Cancer overdiagnosis: a biological challenge and clinical dilemma

High-throughput enrichment of portal venous circulating tumor cells for highly sensitive diagnosis of CA19-9-negative pancreatic cancer patients using inertial microfluidics

The carbohydrate antigen 19-9 (CA19-9) is commonly used as a representative biomarker for pancreatic cancer (PC); however, it lacks sensitivity and specificity for early-stage PC diagnosis. Furthermore, some patients with PC are negative for CA19-9 (<37 U/mL), which introduces additional limitations to their accurate diagnosis and treatment. Hence, improved methods to accurately detect PC stages in CA19-9-negative patients are warranted. In this study, tumor-proximal liquid biopsy and inertial microfluidics were coupled to enable high-throughput enrichment of portal venous circulating tumor cells (CTCs) and support the effective diagnosis of patients with early-stage PC. The proposed inertial microfluidic system was shown to provide size-based enrichment of CTCs using inertial focusing and Dean flow effects in slanted spiral channels. Notably, portal venous blood samples were found to have twice the yield of CTCs (21.4 cells per 5 mL) compared with peripheral blood (10.9 CTCs per 5 mL). A combination of peripheral and portal CTC data along with CA19-9 results showed to greatly improve the average accuracy of CA19-9-negative PC patients from 47.1% with regular CA19-9 tests up to 87.1%. Hence, portal venous CTC-based microfluidic biopsy can be used with high sensitivity and specificity for the diagnosis of early-stage PC, particularly in CA19-9-negative patients.

Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis

BACKGROUND

Contemporary prostate cancer (PCa) screening uses first-line prostate-specific antigen (PSA) testing, possibly followed by multiparametric magnetic resonance imaging (mpMRI) for men with elevated PSA levels. First-line biparametric MRI (bpMRI) screening has been proposed as an alternative.

OBJECTIVE

To evaluate the comparative effectiveness and cost-effectiveness of first-line bpMRI versus PSA-based screening.

DESIGN

Decision analysis using a microsimulation model.

DATA SOURCES

Surveillance, Epidemiology, and End Results database; randomized trials.

TARGET POPULATION

U.S. men aged 55 years with no prior screening or PCa diagnosis.

TIME HORIZON

Lifetime.

PERSPECTIVE

U.S. health care system.

INTERVENTION

Biennial screening to age 69 years using first-line PSA testing (test-positive threshold, 4 µg/L) with or without second-line mpMRI or first-line bpMRI (test-positive threshold, PI-RADS [Prostate Imaging Reporting and Data System] 3 to 5 or 4 to 5), followed by biopsy guided by MRI or MRI plus transrectal ultrasonography.

OUTCOME MEASURES

Screening tests, biopsies, diagnoses, overdiagnoses, treatments, PCa deaths, quality-adjusted and unadjusted life-years saved, and costs.

RESULTS OF BASE-CASE ANALYSIS

For 1000 men, first-line bpMRI versus first-line PSA testing prevented 2 to 3 PCa deaths and added 10 to 30 life-years (4 to 11 days per person) but increased the number of biopsies by 1506 to 4174 and the number of overdiagnoses by 38 to 124 depending on the biopsy imaging scheme. At conventional cost-effectiveness thresholds, first-line PSA testing with mpMRI followed by either biopsy approach for PI-RADS 4 to 5 produced the greatest net monetary benefits.

RESULTS OF SENSITIVITY ANALYSIS

First-line PSA testing remained more cost-effective even if bpMRI was free, all men with low-risk PCa underwent surveillance, or screening was quadrennial.

LIMITATION

Performance of first-line bpMRI was based on second-line mpMRI data.

CONCLUSION

Decision analysis suggests that comparative effectiveness and cost-effectiveness of PCa screening are driven by false-positive results and overdiagnoses, favoring first-line PSA testing with mpMRI over first-line bpMRI.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Pancreatic cancer in Saudi Arabia (2005-2020): increasing trend

Pancreatic cancer, a highly fatal malignancy, has shown a global rise in the incidence and mortality rates. However, these rates vary significantly across different regions worldwide. This study aims to assess the incidence and mortality of pancreatic cancer in Saudi Arabia. We collected the data from 16 annual cancer incidence reports in Saudi Arabia for the study period (2005-2020) and from the WHO's IARC Global Cancer Observatory website. Although the burden of pancreatic cancer in Saudi Arabia is relatively lower compared to global rates, the disease incidence has shown a steady increase over the study period, in addition to regional variations within the country. The disease predominantly affects the elderly population, aged 50 years and above in both genders, with males exhibiting higher rates than females. Further studies are required to identify the potential risk factors for pancreatic cancer in the Saudi population.

