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Simple Summary: This research is the first comprehensive study in New Zealand to categorise and examine the characteristics of breast cancer based on HER2 status. We explored three HER2 categories: HER2-zero, HER2-low, and HER2-positive, in women diagnosed with invasive breast cancer. Utilising Te Rēhita Mate Ūtaetae (Breast Cancer Foundation NZ National Register), our study analysed data spanning 21 years, revealing that most women underwent HER2 testing. Significantly, many cases previously not recognised as having significant HER2 levels were in fact HER2-low, qualifying them for newer, targeted drug therapies. These findings are particularly crucial as they suggest that newer therapies could benefit a larger segment of patients, notably those with advanced breast cancer; approximately 60% of these women might now benefit from these innovative HER2-targeted treatments. The study underscores the urgent need for standardised HER2 testing to personalise and optimise treatment, enhancing outcomes for patients with invasive breast cancer. Objectives: To perform the first national analysis of demographic and clinicopathological features associated with the HER2 positive, HER2-low, and HER2-zero invasive breast cancers in New Zealand. The study will reveal the proportion of women who may benefit from new HER2-targeted antibody drug conjugate (ADC) therapies. Methods: Utilising data from Te Rēhita Mate Ūtaetae (Breast Cancer Foundation NZ National Register), the study analysed data from women diagnosed with invasive breast cancer over a 21-year period. The HER2 status of tumours was classified into three categories—HER2-zero, HER2-low, HER2-positive. Results: From 2009–2021, 94% of women underwent HER2 testing, with 14% diagnosed with HER2-positive breast cancer. For advanced-stage disease, 38% of those formerly classified as HER2-negative were reclassified as HER2-low. Including HER2-positive breast cancers, this indicates that 60% of women with advanced breast cancer may potentially benefit from the new HER2-directed ADCs (approximately 120 women per year). Conclusions: The findings suggest a significant proportion of women with invasive breast cancer in New Zealand could benefit from new HER2-targeted treatments. There is a need to standardise HER2 testing to enhance personalised treatment and improve outcomes. [ABSTRACT FROM AUTHOR]

Abstract Fluorescence in Situ Hybridization (FISH) is a technique for macromolecule identification that utilizes the complementarity of DNA or DNA/RNA double strands. Probes, crafted from selected DNA strands tagged with fluorophore-coupled nucleotides, hybridize to complementary sequences within the cells and tissues under examination. These are subsequently visualized through fluorescence microscopy or imaging systems. However, the vast number of cells and disorganized nucleic acid sequences in FISH images present significant challenges. The manual processing and analysis of these images are not only time-consuming but also prone to human error due to visual fatigue. To overcome these challenges, we propose the integration of medical imaging with deep learning to develop an automated detection system for FISH images. This system features an algorithm capable of quickly detecting fluorescent spots and capturing their coordinates, which is crucial for evaluating cellular characteristics in cancer diagnosis. Traditional models struggle with the small size, low resolution, and noise prevalent in fluorescent points, leading to significant performance declines. This paper offers a detailed examination of these issues, providing insights into why traditional models falter. Comparative tests between the YOLO series models and our proposed method affirm the superior accuracy of our approach in identifying fluorescent dots in FISH images.

AIM: The aim of this study is to standardize in-vitro CRISPR-Cas13 assay for the detection of salivary microRNAs (miRNAs) as Oral Cancer Biomarker. BACKGROUND: Oral cavity cancer poses a significant global health threat, prevalent in both emerging and industrialized nations, primarily attributed to factors such as tobacco and alcohol use. This study addresses the imperative need for adaptive, effective, and non-invasive strategies in the diagnosis and treatment of oral cancer, emphasising the importance of early detection for improved prognosis. The study introduces a novel approach employing the CRISPR-Cas13 system for the detection of salivary miRNA-145 as an oral cancer biomarker. Material and methods: The study utilized the CRISPR-Cas13 system to detect salivary miRNA-145. Specific guide RNA (gRNA) sequences were designed which guides LwaCas13a and targets miRNA-145, resulting in activation of collateral cleavage activity. Total RNA isolated from salivary samples were used in the assay, and the detection of miRNA-145 was assessed through distinct reduction in band intensity and fluorescence detection using a FAM based reporter RNA. Results: This study has successfully set up CRISPR-Cas13 in-vitro assay for detection of miRNA. The assay demonstrated a distinct reduction in band intensity in test samples compared to controls when total RNA was used. The assay employing reporter RNA illustrates fluorescence detection exclusively in test samples utilizing specific gRNA. Conclusion: This study introduces an innovative method for oral cancer detection, leveraging the CRISPR-Cas13 system and salivary miRNA-145 as a biomarker. The approach presents a non-invasive, cost-effective, and efficient alternative for early cancer diagnosis and monitoring, showcasing its potential impact on advancing diagnostic technologies in the field.

AbstractPolydopamine (PDA) stands as a versatile material explored in cancer nanomedicine for its unique properties, offering opportunities for multifunctional drug delivery platforms. This study explores the potential of utilizing a one-pot synthesis to concurrently integrate Fe, Gd and Mn ions into porous PDA-based theranostic drug delivery platforms called Ferritis, Gadolinis and Manganis, respectively. Our investigation spans the morphology, magnetic properties, photothermal characteristics and cytotoxicity profiles of those potent nanoformulations. The obtained structures showcase a spherical morphology, robust magnetic response and promising photothermal behaviour. All of the presented nanoparticles (NPs) display pronounced paramagnetism, revealing contrasting potential for MRI imaging. Relaxivity values, a key determinant of contrast efficacy, demonstrated competitive or superior performance compared to established, used contrasting agents. These nanoformulations also exhibited robust photothermal properties under near infra-red irradiation, showcasing their possible application for photothermal therapy of cancer. Our findings provide insights into the potential of metal-doped PDA NPs for cancer theranostics.

