Early detection of cancer: past, present, and future

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.

Mitochondria-targeting fluorescent probe with a pH/viscosity response for assisted detection of non-alcoholic fatty liver in mice

Cancer cells are characterized by high viscosity, low pH and high levels of reactive oxygen species. Both pH and viscosity are key indicators which can respond to the microenvironment of cancer cells and are also important indicators for monitoring fatty liver. Based on this, we have constructed a hemicarbocyanine fluorescent probe (HTC) possessing a D-D'(π)-π-A structure using phenol as an electron donor (D), a thiophene moiety as an electron donor and a partial π bridge. The fluorescent probe HTC exhibits pH-responsive properties, and the fluorescence intensity of the probe at 627 nm gradually decreases and the fluorescence at 720 nm gradually increases with the increase of pH for pH = 7 to 10.5. Meanwhile, with an increase of viscosity the fluorescent probe HTC exhibited gradually enhanced fluorescence at 627 nm, thus revealing a response to the change of viscosity. In addition, the fluorescent probe HTC can target mitochondria for cellular fluorescence imaging, and co-localized fluorescence imaging with the commercial mitochondrial probe Mito-Tracker Green with a Pearson's coefficient of 0.91. We have utilized the properties of the fluorescent probe HTC, which exhibits a pH and viscosity response, and have applied it to monitor the change of pH or viscosity in cells and differentiate between normal and cancerous cells, as well as for the identification of non-alcoholic fatty liver mice. In addition, the probe is easily metabolized in mice and has good biocompatibility.

Application of ATR-FTIR spectroscopy and multivariate statistical analysis in cancer diagnosis

Lung cancer is one of the most prevalent and lethal malignant tumors worldwide. Currently, clinical diagnosis primarily relies on chest X-ray examinations, histopathological analysis, and the detection of tumor markers in blood. However, each of these methods has inherent limitations. The current study aims to explore novel diagnostic approaches for lung cancer by employing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in conjunction with multiple machine learning models. Fourier transform infrared spectroscopy can detect subtle differences in the material structures that reflect the carcinogenic process between lung cancer tissues and normal tissues. By applying principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to analyze infrared spectral data, these subtle differences can be amplified. The study revealed that the combination of spectral bands within the 3500-3000 cm-1 and 1600-1500 cm-1 ranges is particularly significant for differentiating between the two groups. Three classification models-Support Vector Machine (SVM), k-Nearest Neighbor (kNN), and Linear Discriminant Analysis (LDA)-were constructed for spectral analysis of various band combinations. The results indicated that in detecting lung cancer samples, the combination of the 3500-3000 cm-1 and 1600-1500 cm-1 bands offers significant advantages. The analysis of the receiver operating characteristic (ROC) curve demonstrated that the area under the curve (AUC) exceeded 0.95 for all models, with the LDA model achieving an accuracy rate of 99.4% in identifying lung cancer patients compared to healthy individuals. The findings suggest that the integration of ATR-FTIR spectroscopy with multiple machine learning models represents a promising auxiliary diagnostic method for clinical lung cancer diagnosis, enabling detection at the molecular level.

Penalized landmark supermodels (penLM) for dynamic prediction for time-to-event outcomes in high-dimensional data

BACKGROUND

To effectively monitor long-term outcomes among cancer patients, it is critical to accurately assess patients' dynamic prognosis, which often involves utilizing multiple data sources (e.g., tumor registries, treatment histories, and patient-reported outcomes). However, challenges arise in selecting features to predict patient outcomes from high-dimensional data, aligning longitudinal measurements from multiple sources, and evaluating dynamic model performance.

METHODS

We provide a framework for dynamic risk prediction using the penalized landmark supermodel (penLM) and develop novel metrics ([Formula: see text] and [Formula: see text]) to evaluate and summarize model performance across different timepoints. Through simulations, we assess the coverage of the proposed metrics' confidence intervals under various scenarios. We applied penLM to predict the updated 5-year risk of lung cancer mortality at diagnosis and for subsequent years by combining data from SEER registries (2007-2018), Medicare claims (2007-2018), Medicare Health Outcome Survey (2006-2018), and U.S. Census (1990-2010).

RESULTS

The simulations confirmed valid coverage (~ 95%) of the confidence intervals of the proposed summary metrics. Of 4,670 lung cancer patients, 41.5% died from lung cancer. Using penLM, the key features to predict lung cancer mortality included long-term lung cancer treatments, minority races, regions with low education attainment or racial segregation, and various patient-reported outcomes beyond cancer staging and tumor characteristics. When evaluated using the proposed metrics, the penLM model developed using multi-source data ([Formula: see text]of 0.77 [95% confidence interval: 0.74-0.79]) outperformed those developed using single-source data ([Formula: see text]range: 0.50-0.74).

CONCLUSIONS

The proposed penLM framework with novel evaluation metrics offers effective dynamic risk prediction when leveraging high-dimensional multi-source longitudinal data.

The impact of educational intervention based on the theory of planned behavior on preventive behaviors for gastric cancer in obese and smoking individuals

BACKGROUND

Gastric cancer remains a significant global health issue due to its aggressive nature and high heterogeneity, making early detection and prevention critical. Obesity and smoking are established risk factors that significantly contribute to the development of gastric cancer. Despite the clear links between these risk factors and the disease, there is a lack of targeted educational interventions that address these behaviors. This study aims to fill this gap by investigating the impact of an educational intervention based on the Theory of Planned Behavior (TPB) on promoting preventive behaviors for gastric cancer among obese and smoking individuals.

METHODS

This quasi-experimental study was conducted in 2021-2022 on 150 obese or overweight individuals, more than 25 years old who smoked (cigarettes and hookah) in Fasa city, Iran. From six urban health centers, two centers were randomly selected (one as the experimental group and the other as the control group). Data collection tools included a demographic characteristics questionnaire based on the TPB model (a researcher-made questionnaire). Based on pre-test results, the educational intervention for the experimental group included 12 educational sessions for 50 min, following the TPB model, through lectures, Question and Answers, group discussions, practical demonstrations, video clips, and PowerPoint presentations. The questionnaires were completed by both groups before and six months after the intervention. Data were analyzed using SPSS 22 and descriptive and analytical statistical methods (paired t- test, McNemar test, Chi-square test, and independent t-test) (p < 0.05).

RESULTS

The results showed no significant difference between the two groups before the educational intervention. However, six months after the intervention, the experimental group showed a significant increase in TPB model cues (awareness, attitude, subjective norms, perceived behavioral control, behavioral intention, and behavior) (P < 0.001).

CONCLUSION

The findings of the present study indicate that the educational intervention based on the TPB model is useful in improving gastric cancer screening and preventive behaviors. It can also be used in planning and implementing appropriate programs to prevent and treat this disease.

Clinicopathological and prognostic significance of exosomal PD-L1 in cancer therapy

AIM

The exosomal programmed death ligand-1(exoPD-L1) has recently become a topic of interest in the field of oncology. But the prognostic role of exoPD-L1 in cancer patients is inconsistent across previous studies. Therefore, a quantitative meta-analysis was performed to evaluate the prognostic and clinicopathological value of exoPD-L1 in cancer patients.

MATERIALS AND METHODS

Twenty eligible studies were included in this study. The relationship between baseline level of exoPD-L1 and clinicopathological features, therapeutic response, overall survival (OS) and progression-free survival (PFS) was evaluated.

RESULTS

Pooled analysis indicated that high level of exoPD-L1 was significantly associated with higher tumor stage, positive lymph node metastasis, and advanced TNM stage. Elevated exoPD-L1 was associated with short OS [HR = 1.80 (1.27-2.55), p = 0.001]. In the subgroup analysis, high-level exoPD-L1 was consistently associated with poor OS in sample source, detection method, and lymphoma patients. Moreover, elevated exoPD-L1 was predictive of worse PFS [HR = 1.28 (1.13-4.18), p = 0.000]. In addition, a striking difference between cancer patients and healthy donors was observed in the level of exoPD-L1.

