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Background: Liquid biopsy is considered a complementary and recently also an alternative method to surgical biopsy. It allows for the acquisition of valuable information regarding the potential presence of tumors, particularly through the analysis of circulating tumor DNA (ctDNA). CtDNA is a fraction of circulating free DNA (cfDNA) that can be extracted from various tissues, with blood being the most readily available., Results: To maximize the yield of plasma separation, specific Streck tubes are recommended for blood collection. The MagPurix CFC DNA Extraction Kit can be used for cfDNA extraction, and the TWIST Library Preparation protocol can be optimized for further analysis. Next-generation sequencing (NGS) can be employed to compare somatic and germline lineages, enabling the identification of somatic variants with a Variant Allele Frequency (VAF) of 5 % or higher, which are absent in the germline lineage., Conclusion: This analysis helps in the assessment of recurrence, analysis, and monitoring of cancer tissue., Competing Interests: Declaration of competing interest The authors of this scientific article often publish together, being part of the same group and/or scientific society. The scientific journal designated to publish this article has a specific policy to ensure the optimal handling of these situations. The journal’s policy ensures that the peer review process is kept independent by selecting reviewers independent of the authors of the article. All affiliations of the authors with private companies have been declared to make clear the position regarding the interests of these companies. The authors are affiliated with private companies for which there could be a possible conflict of interest. The authors state that the research was conducted in the absence of any commercial relationship that could be construed as a possible direct conflict of interest avoiding mention of any products or services sold by private companies related to the authors. The authors of this article are reported to be patents inventors., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: The objective of this study was to estimate the incidence, timing, and type of new cancer diagnosis among patients with cryptogenic stroke., Methods: We used data from the ARCADIA trial, which enrolled patients with cryptogenic stroke and atrial cardiopathy. Participants were prospectively followed, and serious adverse events were assessed every 3 months or sooner if investigators were alerted between visits to an event. Kaplan-Meier statistics were used to estimate the cumulative incidence of a cancer diagnosis within the first year after randomization., Results: Among 878 participants without baseline history of cancer, 13 (1.5%) were diagnosed with incident cancer in the year after randomization, comprising 12 solid cancers (3 prostate, 2 breast, 2 gastrointestinal, and 5 other primary sites) and 1 hematologic cancer (non-Hodgkin lymphoma). The cumulative incidences of a cancer diagnosis were 0% at 3 months, 0.6% (95% CI 0.2%-1.5%) at 6 months, and 2.0% (95 CI 1.1%-3.4%) at 1 year. The median time from index stroke to cancer diagnosis was 261 days (interquartile range 183-358)., Discussion: In a multicenter cryptogenic stroke cohort with prospective follow-up, the 1-year cumulative incidence of a cancer diagnosis was 2%. This rate may be an underestimation because of the clinical trial population and exclusion of cancers diagnosed immediately after stroke., Trial Registration Information: ClinicalTrials.gov Identifier: NCT03192215. Registered June 20, 2017. First patient enrolled February 1, 2018.

Background: Cytopathological examination serves as a tool for diagnosing solid tumors and hematologic malignancies. Artificial intelligence (AI)-assisted methods have been widely discussed in the literature for increasing sensitivity, specificity and accuracy in the diagnosis of cytopathological clinical samples. Many of these tools are also used in clinical practice. There is a growing body of literature describing the role of AI in clinical settings, particularly in improving diagnostic accuracy and providing predictive and prognostic insights., Methods: A comprehensive search for this systematic review was conducted using databases Google, PUBMED (n = 450) and Google Scholar (n = 1067) with the keywords "Artificial Intelligence" AND "cytopathological" and "fine needle aspiration" AND "Deep Learning" AND "Machine Learning" AND "Hematologic Disorders" AND "Lung Cancer" AND "Pap Smear" and "cervical cancer screening" AND "Thyroid Cancer" AND "Breast Cancer" and "Sensitivity" and "Specificity". The search focused on literature reviews and systematic reviews published in English language between 2020 and 2024. PRISMA guidelines were adhered to with studies included and excluded as depicted in a flowchart. 417 results were screened with 34 studies were chosen for this review., Results: In the screening of patients with cervical cancer, bone marrow and peripheral blood smears and benign and malignant lesions in the lung, AI-assisted methods, particularly machine learning and deep learning (a subset of machine learning) methods, were applied to cytopathological data. These methods yielded greater diagnostic accuracy, specificity and sensitivity and decreased interobserver variability. Data sets were collected for both training and validation. Human machine combined performance was also found to be comparable to standalone performance in comparison with medical performance as well., Conclusions: The use of AI in the analysis of cytopathological samples in research and clinical settings is increasing, and the involvement of pathologists in AI workflows is becoming increasingly important., Competing Interests: Declarations Ethical approval and consent to participate Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Cancer is one of the most serious health problems worldwide. Because cancer has no specific symptoms in its early stages, it is often not diagnosed until it is in advanced stages, reducing the likelihood of successful treatment. Therefore, early diagnosis of cancer is a formidable challenge. Mass spectrometry-based proteomics offers a robust technical foundation for cancer diagnosis. However, mass spectrometry data are characterized by high dimensionality, large data volume, and noise interference, which can lead to diagnostic errors in clinical applications. To address this challenge, an improved algorithm combining principal component analysis (PCA) with a convolutional neural network (CNN) algorithm (denoted as PCA-1DSE-ResCNN) was proposed to assist in analyzing high-dimensional mass spectral data. The algorithm initially reduced the dimensionality of the data through the PCA technique. Subsequently, the convolutional neural network algorithm (1DSE-ResCNN) integrating residual blocks and squeeze-and-excitation blocks was used as a classifier. This approach can not only alleviate the issues of overfitting and gradient vanishing caused by deep network layers but also reduce redundant information, enabling the algorithm to effectively learn high-dimensional data features and deal with nonlinear relationships. To validate the effectiveness of the algorithm, the high-dimensional ovarian cancer mass spectrometry dataset was selected as an example to examine its application performance in early diagnosis of ovarian cancer. The experimental results demonstrated that the PCA-1DSE-ResCNN algorithm outperforms other methods in terms of accuracy, specificity, and sensitivity on three high-dimensional ovarian cancer datasets. This study will contribute to the rapid diagnosis and early detection of cancer.

The specificity and sensitivity of a simple non-invasive multi-cancer screening method in detecting breast, lung, prostate, and colorectal cancer in breath samples were evaluated in a double-blind study. Breath samples of 1386 participants (59.7% males, median age 56.0 years) who underwent screening for cancer using gold-standard screening methods, or a biopsy for a suspected malignancy were collected. The samples were analyzed using a bio-hybrid platform comprising trained detection canines and artificial intelligence tools. According to cancer screening/biopsy results, 1048 (75.6%) were negative for cancer and 338 (24.4%) were positive. Among the 338 positive samples, 261 (77.2%) were positive for one of the four cancer types that the bio-hybrid platform was trained to detect, with an overall sensitivity and specificity of 93.9% (95% confidence interval [CI] 90.3-96.2%) and 94.3% (95% CI 92.7%-95.5%), respectively. The sensitivity of each cancer type was similar; breast: 95.0% (95% CI 87.8-98.0%), lung: 95.0% (95% CI 87.8-98.0%), colorectal: 90.0% (95% CI 74.4-96.5%), prostate: 93.0% (95% CI 84.6-97.0%). The sensitivity of 14 other malignant tumors that the bio-hybrid platform was not trained to detect, but identified, was 81.8% (95% CI 71.8%-88.8%). Early cancer (0-2) detection sensitivity was 94.8% (95% CI 91.0%-97.1%). This bio-hybrid multi-cancer screening platform demonstrated high sensitivity and specificity and enables early-stage cancer detection., Competing Interests: Declarations Competing interests Milana Avdalimov and Assaf Rabinowicz are SpotitEarly Ltd. employees. Sharon Furman-Assaf and Ronit Shmuel received funding from SpotitEarly Ltd. All other authors have no competing interests to declare., (© 2024. The Author(s).)