Abstract The imperative need for sensitive and precise tools is underscored in cancer diagnostics, with biomarkers playing a pivotal role in facilitating early detection and tumor diagnosis. Despite their classical pathological classification, testicular tumors lack valuable markers, emphasizing the necessity to identify and apply serum tumor markers in clinical management. Unfortunately, existing biomarkers exhibit limited sensitivities and specificities. Recent years have witnessed the discovery of novel RNA molecules, presenting a potential breakthrough as diagnostic tools and promising biomarkers. This report presents compelling evidence supporting the detection of early testicular cancer by applying a set of nine microRNAs (miRNAs), establishing them as valuable serum biomarkers for diagnosis. We developed a standardized serum-based measurement protocol and conducted comprehensive statistical analyses on the dataset to underscore the diagnostic accuracy of the miRNA pool. Notably, with a sensitivity exceeding 93%, miR-21, miR-29a, and miR-106b surpass classical serum tumor markers in the context of testicular cancer. Specifically, these miRNAs are poised to enhance clinical decision-making in testicular cancer detection and hold the potential for assessing tumor growth in monitoring chemotherapy outcomes.

Currently, Raman imaging as a non-destructive technique providing knowledge on structural characterization of the investigated samples is gaining more and more interest among industrial formulation and process scientists. In the pharmaceutical sector, the creation of novel products and formulations necessitates flexible and adaptable analysis, and increasingly also imaging capabilities. In this paper, the attention is directed toward the research progress, that has occurred in the application of non-invasive Raman chemical imaging techniques in industrial pharmacy and medical diagnostics in recent years. This work aims to explore the potential of Raman imaging as a knowledge discovery method for the non-destructive evaluation of pharmaceutical formulations as well as human cells to support medical diagnostics in clinical practice. A review of the latest scientific papers indicates that the applications of Raman imaging in pharmaceutical sciences and medical diagnostics are diverse and far-reaching from ensuring the quality of pharmaceutical formulations to studying complex drug delivery systems, monitoring manufacturing processes, and medical diagnostics of cancers and other diseases. As technology continues to evolve, the integration of Raman imaging into pharmaceutical and clinical practices is expected to expand, providing new insights and solutions to the challenges faced by the pharmaceutical industry and medical diagnostics.

The growing cancer burden in Africa demands urgent action. Medical imaging is crucial for cancer diagnosis and management and is an essential enabler of precision medicine. To understand the readiness for quantitative imaging analysis to support cancer management in Africa, we analyzed the utilization patterns of imaging modalities for cancer research across the continent. We retrieved articles by systematically searching PubMed, using a combination of search terms {"Neoplasm"} AND {"Radiology" or "Diagnostic imaging" or "Radiography" or "Interventional Radiology" or "Radiotherapy" or "Radiation Oncology"} AND {Africa∗ or 54 African countries}. Articles describing cancer diagnosis or management in humans with the utilization of imaging were included. Exclusion criteria were review articles, non-English articles, publications before 2000, noncancer diagnoses, and studies conducted outside Africa. The analysis of diagnostic imaging in Africa revealed a diverse utilization pattern across different cancer types and regions. The literature search identified 107 publications on cancer imaging in Africa. The studies were carried out in 19 African countries on 12 different cancer types with 6 imaging modalities identified. Most cancer imaging research studies used multiple imaging modalities. Ultrasound was the most used distinct imaging modality and MRI was the least frequently used. Most research studies originated from Nigeria, South Africa, and Egypt. We demonstrate substantial variability in the presence of imaging modalities, widespread utilization of ultrasonography, and limited availability of advanced imaging modalities for cancer research. [ABSTRACT FROM AUTHOR]

Introduction: Colorectal cancer (CRC) is one of the most deadly cancers on a global scale. Diagnosis of CRC is challenging and it is often detected at a late stage. Identification of relevant biomarkers could lead to the development of effective diagnostic methods for CRC. Areas covered: We reviewed the literature on lipid (including exosomal) biomarkers that have the potential to become common, minimally invasive and effective diagnostic tools for CRC. We showed that differences in lipid levels (single compounds and entire panels) make it possible to classify patients into diseased or healthy groups, determine the stage of CRC, as well as accompanying inflammation and immune reactions associated with tumorigenesis. We also discussed exosomes which are important components of the tumor microenvironment that influence tumor progression and for which only a small number of studies were conducted so far in this area. Expert opinion: A rapid development in the field of lipid-based biomarkers, including exosomal lipid biomarkers, is expected as growing evidence shows their potential application and good accuracy. However, one of the major issues that needs to be addressed within this topic is to translate findings into a noninvasive and versatile diagnostic test robustly validated in clinical conditions. [ABSTRACT FROM AUTHOR]

