Biology subjects

Nichols, K. E.

Publications and source records attributed to Nichols, K. E..

3 recordsLinked to original sources

bioRxiv2026

Telomere length of both parents contribute to heritable POT1 cancer-predisposition syndrome

Germline mutations in POT1 are linked to familial cancer predisposition, and somatic POT1 mutations occur recurrently in tumors. These mutations promote oncogenesis by enabling aberrant telomere elongation. For inherited POT1 mutations, a critical question is the extent to which elongated telomeres are transmitted to the next generation from the POT1 carrier parent and whether the inherited excessively long telomeres elevate cancer risk. Using a nanopore sequencing approach that provides haplotype-specific telomere length measurements, we examined telomere inheritance in families harboring POT1 mutations. We found that individuals preferentially inherit their longest telomeres from the carrier parent, consistent with extensive telomere elongation in the carrier germline, whereas comparatively short telomeres are predominantly inherited from the non-carrier parent. Analysis of carrier and non-carrier siblings further showed that telomeres inherited from both parents are elongated in POT1 carriers, with the shortest telomeres undergoing preferential elongation. These findings support a potential mechanism of genetic anticipation in which POT1 mutations progressively reduce the likelihood that short telomeres capable of enforcing telomere-based tumor suppression are inherited from the carrier parent. Together, our results demonstrate that telomeres inherited from both parents jointly shape telomere-based tumor suppressive barriers. Summary sentenceAllele specific nanopore sequencing reveals that POT1 mutations reshape germline and somatic telomere dynamics, uncovering a novel mechanism of generational anticipation driven by preferential elongation of short inherited telomeres.

genetics↗

bioRxiv2020

A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome

De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation (FM)) of deleterious autosomal dominant germline mutations for any syndrome. We introduce Famdenovo.TP53 for Li-Fraumeni syndrome (LFS) and analyze 324 LFS family pedigrees from four US cohorts: a validation set of 186 pedigrees and a discovery set of 138 pedigrees. The concordance index for Famdenovo.TP53 prediction was 0.95 (95% CI: [0.92, 0.98]). Forty individuals (95% CI: [30, 50]) were predicted as DNM carriers, increasing the total number from 42 to 82. We compared clinical and biological features of FM versus DNM carriers: 1) cancer and mutation spectra along with parental ages were similarly distributed; 2) ascertainment criteria like early-onset breast cancer (age 20 to 35 years) provides a condition for an unbiased estimate of the DNM rate: 48% (23 DNMs versus 25 FMs); 3) hotspot mutation R248W was not observed in DNMs, although it was as prevalent as hotspot mutation R248Q in FMs. Furthermore, we introduce Famdenovo.BRCA for hereditary breast and ovarian cancer syndrome, and apply it to a small set of family data from the Cancer Genetics Network. In summary, we introduce a novel statistical approach to systematically evaluate deleterious DNMs in inherited cancer syndromes. Our approach may serve as a foundation for future studies evaluating how new deleterious mutations can be established in the germline, such as those in TP53.

genetics↗

bioRxiv2018

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): A Cloud-based Platform for Curating and Classifying Germline Variants

Variant interpretation in the era of next-generation sequencing (NGS) is challenging. While many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here we present \"PeCanPIE\" - the Pediatric Cancer Variant Pathogenicity Information Exchange, a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in Variant Call Format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4,000 pediatric cancer patients, and serves as a repository for the expert-reviewed results. While PeCanPIEs web-based interface was designed to be accessible to non-bioinformaticians, its back end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

bioinformatics↗