CONCLUSION

exoPD-L1 is an original and effective liquid biomarker for cancer patients. However, large-scale, prospective investigations are still needed to confirm our findings.

Combining anti-checkpoint immunotherapies and cancer vaccines as a novel strategy in oncological therapy: A review

The field of cancer immunotherapy has experienced remarkable advancements in the treatment of human cancers over recent decades. Therapeutic cancer vaccines have been employed to elicit antitumor immune responses through the generation of specific reactions against tumor-associated antigens. Although preclinical studies have demonstrated hopeful results and at least one product is approved for clinical use, the overall efficacy of cancer vaccines remains restricted. The co-administration of anti-checkpoint antibodies alongside cancer vaccines is proposed as a potential strategy to enhance the clinical efficacy of immunotherapies. Among the various anti-checkpoint agents, monoclonal antibodies targeting CD127, OX40, and CD40 have been further investigated in combined administration with cancer vaccines, demonstrating a synergistic impact on disease outcomes in both animal models and human subjects. This combinational approach has been shown to suppress tumor regression, improve survival rates, and promote the efficacy of cancer vaccines via multiple mechanisms, including the augmentation of generation, activation, and expansion of CD8+ T cells, as well as the production of tumor-inhibitory cytokines. Importantly, the impact of the concurrent administration of anti-checkpoint agents and cancer vaccines surpass those observed with the sole vaccine, indicating that this strategy may offer significant advantages for clinical application in cancer patients. In this review, we aim to provide a comprehensive overview of the significance and therapeutic potential of the combined administration of checkpoint agonist/antagonist antibodies and cancer vaccines for human tumors.

An Interdisciplinary Perspective on Improving Cancer Care in the State of Mississippi as an Example of Cancer Care Improvements in the Global South

Cancer disparities, a critical public health issue, particularly in states such as Mississippi, where socioeconomic factors significantly influence health outcomes, require our collective attention. This paper delves into the multifaceted nature of cancer disparities through a macro-level analysis of cancer data, specifically focusing on Mississippi as a microcosm of broader national and global trends. Two key indices, the Socio-Demographic Index (SDI) and the Social Deprivation Index (SDeI), provide valuable insights. The former offers a macro-level understanding of the socioeconomic factors that shape health and cancer outcomes. The latter quantifies disadvantages in small areas, identifying regions that need scientific, policy, and administrative support. The poor health care and cancer care (CC) outcomes in Mississippi are well documented and detailed here. However, SDI and SDeI data are not yet available in Mississippi. With biological, technological, and clinical research design advancements and other new innovative strategies emerging in the past decade in CC, a 'leapfrogging' of CC outcomes in Mississippi is within our reach. To achieve this goal, an interdisciplinary approach (IDA) addressing and solving the challenges faced in Mississippi is required. The IDA team must include disciplines that can determine SDI and SDeI for Mississippi and tie those findings to successfully apply new technological advances and innovations efficiently and cost-effectively by building infrastructure and developing implementation strategies. This can serve as a pilot demonstration project that will also help other similar regions within the United States, as well as the Global South.

α1-Acid Glycoprotein with Highly Fucosylated Glycans as a Potential Diagnostic Marker for Early Detection of Hepatobiliary and Pancreatic Cancers

Background: Previously, we reported elevated levels of fucosylated α1-acid glycoprotein (fAGP) in plasma samples from patients with diverse types of cancers. Accordingly, fAGP was assumed to be a potential biomarker for the early detection of cancers. Methods: The fAGP level was retrospectively measured in preoperative plasma samples from 213 patients with either hepatic, biliary tract, or pancreatic cancer and was analyzed together with levels of six existing tumor markers determined as reference standards. Results: When the cutoff value was set at 25.45 U/μg, elevated levels of fAGP were significantly observed in cancer patients. The sensitivity, specificity, and accuracy for the detection of malignancy in these diseases were determined to be 70.79, 51.72, and 68.12, respectively. In contrast, all the tumor markers exhibited low sensitivity and accuracy, even though they commonly had extremely high (≥80%) specificity. Further, a significant number of patients in both early and advanced clinical stages were found to be false negative in these tumor makers but were found to be positive in the fAGP level. A dramatic improvement in the diagnosis by tumor markers in such patients with all clinical stages was found by the determination of the fAGP level. This indicated that fAGP could serve to correct false-negative diagnosis with tumor markers. Conclusions: It is believed that fAGP could be a relevant, unique, and highly sensitive biomarker for early diagnosis of hepatobiliary and pancreatic cancers.

Burden of melanoma in China and its provinces from 1990 to 2021: an analysis for the Global Burden of Disease Study 2021

Background

The incidence of melanoma in China has been increasing over the past few decades. This study aimed to investigate the burden of melanoma at both national and subnational level in China, where the population is rapidly aging.

Methods

The annual melanoma data from 1990 to 2021 was collected from the Global Burden of Disease (GBD) 2021 China subnational study. Number of cases and age-standardized rates were estimated for incidence, mortality, prevalence, disability-adjusted life-years (DALYs) of melanoma by age and sex at subnational level with 33 province-level administrative units. Joinpoint regression model was used to evaluate the trends in disease burdens attributable to melanoma across time. A decomposition method was used to attribute changes in total deaths and DALYs to three explanatory components: population growth, population aging, and change of age-specific rates.

Results

Over the past 30 years, the age-standardized incidence rate (ASIR) of melanoma in China has shown an upward trend. The ASIR of melanoma in 2021 was 0.7 per 100,000 (95%UI 0.4-0.9), representing an increase of 89.2% (95% UI: 14.7-157.9%) from 1990. Among younger adults aged <60 years, melanoma was more common in men, whereas among older adults who were aged >60 years, it was more common in women. The ASIR was higher in the coastal provinces in 2021 and the age-standardized rates (ASR) of DALYs was generally higher in the western provinces. Total numbers of death and DALYs of melanoma increased over the study period, mainly driven by population aging in China.

Conclusion

China has experienced a substantial increase in the burden of melanoma from 1990 to 2021. It is beneficial to develop more targeted strategies for older adults populations, especially for women, to reduce the melanoma burden throughout China, particularly in some coastal and western provinces.

Liquid biopsy in lung cancer: The role of circulating tumor cells in diagnosis, treatment, and prognosis

Despite numerous therapeutic advancements, such as immune checkpoint inhibitors, lung cancer continues to be the leading cause of cancer-related mortality. Therefore, the identification of cancer at an early stage is becoming a significant subject in contemporary oncology. Despite significant advancements in early detection tactics in recent decades, they continue to provide challenges because of the inconspicuous symptoms observed during the early stages of the primary tumor. Presently, tumor biomarkers and imaging techniques are extensively employed across different forms of cancer. Nevertheless, every approach has its own set of constraints. In certain instances, the detriments outweigh the advantages. Hence, there is an urgent need to enhance early detection methods. Currently, liquid biopsy is considered more flexible and not intrusive method in comparison to conventional test for early detection. Circulating tumor cells (CTCs) are crucial components of liquid biopsy and have a pivotal function in the spread and formation of secondary tumors. These indicators show great promise in the early identification of cancer. This study presents a comprehensive examination of the methodologies employed for the isolation and enrichment of circulating tumor cells (CTCs) in lung cancer. Additionally, it explores the formation of clusters of CTCs, which have a pivotal function in facilitating the effective dissemination of cancer to distant organs. In addition, we discuss the importance of CTCs in the detection, treatment, and prognosis of lung cancer.

