Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive ...context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.
Local concentrations of mutations are well known in human cancers. However, their three-dimensional spatial relationships in the encoded protein have yet to be systematically explored. We developed a ...computational tool, HotSpot3D, to identify such spatial hotspots (clusters) and to interpret the potential function of variants within them. We applied HotSpot3D to >4,400 TCGA tumors across 19 cancer types, discovering >6,000 intra- and intermolecular clusters, some of which showed tumor and/or tissue specificity. In addition, we identified 369 rare mutations in genes including TP53, PTEN, VHL, EGFR, and FBXW7 and 99 medium-recurrence mutations in genes such as RUNX1, MTOR, CA3, PI3, and PTPN11, all mapping within clusters having potential functional implications. As a proof of concept, we validated our predictions in EGFR using high-throughput phosphorylation data and cell-line-based experimental evaluation. Finally, mutation-drug cluster and network analysis predicted over 800 promising candidates for druggable mutations, raising new possibilities for designing personalized treatments for patients carrying specific mutations.
Networks of biopolymers occur often in nature, and are vulnerable to damage over time. In this work, a coarse grained model of collagen IV molecules is applied in a 2D hexagonal network and the ...mechanisms by which these networks can rupture are explored. The networks are stretched linearly in order to study their structural limits and mechanism of rupture over timescale of up to 100 μs. Metrics are developed to track the damage networks suffer over time, and qualitatively analyse ruptures that occur. Further simulations repeatedly stretch the networks sinusoidally to mimic the
in vivo
strains. Defects of increasing levels of complexity are introduced into an ordered network, and their effect on the rupturing behaviour of the biopolymer networks studied. The effect of introducing holes of varying size in the network, as well as strips of finite width to mimic surgical damage are studied. These demonstrate the importance of the flexibility of the networks to preventing damage.
We use a coarse grained polymer model and a simple graph representation to introduce defects into a biopolymer network, then cause them to rupture.
A method to generate and simulate biological networks is discussed. An expanded Wooten-Winer-Weaire bond switching methods is proposed which allows for a distribution of node degrees in the network ...while conserving the mean average node degree. The networks are characterised in terms of their polygon structure and assortativities (a measure of local ordering). A wide range of experimental images are analysed and the underlying networks quantified in an analogous manner. Limitations in obtaining the network structure are discussed. A "network landscape" of the experimentally observed and simulated networks is constructed from the underlying metrics. The enhanced bond switching algorithm is able to generate networks spanning the full range of experimental observations.
We discuss a Monte Carlo method to simulate biological networks and compare to the underlying networks in experimental images.
Non-coding mutations can create splice sites, however the true extent of how such somatic non-coding mutations affect RNA splicing are largely unexplored. Here we use the MiSplice pipeline to analyze ...783 cancer cases with WGS data and 9494 cases with WES data, discovering 562 non-coding mutations that lead to splicing alterations. Notably, most of these mutations create new exons. Introns associated with new exon creation are significantly larger than the genome-wide average intron size. We find that some mutation-induced splicing alterations are located in genes important in tumorigenesis (ATRX, BCOR, CDKN2B, MAP3K1, MAP3K4, MDM2, SMAD4, STK11, TP53 etc.), often leading to truncated proteins and affecting gene expression. The pattern emerging from these exon-creating mutations suggests that splice sites created by non-coding mutations interact with pre-existing potential splice sites that originally lacked a suitable splicing pair to induce new exon formation. Our study suggests the importance of investigating biological and clinical consequences of noncoding splice-inducing mutations that were previously neglected by conventional annotation pipelines. MiSplice will be useful for automatically annotating the splicing impact of coding and non-coding mutations in future large-scale analyses.
Several studies have evaluated whether the distribution of natural environments differs between marginalized and privileged neighborhoods. However, most studies restricted their analyses to a single ...or handful of cities and used different natural environment measures.
We evaluated whether natural environments are inequitably distributed based on socioeconomic status (SES) and race/ethnicity in the contiguous United States.
We obtained SES and race/ethnicity data (2015-2019) for all U.S. Census tracts. For each tract, we calculated the Normalized Different Vegetation Index (NDVI) for 2020, NatureScore (a proprietary measure of the quantity and quality of natural elements) for 2019, park cover for 2020, and blue space for 1984-2018. We used generalized additive models with adjustment for potential confounders and spatial autocorrelation to evaluate associations of SES and race/ethnicity with NDVI, NatureScore, park cover, and odds of containing blue space in all tracts (
) and in urban tracts (
). To compare effect estimates, we standardized NDVI, NatureScore, and park cover so that beta coefficients presented a percentage increase or decrease of the standard deviation (SD).
Tracts with higher SES had higher NDVI, NatureScore, park cover, and odds of containing blue space. For example, urban tracts in the highest median household income quintile had higher NDVI 44.8% of the SD (95% CI: 42.8, 46.8) and park cover 16.2% of the SD (95% CI: 13.5, 19.0) compared with urban tracts in the lowest median household income quintile. Across all tracts, a lower percentage of non-Hispanic White individuals and a higher percentage of Hispanic individuals were associated with lower NDVI and NatureScore. In urban tracts, we observed weak positive associations between percentage non-Hispanic Black and NDVI, NatureScore, and park cover; we did not find any clear associations for percentage Hispanics.
Multiple facets of the natural environment are inequitably distributed in the contiguous United States. https://doi.org/10.1289/EHP11164.
