Personalized Computational Modeling of Left Atrial Geometry and Transmural Myofiber Architecture

Publication date: Available online 5 April 2018
Source:Medical Image Analysis
Author(s): Thomas E Fastl, Catalina Tobon-Gomez, Andrew Crozier, John Whitaker, Ronak Rajani, Karen P McCarthy, Damian Sanchez-Quintana, Siew Y Ho, Mark D O'Neill, Gernot Plank, Martin J Bishop, Steven A Niederer
Atrial fibrillation (AF) is a supraventricular tachyarrhythmia characterized by complete absence of coordinated atrial contraction and associated with an increased morbidity and mortality. Personalized computational modeling provides a novel framework for integrating and interpreting the role of atrial electrophysiology (EP) including the underlying anatomy and microstructure in the development and sustenance of AF. Coronary computed tomography angiography data were segmented using a statistics-based approach and the smoothed voxel representations were discretized into high-resolution tetrahedral finite element (FE) meshes. To estimate the complex left atrial myofiber architecture, individual fiber fields were generated according to morphological data on the endo- and epicardial surfaces based on local solutions of Laplace's equation and transmurally interpolated to tetrahedral elements. The influence of variable transmural microstructures was quantified through EP simulations on 3 patients using 5 different fiber interpolation functions. Personalized geometrical models included the heterogeneous thickness distribution of the left atrial myocardium and subsequent discretization led to high-fidelity tetrahedral FE meshes. The novel algorithm for automated incorporation of the left atrial fiber architecture provided a realistic estimate of the atrial microstructure and was able to qualitatively capture all important fiber bundles. Consistent maximum local activation times were predicted in EP simulations using individual transmural fiber interpolation functions for each patient suggesting a negligible effect of the transmural myofiber architecture on EP. The established modeling pipeline provides a robust framework for the rapid development of personalized model cohorts accounting for detailed anatomy and microstructure and facilitates simulations of atrial EP.

Graphical abstract

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Statistical testing and power analysis for brain-wide association study

Publication date: Available online 5 April 2018
Source:Medical Image Analysis
Author(s): Weikang Gong, Lin Wan, Wenlian Lu, Liang Ma, Fan Cheng, Wei Cheng, Stefan Grünewald, Jianfeng Feng
The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://ift.tt/2H20cfC.

Graphical abstract

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Wheezing in infants: A pandemic condition that need to be treated with patience

Publication date: May–June 2018
Source:Allergologia et Immunopathologia, Volume 46, Issue 3
Author(s): L. Garcia-Marcos




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Genomic and Functional Approaches to Understanding Cancer Aneuploidy

Publication date: Available online 2 April 2018
Source:Cancer Cell
Author(s): Alison M. Taylor, Juliann Shih, Gavin Ha, Galen F. Gao, Xiaoyang Zhang, Ashton C. Berger, Steven E. Schumacher, Chen Wang, Hai Hu, Jianfang Liu, Alexander J. Lazar, Andrew D. Cherniack, Rameen Beroukhim, Matthew Meyerson
Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy.

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Teaser

Analyzing >10,000 human cancers, Taylor et al. show that aneuploidy is correlated with somatic mutation rate, expression of proliferation genes, and decreased leukocyte infiltration. Loss of chromosome arm 3p is common in squamous cancers, but deletion of chromosome 3p reduces cell proliferation in vitro.


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Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas

Publication date: Available online 2 April 2018
Source:Cancer Cell
Author(s): Yang Liu, Nilay S. Sethi, Toshinori Hinoue, Barbara G. Schneider, Andrew D. Cherniack, Francisco Sanchez-Vega, Jose A. Seoane, Farshad Farshidfar, Reanne Bowlby, Mirazul Islam, Jaegil Kim, Walid Chatila, Rehan Akbani, Rupa S. Kanchi, Charles S. Rabkin, Joseph E. Willis, Kenneth K. Wang, Shannon J. McCall, Lopa Mishra, Akinyemi I. Ojesina, Susan Bullman, Chandra Sekhar Pedamallu, Alexander J. Lazar, Ryo Sakai, Vésteinn Thorsson, Adam J. Bass, Peter W. Laird
We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared and distinguishing molecular characteristics of gastrointestinal tract adenocarcinomas (GIACs). Hypermutated tumors were distinct regardless of cancer type and comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing of MLH1 in the context of CpG island methylator phenotype, plus tumors with elevated single-nucleotide variants associated with mutations in POLE. Tumors with chromosomal instability were diverse, with gastroesophageal adenocarcinomas harboring fragmented genomes associated with genomic doubling and distinct mutational signatures. We identified a group of tumors in the colon and rectum lacking hypermutation and aneuploidy termed genome stable and enriched in DNA hypermethylation and mutations in KRAS, SOX9, and PCBP1.

