preprints_ui: wexa8_v1
Data license: ODbL (database) & original licenses (content) · Data source: Open Science Framework
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| wexa8_v1 | gap junction protein, alpha 3, 46kDa (connexin 46) (GJA3) : Machine learning discoveries of 2nd order synergy in Meningiomas | Background : GJA3 belongs to the group of connexins, or gap junction proteins, that are a family of structurally related transmembrane proteins that assemble to form vertebrate gap junctions, which are different from the innexins, form gap junctions in invertebrates. They are essential for many physiological processes, such as proper embryonic development, the coordinated depolarization of cardiac muscle, and the conducted response in microvasculature. For these reasons, mutations in connexin- encoding genes can lead to functional and developmental abnormalities. Meningiomas are the most common intracranial primary neoplasm in adults. Patel et al. [1] analyzed 160 tumors from all 3 World Health Organization (WHO) grades (I through III) us- ing clinical, gene expression, and sequencing data and using unsupervised clustering analysis identified 3 molecular types (A, B, and C) that reliably predicted recurrence. Further, these groups did not directly correlate with the WHO grading system, which classifies more than half of the tumors in the most aggressive molecular type as benign. Issue : Increasing evidence point to the fact that meningioma classification and grading, that is based on histopathology does not always accurately predict tumor aggressiveness and recurrence behaviour and knowledge of the underlying biology of the treatment resistant meningiomas and the impact of genetic alterations in these tumors, is lacking. At the current stage more genomic studies are required to unravel the role of other genes and their interations with other genetic factors. Resolution : In a recently published work Sinha [2], a frame work of a search engine was developed which can rank combinations of factors (genes/proteins) in a signaling pathway. Adapting this search engine to the Meningioma dataset, i present here 2nd order combinations of GJA3, some of which have been known to exist via wet lab experiments, but many are yet to be tested. The reveals combinations might help oncologists/biologists test possible hypotheses that might be the causing factors in meningioma. Further, in my limited grasp, if proven true, the combinations revealed by the search engine might pave way for development of gene based therapies aimed at resolving pathological issues related to meningiomas. | 2025-05-09T15:06:32.200571 | 2025-05-09T16:55:01.341674 | 2025-05-09T16:54:42.113662 | osf | 1 | accepted | 1 | 1 | https://doi.org/10.31219/osf.io/wexa8_v1 | CC-By Attribution 4.0 International | [] | shriprakash sinha | [{"id": "4muv5", "name": "shriprakash sinha", "index": 0, "orcid": "0000-0001-7027-5788", "bibliographic": true}] | shriprakash sinha | Nervous System Diseases; Diseases; Medicine and Health Sciences; Life Sciences; Systems Biology; Computational Biology; Genetics and Genomics | [{"id": "584240d954be81056ceca921", "text": "Nervous System Diseases"}, {"id": "584240d954be81056cecaa5d", "text": "Diseases"}, {"id": "584240da54be81056cecaaaa", "text": "Medicine and Health Sciences"}, {"id": "584240da54be81056cecaab0", "text": "Life Sciences"}, {"id": "584240da54be81056cecac2f", "text": "Systems Biology"}, {"id": "584240da54be81056cecac8d", "text": "Computational Biology"}, {"id": "584240db54be81056cecacea", "text": "Genetics and Genomics"}] | https://osf.io/download/681e1a2749885e100185e9f5 | 0 | available | not_applicable | [] | 2025-05-10T00:11:34.203456 |