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Computer-assisted diagnosis (CAD) plays a key role in cancer diagnosis or screening. Whereas, current CAD performs poorly on whole slide image (WSI) analysis, and thus fails to generalize well. This research aims to develop an automatic classification system to distinguish between different types of carcinomas. Obtaining rich deep features in multi-class classification while achieving high accuracy is still a challenging problem. The detection and classification of cancerous cells in WSI are quite challenging due to the misclassification of normal lumps and cancerous cells. This is due to cluttering, occlusion, and irregular cell distribution. Researchers in the past mostly obtained the hand-crafted features while neglecting the above-mentioned challenges which led to a reduction of the classification accuracy. To mitigate this problem we proposed an efficient dual attention-based network (CytoNet). The proposed network is composed of two main modules (i) Efficient-Net and (ii) Dual Attention Module (DAM). Efficient-Net is capable of obtaining higher accuracy and enhancing efficiency as compared to existing Convolutional Neural Networks (CNNs). It is also useful to obtain the most generic features as it has been trained on ImageNet. Whereas DAM is very robust in obtaining attention and targeted features while negating the background. In this way, the combination of an efficient and attention module is useful to obtain the robust, and intrinsic features to obtain comparable performance. Further, we evaluated the proposed network on two well-known datasets (i) Our generated thyroid dataset (ii) Mendeley Cervical dataset (Hussain in Data Brief, 2019) with enhanced performance compared to their counterparts. CytoNet demonstrated a 99% accuracy rate on the thyroid dataset in comparison to its counterpart. The precision, recall, and F1-score values achieved on the Mendeley Cervical dataset are 0.992, 0.985, and 0.977, respectively. The code implementation is available on GitHub. https://github.com/naveedilyas/CytoNet-An-Efficient-Dual-Attention-based-Automatic-Prediction-of-Cancer-Sub-types-in-Cytol., (© 2024. The Author(s).)

Tertiary lymphoid structures (TLSs) are ectopic lymphocyte aggregates formed in non-lymphoid tissues, including cancers, and are loci for the generation of in situ anti-tumor immune responses, which play a crucial role in cancer control. The state of TLS presence in cancer and its composition can significantly impact the treatment response and prognosis of patients. TLSs have the potential to serve as predictive and prognostic biomarkers for cancer. However, the mechanisms underlying TLS formation in cancer and how the essential components of TLSs affect cancer are not fully understood. In this review, we summarized TLS formation in cancer, the value of the TLS in different states of existence, and its key constituents for cancer prediction and prognosis. Finally, we discussed the impact of cancer treatment on TLSs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Cancer detection poses a significant challenge for researchers and clinical experts due to its status as the leading cause of global mortality. Early detection is crucial, but traditional cancer detection methods often rely on invasive procedures and time-consuming analyses, creating a demand for more efficient and accurate solutions. This paper addresses these challenges by utilizing automated cancer detection through AI-based techniques, specifically focusing on deep learning models. Convolutional Neural Networks (CNNs), including DenseNet121, DenseNet201, Xception, InceptionV3, MobileNetV2, NASNetLarge, NASNetMobile, InceptionResNetV2, VGG19, and ResNet152V2, are evaluated on image datasets for seven types of cancer: brain, oral, breast, kidney, Acute Lymphocytic Leukemia, lung and colon, and cervical cancer. Initially, images undergo segmentation techniques, proceeded by contour feature extraction where parameters such as perimeter, area, and epsilon are computed. The models are rigorously evaluated, with DenseNet121 achieving the highest validation accuracy as 99.94%, 0.0017 as loss, and the lowest Root Mean Square Error (RMSE) values as 0.036056 for training and 0.045826 for validation. These results revealed the capability of AI-based techniques in improving cancer detection accuracy, with DenseNet121 emerging as the most effective model in this study., (© 2024. The Author(s).)

Malignant hypercalcemia is the main metabolic complication of cancer. Clinical presentation varies from asymptomatic to a medical emergency. The main causes include parathyroid hormone-related protein production and bone metastases, while hypervitaminosis D and hyperparathyroidism are rarer causes. Diagnosis is based on the demonstration of elevated serum calcium and low PTH in the context of known or suspected cancer. Treatment is aimed at correcting hypovolemia by hydration, reducing bone resorption, and treating the underlying cancer. The aims are to improve patients' quality of life, minimize delays in oncological management and reduce mortality associated with this condition., Competing Interests: Les auteurs n’ont déclaré aucun conflit d’intérêts en relation avec cet article.

Objective: Analyze the cancer screening status of the cancer screening program in urban areas in Shaanxi province in 2019-2020. Methods: The early diagnosis and early treatment project for urban cancers carried out high-risk population screening for 5 types of high-incidence malignant tumors (breast cancer, lung cancer, upper gastrointestinal cancer, liver cancer, and colorectal cancer) in urban areas. Three prefecture-level cities in Shaanxi province with a population of over 1 million (Xi'an, Baoji, and Shangluo) were selected, and 4 communities with a relatively good working foundation were selected in each city. The general population aged 45-74 years was surveyed on the principles of informed consent and voluntariness, and high-risk groups identified through the questionnaire were further subjected to free endoscopy, ultrasound, CT, and other clinical screenings. The high-risk rates, screening compliance rates, and positive detection rates of the above 5 types of malignant tumors were analyzed. Results: A total of 19 632 people completed the survey effectively, with the proportion of male participants (40.0%) lower than that of females (60.0%). A total of 10 102 high-risk groups were identified, with an initial screening high-risk rate of 51.5%, and the high-risk rates for the 5 types of cancers were 24.1% for breast cancer, 28.6% for lung cancer, 9.1% for upper gastrointestinal cancer, 4.0% for liver cancer, and 20.0% for colorectal cancer. Among the 14 960 person-time initially assessed as high-risk, 5 129 person-time received clinical screening, with a screening compliance rate of 34.3%. The number of people receiving clinical screening and the screening compliance rates for the 5 types of cancers were 1 192 (41.9%) for breast cancer, 2 081 (37.1%) for lung cancer, 574 (32.0%) for upper gastrointestinal cancer, 404 (51.3%) for liver cancer, and 878 (22.3%) for colorectal cancer, with positive detection numbers and rates of 179 (15.0%) for breast, 289 (13.9%) for lung, 9 (1.6%) for upper gastrointestinal, 14 (3.5%) for suspected liver, and 67 (7.6%) for colorectal, respectively. Conclusion: The cancer screening status of the cancer screening program in urban areas in Shaanxi province is beneficial for the detection of precancerous lesions and early cancer patients, and improving the early diagnosis and treatment rate of patients, but the public participation rate is not high, and the project management model and technical plan need to be further improved.

Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structures have posed challenges for the detection of EV glycans. In this study, we provide a streamlined method integrated, me mbrane- s pecific s eparation with lectin-induced ag gr e gation strategy (MESSAGE), for multiplexed profiling of EV glycans. By leveraging a rationally designed lectin-induced aggregation strategy, the expression of EV glycans is converted to size-based signals. With the assistance learning machine algorithms, the MESSAGE strategy with high sensitivity, specificity, and simplicity can be used for early cancer diagnosis and classification, as well as monitoring cancer metastasis via 20 μL plasma sample within 2 h. Furthermore, our platform holds promise for advancing the field of EV-based liquid biopsy for clinical applications, opening new possibilities for the profiling of EV glycan signatures in various disease states.

Nanoflowers, an innovative class of nanoparticles with a distinctive flower-like structure, have garnered significant interest for their straightforward synthesis, remarkable stability, and heightened efficiency. Nanoflowers demonstrate versatile applications, serving as highly sensitive biosensors for rapidly and accurately detecting conditions such as diabetes, Parkinson's, Alzheimer's, and foodborne infections. Nanoflowers, with their intricate structure, show significant potential for targeted drug delivery and site-specific action, while also exhibiting versatility in applications such as enzyme purification, water purification from dyes and heavy metals, and gas sensing through materials like nickel oxide. This review also addresses the structural characteristics, surface modification, and operational mechanisms of nanoflowers. The nanoflowers play a crucial role in preventing premature drug leakage from nanocarriers. Additionally, the nanoflowers contribute to averting systemic toxicity and suboptimal therapy efficiency caused by hypoxia in the tumor microenvironment during chemotherapy and photodynamic therapy. This review entails the role of nanoflowers in cancer diagnosis and treatment. In the imminent future, the nanoflowers system is poised to revolutionize as a smart material, leveraging its exceptional surface-to-volume ratio to significantly augment adsorption efficiency across its intricate petals. This review delves into the merits and drawbacks of nanoflowers, exploring synthesis techniques, types, and their evolving applications in cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Accurate diagnosis of highly aggressive and deadly tumors is essential for effective treatment and improved patient outcomes, and microRNAs (miRNAs) have emerged as crucial biomarkers for their roles in tumor initiation, progression, and metastasis. Herein, we present an on-site visualization colorimetric assay for tumor-associated miRNAs using ruthenium nanoparticle decorated titanium dioxide nanoribbon (Ru@TiO 2 ) as a peroxidase-like (POD) nanozyme. Remarkably, the Ru@TiO 2 nanozyme can catalyze the oxidation of chromogenic substrates through its POD-like activity, which is effectively inhibited by pyrophosphate generated during the rolling circle amplification process, thereby enabling miRNA detection through a visible colorimetric readout. This approach provides a highly sensitive and specificity assay for miRNAs in diluted human serum with a detection limit of 100 pM. It shows great potential for clinical diagnostics and biological research, offering a promising tool for early cancer diagnosis and molecular diagnostics.

In the last two decades, next-generation sequencing (NGS) has facilitated enormous progress in cancer medicine, in both diagnosis and treatment. However, the usefulness of NGS in older cancer patients is unclear. To determine the role of NGS in older cancer patients, we retrospectively assessed demographic, clinicopathologic, and disease-specific data from 100 randomly selected cancer patients (any subtype/stage) who underwent NGS testing in 2020 at our institution and compared the treatment outcomes (progression-free survival [PFS] and overall survival [OS]) in the younger and older patient cohorts (A [n = 34] and B [n = 66]: age < 70 and ≥70 years, respectively). Overall, 27% had targetable mutations, and 8% received NGS-determined targeted therapy (45% and 19% of patients with a targetable mutation in cohorts A and B, respectively; p = 0.2), of whom 38% (3% of the whole cohort) benefited from the therapy (PFS > 6 months). The median OS (from diagnosis) was 192 and 197 weeks in cohorts A and B, respectively ( p = 0.08). This pilot study revealed no significant age-stratified difference in the diagnostic approach and treatment strategy. A small, but relevant, proportion of the cohort (3%) benefited from NGS-determined treatment. Nevertheless, older cancer patients with targetable mutations less frequently received targetable therapies.

Introduction: Faced to the growing development of collecting systematic molecular analyses in relapsed pediatric cancers to transform their targeted matched therapies, this study aimed to assess the clinical and therapeutic indications of systematic diagnostic genomic explorations performed in pediatric solid cancers to determine which type of screening and if it afford at relapse time an accurate targeted strategy., Methods: A total of 280 patients less than 22 years, referred at the University Hospitals of Strasbourg for a newly diagnosed solid tumor from January 2015 to December 2021, were prospectively genomically investigated since diagnosis. Using 7 different molecular tests going from single-gene methods (IHC, FISH, RT-PCR, Sanger sequencing, droplet digital PCR) to largescale analyses (Next-Generation sequencing, RNAsequencing and FoundationOne®CDx), we explored retrospectively the molecular findings in those pediatric solid tumors (except hematolymphoid cancers) to improve diagnosis, prognosis assessment and relapse therapeutics., Results: One hundred and ninety-eight patients (71%) underwent molecular biology (MB) at diagnosis. Thirty-eight different histologies were grouped into cerebral tumors (30%), sarcomas (26%, bone and soft tissues), various blastomas (27%), and other entities (17%). Over a median 40-month follow-up, the overall survival rate of patients was 85% and the relapse rate 28%. Of the 326 analyses carried out, 245 abnormalities (single nucleotide variations: 50%, fusions: 25%, copy number alteration: 20%) concerning 70 oncogenes were highlighted. The overall clinical impact rate was 84%. Broad-spectrum analyses had a higher therapeutic impact (57%) than the targeted analyses (28%). 75% of broad-spectrum tests found an actionable variant conducting 23% of patients to receive rapidly a matched targeted therapy since first relapse., Conclusion: Our experience highlighted the clinical utility of molecular profiling of solid tumors as soon as at diagnosis in children to expect improving access to innovative agents at relapse., (© 2024. The Author(s).)