Whole-body MRI (WBMRI) is an integral part of screening infants, children, and adolescents for presymptomatic neoplasms in certain cancer predisposition syndromes, which include Li-Fraumeni and constitutional mismatch repair deficiency syndromes, among others. The list of syndromes in which WBMRI adds value, as part of a comprehensive surveillance protocol, continues to evolve in response to new evidence, growing experience, and more widespread adoption. In July 2023, the AACR reconvened an international, multidisciplinary panel to revise and update recommendations stemming from the 2016 AACR Special Workshop on Childhood Cancer Predisposition. That initial meeting resulted in a series of publications in Clinical Cancer Research in 2017, including "Pediatric Cancer Predisposition Imaging: Focus on Whole-Body MRI." This 2024 review of WBMRI in cancer predisposition syndrome updates the 2017 WBMRI publication, the revised recommendations derived from the 2023 AACR Childhood Cancer Predisposition Workshop based on available data, societal guidelines, and expert opinion. Different aspects of acquiring and interpreting WBMRI, including diagnostic accuracy, are discussed. The application of WBMRI in resource-poor environments, as well as integration of whole-body imaging techniques with emerging technologies, such as cell-free DNA ("liquid biopsies") and artificial intelligence/machine learning, is also considered., (©2024 American Association for Cancer Research.)

Genomic instability disorders are characterized by DNA or chromosomal instability, resulting in various clinical manifestations, including developmental anomalies, immunodeficiency, and increased risk of developing cancers beginning in childhood. Many of these genomic instability disorders also present with exquisite sensitivity to anticancer treatments such as ionizing radiation and chemotherapy, which may further increase the risk of second cancers. In July 2023, the American Association for Cancer Research held the second Childhood Cancer Predisposition Workshop, where multidisciplinary international experts discussed, reviewed, and updated recommendations for children with cancer predisposition syndromes. This article discusses childhood cancer risks and surveillance recommendations for the group of genomic instability disorders with predominantly recessive inheritance, including the DNA repair disorders ataxia telangiectasia, Nijmegen breakage syndrome, Fanconi anemia, xeroderma pigmentosum, Bloom syndrome, and Rothmund-Thomson syndrome, as well as the telomere biology disorders and mosaic variegated aneuploidy. Recognition of children with genomic instability disorders is important in order to make the proper diagnosis, enable genetic counseling, and inform cancer screening, cancer risk reduction, and choice of anticancer therapy., (©2024 American Association for Cancer Research.)

Biosensor research has long focused on achieving the lowest possible Limits of Detection (LOD), driving significant advances in sensitivity and opening up new possibilities in analysis. However, this intense focus on low LODs may not always meet the practical needs or suit the actual uses of these devices. While technological improvements are impressive, they can sometimes overlook important factors such as detection range, ease of use, and market readiness, which are vital for biosensors to be effective in real-world applications. This review advocates for a balanced approach to biosensor development, emphasizing the need to align technological advancements with practical utility. We delve into various applications, including the detection of cancer biomarkers, pathology-related biomarkers, and illicit drugs, illustrating the critical role of LOD within these contexts. By considering clinical needs and broader design aspects like cost-effectiveness, sustainability, and regulatory compliance, we argue that integrating technical progress with practicality will enhance the impact of biosensors. Such an approach ensures that biosensors are not only technically sound but also widely useable and beneficial in real-world applications. Addressing the diverse analytical parameters alongside user expectations and market demands will likely maximize the real-world impact of biosensors., 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.)

Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electronic health records (EHRs). Artificial intelligence (AI) models have been trained to extract outcomes from individual EHRs. However, patient privacy restrictions have historically precluded dissemination of these models beyond the centers at which they were trained. In this study, the vulnerability of text classification models trained directly on protected health information to membership inference attacks is confirmed. A teacher-student distillation approach is applied to develop shareable models for annotating outcomes from imaging reports and medical oncologist notes. 'Teacher' models trained on EHR data from Dana-Farber Cancer Institute (DFCI) are used to label imaging reports and discharge summaries from the Medical Information Mart for Intensive Care (MIMIC)-IV dataset. 'Student' models are trained to use these MIMIC documents to predict the labels assigned by teacher models and sent to Memorial Sloan Kettering (MSK) for evaluation. The student models exhibit high discrimination across outcomes in both the DFCI and MSK test sets. Leveraging private labeling of public datasets to distill publishable clinical AI models from academic centers could facilitate deployment of machine learning to accelerate precision oncology research., Competing Interests: Competing interests here are no patents related to this research. Dr. Kehl reports funding from the American Association for Cancer Research to his institution related to this research and honoraria from UpToDate and travel sponsored by Meta in the context of a grant submission process unrelated to this research. Dr. Choueiri reports institutional and/or personal, paid and/or unpaid support for research, advisory boards, consultancy, and/or honoraria past 5 years, ongoing or not, from: Alkermes, Arcus Bio, AstraZeneca, Aravive, Aveo, Bayer, Bristol Myers-Squibb, Bicycle Therapeutics, Calithera, Circle Pharma, Deciphera Pharmaceuticals, Eisai, EMD Serono, Exelixis, GlaxoSmithKline, Gilead, HiberCell, IQVA, Infinity, Institut Servier, Ipsen, Jansen, Kanaph, Lilly, Merck, Nikang, Neomorph, Nuscan/PrecedeBio, Novartis, Oncohost, Pfizer, Roche, Sanofi/Aventis, Scholar Rock, Surface Oncology, Takeda, Tempest, Up-To-Date, CME events (Peerview, OncLive, MJH, CCO and others), outside the submitted work. He also reports institutional patents filed on molecular alterations and immunotherapy response/toxicity, and ctDNA. He reports equity in Tempest, Pionyr, Osel, Precede Bio, CureResponse, InnDura Therapeutics, Premium, and Bicycle; committee participation in NCCN, GU Steering Committee, ASCO (BOD 6-2024-, ESMO, ACCRU, KidneyCan). He reports that medical writing and editorial assistance support may have been funded by Communications companies in part. He reports that he has mentored several non-US citizens on research projects with potential funding (in part) from non-US sources/Foreign Components. His institution (Dana-Farber Cancer Institute) may have received additional independent funding of drug companies or/and royalties potentially involved in research around the subject matter. Dr. Bakouny reports Honoraria from UpToDate; serving as Associate Editor at Journal of Clinical Oncology Clinical Cancer Informatics (JCO CCI); serving as co-chair of the American Society of Clinical Oncology’s International Medical Graduate Community of Practice (ASCO IMG CoP); and serving as co-founder of the IMG Oncologists nonprofit non-governmental organization. Dr. Schrag reports funding from AACR to her institution related to this research. Ms. Nichols reports funding from AACR to her institution related to this research. The other authors have no competing interests to disclose., (© 2024. The Author(s).)

The WNT6 ligand is a well-known activator of the WNT signaling pathway, considered a vital player in several important physiologic processes during embryonic development and maintaining homeostasis throughout life, regulating the proliferation and differentiation of multiple stem/progenitor cell types. More recently, as it is the case for many key molecular regulators of embryonic development, dysregulation of WNT6 has been implicated in cancer development and progression in multiple studies. In this review, we overview the most significant recent findings regarding WNT6 in the context of human malignancies, exploring its influence on multiple dimensions of tumor pathophysiology and highlighting the putative underlying WNT6-associated molecular mechanisms. We also discuss the potential clinical implications of WNT6 as a prognostic and therapeutic biomarker. This critical review highlights the emerging relevance of WNT6 in multiple human cancers, and its potential as a clinically-useful biomarker, addressing key unanswered questions that could lead to new opportunities in patient diagnosis, stratification, and the development of rationally-designed precision therapies., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Efficient enrichment and accurate diagnosis of cancer cells from biological samples can guide effective treatment strategies. However, the accessibility and accuracy of rapid identification of tumor cells have been hampered due to the overlap of white blood cells (WBCs) and cancer cells in size. Therefore, a diagnosis system for the identification of tumor cells using reliable surface-enhanced Raman spectroscopy (SERS) bioprobes assisted with high-efficiency microfluidic chips for rapid enrichment of cancer cells was developed. According to this, a homogeneous flower-like Cu 2 O@Ag composite with high SERS performance was constructed. It showed a favorable spectral stability of 5.81% and can detect trace alizarin red (10 -9 mol L -1 ). Finite-difference time-domain (FDTD) simulation of Cu 2 O, Ag and Cu 2 O@Ag, decreased the fluorescence lifetime of methylene blue after adsorption on Cu 2 O@Ag, and surface defects of Cu 2 O observed using a spherical aberration-corrected transmission electron microscope (AC-TEM) demonstrated that the combined effects of electromagnetic enhancement and promoted charge transfer endowed the Cu 2 O@Ag with good SERS activity. In addition, the modulation of the absorption properties of flower-like Cu 2 O@Ag composites significantly improved electromagnetic enhancement and charge transfer effects at 532 nm, providing a reliable basis for the label-free SERS detection. After the cancer cells in blood were separated by a spiral inertial microfluidic chip (purity >80%), machine learning-assisted linear discriminant analysis (LDA) successfully distinguished three types of cancer cells and WBCs with high accuracy (>90%). In conclusion, this study provides a profound reference for the rational design of SERS probes and the efficient diagnosis of malignant tumors.

