Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma
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Min-Kung Hsu1, Chia-Lin Pan2, Feng-Chi Chen3
1Department of Biological Science and Technology, National Chiao-Tung University, Hsinchu, Taiwan.
Introduction:
Alternative RNA splicing is a critical regulatory mechanism during tumorigenesis. However, previous oncological studies mainly focused on the splicing of individual genes. Whether and how transcript isoforms are coordinated to affect cellular functions remain underexplored. Also of great interest is how the splicing regulome cooperates with the transcription regulome to facilitate tumorigenesis. The answers to these questions are of fundamental importance to cancer biology.
Results:
Here, we report a comparative study between the transcript-based network (TN) and the gene-based network (GN) derived from the transcriptomes of paired tumor-normal tissues from 77 lung adenocarcinoma patients. We demonstrate that the two networks differ significantly from each other in terms of patient clustering and the number and functions of network modules. Interestingly, the majority (89.5%) of multi-transcript genes have their transcript isoforms distributed in at least two TN modules, suggesting regulatory and functional divergences between transcript isoforms. Furthermore, TN and GN modules share onlŷ50%-60% of their biological functions. TN thus appears to constitute a regulatory layer separate from GN. Nevertheless, our results indicate that functional convergence and divergence both occur between TN and GN, implying complex interactions between the two regulatory layers. Finally, we report that the expression profiles of module members in both TN and GN shift dramatically yet concordantly during tumorigenesis. The mechanisms underlying this coordinated shifting remain unclear yet are worth further explorations.
Conclusion:
We show that in lung adenocarcinoma, transcript isoforms per se are coordinately regulated to conduct biological functions not conveyed by the network of genes. However, the two networks may interact closely with each other by sharing the same or related biological functions. Unraveling the effects and mechanisms of such interactions will significantly advance our understanding of this deadly disease.
Insights
In lung adenocarcinoma, RNA transcript isoforms are coordinated to perform functions beyond gene networks. These transcript networks interact with gene networks, offering new insights into cancer biology.
Area of Science:
- Molecular Biology
- Cancer Genomics
- Bioinformatics
Background:
- Alternative RNA splicing is crucial in cancer development.
- Previous research focused on individual gene splicing, neglecting coordinated isoform regulation.
- The interplay between splicing and transcription regulomes in cancer is poorly understood.
Purpose of the Study:
- To compare transcript-based networks (TN) with gene-based networks (GN) in lung adenocarcinoma.
- To investigate the coordination of transcript isoforms and their regulatory mechanisms.
- To explore the interaction between splicing and transcription regulomes in tumorigenesis.
Main Methods:
- Comparative analysis of transcriptomes from paired tumor-normal lung adenocarcinoma tissues (n=77).
- Construction and analysis of transcript-based networks (TN) and gene-based networks (GN).
- Evaluation of network module differences, isoform distribution, and functional overlap.
Main Results:
- Transcript-based networks and gene-based networks show significant differences in patient clustering and module functions.
- Most multi-transcript genes exhibit isoform distribution across multiple TN modules, indicating isoform-specific regulation.
- Transcript-based networks and gene-based networks share only 50-60% of biological functions, suggesting distinct regulatory layers.
- Functional convergence and divergence exist between TN and GN, implying complex interactions.
- Expression profiles in both TN and GN modules shift coordinately during tumorigenesis.
Conclusions:
- Transcript isoforms are coordinately regulated in lung adenocarcinoma, performing functions distinct from gene-level networks.
- Transcript and gene networks interact, potentially by sharing biological functions.
- Further research into these interactions is vital for advancing lung cancer understanding and treatment.