The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models., Competing Interests: Declaration of interests Y.A., J.J., and K.S. have filed patent applications based on the method developed in this work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aims: The international system for reporting serous fluid cytopathology (ISRSFC) set forth a five-tiered reporting system with comprehensive validation on pleural and peritoneal fluid cytology. An algorithmic approach for cytomorphological assessment and immunocytochemistry was also described in ISRSFC. Limited data on pericardial fluid are supportive but would benefit from further investigation., Methods: Consecutive pericardial fluid cytology over a 4-year period was reviewed by multiple board-certified pathologists according to the ISRSFC. Cytomorphology and immunocytochemistry were assessed sequentially, with respective diagnostic performances computed and compared. Literature review was performed., Results: In total 358 specimens, including 53 with immunocytochemistry available, were reviewed. There were 137 benign and 221 malignant (MAL) cases. The risks of malignancy were 23.5% non-diagnostic (ND), 29.2% negative for malignancy (NFM), 56.0% atypia of undetermined significance (AUS), 82.6% suspicious for malignancy (SFM) and 99.2% (MAL) for cytomorphological assessment, improving to 23.5% (ND), 29.1% (NFM), 56.8% (AUS), 78.9% (SFM) and 99.3% (MAL) incorporating immunocytochemistry. Ten cases (2.8%) received a change in diagnosis after review of immunocytochemistry. All revisions of diagnostic category were appropriate upgrades/downgrades referenced against clinical information. Cytomorphological typing was accurate for adenocarcinoma (n=81/83, 97.6%), while other carcinomas and lymphomas required immunocytochemistry. Certain subcategories within AUS and SFM pertaining to bland indeterminate epithelial cells or mucinous material were not seen for pericardial fluid., Conclusions: The ISRSFC shows robust diagnostic performance for pericardial fluid cytology. For pericardial effusion, disease composition and applicable cytological subcategories differ from its peritoneal and pleural counterparts. Incorporating immunocytochemistry by an algorithmic approach improves diagnostic accuracy. Cytomorphology is accurate for identifying adenocarcinomas, but further typing necessitates immunocytochemistry is necessary., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Exosomes, which are extracellular vesicles with a diameter ranging from 40 to 160 nm, are abundantly present in various body fluids. Exosomal microRNA (ex-miR), due to its exceptional sensitivity and specificity, has garnered significant attention. Notably, ex-miR is consistently detected in almost all bodily fluids, highlighting its potential as a reliable biomarker. This attribute of ex-miR has piqued considerable interest in its application as a diagnostic tool for the early detection, continuous monitoring, and prognosis evaluation of cancer. Given the critical role of exosomes and their cargo in cancer biology, this review explores the intricate processes of exosome biogenesis and uptake, their multifaceted roles in cancer development and progression, and the potential of ex-miRs as biomarkers for tumor diagnosis and prognosis., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Optical imaging is a powerful tool for early disease detection and effective treatment planning, but its accuracy is often compromised by the uptake of imaging materials by the mononuclear phagocyte system (MPS). Herein, we leverage multivalent host-guest interactions between cyanine dyes and β-cyclodextrin polymers to develop supramolecular probes with enhanced stability, optical, and transport profiles for accurate in vivo imaging. These multivalent interactions not only ensure the stability of the probes but also enhance fluorescence efficiency by minimizing nonradiative decay. Our self-assembly approach effectively modulates probe size and surface properties, enabling evasion of MPS clearance and promoting prolonged bloodstream circulation, thereby improving the signal-to-background ratio for imaging. The effectiveness of our design is demonstrated by substantial advancements in the early diagnosis of acute kidney injury and by providing high-contrast imaging and precise surgical navigation across various tumor models. Our strategy not only advances optical imaging materials toward clinical translation but also establishes a versatile platform applicable to multiple imaging modalities.

Introduction: It is essential to increase the rates of early diagnosis in cancer control, and the diagnostic process needs to be improved to achieve this goal. Previous studies showed that in countries where there is a gatekeeping system, there might be a delay in cancer diagnosis. Our aim is to examine the process of cancer diagnosis in a healthcare system without gatekeeping., Method: A quantitative descriptive study has been conducted in various outpatient clinics of Pendik Training and Research Hospital, between 1 February and 31 May 2019, with individuals aged over 18 and diagnosed with cancer in the last six months. The data was collected through a questionnaire filled in by face-to-face interview method. Patient's socio-economic characteristics, their symptoms at the time of the diagnosis and the diagnosis process were questioned., Result: The median diagnostic interval was 30 days (min-max 1-365), and the median patient interval was 60 (1-600) days. Patients pointed out that the diagnostic tests, especially the pathology reporting process, caused the diagnostic interval to be prolonged. Of the patients, 84% ( n 135) stated that they did not consider their symptoms as a sign of serious illness. The patient interval was shortest with symptoms of haematuria and haematochezia and longest with dysuria and change in bladder habit., Discussion: The study examined the diagnosis process in our health system, where patients can apply for health services at any stage. The results showed that there were no superior outcomes to those observed in primary care-led health systems. Patients reported that waiting times for medical tests led to prolongation of the diagnosis time. Cancer awareness of patients should also be increased to shorten patient admission times.

Night sweats are a common symptom. There is a lack of a uniform definition and a diagnostic guideline. In this article we propose a structural analysis for all levels of healthcare. First, we need to distinguish night sweats with or without fever. We will then discuss the main differential diagnoses (infection, malignancies, sleeping disorders and medication-related) and emphasize the role of diagnostic clues. A screening for infections, sleeping disorders and a medication review are a must for every patient. Furthermore we will explain the role of PET-CT and bone marrow examination.

Cancer, which is characterized by high mortality rates, poses a significant threat to global human health. Early diagnosis is of paramount importance in managing cancer, and tumor markers have emerged as crucial indicators for achieving this goal. The advent of precision medicine has further emphasized the need for the effective detection of these markers. However, traditional detection methods are hampered by numerous limitations. In recent years, nanopore technology has emerged as a promising alternative, due to its unique physical and chemical properties, which facilitate rapid, label-free, and amplification-free detection. This Review focuses on the direct detection of tumor markers through nucleic acid analysis and indirect detection mediated by nucleic acids and facilitated by biological nanopores. Furthermore, it also discusses the challenges and prospects of applying biological nanopore sensing technology in early cancer diagnosis, underscoring its potential to revolutionize tumor marker detection.

