The sequencing of the human genome has resulted in greater attention to genetic variation among individuals, and variation at the DNA sequence level is now being extensively studied. At the same time, it has become possible to study variation at the level of gene expression by various methods. At present, it is largely unknown how widespread this variation in transcript levels is over the entire genome and to what extent individual differences in expression level are genetically determined. In the present study, we used lymphoblastoid cells to examine variation in gene expression and identified genes whose transcript levels differed greatly among unrelated individuals. We also found evidence for familial aggregation of expression phenotype by comparing variation among unrelated individuals, among siblings within families and between monozygotic twins. These observations suggest that there is a genetic contribution to polymorphic variation in the level of gene expression.

SUMMARY Next-generation sequencing of human tumours has refined our understanding of the mutational processes operative in cancer initiation and progression, yet major questions remain regarding factors that induce driver mutations, and the processes that shape their selection during tumourigenesis. We performed whole-exome sequencing (WES) on adenomas from three mouse models of non-small cell lung cancer (NSCLC), induced by exposure to carcinogens (Methylnitrosourea (MNU) and Urethane), or by genetic activation of Kras (KrasLA2). Although the MNU-induced tumours carried exactly the same initiating mutation in Kras as seen in the KrasLA2 model (G12D), MNU tumours had an average of 192 non-synonymous, somatic single nucleotide variants (SNVs), compared to only 6 in tumours from the KrasLA2 model. In contrast, the KrasLA2 tumours exhibited a significantly higher level of aneuploidy and copy number alterations (CNAs) compared to the carcinogen-induced tumours, suggesting that carcinogen and genetically-engineered models adopt different routes to tumour development. The wild type (WT) allele of Kras has been shown to act as a tumour suppressor in mouse models of NSCLC. We demonstrate that urethane-induced tumours from WT mice carry mostly (94%) Q61R Kras mutations, while those from Kras heterozygous animals carry mostly (92%) Q61L mutations, indicating a major role of germline Kras status in mutation selection during initiation. The exome-wide mutation spectra in carcinogen-induced tumours overwhelmingly display signatures of the initiating carcinogen, while adenocarcinomas acquire additional C>T mutations at CpG sites. These data provide a basis for understanding the conclusions from human tumour genome sequencing that identified two broad categories based on relative frequency of SNVs and CNAs1, and underline the importance of carcinogen models for understanding the complex mutation spectra seen in human cancers.

Hop is a small, divergent homeodomain protein that lacks certain conserved residues required for DNA binding. Hop gene expression initiates early in cardiogenesis and continues in cardiomyocytes throughout embryonic and postnatal development. Genetic and biochemical data indicate that Hop functions directly downstream of Nkx2-5. Inactivation of Hop in mice by homologous recombination results in a partially penetrant embryonic lethal phenotype with severe developmental cardiac defects involving the myocardium. Inhibition of Hop activity in zebrafish embryos likewise disrupts cardiac development and results in severely impaired cardiac function. Hop physically interacts with serum response factor (SRF) and inhibits activation of SRF-dependent transcription by inhibiting SRF binding to DNA. Hop encodes an unusual homeodomain protein that modulates SRF-dependent cardiac-specific gene expression and cardiac development.

BackgroundPathologists use visual classification of glomerular lesions to assess samples from patients with diabetic nephropathy (DN). The results may vary among pathologists. Digital algorithms may reduce this variability and provide more consistent image structure interpretation.MethodsWe developed a digital pipeline to classify renal biopsies from patients with DN. We combined traditional image analysis with modern machine learning to efficiently capture important structures, minimize manual effort and supervision, and enforce biologic prior information onto our model. To computationally quantify glomerular structure despite its complexity, we simplified it to three components consisting of nuclei, capillary lumina and Bowman spaces; and Periodic Acid-Schiff positive structures. We detected glomerular boundaries and nuclei from whole slide images using convolutional neural networks, and the remaining glomerular structures using an unsupervised technique developed expressly for this purpose. We defined a set of digital features which quantify the structural progression of DN, and a recurrent network architecture which processes these features into a classification.ResultsOur digital classification agreed with a senior pathologist whose classifications were used as ground truth with moderate Cohen’s kappa κ = 0.55 and 95% confidence interval [0.50, 0.60]. Two other renal pathologists agreed with the digital classification with κ1 = 0.68, 95% interval [0.50, 0.86] and κ2 = 0.48, 95% interval [0.32, 0.64]. Our results suggest computational approaches are comparable to human visual classification methods, and can offer improved precision in clinical decision workflows. We detected glomerular boundaries from whole slide images with 0.93±0.04 balanced accuracy, glomerular nuclei with 0.94 sensitivity and 0.93 specificity, and glomerular structural components with 0.95 sensitivity and 0.99 specificity.ConclusionsComputationally derived, histologic image features hold significant diagnostic information that may augment clinical diagnostics.

The ubiquitin ligase CUL4A has been implicated in tumorigenesis but its contributions to progression and metastasis have not been evaluated. Here we show that CUL4A is elevated in breast cancer as well as ovarian, gastric and colorectal tumors where its expression level correlates positively with distant metastasis. CUL4A overexpression in normal or malignant human mammary epithelial cells increased their neoplastic properties in vitro and in vivo, markedly increasing epithelial-mesenchymal transition (EMT) and the metastatic capacity of malignant cells. In contrast, silencing CUL4A in aggressive breast cancer cells inhibited these processes. Mechanistically, we found CUL4A modulated histone H3K4me3 at the promoter of the EMT regulatory gene ZEB1 in a manner associated with its transcription. ZEB1 silencing blocked CUL4A-driven proliferation, EMT, tumorigenesis and metastasis. Further, in human breast cancers ZEB1 expression correlated positively with CUL4A expression and distant metastasis. Taken together, our findings reveal a pivotal role of CUL4A in regulating the metastatic behavior of breast cancer cells.