scholarly journals A generic multivariate framework for the integration of microbiome longitudinal studies with other data types

2019 ◽  
Author(s):  
Antoine Bodein ◽  
Olivier Chapleur ◽  
Arnaud Droit ◽  
Kim-Anh Lê Cao
Keyword(s):  
Microbial Communities ◽  
Time Course ◽  
Molecular Mechanisms ◽  
Smoothing Splines ◽  
Individual Variability ◽  
Integrated Analysis ◽  
Data Types ◽  
Phenotypic Data ◽  
Different Types ◽  
Derived Data

AbstractSimultaneous profiling of biospecimens using different technological platforms enables the study of many data types, encompassing microbial communities, omics and meta-omics as well as clinical or chemistry variables. Reduction in costs now enables longitudinal or time course studies on the same biological material or system. The overall aim of such studies is to investigate relationships between these longitudinal measures in a holistic manner to further decipher the link between molecular mechanisms and microbial community structures, or host-microbiota interactions. However, analytical frameworks enabling an integrated analysis between microbial communities and other types of biological, clinical or phenotypic data are still in their infancy. The challenges include few time points that may be unevenly spaced and unmatched between different data types, a small number of unique individual biospecimens and high individual variability. Those challenges are further exacerbated by the inherent characteristics of microbial communities-derived data (e.g. sparsity, compositional).We propose a generic data-driven framework to integrate different types of longitudinal data measured on the same biological specimens with microbial communities data, and select key temporal features with strong associations within the same sample group. The framework ranges from filtering and modelling, to integration using smoothing splines and multivariate dimension reduction methods to address some of the analytical challenges of microbiome-derived data. We illustrate our framework on different types of multi-omics case studies in bioreactor experiments as well as human studies.

Clinically relevant multi-omic analysis of colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16063-e16063
Author(s):  
Silvia von der Heyde ◽  
Margarita Krawczyk ◽  
Julia Bischof ◽  
Thomas Corwin ◽  
Peter Frommolt ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Biology ◽  
Molecular Mechanisms ◽  
Molecular Signatures ◽  
Data Types ◽  
Comprehensive Overview ◽  
Phenotypic Data ◽  
Patient Cohort ◽  
The Impact ◽  
Omic Data

e16063 Background: Cancer is a highly heterogeneous disease, both intra- and inter-individually consisting of complex phenotypes and systems biology. Although genomic data has contributed greatly towards the identification of cancer-specific mutations and the progress of precision medicine, genomic alterations are only one of several important biological drivers of cancer. Furthermore, single-layer omics represent only a small piece of the cancer biology puzzle and provide only partial clues to connecting genotype with clinically relevant phenotypic data. A more integrated approach is urgently needed to unravel the underpinnings of molecular signatures and the phenotypic manifestation of cancer hallmarks. Methods: Here we characterize a colorectal cancer (CRC) cohort of 500 patients across multiple distinct omic data types. Across this CRC cohort, we defined clinically relevant whole genome sequencing based metrics such as micro-satellite-instability (MSI) status, and furthermore investigate gene expression at the transcript level using RNA-Seq, as well as at the proteomic level using tandem mass spectrometry. We further characterized a subgroup of 100 of these patients through 16s rRNA sequencing to identify associated microbiome profiles. Results: We combined these analyses with comprehensive clinical data to observe the impact of ascertained molecular signatures on the CRC patient cohort. Here, we report how patient survival correlates both with specific molecular events across individual omic data types, as well as with combined multi-omic analyses. Conclusions: This project highlights the utility of integrating multiple distinct data types to obtain a more comprehensive overview of the molecular mechanisms underpinning colo-rectal cancer. Furthermore, through combining identified aberrant molecular mechanisms with clinical reports, multi-omic data can be prioritized through their impact on patient cohort survival.

Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets

2020 ◽  
Author(s):  
Zhuohui Wei ◽  
Yue Zhang ◽  
Wanlin Weng ◽  
Jiazhou Chen ◽  
Hongmin Cai
Keyword(s):  
Molecular Mechanisms ◽  
Genomic Data ◽  
Low Rank ◽  
Integrated Analysis ◽  
Data Sets ◽  
Omics Data ◽  
Data Types ◽  
Cancer Data ◽  
Cancer Types ◽  
Pan Cancer

