DNA microarray analysis using a smartphone to detect the BRCA-1 gene

A smartphone-colorimetric dual-mode diagnosis method for breast cancer detection of BRCA-1 gene base on silver plated substrate and catalytic hairpin assembly amplification

Breast cancer is the most prevalent malignancy among women worldwide. With rapid societal development, there has been a consistent increase in breast cancer incidence rates annually, accompanied by a progressively younger age of onset. Consequently, there is an urgent need to develop a rapid, sensitive, and highly specific approach for the identification of BRCA-1. In this study, we successfully devised a heterogeneous system based on G-quadruplex DNAzyme for label-free and enzyme-free visual detection of BRCA-1. Moreover, the distinctive G-quadruplex (G4) DNAzyme ensures precise and accurate detection through enzyme-free amplification, colorimetric detection, and catalytic hairpin assembly mechanisms. The utilization of this heterogeneous system effectively minimizes background interference while exhibiting exceptional sensitivity and accuracy with an impressive detection limit as low as 0.6 pM. Furthermore, real sample analysis yielded an area under the ROC curve value of 0.9825 which demonstrates its robust performance for early screening purposes when integrated with smartphone-assisted analysis, thus showcasing its potential for widespread application in early breast cancer diagnosis.

Ganoderma lucidum (Curtis) P. Karst. Immunomodulatory Protein Has the Potential to Improve the Prognosis of Breast Cancer Through the Regulation of Key Prognosis-Related Genes

Background/Objectives: Breast cancer in women is the most commonly diagnosed and most malignant tumor. Although luminal A breast cancer (LumA) has a relatively better prognosis, it still has a persistent pattern of recurrence. Ganoderma lucidum (Curtis) P. Karst. is a kind of traditional Chinese medicine and has antitumor effects. In this study, we aimed to identify the genes relevant to prognosis, find novel targets, and investigate the function of the bioactive protein from G. lucidum, called FIP-glu, in improving prognosis. Methods: Gene expression data and clinical information of LumA breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Using bioinformatics methods, a predictive risk model was constructed to predict the prognosis for each patient. The cell counting kit-8 (CCK8) and clone formation assays were used to validate gene function. The ability of FIP-glu to regulate RNA levels of risk genes was validated. Results: Six risk genes (slit-roundabout GTPase-activating protein 2 (SRGAP2), solute carrier family 35 member 2 (SLC35A2), sequence similarity 114 member A1 (FAM114A1), tumor protein P53-inducible protein 11 (TP53I11), transmembrane protein 63C (TMEM63C), and polymeric immunoglobulin receptor (PIGR)) were identified, and a prognostic model was constructed. The prognosis was worse in the high-risk group and better in the low-risk group. The receiver operating characteristic (ROC) curve confirmed the model's accuracy. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the differentially expressed genes (DEGs) between the high- and low-risk groups were significantly enriched in the immune responses. TMEM63C could promote tumor viability, growth, and proliferation in vitro. FIP-glu significantly regulated these risk genes, and attenuated the promoting effect of TMEM63C in breast cancer cells. Conclusions: SRGAP2, SLC35A2, FAM114A1, TP53I11, TMEM63C, and PIGR were identified as the potential risk genes for predicting the prognosis of patients. TMEM63C could be a potential novel therapeutic target. Moreover, FIP-glu was a promising drug for improving the prognosis of LumA breast cancer.

Identification of a Potential PGK1 Inhibitor with the Suppression of Breast Cancer Cells Using Virtual Screening and Molecular Docking

BACKGROUND/OBJECTIVES

Breast cancer is the second most common malignancy worldwide and poses a significant threat to women's health. However, the prognostic biomarkers and therapeutic targets of breast cancer are unclear. A prognostic model can help in identifying biomarkers and targets for breast cancer. In this study, a novel prognostic model was developed to optimize treatment, improve clinical prognosis, and screen potential phosphoglycerate kinase 1 (PGK1) inhibitors for breast cancer treatment.

METHODS

Using data from the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) were identified in normal individuals and breast cancer patients. The biological functions of the DEGs were examined using bioinformatics analysis. A novel prognostic model was then constructed using the DEGs through LASSO and multivariate Cox regression analyses. The relationship between the prognostic model, survival, and immunity was also evaluated. In addition, virtual screening was conducted based on the risk genes to identify novel small molecule inhibitors of PGK1 from Chemdiv and Targetmol libraries. The effects of the potential inhibitors were confirmed through cell experiments.

