These days, cancer is thought to be more than just one illness, with several complex subtypes that require different screening approaches. These subtypes can be distinguished by the distinct markings left by metabolites, proteins, miRNA, and DNA. Personalized illness management may be possible if cancer is categorized according to its biomarkers. In order to stop cancer from spreading and posing a significant risk to patient survival, early detection and prompt treatment are essential. Traditional cancer screening techniques are tedious, time-consuming, and require expert personnel for analysis. This has led scientists to reevaluate screening methodologies and make use of emerging technologies to achieve better results. Using time and money saving techniques, these methodologies integrate the procedures from sample preparation to detection in small devices with high accuracy and sensitivity. With its proven potential for biomedical use, surface-enhanced Raman scattering (SERS) has been widely used in biosensing applications, particularly in biomarker identification. Consideration was given especially to the potential of SERS as a portable clinical diagnostic tool. The approaches to SERS-based sensing technologies for both invasive and non-invasive samples are reviewed in this article, along with sample preparation techniques and obstacles. Aside from these significant constraints in the detection approach and techniques, the review also takes into account the complexity of biological fluids, the availability of biomarkers, and their sensitivity and selectivity, which are generally lowered. Massive ways to maintain sensing capabilities in clinical samples are being developed recently to get over this restriction. SERS is known to be a reliable diagnostic method for treatment judgments. Nonetheless, there is still room for advancement in terms of portability, creation of diagnostic apps, and interdisciplinary AI-based applications. Therefore, we will outline the current state of technological maturity for SERS-based cancer biomarker detection in this article. The review will meet the demand for reviewing various sample types (invasive and non-invasive) of cancer biomarkers and their detection using SERS. It will also shed light on the growing body of research on portable methods for clinical application and quick cancer detection.

LAMP has received great interest and is widely utilized in life sciences for nucleic acid analysis. To monitor a real-time LAMP assay, a fluorescence DNA dye is an indispensable component and therefore the selection of a suitable dye for real-time LAMP is a need. To aid this selection, we investigated the inhibition effects of twenty-three DNA dyes on real-time LAMP. Threshold time (T_t) values of each real-time LAMP were determined and used as an indicator of the inhibition effect. Based on the inhibition effects, the dyes were classified into four groups: (1) non-inhibition effect, (2) medium inhibition effect, (3) high inhibition effect, and (4) very high inhibition effect. The signal to noise ratio (SNR) and the limit of detection (LOD) of the dyes in groups 1, 2, and 3 were further investigated, and possible inhibition mechanisms of the DNA dyes on the real-time LAMP are suggested and discussed. Furthermore, a comparison of SYTO 9 in different LAMP reactions and different systems is presented. Of the 23 dyes tested, SYTO 9, SYTO 82, SYTO 16, SYTO 13, and Miami Yellow were the best dyes with no inhibitory effect, low LOD and high SNR in the real-time LAMP reactions. The present classification of the dyes will simplify the selection of fluorescence dye for real-time LAMP assays in point of care setting.