Molecular evolutionary analysis of cancer cell lines

Inference of tumor phylogenies with improved somatic mutation discovery

Next-generation sequencing technologies provide a powerful tool for studying genome evolution during progression of advanced diseases such as cancer. Although many recent studies have employed new sequencing technologies to detect mutations across multiple, genetically related tumors, current methods do not exploit available phylogenetic information to improve the accuracy of their variant calls. Here, we present a novel algorithm that uses somatic single-nucleotide variations (SNVs) in multiple, related tissue samples as lineage markers for phylogenetic tree reconstruction. Our method then leverages the inferred phylogeny to improve the accuracy of SNV discovery. Experimental analyses demonstrate that our method achieves up to 32% improvement for somatic SNV calling of multiple, related samples over the accuracy of GATK's Unified Genotyper, the state-of-the-art multisample SNV caller.

Evolution of the cancer genome

Human tumors result from an evolutionary process operating on somatic cells within tissues, whereby natural selection operates on the phenotypic variability generated by the accumulation of genetic, genomic and epigenetic alterations. This somatic evolution leads to adaptations such as increased proliferative, angiogenic, and invasive phenotypes. In this review we outline how cancer genomes are beginning to be investigated from an evolutionary perspective. We describe recent progress in the cataloging of somatic genetic and genomic alterations, and investigate the contributions of germline as well as epigenetic factors to cancer genome evolution. Finally, we outline the challenges facing researchers who investigate the processes driving the evolution of the cancer genome.

Molecular damage in cancer: an argument for mTOR-driven aging

Despite common belief, accumulation of molecular damage does not play a key role in aging. Still, cancer (an age-related disease) is initiated by molecular damage. Cancer and aging share a lot in common including the activation of the TOR pathway. But the role of molecular damage distinguishes cancer and aging. Furthermore, an analysis of the role of both damage and aging in cancer argues against "a decline, caused by accumulation of molecular damage" as a cause of aging. I also discuss how random molecular damage, via rounds of multiplication and selection, brings about non-random hallmarks of cancer.

Phylogenomics of phosphoinositide lipid kinases: perspectives on the evolution of second messenger signaling and drug discovery

Background

Phosphoinositide lipid kinases (PIKs) generate specific phosphorylated variants of phosatidylinositols (PtdIns) that are critical for second messenger signaling and cellular membrane remodeling. Mammals have 19 PIK isoforms spread across three major families: the PtIns 3-kinases (PI3Ks), PtdIns 4-kinases (PI4Ks), and PtdIns-P (PIP) kinases (PIPKs). Other eukaryotes have fewer yet varying PIK complements. PIKs are also an important, emerging class of drug targets for many therapeutic areas including cancer, inflammatory and metabolic diseases and host-pathogen interactions. Here, we report the genomic occurrences and evolutionary relationships or phylogenomics of all three PIK families across major eukaryotic groups and suggest potential ramifications for drug discovery.

Results

Our analyses reveal four core eukaryotic PIKs which are type III PIK4A and PIK4B, and at least one homolog each from PI3K (possibly PIK3C3 as the ancestor) and PIP5K families. We also applied evolutionary analyses to PIK disease ontology and drug discovery. Mutated PIK3CA are known to be oncogenic and several inhibitors are in anti-cancer clinical trials. We found conservation of activating mutations of PIK3CA in paralogous isoforms suggesting specific functional constraints on these residues. By mapping published compound inhibition data (IC50s) onto a phylogeny of PI3Ks, type II PI4Ks and distantly related, MTOR, ATM, ATR and PRKDC kinases, we also show that compound polypharmacology corresponds to kinase evolutionary relationships. Finally, we extended the rationale for drugs targeting PIKs of malarial Plasmodium falciparum, and the parasites, Leishmania sp. and Trypanosoma sp. by identifying those PIKs highly divergent from human homologs.

Conclusion

Our phylogenomic analysis of PIKs provides new insights into the evolution of second messenger signaling. We postulate two waves of PIK diversification, the first in metazoans with a subsequent expansion in cold-blooded vertebrates that was post-emergence of Deutrostomia\Chordata but prior to the appearance of mammals. Reconstruction of the evolutionary relationships among these lipid kinases also adds to our understanding of their roles in various diseases and assists in their development as potential drug targets.

Domain altering SNPs in the human proteome and their impact on signaling pathways

Single nucleotide polymorphisms (SNPs) constitute an important mode of genetic variations observed in the human genome. A small fraction of SNPs, about four thousand out of the ten million, has been associated with genetic disorders and complex diseases. The present study focuses on SNPs that fall on protein domains, 3D structures that facilitate connectivity of proteins in cell signaling and metabolic pathways. We scanned the human proteome using the PROSITE web tool and identified proteins with SNP containing domains. We showed that SNPs that fall on protein domains are highly statistically enriched among SNPs linked to hereditary disorders and complex diseases. Proteins whose domains are dramatically altered by the presence of an SNP are even more likely to be present among proteins linked to hereditary disorders. Proteins with domain-altering SNPs comprise highly connected nodes in cellular pathways such as the focal adhesion, the axon guidance pathway and the autoimmune disease pathways. Statistical enrichment of domain/motif signatures in interacting protein pairs indicates extensive loss of connectivity of cell signaling pathways due to domain-altering SNPs, potentially leading to hereditary disorders.