Purpose: The COVID-19 pandemic was associated with severe disruptions in healthcare worldwide. Cancer patients are at particular risk of adverse consequences from delays in diagnosis and treatment. To evaluate the available data on the impact of the pandemic on cancer diagnoses, oncological care and patient well-being in Germany, the German Society for Epidemiology (DGEpi) in collaboration with the Epidemiological Cancer Registry of Lower Saxony invited to a workshop on "COVID & Cancer" (held on 26-27 October 2023 in Hanover, Germany). This report provides a summary of the scientific presentations, highlights methodological challenges, and recognises essential evidence gaps., Methods: Twelve studies addressing various aspects in relation to cancer diagnoses, oncological care and patient well-being during the COVID-19 pandemic in Germany and two talks sharing experiences from the UK and the Netherlands were presented at the workshop., Results and Conclusions: Results from German cancer registries consistently showed lower number of incident cancer diagnoses among adults during the first months of the pandemic compared to the respective months of the years before the pandemic. Data from the cancer registries of Baden-Württemberg and Lower Saxony found especially for breast cancer a notable drop (by approximately one third) in the numbers of diagnoses during the first restriction period (April-May 2020), during which the nationwide mammography screening programme in Germany was temporarily suspended. Overall, the extent and ways, in which the pandemic had adversely affected cancer diagnoses, oncological care and created service backlogs, is still not adequately understood. The long-term consequences are yet to be determined., (© 2024. The Author(s).)

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., (© 2024. The Author(s).)

An electrochemiluminescence (ECL) detection system is presented integrated with a bipolar electrode system for sensitive cancer diagnosis. In order to achieve the highest electrical conductivity and redox-active surface area, MXene was chosen as the material for the bipolar electrode. As part of the detection process, the anodic pole of the bipolar electrode was modified with the receptor tyrosine kinase like orphan receptor 1 (ROR1) antibody, followed by an immunoassay using the ROR1 antibody-modified Ag triangle that was identified as significantly enhancing ECL. We measured the ECL of luminol using the anode pole of BPE as an analytical signal in the presence of H 2 O 2 . Additionally, 3D-printed microchannels were used to fabricate the BPE system, to reduce the quantity of sample required. It has been shown that the present immunosensors are low-cost and sensitive in detecting types of cancer, with an extended linear range of 10 fg mL -1 to 1 µg mL -1 in the analysis of synthetic samples and achieving an accuracy of ~ 90% in diagnosing ten unknown real samples., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Background: The clinical utility of whole genome sequencing (WGS) in paediatric cancer has been demonstrated in recent years. WGS has been routinely available in the National Health Service (NHS) England for all children with cancer in England since 2021, but its uptake has been variable geographically. To explore the underlying barriers to routine use of WGS in this population across England and more widely in the United Kingdom (UK) and the Republic of Ireland (ROI), a one-day workshop was held in Cambridge, United Kingdom in October 2022., Methods: Following a series of talks, delegates participated in open, round-table discussions to outline local and broader challenges limiting routine WGS for diagnostic work-up for children with cancer in their Principal Treatment Centres (PTCs) and Genomic Laboratory Hubs (GLHs). Within smaller groups, delegates answered structured questions regarding clinical capability, education and training needs, and workforce competence and requirements. Data was recorded, centrally collated, and analysed following the event using thematic analysis., Results: Sixty participants attended the workshop with broad representation from the 20 PTCs across the UK and ROI and the seven GLHs in England. All healthcare professionals involved in the WGS pathway were represented, including paediatric oncologists, clinical geneticists, clinical scientists, and histopathologists. The main themes highlighted by the group in ensuring equitable access to WGS identified were: lack of knowledge equity between NHS trusts, with a perception of WGS being for research only; and perception of lack of financial support for the clinical process surrounding WGS, including lack of time to take informed consent from patients. The latter also included limited trained staff available for data interpretation, affecting the turnaround time for reporting. Finally, the need for an integrated digital pathway to order, track, and return data to clinicians was highlighted., Conclusion: At the workshop, the general motivation for including WGS in the diagnostic work up for children with cancer was high throughout the UK, however a perceived lack of resources and education opportunities limit the widespread use of this commissioned assay. This workshop has led to some recommendations to increase access to WGS in this population in England and more widely in the devolved national of the UK and the ROI., (© 2024. The Author(s).)

Background: Although suspicions of cancer may be raised in patients who visit the emergency department, little is known about emergency department use before a cancer diagnosis. We sought to describe emergency department use among patients in Ontario within the 90 days before confirmed cancer diagnosis and to evaluate factors associated with this emergency department use., Methods: We conducted a retrospective, population-based study of patients aged 18 years or older who had a confirmed cancer diagnosis in Ontario from 2014 to 2021 using linked administrative databases. The primary outcome was any emergency department visit within 90 days before the cancer diagnosis date. We used multivariable logistic regression to evaluate factors associated with emergency department use, such as demographics (e.g., age, sex, rurality, Ontario Health region, indicators of marginalization), comorbidities, previous emergency department visits and hospital admissions, continuity of primary care, type of cancer, and year of cancer diagnosis., Results: We included 651 071 patients with cancer. Of these, 229 683 (35.3%) had an emergency department visit within 90 days before diagnosis, 51.4% of whom were admitted to hospital from the emergency department. Factors associated with increased odds of emergency department use before cancer diagnosis included rurality (odds ratio [OR] 1.15, 95% confidence interval [CI] 1.13-1.17), residence in northern Ontario (North East region OR 1.14, 95% CI 1.10-1.17 and North West region OR 1.27, 95% CI 1.21-1.32, v. Toronto region), and living in the most marginalized areas (material resources OR 1.37, 95% CI 1.35-1.40 and housing OR 1.09, 95% CI 1.06-1.11, v. least marginalized quintile). We observed significant variation in emergency department use by cancer type, with high odds of emergency department use among patients with intracranial, pancreatic, liver or gallbladder, or thoracic cancer., Interpretation: Emergency department use is common before cancer diagnosis, with about one-third of patients with cancer in Ontario using the emergency department before diagnosis. Understanding why patients visit the emergency department before cancer diagnosis is important, particularly for patients who live in rural or marginalized areas, or those who have specific cancer types., Competing Interests: Competing interests:: Keerat Grewal reports grants from the Canadian Institutes of Health Research (CIHR) and the Canadian Association of Emergency Physicians. David Savage reports grants from CIHR, the Northern Ontario Academic Medical Association, the Natural Sciences and Engineering Research Council of Canada, and the Thunder Bay Regional Health Research Institute. Bjug Borgundvaag received speaker fees from the European Society of Emergency Medicine. Jonathan Irish is vice-president, clinical of Cancer Care Ontario–Ontario Health and participates on the board of the Canadian Cancer Society. Monika Krzyzanowska reports funding from Exilixis, Bayer, Eli Lilly, Novartis, and Eisai; honoraria from Eisai and Ipsen; participation on a data safety monitoring board with Novartis; and a leadership role with Cancer Care Ontario–Ontario Health. Venkatesh Thiruganasambandamoorthy reports funding from the Physician’s Service Incorporated Foundation and the University of Ottawa, consulting fees from the National Institute of Health, and chairships with the University of Ottawa and the Society for Academic Emergency Medicine. No other competing interests were declared., (© 2024 CMA Impact Inc. or its licensors.)

