Biology subjects

Maley, C. C.

Publications and source records attributed to Maley, C. C..

24 records · Page 2Linked to original sources

bioRxiv2020

A new method to accurately identify single nucleotide variants using small FFPE breast samples.

Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however, it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing algorithms. We found that the SNV-identification accuracy declined when there was less than 40ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ (DCIS) of the breast to their adjacent invasive ductal carcinoma (IDC) samples. We observed an increased number of mutations (paired-samples sign test, p<0.05), and a higher genetic divergence in the invasive samples (paired-samples sign test, p<0.01). Our algorithm provides a significant improvement in detecting SNVs in FFPE samples over previous approaches. Key PointsO_LIThe sequencing of reduced quantities of DNA extracted from FFPE samples leads to substantial sequencing errors that require correction in order to obtain accurate detection of somatic mutations. C_LIO_LIWe developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants using small amounts of DNA extracted from archival FFPE samples of breast cancers. C_LIO_LIVariant calling software packages need to be optimized to reduce the impact of sequencing errors. Our bioinformatics pipeline represents a significant methodological advance compared to the currently available bioinformatic tools used for the analysis of small FFPE samples. C_LI

genomics↗

bioRxiv2020

Elephant genomes reveal insights into differences in disease defense mechanisms between species

Disease susceptibility and resistance comprise important factors in conservation, particularly in elephants. To determine genetic mechanisms underlying disease resistance and other unique elephant traits, we estimated 862 and 1,017 potential regulatory elements in Asian and African elephants, respectively. These elements are significantly enriched in both species with differentially expressed genes involved in immunity pathways, including tumor-necrosis factor which plays a role in the response to elephant endotheliotropic herpesvirus (EEHV). Population genomics analyses indicate that amplified TP53 retrogenes are maintained by purifying selection and may contribute to cancer resistance in elephants, including less malignancies in African vs. Asian elephants. Positive selection scans across elephant genomes revealed genes that may control iconic elephant traits such as tusk development, memory, and somatic maintenance. Our study supports the hypothesis that interspecies variation in gene regulation contributes to differential inflammatory responses leading to increased infectious disease and cancer susceptibility in Asian versus African elephants. Genomics can inform functional immunological studies which may improve both conservation for elephants and human therapies.

evolutionary biology↗

bioRxiv2020

The Evolution of Human Cancer Gene Duplications across Mammals

Cancer is caused by genetic alterations that affect cellular fitness, and multicellular organisms have evolved mechanisms to suppress cancer such as cell cycle checkpoints and apoptosis. These pathways may be enhanced by the addition of tumor suppressor gene paralogs or deletion of oncogenes. To provide insights to the evolution of cancer suppression across the mammalian radiation, we estimated copy numbers for 548 human tumor suppressor gene and oncogene homologs in 63 mammalian genome assemblies. The naked mole rat contained the most cancer gene copies, consistent with the extremely low rates of cancer found in this species. We found a positive correlation between a species cancer gene copy number and its longevity, but not body size, contrary to predictions from Petos Paradox. Extremely long-lived mammals also contained more copies of caretaker genes in their genomes, suggesting that the maintenance of genome integrity is an essential form of cancer prevention in long-lived species. We found the strongest association between longevity and copy numbers of genes that are both germline and somatic tumor suppressor genes, suggesting selection has acted to suppress both hereditary and sporadic cancers. We also found a strong relationship between the number of tumor suppressor genes and the number of oncogenes in mammalian genomes, suggesting complex regulatory networks mediate the balance between cell proliferation and checks on tumor progression. This study is the first to investigate cancer gene expansions across the mammalian radiation and provides a springboard for potential human therapies based on evolutionary medicine.

evolutionary biology↗

bioRxiv2019

Minimal Barriers to Invasion During Human Colorectal Tumor Growth

Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes. We delineated these modes of invasion by merging ancestral, topographic, and phenotypic information from 12 human colorectal tumors (11 carcinomas, 1 adenoma) obtained through saturation microdissection of 325 small tumor regions. The majority of subclones (29/46, 60%) shared superficial and invasive phenotypes. Of 11 carcinomas, 9 showed evidence of multiclonal invasion, and invasive and metastatic subclones arose early along the ancestral trees. Early multiclonal invasion in the majority of these tumors indicates the expansion of co-evolving subclones with similar malignant potential in absence of late bottlenecks, and suggests that barriers to invasion are minimal during colorectal cancer growth.

cancer biology↗

bioRxiv2019

Exploiting evolutionary herding to control drug resistance in cancer

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased growth rate or increased sensitivity to another drug due to evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called evolutionary herding that aims at controlling the tumour cell population to delay or prevent resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here we present a novel approach for evolutionary herding based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, longitudinal non-destructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary herding in non-small cell lung cancer, showing that herding allows shifting the clonal composition of a tumour in our favour, leading to collateral drug sensitivity and proliferative fitness costs. Through genomic analysis and single-cell sequencing, we were also able to determine the mechanisms that drive such evolved sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can potentially be translated into the clinic to control treatment resistance.

cancer biology↗

bioRxiv2018

Cryptsim: Modeling the evolutionary dynamics of the progression of Barrett’s esophagus to esophageal adenocarcinoma

To alleviate the over-diagnosis and overtreatment of premalignant conditions we need to predict their progression to cancer, and therefore, the dynamics of an evolutionary process. However, monitoring evolutionary processes in vivo is extremely challenging. Computer simulations constitute an attractive alternative, allowing us to study these dynamics based on a set of evolutionary parameters.\n\nWe introduce CryptSim, a simulator of crypt evolution inspired by Barretts esophagus. We detail the most relevant computational strategies it implements, and perform a simulation study showing that the interaction between neighboring crypts may play a crucial role in carcinogenesis.

cancer biology↗