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.

Synergetic surface enhancement of quantum dots-based electrochemiluminescence with photonic crystal light scattering and metal surface plasmon resonance for sensitive bioanalysis

Noble metal nanostructures and photonic crystals (PhCs) have been widely investigated as substrates for constructing surface enhanced electrochemiluminescence (SE-ECL) biosensors. However, their applications are hindered by the limited enhancement intensity of surface plasmon resonance (SPR) and an incomplete mechanism for the photonic enhancement effect. Hence, developing a novel SE-ECL strategy with better signal enhanced capability and enriching our understanding of the intrinsic mechanisms for efficient bioanalysis is extremely urgent. Here, a synergistic SE-ECL strategy was developed for the sensitive determination of prostate specific antigen (PSA) protein. The randomly arranged polystyrene (r-PS) spheres and PS PhC arrays were applied to enhance the ECL emission of cadmium sulfide quantum dots (CdS QDs) and the results suggested that the PhC arrays displayed superior intensity (0.22) than the r-PS interface (0.10). Au nanoparticles (NPs) were introduced onto the two kinds of surfaces and further boosted the ECL intensity. According to the ECL measurements, Au NPs modified at the r-PS surface exhibited only a slight increase (0.13), while the PhC arrays showed approximately 5-fold enhancement (0.92), benefiting from the synergistic enhancement. The finite-difference time-domain (FDTD) simulation indicated that the ECL enhancement was ascribed to the coupled electromagnetic (EM) field at the surfaces of PS PhCs and Au NPs. The SE-ECL could achieve a detection range from 1 pg/mL to 1 μg/mL with a detection limit of 0.41 pg/mL (S/N = 3). This study provides the first combination of PhC arrays and metal surface plasmon nanostructure for the synergetic enhancement of SE-ECL systems. It opens a new avenue for the rational design of advanced ECL biosensors and shows great perspective for clinical diagnosis.

Leveraging radiomics and AI for precision diagnosis and prognostication of liver malignancies

Liver tumors, whether primary or metastatic, have emerged as a growing concern with substantial global health implications. Timely identification and characterization of liver tumors are pivotal factors in order to provide optimum treatment. Imaging is a crucial part of the detection of liver tumors; however, conventional imaging has shortcomings in the proper characterization of these tumors which leads to the need for tissue biopsy. Artificial intelligence (AI) and radiomics have recently emerged as investigational opportunities with the potential to enhance the detection and characterization of liver lesions. These advancements offer opportunities for better diagnostic accuracy, prognostication, and thereby improving patient care. In particular, these techniques have the potential to predict the histopathology, genotype, and immunophenotype of tumors based on imaging data, hence providing guidance for personalized treatment of such tumors. In this review, we outline the progression and potential of AI in the field of liver oncology imaging, specifically emphasizing manual radiomic techniques and deep learning-based representations. We discuss how these tools can aid in clinical decision-making challenges. These challenges encompass a broad range of tasks, from prognosticating patient outcomes, differentiating benign treatment-related factors and actual disease progression, recognizing uncommon response patterns, and even predicting the genetic and molecular characteristics of the tumors. Lastly, we discuss the pitfalls, technical limitations and future direction of these AI-based techniques.

CD74 as a prognostic and M1 macrophage infiltration marker in a comprehensive pan-cancer analysis

CD74 is a type-II transmembrane glycoprotein that has been linked to tumorigenesis. However, this association was based only on phenotypic studies, and, to date, no in-depth mechanistic studies have been conducted. In this study, combined with a multi-omics study, CD74 levels were significantly upregulated in most cancers relative to normal tissues and were found to be predictive of prognosis. Elevated CD74 expression was associated with reduced levels of mismatch-repair genes and homologous repair gene signatures in over 10 tumor types. Multiple fluorescence staining and bulk, spatial, single-cell transcriptional analyses indicated its potential as a marker for M1 macrophage infiltration in pan-cancer. In addition, CD74 expression was higher in BRCA patients responsive to conventional chemotherapy and was able to predict the prognosis of these patients. Potential CD74-activating drugs (HNHA and BRD-K55186349) were identified through molecular docking to CD74. The findings indicate activation of CD74 may have potential in tumor immunotherapy.