Background: Detection of cancer at the early stage currently offers the only viable strategy for reducing disease-related morbidity and mortality. Various approaches for multi-cancer early detection are being explored, which largely rely on capturing signals from circulating analytes shed by tumors into the blood. The fact that biomarker concentrations are limiting in the early stages of cancer, however, compromises the accuracy of these tests. We, therefore, adopted an alternate approach that involved interrogation of the serum metabolome with machine learning-based data analytics. Here, we monitored for modulations in metabolite patterns that correlated with the presence or absence of cancer. Results obtained confirmed the efficacy of this approach by demonstrating that it could detect a total of 15 cancers in women with an average accuracy of about 99%., Aims: To further increase the scope of our test, we conducted an investigator-initiated clinical trial involving a total of 6445 study participants, which included both cancer patients and non-cancer volunteers. Our goal here was to maximize the number of cancers that could be detected, while also covering cancers in both females and males., Methods and Results: Metabolites extracted from individual serum samples were profiled by ultra-performance liquid chromatography coupled to a high-resolution mass spectrometer using an untargeted protocol. After processing, the data were analyzed by our cancer detection machine-learning algorithm to differentiate cancer from non-cancer samples. Results revealed that our test platform could indeed detect a total of 30 cancers, covering both females and males, with an average accuracy of ~98%. Importantly, the high detection accuracy remained invariant across all four stages of the cancers., Conclusion: Thus, our approach of integrating untargeted metabolomics with machine learning-powered data analytics offers a powerful strategy for early-stage multi-cancer detection with high accuracy., Trial Registration: Registration No: CTRI/2023/03/050316., (© 2024 The Author(s). Cancer Reports published by Wiley Periodicals LLC.)

Molecular prognostic and diagnostic tools allow for targeted cancer surveillance, prognostication, and treatment, and these assays have the potential to improve the lives of patients and their relatives. The impact of these advances, however, is not uniform across populations. Underserved communities frequently do not have the same level of access to novel assays, and the clinical application of these tools is often limited by disproportionate representation of White and European ancestry populations in foundational data, as well as limited diversity in clinical trials. In this review, we highlight major advances in clinical molecular assays, key areas of disparity, and contributing factors. We then list ongoing and future areas of intervention to improve access to and efficacy of molecular assays across populations, so that we as a community may work to improve equity at this critical area of cancer care.

Purpose: There is an increasing interest in studying the potential of mobile health (mHealth) technologies, such as smartphone apps and wearables, as monitoring tools for patients with cancer during or after their treatment. However, little research is dedicated to exploring the opinions and concerns of patients regarding the adoption of these technologies. This study aimed to gain insight into patients' perspectives and preferences for participating in mHealth-based monitoring in cancer care., Methods: A qualitative study comprising semistructured interviews was conducted in the Netherlands between April and June 2023. Participants were eligible if they were 18 years or older with a current or past diagnosis of cancer. The interview guide was developed on the basis of the technology acceptance model, with main themes being use, communication, trust, privacy, and expectations., Results: Thirteen participants with urologic primary cancer were interviewed. Most patients had already some familiarity with the use of digital monitoring devices or wearables. Main barriers included persistent reminders of the illness, receiving notifications deemed unnecessary or unwanted, and the acknowledgment that mHealth technology does not serve as a substitute for human doctors. Conversely, patients recognized the potential for time-savings through the utilization of mHealth, viewed active monitoring as nonburdensome, considered mHealth a tool for reducing the communication threshold with their doctor, and expressed willingness to adopt such a platform if they perceived personal or societal relevance., Conclusion: This study has elucidated which factors are important for successful development of mHealth for patients with cancer. While both barriers and facilitators play a role, patients' attitudes were positive toward the implementation of remote digital monitoring, showing promising prospects for future research of mHealth in oncology.

Purpose: The integration of patient-reported outcomes (PROs) into electronic health records (EHRs) has enabled systematic collection of symptom data to manage post-treatment symptoms. The use and integration of PRO data into routine care are associated with overall treatment success, adherence, and satisfaction. Clinical trials have demonstrated the prognostic value of PROs including physical function and global health status in predicting survival. It is unknown to what extent routinely collected PRO data are used in the development of risk prediction models (RPMs) in oncology care. The objective of the scoping review is to assess how PROs are used to train risk RPMs to predict patient outcomes in oncology care., Methods: Using the scoping review methodology outlined in the Joanna Briggs Institute Manual for Evidence Synthesis, we searched four databases (MEDLINE, CINAHL, Embase, and Web of Science) to locate peer-reviewed oncology articles that used PROs as predictors to train models. Study characteristics including settings, clinical outcomes, and model training, testing, validation, and performance data were extracted for analyses., Results: Of the 1,254 studies identified, 18 met inclusion criteria. Most studies performed retrospective analyses of prospectively collected PRO data to build prediction models. Post-treatment survival was the most common outcome predicted. Discriminative performance of models trained using PROs was better than models trained without PROs. Most studies did not report model calibration., Conclusion: Systematic collection of PROs in routine practice provides an opportunity to use patient-reported data to develop RPMs. Model performance improves when PROs are used in combination with other comprehensive data sources.

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice., (©2024 The Authors; Published by the American Association for Cancer Research.)

Current strategies for early cancer detection and diagnosis need updating to achieve greater precision, necessitating the creation of a comprehensive evolutionary map of tumorigenesis. This requires establishing high-quality prospective cohorts, systematically collecting samples for integrated spatiotemporal multiomics analyses, and efficiently translating laboratory findings into clinical applications., (©2024 American Association for Cancer Research.)

Introduction: Multicancer detection tests (MCDs) are blood-based tests designed to detect multiple cancer types. It is currently unclear whether these cancer screening tests improve mortality. To understand awareness of MCDs among providers and patients, as well as explore how they perceive the benefits, harms, and acceptability of MCDs, we have undertaken a focus group study in primary care physicians (PCPs) and laypersons to explore knowledge, attitudes, and expectations of cancer screening using MCDs., Methods: We conducted six focus groups with 45 PCP participants and 12 focus groups with 80 layperson participants. Participants were identified via a consumer research firm and found eligible following the completion of a screener survey. Moderators used a semi-structured guide containing open-ended questions and prompts to facilitate the discussion. Recordings were transcribed and coded line by line using a codebook developed based on questions and emerging discussion concepts, and emergent themes were identified., Results: Both PCP and layperson participants felt the that benefits of MCDs included ease of use and potential ability to detect cancers early. However, they felt that additional data is needed to overcome some of the concerns related to MCDs. PCP participants expressed concerns related to lack of practice guidelines, cost of diagnostic follow-ups, privacy and insurance issues, fear/anxiety related to confirmation of MCD results, and malpractice liability related to perceived false negative test results. Layperson participants expressed concerns related to costs, insurance coverage, and privacy, as well as anxiety over the confirmation of a positive test result., Conclusions: There is a major need for more rigorous data regarding MCDs to inform the development of guidelines for use as cancer screening tools., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Cancer Medicine published by John Wiley & Sons Ltd.)

Purpose: Patients with cancer visit the emergency department (ED) frequently. While some ED visits are necessary, others may be potentially preventable ED visits (PPEDs). Reducing PPEDs is important to improve quality of care and reduce costs. However, a robust definition and the characteristics of patients at risk remain unclear. This study aimed to describe oncology-related PPEDs and identify characteristics of patients at the highest risk for PPEDs to help target interventions and minimize avoidable ED visits., Methods: A retrospective study was conducted using four clinical and administrative databases. All ED visits by oncology patients between April 1, 2019, and April 1, 2021, were identified. A novel definition of PPEDs was explored, specifically visits that resulted in immediate discharge from the ED or admissions <48 hours. Trends in ED use, including PPEDs, were evaluated using descriptive statistics, logistic regression, and machine learning (ML) modeling., Results: During the 2-year period, 6,689 oncology patients visited the ED (N = 13,415 visits). A total of 62.1% of visits were classified as PPEDs. PPEDs were most common among patients with stage I to III breast cancer and those on systemic therapy. Characteristics of patients at high risk for non-PPEDs included stage IV disease with either lung or GI carcinomas and shorter distances to the ED. The highest-performing ML model yielded an AUC of 0.819., Conclusion: Our novel definition of PPEDs appears promising in identifying oncology patients who could avoid the ED with targeted interventions. This work demonstrated that patients with early-stage disease, those with breast cancer, and those on systemic therapy are at the highest risk for PPEDs and may benefit from proactive interventions to avoid the ED. Although our definition requires validation, using ML models for more robust predictive modeling appears promising.

