Copy Number Variation Pattern for Discriminating MACROD2 States of Colorectal Cancer Subtypes

Zhang, Shiqi; Pan, Xiaoyong; Zeng, Tao; Guo, Wei; Gan, Zijun; Zhang, Yuhang; Chen, Lei; Zhang, Yunhua; Huang, Tao; Cai, Yi

doi:10.3389/fbioe.2019.00407

Cited by 19 publications

(16 citation statements)

References 55 publications

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“…Somatic CNV has been found in several types of carcinomas [ 12 , 13 , 14 ] and, in some of them, they are known to be drivers of cancer development [ 15 ] and progression [ 16 ]. They are supposed to be drivers also in PTC since they have been found in a subgroup without any other driver mutation [ 10 ].…”

Section: Discussionmentioning

confidence: 99%

RET Copy Number Alteration in Medullary Thyroid Cancer Is a Rare Event Correlated with RET Somatic Mutations and High Allelic Frequency

Ramone

Mulè

Ciampi

et al. 2020

Genes

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Copy number variations (CNV) of the RET gene have been described in 30% of Medullary Thyroid Cancer (MTC), but no information is available about their role in this tumor. This study was designed to clarify RET gene CNV prevalence and their potential role in MTC development. RET gene CNV were analyzed in 158 sporadic MTC cases using the ION Reporter Software (i.e., in silico analysis) while the multiplex ligation-dependent probe amplification assay (i.e., in vitro analysis) technique was performed in 78 MTC cases. We identified three categories of RET ploidy: 137 in 158 (86.7%) cases were diploid and 21 in 158 (13.3%) were aneuploid. Among the aneuploid cases, five out of 21 (23.8%) showed an allelic deletion while 16 out of 21 (76.2%) had an allelic amplification. The prevalence of amplified or deleted RET gene cases (aneuploid) was higher in RET positive tumors. Aneuploid cases also showed a higher allelic frequency of the RET driver mutation. The prevalence of patients with metastatic disease was higher in the group of aneuploid cases while the higher prevalence of disease-free patients was observed in diploid tumors. A statistically significant difference was found when comparing the ploidy status and mortality. RET gene CNVs are rare events in sporadic MTC and are associated with RET somatic mutation, suggesting that they could not be a driver mechanism of tumoral transformation per se. Finally, we found a positive correlation between RET gene CNV and a worse clinical outcome.

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Section: Discussionmentioning

confidence: 99%

RET Copy Number Alteration in Medullary Thyroid Cancer Is a Rare Event Correlated with RET Somatic Mutations and High Allelic Frequency

Ramone

Mulè

Ciampi

et al. 2020

Genes

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“…Irrelevant features (genes) were excluded by Boruta method. The remaining features were further analyzed by the mRMR method ( Peng et al, 2005 ; Wang et al, 2018 ; Li et al, 2019 , 2020 ; Zhang et al, 2019 ; Zhang S. Q. et al, 2020 ; Chen et al, 2020 ). This method tries to find out essential features with maximum relevance to class labels and minimum redundancy to other features.…”

Section: Methodsmentioning

confidence: 99%

Identifying Transcriptomic Signatures and Rules for SARS-CoV-2 Infection

Zhang

Zeng

et al. 2021

Front. Cell Dev. Biol.

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The world-wide Coronavirus Disease 2019 (COVID-19) pandemic was triggered by the widespread of a new strain of coronavirus named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Multiple studies on the pathogenesis of SARS-CoV-2 have been conducted immediately after the spread of the disease. However, the molecular pathogenesis of the virus and related diseases has still not been fully revealed. In this study, we attempted to identify new transcriptomic signatures as candidate diagnostic models for clinical testing or as therapeutic targets for vaccine design. Using the recently reported transcriptomics data of upper airway tissue with acute respiratory illnesses, we integrated multiple machine learning methods to identify effective qualitative biomarkers and quantitative rules for the distinction of SARS-CoV-2 infection from other infectious diseases. The transcriptomics data was first analyzed by Boruta so that important features were selected, which were further evaluated by the minimum redundancy maximum relevance method. A feature list was produced. This list was fed into the incremental feature selection, incorporating some classification algorithms, to extract qualitative biomarker genes and construct quantitative rules. Also, an efficient classifier was built to identify patients infected with SARS-COV-2. The findings reported in this study may help in revealing the potential pathogenic mechanisms of COVID-19 and finding new targets for vaccine design.

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“…Instead of directly using combined features from network embeddings and functional embeddings for each protein, we further use minimum redundancy maximum relevance (mRMR) (Peng et al, 2005 ) to analyze these embedding features, which has wide applications in tackling different biological problems (Wang et al, 2018 ; Li et al, 2019 , 2020 ; Zhang et al, 2019 , 2020 ; Chen et al, 2020 ). This method has two criteria to evaluate the importance of features.…”

Section: Methodsmentioning

confidence: 99%

Identification of Protein Subcellular Localization With Network and Functional Embeddings

Pan

Zeng

et al. 2021

Front. Genet.

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The functions of proteins are mainly determined by their subcellular localizations in cells. Currently, many computational methods for predicting the subcellular localization of proteins have been proposed. However, these methods require further improvement, especially when used in protein representations. In this study, we present an embedding-based method for predicting the subcellular localization of proteins. We first learn the functional embeddings of KEGG/GO terms, which are further used in representing proteins. Then, we characterize the network embeddings of proteins on a protein–protein network. The functional and network embeddings are combined as novel representations of protein locations for the construction of the final classification model. In our collected benchmark dataset with 4,861 proteins from 16 locations, the best model shows a Matthews correlation coefficient of 0.872 and is thus superior to multiple conventional methods.

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Copy Number Variation Pattern for Discriminating MACROD2 States of Colorectal Cancer Subtypes

Cited by 19 publications

References 55 publications

RET Copy Number Alteration in Medullary Thyroid Cancer Is a Rare Event Correlated with RET Somatic Mutations and High Allelic Frequency

RET Copy Number Alteration in Medullary Thyroid Cancer Is a Rare Event Correlated with RET Somatic Mutations and High Allelic Frequency

Identifying Transcriptomic Signatures and Rules for SARS-CoV-2 Infection

Identification of Protein Subcellular Localization With Network and Functional Embeddings

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