Background and aim: Patients suffering from cancer are reported to have an increased risk of ischemic stroke (IS). We aimed to identify cancer-associated biomarkers found to differentiate between IS associated with cancer from those not associated with cancer. Summary of review: We performed a systematic search of PubMed and EMBASE databases according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The study is reported in PROSPERO (#CRD42022355129). In total, 5563 papers were screened, of which 49 papers were included. Seven biomarkers were identified which had the potential to differentiate between patients who had cancer or stroke or both conditions. D-dimer was the most frequently monitored biomarker, and high levels were significantly associated with cancer-related strokes in (42/44) studies. Fibrinogen was significantly associated with cancer-related strokes in 11/27 studies. A higher level of C-reactive protein, investigated in 19 studies, was associated with cancer-related strokes, but conclusive multivariate analysis was not performed. Finally, the four cancer-associated antigens CA125, CA153, CA199, and carcinoembryonic antigen were only reported on in three to six studies, respectively. These studies all originated from the Guangxi province in China. CA125 was associated with an increased risk of IS in four of six studies. Conclusion: Increased D-dimer seems associated with cancer-related IS. CRP may also be a candidate as a cancer-associated stroke biomarker, but this requires further verification. Fibrinogen and the more specific cancer biomarkers have not yet been proven helpful for detecting cancer-related strokes. [ABSTRACT FROM AUTHOR]

Simple Summary: This review discusses the importance of advancements in cancer diagnosis and treatment, emphasizing the need for early detection methods. It highlights the role of DNA methylation, an epigenetic change, as a promising marker for detecting cancer. This review explains how DNA methylation patterns differ between cancerous and healthy cells, influencing gene expression and contributing to genomic instability. It also delves into the challenges and methods associated with detecting DNA methylation, particularly in cell-free DNA (cfDNA) from bodily fluids, known as liquid biopsies. Different tests for single-cancer detection, such as colorectal, lung, and bladder cancer, as well as multi-cancer detection tests, are discussed along with their methodologies and clinical applications. Biological factors influencing DNA methylation, such as age, gender, and environmental influences, are also explored. The conclusion emphasizes the potential of cfDNA methylation analysis in cancer diagnostics but acknowledges the current limitations and challenges, highlighting the need for further research and advancements in methodology and understanding. In current clinical practice, effective cancer testing and screening paradigms are limited to specific types of cancer, exhibiting varying efficiency, acceptance, and adherence. Cell-free DNA (cfDNA) methylation profiling holds promise in providing information about the presence of malignity regardless of its type and location while leveraging blood-based liquid biopsies as a method to obtain analytical samples. However, technical difficulties, costs and challenges resulting from biological variations, tumor heterogeneity, and exogenous factors persist. This method exploits the mechanisms behind cfDNA release but faces issues like fragmentation, low concentrations, and high background noise. This review explores cfDNA methylation's origins, means of detection, and profiling for cancer diagnostics. The critical evaluation of currently available multi-cancer early detection methods (MCEDs) as well as tests targeting single genes, emphasizing their potential and limits to refine strategies for early cancer detection, are explained. The current methodology limitations, workflows, comparisons of clinically approved liquid biopsy-based methylation tests for cancer, their utilization in companion diagnostics as well as the biological limitations of the epigenetics approach are discussed, aiming to help healthcare providers as well as researchers to orient themselves in this increasingly complex and evolving field of diagnostics. [ABSTRACT FROM AUTHOR]

Summary: Background: Deployment and access to state-of-the-art precision medicine technologies remains a fundamental challenge in providing equitable global cancer care in low-resource settings. The expansion of digital pathology in recent years and its potential interface with diagnostic artificial intelligence algorithms provides an opportunity to democratize access to personalized medicine. Current digital pathology workstations, however, cost thousands to hundreds of thousands of dollars. As cancer incidence rises in many low- and middle-income countries, the validation and implementation of low-cost automated diagnostic tools will be crucial to helping healthcare providers manage the growing burden of cancer. Methods: Here we describe a low-cost ($230) workstation for digital slide capture and computational analysis composed of open-source components. We analyze the predictive performance of deep learning models when they are used to evaluate pathology images captured using this open-source workstation versus images captured using common, significantly more expensive hardware. Validation studies assessed model performance on three distinct datasets and predictive models: head and neck squamous cell carcinoma (HPV positive versus HPV negative), lung cancer (adenocarcinoma versus squamous cell carcinoma), and breast cancer (invasive ductal carcinoma versus invasive lobular carcinoma). Findings: When compared to traditional pathology image capture methods, low-cost digital slide capture and analysis with the open-source workstation, including the low-cost microscope device, was associated with model performance of comparable accuracy for breast, lung, and HNSCC classification. At the patient level of analysis, AUROC was 0.84 for HNSCC HPV status prediction, 1.0 for lung cancer subtype prediction, and 0.80 for breast cancer classification. Interpretation: Our ability to maintain model performance despite decreased image quality and low-power computational hardware demonstrates that it is feasible to massively reduce costs associated with deploying deep learning models for digital pathology applications. Improving access to cutting-edge diagnostic tools may provide an avenue for reducing disparities in cancer care between high- and low-income regions. Funding: Funding for this project including personnel support was provided via grants from NIH/NCI R25-CA240134, NIH/NCI U01-CA243075, NIH/NIDCR R56-DE030958, NIH/NCI R01-CA276652, NIH/NCI K08-CA283261, NIH/NCI-SOAR 25CA240134, SU2C (Stand Up to Cancer) Fanconi Anemia Research Fund – Farrah Fawcett Foundation Head and Neck Cancer Research Team Grant, and the European Union Horizon Program (I3LUNG).