Although all cancers share common hallmarks, we have long realized that there is no silver-bullet treatment for the disease. Many clinical oncologists specialize in a single cancer type, based ...predominantly on the tissue of origin. With advances brought by genetics and cancer genomic research, we now know that cancers are profoundly different, both in origins and in genetic alterations. At the same time, commonalities such as key driver mutations, altered pathways, mutational, immune and microbial signatures and other areas (many revealed by pan-cancer studies) point to the intriguing possibility of targeting common traits across diverse cancer types with the same therapeutic strategies. Studies designed to delineate differences and similarities across cancer types are thus critical in discerning the basic dynamics of oncogenesis, as well as informing diagnoses, prognoses and therapies. We anticipate growing emphases on the development and application of therapies targeting underlying commonalities of different cancer types, while tailoring to the unique tissue environment and intrinsic molecular fingerprints of each cancer type and subtype. Here we summarize the facets of pan-cancer research and how they are pushing progress toward personalized medicine.
Cerebrospinal fluid (CSF) 42 amino acid species of amyloid beta (Aβ42) and tau levels are strongly correlated with the presence of Alzheimer's disease (AD) neuropathology including amyloid plaques ...and neurodegeneration and have been successfully used as endophenotypes for genetic studies of AD. Additional CSF analytes may also serve as useful endophenotypes that capture other aspects of AD pathophysiology. Here we have conducted a genome-wide association study of CSF levels of 59 AD-related analytes. All analytes were measured using the Rules Based Medicine Human DiscoveryMAP Panel, which includes analytes relevant to several disease-related processes. Data from two independently collected and measured datasets, the Knight Alzheimer's Disease Research Center (ADRC) and Alzheimer's Disease Neuroimaging Initiative (ADNI), were analyzed separately, and combined results were obtained using meta-analysis. We identified genetic associations with CSF levels of 5 proteins (Angiotensin-converting enzyme (ACE), Chemokine (C-C motif) ligand 2 (CCL2), Chemokine (C-C motif) ligand 4 (CCL4), Interleukin 6 receptor (IL6R) and Matrix metalloproteinase-3 (MMP3)) with study-wide significant p-values (p<1.46×10-10) and significant, consistent evidence for association in both the Knight ADRC and the ADNI samples. These proteins are involved in amyloid processing and pro-inflammatory signaling. SNPs associated with ACE, IL6R and MMP3 protein levels are located within the coding regions of the corresponding structural gene. The SNPs associated with CSF levels of CCL4 and CCL2 are located in known chemokine binding proteins. The genetic associations reported here are novel and suggest mechanisms for genetic control of CSF and plasma levels of these disease-related proteins. Significant SNPs in ACE and MMP3 also showed association with AD risk. Our findings suggest that these proteins/pathways may be valuable therapeutic targets for AD. Robust associations in cognitively normal individuals suggest that these SNPs also influence regulation of these proteins more generally and may therefore be relevant to other diseases.
Background
Venous resection may be required to achieve complete resection of pancreatic cancers. We assessed the ability of radiographic criteria to predict the need for superior mesenteric–portal ...vein (SMV-PV) resection and the presence of histologic vein invasion.
Methods
All patients who underwent pancreaticoduodenectomy from 2004 to 2011 at the authors’ institution were identified. Preoperative pancreatic protocol CT images were re-reviewed to characterize the extent of tumor–vein circumferential interface (TVI) as demonstrating no interface, ≤180° of vessel circumference, >180° of vessel circumference, or occlusion. Findings were correlated with the need for venous resection, histologic venous invasion, and survival.
Results
A total of 254 patients underwent pancreaticoduodenectomy and met inclusion criteria; 98 (39.6 %) required SMV-PV resection. In our cohort, 76.4 % of patients received neoadjuvant chemoradiation. The TVI classification system predicted with fair accuracy both the need for SMV-PV resection at the time of surgery and histologic invasion of the vein. In particular, 89.5 % of patients with TVI >180° or occlusion required SMV-PV resection. Of those, 82.4 % had documented histologic SMV-PV invasion. TVI ≤180° was associated with favorable overall survival compared to a greater circumferential interface.
Conclusions
A tomographic classification of the tumor–SMV-PV interface can predict the need for venous resection, pathologic venous involvement, and survival. To assist in treatment planning, a standardized assessment of this anatomic relationship should be routinely performed.
To assess whether a national standard for improving care of deteriorating patients affected ICU admissions following cardiac arrests from hospital wards.
Retrospective study assessing changes from ...baseline (January 1, 2008, to June 30, 2010), rollout (July 1, 2010, to December 31, 2012), and after (January 1, 2013, to 31 December 31, 2014) national standard introduction. Conventional inferential statistics, interrupted time series analysis, and adjusted hierarchical multiple logistic regression analysis.
More than 110 ICU-equipped Australian hospitals.
Adult patients (≥ 18 yr old) admitted to participating ICUs.
Introducing a national framework to improve care of deteriorating patients including color-coded observation charts, mandatory rapid response system, enhanced governance, and staff education for managing deteriorating patients.
Cardiac arrest-related ICU admissions from the ward decreased from 5.6% (baseline) to 4.9% (rollout) and 4.1% (intervention period). Interrupted time series analysis revealed a decline in the rate of cardiac arrest-related ICU admissions in the rollout period, compared with the baseline period (p = 0.0009) with a subsequent decrease in the rate in the intervention period (p = 0.01). Cardiac arrest-related ICU admissions were less likely in the intervention period compared with the baseline period (odds ratio, 0.85; 95% CI, 0.78-0.93; p = 0.001), as was in-hospital mortality from cardiac arrests (odds ratio, 0.79; 95% CI, 0.65-0.96; p = 0.02).
Introducing a national standard to improve the care of deteriorating patients was associated with reduced cardiac arrest-related ICU admissions and subsequent in-hospital mortality of such patients.
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