDepartment of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Hiroto KatohDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Shogo YamamotoGenome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
Kenji TatsunoGenome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
Masashi FukayamaDepartment of Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Hiroyuki AburataniGenome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.
Shumpei IshikawaDepartment of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan. sish.gpat@mri.tmd.ac.jp.
Tokyo Medical and Dental University · JPThe University of Tokyo · JPTokyo University of Information Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer microenvironment plays a vital role in cancer development and progression, and cancer-stromal interactions have been recognized as important targets for cancer therapy. However, identifying relevant and druggable cancer-stromal interactions is challenging due to the lack of quantitative methods to analyze whole cancer-stromal interactome.

resultsWe present CASTIN (CAncer-STromal INteractome analysis), a novel framework for the evaluation of cancer-stromal interactome from RNA-Seq data using cancer xenograft models. For each ligand-receptor interaction which is derived from curated protein-protein interaction database, CASTIN summarizes gene expression profiles of cancer and stroma into three evaluation indices. These indices provide quantitative evaluation and comprehensive visualization of interactome, and thus enable to identify critical cancer-microenvironment interactions, which would be potential drug targets. We applied CASTIN to the dataset of pancreas ductal adenocarcinoma, and successfully characterized the individual cancer in terms of cancer-stromal relationships, and identified both well-known and less-characterized druggable interactions.

conclusionsCASTIN provides comprehensive view of cancer-stromal interactome and is useful to identify critical interactions which may serve as potential drug targets in cancer-microenvironment. CASTIN is available at: http://github.com/tmd-gpat/CASTIN .

Indexed as

Cell CommunicationTumor MicroenvironmentAnimalsCell Line, TumorComputational BiologyDisease Models, AnimalFemaleGene Expression ProfilingHeterograftsHumansMiceNeoplasmsProtein Interaction MappingStromal CellsTranscriptomeWorkflowCancer microenvironmentCancer-stromal interactionsRNA-SeqXenograft mouse model

Identifiers

PMID27829362
PMCPMC5103609
OpenAlexW2556938617

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.