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Published on: July 27, 2019

Identification of novel sense and antisense transcription at the TRPM2 locus in cancer

Ugo Orfanelli1, Ann-Kathrin Wenke, Claudio Doglioni

  • 1DIBIT-San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan, Italy.

Cell Research
|October 30, 2008
PubMed

Insights

Researchers identified a new melanoma-associated transcript, TRPM2-AS, which may drive cancer by affecting cell death genes. Its related transcript, TRPM2-TE, also promotes melanoma growth.

Area of Science:

  • Genomics
  • Cancer Biology
  • Molecular Oncology

Background:

  • Cancer is associated with genome-wide hypomethylation, potentially increasing transcriptional noise.
  • Antisense transcripts may arise from this noise, impacting oncosuppressor gene function and promoting malignancy.

Purpose of the Study:

  • To computationally identify and characterize novel antisense transcripts in melanoma.
  • To investigate the role of identified transcripts in melanoma progression and cell death pathways.

Main Methods:

  • Computational identification of melanoma-enriched antisense transcripts.
  • Genomic region analysis and CpG island mapping.
  • Quantitative PCR for transcript expression analysis.
  • Functional studies involving gene knock-out and over-expression.

Main Results:

  • Identification of TRPM2-AS, a melanoma-enriched antisense transcript within the TRPM2 locus.
  • Discovery of TRPM2-TE, another tumor-enriched transcript in the same region, sharing a CpG island with TRPM2-AS.
  • TRPM2-AS and TRPM2-TE were upregulated in melanoma, correlating with the methylation status of the shared CpG island.
  • Knock-out of TRPM2-TE or over-expression of TRPM2 increased melanoma cell susceptibility to apoptosis and necrosis.

Conclusions:

  • TRPM2-AS and TRPM2-TE are key players in melanoma development and progression.
  • Modulating TRPM2 expression impacts melanoma cell death, suggesting therapeutic potential.
  • The findings highlight the broader relevance of antisense transcripts in various cancer types and validate computational approaches for target discovery.

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