The role of circRNAs in resistance to doxorubicin

Doxorubicin is an anthracyline recognized as an antitumor antibiotic agent. It is widely used in the chemotherapeutic regimens in different types of cancers. Resistance to doxorubicin is a major clinical obstacle and main cause of failure in cancer chemotherapy. Among different mechanisms involved in this process, the role of epigenetic factors has been highlighted. Circular RNAs (circRNAs) have a prominent role in this process. Here, we summarize the recent findings on the role of circRNAs in doxorubicin resistance, particularly in breast cancer and osteosarcoma and underscore their clinical application as potential biomarkers and therapeutic targets in this field. Recognition of the underlying mechanism of circRNAs involvement in doxorubicin resistance will expand our understanding of chemoresistance establishment and may provide a prospect to develop circRNA-based predictive biomarkers of chemotherapy or therapeutic strategies for cancer patients.

Recent advances in the CRISPR/Cas system-based visual detection method

Currently, various infectious pathogens and bacterial toxins as well as heavy metal pollution pose severe threats to global environmental health and the socio-economic infrastructure. Therefore, there is a pressing need for rapid, sensitive, and convenient visual molecular detection methods. The rapidly evolving detection approach based on clustered regularly interspaced short palindromic repeats (CRISPR)/associated nucleases (Cas) has opened a new frontier in the field of molecular diagnostics. This paper reviews the development of visual detection methods in recent years based on different Cas and analyzes their advantages and disadvantages as well as the challenges of future research. Firstly, different CRISPR/Cas effectors and their working principles in the diagnosis of various diseases are briefly reviewed. Subsequently, the article focuses on the development of visual readout signals in point-of-care testing using laboratory-based CRISPR/Cas technology, including colorimetric, fluorescence, and lateral flow analysis. Finally, the challenges and prospects of visual detection methods based on CRISPR/Cas technology are discussed.

Improving performance in colorectal cancer histology decomposition using deep and ensemble machine learning

In routine colorectal cancer management, histologic samples stained with hematoxylin and eosin are commonly used. Nonetheless, their potential for defining objective biomarkers for patient stratification and treatment selection is still being explored. The current gold standard relies on expensive and time-consuming genetic tests. However, recent research highlights the potential of convolutional neural networks (CNNs) to facilitate the extraction of clinically relevant biomarkers from these readily available images. These CNN-based biomarkers can predict patient outcomes comparably to golden standards, with the added advantages of speed, automation, and minimal cost. The predictive potential of CNN-based biomarkers fundamentally relies on the ability of CNNs to accurately classify diverse tissue types from whole slide microscope images. Consequently, enhancing the accuracy of tissue class decomposition is critical to amplifying the prognostic potential of imaging-based biomarkers. This study introduces a hybrid deep transfer learning and ensemble machine learning model that improves upon previous approaches, including a transformer and neural architecture search baseline for this task. We employed a pairing of the EfficientNetV2 architecture with a random forest classification head. Our model achieved 96.74% accuracy (95% CI: 96.3%-97.1%) on the external test set and 99.89% on the internal test set. Recognizing the potential of these models in the task, we have made them publicly available.

Early cancer screening surveillance in one medical center of China

Objectives

Cancer screening aims to detect and treat malignant lesions at an early stage and to prolong patients' lifetime. There is still a lack of effective cancer screening programs in China. We initiated a screening project in 2018 and this study presented the cancer screening status in China.

Methods

We conducted a cross-sectional study in one cancer-care medical center of China. The screening program included routine blood tests, plasma tumor markers, gastric endoscopy, colonoscopy, ultrasound, and computed tomography (CT) scans. Screening results were presented as sensitivity, specificity and positive predictive values (PPVs).

Results

Twenty-three (1.46%) out of 1,576 participants were eventually diagnosed with malignant tumors or high-grade intraepithelial neoplasia (HGIN). A family history of malignancy (78.26% in diagnosed cancer and HGIN vs. 46.36% in the others) was the only statistically significant parameter associated with cancer detection (p = 0.002). None of the common tumor markers were associated with the cancers screened. Except for colonoscopy (50.00%) and ultrasound for renal cancer (66.67%), the sensitivities of most screening methods were 100%. The specificities of all the screening means were above 96%. Most PPVs ranged from 30-60%.

Conclusion

We emphasized risk stratification for early cancer screening, such as a family history of cancer. The survey illustrated that gastric endoscopy, colonoscopy, ultrasound, and lung CT for early cancer screening had high specificity, reasonable sensitivity, and PPV. We anticipated this report would motivate larger-sample studies to estimate the risk-to-benefit ratio of cancer screening and urge the establishment of a native Chinese screening project and even guidelines.

Establishment of a multi-line immunochromatography based on magnetic nanoparticles for simultaneous screening of multiple biomarkers

Biomarkers screening is a benefit approach for early diagnosis of major diseases. In this study, magnetic nanoparticles (MNPs) have been utilized as labels to establish a multi-line immunochromatography (MNP-MLIC) for simultaneous detection of carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA 19-9), and alpha-fetoprotein (AFP) in a single serum sample. Under the optimal parameters, the three biomarkers can be rapidly and simultaneously qualitative screening within 15 min by naked eye. As for quantitative detection, the MNP-MLIC test strips were precisely positioned and captured by a smartphone, and signals on the test and control lines were extracted by ImageJ software. The signal ratio of test and control lines has been calculated and used to plot quantitative standard curves with the logarithmic concentration, of which the correlation coefficients are more than 0.99, and the limit of detection for CEA, CA 19-9, and AFP were 0.60 ng/mL, 1.21 U/mL, and 0.93 ng/mL, respectively. The recoveries of blank serum were 75.0 ~ 112.5% with the relative standard deviation ranging from 2.5 to 15.3%, and the specificity investigation demonstrated that the MNP-MLIC is highly specific to the three biomarkers. In conclusion, the developed MNP-MLIC offers a rapid, simple, accurate, and highly specific method for simultaneously detecting multiple biomarkers in serum samples, which provides an efficient and accurate approach for the early diagnosis of diseases.

Realization of high-performance biosensor through sandwich analysis utilizing weak value amplification

A label-free optical sandwich immunoassay sensor, utilizing weak value amplification and total internal reflection, was devised for real-time, high-sensitivity analysis and detection of low-concentration targets. 3D printed channels and sodium chloride solution were employed to ensure reproducibility, reliability, and stability of the measurements for calibration. The sandwich structure demonstrated enhanced responsiveness in the proposed optical biosensor through a comparative analysis of the direct assay and sandwich assay for detecting alpha-fetoprotein (AFP) at the same concentration. By optimizing the binding sequences of the coating antibody, target, and detection antibody in the sandwich method, a more suitable sandwich sensing approach based on weak value amplification was achieved. With this approach, the limit of detection (LOD) of 6.29 ng/mL (pM level) for AFP in PBS solution was achieved. AFP testing and regeneration experiments in human serum have proved the feasibility of our methods in detecting complex samples and the reusability of sensing chips. Additionally, the method demonstrated excellent selectivity for unpaired antigens. The efficacy of this methodology was evaluated by simultaneously detecting AFP, carcinoembryonic antigen (CEA), and CA15-3 on a singular sensor chip. In conclusion, the label-free sandwich immunoassay sensing scheme holds promise for advancing the proposed optical sensors based on weak value amplification in early diagnosis and prevention applications. Compared to other biomarker detection methods, it will be easier to promote in practical applications.

Modeling the population health impact of incorporating a multi-cancer early detection (MCED) test to existing cancer screening among immunocompromised individuals

OBJECTIVE

To assess the screening efficiency of an multi-cancer early detection (MCED) test added to standard of care (SoC) screening, compared to SoC screening alone, among immunocompromised individuals, and to estimate the diagnostic workup costs associated with positive screening results.

