Particulate Matters Affecting lncRNA Dysregulation and Glioblastoma Invasiveness: In Silico Applications and Current Insights
With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation wit...
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| Published in | Journal of molecular neuroscience Vol. 72; no. 11; pp. 2188 - 2206 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.11.2022
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0895-8696 1559-1166 1559-1166 |
| DOI | 10.1007/s12031-022-02069-9 |
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| Abstract | With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation with various health hazards and have also been determined to be carcinogenic. In addition to disrupting known cellular pathways, PMs have also been associated with lncRNA dysregulation—a factor that increases predisposition towards the onset or progression of cancer. lncRNA dysregulation is further seen to mediate glioblastoma multiforme (GBM) progression. The vast array of information regarding cancer types including GBM and its various precursors can easily be obtained via innovative in silico approaches in the form of databases such as GEO and TCGA; however, a need to obtain selective and specific information correlating anthropogenic factors and disease progression—in the case of GBM—can serve as a critical tool to filter down and target specific PMs and lncRNAs responsible for regulating key cancer hallmarks in glioblastoma. The current review article proposes an in silico approach in the form of a database that reviews current updates on correlation of PMs with lncRNA dysregulation leading to GBM progression. |
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| AbstractList | With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation with various health hazards and have also been determined to be carcinogenic. In addition to disrupting known cellular pathways, PMs have also been associated with lncRNA dysregulation—a factor that increases predisposition towards the onset or progression of cancer. lncRNA dysregulation is further seen to mediate glioblastoma multiforme (GBM) progression. The vast array of information regarding cancer types including GBM and its various precursors can easily be obtained via innovative in silico approaches in the form of databases such as GEO and TCGA; however, a need to obtain selective and specific information correlating anthropogenic factors and disease progression—in the case of GBM—can serve as a critical tool to filter down and target specific PMs and lncRNAs responsible for regulating key cancer hallmarks in glioblastoma. The current review article proposes an in silico approach in the form of a database that reviews current updates on correlation of PMs with lncRNA dysregulation leading to GBM progression. With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation with various health hazards and have also been determined to be carcinogenic. In addition to disrupting known cellular pathways, PMs have also been associated with lncRNA dysregulation-a factor that increases predisposition towards the onset or progression of cancer. lncRNA dysregulation is further seen to mediate glioblastoma multiforme (GBM) progression. The vast array of information regarding cancer types including GBM and its various precursors can easily be obtained via innovative in silico approaches in the form of databases such as GEO and TCGA; however, a need to obtain selective and specific information correlating anthropogenic factors and disease progression-in the case of GBM-can serve as a critical tool to filter down and target specific PMs and lncRNAs responsible for regulating key cancer hallmarks in glioblastoma. The current review article proposes an in silico approach in the form of a database that reviews current updates on correlation of PMs with lncRNA dysregulation leading to GBM progression.With a reported rise in global air pollution, more than 50% of the population remains exposed to toxic air pollutants in the form of particulate matters (PMs). PMs, from various sources and of varying sizes, have a significant impact on health as long-time exposure to them has seen a correlation with various health hazards and have also been determined to be carcinogenic. In addition to disrupting known cellular pathways, PMs have also been associated with lncRNA dysregulation-a factor that increases predisposition towards the onset or progression of cancer. lncRNA dysregulation is further seen to mediate glioblastoma multiforme (GBM) progression. The vast array of information regarding cancer types including GBM and its various precursors can easily be obtained via innovative in silico approaches in the form of databases such as GEO and TCGA; however, a need to obtain selective and specific information correlating anthropogenic factors and disease progression-in the case of GBM-can serve as a critical tool to filter down and target specific PMs and lncRNAs responsible for regulating key cancer hallmarks in glioblastoma. The current review article proposes an in silico approach in the form of a database that reviews current updates on correlation of PMs with lncRNA dysregulation leading to GBM progression. |
| Author | Mukherjee, Swagatama Desai, Dhwani Kundu, Uma Pillai, Prakash P. |
| Author_xml | – sequence: 1 givenname: Swagatama surname: Mukherjee fullname: Mukherjee, Swagatama organization: Division of Neurobiology, Department of Zoology, The Maharaja Sayajirao University of Baroda – sequence: 2 givenname: Uma surname: Kundu fullname: Kundu, Uma organization: Division of Neurobiology, Department of Zoology, The Maharaja Sayajirao University of Baroda – sequence: 3 givenname: Dhwani surname: Desai fullname: Desai, Dhwani organization: Integrated Microbiome Resource, Department of Pharmacology and Marine Microbial Genomics and Biogeochemistry lab, Department of Biology, Dalhousie University – sequence: 4 givenname: Prakash P. orcidid: 0000-0003-3755-6427 surname: Pillai fullname: Pillai, Prakash P. email: prakash.pillai-zoo@msubaroda.ac.in organization: Division of Neurobiology, Department of Zoology, Faculty of Science, The Maharaja Sayajirao University of Baroda |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36370303$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1039_D3LC00204G crossref_primary_10_1016_j_cca_2023_117618 crossref_primary_10_3390_ijms24055045 |
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| Keywords | In silico studies Long noncoding RNA Glioblastoma multiforme Particulate matter |
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| SubjectTerms | Air pollution Anthropogenic factors Biomedical and Life Sciences Biomedicine Brain cancer Cancer Carcinogens Cell Biology Correlation Glioblastoma Global air pollution Health hazards Human influences Invasiveness Neurochemistry Neurology Neurosciences Non-coding RNA Pollutants Proteomics |
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