Implementation considerations for risk-tailored cancer screening in the population: A scoping review

BACKGROUND

Risk-tailored screening has emerged as a promising approach to optimise the balance of benefits and harms of existing population cancer screening programs. It tailors screening (e.g., eligibility, frequency, interval, test type) to individual risk rather than the current one-size-fits-all approach of most organised population screening programs. However, the implementation of risk-tailored cancer screening in the population is challenging as it requires a change of practice at multiple levels i.e., individual, provider, health system levels. This scoping review aims to synthesise current implementation considerations for risk-tailored cancer screening in the population, identifying barriers, facilitators, and associated implementation outcomes.

METHODS

Relevant studies were identified via database searches up to February 2023. Results were synthesised using Tierney et al. (2020) guidance for evidence synthesis of implementation outcomes and a multilevel framework.

RESULTS

Of 4138 titles identified, 74 studies met the inclusion criteria. Most studies in this review focused on the implementation outcomes of acceptability, feasibility, and appropriateness, reflecting the pre-implementation stage of most research to date. Only six studies included an implementation framework. The review identified consistent evidence that risk-tailored screening is largely acceptable across population groups, however reluctance to accept a reduction in screening frequency for low-risk informed by cultural norms, presents a major barrier. Limited studies were identified for cancer types other than breast cancer.

CONCLUSIONS

Implementation strategies will need to address alternate models of delivery, education of health professionals, communication with the public, screening options for people at low risk of cancer, and inequity in outcomes across cancer types.

Prospects for liquid biopsy using microRNA and extracellular vesicles in breast cancer

Among the analytes circulating in body fluids, microRNAs, a type of non-coding RNA and known to exist 2655 in primates, have attracted attention as a novel biomarker for cancer screening. MicroRNAs are signaling molecules with important gene expression regulatory functions that can simultaneously control many gene functions and multiple different pathways in living organisms. These microRNAs are transported in extracellular vesicles (EVs), which are lipid bilayers with 50-150 nm in diameter, and are used as communication tools between cells. Furthermore, the EVs that carry these microRNAs circulate in the bloodstream and have other important implications for understanding the pathogenesis and diagnosis of breast cancer. The greatest benefit from cancer screening is the reduction in breast cancer mortality rate through early detection. Other benefits include reduced incidence of breast cancer, improved quality of life, prognosis prediction, contribution to personalized medicine, and relative healthcare cost containment. This paper outlines the latest developments in liquid biopsy for breast cancer, especially focusing on microRNA and EV diagnostics.

Overexpression of Transmembrane Phosphatase with Tensin homology (TPTE) in prostate cancer is clinically significant, suggesting its potential as a valuable biomarker

PURPOSE

Cancer testis antigens (CTAs) are a family of proteins typically expressed in male testicles but overexpressed in various cancer cell types. Transmembrane Phosphatase with Tensin homology (TPTE) is expressed only in the testis of healthy individuals and is a member of the family of CTAs. The current study, for the first time, examined the significance of TPTE expression in prostate cancer (PCa) tissues by generating a novel antibody marker targeting TPTE protein.

METHODS

Polyclonal antibodies were prepared for TPTE-p1 and TPTE-p2 peptides, which are derived from the extracellular domains of TPTE. Anti-TPTE-p2 antibody was then used to study the extent and pattern of TPTE expression in 102 PCa and 48 benign prostatic hyperplasia (BPH) tissue samples by immunohistochemistry. The viability of cancer cell lines (PC-3 and MCF-7 cells) was also evaluated in the presence of anti-TPTE-p2 antibody using the MTT test.