METHODS

We estimated the potential impact of cancer screening among immunocompromised individuals aged 50-79 years within the University of Utah Health system who underwent a stem cell/solid organ transplant or were diagnosed with a primary or secondary immunodeficiency disorder between January 2000 and February 2018. We derived cancer incidence rates from the Huntsman Cancer Institute Tumor Registry, and screening performance of SoC screening and an MCED test from published literature. Outcomes of screening efficiency included the true-positive to false-positive (TP:FP) ratio, diagnostic yield (DY), and cancer detection rate (CDR) for SoC screening alone and an incremental MCED test. Scenario and probabilistic sensitivity analyses were conducted.

RESULTS

Among 4932 immunocompromised individuals aged 50-79 years, we estimated that 2595 tests would be done under SoC screening and assumed that all individuals received an additional MCED test. Adding an MCED test to SoC screening substantially improved screening efficiency (TP:FP = 1:1, DY = 5.15/1000 tests, CDR = 42.0%), compared to SoC screening alone (TP:FP = 1:99, DY = 1.23/1000 tests, CDR = 5.3%), assuming an MCED test with 100% uptake. Our findings were also robust to parameter uncertainty.

CONCLUSION

Adding an MCED test to complement existing screening may be a highly efficient strategy to increase the detection of cancers among immunocompromised individuals. These results could help to improve cancer prevention and detection efforts among individuals with multiple cancer risk factors.

Second primary malignancies in women with breast cancer

BACKGROUND

Increased screening and treatment advancements have resulted in improved survival rates in women with breast cancer (BC). However, recent data suggests these women have elevated risk of developing a second primary malignancy (SPM) compared to the general population. Limited data exists on factors associated with BC patients developing a SPM.

METHOD

A retrospective review of a prospective single institution database (1990-2016) identified 782 patients with a history of BC. One hundred and ninety-four BC patients developed a SPM. Clinicopathologic and treatment characteristics were analyzed.

RESULTS

Of the 194 patients (24.8%) who developed a SPM, 56 (28.9%) BC patients were <50 years old (range: 24-87 years). Two-thirds (64.9%) had at least one first or second degree relative with a malignancy (no relatives-35.1%; ≥1 relative-62.9%). Most patients had invasive ductal carcinoma (n = 117, 60.3%) or ductal carcinoma in situ (n = 39, 20.1%). Twenty-two patients (11.3%) had pathogenic genetic mutations. Mean time to developing a SPM was 8.9 years (range: 4 months-50 years). Eighty (47.6%) patients received chemotherapy with 91 (54.5%) completing radiation. The most common SPMs were breast (22%), melanoma (17.8%), gynecologic (14.1%), colorectal (12.6%), hematologic (8.9%), and sarcoma (6.5%). Most breast tumors were estrogen receptor (ER) (n = 99, 78.0%) or progesterone receptor (PR) positive (n = 87, 73.1%) but not HER2-neu positive (n = 13, 14.0%).

CONCLUSION

Most BC patients who developed a SPM had ER/PR positive tumors and a family history of malignancy, with most <50 years old. Although chemotherapy and radiation increase cancer risk, there were an equal number of patients with SPMs who did or did not receive either treatment. Most SPMs were breast, soft tissue, gynecologic, hematologic, or colorectal. BC patients should be followed closely given an elevated propensity for developing SPMs.

A roadmap for empowering cardiovascular disease patients: a 5P-Medicine approach and technological integration

This article explores the multifaceted concept of cardiovascular disease (CVD) patients' empowerment, emphasizing a shift from compliance-oriented models to active patient participation. In recognizing that cardiovascular disease is a paramount global health challenge, this study illuminates the pressing need for empowering patients, underscoring their role as active participants in their healthcare journey. Grounded in 5P-Medicine principles-Predictive, Preventive, Participatory, Personalized, and Precision Medicine-the importance of empowering CVD patients through analytics, prevention, participatory decision making, and personalized treatments is highlighted. Incorporating a comprehensive overview of patient empowerment strategies, including self-management, health literacy, patient involvement, and shared decision making, the article advocates for tailored approaches aligned with individual needs, cultural contexts, and healthcare systems. Technological integration is examined to enhance patient engagement and personalized healthcare experiences. The critical role of patient-centered design in integrating digital tools for CVD management is emphasized, ensuring successful adoption and meaningful impact on healthcare outcomes. The conclusion proposes vital research questions addressing challenges and opportunities in CVD patient empowerment. These questions stress the importance of medical community research, understanding user expectations, evaluating existing technologies, defining ideal empowerment scenarios, and conducting a literature review for informed advancements. This article lays the foundation for future research, contributing to ongoing patient-centered healthcare evolution, especially in empowering individuals with a 5P-Medicine approach to cardiovascular diseases.

Benefits and Harms of Interception and Early Detection of Cancer

Strategies for early detection and interception of cancer are based on 2 synergistic elements: proactive search for asymptomatic cancer, precancer, or cancer predisposition and proactive disruption of cancer evolution. Benefits and harms of both these elements will vary widely depending on the screened populations, the types of cancers targeted, the detection modalities, and the health care delivery approaches following diagnosis. This article attempts to identify common elements that can inform the evaluation of alternative strategies across many of these scenarios.

Recent developments in cancer diagnosis and treatment using nanotechnology

The article provides an insightful overview of the pivotal role of nanotechnology in revolutionizing cancer diagnosis and treatment. It discusses the critical importance of nanoparticles in enhancing the accuracy of cancer detection through improved imaging contrast agents and the synthesis of various nanomaterials designed for oncology applications. The review broadly classifies nanoparticles used in therapeutics, including metallic, magnetic, polymeric, and many other types, with an emphasis on their functions in drug delivery systems for targeted cancer therapy. It details targeting mechanisms, including passive and intentional targeting, to maximize treatment efficacy while minimizing side effects. Furthermore, the article addresses the clinical applications of nanomaterials in cancer treatment, highlights prospects, and addresses the challenges of integrating nanotechnology into cancer treatment.

Biomarkers in Cancer Screening: Promises and Challenges in Cancer Early Detection

Cancer continues to be one the leading causes of death worldwide, primarily due to the late detection of the disease. Cancers detected at early stages may enable more effective intervention of the disease. However, most cancers lack well-established screening procedures except for cancers with an established early asymptomatic phase and clinically validated screening tests. There is a critical need to identify and develop assays/tools in conjunction with imaging approaches for precise screening and detection of the aggressive disease at an early stage. New developments in molecular cancer screening and early detection include germline testing, synthetic biomarkers, and liquid biopsy approaches.

Effectiveness of an ultrasound basic cancer training program through on-site training and virtual case discussions in rural Tanzania: a proof-of-concept study

Introduction

Cancer rates are rising in low- and middle-income countries. While point-of-care ultrasound is now available globally and could serve to mitigate against this rise, its use in diagnosing cancers is inconsistent in lower-resourced healthcare contexts. This proof-of-concept study investigates the feasibility of an ultrasound training concept in a low-resource setting. It evaluates whether this educational concept led to improved knowledge and application of ultrasound diagnostics, cancer screening and staging and patient care.

Material and methods

The curriculum was developed through expert exchange and is based on the World Health Organisation's Manual of Diagnostic Ultrasound. It consisted of two didactic components: an on-site training phase across 5 days for a total of 24 hours, and a digital follow-up phase involving the meeting of a bi-weekly tumor board online. The learning objectives of the on-site training were normal imaging and recognition of common pathologies of the abdominal organs, vessels, lymph nodes, female breasts and lungs. The virtual tumour boards met to discuss cases and ultrasound findings, thus aiding continuing professional development after the training sessions had concluded. The face-to-face course component was accompanied by tests given before and after training as well as an evaluation sheet (Likert-scale with 1 = 'completely/very good' and 7 'not at all/very poor').

Results

Of 20 participants from a rural hospital in Tanzania, a total of 16 were included in the analysis (clinical officers n = 6; medical officers n = 10). A significant increase in knowledge (p < 0.01) was measured both in the subjective self-assessment and in the theoretical competence tests. In multivariate linear regression, the status 'medical officers yes' (β = 5.4; p = 0.04) had a significant influence on theory test results at T2. During the 24 virtual tumour board meetings, 28 cases were discussed and a continuous improvement in image acquisition quality was observed.

