Potential biomarkers for the diagnosis of respiratory tract infection and lungs cancer

Abstract

Major hurdle faced by many physicians in treating various respiratory tract infections and lung carcinomas is their late or mis-diagnosis. In most respiratory tract infections the manner of infection is not completely understood. Similarly, various lung carcinomas are diagnosed at advance stages at which not only the treatment possibilities are narrowed but the chances of survival are also reduced. So, for the sake of better treatment, the quick and improved diagnostic strategies are suggested. Protein biomarkers fully fit the description in this regard as they have shown great potential in specific diagnosis of many respiratory diseases and also have shown capability in timely pin pointing different stages of lung carcinomas. Many serum biomarkers are presently being used for diagnosis but the efficiency for diagnosis of these biomarkers is lower when used alone. So, physicians are suggested to use the combination of different biomarkers. Moreover, genetic biomarkers are also currently studied to indicate the exact stage of disease, the possible damage occurred, the severity of disease and also for the analysis of the possible body response to the therapeutics.

Biomarkers for respiratory diseases: Present applications and future discoveries

“…The application of a specific biomarker in the diagnosis or prediction of drug response in the absence of other bioinformation, such as clinical characteristics, imaging and physiology, can lead to ‘false’ conclusions due to bias or low clinical utility. Recently, interest has been focused on establishing multiple biomarker models, which can be more efficient in diagnosis and prediction 16,105,106 . A multiple biomarker model instead of a single biomarker model has an intrinsic statistical advantage, in which each variable can be assigned a statistical weight.…”

“…Recently, interest has been focused on establishing multiple biomarker models, which can be more efficient in diagnosis and prediction. 16,105,106 A multiple biomarker model instead of a single biomarker model has an intrinsic statistical advantage, in which each variable can be assigned a statistical weight. Therefore, the composite index can be calculated by summing the value of multiple biomarkers with different weights.…”

DNA-only bioassay for simultaneous detection of proteins and nucleic acids

“…Also, it has been demonstrated that the detection of colorectal cancer by the widely used carcinoembryonic antigen reaches 30-40% of sensitivity, which remarkably increases to 88% when combined with the detection of free circulating DNA [6]. Moreover, the combination of biomarkers can also provide information about the stage of cancer as well as about the response to a therapy [7]. According to a recent review, one of the next goals in the detection of cancer biomarkers is to develop NA-based techniques for personalized and point-ofcare (POC) diagnostics that can detect both NA and non-NA targets [8].…”

Artificial Intelligence for Long-term Respiratory Disease Management

“…This technology has been mechanical in nature but in recent years has been realised as electronic measurement devices with wireless connectivity, typically Bluetooth. Other diagnosis techniques which complement spirometry include the use of biomarkers for COPD or lung cancer [11,12]. Such biomarkers may be realised as implantable monitors or home test kits; employing AI would make a powerful point-of-care system.…”