Background: Cancer places a high burden on society and health-care systems. Cancer research requires high-quality data, which is resource-intensive to obtain. Using administrative datasets such as cancer registries could improve the efficiency of cancer studies if data were valid and timely. We aimed to compare the validity and timeliness of diagnostic cancer data on-site during the SYMPLIFY study to that obtained from the cancer registries of England and Wales., Methods: Cancer data were collected from 5461 participants across 44 hospital sites during a prospective observational study in England and Wales, SYMPLIFY (ISRCTN10226380). Linked cancer data were obtained from Digital Health and Care Wales (DHCW), the Welsh Cancer Intelligence and Surveillance Unit (WCISU), and the English National Cancer Registration Dataset (NCRD) and Rapid Cancer Registration Dataset (RCRD), regularly between April, 2022, and September, 2023. The primary objectives of the study were to evaluate the validity (via assessment of the proportion of completed data fields and concordance with SYMPLIFY sites), and timeliness of the data in all datasets, for all cancers diagnosed within 9 months of study enrolment. Data fields investigated were cancer site via International Classification of Disease, 10th Revision (ICD-10) code; cancer morphology via International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) morphology histology code and broad morphological grouping; overall stage; and TNM classification., Findings: For data collected between April, 2022, and September, 2023, completeness at the last data cut available for each dataset ranged from 84% to 100% for ICD-O-3 morphology, from 43% to 100% for overall stage, and from 74% to 83% for TNM stage. The concordance between SYMPLIFY data and NCRD was 96% (95% CI 92-98) for ICD-10, 60% (53-66) for ICD-O-3 morphology, 83% (78-88) for ICD-O-3 broad morphology groupings, 73% (67-78) for stage, and 51% (44-59) for TNM; and with WCISU was 89% (95% CI 81-94) for ICD-10, 63% (53-73) for ICD-O-3 morphology, 80% (70-87) for ICD-O-3 broad morphology groupings, 83% (74-90) for overall stage, and 49% (38-61) for TNM stage. Concordance between SYMPLIFY and RCRD was 95% (95% CI 92-98) for ICD-10, 67% (60-74) for ICD-O-3 morphology, 85% (79-90) for ICD-O-3 broad morphology groupings, and 73% (65-80) for overall stage; and between SYMPLIFY and DHCW was 96% (91-99) for ICD-10, 74% (64-83) for ICD-O-3 morphology, 84% (75-91) for ICD-O-3 broad morphology groupings, and 87% (74-95) for stage. The SYMPLIFY dataset reached completion at 12 months post-enrolment in November, 2022, compared with 13 months for NCRD in December, 2023. RCRD and DHCW reached completion at 13 months and 15 months post-enrolment, in December, 2022, and February, 2023, respectively., Interpretation: We report similar completeness of data fields, concordance, and timeliness between on-site and centrally collected cancer outcomes data. Our findings suggest that central registry data can help alleviate the resource burden in clinical trials and improve cancer research. Cancer registries might need additional resources to provide data for registry-based trials at scale., Funding: GRAIL Bio UK., Competing Interests: Declaration of interests BDN and MRM receive institutional research funding from GRAIL. BDN reports grants, honoraria, and consulting fees from the National Institute for Health and Care Research (NIHR), Cancer Research UK, Royal College of General Practitioners, and Multi-Cancer Early Detection Consortium. DH and DA report payment to their institution from National Health Service Wales Cancer Network for additional cancer registration officer time to expedite population-based cancer registration for this study. DH and DA report grants from Moondance Cancer Initiative. FDRN reports honoraria for occasional sessional payment for congress talks for AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, and Pfizer. RP reports funding from GRAIL and National Health Service England for the completion of this study, as well as grants from Medical Research Council, NIHR, and the Medical Science Division at the University of Oxford and is a statistical editor for BMJ and BMJ Medicine. HK, KNK, SH, KR, YL, and HN were all employees of GRAIL at the time of the study. HK reports a leadership position with GRAIL. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Early cancer diagnosis from bisulfite-treated cell-free DNA (cfDNA) fragments requires tedious data analytical procedures. Here, we present a deep-learning-based approach for early cancer interception and diagnosis (DECIDIA) that can achieve accurate cancer diagnosis exclusively from bisulfite-treated cfDNA sequencing fragments. DECIDIA relies on transformer-based representation learning of DNA fragments and weakly supervised multiple-instance learning for classification. We systematically evaluate the performance of DECIDIA for cancer diagnosis and cancer type prediction on a curated dataset of 5389 samples that consist of colorectal cancer (CRC; n = 1574), hepatocellular cell carcinoma (HCC; n = 1181), lung cancer (n = 654), and non-cancer control (n = 1980). DECIDIA achieved an area under the receiver operating curve (AUROC) of 0.980 (95% CI, 0.976-0.984) in 10-fold cross-validation settings on the CRC dataset by differentiating cancer patients from cancer-free controls, outperforming benchmarked methods that are based on methylation intensities. Noticeably, DECIDIA achieved an AUROC of 0.910 (95% CI, 0.896-0.924) on the externally independent HCC testing set in distinguishing HCC patients from cancer-free controls, although there was no HCC data used in model development. In the settings of cancer-type classification, we observed that DECIDIA achieved a micro-average AUROC of 0.963 (95% CI, 0.960-0.966) and an overall accuracy of 82.8% (95% CI, 81.8-83.9). In addition, we distilled four sequence signatures from the raw sequencing reads that exhibited differential patterns in cancer versus control and among different cancer types. Our approach represents a new paradigm towards eliminating the tedious data analytical procedures for liquid biopsy that uses bisulfite-treated cfDNA methylome., (© 2024 The Author(s). Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

A stroma a‑reactive invasion front area (SARIFA) is a new prognostic biomarker in carcinomas. Essentially, SARIFA describes the occurrence of direct contact between at least five tumor cells and adipocytes. This phenomenon is extremely easy and quick to identify, shows an extremely low interobserver variability, and does not require any additional staining as it can be identified on standard HE sections. The prognostic efficiency has now been demonstrated in gastric, colorectal, pancreatic, and prostate carcinoma., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Protein phosphatases have demonstrated considerable promise in the realm of early tumor diagnosis across various malignancies. These enzymes play a critical role in modulating the PI3K-Akt signaling pathway, which is integral to cellular processes such as proliferation, survival, and migration. When the activity of protein phosphatases becomes abnormal, it can disrupt these essential signaling pathways, potentially leading to the initiation and progression of tumors. Consequently, monitoring for abnormal expression and activity levels of protein phosphatases could serve as a vital biomarker for early cancer detection. By identifying these alterations, clinicians may be better equipped to diagnose tumors at an earlier stage, significantly improving patient outcomes.In summary, our study highlights the multifaceted and significant role of PTEN in various forms of cancer, including esophageal squamous cell carcinoma (ESCA). Further analysis showed that the expression levels of protein phosphatase and PTEN protein were significantly associated with the early diagnosis of tumors, especially in the early stage of tumors, and their detection sensitivity and specificity were high. Therefore, by detecting the expression of protein phosphatase and PTEN protein, the early diagnosis of tumor can be achieved, and the therapeutic effect and prognosis of patients can be improved., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Unnecessary group and screens (G&S) can lead to unnecessary antibody investigations, use of technologist time, and laboratory resources., Local Problem: A baseline audit at our institution identified that 25% of G&S from the cancer center were unnecessary. We aimed to reduce the ratio of monthly G&S to CBC samples processed from the cancer center by 10% (from 0.034 to 0.031) by January 2024., Methods: This represents an interrupted time series design from November 2022 to January 2024. Using Plan Do Study Act (PDSA) cycles, we aimed to increase the use of an existing reflex testing system, termed "do not test." When this option is selected, the blood bank will only process the G&S sample if specific CBC criteria are met (e.g., hemoglobin <9.0 g/dL). Educational sessions increased awareness of this feature and sought feedback from end-users on its usability. With feedback, the design was updated to include a modifiable hemoglobin threshold for G&S testing, automatic re-selection of the "do not test" feature for future G&S orders, and aesthetic changes to make the feature more visible., Results: The percentage of samples with "do not test" selected increased from 7.2% to 63.0% (p < .0001) and the ratio of G&S to CBC specimens improved from 0.034 to 0.028, exceeding the target of 0.031. We noted an improvement in the appropriateness of G&S orders from 75% at baseline (n = 20) to 97.5% (n = 80) post intervention (p = .003)., Conclusions: We describe an effective strategy to improve G&S utilization at our institution's cancer center using a reflex testing system., (© 2024 The Author(s). Transfusion published by Wiley Periodicals LLC on behalf of AABB.)