Conclusion

The ultrasound education concept comes with a sustainable increase in clinical competence and improved oncological ultrasound screening locally. There is potential for the transfer of the concept to other locations, which can be explored in the future.

Revisiting the standards of cancer detection and therapy alongside their comparison to modern methods

In accordance with the World Health Organization data, cancer remains at the forefront of fatal diseases. An upward trend in cancer incidence and mortality has been observed globally, emphasizing that efforts in developing detection and treatment methods should continue. The diagnostic path typically begins with learning the medical history of a patient; this is followed by basic blood tests and imaging tests to indicate where cancer may be located to schedule a needle biopsy. Prompt initiation of diagnosis is crucial since delayed cancer detection entails higher costs of treatment and hospitalization. Thus, there is a need for novel cancer detection methods such as liquid biopsy, elastography, synthetic biosensors, fluorescence imaging, and reflectance confocal microscopy. Conventional therapeutic methods, although still common in clinical practice, pose many limitations and are unsatisfactory. Nowadays, there is a dynamic advancement of clinical research and the development of more precise and effective methods such as oncolytic virotherapy, exosome-based therapy, nanotechnology, dendritic cells, chimeric antigen receptors, immune checkpoint inhibitors, natural product-based therapy, tumor-treating fields, and photodynamic therapy. The present paper compares available data on conventional and modern methods of cancer detection and therapy to facilitate an understanding of this rapidly advancing field and its future directions. As evidenced, modern methods are not without drawbacks; there is still a need to develop new detection strategies and therapeutic approaches to improve sensitivity, specificity, safety, and efficacy. Nevertheless, an appropriate route has been taken, as confirmed by the approval of some modern methods by the Food and Drug Administration.

Optimizing the performance of silica nanoparticles functionalized with a near-infrared fluorescent dye for bioimaging applications

Modified fluorescent nanoparticles continue to emerge as promising candidates for drug delivery, bioimaging, and labeling tools for various biomedical applications. The ability of nanomaterials to fluorescently label cells allow for the enhanced detection and understanding of diseases. Silica nanoparticles have a variety of unique properties that can be harnessed for many different applications, causing their increased popularity. In combination with an organic dye, fluorescent nanoparticles demonstrate a vast range of advantageous properties including long photostability, surface modification, and signal amplification, thus allowing ease of manipulation to best suit bioimaging purposes. In this study, the Stöber method with tetraethyl orthosilicate (TEOS) and a fluorescent dye sulfo-Cy5-amine was used to synthesize fluorescent silica nanoparticles. The fluorescence spectra, zeta potential, quantum yield, cytotoxicity, and photostability were evaluated. The increased intracellular uptake and photostability of the dye-silica nanoparticles show their potential for bioimaging.

How I treat long-term survivors of childhood acute leukemia

ABSTRACT

The population of survivors of childhood leukemia who reach adulthood is growing due to improved therapy. However, survivors are at risk of long-term complications. Comprehensive follow-up programs play a key role in childhood leukemia survivor care. The major determinant of long-term complications is the therapeutic burden accumulated over time. Relapse chemotherapy, central nervous system irradiation, hematopoietic stem cell transplantation, and total body irradiation are associated with greater risk of long-term complications. Other parameters include clinical characteristics such as age and sex as well as environmental, genetic, and socioeconomic factors, which can help stratify the risk of long-term complications and organize follow-up program. Early diagnosis improves the management of several late complications such as anthracycline-related cardiomyopathy, secondary cancers, metabolic syndrome, development defects, and infertility. Total body irradiation is the treatment associated with worse long-term toxicity profile with a wide range of complications. Patients treated with chemotherapy alone are at a lower risk of long-term complications, although the optimal long-term follow-up remains unclear. Novel immunotherapies and targeted therapy are generally associated with a better short-term safety profile but still require careful long-term toxicity monitoring. Advances in understanding genetic susceptibility to long-term complications could enable tailored therapeutic strategies for leukemia treatment and optimized follow-up programs.

HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers

Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.

Malignant tumor cells engender second membrane-lined organelles for self-protection and tumor progression

Cancer is a leading cause of mortality in humans, but the efficacy of current treatments for many cancers is limited, as they lack unique mechanistically defined targets. Here, we show that, upon malignant transformation, aggressive oncocells generate a second membrane exterior to their plasma membrane to form cytocapsulas (CCs) and cytocapsular tubes (CCTs), which all together constitute cytocapsular oncocells with pleotropic biological functions in cancer patient tissues in vivo. Proteomic and biochemical analyses revealed that the PMCA2 calcium pump is highly up-regulated in CCs and CCTs in malignant tumors but not in normal tissues, thus identifying a unique cancer biomarker and target for cancer therapy. Cytocapsular oncocells are universally present in solid cancers and appear in hematologic cancers in immune organs. Multi-cell malignant tumors are also enveloped by protective CC membranes. These cytocapsular tumors (CTs) generate numerous CCTs that form freeways for cancer cell metastasis to both neighboring and distant destinations. Entire cytocapsular tumor networks (CTNs) dominate physical cancer metastasis pathways in cancer patients in vivo. Later, CCTs invade micro blood vessels and release cytocapsular oncocells into the blood, providing a source of circulating tumor cells. CTNs interconnect cytocapsular tumors in primary and secondary cancer niches, creating larger cytocapsular tumor network systems (CTNSs). Primary and secondary CTNSs are in turn interconnected, forming dynamic and integrated CTNSs. Thus, interconnected cytocapsular oncocells, CTNs, and CTNSs coordinate cancer progression via the integrated cytocapsular membrane systems.

Exosomes in Cancer: Diagnostic and Therapeutic Applications

Small extracellular vesicles called exosomes are produced by cells and contain a range of biomolecules, including proteins, lipids, and nucleic acids. Exosomes have been implicated in the development and spread of cancer, and recent studies have shown that their contents may be exploited as biomarkers for early detection and ongoing surveillance of the disease. In this review article, we summarize the current knowledge on exosomes as biomarkers of cancer. We discuss the various methods used for exosome isolation and characterization, as well as the different types of biomolecules found within exosomes that are relevant for cancer diagnosis and prognosis. We also highlight recent studies that have demonstrated the utility of exosomal biomarkers in different types of cancer, such as lung cancer, breast cancer, and pancreatic cancer. Overall, exosomes show great promise as noninvasive biomarkers for cancer detection and monitoring. Exosomes have the ability to transform cancer diagnostic and therapeutic paradigms, providing promise for more efficient and individualized. This review seeks to serve as an inspiration for new ideas and research in the never-ending fight against cancer. Moreover, further studies are needed to validate their clinical utility and establish standardized protocols for their isolation and analysis. With continued research and development, exosomal biomarkers have the potential to revolutionize cancer diagnosis and treatment.

An Overview of Advances in Rare Cancer Diagnosis and Treatment

Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct subtypes characterized by infrequent incidence. Despite the inherent challenges in addressing the diagnosis and treatment of rare cancers due to their low occurrence rates, several biomedical breakthroughs have led to significant advancement in both areas. This review provides a comprehensive overview of state-of-the-art diagnostic techniques that encompass new-generation sequencing and multi-omics, coupled with the integration of artificial intelligence and machine learning, that have revolutionized rare cancer diagnosis. In addition, this review highlights the latest innovations in rare cancer therapeutic options, comprising immunotherapy, targeted therapy, transplantation, and drug combination therapy, that have undergone clinical trials and significantly contribute to the tumor remission and overall survival of rare cancer patients. In this review, we summarize recent breakthroughs and insights in the understanding of rare cancer pathophysiology, diagnosis, and therapeutic modalities, as well as the challenges faced in the development of rare cancer diagnosis data interpretation and drug development.