This review article offers a comprehensive analysis of current developments in the application of machine learning for cancer diagnostic systems. The effectiveness of machine learning approaches has become evident in improving the accuracy and speed of cancer detection, addressing the complexities of large and intricate medical datasets. This review aims to evaluate modern machine learning techniques employed in cancer diagnostics, covering various algorithms, including supervised and unsupervised learning, as well as deep learning and federated learning methodologies. Data acquisition and preprocessing methods for different types of data, such as imaging, genomics, and clinical records, are discussed. The paper also examines feature extraction and selection techniques specific to cancer diagnosis. Model training, evaluation metrics, and performance comparison methods are explored. Additionally, the review provides insights into the applications of machine learning in various cancer types and discusses challenges related to dataset limitations, model interpretability, multi-omics integration, and ethical considerations. The emerging field of explainable artificial intelligence (XAI) in cancer diagnosis is highlighted, emphasizing specific XAI techniques proposed to improve cancer diagnostics. These techniques include interactive visualization of model decisions and feature importance analysis tailored for enhanced clinical interpretation, aiming to enhance both diagnostic accuracy and transparency in medical decision-making. The paper concludes by outlining future directions, including personalized medicine, federated learning, deep learning advancements, and ethical considerations. This review aims to guide researchers, clinicians, and policymakers in the development of efficient and interpretable machine learning-based cancer diagnostic systems.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. Methods RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. Results An initial cluster analysis of RNA-seq expression data showed separation by the subjects’ gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). Conclusions Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. Methods: RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. Results: An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). Conclusions: Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method. [ABSTRACT FROM AUTHOR]

Breast cancer is an illness that affects many women and can cause even death; this is a case of not being detected on time, which could be due to a human error during the analysis of radiographic images or not going on time in a health center. For this, using machine learning (ML) to analyze radiographic images is proposed as a support tool for radiologists aiming to reduce false diagnostic rates. While researching information, it was detected that this technology has many benefits in the health area; however, it also has limitations or disadvantages. The importance of this paper is to demonstrate that there are not enough clinical tests nor details about the methodologies that were used; there should be more to assert that ML is defined at the moment of making a diagnosis, which generates no conclusive results regarding effectiveness and therefore creates mistrust in doctors, and some people might rather use deep learning (DL) for its application in the detection of breast cancer because DL has more practical tests and fewer limitations than machine learning. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) is a routine diagnostic modality in oncology that produces excellent imaging resolution and tumor contrast without the use of ionizing radiation. However, improved contrast agents are still needed to further increase detection sensitivity and avoid toxicity/allergic reactions associated with paramagnetic metal contrast agents, which may be seen in a small percentage of the human population. Fluorine‐19 (19F)‐MRI is at the forefront of the developing MRI methodologies due to near‐zero background signal, high natural abundance of 100%, and unambiguous signal specificity. In this study, we have developed a colloidal nanoemulsion (NE) formulation that can encapsulate high volumes of the fluorous MRI tracer, perfluoro‐[15‐crown‐5]‐ether (PFCE) (35% v/v). These nanoparticles exhibit long‐term (at least 100 days) stability and high PFCE loading capacity in formulation with our semifluorinated triblock copolymer, M2F8H18. With sizes of approximately 200 nm, these NEs enable in vivo delivery and passive targeting to tumors. Our diagnostic formulation, M2F8H18/PFCE NE, yielded in vivo19F‐MR images with a high signal‐to‐noise ratio up to 100 in a tumor‐bearing mouse model at clinically relevant scan times. M2F8H18/PFCE NE circulated stably in the vasculature, accumulated in high concentration of an estimated 4–9 × 1017 19F spins/voxel at the tumor site, and cleared from most organs over the span of 2 weeks. Uptake by the mononuclear phagocyte system to the liver and spleen was also observed, most likely due to particle size. These promising results suggest that M2F8H18/PFCE NE is a favorable 19F‐MR diagnostic tracer for further development in oncological studies and potential clinical translation. [ABSTRACT FROM AUTHOR]

This article delves into the analysis of the impact of bio-realization engineering technologies on cancer diagnostic processes within the contemporary healthcare system. The objective of the article is to identify the potential of molecular-genetic testing and other bio-realization methods in enhancing diagnostic capabilities and therapeutic approaches for oncological diseases. To achieve this goal, general scientific methods of analysis and synthesis of existing research in this field are utilized, including a review of scientific literature and a critical analysis of the results of experimental studies. The findings confirm the significant impact of bio-realization engineering technologies on the advancement of cancer diagnostics. Specifically, molecular-genetic testing opens new avenues for early detection and personalized treatment approaches for cancer, based on the genetic characteristics of tumors. These technologies are particularly valuable for countries with limited medical resources, as they offer cost-effective and efficient solutions that provide broader access to quality diagnostic services. They also contribute to improving the overall efficacy of treatment strategies and optimizing medical research, reducing the burden on medical staff. The practical significance of the obtained results lies in the possibility of their application in the development of new diagnostic tools and techniques aimed at enhancing the accuracy, accessibility, and efficiency of cancer treatment. This, in turn, may contribute to reducing mortality from oncological diseases and improving patients' quality of life. Bio-realization engineering technologies, particularly molecular-genetic testing, play a pivotal role in modern oncological diagnostics, offering promising opportunities for the improvement of diagnostic and therapeutic procedures for cancer. Their integration into the healthcare system enhances diagnostic accuracy, treatment accessibility, and the overall level of medical services, opening new horizons in the fight against oncological diseases. [ABSTRACT FROM AUTHOR]

