The role of non-coding variants in hereditary cancer syndromes: mechanistic insights and clinical implications

Shinto Bosco1, Shreya Singh Beniwal2, Yamini Saraswathi Gurram3

  • 1Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pimpri, Pune, India.

Insights

Non-coding genetic variants significantly contribute to hereditary cancers by altering gene regulation and RNA function. Incorporating these variants into genetic testing enhances cancer risk prediction and diagnosis accuracy.

Area of Science:

  • Genetics
  • Oncology
  • Molecular Biology

Background:

  • Hereditary cancers are linked to genetic mutations, with a focus on coding regions.
  • Non-coding variants, affecting gene regulation and RNA splicing, are often overlooked in standard genetic tests.
  • A significant portion of hereditary cancer cases remain genetically unresolved after conventional testing.

Purpose of the Study:

  • To highlight the critical role of non-coding mutations in hereditary cancer susceptibility.
  • To review advancements in identifying non-coding variants using whole-genome and RNA sequencing.
  • To discuss the clinical implications and therapeutic potential of non-coding variants.

Main Methods:

  • Review of recent literature on whole-genome sequencing and RNA sequencing.
  • Analysis of molecular mechanisms of non-coding variants in gene expression and splicing.
  • Examination of functional validation strategies and multi-omics data integration.

Main Results:

  • Non-coding mutations significantly impact hereditary cancer risk by altering gene regulation and RNA function.
  • Deep intronic splice-altering variants, enhancer mutations, and dysregulated non-coding RNAs contribute to hereditary cancer susceptibility.
  • RNA-targeted therapies show promise for cancer treatment.

Conclusions:

  • Including non-coding regions in genetic testing improves cancer diagnosis and risk prediction.
  • Understanding non-coding variants is crucial for resolving unresolved familial cancer syndromes.
  • Future research should integrate multi-omics data and advanced tools for personalized cancer diagnostics and therapeutics.

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