Abstract The significance of pan-cancer categories has recently been recognized as widespread in cancer research. Pan-cancer categorizes a cancer based on its molecular pathology rather than an organ. The molecular similarities among multi-omics data found in different cancer types can play several roles in both biological processes and therapeutic developments. Therefore, an integrated analysis for various genomic data is frequently used to reveal novel genetic and molecular mechanisms. However, a variety of algorithms for multi-omics clustering have been proposed in different fields. The comparison of different computational clustering methods in pan-cancer analysis performance remains unclear. To increase the utilization of current integrative methods in pan-cancer analysis, we first provide an overview of five popular computational integrative tools: similarity network fusion, integrative clustering of multiple genomic data types (iCluster), cancer integration via multi-kernel learning (CIMLR), perturbation clustering for data integration and disease subtyping (PINS) and low-rank clustering (LRACluster). Then, a priori interactions in multi-omics data were incorporated to detect prominent molecular patterns in pan-cancer data sets. Finally, we present comparative assessments of these methods, with discussion over key issues in applying these algorithms. We found that all five methods can identify distinct tumor compositions. The pan-cancer samples can be reclassified into several groups by different proportions. Interestingly, each method can classify the tumors into categories that are different from original cancer types or subtypes, especially for ovarian serous cystadenocarcinoma (OV) and breast invasive carcinoma (BRCA) tumors. In addition, all clusters of the five computational methods show notable prognostic values. Furthermore, both the 9 recurrent differential genes and the 15 common pathway characteristics were identified across all the methods. The results and discussion can help the community select appropriate integrative tools according to different research tasks or aims in pan-cancer analysis.

Classic and Novel Signaling Pathways Involved in Cancer: Targeting the NF-κB and Syk Signaling Pathways

2019 ◽  
Vol 14 (3) ◽  
pp. 219-225 ◽  
Author(s):  
Cong Tang ◽  
Guodong Zhu
Keyword(s):  
Cancer Therapy ◽  
Tyrosine Kinase ◽  
Signaling Pathways ◽  
Molecular Mechanisms ◽  
Therapeutic Potential ◽  
Cell Receptor ◽  
Transmembrane Receptors ◽  
Biological Responses ◽  
Different Types

The nuclear factor kappa B (NF-κB) consists of a family of transcription factors involved in the regulation of a wide variety of biological responses. Growing evidence support that NF-κB plays a major role in oncogenesis as well as its well-known function in the regulation of immune responses and inflammation. Therefore, we made a review of the diverse molecular mechanisms by which the NF-κB pathway is constitutively activated in different types of human cancers and the potential role of various oncogenic genes regulated by this transcription factor in cancer development and progression. We also discussed various pharmacological approaches employed to target the deregulated NF-κB signaling pathway and their possible therapeutic potential in cancer therapy. Moreover, Syk (Spleen tyrosine kinase), non-receptor tyrosine kinase which mediates signal transduction downstream of a variety of transmembrane receptors including classical immune-receptors like the B-cell receptor (BCR), which can also activate the inflammasome and NF-κB-mediated transcription of chemokines and cytokines in the presence of pathogens would be discussed as well. The highlight of this review article is to summarize the classic and novel signaling pathways involved in NF-κB and Syk signaling and then raise some possibilities for cancer therapy.

Advanced type parameter features

2018 ◽  
Author(s):  
Michael Metcalf ◽  
John Reid ◽  
Malcolm Cohen
Keyword(s):  
Data Types ◽  
Derived Data ◽  
Type Parameter

The advanced type parameter features consist of type parameter enquiry and the ability to parameterize derived-data types.

scholarly journals Immunomodulatory Effects of Radiotherapy

2020 ◽  
Vol 21 (21) ◽  
pp. 8151
Author(s):  
Sharda Kumari ◽  
Shibani Mukherjee ◽  
Debapriya Sinha ◽  
Salim Abdisalaam ◽  
Sunil Krishnan ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Carbon Particle ◽  
Dna Lesions ◽  
X Rays ◽  
Adaptive Immune ◽  
High Let Radiation ◽  
Different Types ◽  
High Let ◽  
Radiation Induced ◽  
Tumor Death

Radiation therapy (RT), an integral component of curative treatment for many malignancies, can be administered via an increasing array of techniques. In this review, we summarize the properties and application of different types of RT, specifically, conventional therapy with x-rays, stereotactic body RT, and proton and carbon particle therapies. We highlight how low-linear energy transfer (LET) radiation induces simple DNA lesions that are efficiently repaired by cells, whereas high-LET radiation causes complex DNA lesions that are difficult to repair and that ultimately enhance cancer cell killing. Additionally, we discuss the immunogenicity of radiation-induced tumor death, elucidate the molecular mechanisms by which radiation mounts innate and adaptive immune responses and explore strategies by which we can increase the efficacy of these mechanisms. Understanding the mechanisms by which RT modulates immune signaling and the key players involved in modulating the RT-mediated immune response will help to improve therapeutic efficacy and to identify novel immunomodulatory drugs that will benefit cancer patients undergoing targeted RT.