Currently, Raman imaging as a non-destructive technique providing knowledge on the structural characterization of the investigated samples is gaining more and more interest among industrial formulation and process scientists. In the pharmaceutical sector, the creation of novel products and formulations necessitates flexible and adaptable analysis, and increasingly also imaging capabilities. In this paper, attention is directed towards the research progress that has occurred in the application of noninvasive Raman chemical imaging techniques in industrial pharmacy and medical diagnostics in recent years. This work aims to explore the potential of Raman imaging as a knowledge discovery method for the non-destructive evaluation of pharmaceutical formulations as well as human cells to support medical diagnostics in clinical practice. A review of the latest scientific papers indicates that the applications of Raman imaging in pharmaceutical sciences and medical diagnostics are diverse and far-reaching from ensuring the quality of pharmaceutical formulations to studying complex drug delivery systems, monitoring manufacturing processes, and medical diagnostics of cancers and other diseases. As technology continues to evolve, the integration of Raman imaging into pharmaceutical and clinical practices is expected to expand, providing new insights and solutions to the challenges faced by the pharmaceutical industry and medical diagnostics. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) appears among the most frequently diagnosed types of malignancies in males. Because of the high demand and increasing detection rate of early PCa, alongside the specificity limitations of the gold standard clinical tools available for the diagnosis and prognosis of prostate cancer, there is an urgent need for more reliable PCa markers and highly sensitive diagnostic tools to avoid under-treatment and over-diagnosis. PCA3, or prostate cancer antigen 3, is a potential prostate cancer biomarker that is more specific and useful for preventing unnecessary repeat biopsies, particularly in men with persistently high prostate-specific antigen indices after a negative biopsy. Additionally, an electrochemically based biosensor would prove to be a powerful diagnostic tool for PCA3 detection in urine because of its simplicity, sensitivity, and cost-effectiveness, in contrast to the more traditional PCa diagnostics that depend on blood testing. This paper aimed to design a novel and simple electrochemical impedimetric biosensor based on a label-free RNA-aptamer (CG3-PCA3) as the molecular recognition element for detecting PCA3. The proposed aptasensor for the detection of PCA3 has been developed using a screen-printed carbon electrode (SPCE) modified by gold nanoparticles (AuNPs), further improving sensitivity and allowing the immobilisation of thiolate aptamers on its surface. The findings presented here demonstrated a high sensitivity to PCA3, with a detection limit of 20 fM in artificial urine and 1 fM in buffer. These results indicate that the PCA3 aptasensor could be a promising tool for routine PCa diagnosis due to its high sensitivity and cost-effectiveness.

The healthcare industry is constantly changing because of technological breakthroughs that spur new methods of diagnosing and treating illnesses. This study investigates the development of Ion Sensitive Field Effect Transistor (ISFET) sensors for DNA-based blood cancer diagnosis. This work presents the design of a two-dimensional ion-sensitive field-effect transistor. Concentration fluctuations and transfer characteristics with different oxides are studied using blood from two electrolyte solutions. It is possible to evaluate how the modeled device can be utilized as a pH sensor or a biosensor in healthcare applications by looking at how the pH changes for different oxides. Additionally, several oxides were examined in the simulated ISFET devices' output characteristics. Blood is the electrolyte to study the device's sensitivity for different oxides. When pH 7.4 is considered, SiO2 oxide is significantly more sensitive than other oxides. The resulting 2D-ISFET exhibits remarkable blood electrolyte sensitivity and holds potential as a quick detection tool for blood cancer. The results show that the ISFET possesses drain-induced barrier lowering (DIBL), greater ON-current (ION) and switching ratio (ION/IOFF), and decreased subthreshold swing (SS). The pH sensor's sensitivity and the suggested equipment can detect up to 30 fg/mL of blood cancer biomarkers. An important development in technology-driven healthcare is the emergence of DNA-based blood cancer detection utilizing ISFET sensors. This opens up new avenues for improving cancer diagnosis and patient outcomes.

Cancer stands as one of the most common and lethal diseases, imposing a substantial burden on global mortality rates. Breast cancer is distinct from other forms of cancer in which it is the primary cause of death for women. Early detection of breast cancer can significantly lower the risk of mortality, improving the prognosis for those who are affected. The death rate of breast cancer has been steadily rising, according to epidemiological data, especially since the COVID-19 pandemic. This emphasizes the necessity of sensitive and precise technologies that can be utilized in early breast cancer diagnosis. In this process, biomarkers play a pivotal role by facilitating the early detection and diagnosis of breast cancer. Currently, a wide variety of cancer biomarkers have been identified, improving the accuracy of cancer diagnosis. These biomarkers can be applied in liquid biopsies as well as on solid tissues. In the context of breast cancer, biomarkers are particularly valuable for determining who is predisposed to the disease, predicting prognosis at the time of diagnosis, and selecting the best course of therapy. This review comprehensively explores the recently developed gene-based biomarkers from biofluids that are used in the context of breast cancer, as well as the conventional and cutting-edge techniques that have been employed for breast cancer diagnosis. • Molecular classification of breast cancer has an important role in the precise diagnostics of tumor samples. • Next-generation sequencing is employed for the purposes of applying precision oncology. • Recent advance in liquid biopsy allows the application of novel ctDNA and RNA based biomarkers. [ABSTRACT FROM AUTHOR]

