An intuitionistic approach for the predictability of anti-angiogenic inhibitors in cancer diagnosis

by Selleckchem | Jun 21 2023

Malignant cancer angiogenesis has historically attracted enormous scientific attention. Although angiogenesis is requisite for a child's development and conducive to tissue homeostasis, it is deleterious when cancer lurks. Today, anti-angiogenic biomolecular receptor tyrosine kinase inhibitors (RTKIs) to target angiogenesis have been prolific in treating various carcinomas. Angiogenesis is a pivotal component in malignant transformation, oncogenesis, and metastasis that can be activated by a multiplicity of factors (e.g., VEGF (Vascular endothelial growth factor), (FGF) Fibroblast growth factor, (PDGF) Platelet-derived growth factor and others). The advent of RTKIs, which primarily target members of the VEGFR (VEGF Receptor) family of angiogenic receptors has greatly ameliorated the outlook for some cancer forms, including hepatocellular carcinoma, malignant tumors, and gastrointestinal carcinoma. Cancer therapeutics have evolved steadily with active metabolites and strong multi-targeted RTK inhibitors such as E7080, CHIR-258, SU 5402, etc. This research intends to determine the efficacious anti-angiogenesis inhibitors and rank them by using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE- II) decision-making algorithm. The PROMETHEE-II approach assesses the influence of growth factors (GFs) in relation to the anti-angiogenesis inhibitors. Due to their capacity to cope with the frequently present vagueness while ranking alternatives, fuzzy models constitute the most suitable tools for producing results for analyzing qualitative information. This research's quantitative methodology focuses on ranking the inhibitors according to their significance concerning criteria. The evaluation findings indicate the most efficacious and idle alternative for inhibiting angiogenesis in cancer.

Comments:

The research aims to determine the most effective anti-angiogenesis inhibitors for cancer treatment and rank them using the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE-II) decision-making algorithm. The study focuses on evaluating the influence of growth factors (GFs) in relation to the anti-angiogenesis inhibitors.

Angiogenesis, the formation of new blood vessels, plays a crucial role in the development of cancer and its progression, including metastasis. Targeting angiogenesis has been a significant area of research in the field of cancer therapeutics. Biomolecular receptor tyrosine kinase inhibitors (RTKIs), such as those targeting members of the VEGFR (VEGF Receptor) family, have shown promise in treating various types of carcinomas, including hepatocellular carcinoma, malignant tumors, and gastrointestinal carcinoma.

The advent of RTKIs, along with strong multi-targeted inhibitors like E7080, CHIR-258, and SU 5402, has improved the outlook for cancer treatment. However, determining the most effective anti-angiogenesis inhibitors and ranking them is essential for optimizing treatment strategies.

The PROMETHEE-II decision-making algorithm is employed in this research to evaluate the inhibitors' significance based on predetermined criteria. It allows for the consideration of various factors and their relative importance. Fuzzy models, which are capable of handling vague or qualitative information, are utilized to analyze the data and generate results.

The quantitative methodology of this research involves ranking the inhibitors according to their significance concerning the defined criteria. By applying the PROMETHEE-II algorithm and fuzzy models, the evaluation aims to identify the most efficacious and suitable alternative for inhibiting angiogenesis in cancer.

The evaluation findings obtained from this study will provide valuable insights into the efficacy of different anti-angiogenesis inhibitors and their potential for cancer treatment. This information can assist researchers and clinicians in making informed decisions regarding treatment options and developing personalized therapeutic approaches for cancer patients.