RESULTS

A total of 230 up- and 325 down-regulated DEGs were identified in HER2, LumA, LumB, and TN breast cancer subtypes. A new prognostic model was constructed using ten risk genes. The analysis from The Cancer Genome Atlas (TCGA) indicated that the prognosis was poorer in the high-risk group compared to the low-risk group. The accuracy of the model was confirmed using the ROC curve. Furthermore, functional enrichment analyses indicated that the DEGs between low- and high-risk groups were linked to the immune response. The risk score was also correlated with tumor immune infiltrates. Moreover, four compounds with the highest score and the lowest affinity energy were identified. Notably, D231-0058 showed better inhibitory activity against breast cancer cells.

CONCLUSIONS

Ten genes (ACSS2, C2CD2, CXCL9, KRT15, MRPL13, NR3C2, PGK1, PIGR, RBP4, and SORBS1) were identified as prognostic signatures for breast cancer. Additionally, results showed that D231-0058 (2-((((4-(2-methyl-1H-indol-3-yl)-1,3-thiazol-2-yl)carbamoyl)methyl)sulfanyl)acetic acid) may be a novel candidate for treating breast cancer.

An integrated microfluidic platform for nucleic acid testing

This study presents a rapid and versatile low-cost sample-to-answer system for SARS-CoV-2 diagnostics. The system integrates the extraction and purification of nucleic acids, followed by amplification via either reverse transcription-quantitative polymerase chain reaction (RT-qPCR) or reverse transcription loop-mediated isothermal amplification (RT-LAMP). By meeting diverse diagnostic and reagent needs, the platform yields testing results that closely align with those of commercial RT-LAMP and RT‒qPCR systems. Notable advantages of our system include its speed and cost-effectiveness. The assay is completed within 28 min, including sample loading (5 min), ribonucleic acid (RNA) extraction (3 min), and RT-LAMP (20 min). The cost of each assay is ≈ $9.5, and this pricing is competitive against that of Food and Drug Administration (FDA)-approved commercial alternatives. Although some RNA loss during on-chip extraction is observed, the platform maintains a potential limit of detection lower than 297 copies. Portability makes the system particularly useful in environments where centralized laboratories are either unavailable or inconveniently located. Another key feature is the platform's versatility, allowing users to choose between RT‒qPCR or RT‒LAMP tests based on specific requirements.

3D Printing for Cancer Diagnosis: What Unique Advantages Are Gained?

Cancer is a complex disease with global significance, necessitating continuous advancements in diagnostics and treatment. 3D printing technology has emerged as a revolutionary tool in cancer diagnostics, offering immense potential in detection and monitoring. Traditional diagnostic methods have limitations in providing molecular and genetic tumor information that is crucial for personalized treatment decisions. Biomarkers have become invaluable in cancer diagnostics, but their detection often requires specialized facilities and resources. 3D printing technology enables the fabrication of customized sensor arrays, enhancing the detection of multiple biomarkers specific to different types of cancer. These 3D-printed arrays offer improved sensitivity, allowing the detection of low levels of biomarkers, even in complex samples. Moreover, their specificity can be fine-tuned, reducing false-positive and false-negative results. The streamlined and cost-effective fabrication process of 3D printing makes these sensor arrays accessible, potentially improving cancer diagnostics on a global scale. By harnessing 3D printing, researchers and clinicians can enhance early detection, monitor treatment response, and improve patient outcomes. The integration of 3D printing in cancer diagnostics holds significant promise for the future of personalized cancer care.

Integrating nucleic acid sequence-based amplification and microlensing for high-sensitivity self-reporting detection

We use electron-beam patterned functional microgels to integrate self-reporting molecular beacons, dielectric microlenses, and solid-phase and/or solution-phase nucleic acid amplification in a viral-detection microarray model. The detection limits for different combinations of these elements range from 10-10 M for direct target-beacon hybridization alone to 10-18 M when all elements are integrated simultaneously.