Liquid biopsy for minimally invasive diagnosis and monitoring of cancer patients is progressing toward routine clinical practice. With the implementation of highly sensitive next-generation sequencing (NGS) based assays for the analysis of cfDNA, however, consideration of the utility of liquid biopsy for clinical genetic testing is critical. While the focus of liquid biopsy for cancer diagnosis is the detection of circulating tumor DNA (ctDNA) as a fraction of total cell-free DNA (cfDNA), cfDNA analysis reveals both somatic mosaic tumor and germline variants and clonal hematopoiesis. Here we outline advantages and limitations of mosaic and germline variant detection as well as the impact of clonal hematopoiesis on liquid biopsy in cancer diagnosis. We also evaluate the potential of cfDNA analysis for the molecular diagnosis of monogenic mosaic disorders. [ABSTRACT FROM AUTHOR]

Nanotechnology is revolutionising different areas from manufacturing to therapeutics in the health field. Carbon nanotubes (CNTs), a promising drug candidate in nanomedicine, have attracted attention due to their excellent and unique mechanical, electronic, and physicochemical properties. This emerging nanomaterial has attracted a wide range of scientific interest in the last decade. Carbon nanotubes have many potential applications in cancer therapy, such as imaging, drug delivery, and combination therapy. Carbon nanotubes can be used as carriers for drug delivery systems by carrying anticancer drugs and enabling targeted release to improve therapeutic efficacy and reduce adverse effects on healthy tissues. In addition, carbon nanotubes can be combined with other therapeutic approaches, such as photothermal and photodynamic therapies, to work synergistically to destroy cancer cells. Carbon nanotubes have great potential as promising nanomaterials in the field of nanomedicine, offering new opportunities and properties for future cancer treatments. In this paper, the main focus is on the application of carbon nanotubes in cancer diagnostics, targeted therapies, and toxicity evaluation of carbon nanotubes at the biological level to ensure the safety and real-life and clinical applications of carbon nanotubes.

Breast cancer is one of the most commonly diagnosed cancer types worldwide. Regarding molecular characteristics and classification, it is a heterogeneous disease, which makes it more challenging to diagnose. As is commonly known, early detection plays a pivotal role in decreasing mortality and providing a better prognosis for all patients. Different treatment strategies can be adjusted based on tumor progression and molecular characteristics, including personalized therapies. However, dealing with resistance to drugs and recurrence is a challenge. The therapeutic options are limited and can still lead to poor clinical outcomes. This review aims to shed light on the current perspective on the role of miRNAs in breast cancer diagnostics, characteristics, and prognosis. We discuss the potential role of selected non-coding RNAs most commonly associated with breast cancer. These include miR-21, miR-106a, miR-155, miR-141, let-7c, miR-335, miR-126, miR-199a, miR-101, and miR-9, which are perceived as potential biomarkers in breast cancer prognosis, diagnostics, and treatment response monitoring. As miRNAs differ in expression levels in different types of cancer, they may provide novel cancer therapy strategies. However, some limitations regarding dynamic alterations, tissue-specific profiles, and detection methods must also be raised.

Recent evidence has shown that the human microbiome is associated with various diseases, including cancer. The salivary microbiome, fecal microbiome, and circulating microbial DNA in blood plasma have all been used experimentally as diagnostic biomarkers for many types of cancer. The microbiomes present within local tissue, other regions, and tumors themselves have been shown to promote and restrict the development and progression of cancer, most often by affecting cancer cells or the host immune system. These microbes have also been shown to impact the efficacy of various cancer therapies, including radiation, chemotherapy, and immunotherapy. Here, we review the research advances focused on how microbes impact these different facets and why they are important to the clinical care of cancer. It is only by better understanding the roles these microbes play in the diagnosis, development, progression, and treatment of cancer, that we will be able to catch and treat cancer early.

Simple Summary: This review aims to highlight the usage of circulating tumour DNA and circulating tumour cells in various manners for the care of cancer patients. The different technologies that are currently employed using these biomarkers are mentioned and contrasted with another whilst also discussing their limitations such as affordability and scalability. The review also aims to bring light to newer emerging technologies in the space of liquid biopsy that have yet to be approved by a regulatory board but have been developed with the notion of affordability and scalability in mind. These factors of technology are found to be important in order to provide cutting edge diagnostic and monitoring regimes as they can lead to personalised treatments and patient stratification for all. 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. [ABSTRACT FROM AUTHOR]

In the last decade, terahertz (THz) technologies have been introduced to the detection, identification, and quantification of biomolecules in various biological samples. This review focuses on substances that represent important biomarkers in the urine associated with various cancers and their treatments. From a diagnostic point of view, urine liquid biopsy is particularly important because it allows the non-invasive and rapid collection of large volumes of samples. In this review, the THz spectral responses of substances considered metabolic biomarkers in urine and obtained in previous studies are collected. In addition, the findings from the relatively small number of prior studies that have already been carried out on urine samples are summarised. In this context, we also present the different THz methods used for urine analysis. Finally, a brief discussion is given, presenting perspectives for future research in this field, interpreted based on the results of previous studies. This work provides important information on the further application of THz techniques in biomedicine for detecting and monitoring urinary biomarkers for various diseases, including cancer. [ABSTRACT FROM AUTHOR]