Non-invasive detection of tumors is of utmost importance to save lives. Nonetheless, identifying tumors through gas analysis is a challenging task. In this work, biosensors with remarkable gas-sensing characteristics were developed using a self-assembly method consisting of peptides and MXene. Based on these biosensors, a mimetic biosensor array (MBA) was fabricated and integrated into a real-time testing platform (RTP). In addition, machine learning (ML) algorithms were introduced to improve the RTP's detection and identification capabilities of exhaled gas signals. The synthesized biosensor, with the ability to specifically bind to targeted gas molecules, demonstrated higher performance than the pristine MXene, with a response up to 150% greater. Besides, the MBA successfully detected 15 odor molecules affiliated with five categories of alcohols, ketones, aldehydes, esters, and acids by pattern recognition algorithms. Furthermore, with the ML assistance, the RTP detected the breath odor samples from volunteers of four categories, including healthy populations, patients of lung cancer, upper digestive tract cancer, and lower digestive tract cancer, with accuracies of 100%, 94.1%, 90%, and 95.2%, respectively. In summary, we have developed a cost-effective and precise model for non-invasive tumor diagnosis. Furthermore, this prototype also offers a versatile solution for diagnosing other diseases like nephropathy, diabetes, etc., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

To enhance the precision and reliability of early disease detection, especially in malignancies, an exhaustive investigation of multi-target biomarkers is essential. In this study, an advanced integrated electrochemical biosensor array that demonstrates exceptional performance was constructed. This biosensor was developed through a controllable porous-size mechanism and in-situ modification of carbon nanotubes (CNTs) to quantify multiplex biomarkers-specifically, C-reaction protein (CRP), carbohydrate antigen 125 (CA125), and carcinoembryonic antigen (CEA)-in human serum plasma. The fabrication process involved creating a highly ordered three-dimensional inverse-opal structure with the CNTs (pCNTs) modifier through microdroplet-based microfluidics, confined spatial self-assembly of nanoparticles, and chemical wet-etching. This innovative approach allowed for direct in-situ modification of nanomaterial onto the surface of electrode array, eliminating secondary transfer and providing exceptional control over structure and stability. The outstanding electrochemical performance was achieved through the synergistic effect of the pCNTs nanomaterial, aptamer, and horseradish peroxidase-labeled (HRP-) antibody. Additionally, the integrated biosensor array platform comprised multiple individually addressable electrode units (n = 11), enabling simultaneous multi-parallel/target testing, thereby ensuring accuracy and high throughput. Crucially, this integrated biosensor array accurately quantified multiplex biomarkers in human serum, yielding results comparable to commercial methods. This integrated technology holds promise for point-of-care testing (POCT) in early disease diagnosis and biological analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Because of their unique electromechanical coupling response, piezoelectric smart biomaterials demonstrated distinctive capability toward effective, efficient, and quick diagnosis and treatment of a wide range of diseases. Such materials have potentiality to be utilized as wireless therapeutic methods with ultrasonic stimulation, which can be used as self-powered biomedical devices. An emerging advancement in the realm of personalized healthcare involves the utilization of piezoelectric biosensors for a range of therapeutic diagnosis such as diverse physiological signals in the human body, viruses, pathogens, and diseases like neurodegenerative ones, cancer, etc. The combination of piezoelectric nanoparticles with ultrasound has been established as a promising approach in sonodynamic therapy and piezocatalytic therapeutics and provides appealing alternatives for noninvasive treatments for cancer, chronic wounds, neurological diseases, etc. Innovations in implantable medical devices (IMDs), such as implantable piezoelectric energy generator (iPEG), offer significant advantages in improving physiological functioning and ability to power a cardiac pacemaker and restore the heart function. This comprehensive review critically evaluates the role of piezoelectricity in disease diagnosis and treatment, highlighting the implication of piezoelectric smart biomaterials for biomedical devices. It also discusses the potential of piezoelectric materials in healthcare monitoring, tissue engineering, and other medical applications while emphasizing future trends and challenges in the field.

The isolation of circulating tumoral DNA (ctDNA) present in the bloodstream brings about the opportunity to detect genomic aberrations from the tumor of origin. However, the low amounts of ctDNA present in liquid biopsy samples makes the development of highly sensitive techniques necessary to detect targetable mutations for the diagnosis, prognosis, and monitoring of cancer patients. Here, we employ standard genomic DNA (gDNA) and eight liquid biopsy samples from different cancer patients to examine the newly described CRISPR-Cas13a-based technology in the detection of the BRAF p.V600E actionable point mutation and appraise its diagnostic capacity with two PCR-based techniques: quantitative Real-Time PCR (qPCR) and droplet digital PCR (ddPCR). Regardless of its lower specificity compared to the qPCR and ddPCR techniques, the CRISPR-Cas13a-guided complex was able to detect inputs as low as 10 pM. Even though the PCR-based techniques have similar target limits of detection (LoDs), only the ddPCR achieved a 0.1% variant allele frequency (VAF) detection with elevated reproducibility, thus standing out as the most powerful and suitable tool for clinical diagnosis purposes. Our results also demonstrate how the CRISPR-Cas13a can detect low amounts of the target of interest, but its base-pair specificity failed in the detection of actionable point mutations at a low VAF; therefore, the ddPCR is still the most powerful and suitable technique for these purposes.

New point-of-care tests (POCTs), which are especially useful in low-resource settings, are needed to expand screening capacity for diseases that cause significant mortality: tuberculosis, multiple cancers, and emerging infectious diseases. Recently, clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostic (CRISPR-Dx) assays have emerged as powerful and versatile alternatives to traditional nucleic acid tests, revealing a strong potential to meet this need for new POCTs. In this review, we discuss CRISPR-Dx assay techniques that have been or could be applied to develop POCTs, including techniques for sample processing, target amplification, multiplex assay design, and signal readout. This review also describes current and potential applications for POCTs in disease diagnosis and includes future opportunities and challenges for such tests. These tests need to advance beyond initial assay development efforts to broadly meet criteria for use in low-resource settings.

Liquid biopsy is a minimally invasive method that uses biofluid samples instead of tissue samples for cancer diagnosis. Exosomes are small extracellular vesicles secreted by donor cells and act as mediators of intercellular communication in human health and disease. Due to their important roles, exosomes have been considered as promising biomarkers for liquid biopsy. However, traditional methods for exosome isolation and cargo detection methods are time-consuming and inefficient, limiting their practical application. In the past decades, many new strategies, such as microfluidic chips, nanowire arrays and electrochemical biosensors, have been proposed to achieve rapid, accurate and high-throughput detection and analysis of exosomes. In this review, we discussed about the new advance in exosome-based liquid biopsy technology, including isolation, enrichment, cargo detection and analysis approaches. The comparison of currently available methods is also included. Finally, we summarized the advantages and limitations of the present strategies and further gave a perspective to their future translational use., (© 2024. The Author(s).)