Aims: To investigate the impact of diagnosis age of type 2 diabetes mellitus (T2DM) on subsequent adverse outcomes within the Chinese population., Methods: 549,959 eligible T2DM patients were included from Ningbo and Jinhua city in Zhejiang province, China. Standardized ratio was used to evaluate the risks of coronary heart disease (CHD), stroke, cancer and all-cause death in different T2DM diagnosis age groups., Results: For all adverse outcomes, higher excess risks were observed in the youngest age group (30-39) than in the oldest age group (≥80) with T2DM. The standardized incidence ratios (SIR) were 5.93 (95% CI: 3.46, 10.14) for CHD, 5.45 (95% CI: 3.72, 7.99) for stroke and 1.85 (95% CI: 1.38, 2.49) for cancer in the youngest age group, and were 1.32 (95% CI: 1.08, 1.60) for CHD, 1.25 (95% CI: 1.08, 1.44) for stroke, and 0.78 (95% CI: 0.56, 1.09) for cancer, respectively, in the oldest age group. The standardized mortality ratios (SMR) for all-cause death were 3.15 (1.69, 5.84) vs. 1.12 (0.88, 1.43). These excess risks decreased with increasing diagnosis age (all P value < 0.001). Consistent results were observed when individuals were stratified by sex or further excluded with the time from T2DM diagnosis to endpoints less than 1 or 2 years., Conclusions: Th earlier the diagnosis of T2DM, the higher the risk for subsequent adverse outcomes. It is imperative to enhance the management and monitoring of early-onset patients during follow-up., 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 Author(s). Published by Elsevier B.V. All rights reserved.)

Cancer screening is the most cost-effective prevention strategy that enables improved cancer morbidity and mortality rates. However, there was a significant decline in cancer screening during the COVID-19 pandemic worldwide. This study aimed to measure regional differences in cancer screening by comparing screening rates before and during COVID-19 and to examine factors explaining the regional difference in cancer screening. All variables including the differences in cancer screening rate before and during the COVID-19 pandemic were collected from 229 administrative subregions in South Korea and joined with each community in ArcGIS environment. Factors explaining regional difference in cancer screening were analyzed through descriptive statistics, correlation analysis, and interactive decision tree modeling. Cancer screening rates decreased in all regions during the COVID-19 pandemic in South Korea. The findings revealed that national health insurance premiums, the number of cancer screening facilities, livelihood benefit recipients, and the population aged 65+ could be classified as variables highly affecting the decrease in cancer screening rate. These findings highlight the efforts to appraise different barriers to cancer screening in each community. In addition, it is important to promote sustainable cancer screening strategies from regional perspectives based on regional vulnerabilities and their complex impact on cancer screening., 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.

Background: Survival from childhood and adolescent cancer has increased, but the chance of a livebirth in female survivors under 18 years at diagnosis may be reduced., Methods: We performed a national population-based analysis, including all female cancer survivors diagnosed in Scotland before the age of 18 years between 1981 and 2012. Scottish Cancer Registry records were linked to Scottish maternity records. Females from the exposed group with no pregnancies before cancer diagnosis (n = 2118) were compared with three general population controls matched for age and year of diagnosis., Findings: The cumulative incidence of a livebirth for all diagnoses was reduced to 37% (95% CI 33-40%) for cancer survivors at 30 years of age vs 58% (57-60%) for controls. The deficit varying by diagnosis: for lymphoid leukaemia, the cumulative incidence at 30 years was 29% (23-36%) vs 57% (52-61%) for controls with similar deficits in CNS tumours and retinoblastoma. There was a steady improvement in the chance of livebirth in those diagnosed more recently., Interpretation: We have shown a reduced chance of livebirth in female survivors of cancer diagnosed before age 18. The deficit is present for all diagnoses., (© 2024. The Author(s).)

Early detection of cancer predisposition syndromes (CPS) is crucial to determine optimal treatments and follow-up, and to provide appropriate genetic counseling. This study outlines an approach in a pediatric oncology unit, where 50 randomly selected patients underwent clinical assessment, leading to 44 eligible for genetic testing. We identified 2 pathogenic or likely pathogenic variants in genes associated with CPS and 6 variants of uncertain significance (VUS) potentially associated with cancer development. We emphasize the importance of a thorough and accurate collection of family history and physical examination data and the full coordination between pediatric oncologists and geneticists., Competing Interests: The authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Cysteine cathepsins are a fascinating group of proteolytic enzymes that play diverse and crucial roles in numerous biological processes, both in health and disease. Understanding these proteases is essential for uncovering novel insights into the underlying mechanisms of a wide range of disorders, such as cancer. Cysteine cathepsins influence cancer biology by participating in processes such as extracellular matrix degradation, angiogenesis, immune evasion, and apoptosis. In this comprehensive review, we explore foundational research that illuminates the diverse and intricate roles of cysteine cathepsins as diagnostic markers and therapeutic targets for cancer. This review aims to provide valuable insights into the clinical relevance of cysteine cathepsins and explore their capacity to advance personalised and targeted medical interventions in oncology., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Asian New York City residents have the lowest cancer screening uptake across race and ethnicity. Few studies have examined screening differences across Asian ethnic subgroups in New York City., Methods: Cross-sectional survey data were analyzed using multivariable logistic and multinomial regression analyses. Differences among Chinese, Korean, and South Asian adults in breast, cervical, and colorectal cancer screening uptake; breast and colorectal cancer screening knowledge; and cancer fatalism were examined. Associations between breast and colorectal cancer screening knowledge and their uptake were also assessed along with associations between cancer fatalism and breast, cervical, and colorectal cancer screening uptake., Results: Korean women reported 0.52 times [95% confidence interval (CI), 0.31-0.89] lower odds of Pap test uptake compared with Chinese women; South Asian adults had 0.43 times (95% CI, 0.24-0.79) lower odds of colorectal cancer screening uptake compared with Chinese adults. Korean adults reported 1.80 times (95% CI, 1.26-2.58) higher odds of knowing the correct age to begin having mammograms compared with Chinese adults; South Asian adults had 0.67 times (95% CI, 0.47-0.96) lower odds of knowing the correct age to begin colorectal cancer screening compared with Chinese adults. Korean adults had 0.37 times (95% CI, 0.27-0.53) lower odds of reporting cancer fatalism compared with Chinese adults., Conclusions: Low cancer screening uptake among Asian American adults, low screening knowledge, and high cancer fatalism were found. Cancer screening uptake, knowledge, and fatalism varied by ethnic subgroup., Impact: Findings indicate the need for ethnicity-specific cultural and linguistic tailoring for future cancer screening interventions., (©2024 American Association for Cancer Research.)