With the growing number of cancer cases, new tools are required to obtain extensive molecular profiles of patients to help identify the disease. Early diagnosis of cancer is based on the analysis of relevant biomarkers, which can be used to monitor the population in order to identify the disease until it can be determined using standard methods and is not clinically manifest. Heat shock proteins, which act as molecular chaperones, are among the potential markers of cancer. Changes in heat shock protein expression can serve as an important diagnostic marker of the cell's response to damage. This paper presents a brief overview of the prevalence of oncological diseases in the world, the need for the development of early oncological diagnostics, as well as the prospects for the use of heat shock proteins in making an oncological diagnosis. [ABSTRACT FROM AUTHOR]

The Danish head and neck cancer fast-track program is a national standardized pathway aiming to reduce waiting time and improve survival for patients suspected of cancer in the head and neck (HNC). Until now, the frequency of missed cancer in the fast-track program has not been addressed. A missed cancer leads to treatment delay and may cause disease progression and worsening of prognosis. The study objective was to estimate the frequency of patients with missed cancers in the Danish HNC fast-track program and to evaluate the accuracy of the program. Patients who were rejected from the HNC fast-track program because cancer was not found between 1 July 2012 and 31 December 2018 at Odense University Hospital, Denmark were included and followed for three years. Patients were categorized into groups depending on the diagnostic evaluation. Group 1 included patients evaluated with standard clinical work-up without imaging and biopsy. Group 2 included patients evaluated with imaging and/or biopsy in addition to the standard clinical work-up. The local cancer database and electronic patient records were reviewed to determine if a missed cancer had occurred within the follow-up period. A total of 8345 HNC fast-track courses were initiated during the study period. 1499 were patients suspected of recurrent cancer and were excluded leaving 6846 patients to be assessed for eligibility. Of these, 3752 patients were rejected because cancer was not found. Ten patients were subsequently diagnosed with cancer within the follow-up period resulting in an overall frequency of 0.15%. For group 1 and 2, the frequency was 0.04% and 0.10%, respectively. The sensitivity of the fast-track program was 99.67% and the negative predictive value was 99.73%. The frequency of missed cancer in a tertiary HNC center following the Danish fast track program is low. [ABSTRACT FROM AUTHOR]

Nano- and microemulsions are colloidal systems that are widely used in various fields of biomedicine, including wound and burn healing, cosmetology, the development of antibacterial and antiviral drugs, oncology, etc. The stability of these systems is governed by the balance of molecular interactions between nanodomains. Microemulsions as a colloidal form play a special important role in stability. The microemulsion is the thermodynamically stable phase from oil, water, surfactant and co-surfactant which forms the surface of drops with very small surface energy. The last phenomena determines the shortage time of all fluid dispersions including nanoemulsions and emulgels. This review examines the theory and main methods of obtaining nano- and microemulsions, particularly focusing on the structure of microemulsions and methods for emulsion analysis. Additionally, we have analyzed the main preclinical and clinical studies in the field of wound healing and the use of emulsions in cancer therapy, emphasizing the prospects for further developments in this area. [ABSTRACT FROM AUTHOR]

There remains tremendous interest in developing liquid biopsy assays for detection of cancer‐specific alterations, such as mutations and DNA methylation, in cell‐free DNA (cfDNA) obtained through noninvasive blood draws. However, liquid biopsy analysis is often challenging due to exceedingly low fractions of circulating tumor DNA (ctDNA), necessitating the use of extended tumor biomarker panels. While multiplexed PCR strategies provide advantages such as higher throughput, their implementation is often hindered by challenges such as primer‐dimers and PCR competition. Alternatively, digital PCR (dPCR) approaches generally offer superior performance, but with constrained multiplexing capability. This paper describes development and validation of the first multiplex digital methylation‐specific PCR (mdMSP) platform for simultaneous analysis of four methylation biomarkers for liquid‐biopsy‐based detection of non‐small cell lung cancer (NSCLC). mdMSP employs a microfluidic device containing four independent, but identical modules, housing a total of 40 160 nanowells. Analytical validation of the mdMSP platform demonstrates multiplex detection at analytical specificities as low as 0.0005%. The clinical utility of mdMSP is also demonstrated in a cohort of 72 clinical samples of low‐volume liquid biopsy specimens from patients with computed tomography (CT)‐scan indeterminant pulmonary nodules, exhibiting superior clinical performance when compared to traditional MSP assays for noninvasive detection of early‐stage NSCLC. [ABSTRACT FROM AUTHOR]

Skin cancer is one of the most commonly diffused cancers in the world and its incidence rates have constantly increased in recent years. At the current state of the art, there is a lack of objective, quick and non-invasive methods for diagnosing this condition; this, combined with hospital crowding, may lead to late diagnosis. Starting from these considerations, this paper addresses the implementation of a microwave reflectometry based-system that can be used as a non-invasive method for the in-vivo diagnosis and early detection of biological abnormalities, such as skin cancer. This system relies on the dielectric contrasts existing between normal and anomalous skin tissues at microwave frequencies (in a frequency range up to 3 GHz). In particular, a truncated open-ended coaxial probe was designed, manufactured and tested to sense (in combination with a miniaturized Vector Network Analyzer) the variations of skin dielectric properties in a group of volunteer patients. The specific data processing demonstrated the suitability of the system for discriminating malignant and benign lesions from healthy skin, ensuring simultaneously effectiveness, low cost, compactness, comfortability, and high sensitivity.

