Abstract

BACKGROUND

Deep learning through convolutional neural networks (CNN) has recently emerged as a top-performing machine-learning algorithm across various image classification tasks.

OBJECTIVES

We propose a CNN approach that integrates multimodal MRI data, tumor volumetrics, and Karnofsky performance score (KPS) to predict overall survival (OS) in glioma patients with IDH wild-type mutation (IDHwt).

METHODS

High-grade and low-grade IDHwt glioma patients were identified from The Cancer Genome Atlas. Corresponding multimodal MRI (T2, FLAIR, T1-pre and post contrast) were obtained from The Cancer Imaging Archives. A fully-automated algorithm was used to segment tumor margins and determine whole tumor volumes as well as lobe locations. Patients with were stratified into three groups based on OS: poor (1-to-6 months), average (6-to-24 months), high (>24 months). A CNN was used to integrate multimodal MR, tumor volume and location, and KPS to predict patient OS. The 3D CNN is based on a generative-adversarial network for semi-supervised learning utilizing feature-matching. Non-imaging data were integrated into the classifier by concatenation with imaging features in the penultimate layer.

RESULTS

A total of 110 patients were analyzed (26 poor-survival, 61 average-survival, 23 high-survival). Single-factor ANOVA did not detect a significant difference in OS based on tumor volume, lobe location, or KPS parameters individually. However, integrated multimodal CNN accurately predicted survival cohort in 82% of patients by five-fold validation. Features most highly correlated with survival were identified.

CONCLUSION

A deep learning algorithm integrating imaging and clinical data can predict OS in IDHwt glioma with 82% accuracy. Future work will validate this methodology prospectively.

OBJECTIVE: Intravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma. METHODS: Fifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm2. Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses. RESULTS: We found that fCER and D*CER correlated with rCBFCER. The best cutoffs for 6-month survival were fCER>9.86% and D*CER>21.712 x10-3mm2/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162-25.88; AUC: 0.723; P = 0.031); fCER combined with treatment predicted survival with 100% accuracy. CONCLUSIONS: The IVIM-metrics fCER and D*CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma.

Functional diffusion mapping (fDM) is a cancer imaging technique that quantifies voxelwise changes in apparent diffusion coefficient (ADC). Previous studies have shown value of fDMs in bevacizumab therapy for recurrent glioblastoma multiforme (GBM). The aim of the present study was to implement explicit criteria for diffusion MRI quality control and independently evaluate fDM performance in a multicenter clinical trial (RTOG 0625/ACRIN 6677). A total of 123 patients were enrolled in the current multicenter trial and signed institutional review board-approved informed consent at their respective institutions. MRI was acquired prior to and 8 weeks following therapy. A 5-point QC scoring system was used to evaluate DWI quality. fDM performance was evaluated according to the correlation of these metrics with PFS and OS at the first follow-up time-point. Results showed ADC variability of 7.3% in NAWM and 10.5% in CSF. A total of 68% of patients had usable DWI data and 47% of patients had high quality DWI data when also excluding patients that progressed before the first follow-up. fDM performance was improved by using only the highest quality DWI. High pre-treatment contrast enhancing tumor volume was associated with shorter PFS and OS. A high volume fraction of increasing ADC after therapy was associated with shorter PFS, while a high volume fraction of decreasing ADC was associated with shorter OS. In summary, DWI in multicenter trials are currently of limited value due to image quality. Improvements in consistency of image quality in multicenter trials are necessary for further advancement of DWI biomarkers.

The low-density lipoprotein receptor (LDLR) controls cellular delivery of cholesterol and clears LDL from the bloodstream, protecting against atherosclerotic heart disease, the leading cause of death in the United States. We therefore sought to identify regulators of the LDLR beyond the targets of current clinical therapies and known causes of familial hypercholesterolemia. We show that Cold Shock Domain-Containing Protein E1 (CSDE1) enhances hepatic LDLR mRNA decay via its 3’ untranslated region to regulate atherogenic lipoproteins in vivo . Using parallel phenotypic genome-wide CRISPR interference screens, we found 40 specific regulators of the LDLR left unidentified by observational human genetics. Among these, we show that CSDE1 regulates the LDLR at least as strongly as the mechanistically distinct pathways exploited by the best available clinical therapies: statins and PCSK9 inhibitors. Additionally, we show that hepatic gene silencing of Csde1 treats diet-induced dyslipidemia in mice better than that of Pcsk9 . Our results reveal the therapeutic potential of manipulating a newly identified key factor in the post-transcriptional regulation of the LDLR mRNA for the prevention of cardiovascular disease. We anticipate that our approach of modelling a clinically relevant phenotype in a forward genetic screen, followed by mechanistic pharmacologic dissection and in vivo validation, will serve as a generalizable template for the identification of therapeutic targets in other human disease states.

One Sentence Summary

A genome-wide CRISPR screen identifies CSDE1 as a key regulator of hepatic LDLR mRNA decay in vivo , making it a promising target for heart disease.

