CA 19-9 and ALP as potential biomarkers for pancreatic cancer risk: Analysis from a large lab test database.

Smyth, Carol; Bhan, Jason; Dhaliwal, Ajitpal Singh; Sorokina, Tatiana; Alarcon, Mauricio; Levitz, Jason S.

doi:10.1200/jco.2015.33.15_suppl.e15211

Cited by 2 publications

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“…Normally, the serum ALP concentration of normal adults is 40–190 U/L, while those of children and pregnant women can reach 500 U/L [ 2 ]. A variety of diseases have been found to be associated with abnormal ALP activity, such as bone cancer, prostate cancer, liver disease, breast cancer, nasopharyngeal carcinoma, colorectal cancer and pancreatic cancer [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. Therefore, the detection of ALP activities is of great significance in clinical diagnosis and disease treatment.…”

Section: Introductionmentioning

confidence: 99%

Construction of Aggregation-Induced Emission Molecule–MnO2 Composite Nanoprobe and Its Application in Alkaline Phosphatase Detection

Cui

Zhao

2023

Nanomaterials

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Alkaline phosphatase (ALP) is among the most studied enzymes by far, playing an important role in the metabolism of organisms and the regulation of protein activity. Herein, a label-free composite nanoprobe is constructed by combining inorganic nanomaterials and aggregation-induced emission (AIE) molecule to achieve highly sensitive and selective detection of ALP. Negatively charged 9,10-bis [2-(6-sulfonatopropoxyl) naphthylethenyl] anthracene (BSNVA) molecule is synthesized, which has the AIE performance and can be assembled on the surface of amino–SiO2 nanoparticles through electrostatic interaction for fluorescence enhancement. MnO2 nanosheets are rich in negative charges, enabling them to be wrapped on the surface of the amino–SiO2 nanosphere to shield the positive charge on its surface, making it impossible for BSNVA to accumulate on the surface and then weakening the bio-fluorescence of the system. Furthermore, with catalyzed substrates induced by ALP, generating ascorbic acid and the redox reaction between ascorbic acid and MnO2, the nanoprobe helps in realizing the high-sensitivity detection of ALP with a detection limit of 0.38 mU/mL. The proposed strategy requires no complex cleaning and modification processes and can overcome the quenching effect caused by the aggregation of traditional organic dyes, proving to be a simple, low-cost and “turn-on” fluorescent detection method for ALP.

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Section: Introductionmentioning

confidence: 99%

Construction of Aggregation-Induced Emission Molecule–MnO2 Composite Nanoprobe and Its Application in Alkaline Phosphatase Detection

Cui

Zhao

2023

Nanomaterials

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“…Lab tests mainly pay attention to specific substances in the body and generally involve the detection of body fluids, including blood, urine, cerebrospinal fluid (CSF), and so on [ 9 – 11 ]. However, lab tests reflect the overall conditions of the body with the use of only a few markers for tumor screening, such as carcino-embryonic antigen, CEA and alpha fetoprotein, AFP [ 10 ]. Doctors cannot diagnose cancer only based on lab tests.…”

Section: Introductionmentioning

confidence: 99%

Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets

et al. 2017

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Detection and diagnosis of cancer are especially important for early prevention and effective treatments. Traditional methods of cancer detection are usually time-consuming and expensive. Liquid biopsy, a newly proposed noninvasive detection approach, can promote the accuracy and decrease the cost of detection according to a personalized expression profile. However, few studies have been performed to analyze this type of data, which can promote more effective methods for detection of different cancer subtypes. In this study, we applied some reliable machine learning algorithms to analyze data retrieved from patients who had one of six cancer subtypes (breast cancer, colorectal cancer, glioblastoma, hepatobiliary cancer, lung cancer and pancreatic cancer) as well as healthy persons. Quantitative gene expression profiles were used to encode each sample. Then, they were analyzed by the maximum relevance minimum redundancy method. Two feature lists were obtained in which genes were ranked rigorously. The incremental feature selection method was applied to the mRMR feature list to extract the optimal feature subset, which can be used in the support vector machine algorithm to determine the best performance for the detection of cancer subtypes and healthy controls. The ten-fold cross-validation for the constructed optimal classification model yielded an overall accuracy of 0.751. On the other hand, we extracted the top eighteen features (genes), including TTN, RHOH, RPS20, TRBC2, in another feature list, the MaxRel feature list, and performed a detailed analysis of them. The results indicated that these genes could be important biomarkers for discriminating different cancer subtypes and healthy controls.

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CA 19-9 and ALP as potential biomarkers for pancreatic cancer risk: Analysis from a large lab test database.

Cited by 2 publications

References 0 publications

Construction of Aggregation-Induced Emission Molecule–MnO2 Composite Nanoprobe and Its Application in Alkaline Phosphatase Detection

Construction of Aggregation-Induced Emission Molecule–MnO2 Composite Nanoprobe and Its Application in Alkaline Phosphatase Detection

Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets

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