RESULTS

The immunohistochemical analysis demonstrated a significant increase in cytoplasmic and membrane TPTE expression in the PCa samples compared to the BPH group (both P < 0.0001). Cytoplasmic TPTE expression was positively correlated with Gleason score and PSA levels (P = 0.03 and P = 0.001, respectively). Significant correlations were identified between the levels of PSA and perineural invasion and the membrane expression (P = 0.01, P = 0.04, respectively). Moreover, anti-TPTE-p2 antibody inhibited PC-3 and MCF-7 cells proliferation compared to the control group for 24 h (P < 0.001 and P = 0.001, respectively) as well as for 48 h (P = 0.001 and P = 0.001, respectively).

CONCLUSION

Our findings indicate that increased TPTE expression is associated with progression of disease. The ability of anti-TPTE-p2 antibody to recognize and target the TPTE protein makes it a potential biomarker to assess and/or target the PCa.

miR-203a-A multifaceted regulator modulating cancer hallmarks and therapy response

MicroRNAs (miRNAs) are a class of noncoding RNAs of about 19-25 nucleotides, which serve as critical modulators of various cellular and biological processes by target gene regulation. Dysregulated expression of miRNAs modulates the pathophysiology of various human diseases, including cancer. Among miRNAs, miR-203a is one of the most extensively researched dysregulated miRNAs in different cancers. Our review investigated the roles of miR-203a in the hallmarks of cancer modulating different pathways through target gene regulations, chemoresistance, its crosstalk with other ncRNAs or genes in terms of ceRNAs impacting oncogenesis, and its potential applications in the diagnosis, prognosis, and chemotherapeutic responses in different cancer types. miR-203a impacts cancer cell behavior by regulating these exclusive hallmarks- sustaining proliferation, cell growth, invasion and metastasis, cell death, and angiogenesis. Besides, miR-203a is found in human circulating biofluids like plasma or serum of colorectal cancer, cervical cancer, and hepatocellular carcinoma, hinting at its potential as a biomarker. Further, miR-203a is involved in enhancing the chemosensitivity of cisplatin, docetaxel, paclitaxel, doxorubicin, and 5-fluorouracil in a variety of malignancies through their cognate target genes. These results suggest that miR-203a is a crucial multifaceted miRNA that controls cancer cell proliferation, metastasis, and chemotherapy response, shedding new light on its possible application.

Polypeptides from traditional Chinese medicine: Comprehensive review of perspective towards cancer management

Cancer has always been a focus of global attention, and the difficulty of treatment and poor prognosis have always plagued humanity. Conventional chemotherapeutics and treatment with synthetic disciplines will cause adverse side effects and drug resistance. Therefore, searching for a safe, valid, and clinically effective drug is necessary. At present, some natural compounds have proved to have the potential to fight cancer. Polypeptides obtained from traditional Chinese medicine are good anti-cancer ingredients. The anticancer activity has been fully demonstrated in vivo and in vitro. However, most of the functional studies on traditional Chinese medicine polypeptides are at the stage of basic experimental research, and fewer of them have been applied to clinical trials. Hence, this review mainly discusses the chemical structure, extraction, separation and purification methods, the anti-cancer mechanism, and structure-activity relationships of traditional Chinese medicine polypeptides. It provides theoretical support for strengthening the rapid separation and purification and the overall efficacy and mechanism of action, as well as the industrialization and clinical application of traditional Chinese medicine polypeptides.

Shared medical decision in prostate cancer screening in primary care: a systematic literature review of current evidence

PURPOSE

Prostate cancer screening has not significantly reduced mortality. International guidelines strongly endorse shared decision-making to navigate risks, emphasizing its crucial role prior to prescribing a prostate-specific antigen test. This study aims to provide insight into the current role of shared decision-making in primary care for prostate cancer screening and suggest ways to improve the process.

METHODS

PubMed, Cochrane, and Lissa databases were searched for following terms: 'prostate-specific antigen' or 'prostate cancer screening' combined with 'shared decision making', 'informed decision making' or 'decision support' and 'primary care'. All studies were screened by two independent reviewers. This systematic review followed the PRISMA guidelines.

RESULTS

Of 85 articles screened, 34 were included. Key findings included heterogenous and poor quality implementation of shared decision-making in practice, patients with limited knowledge of shared decision-making, clinicians infrequently discussing patients' views, decision aids that could be better integrated into practice, and finally, changes in care systems to support the expansion of shared decision-making in prostate cancer screening.

