The Evolution of Affordable Technologies in Liquid Biopsy Diagnostics: The Key to Clinical Implementation.

Cancer remains a leading cause of death worldwide, despite many advances in diagnosis and treatment. Precision medicine has been a key area of focus, with research providing insights and progress in helping to lower cancer mortality through better patient stratification for therapies and more precise diagnostic techniques. However, unequal access to cancer care is still a global concern, with many patients having limited access to diagnostic tests and treatment regimens. Noninvasive liquid biopsy (LB) technology can determine tumour-specific molecular alterations in peripheral samples. This allows clinicians to infer knowledge at a DNA or cellular level, which can be used to screen individuals with high cancer risk, personalize treatments, monitor treatment response, and detect metastasis early. As scientific understanding of cancer pathology increases, LB technologies that utilize circulating tumour DNA (ctDNA) and circulating tumour cells (CTCs) have evolved over the course of research. These technologies incorporate tumour-specific markers into molecular testing platforms. For clinical translation and maximum patient benefit at a wider scale, the accuracy, accessibility, and affordability of LB tests need to be prioritized and compared with gold standard methodologies in current use. In this review, we highlight the range of technologies in LB diagnostics and discuss the future prospects of LB through the anticipated evolution of current technologies and the integration of emerging and novel ones. This could potentially allow a more cost-effective model of cancer care to be widely adopted.

Attitudes, beliefs, and knowledge regarding medical cannabis among healthcare students in the Republic of Cyprus: a cross-sectional descriptive correlational study.

Background: Although international research-based literature from the last 2 decades seems to favor the use of medical cannabis (MC), there is a lack of evidence concerning healthcare students' education on MC in the Republic of Cyprus and across the world. Therefore, this study explores healthcare students' attitudes, beliefs, and knowledge regarding the use of MC. We paid special attention to differences across specific sociodemographic (gender, age, and religion status) and educational (level of study and study field) characteristics. Methods: A descriptive cross-sectional study was conducted between November 2019 and March 2020. All active undergraduate and postgraduate healthcare students (nurses, physiotherapists, speech therapists, pharmacists, and occupational therapists; N = 900) studying in public and private universities in the Republic of Cyprus were eligible to participate (final sample: N = 819, response rate = 91%). To collect data on the attitudes, beliefs and knowledge of the participants, we used the Medical Cannabis Questionnaire (MCQ). To analyze the data, we employed the Pearson's chi-square test for group differences, in addition to assessing the descriptive and inferential statistics. Results: Approximately 82.2% believed that MC education should be integrated into the clinical practice requirements. Statistically significant differences were observed between genders in terms of beliefs/risk associated with the use of MC, with males being more likely to believe that there are significant mental-health benefits associated with using ΜC compared to females (84.9% vs. 76.2%, p<0.05). Females were more likely than males to believe that using MC poses serious physical (76.8% vs. 60.6%, p<0.001) and mental-health (77.9% vs. 66%, p<0.001) risks. Moreover, participants who received formal education about MC during their study/training were more prepared to answer patient/client questions about ΜC (p < 0.001). In addition, participants who received formal education had more frequently friends (p < 0.001) or family members who used MC (p < 0.005). Conclusion: This study provides useful information for curriculum development, educational changes, and policy decisions related to cannabis use for medical purposes in the Republic of Cyprus. The results showed that the majority of the healthcare students who participated in the study favored MC use. However, the participants reported a lack of knowledge and recommended additional evidence-based research and education to enhance their knowledge about MC use. Therefore, we recommend the implementation of formal education on MC among healthcare students in the Republic of Cyprus during their study and clinical training. Furthermore, it is important to include MC-related theoretical and clinical/laboratory courses during studies and clinical practice.

Classification of nucleic acid amplification on ISFET arrays using spectrogram-based neural networks.

The COVID-19 pandemic has highlighted a significant research gap in the field of molecular diagnostics. This has brought forth the need for AI-based edge solutions that can provide quick diagnostic results whilst maintaining data privacy, security and high standards of sensitivity and specificity. This paper presents a novel proof-of-concept method to detect nucleic acid amplification using ISFET sensors and deep learning. This enables the detection of DNA and RNA on a low-cost and portable lab-on-chip platform for identifying infectious diseases and cancer biomarkers. We show that by using spectrograms to transform the signal to the time-frequency domain, image processing techniques can be applied to achieve the reliable classification of the detected chemical signals. Transformation to spectrograms is beneficial as it makes the data compatible with 2D convolutional neural networks and helps gain significant performance improvement over neural networks trained on the time domain data. The trained network achieves an accuracy of 84% with a size of 30kB making it suitable for deployment on edge devices. This facilitates a new wave of intelligent lab-on-chip platforms that combine microfluidics, CMOS-based chemical sensing arrays and AI-based edge solutions for more intelligent and rapid molecular diagnostics.

Automating the Design of Cancer Specific DNA Probes Using Computational Algorithms.

This paper introduces a novel Python script which automates the design process of cancer variant-specific DNA probes, based on the amplification method LAMP (Loop-Mediated Isothermal Amplification). With just an input of the DNA sequence and the mutation base location, the script outputs suggestions of two best fitting primer sets for a given target, together with an estimated working efficiency. The script also implements a feature of 'script training', using experimentally-validated primers as a benchmark for primer design optimisation. The proposed script has been tested using the gene sequences of ESR1 p.E380Q and ESR1 p.Y537S cancer specific mutations, with the results to closely resemble the experimentally validated primer sets. Creating a rapid LAMP primer design utility allows LAMP to be more easily used as a molecular method for assay development in Lab-on-Chip (LoC) systems to track mutational profiles of variant-specific assays.