Molecular imaging of cancer is a collaborative endeavor, uniting scientists and physicians from diverse fields. Such collaboration is actively developing and translating cutting-edge molecular imaging approaches to enhance the diagnostic landscape of human malignancies. The advent of positron emission tomography (PET) and PET imaging tracers has realized non-invasive target annotation and tumor characterization at the molecular level. In surgical procedures, novel imaging techniques, such as fluorescence or Cherenkov luminescence, help identify tumors and enhance surgical precision. Simultaneously, progress in imaging equipment, innovative algorithms, and artificial intelligence has opened avenues for next-generation cancer screening and imaging, augmenting the efficiency and accuracy of cancer diagnosis. In this review, we provide a panorama of molecular cancer imaging and ongoing developments in the field., Competing Interests: Declaration of interests W.W. is a consultant of Alpha Nuclide (Ningbo) Medical Technology Co., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Continuously improving cancer-specific survival puts a growing proportion of cancer patients at risk of major adverse cardiovascular events (MACE), but tailored tools for cardiovascular risk prediction remain unavailable., Objectives: To assess a broad panel of cardiovascular biomarkers and risk factors for the prediction of MACE and cardiovascular death in cancer patients., Methods: In total, 2192 patients with newly diagnosed or recurrent cancer were followed prospectively for the occurrence of 2-year MACE and 5-year cardiovascular death. Univariable and multivariable risk models were fit to assess independent associations of cardiovascular risk factors and biomarkers with adverse outcomes, and a risk score was developed., Results: Traditional cardiovascular risk factors and selected cancer types were linked to higher MACE risk. While levels of Lp(a), CRP, and GDF-15 did not associate with MACE, levels of ICAM-1, P-/E-/L-selectins, and NT-proBNP were independently linked to 2-year MACE risk. A clinical risk score was derived, assigning +1 point for male sex, smoking, and age of ≥60 years and +2 points for atherosclerotic disease, yielding a bootstrapped C-statistic of 0.76 (95% CI: 0.71-0.81) for the prediction of 2-year MACE. Implementation of biomarker data conferred improved performance (0.83, 95% CI: 0.78-0.88), with a simplified model showing similar performance (0.80, 95% CI: 0.74-0.86). The biomarker-enhanced and simplified prediction models achieved a C-statistic of 0.82 (95% CI: 0.71-0.93) and 0.74 (95% CI: 0.64-0.83) for the prediction of 5-year cardiovascular death., Conclusion: Biomarker-enhanced risk prediction strategies allow the identification of cancer patients at high risk of MACE and cardiovascular death. While external validation studies are ongoing, this first-of-its-kind risk score may provide the basis for personalized cardiovascular risk assessment across cancer entities., Competing Interests: Declaration of competing interests S.K. has received funding from the Jubiläumsstiftung SwissLife, the Lindenhof Foundation, the Novartis Foundation for Medical-Biological Research, the Swiss Heart Foundation, the Swiss Society of Cardiology, and the Theodor-Ida-Herzog-Egli Foundation, and materials and equipment from Roche Diagnostics. He has received travel support from the European Atherosclerosis Society, the European Society of Cardiology, the European Society of Clinical Investigation, Sphingotec GmbH, the 4TEEN4 Pharmaceuticals GmbH, and the PAM Theragnostics GmbH. L.L. is a co-inventor on the international patent WO/2020/226993 filed in April 2020. The patent relates to the use of antibodies that specifically bind IL-1α to reduce various sequelae of ischemia–reperfusion injury to the central nervous system. He further reports speaker fees from Daiichi Sankyo outside the submitted work. Moreover, he is counselor of the European Society for Clinical Investigation and has received fundings from the Novartis Foundation for Medical-Biological Research, the Swiss Heart Foundation, and the Italian Ministry of Health. T.M.S. declares funding from the Lindenhof Foundation. F.A.W. is supported by a grant of the Lindenhof Foundation (through S.K., T.F.L, and T.M.S.) and the Foundation for Cardiovascular Research—Zurich Heart House. He has received funding from the Fonds zur Förderung des akademischen Nachwuchses of the University of Zurich, the European Society of Cardiology, 4TEEN4 Pharmaceuticals GmbH, PAM Theragnostics GmbH, and Sphingotec GmbH outside the submitted work. Outside this work, I.P. reports honoraria for lectures from Bayer, BMS/Pfizer, and Sanofi and participation in advisory boards from Bayer and BMS/Pfizer. Outside this work, T.F.L. declares research and educational grants to the institution from Abbott, Amgen, AstraZeneca, Boehringer Ingelheim, Daiichi Sankyo, Menarini Foundation, Novartis, Novo Nordisk, Roche Diagnostics, Sanofi, and Vifor and honoraria from Amgen, Dacadoo, Daiichi Sankyo, Menarini Foundation, Novartis, Novo Nordisk, Philips, and Pfizer. He holds leadership positions at the European Society of Cardiology, Swiss Heart Foundation, and the Foundation for Cardiovascular Research—Zurich Heart House. C.A. reports honoraria for lectures from Bayer, Daiichi Sankyo, BMS/Pfizer, and Sanofi and participation in advisory boards from Bayer, Boehringer Ingelheim, Daiichi Sankyo, and BMS/Pfizer. F.Moik reports honoraria for lectures from BMS and MSD and participation in advisory boards from BMS. All other authors have no competing interests to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

HERC5, a vital protein in the HERC family, plays crucial roles in immune response, cancer progression, and antiviral defense. This bioinformatic study comprehensively assessed HERC5's significance across various malignancies by analyzing its gene expression, immune and molecular subtype expressions, target proteins, biological functions, and prognostic and diagnostic values in pan-cancer. We further examined its correlation with clinical features, co-expressed and differentially expressed genes, and prognosis in clinical subgroups, focusing on endometrial cancer (UCEC). Our findings showed that HERC5 RNA is expressed at low levels in most cancers and significantly differs across immune and molecular subtypes. HERC5 accurately predicts cancer and correlates with most cancer prognoses. In UCEC, HERC5 was significantly associated with age, hormonal status, clinical stage, treatment status, and metastasis. Elevated HERC5 expression was linked to worse progression-free interval, disease-specific survival, and overall survival in UCEC, particularly in diverse clinical subgroups. Significant differences in HERC5 expression were also observed in various human cancer cell line validations. In summary, HERC5 may be a critical biomarker for pan-cancer prognosis, progression, and diagnosis, as well as a promising new target for cancer therapy., (© 2024 The Author(s). APMIS published by John Wiley & Sons Ltd on behalf of Scandinavian Societies for Pathology, Medical Microbiology and Immunology.)

Polycystic ovary syndrome (PCOS) is a metabolic disease that affects the reproductive system, and its pathogenesis remains unresolved. Through the application of bioinformatics and molecular biology techniques, this study has identified a significant association between translocase of outer mitochondrial membrane 40 (TOMM40) and both PCOS and pan-cancers. The selection of PCOS biomarkers included TOMM40, which we found to be significantly decreased in the PCOS group both in vitro and in vivo, using molecular biology methods such as Western Blot as well as immunohistochemistry. Over-expression TOMM40 can rescue the effect on apoptosis rate and proliferation suppression induced by DHEA in KGN cells. TOMM40 as a biomarker for the diagnosis of PCOS. The pan-cancer analysis revealed an association between elevated TOMM40 expression in Uterine Corpus Endometrial Carcinoma and an unfavorable prognosis, while increased TOMM40 expression in six tumor types was linked to a favorable prognosis. Therefore, TOMM40 can be regarded as a promising biomarker for diagnosing both PCOS and pan-cancer., (© 2024. The Author(s).)

Background: Cancer rates in rural areas vary by insurance status, socioeconomic status, region, race, and ethnicity., Methods: California Cancer Registry data (2015-2019) were used to investigate the stage of diagnosis by levels of rurality for the five most common cancers. The percentage of residents in rural blocks within census tract aggregation zones was categorized into deciles up to 50%. Multivariable logistic regression was used to estimate associations with rurality, with separate models by cancer site, sex, race, and ethnicity (non-Hispanic White and Hispanic). Covariates included individual-level and zone-level factors., Results: The percentage of late-stage cancer diagnosis was 28% for female breast, 27% for male prostate, 77% for male lung, 71% for female lung, 60% for male colorectal, 59% for female colorectal, 7.8% for male melanoma, and 5.9% for female melanoma. Increasing rurality was significantly associated with increased odds of late-stage cancer diagnosis for female breast cancer (Ptrend < 0.001), male lung cancer (Ptrend < 0.001), female lung cancer (Ptrend < 0.001), and male melanoma (Ptrend = 0.01), after adjusting for individual-level and zone-level factors. The strength of associations varied by sex and ethnicity. For males with lung cancer, odds of late-stage diagnosis in areas with >50% rural population was 1.24 (95% confidence interval, 1.06-1.45) for non-Hispanic White patients and 2.14 (95% confidence interval, 0.86-5.31) for Hispanic patients, compared with areas with 0% rural residents., Conclusions: Increasing rurality was associated with increased odds for late-stage diagnosis for breast cancer, lung cancer, and melanoma, with the strength of associations varying across sex and ethnicity., Impact: Our findings will inform cancer outreach to these rural subpopulations., (©2024 American Association for Cancer Research.)

Cytopathology represents a well established diagnostic approach because of its limited cost, reliability, and minimal invasiveness with respect to other methodologies. The evolving complexity of the different classifications systems and the implementation of ancillary techniques to refine the diagnosis is progressively helping in the risk of malignancy stratification, and the adoption of next-generation sequencing techniques contributes to enrich this valuable tool with predictive information, which is always more essential in the tailored medicine era. The recent introduction of digital and computational pathology is further boosting the potentialities of cytopathology, aiding in the interpretation of samples to improve the cost effectiveness of large screening programs and the diagnostic efficiency within intermediate/atypical categories. Moreover, the adoption of artificial intelligence tools is promising to complement molecular investigations, representing a stimulating perspective in the cytopathology field. In this work, the authors tried to summarize the multifaceted nature of this complex and evolving field of pathology, synthesizing the most recent advances and providing the young pathologists' perspective on this fascinating world., (© 2024 American Cancer Society.)