Colorimetric hand-held sensors and biosensors with a small digital camera as signal recorder, a review

Sensors, biosensors, lateral flow immunoassays, portable thin-layer chromatography and similar devices for hand-held assay are tools suitable for field or out of laboratories assays of various analytes. The assays frequently exert a limit of detection and sensitivity close to more expensive and elaborative analytical methods. In recent years, huge progress has been made in the field of optical instruments where digital cameras or light sensitive chips serve for the measurement of color density. General availability of cameras, a decrease of prices and their integration into wide spectrum phones, tablets and computers give the promise of easy application of analytical methods where such cameras will be employed. This review summarizes research on hand-held assays where small cameras like the ones integrated into smartphones are used. Discussion about such assays, their practical applicability and relevant specifications are also written here.

Dual-Mode Photonic Sensor Array for Detecting and Discriminating Hydrazine and Aliphatic Amines

Colorimetric chemosensors have attracted tremendous interest for sensing hazardous substances in an uncomplicated and economical manner. Herein, a series of push-pull dicyanovinyl-substituted oligothiophene derivatives were designed, and the impacts of different end-cappers on their photophysical properties were comprehensively investigated. Interestingly, combined with a zinc porphyrin derivative (Zn-TPP), one dicyanovinyl-substituted oligothiophene derivative (NA-3T-CN) can be further developed into colorimetric and fluorescent sensor array for dual-mode detection of aliphatic amines and hydrazine. The obtained sensors showed satisfactory results between optical response and analyte's concentration both in selective single-sensor type and in enhanced multisensory mode. Based on the fluorescence change of the NA-3T-CN system, the detection limit for N₂H₄ was calculated to be around 1.22 × 10^-5 mol/L in THF. The stained TLC-supported sensor array offers obvious optical changes for down to 0.5 wt % hydrazine solution for naked-eye sensing. An aromatic amine like aniline has no obvious effect on the dicyanovinyl-substituted oligothiophene derivatives. We also found that a zinc porphyrin derivative has an obvious colorimetric response to the presence of hydrazine, ethanolamine, and aniline. Furthermore, smartphone-enabled readout system and data treatment based on RGB changes of the sensor array were performed, and the discrimination capability among hydrazine, aliphatic amines, and aromatic amine was satisfactory. In this regard, related push-pull oligothiophene derivatives not only can be regarded as models for a fundamental understanding of the relationship between molecular structure and photophysical properties but also present potential applications in the field of real-time and visual detection of hazardous chemicals.

Identification of significant gene biomarkers of low back pain caused by changes in the osmotic pressure of nucleus pulposus cells

The incidence of intervertebral disc (IVD) degeneration disease, caused by changes in the osmotic pressure of nucleus pulposus (NP) cells, increases with age. In general, low back pain is associated with IVD degeneration. However, the mechanism and molecular target of low back pain have not been elucidated, and there are no data suggesting specific biomarkers of low back pain. Therefore, the research aims to identify and verify the significant gene biomarkers of low back pain. The differentially expressed genes (DEGs) were screened in the Gene Expression Omnibus (GEO) database, and the identification and analysis of significant gene biomarkers were also performed with various bioinformatics programs. A total of 120 patients with low back pain were recruited. Before surgery, the degree of pain was measured by the numeric rating scale (NRS), which enables comparison of the pain scores from individuals. After surgery, IVD tissues were obtained, and NP cells were isolated. The NP cells were cultured in two various osmotic media, including iso-osmotic media (293 mOsm/kg H₂O) to account for the morbid environment of NP cells in IVD degeneration disease and hyper-osmotic media (450 mOsm/kg H₂O) to account for the normal condition of NP cells in healthy individuals. The relative mRNA expression levels of CCL5, OPRL1, CXCL13, and SST were measured by quantitative real-time PCR in the in vitro analysis of the osmotic pressure experiments. Finally, correlation analysis and a neural network module were employed to explore the linkage between significant gene biomarkers and pain. A total of 371 DEGs were identified, including 128 downregulated genes and 243 upregulated genes. Furthermore, the four genes (CCL5, OPRL1, SST, and CXCL13) were identified as significant gene biomarkers of low back pain (P < 0.001) based on univariate linear regression, and CCL5 (odds ratio, 34.667; P = 0.003) and OPRL1 (odds ratio, 19.875; P < 0.001) were significantly related to low back pain through multivariate logistic regression. The expression of CCL5 and OPRL1 might be correlated with low back pain in patients with IVD degeneration disease caused by changes in the osmotic pressure of NP cells.

