Evidence map›Paper›PMID 23299538›Full record

ArticleBritish journal of cancer2013

Lack of correlation between predicted and actual off-target effects of short-interfering RNAs targeting the human papillomavirus type 16 E7 oncogene.

J E Hanning, H K Saini, M J Murray, S van Dongen, M P A Davis, E M Barker, D M Ward, C G Scarpini, A J Enright, M R Pett and 1 more

Abstract read
In one paragraph

Article in British journal of cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Review
  2. PeerJ · 2017
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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

11 authors.

J E HanningDepartment of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK.
H K Saini
M J Murray
S van Dongen
M P A Davis
E M Barker
D M Ward
C G Scarpini
A J Enright
M R Pett
N Coleman

Funding

Cancer Research UK 13080Medical Research Council MC_U105359875
6 · The paper itself

Abstract

backgroundWhen designing therapeutic short-interfering RNAs (siRNAs), off-target effects (OTEs) are usually predicted by computational quantification of messenger RNAs (mRNAs) that contain matches to the siRNA seed sequence in their 3' UTRs. It is assumed that the higher the number of predicted transcriptional OTEs, the greater the size of the actual OTE signature and the more detrimental the phenotypic consequences in target-negative cells.

methodsWe tested this general assumption by investigating the OTEs of potential therapeutic siRNAs targeting the human papillomavirus (HPV) type-16 E7 oncogene. We studied HPV-negative squamous epithelial cells, from normal cervix (NCx) and skin (HaCaT), which would be vulnerable to 'bystander' OTEs following transfection in vivo.

resultsWe observed no correlation between the number of computationally predicted OTEs and the actual number of seed-dependent OTEs (P=0.76). On average only 20.5% of actual transcriptional OTEs were seed-dependent (i.e., predicted). The unpredicted OTEs included stimulation of innate immune pathways, as well as indirect (downstream) effects of other OTEs, which affected important cancer-associated pathways. Although most significant OTEs observed were seen in both NCx and HaCaT cells, only 0-5.9% of differentially expressed genes overlapped between the two cell types.

conclusionThese data do not support the assumption that actual OTEs correlate well with predicted OTEs.

Indexed as

Carcinoma, Squamous CellCell Line, TumorCervix UteriEpithelial CellsFemaleHuman papillomavirus 16HumansPapillomavirus E7 ProteinsRNA InterferenceRNA, Small InterferingSkinUterine Cervical Neoplasmsoncogene protein E7, Human papillomavirus type 16Papillomavirus E7 ProteinsRNA, Small Interfering

Identifiers

PMID23299538
PMCPMC3566827

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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.