86 research outputs found
The microbiota-gut-brain axis:An emerging therapeutic target in chemotherapy-induced cognitive impairment
Chemotherapy-induced cognitive impairment (CICI) is an ill-defined complication of chemotherapy treatment that places a significant psychosocial burden on survivors of cancer and has a considerable impact on the activities of daily living. CICI pathophysiology has not been clearly defined, with candidate mechanisms relating to both the direct cytotoxicity of chemotherapy drugs on the central nervous system (CNS) and more global, indirect mechanisms such as neuroinflammation and blood brain barrier (BBB) damage. A growing body of research demonstrates that changes to the composition of the gastrointestinal microbiota is an initiating factor in numerous neurocognitive conditions, profoundly influencing both CNS immunity and BBB integrity. Importantly, chemotherapy causes significant disruption to the gastrointestinal microbiota. While microbial disruption is a well-established factor in the development of chemotherapy-induced gastrointestinal toxicities (largely diarrhoea), its role in CICI remains unknown, limiting microbial-based therapeutics or risk prediction strategies. Therefore, this review aims to synthesise and critically evaluate the evidence addressing the microbiota-gut-brain axis as a critical factor influencing the development of CICI
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Biological predictors of chemotherapy-induced peripheral neuropathy (CIPN): MASCC neurological complications working group overview.
Chemotherapy-induced peripheral neuropathy (CIPN) is a common and debilitating condition associated with a number of chemotherapeutic agents. Drugs commonly implicated in the development of CIPN include platinum agents, taxanes, vinca alkaloids, bortezomib, and thalidomide analogues. As a drug response can vary between individuals, it is hypothesized that an individual's specific genetic variants could impact the regulation of genes involved in drug pharmacokinetics, ion channel functioning, neurotoxicity, and DNA repair, which in turn affect CIPN development and severity. Variations of other molecular markers may also affect the incidence and severity of CIPN. Hence, the objective of this review was to summarize the known biological (molecular and genomic) predictors of CIPN and discuss the means to facilitate progress in this field
Tomographic phase and attenuation extraction for a sample composed of unknown materials using X-ray propagation-based phase-contrast imaging
Propagation-based phase-contrast X-ray imaging (PB-PCXI) generates image
contrast by utilizing sample-imposed phase-shifts. This has proven useful when
imaging weakly-attenuating samples, as conventional attenuation-based imaging
does not always provide adequate contrast. We present a PB-PCXI algorithm
capable of extracting the X-ray attenuation, , and refraction, ,
components of the complex refractive index of distinct materials within an
unknown sample. The method involves curve-fitting an error-function-based model
to a phase-retrieved interface in a PB-PCXI tomographic reconstruction, which
is obtained when Paganin-type phase-retrieval is applied with incorrect values
of and . The fit parameters can then be used to calculate true
and values for composite materials. This approach requires no
a priori sample information, making it broadly applicable. Our PB-PCXI
reconstruction is single distance, requiring only one exposure per tomographic
angle, which is important for radiosensitive samples. We apply this approach to
a breast-tissue sample, recovering the refraction component, , with 0.6
- 2.4\% accuracy compared to theoretical values.Comment: 8 pages, 4 figures and 1 tabl
Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context
Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas
Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN
Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas
This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing
molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images
of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL
maps are derived through computational staining using a convolutional neural network trained to
classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and
correlation with overall survival. TIL map structural patterns were grouped using standard
histopathological parameters. These patterns are enriched in particular T cell subpopulations
derived from molecular measures. TIL densities and spatial structure were differentially enriched
among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial
infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic
patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for
the TCGA image archives with insights into the tumor-immune microenvironment
EarthFinder Probe Mission Concept Study: Characterizing nearby stellar exoplanet systems with Earth-mass analogs for future direct imaging
EarthFinder is a NASA Astrophysics Probe mission concept selected for study as input to the 2020 Astrophysics National Academies Decadal Survey. The EarthFinder concept is based on a dramatic shift in our understanding of how PRV measurements should be made. We propose a new paradigm which brings the high precision, high cadence domain of transit photometry as demonstrated by Kepler and TESS to the challenges of PRV measurements at the cm/s level. This new paradigm takes advantage of: 1) broad wavelength coverage from the UV to NIR which is only possible from space to minimize the effects of stellar activity; 2) extremely compact, highly stable, highly efficient spectrometers (R>150,000) which require the diffraction-limited imaging possible only from space over a broad wavelength range; 3) the revolution in laser-based wavelength standards to ensure cm/s precision over many years; 4) a high cadence observing program which minimizes sampling-induced period aliases; 5) exploiting the absolute flux stability from space for continuum normalization for unprecedented line-by-line analysis not possible from the ground; and 6) focusing on the bright stars which will be the targets of future imaging missions so that EarthFinder can use a ~1.5 m telescope
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