Salem Malikić
A5045683675- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Genetic factors in colorectal cancer
- Evolution and Genetic Dynamics
- Genomics and Phylogenetic Studies
- Genomics and Rare Diseases
- Bioinformatics and Genomic Networks
- Epigenetics and DNA Methylation
- Gene expression and cancer classification
- Genomics and Chromatin Dynamics
- Genomic variations and chromosomal abnormalities
- Pancreatic and Hepatic Oncology Research
- RNA modifications and cancer
- Chromosomal and Genetic Variations
- Cancer-related molecular mechanisms research
- Nutrition, Genetics, and Disease
- Genetics, Bioinformatics, and Biomedical Research
- DNA Repair Mechanisms
- Lung Cancer Treatments and Mutations
- Mitochondrial Function and Pathology
- RNA Research and Splicing
- Cancer, Hypoxia, and Metabolism
- Pharmacogenetics and Drug Metabolism
- Melanoma and MAPK Pathways
- Ferroptosis and cancer prognosis
National Cancer Institute
2020-2025
Center for Cancer Research
2020-2025
Simon Fraser University
2015-2024
National Institutes of Health
2020-2024
Indiana University Bloomington
2015-2020
Genome British Columbia
2020
BC Cancer Agency
2015
Indiana University
2015
Indiana University – Purdue University Indianapolis
2015
Indiana University School of Medicine
2015
Cancer develops through a process of somatic evolution
Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, drivers ITH across cancer types are poorly understood. To address this, we extensively characterize whole-genome sequences 2,658 samples spanning 38 types. Nearly all informative (95.1%) contain evidence distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection driver mutations most...
Abstract Motivation: Intra-tumor heterogeneity presents itself through the evolution of subclones during cancer progression. Although recent research suggests that this has clinical implications, in silico determination clonal subpopulations remains a challenge. Results: We address problem novel combinatorial method, named clonality inference tumors using phylogeny (CITUP), infers populations and their frequencies while satisfying phylogenetic constraints is able to exploit data from...
Abstract Understanding the clonal architecture and evolutionary history of a tumour poses one key challenges to overcome treatment failure due resistant cell populations. Previously, studies on subclonal evolution have been primarily based bulk sequencing in some recent cases single-cell data. Either data type alone has shortcomings with regard this task, but methods integrating both types lacking. Here, we present B-SCITE, first computational approach that infers phylogenies from combined...
Available computational methods for tumor phylogeny inference via single-cell sequencing (SCS) data typically aim to identify the most likely perfect tree satisfying infinite sites assumption (ISA). However, limitations of SCS technologies including frequent allele dropout and variable sequence coverage may prohibit a phylogeny. In addition, ISA violations are commonly observed in phylogenies due loss heterozygosity, deletions, convergent evolution. order address such limitations, we...
Abstract Most current studies rely on short-read sequencing to detect somatic structural variation (SV) in cancer genomes. Long-read offers the advantage of better mappability and long-range phasing, which results substantial improvements germline SV detection. However, long-read detection methods do not generalize well analysis SVs tumor genomes with complex rearrangements, heterogeneity, aneuploidy. Here, we present Severus: a method for accurate different types using phased breakpoint...
High-throughput sequencing provides the means to determine allelic decomposition for any gene of interest-the number copies and exact sequence content each copy a gene. Although many clinically functionally important genes are highly polymorphic have undergone structural alterations, no high-throughput data analysis tool has yet been designed effectively solve full problem. Here we introduce combinatorial optimization framework that successfully resolves this challenging problem, including...
Summary Cancer develops through a process of somatic evolution. Here, we use whole-genome sequencing 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution mutational processes, and driver mutation sequences 39 cancer types. The early phases oncogenesis are driven by point mutations in small set genes, often including biallelic inactivation suppressors. Early is also characterised specific copy number gains, such as trisomy 7 glioblastoma or isochromosome 17q...
Abstract We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines allele frequencies both SV breakends, then simultaneously estimates and copy number. assess performance using in silico mixtures real samples, at known proportions, created two clonal metastases same patient. find that SVclone’s is comparable to single-nucleotide variant-based methods, despite having...
Abstract The type and genomic context of cancer mutations depend on their causes. These causes have been characterized using signatures that represent mutation types co-occur in the same tumours. However, it remains unclear how processes change during evolution due to lack reliable methods reconstruct evolutionary trajectories mutational signature activity. Here, as part ICGC/TCGA Pan-Cancer Analysis Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data from 2658...