Detection of Multiple Breast Cancer ESR1 Mutations on an ISFET Based Lab-on-Chip Platform.

ESR1 mutations are important biomarkers in metastatic breast cancer. Specifically, p.E380Q and p.Y537S mutations arise in response to hormonal therapies given to patients with hormone receptor positive (HR+) breast cancer (BC). This paper demonstrates the efficacy of an ISFET based CMOS integrated Lab-on-Chip (LoC) system, coupled with variant-specific isothermal amplification chemistries, for detection and discrimination of wild type (WT) from mutant (MT) copies of the ESR1 gene. Hormonal resistant cancers often lead to increased chances of metastatic disease which leads to high mortality rates, especially in low-income regions and areas with low healthcare coverage. Design and optimization of bespoke primers was carried out and tested on a qPCR instrument and then benchmarked versus the LoC platform. Assays for detection of p.Y537S and p.E380Q were developed and tested on the LoC platform, achieving amplification in under 25 minutes and sensitivity of down to 1000 copies of DNA per reaction for both target assays. The LoC system hereby presented, is cheaper and smaller than other standard industry equivalent technologies such as qPCR and sequencing. The LoC platform proposed, has the potential to be used at a breast cancer point-of-care testing setting, offering mutational tracking of circulating tumour DNA in liquid biopsies to assist patient stratification and metastatic monitoring.

Pilot exploration of post-traumatic stress symptoms in intensive care unit survivors in Cyprus.

BACKGROUND: Approximately, 20% of intensive care unit (ICU) survivors develop post-traumatic stress disorder (PTSD) symptoms. Although Davidson Trauma Scale (DTS) provides a comprehensive approach to PSTD symptoms, there is no evidence on DTS-I-M use in ICU survivors. AIMS AND OBJECTIVES: To validate the modified intensity Davidson Trauma Scale (DTS-I-M) (wherein the frequency and severity subscales are combined to express symptoms intensity) in a convenience sample of ICU survivors in Cyprus, and to explore the prevalence of PTSD symptoms and related predictors. DESIGN: An instrument validation design, along with a cross-sectional, correlational study design was employed. METHODS: Translation and cultural adaptation of the instrument were achieved through a group of experts and pilot testing. The DTS-I-M was administered via telephone. Participants' clinical data (length of ICU stay [LOS], mechanical ventilation duration [MVD], admission diagnosis, medication history) and demographics (age, gender) were collected. Non-parametric comparisons, and regression analyses to identify predictors of DTS-I-M scores and PTSD symptoms were employed. RESULTS: The Cypriot DTS-I-M version demonstrated high test-retest (Pearson's r = 0.928, P < .001) and internal consistency (Cronbach's [α] alpha = .97) reliability in a sample of 69 ICU survivors (62.7% response). About 36.2% of participants reported PTSD symptoms. Factor analysis confirmed the construct validity of the DTS-I-M, and a 3-factor structure (encompassing intrusive, avoidance, hyperarousal, mood, and cognitive symptoms). In a multiple regression, MVD (B = -3.11, OR [95% CI] = 22.58 [3.07-166.09, P = .002]) and LOS (r2 = 0.302, P = .002) were statistically significant predictors of DTS-I-M score. CONCLUSION: We confirm the applicability of the DTS-I-M for the assessment of PTSD symptoms in ICU survivors; and offer preliminary evidence on the prevalence and predictors of post-ICU PTSD symptoms in Cyprus. RELEVANCE TO CLINICAL PRACTICE: DTS-I-M is an appropriate screening tool for PTSD symptoms after ICU hospitalization. Patients with longer MVD and LOS are at higher risk for post-ICU PTSD symptoms and seem to experience more intense relevant symptoms.

A novel hotspot specific isothermal amplification method for detection of the common PIK3CA p.H1047R breast cancer mutation.

Breast cancer (BC) is a common cancer in women worldwide. Despite advances in treatment, up to 30% of women eventually relapse and die of metastatic breast cancer. Liquid biopsy analysis of circulating cell-free DNA fragments in the patients' blood can monitor clonality and evolving mutations as a surrogate for tumour biopsy. Next generation sequencing platforms and digital droplet PCR can be used to profile circulating tumour DNA from liquid biopsies; however, they are expensive and time consuming for clinical use. Here, we report a novel strategy with proof-of-concept data that supports the usage of loop-mediated isothermal amplification (LAMP) to detect PIK3CA c.3140 A > G (H1047R), a prevalent BC missense mutation that is attributed to BC tumour growth. Allele-specific primers were designed and optimized to detect the p.H1047R variant following the USS-sbLAMP method. The assay was developed with synthetic DNA templates and validated with DNA from two breast cancer cell-lines and two patient tumour tissue samples through a qPCR instrument and finally piloted on an ISFET enabled microchip. This work sets a foundation for BC mutational profiling on a Lab-on-Chip device, to help the early detection of patient relapse and to monitor efficacy of systemic therapies for personalised cancer patient management.