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Sienkiewicz, K.

Publications and source records attributed to Sienkiewicz, K..

4 recordsLinked to original sources

A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.

Somatic mosaicism is an important cause of disease, but mosaic and somatic variants are often challenging to detect because they exist in only a fraction of cells. To address the need for benchmarking subclonal variants in normal cell populations, we developed a benchmark containing mosaic variants in the Genome in a Bottle Consortium (GIAB) HG002 reference material DNA from a large batch of a normal lymphoblastoid cell line. First, we used a somatic variant caller with high coverage (300x) Illumina whole genome sequencing data from the Ashkenazi Jewish trio to detect variants in HG002 not detected in at least 5% of cells from the combined parental data. These candidate mosaic variants were subsequently evaluated using >100x BGI, Element, and PacBio HiFi data. High confidence candidate SNVs with variant allele fractions above 5% were included in the HG002 draft mosaic variant benchmark, with 13/85 occurring in medically relevant gene regions. We also delineated a 2.45 Gbp subset of the previously defined germline autosomal benchmark regions for HG002 in which no additional mosaic variants >2% exist, enabling robust assessment of false positives. The variant allele fraction of some mosaic variants is different between batches of cells, so using data from the homogeneous batch of reference material DNA is critical for benchmarking these variants. External validation of this mosaic benchmark showed it can be used to reliably identify both false negatives and false positives for a variety of technologies and detection algorithms, demonstrating its utility for optimization and validation. By adding our characterization of mosaic variants in this widely-used cell line, we support extensive benchmarking efforts using it in simulation, spike-in, and mixture studies.

bioinformatics↗

Genomic Analyses of the Metastasis-derived LNCaP, VCaP, and PC3-AR Prostate Cancer Cell Lines

The lymph node metastasis-derived LNCaP, the bone metastasis-derived PC3 (skull), and VCaP (vertebral) cell lines are widely used preclinical models of human prostate cancer (CaP) and have been described in >19,000 publications. Here, we report on short-read whole-genome sequencing and genomic analyses of LNCaP, VCaP, and PC3 cells stably transduced with WT AR (PC3-AR). LNCaP cells are composed of multiple subpopulations, which results in non-integral copy number states and a high mutational load when the data is analyzed in bulk. All three cell lines contain pathogenic mutations and homozygous deletions in genes involved in DNA mismatch repair, along with deleterious mutations in cellcycle, Wnt signaling, and other cellular processes. Furthermore, LNCaP cells contain a missense mutation in a well-known CaP hotspot of TP53, whereas both PC3-AR and VCaP have truncating mutations in TP53 and do not express p53 protein. In addition, we detect the signatures of chromothripsis of the q arms of chromosome 5 in both PC3-AR and VCaP cells, strengthening the association of TP53 inactivation with chromothripsis reported in other systems. Our work provides a resource for genetic, genomic, and biological studies employing these commonly-used prostate cancer cell lines.

bioinformatics↗

Data Integration with SUMO Detects Latent Relationships Between Patients in Lower-Grade Gliomas

Joint analysis of multiple genomic data types can facilitate the discovery of complex mechanisms of biological processes and genetic diseases. We present a novel data integration framework based on non-negative matrix factorization that uses patient similarity networks. Our implementation supports continuous multi-omic datasets for molecular subtyping and handles missing data without using imputation, making it more efficient for genome-wide assays in large cohorts. Applying our approach to gene expression, microRNA expression, and methylation data from patients with lower grade gliomas, we identify a subtype with a significantly poorer prognosis. Tumors assigned to this subtype are hypomethylated genome-wide with a gain of AP-1 occupancy in the demethylated distal enhancers. These tumors genomic profiles are similar to Grade IV gliomas: they are enriched for somatic chr7 gain, chr10 loss, and other molecular events that have yet to be used in the diagnosis of lower-grade gliomas as per the current WHO guidelines.

bioinformatics↗

Mapping chromatin accessibility and active regulatory elements reveals new pathological mechanisms in human gliomas

Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We performed whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel novel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we created an atlas of active enhancers and promoters in benign and malignant gliomas. We explored these elements and intersected with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas. SignificanceEpigenetics-driven deregulation of gene expression accompanies cancer development, but its comprehensive characterization in cancer patients is fragmentary. We performed whole-genome profiling of gene expression, open chromatin, histone modifications and DNA-methylation profiles in the same samples from benign and malignant gliomas. Our study provides a first comprehensive atlas of active regulatory elements in gliomas, which allowed identification of the functional enhancers and promoters in patient samples. This comprehensive approach revealed epigenetic patterns influencing gene expression in benign gliomas and a new pathogenic mechanism involving FOXM1-driven network in glioblastomas. This atlas provides a common set of elements for cross-comparisons of existing and new datasets, prompting novel discoveries and better understanding of gliomagenesis. HighlightsO_LIWe provide an atlas of cis-regulatory elements active in human gliomas C_LIO_LIEnhancer-promoter contacts operating in gliomas are revealed C_LIO_LIDiverse enhancer activation is pronounced in malignant gliomas C_LIO_LIChromatin loop activates FOXM1-ANXA2R pathological network in glioblastomas. C_LI

cancer biology↗