Abstract Motivation: CYP2D6 is highly polymorphic gene which encodes the (CYP2D6) enzyme, involved in metabolism of 20–25% all clinically prescribed drugs and other xenobiotics human body. genotyping recommended prior to treatment decisions involving one or more numerous sensitive allelic composition. In this context, high-throughput sequencing (HTS) technologies provide a promising time-efficient cost-effective alternative currently used techniques. To achieve accurate interpretation HTS...
Abstract Melanoma, a highly heterogeneous cancer, evolves through complex interplay of genetic alterations, including both single nucleotide variants (SNVs) and structural (SVs). To study the evolutionary trajectory melanoma, we established model system composed 24 single-cell-derived clonal sublines (C1-C24) from M4 melanoma model, developed in genetically engineered hepatocyte growth factor (HGF)-transgenic mouse. While SNVs have been extensively used to construct phylogenetic trees using...
Abstract Melanoma is the most serious form of skin cancer, developed by malignant evolution melanocytes. Malignant melanoma incidence increasing faster than other cancers. While stage zero highly treatable, survivability dramatically decreases in its advanced stages. has shown to be one heterogeneous cancers from RNA and exome analyses The Cancer Genome Atlas groups. A better understanding key genomic epigenomic events that characterize diverse subclonal populations may reveal insights into...
Abstract Most human cancers arise from somatic alterations, ranging single nucleotide variations to structural (SVs) that can alter the genomic organization. Pathogenic SVs are identified in various cancer types and subtypes, they play a crucial role diagnosis patient stratification. However, studies on have been limited due biological computational challenges, including tumor heterogeneity, aneuploidy, diverse spectrum of simpler deletions focal amplifications catastrophic events shuffling...
SUMMARY Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin drivers ITH across cancer types are poorly understood. To address this question, we extensively characterize whole-genome sequences 2,658 samples, spanning 38 types. Nearly all informative samples (95.1%) contain evidence distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection...
We introduce a new dissimilarity measure between pair of "clonal trees", each representing the progression and mutational heterogeneity tumor sample, constructed by use single cell or bulk high throughput sequencing data. In clonal tree, vertex represents specific clone, is labeled with one more mutations in way that mutation assigned to oldest clone harbors it. Given two trees, our multi-labeled tree (MLTD) defined as minimum number mutation/label deletions, (empty) leaf (clonal)...
Inference of intra-tumor heterogeneity can provide valuable insight into cancer evolution. Somatic mutations detected by sequencing help estimate the purity a tumor sample and reconstruct its subclonal composition. Although several methods have been developed to infer heterogeneity, majority these tools rely on variant allele frequencies as estimated via ultra-deep from multiple samples same tumor. In practice, obtaining data large number per patient is only feasible in few types such liquid...
Abstract Motivation Recent advances in single-cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to phylogeny reconstruction via SCS data are typically based on general computational methods for solving integer linear program, or a constraint satisfaction which, although guaranteeing convergence the most likely solution, very slow. Others Monte Carlo Markov Chain alternative heuristics not only no such guarantee, but also faster...
Abstract Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present first formal study on adaptation gene expression in subclonal evolution. model changes as stochastic Ornstein–Uhlenbeck processes, jointly leveraging history subclones and single-cell data. Applying our sublines derived from single a mouse melanoma revealed that with distinct phenotypes are underlined different patterns adaptation, indicating non-genetic...
Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present a formal study on adaptation gene expression in subclonal evolution. model changes as stochastic Ornstein-Uhlenbeck processes, jointly leveraging history subclones and single-cell data. Applying our sublines derived from single mouse melanoma revealed that with distinct phenotypes are underlined different patterns adaptation, indicating non-genetic mechanisms cancer...
As multi-region, time-series and single-cell sequencing data become more widely available; it is becoming clear that certain tumors share evolutionary characteristics with others. In the last few years, several computational methods have been developed goal of inferring subclonal composition history from tumor biopsy data. However, phylogenetic trees they report differ significantly between (even those similar characteristics).In this article, we present a novel combinatorial optimization...
Recent studies exploring the impact of methylation in tumor evolution suggest that while status many CpG sites are preserved across distinct lineages, others altered as cancer progresses. Since changes a site may be retained mitosis, they could used to infer progression history via single-cell lineage tree reconstruction. In this work, we introduce first principled distance-based computational method, Sgootr, for inferring tumor's single and jointly identifying lineage-informative which...