Graphical Abstract

Prior efforts to identify regulators of hematopoietic stem cell physiology have relied mainly on candidate gene approaches with genetically modified mice. Here we used a genome-wide association study (GWAS) strategy with the hybrid mouse diversity panel to identify the genetic determinants of hematopoietic stem/progenitor cell (HSPC) frequency. Among 108 strains, we observed ∼120- to 300-fold variation in three HSPC populations. A GWAS analysis identified several loci that were significantly associated with HSPC frequency, including a locus on chromosome 5 harboring the homeodomain-only protein gene (Hopx). Hopx previously had been implicated in cardiac development but was not known to influence HSPC biology. Analysis of the HSPC pool in Hopx-/- mice demonstrated significantly reduced cell frequencies and impaired engraftment in competitive repopulation assays, thus providing functional validation of this positional candidate gene. These results demonstrate the power of GWAS in mice to identify genetic determinants of the hematopoietic system.

We have tested the predictive value of apparent diffusion coefficient (ADC) histogram analysis in stratifying progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients with recurrent glioblastoma multiforme (GBM) from the multi-center BRAIN study. Available MRI's from patients enrolled in the BRAIN study (n = 97) were examined by generating ADC histograms from areas of enhancing tumor on T1 weighted post-contrast images fitted to a two normal distribution mixture curve. ADC classifiers including the mean ADC from the lower curve (ADC-L) and the mean lower curve proportion (LCP) were tested for their ability to stratify PFS and OS by using Cox proportional hazard ratios and the Kaplan-Meier method with log-rank test. Mean ADC-L was 1,209 × 10(-6)mm(2)/s ± 224 (SD), and mean LCP was 0.71 ± 0.23 (SD). Low ADC-L was associated with worse outcome. The hazard ratios for 6-month PFS, overall PFS, and OS in patients with less versus greater than mean ADC-L were 3.1 (95 % confidence interval: 1.6, 6.1; P = 0.001), 2.3 (95 % CI: 1.3, 4.0; P = 0.002), and 2.4 (95 % CI: 1.4, 4.2; P = 0.002), respectively. In patients with ADC-L <1,209 and LCP >0.71 versus ADC-L >1,209 and LCP <0.71, there was a 2.28-fold reduction in the median time to progression, and a 1.42-fold decrease in the median OS. The predictive value of ADC histogram analysis, in which low ADC-L was associated with poor outcome, was confirmed in bevacizumab-treated patients with recurrent GBM in a post hoc analysis from the multi-center (BRAIN) study.

Background

Gene regulatory networks control tissue homeostasis and disease progression in a cell type-specific manner. Ubiquitously expressed chromatin regulators modulate these networks, yet the mechanisms governing how tissue specificity of their function is achieved are poorly understood. BRD4 (bromodomain-containing protein 4), a member of the BET (bromo- and extraterminal domain) family of ubiquitously expressed acetyl-lysine reader proteins, plays a pivotal role as a coactivator of enhancer signaling across diverse tissue types in both health and disease and has been implicated as a pharmacological target in heart failure. However, the cell-specific role of BRD4 in adult cardiomyocytes remains unknown.

Methods

We combined conditional mouse genetics, unbiased transcriptomic and epigenomic analyses, and classic molecular biology and biochemical approaches to understand the mechanism by which BRD4 in adult cardiomyocyte homeostasis.

Results

Here, we show that cardiomyocyte-specific deletion of Brd4 in adult mice leads to acute deterioration of cardiac contractile function with mutant animals demonstrating a transcriptomic signature characterized by decreased expression of genes critical for mitochondrial energy production. Genome-wide occupancy data show that BRD4 enriches at many downregulated genes (including the master coactivators Ppargc1a, Ppargc1b, and their downstream targets) and preferentially colocalizes with GATA4 (GATA binding protein 4), a lineage-determining cardiac transcription factor not previously implicated in regulation of adult cardiac metabolism. BRD4 and GATA4 form an endogenous complex in cardiomyocytes and interact in a bromodomain-independent manner, revealing a new functional interaction partner for BRD4 that can direct its locus and tissue specificity.

Conclusions

These results highlight a novel role for a BRD4-GATA4 module in cooperative regulation of a cardiomyocyte-specific gene program governing bioenergetic homeostasis in the adult heart.

Pathogenic mutations in LAMIN A/C (LMNA) cause abnormal nuclear structure and laminopathies. These diseases have myriad tissue-specific phenotypes, including dilated cardiomyopathy (DCM), but how LMNA mutations result in tissue-restricted disease phenotypes remains unclear. We introduced LMNA mutations from individuals with DCM into human induced pluripotent stem cells (hiPSCs) and found that hiPSC-derived cardiomyocytes, in contrast to hepatocytes or adipocytes, exhibit aberrant nuclear morphology and specific disruptions in peripheral chromatin. Disrupted regions were enriched for transcriptionally active genes and regions with lower LAMIN B1 contact frequency. The lamina-chromatin interactions disrupted in mutant cardiomyocytes were enriched for genes associated with non-myocyte lineages and correlated with higher expression of those genes. Myocardium from individuals with LMNA variants similarly showed aberrant expression of non-myocyte pathways. We propose that the lamina network safeguards cellular identity and that pathogenic LMNA variants disrupt peripheral chromatin with specific epigenetic and molecular characteristics, causing misexpression of genes normally expressed in other cell types.

Respiratory disease is the third leading cause of death in the industrialized world. Consequently, the trachea, lungs, and cardiopulmonary vasculature have been the focus of extensive investigations. Recent studies have provided new information about the mechanisms driving lung development and differentiation. However, there is still much to learn about the ability of the adult respiratory system to undergo repair and to replace cells lost in response to injury and disease. This Review highlights the multiple stem/progenitor populations in different regions of the adult lung, the plasticity of their behavior in injury models, and molecular pathways that support homeostasis and repair.