Nanozymes are a group of nanomaterials that garnered significant attention due to their enzyme-mimicking properties and their catalytic activities comparable to those of natural enzymes. The ability of nanozymes to emulate crucial biological processes which can conquer the drawbacks of natural enzymes, such as their restricted thermostability as well as substrate range. Auriferous (gold) nanozymes possess remarkable enzyme-like properties, such as reductase, peroxidase, superoxide dismutase, oxidase, and catalase. This characteristic makes them a strong competitor for possible applications in the fields of biomedicine as well as biochemical analysis, especially when compared to natural enzymes, along with their simple manufacturing, adaptable features, biocompatibility, and affordability. This review evaluates the factors that affect the catalytic activity of auriferous nanozymes. We offer a thorough investigation of their diagnostic applications, including detecting cancer, microorganisms, glucose, cysteine, and uric acid. Furthermore, we delve into the applications of gold nanozyme in therapeutics including chemodynamic therapy, radiotherapy, and photothermal therapy. In contrast to previous review, our review highlights various advantages of auriferous nanozymes in diagnostics and therapies and provides novel insights into the diverse applications of gold nanozymes encompassing current research studies., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Accurate tumor detection is crucial for the early discovery and subsequent treatment of small neoplastic foci. Molecular imaging, which combines non-invasiveness, high specificity, and strong sensitivity, excels in diagnosing early tumors and stands out among tumor diagnosis methods. Here, we introduced a dual-modal imaging probe capable of actively targeting tumor cells, suitable for both near-infrared (NIR) fluorescence and magnetic resonance imaging (MRI). Dendritic mesoporous silica was used as a carrier for the probe, encapsulating Ag 2 S quantum dots (QDs) for NIR fluorescence imaging. Additionally, the probe conjugated the MRI contrast agent Gd-DOTA and cetuximab, which targeted EGFR on the tumor cell membrane surface, to achieve dual-modal imaging in the tumor area. This strategy provided a methodology for the accurate diagnosis of early-stage tumor lesions and guides precise lesion resection during surgery, offering significant potential for clinical application.

Background: In primary care, health professionals use blood tests to investigate nonspecific presentations to inform referral decisions. Reference ranges for the commonly used blood tests in western countries were developed in predominately White populations, and so may perform differently when applied to non-White populations. Knowledge of ethnic variation in blood test results in healthy/general populations could help address ethnic inequalities in cancer referral for diagnosis and outcomes., Objective: This systematic review explored evidence of ethnic differences in the distribution of selected blood test results among healthy/general populations to inform future research aimed at addressing inequalities in cancer diagnosis., Methods: We searched PubMed and EMBASE to identify studies reporting measures of haemoglobin, MCV, calcium, albumin, platelet count, and CRP in nondiseased adults from at least 2 different ethnic groups. Two reviewers independently screened studies, completed data extraction and quality assessment using an adapted Newcastle-Ottawa scale. Participants were stratified into White, Black, Asian, Mixed, and Other groups. Data were synthesised narratively and meta-analyses were conducted where possible., Results: A total of 47 papers were included. Black men and women have lower average values of haemoglobin, MCV, and albumin, and higher average values of CRP relative to their White counterparts. Additionally, Black men have lower average haemoglobin than Asian men, whereas Asian women have lower average CRP values when compared with White women., Conclusions: There is evidence of ethnic differences in average values of haemoglobin, MCV, CRP, and albumin in healthy/general populations. Further research is needed to explore the reasons for these differences. Systematic review registration: CRD42021274580., (© The Author(s) 2024. Published by Oxford University Press.)

The autofluorescence of erythrocyte porphyrins has emerged as a potential method for multi-cancer early detection (MCED). With this method's dependence on research-grade spectrofluorometers, significant improvements in instrumentation are necessary to translate its potential into clinical practice, as with any promising medical technology. To fill this gap, in this paper, we present an automated ratio porphyrin analyzer for cancer screening (ARPA-CS), a low-cost, portable, and automated instrument for MCED via the ratio fluorometry of porphyrins. The ARPA-CS aims to facilitate cancer screening in an inexpensive, rapid, non-invasive, and reasonably accurate manner for use in primary clinics or at point of care. To accomplish this, the ARPA-CS uses an ultraviolet-excited optical apparatus for ratio fluorometry that features two photodetectors for detection at 590 and 630 nm. Additionally, it incorporates a synchronous detector for the precision measurement of signals based on the Walsh-ordered Walsh-Hadamard transform (WHT) w and circular shift. To estimate its single-photodetector capability, we established a linear calibration curve for the ARBA-CS exceeding four orders of magnitude with a linearity of up to 0.992 and a low detection limit of 0.296 µg/mL for riboflavin. The ARPA-CS also exhibited excellent repeatability (0.21%) and stability (0.60%). Moreover, the ratio fluorometry of three serially diluted standard solutions of riboflavin yielded a ratio of 0.4, which agrees with that expected based on the known emission spectra of riboflavin. Additionally, the ratio fluorometry of the porphyrin solution yielded a ratio of 49.82, which was ascribed to the predominant concentration of protoporphyrin IX in the brown eggshells, as confirmed in several studies. This study validates this instrument for the ratio fluorometry of porphyrins as a biomarker for MCED. Nevertheless, large and well-designed clinical trials are necessary to further elaborate more on this matter.

