Biology subjects

Lehtonen, R.

Publications and source records attributed to Lehtonen, R..

2 recordsLinked to original sources

bioRxiv2018

ESR1, WT1, WNT4, ATM and TERT loci are major contributors to uterine leiomyoma predisposition

Uterine leiomyomas (ULs) are benign tumors that are a major burden to womens health. A genome-wide association study on 5,417 UL cases and 331,791 controls was performed, followed by replication of the genomic risk in two cohorts. Effects of the identified risk alleles were evaluated in view of molecular and clinical features.\n\nFive loci displayed a genome-wide significant association; the previously reported TNRC6B, and four novel loci ESR1 (ER), WT1, WNT4, and ATM. The sixth hit TERT is also a conceivable target. The combined polygenic risk contributed by these loci was associated with MED12 mutation-positive tumors. The findings link genes for uterine development and genetic stability to leiomyomagenesis. While the fundamental role of sex hormones in UL aetiology has been clear, this work reveals a connection to estrogen receptor alpha on genetic level and suggests that determinants of UL growth associated with estrogen exposure have an inherited component.

genomics↗

bioRxiv2018

Identifying differentially methylated sites in samples with varying tumor purity

DNA methylation aberrations are common in many cancer types. A major challenge hindering comparison of patient-derived samples is that they comprise of heterogeneous collection of cancer and microenvironment cells. We present a computational method that allows comparing cancer methylomes in two or more heterogeneous tumor samples featuring differing, unknown fraction of cancer cells. The method is unique in that it allows comparison also in the absence of normal cell control samples and without prior tumor purity estimates, as these are often unavailable or unreliable in clinical samples. We use simulations and next-generation methylome, RNA, and whole-genome sequencing data from two cancer types to demonstrate that the method is accurate and outperforms alternatives. The results show that our method adapts well to various cancer types and to a wide range of tumor content, and works robustly without a control or with controls derived from various sources. The method is freely available at https://bitbucket.org/anthakki/dmml.

bioinformatics↗