In this article the review of genetic analysis of circulating tumor DNA as one of the most intensively studied diagnostic methods in oncology is present. Due to its high sensitivity and specifi city and the ability to be used in solving diff erent clinical problems such as diagnosing and then monitoring of tumor burden, evaluating the probability of disease relapse and also correction of therapy used in case of detecting tumor’s resistance to it, this method is one of the most perspective to be implemented into public healthcare. Nevertheless, its high cost, a little quantity of clinical trials and necessity of standardization cannot aff ord this method to be used in clinic now.

Hypermethylation of tumor-suppressor genes and global hypomethylation, which is related to methylation level at the retroelement, have been recognized as features of the cancer genome. In this study, we developed a hybridization-based CpG methylation level detection method using methyl-CpG-binding domain–fused firefly luciferase (MBD-Fluc). In this method, methylated probe oligonucleotides were used to capture target oligonucleotides. Fully methylated and hemimethylated double-stranded DNA (dsDNA) was formed by hybridization of the methylated captured oligonucleotides with methylated or unmethylated target oligonucleotides, respectively. MBD-Fluc specifically binds to fully methylated dsDNA but not to hemimethylated dsDNA; therefore, methylated target oligonucleotides can be detected by measuring the luciferase activity of the bound MBD-Fluc. Using the corresponding methylated probe oligonucleotides, the CpG methylation levels of SEPT9, BRCA1, and long interspersed nuclear element-1 (LINE-1) oligonucleotides were quantified. Moreover, we demonstrated that the emission detection signal was not affected by the methylation state of the overhang region of the target oligonucleotide, which was not hybridized to the probe oligonucleotide, indicating that methylated CpG of the target region could be accurately detected. Unmethylated-CpG-binding domain–fused luciferases and 5-hydroxymethyl-CpG-binding domain–fused luciferases have been constructed, suggesting that other modified bases can be detected by the same platform. [ABSTRACT FROM AUTHOR]

Liquid biopsy, a powerful non-invasive test, has been widely used in cancer diagnosis and treatment. Platelets, the second most abundant cells in peripheral blood, are becoming one of the richest sources of liquid biopsy with the capacity to systematically and locally respond to the presence of cancer and absorb and store circulating proteins and different types of nucleic acids, thus called "tumoreducated platelets (TEPs)". The contents of TEPs are significantly and specifically altered, empowering them with the potential as cancer biomarkers. The current review focuses on the alternation of TEP content, including coding and noncoding RNA and proteins, and their role in cancer diagnostics. [ABSTRACT FROM AUTHOR]

Exosomal microRNAs (miRNAs) have considerable potential as pivotal biomarkers to monitor cancer development, dis‐ease progression, treatment effects and prognosis. Here, we report an efficient target recycling amplification process (TRAP) for the digital detection of miRNAs using photonic resonator absorption microscopy. We achieve multiplex digital detection with sub‐attomolar sensitivity in 20 minutes, robust selectivity for single nucleotide variants, and a broad dynamic range from 1 aM to 1 pM. Compared with traditional qRT‐PCR, TRAP showed similar accuracy in profiling exosomal miRNAs derived from cancer cells, but also exhibited at least 31‐fold and 61‐fold enhancement in the limits of miRNA‐375 and miRNA‐21 detection, respectively. The TRAP approach is ideal for exosomal or circulating miRNA biomarker quantification, where the miRNAs are present in low concentrations or sample volume, with potentials for frequent, low‐cost, and minimally invasive point‐of‐care testing. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs)-based theranostic nanomedicine has demonstrated enormous potential for cancer diagnosis and therapy due to its versatile physiochemical properties, such as structural and morphological properties, specific cellular targeting, tunable pore and particle size, higher surface area, drug-loading capacity, biodegradability and biocompatibility. Notably, MOFs, loaded with diagnostic and therapeutic agents and functionalized with targeting moiety, are capable of catering to both targeted imaging and therapy simultaneously. Additionally, MOFs have demonstrated excellent potential in drug delivery, drug targeting, bioimaging, biosensing, biocatalysis and so on. However, major challenges associated with MOFs include improving their stability, biocompatibility and therapeutic efficacy and reducing the toxicity. This special report sheds light on the historical development, synthesis, recent advancements, toxicity and challenges associated with MOFs-based cancer nanotheranostics for their clinical translation. [ABSTRACT FROM AUTHOR]

Cancer is a genetic disease induced by mutations in DNA, in particular point mutations in important driver genes that lead to protein malfunctioning and ultimately to tumorigenesis. Screening for the most common DNA point mutations, especially in such genes as TP53, BRCA1 and BRCA2, EGFR, KRAS, or BRAF, is crucial to determine predisposition risk for cancer or to predict response to therapy. In this review, we briefly depict how these genes are involved in cancer, followed by a description of the most common techniques routinely applied for their analysis, including high-throughput next-generation sequencing technology and less expensive low-throughput options, such as real-time PCR, restriction fragment length polymorphism, or high resolution melting analysis. We then introduce benefits of electrochemical biosensors as interesting alternatives to the standard methods in terms of cost, speed, and simplicity. We describe most common strategies involved in electrochemical biosensing of point mutations, relying mostly on PCR or isothermal amplification techniques, and critically discuss major challenges and obstacles that, until now, prevented their more widespread application in clinical settings. [ABSTRACT FROM AUTHOR]