scholarly journals Motif-based phosphoproteome clustering improves modeling and interpretation

2021 ◽  
Author(s):  
Marc Creixell ◽  
Aaron Samuel Meyer
Keyword(s):  
Lung Cancer ◽  
Large Scale ◽  
Genetic Mutations ◽  
Kinase Signaling ◽  
Proteomic Profiling ◽  
Sequence Profile ◽  
Robust Clustering ◽  
Making Sense ◽  
Global View ◽  
Motif Clustering

Cell signaling is orchestrated in part through a network of protein kinases and phosphatases. Dysregulation of kinase signaling is widespread in diseases such as cancer and is readily targetable through inhibitors of kinase enzymatic activity. Mass spectrometry-based analysis of kinase signaling can provide a global view of kinase signaling regulation but making sense of these data is complicated by its stochastic coverage of the proteome, measurement of substrates rather than kinase signaling itself, and the scale of the data collected. Here, we implement a dual data and motif clustering strategy (DDMC) that simultaneously clusters substrate peptides into similarly regulated groups based on their variation within an experiment and their sequence profile. We show that this can help to identify putative upstream kinases and supply more robust clustering. We apply this clustering to large-scale clinical proteomic profiling of lung cancer and identify conserved proteomic signatures of tumorigenicity, genetic mutations, and tumor immune infiltration. We propose that DDMC provides a general and flexible clustering strategy for the analysis of phosphoproteomic data.

scholarly journals Massive and Microscopic Sensemaking During COVID-19 Times

2020 ◽  
pp. 107780042096247 ◽  
Author(s):  
Annette N. Markham ◽  
Anne Harris ◽  
Mary Elizabeth Luka
Keyword(s):  
Critical Pedagogy ◽  
Lived Experience ◽  
Large Scale ◽  
Ethic Of Care ◽  
Feminist Perspective ◽  
The Other ◽  
Self And Other ◽  
Planetary Scale ◽  
Making Sense ◽  
Ongoing Experiment

How does this pandemic moment help us to think about the relationships between self and other, or between humans and the planet? How are people making sense of COVID-19 in their everyday lives, both as a local and intimate occurrence with microscopic properties, and a planetary-scale event with potentially massive outcomes? In this paper we describe our approach to a large-scale, still-ongoing experiment involving more than 150 people from 26 countries. Grounded in autoethnography practice and critical pedagogy, we offered 21 days of self guided prompts to for us and the other participants to explore their own lived experience. Our project illustrates the power of applying a feminist perspective and an ethic of care to engage in open ended collaboration during times of globally-felt trauma.

scholarly journals Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Deborah O. Dele-Oni ◽  
Karen E. Christianson ◽  
Shawn B. Egri ◽  
Alvaro Sebastian Vaca Jacome ◽  
Katherine C. DeRuff ◽  
...  
Keyword(s):  
Large Scale ◽  
Cell Model ◽  
Cellular Responses ◽  
Proteomic Profiling ◽  
Reduced Representation ◽  
Link Type ◽  
Original Dataset ◽  
Quality Control Metrics ◽  
Biological Insight ◽  
Chromatin Profiling

AbstractWhile gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of “connectivity” to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics.

The Survival of Patients with Inoperable Lung Cancer: A Large-Scale Randomized Study of Radiation Therapy Versus Placebo

Radiology ◽  
1968 ◽  
Vol 90 (4) ◽  
pp. 688-697 ◽  
Author(s):  
Bernard Roswit ◽  
Mary Ellen Patno ◽  
Robert Rapp ◽  
Arnolds Veinbergs ◽  
Bernard Feder ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Radiation Therapy ◽  
Large Scale ◽  
Randomized Study

scholarly journals Adherence and competence assessment in studies of CBT for psychosis: current status and future directions

2011 ◽  
Vol 20 (2) ◽  
pp. 121-126 ◽  
Author(s):  
D. Fowler ◽  
R. Rollinson ◽  
P. French
Keyword(s):  
Cognitive Therapy ◽  
Large Scale ◽  
Rating Scale ◽  
Current Status ◽  
Behaviour Therapy ◽  
Future Directions ◽  
Making Sense ◽  
Cognitive Behaviour ◽  
The Uk ◽  
Careful Assessment

All good quality trials of psychological interventions need to check formally that therapists have used the techniques prescribed in the published therapy manuals, and that the therapy has been carried out competently. This paper reviews methods of assessing adherence and competence used in recent large-scale trials of Cognitive Behaviour Therapy (CBT) for psychosis in the UK carried out by our research groups. A combination of the Cognitive Therapy Rating Scale and specific versions of the Cognitive Therapy for Psychosis Adherence Scales provides an optimal assessment of adherence and competence. Careful assessment of the competence and adherence can help identify the procedures actually carried out with individuals within trials. The basic use of such assessments is to provide an external check on treatment fidelity on a sample of sessions. Such assessment can also provide the first step towards moving research towards making sense of CBT for psychosis as a complex intervention and identifying which techniques work for which problems of people with psychosis, at which stages of disorder?

