Computational systems biology approach for permanent tumor elimination and normal tissue protection using negative biasing: Experimental validation in malignant melanoma as case study

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dc.contributor.author Kumari, Bindu
dc.contributor.author Sakode, Chandrashekhar
dc.contributor.author Lakshminarayanan, Raghavendran
dc.contributor.author Roy, Prasun K.
dc.date.accessioned 2024-01-31T09:41:42Z
dc.date.available 2024-01-31T09:41:42Z
dc.date.issued 2023-03-21
dc.identifier.issn 15471063
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/2725
dc.description This paper published with affiliation IIT (BHU), Varanasi in Open Access Mode. en_US
dc.description.abstract Complete spontaneous tumor regression (without treatment) is well documented to occur in animals and humans as epidemiological analysis show, whereby the malignancy is permanently eliminated. We have developed a novel computational systems biology model for this unique phenomenon to furnish insight into the possibility of therapeutically replicating such regression processes on tumors clinically, without toxic side effects. We have formulated oncological informatics approach using cell-kinetics coupled differential equations while protecting normal tissue. We investigated three main tumor-lysis components: (i) DNA blockade factors, (ii) Interleukin-2 (IL-2), and (iii) Cytotoxic T-cells (CD8+ T). We studied the temporal variations of these factors, utilizing preclinical experimental investigations on malignant tumors, using mammalian melanoma microarray and histiocytoma immunochemical assessment. We found that permanent tumor regression can occur by: 1) Negative-Bias shift in population trajectory of tumor cells, eradicating them under first-order asymptotic kinetics, and 2) Temporal alteration in the three antitumor components (DNA replicationblockade, Antitumor T-lymphocyte, IL-2), which are respectively characterized by the following patterns: (a) Unimodal Inverted-U function, (b) Bimodal M-function, (c) Stationary-step function. These provide a time-wise orchestrated tri-phasic cytotoxic profile. We have also elucidated geneexpression levels corresponding to the above three components: (i) DNA-damage G2/M checkpoint regulation [genes: CDC2-CHEK], (ii) Chemokine signaling: IL-2/15 [genes: IL2RG-IKT3], (iii) Tlymphocyte signaling (genes: TRGV5-CD28). All three components quantitatively followed the same activation profiles predicted by our computational model (Smirnov-Kolmogorov statistical test satisfied, α = 5%). We have shown that the genes CASP7-GZMB are signatures of Negative-bias dynamics, enabling eradication of the residual tumor. Using the negative-biasing principle, we have furnished the dose-time profile of equivalent therapeutic agents (DNA-alkylator, IL-2, T-cell input) so that melanoma tumor may therapeutically undergo permanent extinction by replicating the spontaneous tumor regression dynamics. en_US
dc.language.iso en en_US
dc.publisher American Institute of Mathematical Sciences en_US
dc.relation.ispartofseries Mathematical Biosciences and Engineering;20
dc.subject bioinformatics en_US
dc.subject chemotherapy en_US
dc.subject histiocytoma microarray en_US
dc.subject immunotherapy en_US
dc.subject melanoma en_US
dc.subject Negative bias en_US
dc.subject spontaneous cancer regression en_US
dc.subject systems biology en_US
dc.title Computational systems biology approach for permanent tumor elimination and normal tissue protection using negative biasing: Experimental validation in malignant melanoma as case study en_US
dc.type Article en_US


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