Publications by authors named "B Abedi-Ardekani"

Various terms are used to describe non-malignant tissue located in the proximity of a tumor, belonging to the organ from which the tumor originated. Traditionally, these tissues, sometimes called "normal adjacent tissue" have been used as controls in cancer studies, and were considered representative of morphologically healthy, non-cancerous tissue. However, with the advancement of OMIC technologies, such tissues are increasingly recognized to be distinct from both tumor and healthy tissues.

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Article Synopsis
  • Next-generation sequencing techniques, like whole-exome and error-corrected sequencing, are used to analyze mutation patterns in both cancerous and non-cancerous tissues.
  • The review emphasizes the potential of using these techniques on archived tissue samples fixed in formalin or alcohol to identify mutational signatures that reflect prior exposure to mutagens.
  • By distinguishing between DNA damage from tissue fixation and true biological mutations, this research helps improve our understanding of cancer causes and supports prevention strategies aimed at reducing exposure to cancer risk agents.
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Tobacco smoke, alone or combined with alcohol, is the predominant cause of head and neck cancer (HNC). Here, we further explore how tobacco exposure contributes to cancer development by mutational signature analysis of 265 whole-genome sequenced HNC from eight countries. Six tobacco-associated mutational signatures were detected, including some not previously reported.

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International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not yet been identified by conventional epidemiology make a substantial contribution to cancer burden. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence. Underlying causes can be inferred by sequencing the genomes of cancers from populations with different incidence rates and detecting differences in patterns of somatic mutations.

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Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.

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