Supervised and unsupervised algorithms for bioinformatics and data science

Bioinformatics refers to an ever evolving huge field of research based on millions of algorithms, designated to several data banks. Such algorithms are either supervised or unsupervised. In this article, a detailed overview of the supervised and unsupervised techniques is presented with the aid of examples. The aim of this article is to provide the readers with the basic understanding of the state of the art models, which are key ingredients of explainable machine learning in the field of bioinformatics.

[E-health and "Cancer outside the hospital walls", Big Data and artificial intelligence]

To heal otherwise in oncology has become an imperative of Public Health and an economic imperative in France. Patients can therefore receive live most of their care outside of hospital with more ambulatory care. This ambulatory shift will benefit from the digital revolution and the development of digital health or e-health. Cancer research will also benefit with Big Data and artificial intelligence, which gather and analyze a huge amount of data. In this synthesis, we describe the different e-health tools and their potential impacts in oncology, at the levels of education and information of patients and caregivers, prevention, screening and diagnosis, treatment, follow-up, and research. A few randomized studies have already demonstrated clinical benefits. Large Big Data projects such as ConSoRe and Health Data Hub have been launched in France. We also discuss the issues and limitations of "cancer outside the hospital walls and e-health" from the point of view of patients, health care professionals, health facilities and government. This new organization will have to provide remote support "outside the walls" with care and follow-up of quality, continuous and prolonged in total safety and equity. Ongoing and future randomized clinical trials will need to definitively demonstrate areas of interest, advantages and drawbacks not only for patients, but also for caregivers, health facilities and governments.

Multiplexed Paper Microfluidics for Titration and Detection of Ingredients in Beverages

Food safety and access to systematic approaches for ensuring detection of food hazards is an important issue in most developing countries. With the arrival of paper-based analytical devices (µPADs) as a promising, rapid, easy-to-use, and low-cost analytical tool, we demonstrated a simple microfluidic-based titration study for the analysis of packaged fruit juices. Similar, to the titration experiments using traditional glassware in chemistry laboratories, in this study the titration experiments were developed using paper microfluidics for the analysis of several analytes such as pH, vitamin C, sugars, and preservatives present in the packaged fruit juices. The allergen found commonly in dairy based mixtures and the non-pathogenic biochemical component responsible for food spoilage in cider based fruit juices were also determined. The results obtained using paper microfluidics were compared with those obtained using a conventional spectrophotometric technique. Finally, a paper microfluidics based multiplexed sensor was developed for the analysis of common nutritional ingredients, an allergen, and a non-pathogenic byproduct present in packaged fruit juices on a single platform. Overall, the results presented in this study reveal that the proposed paper microfluidic assisted colorimetric multiplexed sensor offers a quick and reliable tool for on-spot routine analysis for food safety applications.

Outpatient Cancer Care Delivery in the Context of E-Oncology: A French Perspective on "Cancer outside the Hospital Walls"

In oncology, the treatment of patients outside of hospitals has become imperative due to an increasing number of patients who are older and live longer, along with issues such as medical desertification, oncologist hyperspecialization, and difficulties in financing mounting health expenditures. Treatments have become less "invasive", with greater precision and efficiency. Patients can therefore receive most of their care outside of hospitals. The development of e-health can address these new imperatives. In this letter, we describe the different e-health tools and their potential clinical impacts in oncology, as already reported at every level of care, including education, prevention, diagnosis, treatment, and monitoring. A few randomized studies have yet demonstrated the clinical benefit. We also comment on issues and limits of "cancer outside the hospital walls" from the point of view of patients, health care professionals, health facilities, and public authorities. Care providers in hospitals and communities will have to adapt to these changes within well-coordinated networks in order to better meet patient expectations regarding increasing education and personalizing management. Ultimately, controlled studies should aim to definitively demonstrate areas of interest, benefits, and incentives, for not only patients, but also caregivers (formal and informal) and health care providers, health care facilities, and the nation.