Synthesis and Application of a Near-Infrared Light-Emitting Fluorescent Probe for Specific Imaging of Cancer Cells with High Sensitivity and Selectivity

Background

The preclinical diagnosis of tumors is of great significance to cancer treatment. Near-infrared fluorescence imaging technology is promising for the in-situ detection of tumors with high sensitivity.

Methods

Here, a fluorescent probe was synthesized on the basis of Au nanoclusters with near-infrared light emission and applied to fluorescent cancer cell labeling. Near-infrared methionine-N-Hydroxy succinimide Au nanoclusters (Met-NHs-AuNCs) were prepared successfully by one-pot synthesis using Au nanoclusters, methionine, and N-Hydroxy succinimide as frameworks, reductants, and stabilizers, respectively. The specific fluorescence imaging of tumor cells or tissues by fluorescent probe was studied on the basis of SYBYL Surflex-DOCK simulation model of LAT1 active site of overexpressed receptor on cancer cell surface. The results showed that Met-NHs-AuNCs interacted with the surface of LAT1, and C_Score scored the conformation of the probe and LAT1 as five.

Results

Characterization and in vitro experiments were conducted to explore the Met-NHs-AuNCs targeted uptake of cancer cells. The prepared near-infrared fluorescent probe (Met-NHs-AuNCs) can specifically recognize the overexpression of L-type amino acid transporter 1 (LAT1) in cancer cells so that it can show red fluorescence in cancer cells. Meanwhile, normal cells (H9c2) have no fluorescence.

Conclusion

The fluorescent probe demonstrates the power of targeting and imaging cancer cells.

Applications of Exosome Vesicles in Different Cancer Types as Biomarkers

One of the biggest challenges in the fight against cancer is early detection. Early diagnosis is vital, but there are some barriers such as economic, cultural, and personal factors. Considering the disadvantages of radiological imaging techniques or serological analysis methods used in cancer diagnosis, such as being expensive, requiring expertise, and being time-consuming, there is a need to develop faster, more reliable, and cost-effective diagnostic methods for use in cancer diagnosis. Exosomes, which are responsible for intercellular communication with sizes ranging from 30-120 nm, are naturally produced biological nanoparticles. Thanks to the cargo contents they carry, they are a potential biomarker to be used in the diagnosis of cancer. Exosomes, defined as extracellular vesicles of endosomal origin, are effective in cancer growth, progression, metastasis, and drug resistance, and changes in microenvironmental conditions during tumor development change exosome secretion. Due to their high cellular activity, tumor cells produce much higher exosomes than healthy cells. Therefore, it is known that the number of exosomes in body fluids is significantly rich compared to other cells and can act as a stand-alone diagnostic biomarker. Cancer- derived exosomes have received great attention in recent years for the early detection of cancer and the evaluation of therapeutic response. In this article, the content, properties, and differences of exosomes detected in common types of cancer (lung, liver, pancreas, ovaries, breast, colorectal), which are the leading causes of cancer-related deaths, are reviewed. We also discuss the potential utility of exosome contents as a biomarker for early detection, which is known to be important in targeted cancer therapy.

Miniaturized, high numerical aperture confocal fluorescence detection enhanced with pyroelectric droplet accumulation for sub-attomole analyte diagnosis

To meet the growing demand for early fatal disease screening among large populations, current fluorescence detection instruments aiming at point-of-care diagnosis have the tendency to be low cost and high sensitivity, with a high potential for the analysis of low-volume, multiplex analytes with easy operation. In this work, we present the development of a miniaturized, high numerical aperture confocal fluorescence scanner for sub-micro-liter fluid diagnosis. It is enhanced with high-rate analyte accumulation using a pyroelectro-hydrodynamic dispensing system for generating tiny, stable sample droplets. The simplified confocal fluorescence scanner (numerical aperture 0.79, working distance 7.3 mm) uses merely off-the-shelf mass-production optical components. Experimental results show that it can achieve a high-sensitive, cost-efficient detection for sub-micro-liter, low-abundant (0.04 µL, 0.67 attomoles) fluid diagnosis, promising for point-of-care diagnosis.

Age and cancer type: associations with increased odds of receiving a late diagnosis in people with advanced cancer

PURPOSE

In order to deliver appropriate and timely care planning and minimise avoidable late diagnoses, clinicians need to be aware of which patients are at higher risk of receiving a late cancer diagnosis. We aimed to determine which demographic and clinical factors are associated with receiving a 'late' cancer diagnosis (within the last 12 weeks of life).

METHOD

Retrospective cohort study of 2,443 people who died from cancer ('cancer decedents') in 2013-2015. Demographic and cancer registry datasets linked using patient-identifying Community Health Index numbers. Analysis used binary logistic regression, with univariate and adjusted odds ratios (SPSS v25).

RESULTS

One third (n = 831,34.0%) received a late diagnosis. Age and cancer type were significantly associated with late cancer diagnosis (p < 0.001). Other demographic factors were not associated with receiving a late diagnosis. Cancer decedents with lung cancer (Odds Ratios presented in abstract are the inverse of those presented in the main text, where lung cancer is the reference category. Presented as 1/(OR multivariate)) were more likely to have late diagnosis than those with bowel (95% Confidence Interval [95%CI] Odds Ratio (OR)1.52 (OR1.12 to 2.04)), breast or ovarian (95%CI OR3.33 (OR2.27 to 5.0) or prostate (95%CI OR9.09 (OR4.0 to 20.0)) cancers. Cancer decedents aged > 85 years had higher odds of late diagnosis (95%CI OR3.45 (OR2.63 to 4.55)), compared to those aged < 65 years.

CONCLUSIONS

Cancer decedents who were older and those with lung cancer were significantly more likely to receive late cancer diagnoses than those who were younger or who had other cancer types.

Prevalence of unmet supportive care needs reported by individuals ever diagnosed with cancer in Australia: a systematic review to support service prioritisation

PURPOSE

Improved health outcomes for individuals ever diagnosed with cancer require comprehensive, coordinated care that addresses their supportive care needs. Implementing interventions to address these is confounded by a lack of evidence on population needs and a large pool of potential interventions. This systematic review estimates the point prevalence of different supportive care needs stratified by the tool used to measure needs and cancer type in Australia.

METHODS

We searched MEDLINE, Embase, and Scopus from 2010 to April 2023 to identify relevant studies published on the prevalence of supportive care needs in Australia.

RESULTS

We identified 35 studies that met the inclusion criteria. The highest prevalent unmet need across all cancers was 'fear of cancer spreading' (20.7%) from the Supportive Care Needs Survey Short-Form 34 (SCNS-SF34), ranging from 9.4% for individuals ever diagnosed with haematological cancer to 36.3% for individuals ever diagnosed with gynaecological cancer, and 'concerns about cancer coming back' (17.9%) from the Cancer Survivors' Unmet Needs (CaSUN), ranging from 9.7% for individuals ever diagnosed with prostate cancer to 37.8% for individuals ever diagnosed with breast cancer. Two studies assessed needs in Aboriginal and Torres Strait Islander populations, reporting the highest needs for financial worries (21.1%).

CONCLUSIONS

Point prevalence estimates presented here, combined with estimates of the costs and effects of potential interventions, can be used within economic evaluations to inform evidence-based local service provision to address the supportive care needs of individuals ever diagnosed with cancer.

IMPLICATIONS FOR CANCER SURVIVORS

Local health services can use local evidence to prioritise the implementation of interventions targeted at unmet needs.