scholarly journals Comprehensive Analysis of Transcriptome and Metabolome Reveals the Flavonoid Metabolic Pathway Is Associated with Fruit Peel Coloration of Melon

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2830
Author(s):  
Aiai Zhang ◽  
Jing Zheng ◽  
Xuemiao Chen ◽  
Xueyin Shi ◽  
Huaisong Wang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Fruit Peel ◽  
External Quality ◽  
Color Formation ◽  
Peel Color ◽  
Dark Green

The peel color is an important external quality of melon fruit. To explore the mechanisms of melon peel color formation, we performed an integrated analysis of transcriptome and metabolome with three different fruit peel samples (grey-green ‘W’, dark-green ‘B’, and yellow ‘H’). A total of 40 differentially expressed flavonoids were identified. Integrated transcriptomic and metabolomic analyses revealed that flavonoid biosynthesis was associated with the fruit peel coloration of melon. Twelve differentially expressed genes regulated flavonoids synthesis. Among them, nine (two 4CL, F3H, three F3′H, IFS, FNS, and FLS) up-regulated genes were involved in the accumulation of flavones, flavanones, flavonols, and isoflavones, and three (2 ANS and UFGT) down-regulated genes were involved in the accumulation of anthocyanins. This study laid a foundation to understand the molecular mechanisms of melon peel coloration by exploring valuable genes and metabolites.

scholarly journals Decoding the temporal nature of brain GR activity in the NFκB signal transition leading to depressive-like behavior

2021 ◽  
Author(s):  
Young-Min Han ◽  
Min Sun Kim ◽  
Juyeong Jo ◽  
Daiha Shin ◽  
Seung-Hae Kwon ◽  
...  
Keyword(s):  
Inhibitory Action ◽  
Time Course ◽  
Molecular Mechanisms ◽  
Late Phase ◽  
Fine Tuning ◽  
Dependent Manner ◽  
Middle Phase ◽  
Temporal Shift

AbstractThe fine-tuning of neuroinflammation is crucial for brain homeostasis as well as its immune response. The transcription factor, nuclear factor-κ-B (NFκB) is a key inflammatory player that is antagonized via anti-inflammatory actions exerted by the glucocorticoid receptor (GR). However, technical limitations have restricted our understanding of how GR is involved in the dynamics of NFκB in vivo. In this study, we used an improved lentiviral-based reporter to elucidate the time course of NFκB and GR activities during behavioral changes from sickness to depression induced by a systemic lipopolysaccharide challenge. The trajectory of NFκB activity established a behavioral basis for the NFκB signal transition involved in three phases, sickness-early-phase, normal-middle-phase, and depressive-like-late-phase. The temporal shift in brain GR activity was differentially involved in the transition of NFκB signals during the normal and depressive-like phases. The middle-phase GR effectively inhibited NFκB in a glucocorticoid-dependent manner, but the late-phase GR had no inhibitory action. Furthermore, we revealed the cryptic role of basal GR activity in the early NFκB signal transition, as evidenced by the fact that blocking GR activity with RU486 led to early depressive-like episodes through the emergence of the brain NFκB activity. These results highlight the inhibitory action of GR on NFκB by the basal and activated hypothalamic-pituitary-adrenal (HPA)-axis during body-to-brain inflammatory spread, providing clues about molecular mechanisms underlying systemic inflammation caused by such as COVID-19 infection, leading to depression.

scholarly journals Early alterations of neurovascular unit in the retina in mouse models of tauopathy

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Fan Xia ◽  
Yonju Ha ◽  
Shuizhen Shi ◽  
Yi Li ◽  
Shengguo Li ◽  
...  
Keyword(s):  
Transgenic Mice ◽  
Mouse Models ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Leukocyte Adhesion ◽  
Neurovascular Unit ◽  
Integrated Analysis ◽  
Therapeutic Effects ◽  
Retinal Ganglion ◽  
Potential Biomarker