CONCLUSION

Decision aids are essential tools in the informed decision-making process. Integrating these elements into practice would require training for doctors and adjustments to the healthcare system.

Clinical performance and utility: A microsimulation model to inform the design of screening trials for a multi-cancer early detection test

OBJECTIVES

Designing cancer screening trials for multi-cancer early detection (MCED) tests presents a significant methodology challenge, as natural histories of cell-free DNA-shedding cancers are not yet known. A microsimulation model was developed to project the performance and utility of an MCED test in cancer screening trials.

METHODS

Individual natural history of preclinical progression through cancer stages for 23 cancer classes was simulated by a stage-transition model under a broad range of cancer latency parameters. Cancer incidences and stage distributions at clinical presentation in simulated trials were set to match the data from Surveillance, Epidemiology, and End Results program. One or multiple rounds of annual screening using a targeted methylation-based MCED test (GalleriⓇ) was conducted to detect preclinical cancers. Mortality benefit of early detection was simulated by a stage-shift model.

RESULTS

In simulated trials, accounting for healthy volunteer effect and varying test sensitivity, positive predictive value in the prevalence screening round reached 48% to 61% in 6 natural history scenarios. After 3 rounds of annual screening, the cumulative proportions of stage I/II cancers increased by approximately 9% to 14%, the incidence of stage IV cancers was reduced by 37% to 46%, the reduction of stages III and IV cancer incidences was 9% to 24%, and the reduction of mortality reached 13% to 16%. Greater reductions of late-stage cancers and cancer mortality were achieved by five rounds of MCED screening.

CONCLUSIONS

Simulation results guide trial design and suggest that adding this MCED test to routine screening in the United States may shift cancer detection to earlier stages, and potentially save lives.

Circulating cell-free DNA-based multi-cancer early detection

Patients benefit considerably from early detection of cancer. Existing single-cancer tests have various limitations, which could be effectively addressed by circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED). With sensitive detection and accurate localization of multiple cancer types at a very low and fixed false-positive rate (FPR), MCED has great potential to revolutionize early cancer detection. Herein, we review state-of-the-art approaches for cfDNA-based MCED and their limitations and discuss both technical and clinical challenges in the development and application of MCED tests. Given the constant improvements in technology and understanding of cancer biology, we propose that a cfDNA-based targeted sequencing assay that integrates multimodal features should be optimized for MCED.

Multi-Cancer Early Detection: The New Frontier in Cancer Early Detection

The new generation of cancer early detection tests holds remarkable promise for revolutionizing and changing the paradigm of cancer early detection. Dozens of cancer early detection tests are being developed and evaluated. Some are already commercialized and available for use, most as a complement to and not in place of existing recommended cancer screening tests. This review evaluates existing single- and multi-cancer early detection tests (MCEDs), discussing their performance characteristics including sensitivity, specificity, positive and negative predictive values, and accuracy. It also critically looks at the potential harms that could result from these tests, including false positive and negative results, the risk of overdiagnosis and overtreatment, psychological and economic harms, and the risk of widening cancer inequities. We also review the large-scale, population-based studies that are being launched in the United States and United Kingdom to determine the impact of MCEDs on clinically relevant outcomes and implications for current practice.

Predictive Performance of Cell-Free Nucleic Acid-Based Multi-Cancer Early Detection Tests: A Systematic Review

BACKGROUND

Cancer-screening tests that can detect multiple cancer types, or multi-cancer early detection (MCED) tests, have emerged recently as a potential new tool in decreasing cancer morbidity and mortality. Most MCED assays are based on detecting cell-free tumor DNA (CF-DNA) in the blood. MCEDs offer the potential for screening for cancer organ sites with high mortality, both with and without recommended screening. However, their clinical utility has not been established. Before clinical utility can be established, the clinical validity of MCEDs, i.e., their ability to predict cancer status, must be demonstrated. In this study we performed a systematic review of the predictive ability for cancer of cell-free-nucleic acid-based MCED tests.