MTSS1 is downregulated in nasopharyngeal carcinoma (NPC) which disrupts adherens junctions leading to enhanced cell migration and invasion

Loss of cell-cell adhesions is the indispensable first step for cancer cells to depart from the primary tumor mass to metastasize. Metastasis suppressor 1 (MTSS1) is frequently lost in metastatic tissues, correlating to advanced tumor stages and poor prognosis across a variety of cancers. Here we explore the anti-metastatic mechanisms of MTSS1, which have not been well understood. We found that MTSS1 is downregulated in NPC tissues. Lower levels of MTSS1 expression correlate to worse prognosis. We show that MTSS1 suppresses NPC cell migration and invasion in vitro through cytoskeletal remodeling at cell-cell borders and assembly of E-cadherin/β-catenin/F-actin in adherens junctions. The I-BAR domain of MTSS1 was both necessary and sufficient to restore this formation of E-cadherin/β-catenin/F-actin-mediated cell adherens junctions.

Provision of screening services for cervical and breast cancer - A scientific study commissioned by the European Board & College of Obstetrics and Gynaecology (EBCOG)

OBJECTIVE

Cancer screening can play an important role in early detection, improving treatment outcomes and reducing morbidity and mortality. Breast and cervical cancers belong to the most common gynaecological cancers group. Countries provide different screening programmes on its eligible population basis centred on different health care policies. This scientific study aims to assess and understand the health inequalities in the member countries of the European Board & College of Obstetrics and Gynaecology (EBCOG) as regards screening programmes of gynaecological cancer, with a special focus on breast and cervical cancers' screening strategies.

STUDY DESIGN

A descriptive questionnaire-based study was conducted, addressed to EBCOG member countries.

RESULTS

Ninety-one percent of the countries have an organized national or regional screening programme for cervical cancer. Of these, 45% of countries use both cytology and testing for Human Papilloma Virus (HPV) as screening test, 31% use cytology exclusively and 17% only perform HPV testing. Considerable differences were found regarding the interval of screening test: there are countries performing HPV detection triennially, while others perform only conventional cytology every 5 years. Sixty-nine percent of countries included in this study begin screening for cervical cancer in women aged 25 to 29 years, four of them using HPV detection as the screening test. Six countries begin cervical cancer screening before the age of 25. As regards vaccination against HPV, almost all countries have implemented national HPV vaccination programme, except in Poland and Turkey. The 9-valent HPV vaccine is the most frequently offered (77% of countries) and the majority vaccination programmes include both girls and boys. As regards breast cancer screening, all thirty-two countries have an implemented screening programme. All countries perform mammography as the screening test, 62.5% of them begin in women aged 50 to 54, with a 2-yearly interval in the majority. In five countries, screening programmes are performed biennially, starting between 45 and 49 years old. Seven countries start in women aged 41 to 44.

CONCLUSIONS

There are discrepancies around gynaecological cancer screenings provision among EBCOG member countries. It is important to establish European recommendations about screening for gynaecological cancers, in order to standardize the access to equitable better health care in gynaecological cancers within Europe.

EBCOG position statement on Inequalities in screening for cervical and breast cancer

Gynaecological cancers, namely breast and cervical cancer represent a high burden in women's health. It is well established that cervical and breast cancer screening programmes are effective in reducing morbidity and mortality. It is of the most importance to define strategies to provide a universal access to screening. In European countries, significant progress has been made over the past years concerning screening strategies, namely the choice of screening test, its frequency as well as the age to start and stop the screening. Introduction of Human Papillomavirus vaccination programmes is also making a measurable impact to reduce cervical cancer prevalence and mortality. Our survey has shown a variation among European countries in delivery of cervical and breast cancer screening programmes. These variations can be due to organizational, economic or cultural reasons. The European Board and College of Obstetrics and Gynaecology calls for an implementation of a unified policy of prevention, screening and early detection of cervical and breast cancer across Europe to optimize clinical outcomes and reduce variations.

Disparities in testicular cancer incidence, mortality, and place of death trends from 1999 to 2020: A comprehensive cohort study

BACKGROUND

Testicular cancer (TC) mortality rates have decreased over time, however it is unclear whether these improvements are consistent across all communities.

AIMS

The aim of this study was to analyze trends in TC incidence, mortality, and place of death (PoD) in the United States between 1999-2020 and identify disparities across race, ethnicity, and geographic location.

METHODS AND RESULTS

This cross-sectional study used CDC WONDER and NAACCR, to calculate age-adjusted rates of TC incidence and mortality, respectively. PoD data for individuals who died of TC were collected from CDC WONDER. Using Joinpoint analysis, longitudinal mortality trends were evaluated by age, race, ethnicity, US census region, and urbanization category. TC stage (localized vs metastatic) trends were also evaluated. Univariate and multivariate regression analysis identified demographic disparities for PoD. A total of 8,456 patients died of TC from 1999-2020. Average annual percent change (AAPC) of testicular cancer-specific mortality (TCSM) remained largely stable (AAPC, 0.4; 95% CI -0.2 to 0.9; p = 0.215). Men ages 25-29 experienced a significant increase in TCSM (AAPC, 1.3, p = 0.003), consistent with increased metastatic testicular cancer-specific incidence (TCSI) trend for this age group (AAPC, 1.6; p < 0.01). Mortality increased for Hispanic men (AAPC, 1.7, p < 0.001), with increased metastatic TCSI (AAPC, 2.5; p < 0.001). Finally, younger (<45), single, and Hispanic or Black men were more likely to die in medical facilities (all p < 0.001). The retrospective study design is a limitation.

CONCLUSION

Significant increases in metastatic TC were found for Hispanic men and men aged 25-29 potentially driving increasing testicular cancer specific mortality in these groups. Evidence of racial and ethnic differences in place of death may also highlight treatment disparities.

Improved accuracy in colorectal cancer tissue decomposition through refinement of established deep learning solutions

Hematoxylin and eosin-stained biopsy slides are regularly available for colorectal cancer patients. These slides are often not used to define objective biomarkers for patient stratification and treatment selection. Standard biomarkers often pertain to costly and slow genetic tests. However, recent work has shown that relevant biomarkers can be extracted from these images using convolutional neural networks (CNNs). The CNN-based biomarkers predicted colorectal cancer patient outcomes comparably to gold standards. Extracting CNN-biomarkers is fast, automatic, and of minimal cost. CNN-based biomarkers rely on the ability of CNNs to recognize distinct tissue types from microscope whole slide images. The quality of these biomarkers (coined 'Deep Stroma') depends on the accuracy of CNNs in decomposing all relevant tissue classes. Improving tissue decomposition accuracy is essential for improving the prognostic potential of CNN-biomarkers. In this study, we implemented a novel training strategy to refine an established CNN model, which then surpassed all previous solutions . We obtained a 95.6% average accuracy in the external test set and 99.5% in the internal test set. Our approach reduced errors in biomarker-relevant classes, such as Lymphocytes, and was the first to include interpretability methods. These methods were used to better apprehend our model's limitations and capabilities.

Cell-Free miRNAs as Non-Invasive Biomarkers in Brain Tumors

Diagnosing brain tumors, especially malignant variants, such as glioblastoma, medulloblastoma, or brain metastasis, presents a considerable obstacle, while current treatment methods often yield unsatisfactory results. The monitoring of individuals with brain neoplasms becomes burdensome due to the intricate tumor nature and associated risks of tissue biopsies, compounded by the restricted accuracy and sensitivity of presently available non-invasive diagnostic techniques. The uncertainties surrounding diagnosis and the tumor's reaction to treatment can lead to delays in critical determinations that profoundly influence the prognosis of the disease. Consequently, there exists a pressing necessity to formulate and validate dependable, minimally invasive biomarkers that can effectively diagnose and predict brain tumors. Cell-free microRNAs (miRNAs), which remain stable and detectable in human bodily fluids, such as blood and cerebrospinal fluid (CSF), have emerged as potential indicators for a range of ailments, brain tumors included. Numerous investigations have showcased the viability of profiling cell-free miRNA expression in both CSF and blood samples obtained from patients with brain tumors. Distinct miRNAs demonstrate varying expression patterns within CSF and blood. While cell-free microRNAs in the blood exhibit potential in diagnosing, prognosticating, and monitoring treatment across diverse tumor types, they fall short in effectively diagnosing brain tumors. Conversely, the cell-free miRNA profile within CSF demonstrates high potential in delivering precise and specific evaluations of brain tumors.