Background: Cancer is a significant public health problem, causing dozens of millions of deaths annually. New cancer screening programs are urgently needed for early cancer detection, as this approach can improve treatment outcomes and increase patient survival. The search for affordable, noninvasive, and highly accurate cancer detection methods revealed a valuable source of tumor-derived metabolites in the human metabolome through the exploration of volatile organic compounds (VOCs) in noninvasive biofluids., Aim of Review: This review discusses volatilomics-based approaches for cancer detection using noninvasive biomatrices (breath, saliva, skin secretions, urine, feces, and earwax). We presented the historical background, the latest approaches, and the required stages for clinical validation of volatilomics-based methods, which are still lacking in terms of making noninvasive methods available and widespread to the population. Furthermore, insights into the usefulness and challenges of volatilomics in clinical implementation steps for each biofluid are highlighted., Key Scientific Concepts of Review: We outline the methodologies for using noninvasive biomatrices with up-and-coming clinical applications in cancer diagnostics. Several challenges and advantages associated with the use of each biomatrix are discussed, aiming at encouraging the scientific community to strengthen efforts toward the necessary steps to speed up the clinical translation of volatile-based cancer detection methods, as well as discussing in favor of (i) hybrid applications (i.e., using more than one biomatrix) to describe metabolite modulations that can be "cancer volatile fingerprints" and (ii) in multi-omics approaches integrating genomics, transcriptomics, and proteomics into the volatilomic data, which might be a breakthrough for diagnostic purposes, onco-pathway assessment, and biomarker validations., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Given the high degree of variability and complexity of cancer, precise monitoring and logical analysis of different nucleic acid markers are crucial for improving diagnostic precision and patient survival rates. However, existing molecular diagnostic methods normally suffer from high cost, cumbersome procedures, dependence on specialized equipment and the requirement of in-depth expertise in data analysis, failing to analyze multiple cancer-associated nucleic acid markers and provide immediate results in a point-of-care manner. Herein, we demonstrate a transistor-based DNA molecular computing (TDMC) platform that enables simultaneous detection and logical analysis of multiple microRNA (miRNA) markers on a single transistor. TDMC can perform not only basic logical operations such as "AND" and "OR", but also complex cascading computing, opening up new dimensions for multi-index logical analysis. Owing to the high efficiency, sensing and computations of multi-analytes can be operated on a transistor at a concentration as low as 2×10 -16 M, reaching the lowest concentration for DNA molecular computing. Thus, TDMC achieves an accuracy of 98.4 % in the diagnosis of hepatocellular carcinoma from 62 serum samples. As a convenient and accurate platform, TDMC holds promise for applications in "one-stop" personalized medicine., (© 2024 Wiley-VCH GmbH.)

Cancer diagnosis plays a key role in facilitating treatment and improving survival rates of patients. The combination of near-infrared (NIR) spectroscopy with data-driven algorithms offers a rapid and cost-effective approach for such a task. Due to the limitations of objective cases, the number of tumor samples is usually smaller, and the resulting dataset exhibit the issues of class imbalance, which has a more serious impact on the performance of diagnostic models. To deal with class imbalance and improve the sensitivity, this work investigates the feasibility of NIR spectroscopy combined with virtual sample generation (VSG) as well as ensemble strategy for developing diagnostic models. Based on preliminary experiment, several learning algorithms such as discriminant analysis (DA) and partial least square-discriminant analysis (PLS-DA) are screened out as algorithms for constructing prediction models. Three algorithms of VSG including synthetic minority oversampling technique (SMOTE), Borderline-SMOTE and adaptive synthetic sampling (ADASYN) are used for experiment. A fixed sample subset composed of 27 cancer samples and 54 normal samples are hold out as the test set. Three training sets containing 5, 10, 25 minority class samples and 54 majority class samples are used for model development. The experimental result indicates that overall, with PLS-DA algorithm, all VSG approaches can significantly improve the sensitivity of cancer diagnosis for all cases of training sets with different minority samples, but ADASYN performs the best. It reveals that the integration of NIR, PLS-DA, and ADASYN is a promising tool package for developing diagnosis methods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Medical applications of iridium (III) complexes include their use as state-of-the-art theranostic agents - molecules that combine therapeutic and diagnostic functions into a single entity. These complexes offer a promising avenue in medical diagnostics, precision imaging at single-cell resolution and targeted anticancer therapy due to their unique properties. In this review we report a short summary of their application in medical diagnostics, imaging at single-cell level and targeted anticancer therapy. The exceptional photophysical properties of Iridium (III) complexes, including their brightness and photostability, make them excellent candidates for bioimaging. They can be used to image cellular processes and the microenvironment within single cells with unprecedented clarity, aiding in the understanding of disease mechanisms at the molecular level. Moreover the iridium (III) complexes can be designed to selectively target cancer cells,. Upon targeting, these complexes can act as photosensitizers for photodynamic therapy (PDT), generating reactive oxygen species (ROS) upon light activation to induce cell death. The integration of diagnostic and therapeutic capabilities in Iridium (III) complexes offers the potential for a holistic approach to cancer treatment, enabling not only the precise eradication of cancer cells but also the real-time monitoring of treatment efficacy and disease progression. This aligns with the goals of personalized medicine, offering hope for more effective and less invasive cancer treatment strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Objective　To decrease cancer mortality by implementing cancer screening programs, rigorous quality control measures that utilize standardized indicators are imperative. In Japan, although each municipality performing cancer screening programs implements quality control for their programs using the checklist authorized by the Ministry of Health, Labour and Welfare, compliance with all the items listed is not possible because calculating sensitivity and specificity using cancer registry data is difficult under these circumstances. This report elucidates the methodology for calculating indicators, including sensitivity and specificity, by delineating the parameters of false-negative cases within population-based cancer screening programs in Japan. Furthermore, the inherent challenges associated with ensuring the quality control of cancer screening procedures are expounded upon in this report.Method　Data from the Prefectural Cancer Registry of Japan and cancer screening records compiled by municipalities were used to differentiate true-positive, true-negative, false-positive, and false-negative cases based on the combination of screening test outcomes and subsequent cancer incidence.Results　A false-negative case was defined as an examinee who received a cancer diagnosis within one year after undergoing the screening test, notwithstanding the negative judgment of the cancer screening decision. The duration for judgment of true-positive, true-negative, and false-negative cases was also extended to one year. Cancer identification after cancer screening was ascertained using data from the Prefectural Cancer Registry, ensuring uniform categorization of the four cases. Subsequently, sensitivity and specificity values were calculated for municipalities conducting cancer screening programs.Conclusion　Sensitivity and specificity are indispensable metrics for the inherent quality control of cancer screening because these parameters directly assess the efficacy of screening tests. The anticipated increase in the number of municipalities engaged in comprehensive quality control of cancer screening in Japan is poised to enhance the efficiency of cancer control policies. This augmentation will be accomplished through the meticulous utilization of the sensitivity and specificity values elucidated in the present report. The forthcoming challenges involve the proliferation of medical institutes reporting their adherence to the checklist stipulated by the National Cancer Center of Japan and the widespread dissemination of fundamental knowledge pertaining to cancer screening.

