Obdulia Covarrubias-Zambrano, Deepesh Agarwal, Madumali Kalubowilage, Sumia Ehsan, Asanka S Yapa, Jose Covarrubias, Anup Kasi, Balasubramaniam Natarajan, Stefan H Bossmann
{"title":"基于蛋白酶活性的纳米生物传感器早期检测胰腺癌。","authors":"Obdulia Covarrubias-Zambrano, Deepesh Agarwal, Madumali Kalubowilage, Sumia Ehsan, Asanka S Yapa, Jose Covarrubias, Anup Kasi, Balasubramaniam Natarajan, Stefan H Bossmann","doi":"10.18103/mra.v12i7.5632","DOIUrl":null,"url":null,"abstract":"<p><p>Five-year survival rate for pancreatic cancer patients has increased to 12.8% afterthe initial diagnosis, still making it one of the deadliest cancertypes. This disease is known as the \"silent killer\" because early detection is challenging due to the location of the pancreas in the body and the nonspecific clinical symptoms. The Bossmann group has developed ultrasensitive nanobiosensors for protease/arginase detection comprised of Fe/Fe<sub>3</sub>O<sub>4</sub> nanoparticles, cyanine 5.5, and designer peptide sequences linked to TCPP. Initial data obtained from both gene expression analysis and protease/arginase activity detection in serum indicated the feasibility of early pancreatic cancer detection. Several matrix metalloproteinases (MMPs, -1, -3, and -9), cathepsins (CTS) B and E, neutrophil elastase, and urokinase plaminogen activator (uPA) have been identified as candidates for proximal biomarkers. In this study, we have confirmed our initial results from 2018 performing serum sample analysis assays using a larger group sample size (n = 159), which included localized (n=33) and metastatic pancreatic cancer (n=50), pancreatitis (n=26), and an age-matched healthy control group (n=50). The data obtained from the eight nanobiosensors capable of ultrasensitive protease and arginase activity measurements were analyzed by means of an optimized information fusion-based hierarchical decision structure. This permits the modeling of early-stage detection of pancreatic cancer as a multi-class classification problem. The most striking result is that this methodology permits the detection of localized pancreatic cancers from serum analyses with around 96% accuracy.</p>","PeriodicalId":94137,"journal":{"name":"Medical research archives","volume":"12 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12031639/pdf/","citationCount":"0","resultStr":"{\"title\":\"Protease activity-based nanobiosensors for early detection of pancreatic cancer.\",\"authors\":\"Obdulia Covarrubias-Zambrano, Deepesh Agarwal, Madumali Kalubowilage, Sumia Ehsan, Asanka S Yapa, Jose Covarrubias, Anup Kasi, Balasubramaniam Natarajan, Stefan H Bossmann\",\"doi\":\"10.18103/mra.v12i7.5632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Five-year survival rate for pancreatic cancer patients has increased to 12.8% afterthe initial diagnosis, still making it one of the deadliest cancertypes. This disease is known as the \\\"silent killer\\\" because early detection is challenging due to the location of the pancreas in the body and the nonspecific clinical symptoms. The Bossmann group has developed ultrasensitive nanobiosensors for protease/arginase detection comprised of Fe/Fe<sub>3</sub>O<sub>4</sub> nanoparticles, cyanine 5.5, and designer peptide sequences linked to TCPP. Initial data obtained from both gene expression analysis and protease/arginase activity detection in serum indicated the feasibility of early pancreatic cancer detection. Several matrix metalloproteinases (MMPs, -1, -3, and -9), cathepsins (CTS) B and E, neutrophil elastase, and urokinase plaminogen activator (uPA) have been identified as candidates for proximal biomarkers. In this study, we have confirmed our initial results from 2018 performing serum sample analysis assays using a larger group sample size (n = 159), which included localized (n=33) and metastatic pancreatic cancer (n=50), pancreatitis (n=26), and an age-matched healthy control group (n=50). The data obtained from the eight nanobiosensors capable of ultrasensitive protease and arginase activity measurements were analyzed by means of an optimized information fusion-based hierarchical decision structure. This permits the modeling of early-stage detection of pancreatic cancer as a multi-class classification problem. The most striking result is that this methodology permits the detection of localized pancreatic cancers from serum analyses with around 96% accuracy.</p>\",\"PeriodicalId\":94137,\"journal\":{\"name\":\"Medical research archives\",\"volume\":\"12 7\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12031639/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical research archives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18103/mra.v12i7.5632\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical research archives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18103/mra.v12i7.5632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Protease activity-based nanobiosensors for early detection of pancreatic cancer.
Five-year survival rate for pancreatic cancer patients has increased to 12.8% afterthe initial diagnosis, still making it one of the deadliest cancertypes. This disease is known as the "silent killer" because early detection is challenging due to the location of the pancreas in the body and the nonspecific clinical symptoms. The Bossmann group has developed ultrasensitive nanobiosensors for protease/arginase detection comprised of Fe/Fe3O4 nanoparticles, cyanine 5.5, and designer peptide sequences linked to TCPP. Initial data obtained from both gene expression analysis and protease/arginase activity detection in serum indicated the feasibility of early pancreatic cancer detection. Several matrix metalloproteinases (MMPs, -1, -3, and -9), cathepsins (CTS) B and E, neutrophil elastase, and urokinase plaminogen activator (uPA) have been identified as candidates for proximal biomarkers. In this study, we have confirmed our initial results from 2018 performing serum sample analysis assays using a larger group sample size (n = 159), which included localized (n=33) and metastatic pancreatic cancer (n=50), pancreatitis (n=26), and an age-matched healthy control group (n=50). The data obtained from the eight nanobiosensors capable of ultrasensitive protease and arginase activity measurements were analyzed by means of an optimized information fusion-based hierarchical decision structure. This permits the modeling of early-stage detection of pancreatic cancer as a multi-class classification problem. The most striking result is that this methodology permits the detection of localized pancreatic cancers from serum analyses with around 96% accuracy.