Epigenetic regulation during cancer transitions across 11 tumour types

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasi

Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment.

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs\u27 recapitulation of human tumors

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease

Fast Evolution from Precast Bricks: Genomics of Young Freshwater Populations of Threespine Stickleback <i>Gasterosteus aculeatus</i>

<div><p>Adaptation is driven by natural selection; however, many adaptations are caused by weak selection acting over large timescales, complicating its study. Therefore, it is rarely possible to study selection comprehensively in natural environments. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is a well-studied model organism with a short generation time, small genome size, and many genetic and genomic tools available. Within this originally marine species, populations have recurrently adapted to freshwater all over its range. This evolution involved extensive parallelism: pre-existing alleles that adapt sticklebacks to freshwater habitats, but are also present at low frequencies in marine populations, have been recruited repeatedly. While a number of genomic regions responsible for this adaptation have been identified, the details of selection remain poorly understood. Using whole-genome resequencing, we compare pooled genomic samples from marine and freshwater populations of the White Sea basin, and identify 19 short genomic regions that are highly divergent between them, including three known inversions. 17 of these regions overlap protein-coding genes, including a number of genes with predicted functions that are relevant for adaptation to the freshwater environment. We then analyze four additional independently derived young freshwater populations of known ages, two natural and two artificially established, and use the observed shifts of allelic frequencies to estimate the strength of positive selection. Adaptation turns out to be quite rapid, indicating strong selection acting simultaneously at multiple regions of the genome, with selection coefficients of up to 0.27. High divergence between marine and freshwater genotypes, lack of reduction in polymorphism in regions responsible for adaptation, and high frequencies of freshwater alleles observed even in young freshwater populations are all consistent with rapid assembly of <i>G. aculeatus</i> freshwater genotypes from pre-existing genomic regions of adaptive variation, with strong selection that favors this assembly acting simultaneously at multiple loci.</p></div

Map showing the locations of populations studied.

<p>Please see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004696#pgen-1004696-t001" target="_blank">Table 1</a> for description of sampling sites.</p

Sampling sites and library characteristics.

a<p>marine population;</p>b<p>recent natural freshwater populations;</p>c<p>artificial freshwater populations;</p>d<p>older natural freshwater populations.</p><p>Columns provide description, coordinates of the sampling sites, number of individuals in the sample, characteristic of the libraries, numbers of reads, coverage and nucleotide diversity for each sample.</p><p>Sampling sites and library characteristics.</p

SNPs in protein-coding genes.

<p>The numbers of nonsynonymous and synonymous SNPs within DIs and outside them, in the comparison of two marine and two freshwater populations (marker SNPs, under the strong criterion) and SNPs within the Nilma marine population.</p><p>SNPs in protein-coding genes.</p

Comparison of mean frequencies of freshwater alleles at marker SNPs within and outside of identified DIs, at freshwater populations of different ages.

<p>Each two boxes correspond to the four young freshwater populations (anadromous from Lake Ershovskoye, Lake Martsy, Quarry Malysh, Quarry Goluboy). Statistical analysis was performed with two-tailed nonparametric Mann–Whitney <i>U</i> test. P values of <0.001 are designated with three (***) asterisks. Dashes, boxes and whiskers correspond to the median, standard deviation, and 5^th and 95^th percentiles, respectively. Red, marker SNPs (under the strong criterion) located within clumps; purple, marker SNPs (under the strong criterion) located outside clumps.</p

Mean frequencies of freshwater alleles at marker SNPs within identified DIs, at freshwater populations of different ages.

<p>(<b>A</b>) Natural populations. The horizontal axis shows the approximate ages of populations, ranging (left to right) from two marine populations (∼0 years) to recent (∼34 and ∼250 years) and older lake populations (∼600 and ∼700 years). Whiskers, standard deviation. (<b>B</b>) Experimental populations. For each of the DIs of marker SNPs, the assumed initial 50% frequency of freshwater alleles (black line) and their current frequencies are shown for two experimental populations: quarries Malysh (left) and Goluboy (right), each started in 1978. Dashes, boxes and whiskers correspond to the median, standard deviation, and 5^th and 95^th percentiles, respectively. Red, DIs identified under the strong criterion; blue, DIs identified under the weak criterion.</p