scholarly journals Pipeline design to identify key features and classify the chemotherapy response on lung cancer patients using large-scale genetic data

2018 ◽  
Vol 12 (S5) ◽  
Author(s):  
María Gabriela Valdés ◽  
Iván Galván-Femenía ◽  
Vicent Ribas Ripoll ◽  
Xavier Duran ◽  
Jun Yokota ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Large Scale ◽  
Genetic Data ◽  
Chemotherapy Response ◽  
Lung Cancer Patients ◽  
Key Features ◽  
Pipeline Design

A global view of regulatory networks in lung cancer: An approach to understand homogeneity and heterogeneity

2017 ◽  
Vol 42 ◽  
pp. 31-38 ◽  
Author(s):  
Jiapei Lu ◽  
William Wang ◽  
Menglin Xu ◽  
Yuping Li ◽  
Chengshui Chen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Regulatory Networks ◽  
Global View

scholarly journals Molecular Inverse Comorbidity between Alzheimer’s disease and Lung Cancer: new insights from Matrix Factorization

2019 ◽  
Author(s):  
Alessandro Greco ◽  
Jon Sanchez Valle ◽  
Vera Pancaldi ◽  
Anaïs Baudot ◽  
Emmanuel Barillot ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Matrix Factorization ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Biological Data ◽  
Biological Data Analysis ◽  
Specific Factors ◽  
Molecular Bases

AbstractMatrix Factorization (MF) is an established paradigm for large-scale biological data analysis with tremendous potential in computational biology.We here challenge MF in depicting the molecular bases of epidemiologically described Disease-Disease (DD) relationships. As use case, we focus on the inverse comorbidity association between Alzheimer’s disease (AD) and lung cancer (LC), described as a lower than expected probability of developing LC in AD patients. To the day, the molecular mechanisms underlying DD relationships remain poorly explained and their better characterization might offer unprecedented clinical opportunities.To this goal, we extend our previously designed MF-based framework for the molecular characterization of DD relationships. Considering AD-LC inverse comorbidity as a case study, we highlight multiple molecular mechanisms, among which the previously identified immune system and mitochondrial metabolism. We then discriminate mechanisms specific to LC from those shared with other cancers through a pancancer analysis. Additionally, new candidate molecular players, such as Estrogen Receptor (ER), CDH1 and HDAC, are pinpointed as factors that might underlie the inverse relationship, opening the way to new investigations. Finally, some lung cancer subtype-specific factors are also detected, suggesting the existence of heterogeneity across patients also in the context of inverse comorbidity.

scholarly journals Comprehensive analysis of inhibitor of differentiation/DNA-binding gene family in lung cancer using bioinformatics methods

2020 ◽  
Vol 40 (2) ◽  
Author(s):  
Suming Xu ◽  
Yaoqin Wang ◽  
Yanhong Li ◽  
Lei Zhang ◽  
Chunfang Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Transcription Factor ◽  
Dna Binding ◽  
Mrna Expression ◽  
Family Members ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Genetic Mutations ◽  
Expression Levels ◽  
Mrna Expression Levels

Abstract The inhibitor of differentiation/DNA-binding (ID) is a member of the helix–loop–helix (HLH) transcription factor family, and plays a role in tumorigenesis, invasiveness and angiogenesis. The aims were to investigate the expression patterns and prognostic values of individual ID family members in lung cancer, and the potential functional roles. The expression levels of ID family were assessed using the Oncomine online database and GEPIA database. Furthermore, the prognostic value of ID family members was evaluated using the Kaplan–Meier plotter database. The genetic mutations of ID family members were investigated using the cBioPortal database. Moreover, enrichment analysis was performed using STRING database and Funrich software. It was found that all the ID family members were significantly down-regulated in lung cancer. Prognostic results indicated that low mRNA expression levels of ID1 or increased mRNA expression levels of ID2/3/4 were associated with improved overall survival, first progression and post progression survival. Additionally, genetic mutations of ID family members were identified in lung cancer, and it was suggested that amplification and deep deletion were the main mutation types. Furthermore, functional enrichment analysis results suggested that ID1/2/4 were significantly enriched in ‘regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism’ for biological process, ‘transcription factor activity’ for molecular function and ‘HLH domain’ for protein domain. However, it was found that ID3 was not enriched in the above functions. The aberrant expression of ID family members may affect the occurrence and prognosis of lung cancer, and may be related to cell metabolism and transcriptional regulation.

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