Evidence map›Paper›PMID 19379481›Full record

ArticleBMC genomics2009

A transcriptional sketch of a primary human breast cancer by 454 deep sequencing.

Alessandro Guffanti, Michele Iacono, Paride Pelucchi, Namshin Kim, Giulia Soldà, Larry J Croft, Ryan J Taft, Ermanno Rizzi, Marjan Askarian-Amiri, Raoul J Bonnal and 10 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% 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

132 citing papers in PubMed, 1 synthesis or guideline pooled it, 231 citations in OpenAlex.

  1. Pooled it
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  11. New epigenetic players in stroke pathogenesis: From non-coding RNAs to exosomal non-coding RNAs.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2021
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  12. Review
  13. Non-coding RNA · 2020
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  14. MALAT1: a therapeutic candidate for a broad spectrum of vascular and cardiorenal complications.Hypertension research : official journal of the Japanese Society of Hypertension · 2020
    Review
  15. Review
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72 more citing papers are in PubMed but not listed here.

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

20 authors at 8 institutions in 4 countries.

Alessandro GuffantiInstitute of Biomedical Technologies, National Research Council, Milan, Italy. alessandro.guffanti@genomnia.com
Michele Iacono
Paride Pelucchi
Namshin Kim
Giulia Soldà
Larry J Croft
Ryan J Taft
Ermanno Rizzi
Marjan Askarian-Amiri
Raoul J Bonnal
Maurizio Callari
Flavio Mignone
Graziano Pesole
Giovanni Bertalot
Luigi Rossi Bernardi
Alberto Albertini
Christopher Lee
John S Mattick
Ileana Zucchi
Gianluca De Bellis
Institute of Biomedical Technologies · ITNational Research Council · ITUniversity of Queensland · AUUniversity of California, Los Angeles · USUniversity of Milan · ITEuropean Institute of Oncology · ITFondazione IRCCS Istituto Nazionale dei Tumori · ITMultiMedica · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A)+ transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts.

resultsWe analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1, which is highly expressed in many human carcinomas.

conclusionOur results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling.

Indexed as

Gene Expression ProfilingSequence Analysis, DNATranscription, GeneticAmino Acid SequenceBase SequenceBreast NeoplasmsCalmodulin-Binding ProteinsComputational BiologyCytoskeletal ProteinsDatabases, GeneticDNA, ComplementaryFemaleGene Expression Regulation, NeoplasticHistone-Lysine N-MethyltransferaseHumansMolecular Sequence DataCalmodulin-Binding ProteinsCytoskeletal ProteinsDNA, ComplementaryHistone-Lysine N-MethyltransferaseNSD3 protein, humanNuclear ProteinsRNA, UntranslatedUbiquitin-Protein LigasesUBR4 protein, human

Identifiers

PMID19379481
PMCPMC2678161
OpenAlexW2025323279

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.