Neurofibromatosis type 1 (NF1), Noonan syndrome, and related syndromes, grouped as RASopathies, result from dysregulation of the RAS-MAPK pathway and demonstrate varied multisystemic clinical phenotypes. Together, RASopathies are among the more prevalent genetic cancer predisposition syndromes and require nuanced clinical management. When compared with the general population, children with RASopathies are at significantly increased risk of benign and malignant neoplasms. In the past decade, clinical trials have shown that targeted therapies can improve outcomes for low-grade and benign neoplastic lesions but have their own challenges, highlighting the multidisciplinary care needed for such individuals, specifically those with NF1. This perspective, which originated from the 2023 American Association for Cancer Research Childhood Cancer Predisposition Workshop, serves to update pediatric oncologists, neurologists, geneticists, counselors, and other health care professionals on revised diagnostic criteria, review previously published surveillance guidelines, and harmonize updated surveillance recommendations for patients with NF1 or RASopathies., (©2024 American Association for Cancer Research.)

Family-history assessment can identify individuals above population-risk for cancer to enable targeted Screening, Prevention and Early Detection (SPED). The online patient-facing cancer Family History Questionnaire Service (cFHQS) is a digitalised, resource efficient tool for family history data capture to facilitate this. The capturing of digital data from cFHQS allows for data interrogation of patients referred to Clinical Genetics for the purposes of service improvement. Digital data from 4,044 cFHQS respondents over a three-year period was collected and interrogated with respect to the number and type of familial tumour diagnoses to enable service improvement and streamlining of referral pathways. 81% of colorectal and 71% of breast screening assessments were population- or moderate-risk. Most patients who completed cFHQS reported more than one diagnosis of cancer/tumour/polyps in their family. 2.5% of family history assessment patients had a second indication that required assessment that would have been missed if single tumour type assessment was undertaken. Implementation of an innovative, digital family history data collection pathway has allowed large scale interrogation of referral patterns and assessment outcomes to enable service development. The high volume of inappropriate referrals to Clinical Genetics for population and moderate risk patients highlighted the need for dedicated secondary care pathway provision for these patients. The use of cFHQS streamlined family history assessment allows for redistribution of resources to improve equity and access to genetic cancer risk assessment., (© 2024. The Author(s).)

Liquid biopsy technology provides invaluable support for the early diagnosis of tumors and surveillance of disease course by detecting tumor-related biomarkers in bodily fluids. Currently, liquid biopsy techniques are mainly divided into two categories: biomarker and label-free. Biomarker liquid biopsy techniques utilize specific antibodies or probes to identify and isolate target cells, exosomes, or molecules, and these techniques are widely used in clinical practice. However, they have certain limitations including dependence on tumor markers, alterations in cell biological properties, and high cost. In contrast, label-free liquid biopsy techniques directly utilize physical or chemical properties of cells, exosomes, or molecules for detection and isolation. These techniques have the advantage of not needing labeling, not impacting downstream analysis, and low detection cost. However, most are still in the research stage and not yet mature. This review first discusses recent advances in liquid biopsy techniques for early tumor diagnosis and disease surveillance. Several current techniques are described in detail. These techniques exploit differences in biomarkers, size, density, deformability, electrical properties, and chemical composition in tumor components to achieve highly sensitive tumor component identification and separation. Finally, the current research progress is summarized and the future research directions of the field are discussed., (© 2024 The Author(s). Small published by Wiley‐VCH GmbH.)

Background: Currently the clinicopathologic significance of psammoma bodies in cytology specimens are not completely understood, including types of cytology specimens and pathologic conditions frequently associated with this unique cytologic feature. In this study, we undertook a retrospective approach to review the specimen types, cytology preparations, patient characteristics, organs or tissues involved and differential diagnoses in cytology specimens with the finding of psammoma bodies., Methods: Cytology cases with the finding of psammoma bodies from January 2004 to December 2022 were retrieved from our institution's pathology databases, and their clinicopathological features were reviewed., Results: A total of 78 cytology specimens with the finding of psammoma bodies were recorded in our CoPath system. The mean age at diagnosis was 59 years. The patient group showed female gender predominancy (90%). FNA specimens comprised about 38.5% of total cases. Other common specimen types were body cavity fluids (38.5%), including pleural effusion and peritoneal fluid, and about 20.5% of the cases were pelvic washing performed during gynecologic surgeries. Most cytology cases with psammoma bodies had a malignant diagnosis (69%). About 18% of the cases were in the indeterminate diagnostic categories, with 12% suspicious for malignancy and 6% of the cases with atypical cells. About 5% of cases were placed in the neoplastic category, while 8% of cases were negative for malignancy. About 79% of peritoneal cytology with psammoma bodies were neoplastic and mostly gynecologic tumors. Pleural fluids with psammoma bodies were very likely to be malignant and involved by serous carcinoma (15 of 16 cases, 94%). Papillary thyroid carcinoma was the second most common malignancy in our series, present in about 53% of thyroid cytologies with the finding of psammoma bodies., Conclusion: Our study showed that psammoma bodies in cytology preparations were more often associated with malignancies in our study of 78 cytology specimens (69%). The most sampled location in our study was peritoneal cavity, followed by pleural cavity, thyroid, lymph nodes, neck masses, and omentum. The clinicopathologic value of psammoma bodies in predicting malignancy varies depending on locations and specimen types., (© 2024 Wiley Periodicals LLC.)

Introduction: Current literature lacks data regarding the influence of serous fluid volume (SFV) on next-generation sequencing (NGS) performed on malignant cases. In this study, we highlight the impact of SFV and other parameters influencing the outcome of NGS analysis., Materials and Methods: We evaluated 827 samples of serous fluids from 607 patients. Of these, 72 samples underwent NGS analysis. Effusion volume, tumor cellularity, DNA, and RNA quality metrics, as well as clinicopathologic and molecular data were evaluated. Pleural fluid accounted for 56.3% of the fluid samples collected. The most common primary tumor site was gastrointestinal/pancreatobiliary, adenocarcinoma was the most common histologic type. Overall mean volume was 293 mL. The mean Qubit DNA of the 72 effusion samples that underwent NGS analysis was 14.3 ng/μL and mean Qubit RNA was 28.2 ng/μL. The mean Qubit DNA concentration increases in SFV up to 100 mL only., Results: No correlation exists between SFV and mean tumor cellularity. In addition, 74.6% (50 of 67) of sequenced samples showed oncogenic drivers; KRAS was the most common driver followed by EGFR. Three cases displayed ALK fusions, and 1 case displayed NTRK1 fusion. The DNA yield is higher in SFV of 100 mL as a cutoff. Beyond 100 mL, there is no impact of SFV on DNA yield. SFV does not impact RNA yield and mean tumor cellularity. Effusion samples should be submitted for molecular testing despite low tumor cellularity., Conclusions: Our results as a pilot study are important in optimization of SFV for both diagnosis as well as NGS analysis for improving management., (Copyright © 2024 American Society of Cytopathology. Published by Elsevier Inc. All rights reserved.)

The red cell distribution width (RDW) is a standard variable reported in the complete blood count. It has been found to have a consistent relationship to life expectancy in older individuals, prognosis in patients with cardiovascular disease, outcome in those with hematological and non-hematological neoplasms and in a variety of medical circumstances such as non-cardiovascular or cancer related critical illness and postoperative outcome from various procedures. This report reviews some of the key medical publications establishing these relationships with RDW. The precise pathobiological processes that explain the predictive value of the RDW in this wide array of circumstances or why an alteration in erythropoiesis (exaggerated red cell size variation) occurs is uncertain. The possible role of inflammation has been one hypothesis considered, but not established., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Liquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community on which methods are the most effective or how to process the data. To circumvent this, we performed a large-scale study using various machine-learning techniques. First, we took a closer look at existing datasets and filtered out some patients to assert data collection quality. The final data collection included platelet RNA samples acquired from 1397 cancer patients (17 types of cancer) and 354 asymptomatic, presumed healthy, donors. Then, we assessed an array of different machine-learning models and techniques (e.g., feature selection of RNA transcripts) in pan-cancer detection and multiclass classification. Our results show that simple logistic regression performs the best, reaching a 68% cancer detection rate at a 99% specificity level, and multiclass classification accuracy of 79.38% when distinguishing between five cancer types. In summary, by revisiting classical machine-learning models, we have exceeded the previously used method by 5% and 9.65% in cancer detection and multiclass classification, respectively. To ease further research, we open-source our code and data processing pipelines (https://gitlab.com/jopekmaksym/improving-platelet-rna-based-diagnostics), which we hope will serve the community as a strong baseline., (© 2024 The Author(s). Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)