Related Experiment Video
Updated: May 15, 2026

Use of Interferon-γ Enzyme-linked Immunospot Assay to Characterize Novel T-cell Epitopes of Human Papillomavirus
Published on: March 8, 2012
Lack of correlation between predicted and actual off-target effects of short-interfering RNAs targeting the human
J E Hanning1, H K Saini, M J Murray
1Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK.
Background:
When 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.
Methods:
We 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.
Results:
We 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.
Conclusion:
These data do not support the assumption that actual OTEs correlate well with predicted OTEs.
Insights
Computational prediction of off-target effects (OTEs) in short-interfering RNA (siRNA) therapeutics does not accurately reflect actual transcriptional OTEs. This study found no correlation between predicted and observed OTEs, highlighting limitations in current prediction methods.
Area of Science:
- RNA interference (RNAi) therapeutics
- Computational biology
- Molecular diagnostics
Background:
- Therapeutic short-interfering RNAs (siRNAs) are designed to minimize off-target effects (OTEs).
- Current prediction methods focus on matches between siRNA seed sequences and messenger RNA (mRNA) 3' UTRs.
- It is assumed that more predicted OTEs lead to greater actual OTEs and detrimental phenotypic consequences.
Purpose of the Study:
- To investigate the accuracy of computational prediction of OTEs for therapeutic siRNAs.
- To evaluate the correlation between predicted and actual OTEs in HPV-negative cells.
Main Methods:
- Investigated OTEs of siRNAs targeting the human papillomavirus (HPV) type-16 E7 oncogene.
- Utilized HPV-negative squamous epithelial cells (normal cervix and HaCaT skin cells).
- Analyzed transcriptional OTEs, including seed-dependent and unpredicted effects.
Main Results:
- No correlation was observed between computationally predicted OTEs and actual seed-dependent OTEs (P=0.76).
- Only 20.5% of actual transcriptional OTEs were predicted; unpredicted OTEs involved immune pathways and cancer-associated pathways.
- Differential gene expression overlap between cell types was minimal (0-5.9%).
Conclusions:
- Current computational methods for predicting siRNA OTEs are not well-supported by experimental data.
- Actual OTEs encompass unpredicted effects, including immune responses and downstream pathway alterations.
- The assumption that predicted OTEs correlate with actual OTEs is not supported by these findings.
Related Concept Videos
Initiation of Translation
First, the initiator tRNA must be selected from the pool of elongator tRNAs by eukaryotic initiation factor 2 (eIF2). The initiator tRNA (Met-tRNAi) has conserved sequence elements including modified bases at...
Rous Sarcoma Virus (RSV) and Cancer
RSV is a retrovirus that contains two copies of a plus-strand RNA genome. Its genome consists of four main open...
Rous Sarcoma Virus (RSV) and Cancer
RSV is a retrovirus that contains two copies of a plus-strand RNA genome. Its genome consists of four main open...
Mechanisms of Retrovirus-induced Cancers