Circulating tumor cell (CTC) numbers in the blood of cancer patients can indicate the progression and invasiveness of tumors, and their prognostic and predictive value has been repeatedly demonstrated. However, the standard baseline CTC count at the beginning of treatment, while informative, is not completely reliable and may not adequately reflect the state of the disease. A growing number of studies indicate that the long-term monitoring of CTC numbers in the same patient provides more comprehensive prognostic data and should be incorporated into clinical practice, as a factor that contributes to therapeutic decisions. This review describes the current status of CTC enumeration as a prognostic and predictive factor, highlights the shortcomings of current solutions, and advocates for longitudinal CTC analysis as a more effective method of the evaluation of developing disease, treatment efficacy, and the long term-monitoring of the minimal residual disease. As evidenced by the described reports, the longitudinal monitoring of CTCs should provide a better and more sensitive prediction of the course of the disease, and its incorporation in clinical practice should be beneficial.

Tumor-associated antigens (TAAs) are not exclusively expressed in cancer cells, inevitably causing the "on target, off tumor" effect of molecular recognition tools. To achieve precise recognition of cancer cells, by using protein tyrosine kinase 7 (PTK7) as a model TAA, a DNA molecular logic circuit Aisgc8 was rationally developed by arranging H + -binding i-motif, ATP-binding aptamer, and PTK7-targeting aptamer Sgc8c in a DNA sequence. Aisgc8 output the conformation of Sgc8c to recognize PTK7 on cells in a simulated tumor microenvironment characterized by weak acidity and abundant ATP, but not in a simulated physiological environment. Through in vitro and in vivo results, Aisgc8 demonstrated its ability to precisely recognize cancer cells and, as a result, displayed excellent performance in tumor imaging. Thus, our studies produced a simple and efficient strategy to construct DNA logic circuits, opening new possibilities to develop convenient and intelligent precision diagnostics by using DNA logic circuits.

Multi-Cancer Early Detection is a highly popular topic, bringing the hope of being able to detect very early, non-symptomatic cancers and allowing more successful therapy. A major company in this space is GRAIL, which has attracted very significant financing and launched large-scale tests of its detection systems. However, the real clinical utility of these tests remains to be demonstrated, and fundamental issues are still pending., (© 2024 médecine/sciences – Inserm.)

Objective: The incidence rates of dementia, mild cognitive impairment, and cancer increase with age, posing challenges to affected individuals and their families. However, there are currently no clear cancer screening guidelines for individuals with cognitive impairment. This study analyzed the impact of carer health literacy on screening behaviors in this population., Methods: We conducted a postal follow-up survey, associated with the National Center for Geriatrics and Gerontology-Life STORIES of People with Dementia, that targeted primary carers to assess their reports regarding patient attendance at regular cancer screenings recommended by the Japanese Ministry of Health, Labor and Welfare, over the preceding 2 years. Screening rates were compared between the memory clinic cohort and the national average, and the influence of carer health literacy level on screening was analyzed., Results: Among the 826 total individuals analyzed, the memory clinic cohort exhibited lower breast cancer screening rates, at 11% among female patients aged 65-74 years versus the national average of 32%. Higher health literacy among carers was significantly associated with increased screening. For female patients, carers with high levels of communicative health literacy were more likely to ensure that patients attended screenings for gastric (adjusted odds ratio [AOR], 1.77; 95% confidence interval [CI], 1.03-3.04), colorectal (AOR, 1.70, 95% CI 1.08-2.70), and breast cancers (AOR, 3.08; 95% CI, 1.40-6.76). Among the male patients, high communicative health literacy was associated with increased lung cancer screening attendance (AOR, 1.82; 95% CI, 1.11-2.99)., Conclusions: Our research highlights a notable gap in cancer screening attendance between individuals with cognitive impairment and the general population, potentially arising from the intricate nature of screening procedures and the extensive burden on carers. More informed decisions and increased screening rates can be achieved through patient-centric communication strategies that accommodate the cognitive abilities of patients, ensuring the comprehensibility and accessibility of health-related information., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Advances in cancer diagnostics play a pivotal role in increasing early detection of cancer. Integrating laser-induced breakdown spectroscopy (LIBS) with machine learning algorithms has attracted wide interest in cancer diagnosis. However, using a single model`s efficacy is limited by algorithm principles, making it challenging to meet the comprehensive needs of cancer diagnosis. Here, we demonstrate a bagging-voting fusion (BVF) algorithm for the detection and identification of multiple types of cancer. In the BVF model of this paper, support vector machine (SVM), artificial neural network (ANN), k-nearest neighbors (KNN), quadratic discriminant analysis (QDA), and random forest (RF) models, which have relatively small homogeneity to obtain more comprehensive decision boundaries, are fused at both the training and decision levels. LIBS spectral data was collected from four types of serum samples, including liver cancer, lung cancer, esophageal cancer, and healthy control. LIBS detection was conducted on the samples, which were directly dropped onto ordered microarray silicon substrates and dried. The results showed that the BVF model achieved an accuracy of 92.53 % and a recall of 92.92 % across the four types of serum, outperforming the best single machine-learning model (SVM: accuracy 75.86 %, recall 77.50 %). Moreover, the BVF model with manual line selection feature extraction required only 140 s for a single detection and identification. In conclusion, the aforementioned results demonstrated that LIBS with BVF has excellent performance in detecting a multitude of cancers, and is expected to provide a new method for efficient and accurate cancer diagnosis., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest related to this article., (Copyright © 2024. Published by Elsevier Ltd.)