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Liu et al. analyze 921 gastrointestinal (GI) tract adenocarcinomas and find that hypermutated tumors are enriched for insertions/deletions, upper GI tumors with chromosomal instability harbor fragmented genomes, and a group of genome-stable colorectal tumors are enriched in mutations in SOX9 and PCBP1.


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Angiogenin/Ribonuclease 5 Is an EGFR Ligand and a Serum Biomarker for Erlotinib Sensitivity in Pancreatic Cancer

Publication date: Available online 29 March 2018
Source:Cancer Cell
Author(s): Ying-Nai Wang, Heng-Huan Lee, Chao-Kai Chou, Wen-Hao Yang, Yongkun Wei, Chun-Te Chen, Jun Yao, Jennifer L. Hsu, Cihui Zhu, Haoqiang Ying, Yuanqing Ye, Wei-Jan Wang, Seung-Oe Lim, Weiya Xia, How-Wen Ko, Xiuping Liu, Chang-Gong Liu, Xifeng Wu, Huamin Wang, Donghui Li, Laura R. Prakash, Matthew H. Katz, Yaan Kang, Michael Kim, Jason B. Fleming, David Fogelman, Milind Javle, Anirban Maitra, Mien-Chie Hung
Pancreatic ribonuclease (RNase) is a secreted enzyme critical for host defense. We discover an intrinsic RNase function, serving as a ligand for epidermal growth factor receptor (EGFR), a member of receptor tyrosine kinase (RTK), in pancreatic ductal adenocarcinoma (PDAC). The closely related bovine RNase A and human RNase 5 (angiogenin [ANG]) can trigger oncogenic transformation independently of their catalytic activities via direct association with EGFR. Notably, high plasma ANG level in PDAC patients is positively associated with response to EGFR inhibitor erlotinib treatment. These results identify a role of ANG as a serum biomarker that may be used to stratify patients for EGFR-targeted therapies, and offer insights into the ligand-receptor relationship between RNase and RTK families.

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Teaser

Wang et al. identify angiogenin (ANG) as a ligand for epidermal growth factor receptor (EGFR). ANG-mediated EGFR activation can trigger oncogenic transformation, and high ANG in the plasma of pancreatic adenocarcinoma patients positively correlates with response to the EGFR inhibitor erlotinib.


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GKAP Acts as a Genetic Modulator of NMDAR Signaling to Govern Invasive Tumor Growth

Publication date: Available online 29 March 2018
Source:Cancer Cell
Author(s): Leanne Li, Qiqun Zeng, Arjun Bhutkar, José A. Galván, Eva Karamitopoulou, Daan Noordermeer, Mei-Wen Peng, Alessandra Piersigilli, Aurel Perren, Inti Zlobec, Hugh Robinson, M. Luisa Iruela-Arispe, Douglas Hanahan
Genetic linkage analysis previously suggested that GKAP, a scaffold protein of the N-methyl-D-aspartate receptor (NMDAR), was a potential modifier of invasion in a mouse model of pancreatic neuroendocrine tumor (PanNET). Here, we establish that GKAP governs invasive growth and treatment response to NMDAR inhibitors of PanNET via its pivotal role in regulating NMDAR pathway activity. Combining genetic knockdown of GKAP and pharmacological inhibition of NMDAR, we implicate as downstream effectors FMRP and HSF1, which along with GKAP demonstrably support invasiveness of PanNET and pancreatic ductal adenocarcinoma cancer cells. Furthermore, we distilled genome-wide expression profiles orchestrated by the NMDAR-GKAP signaling axis, identifying transcriptome signatures in tumors with low/inhibited NMDAR activity that significantly associate with favorable patient prognosis in several cancer types.

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Teaser

Li et al. show that GKAP, a scaffold protein of NMDAR, and its downstream effectors FMRP and HSF1 play important roles in the invasive growth of pancreatic tumors. In several cancer types, low NMDAR activity, based on a transcriptomic signature, associates with favorable patient prognosis.


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