AbstractThe retina, as the only visually accessible tissue in the central nervous system, has attracted significant attention for evaluating it as a biomarker for neurodegenerative diseases. Yet, most of studies focus on characterizing the loss of retinal ganglion cells (RGCs) and degeneration of their axons. There is no integrated analysis addressing temporal alterations of different retinal cells in the neurovascular unit (NVU) in particular retinal vessels. Here we assessed NVU changes in two mouse models of tauopathy, P301S and P301L transgenic mice overexpressing the human tau mutated gene, and evaluated the therapeutic effects of a tau oligomer monoclonal antibody (TOMA). We found that retinal edema and breakdown of blood–retina barrier were observed at the very early stage of tauopathy. Leukocyte adhesion/infiltration, and microglial recruitment/activation were constantly increased in the retinal ganglion cell layer of tau transgenic mice at different ages, while Müller cell gliosis was only detected in relatively older tau mice. Concomitantly, the number and function of RGCs progressively decreased during aging although they were not considerably altered in the very early stage of tauopathy. Moreover, intrinsically photosensitive RGCs appeared more sensitive to tauopathy. Remarkably, TOMA treatment in young tau transgenic mice significantly attenuated vascular leakage, inflammation and RGC loss. Our data provide compelling evidence that abnormal tau accumulation can lead to pathology in the retinal NVU, and vascular alterations occur more manifest and earlier than neurodegeneration in the retina. Oligomeric tau-targeted immunotherapy has the potential to treat tau-induced retinopathies. These data suggest that retinal NVU may serve as a potential biomarker for diagnosis and staging of tauopathy as well as a platform to study the molecular mechanisms of neurodegeneration.

scholarly journals The role of m6A modification in the biological functions and diseases

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Xiulin Jiang ◽  
Baiyang Liu ◽  
Zhi Nie ◽  
Lincan Duan ◽  
Qiuxia Xiong ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Rna Modification ◽  
Biological Functions ◽  
Rna Methylation ◽  
Downstream Target ◽  
Different Types ◽  
M6a Rna Methylation

AbstractN6-methyladenosine (m6A) is the most prevalent, abundant and conserved internal cotranscriptional modification in eukaryotic RNAs, especially within higher eukaryotic cells. m6A modification is modified by the m6A methyltransferases, or writers, such as METTL3/14/16, RBM15/15B, ZC3H3, VIRMA, CBLL1, WTAP, and KIAA1429, and, removed by the demethylases, or erasers, including FTO and ALKBH5. It is recognized by m6A-binding proteins YTHDF1/2/3, YTHDC1/2 IGF2BP1/2/3 and HNRNPA2B1, also known as “readers”. Recent studies have shown that m6A RNA modification plays essential role in both physiological and pathological conditions, especially in the initiation and progression of different types of human cancers. In this review, we discuss how m6A RNA methylation influences both the physiological and pathological progressions of hematopoietic, central nervous and reproductive systems. We will mainly focus on recent progress in identifying the biological functions and the underlying molecular mechanisms of m6A RNA methylation, its regulators and downstream target genes, during cancer progression in above systems. We propose that m6A RNA methylation process offer potential targets for cancer therapy in the future.

scholarly journals NMDA and AMPA Receptor Autoantibodies in Brain Disorders: From Molecular Mechanisms to Clinical Features

Cells ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 77
Author(s):  
Fabrizio Gardoni ◽  
Jennifer Stanic ◽  
Diego Scheggia ◽  
Alberto Benussi ◽  
Barbara Borroni ◽  
...  
Keyword(s):  
Glutamate Receptors ◽  
Ampa Receptor ◽  
Molecular Mechanisms ◽  
Clinical Symptoms ◽  
In Vivo Studies ◽  
Ionotropic Glutamate Receptors ◽  
Brain Disorders ◽  
Functional Impairments ◽  
Different Types

The role of autoimmunity in central nervous system (CNS) disorders is rapidly expanding. In the last twenty years, different types of autoantibodies targeting subunits of ionotropic glutamate receptors have been found in a variety of patients affected by brain disorders. Several of these antibodies are directed against NMDA receptors (NMDAR), mostly in autoimmune encephalitis, whereas a growing field of research has identified antibodies against AMPA receptor (AMPAR) subunits in patients with different types of epilepsy or frontotemporal dementia. Several in vitro and in vivo studies performed in the last decade have dramatically improved our understanding of the molecular and functional effects induced by both NMDAR and AMPAR autoantibodies at the excitatory glutamatergic synapse and, consequently, their possible role in the onset of clinical symptoms. In particular, the method by which autoantibodies can modulate the localization at synapses of specific target subunits leading to functional impairments and behavioral alterations has been well addressed in animal studies. Overall, these preclinical studies have opened new avenues for the development of novel pharmacological treatments specifically targeting the synaptic activation of ionotropic glutamate receptors.

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