Objectives: This paper reports on an exploratory study into the perceived benefits and challenges of using an electronic cancer prediction system, C the Signs, for safety netting within a Primary Care Network (PCN) in the East of England., Methods: The study involved semi-structured interviews and a qualitative questionnaire with a sample of 15 clinicians and practice administrators within four GP practices in the PCN., Results: Participants generally perceived benefits of C the Signs for managing and monitoring referrals as part of post-consultation safety netting. Clinicians made little use of the decision support function though, as part of safety netting during the consultation, and referrals were still sent by administrators, rather than directly by clinicians through C the Signs., Conclusion: Emphasising the benefits of C the Signs for post-consultation safety netting is most likely to gain buy-in to the system from clinicians, and can also be used by administrators for shared visibility of referrals. More evidence is needed on the value of C the Signs for safety netting during the consultation, through better diagnosis of cancer, before this is seen as a valued benefit by clinicians and provides motivation to use the system., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Inadequate treatment of venous thromboembolism can have fatal consequences that are often irreversible. If the indication is given, long-term therapeutic anticoagulation may be necessary to reduce the risk of recurrence for those affected. On the other hand, there is an increased risk of bleeding due to continued anticoagulation, so an individual risk/benefit assessment is necessary. A careful assessment of possible contributing factors is therefore essential. If uncertainty persists, comprehensive environmental diagnostics with regard to thrombophilia or cancer can be helpful., Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

Tumor-derived small extracellular vesicle (sEV) microRNAs (miRNAs) are emerging biomarkers for cancer diagnostics. Conventional sEV miRNA detection methods necessitate the lysis of sEVs, rendering them laborious and time-consuming and potentially leading to damage or loss of miRNAs. Membrane fusion-based in situ detection of sEV miRNAs involves the preparation of probe-loaded vesicles ( e.g. , liposomes or cellular vesicles), which are typically sophisticated and require specialist equipment. Membrane perforation methods employ chemical treatments that can induce severe miRNA degradation or leaks. Inspired by previous studies that loaded nucleic acids into EVs or cells using hydrophobic tethers for therapeutic applications, herein, we repurposed this strategy by conjugating a hydrophobic tether onto molecular beacons to aid their transportation into sEVs, allowing for in situ detection of miRNAs in a fusion-free and multiplexing manner. This method enables simultaneous detection of multiple miRNA species within serum-derived sEVs for the diagnosis of prostate cancer, breast cancer, and gastric cancer with an accuracy of 83.3%, 81.8%, and 100%, respectively, in a cohort of 66 individuals, indicating that it holds a high application potential in clinical diagnostics.

Background: Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the "intended effect" (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests., Methods: We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial-colorectal component [PLCO-CRC])., Results: Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 6-fold (NLST), 33-fold (MINN-FOBT-A), or 260 000-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 25% (NLST), 47% (MINN-FOBT-A), or 63% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives., Conclusions: Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests., (Published by Oxford University Press 2024.)

The COVID-19 pandemic affected daily life significantly and had massive consequences for healthcare systems with tremendous regional differences. This retrospective study aimed to investigate whether the pandemic and resulting societal changes impacted the diagnosis of pediatric malignancies in a distinct region. Pediatric cancer cases in Bavaria (2016-2021) and SARS-CoV-2 proceedings during the peak phase of the pandemic (2020-2021) were retrospectively analyzed. All new diagnoses of pediatric malignancies reported from cancer centers in Bavaria were included. Clinical data from pre-pandemic years was compared to diagnoses made during the pandemic. Official SARS-CoV-2 reports were received from the Bavarian Health and Food Safety Authority and data on regional pandemic measures were obtained from the Healthcare Data Platform. With this design, a comprehensive analysis of the pandemic proceedings was performed. We found significantly decreased incidence-rate ratios for pediatric cancer diagnosis during the early spring peak of SARS-CoV-2 as it was observed in May during the pandemic, followed by non-significantly increased metastatic cancer diagnosis two months later. Additionally, the time-to-diagnosis of pediatric malignancies was significantly prolonged during the pandemic, and outpatient contacts were significantly reduced, although the availability of consultations remained the same. From our findings, we may hypothesize that there have been effects on pediatric cancer diagnosis during the COVID-19 pandemic at vulnerable times. Interpretation of changes remains speculative with potential causes from behavior patterns, such as hesitation, concerns, and potential societal changes during phases of public restrictions, rather than overwhelmed medical capacities. Nevertheless, specific awareness is needed to protect this patient population during potential future pandemics.

Histopathology image evaluation is indispensable for cancer diagnoses and subtype classification. Standard artificial intelligence methods for histopathology image analyses have focused on optimizing specialized models for each diagnostic task 1,2 . Although such methods have achieved some success, they often have limited generalizability to images generated by different digitization protocols or samples collected from different populations 3 . Here, to address this challenge, we devised the Clinical Histopathology Imaging Evaluation Foundation (CHIEF) model, a general-purpose weakly supervised machine learning framework to extract pathology imaging features for systematic cancer evaluation. CHIEF leverages two complementary pretraining methods to extract diverse pathology representations: unsupervised pretraining for tile-level feature identification and weakly supervised pretraining for whole-slide pattern recognition. We developed CHIEF using 60,530 whole-slide images spanning 19 anatomical sites. Through pretraining on 44 terabytes of high-resolution pathology imaging datasets, CHIEF extracted microscopic representations useful for cancer cell detection, tumour origin identification, molecular profile characterization and prognostic prediction. We successfully validated CHIEF using 19,491 whole-slide images from 32 independent slide sets collected from 24 hospitals and cohorts internationally. Overall, CHIEF outperformed the state-of-the-art deep learning methods by up to 36.1%, showing its ability to address domain shifts observed in samples from diverse populations and processed by different slide preparation methods. CHIEF provides a generalizable foundation for efficient digital pathology evaluation for patients with cancer., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Modern cancer research depends heavily on the identification and validation of biomarkers because they provide important information about the diagnosis, prognosis, and response to treatment of the cancer. This review will provide a comprehensive overview of cancer biomarkers, including their development phases and recent breakthroughs in transcriptomics and computational techniques for detecting these biomarkers. Blood-based biomarkers have great potential for non-invasive tumor dynamics and treatment response monitoring. These include circulating tumor DNA, exosomes, and microRNAs. Comprehensive molecular profiles are provided by multi-omic technologies, which combine proteomics, metabolomics, and genomes to support the identification of biomarkers and the targeting of therapeutic interventions. Genetic changes are detected by next-generation sequencing, and patterns of protein expression are found by protein arrays and mass spectrometry. Tumor heterogeneity and clonal evolution can be understood using metabolic profiling and single-cell studies. It is projected that the use of several biomarkers-genetic, protein, mRNA, microRNA, and DNA profiles, among others-will rise, enabling multi-biomarker analysis and improving individualised treatment plans. Biomarker identification and patient outcome prediction are further improved by developments in AI algorithms and imaging techniques. Robust biomarker validation and reproducibility require cooperation between industry, academia, and doctors. Biomarkers can provide individualized care, meet unmet clinical needs, and enhance patient outcomes despite some obstacles. Precision medicine will continue to take shape as scientific research advances and the integration of biomarkers with cutting-edge technologies continues to offer a more promising future for personalized cancer care., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2024 Elsevier GmbH. All rights reserved.)