Strategies for improving detection of circulating tumor DNA using next generation sequencing

Cancer has become a global health issue and liquid biopsy has emerged as a non-invasive tool for various applications. In cancer, circulating tumor DNA (ctDNA) can be detected from cell-free DNA (cfDNA) obtained from plasma and has potential for early diagnosis, treatment, resistance, minimal residual disease detection, and tumoral heterogeneity identification. However, the low frequency of ctDNA requires techniques for accurate analysis. Multitarget assay such as Next Generation Sequencing (NGS) need improvement to achieve limits of detection that can identify the low frequency variants present in the cfDNA. In this review, we provide a general overview of the use of cfDNA and ctDNA in cancer, and discuss techniques developed to optimize NGS as a tool for ctDNA detection. We also summarize the results obtained using NGS strategies in both investigational and clinical contexts.

Whole Person Modeling: a transdisciplinary approach to mental health research

The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.

Emerging Role of Tumor-Educated Platelets as a New Liquid Biopsy Tool for Colorectal Cancer

Colorectal cancer (CRC) is a major cause of cancer-associated death universally. Currently, the diagnosis, prognosis, and treatment monitoring of CRC mostly depends on endoscopy integrated with tissue biopsy. Recently, liquid biopsy has gained more and more attention in the area of molecular detection and monitoring of tumors due to ease of sampling, and its safe, non-invasive, and dynamic nature. Platelets, despite their role in hemostasis and thrombosis, are known to have an active, bifacial relationship with cancers. Platelets are the second most common type of cell in the blood and are one of the wealthy liquid biopsy biosources. These cells have the potential to absorb nucleic acids and proteins and modify their transcriptome with regard to external signals, which are termed tumor-educated platelets (TEPs). Liquid biopsies depend on TEPs' biomarkers which can be used to screen and also detect cancer in terms of prognosis, personalized treatment, monitoring, and prediction of recurrence. The value of TEPs as an origin of tumor biomarkers is relatively new, but platelets are commonly isolated using formidable and rapid techniques in clinical practice. Numerous preclinical researches have emphasized the potential of platelets as a new liquid biopsy biosource for detecting several types of tumors. This review discusses the potential use of platelets as a liquid biopsy for CRC.

Recent advances of exosomal circRNAs in cancer and their potential clinical applications

Circular RNA (circRNA) is a type of non-coding RNA that forms a covalently closed, uninterrupted loop. The expression of circRNA differs among cell types and tissues, and various circRNAs are aberrantly expressed in a variety of diseases, including cancer. Aberrantly expressed circRNAs contribute to disease progression by acting as microRNA sponges, functional protein sponges, or novel templates for protein translation. Recent studies have shown that circRNAs are enriched in exosomes. Exosomes are spherical bilayer vesicles released by cells into extracellular spaces that mediate intercellular communication by delivering cargoes. These cargoes include metabolites, proteins, lipids, and RNA molecules. Exosome-mediated cell-cell or cell-microenvironment communications influence the progression of carcinogenesis by regulating cell proliferation, angiogenesis, metastasis as well as immune escape. In this review, we summarize the current knowledge about exosomal circRNAs in cancers and discuss their specific functions in tumorigenesis. Additionally, we discuss the potential value of exosomal circRNAs as diagnostic biomarkers and the potential applications of exosomal circRNA-based cancer therapy.

Enrichment and sensing tumor cells by embedded immunomodulatory DNA hydrogel to inhibit postoperative tumor recurrence

Postoperative tumor recurrence and metastases often lead to cancer treatment failure. Here, we develop a local embedded photodynamic immunomodulatory DNA hydrogel for early warning and inhibition of postoperative tumor recurrence. The DNA hydrogel contains PDL1 aptamers that capture and enrich in situ relapsed tumor cells, increasing local ATP concentration to provide a timely warning signal. When a positive signal is detected, local laser irradiation is performed to trigger photodynamic therapy to kill captured tumor cells and release tumor-associated antigens (TAA). In addition, reactive oxygen species break DNA strands in the hydrogel to release encoded PDL1 aptamer and CpG, which together with TAA promote sufficient systemic antitumor immunotherapy. In a murine model where tumor cells are injected at the surgical site to mimic tumor recurrence, we find that the hydrogel system enables timely detection of tumor recurrence by enriching relapsed tumor cells to increase local ATP concentrations. As a result, a significant inhibitory effect of approximately 88.1% on recurrent tumors and effectively suppressing metastasis, offering a promising avenue for timely and effective treatment of postoperative tumor recurrence.

Diagnostic and prognostic role of circRNAs in pancreatic cancer: a meta-analysis

Background

Circular RNAs (circRNAs) are types of endogenous noncoding RNAs produced by selective splicing that are expressed highly specifically in various organisms and tissues and have numerous clinical implications in the regulation of cancer development and progression. Since circRNA is resistant to digestion by ribonucleases and has a long half-life, there is increasing evidence that circRNA can be used as an ideal candidate biomarker for the early diagnosis and prognosis of tumors. In this study, we aimed to reveal the diagnostic and prognostic value of circRNA in human pancreatic cancer (PC).

Methods

A systematic search for publications from inception to 22 July 2022 was conducted on Embase, PubMed, Web of Science (WOS), and the Cochrane Library databases. Available studies that correlated circRNA expression in tissue or serum with the clinicopathological, diagnostic, and prognostic values of PC patients were enrolled. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were used to evaluate clinical pathological characteristics. Area under the curve (AUC), sensitivity, and specificity were adopted to assess diagnostic value. Hazard ratios (HRs) were utilized to assess disease-free survival (DFS) and overall survival (OS).

Results

This meta-analysis enrolled 32 eligible studies, including six on diagnosis and 21 on prognosis, which accounted for 2,396 cases from 245 references. For clinical parameters, high expression of carcinogenic circRNA was significantly associated with degree of differentiation (OR = 1.85, 95% CI = 1.47-2.34), TNM stage (OR = 0.46, 95% CI = 0.35-0.62), lymph node metastasis (OR = 0.39, 95% CI = 0.32-0.48), and distant metastasis (OR = 0.26, 95% CI = 0.13-0.51). As for clinical diagnostic utility, circRNA could discriminate patients with pancreatic cancer from controls, with an AUC of 0.86 (95% CI: 0.82-0.88), a relatively high sensitivity of 84%, and a specificity of 80% in tissue. In terms of prognostic significance, carcinogenic circRNA was correlated with poor OS (HR = 2.00, 95% CI: 1.76-2.26) and DFS (HR = 1.96, 95% CI: 1.47-2.62).

Conclusion

In summary, this study demonstrated that circRNA may act as a significant diagnostic and prognostic biomarker for pancreatic cancer.

Single test-based diagnosis of multiple cancer types using Exosome-SERS-AI for early stage cancers

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we report the diagnostic accuracy of simultaneous detection of 6 types of early-stage cancers (lung, breast, colon, liver, pancreas, and stomach) by analyzing surface-enhanced Raman spectroscopy profiles of exosomes using artificial intelligence in a retrospective study design. It includes classification models that recognize signal patterns of plasma exosomes to identify both their presence and tissues of origin. Using 520 test samples, our system identified cancer presence with an area under the curve value of 0.970. Moreover, the system classified the tumor organ type of 278 early-stage cancer patients with a mean area under the curve of 0.945. The final integrated decision model showed a sensitivity of 90.2% at a specificity of 94.4% while predicting the tumor organ of 72% of positive patients. Since our method utilizes a non-specific analysis of Raman signatures, its diagnostic scope could potentially be expanded to include other diseases.