CONTENT

We searched PubMed for relevant publications from January 2017 to February 2023, using MeSH terms related to multi-cancer detection, circulating DNA, and related concepts. Of 1811 publications assessed, 61 were reviewed in depth and 20 are included in this review. For almost all studies, the cancer cases were assessed at time of diagnosis. Most studies reported specificity (generally 95% or higher) and overall sensitivity (73% median). The median number of cancer types assessed per assay was 5. Many studies also reported sensitivity by stage and/or cancer type. Sensitivity generally increased with stage.

SUMMARY

To date, relatively few published studies have assessed the clinical validity of MCED tests. Most used cancer cases assessed at diagnosis, with generally high specificity and variable sensitivity depending on cancer type and stage. The next steps should be testing in the intended-use population, i.e., asymptomatic persons.

Synthesis and Biological Evaluation of Oxindole Sulfonamide Derivatives as Bruton's Tyrosine Kinase Inhibitors

Bruton's tyrosine kinase (BTK) is a promising molecular target for several human B-cell-related autoimmune disorders, inflammation, and haematological malignancies. The pathogenic alterations in various cancer tissues depend on mutant BTK for cell proliferation and survival, and BTK is also overexpressed in a range of hematopoietic cells. Due to this, BTK is emerging as a potential drug target to treat various human diseases, and several reversible and irreversible inhibitors have been developed and are being developed. As a result, BTK inhibition, clinically validated as an anticancer treatment, is finding great interest in B-cell malignancies and solid tumours. This study focuses on the design and synthesis of new oxindole sulfonamide derivatives as promising inhibitors of BTK with negligible off-target effects. The most cytotoxic compounds with greater basicity were PID-4 (2.29±0.52 μM), PID-6 (9.37±2.47 μM), and PID-19 (2.64±0.88 μM). These compounds caused a selective inhibition of Burkitt's lymphoma RAMOS cells without significant cytotoxicity in non-BTK cancerous and non-cancerous cell lines. Further, PID-4 showed promising activity in inhibiting BTK and downstream signalling cascades. As a potent inhibitor of Burkitt's lymphoma cells, PID-4 is a promising lead for developing novel chemotherapeutics.

Knowledge of Non-Invasive Biomarkers of Breast Cancer, Risk Factors, and BSE Practices Among Nursing Undergraduates in Farasan Island, KSA

Background of the Study

Mammograms are sometimes met with issues of overdiagnosis and underdiagnosis; therefore, they are less reliable in identifying cancer in women with dense breasts. As a result, it is critical to be aware of other sensitive screening techniques for the early diagnosis of breast cancer.

Aim

The ultimate objective of this study was to assess the knowledge of nursing undergraduates regarding non-invasive biomarkers, such as volatile organic compounds in breath, nipple aspirate fluid, sweat, urine, and tears, for the early detection of breast cancer to help improve patient care, determine the risk factors, and encourage practice of breast self-examination.

Methods

Cross-sectional research was done in the Department of Nursing at Farasan campus using a self-structured questionnaire as the study tool. A total of 260 students willingly participated. The study tool had evaluation questions focused on the non-invasive biomarkers of breast cancer, risk factors, and breast self-examination practices to collect data. The data were subjected to descriptive and inferential statistics. The statistical significance was calculated at P < .05. Data analyses were done using Microsoft Excel (2013).

Results

A significant knowledge gap existed among the study participants about the non-invasive biomarkers of breast cancer. A lesser percentage of students (25%) stated that they do breast self-examination on a monthly basis. The most common reasons for not doing the breast self-examination were "not knowing how to do the breast self-examination" (77.3%), fear of a positive diagnosis (53.9%), thinking that they are not at risk as all were in their teens and hence not required (44.7%), and lack of time (48.7%). Age and frequency of breast self-examination were significantly associated (P < .05) as those few students (22.7%) who were doing breast self-examination practices every 2-4 months belonged to a higher study year. Furthermore, knowledge regarding incidence rates and health care expenditure by the government on breast cancer was also significantly low (P < .05).

Conclusions

Outcomes would help prioritize actions to help future nurses better understand breast cancer, allowing them to extend patient care in the best way possible.

Secular trends of morbidity and mortality of thyroid cancer in five Asian countries from 1990 to 2019 and their predictions to 2035

BACKGROUND

The rising burden of thyroid cancer (TC) is a public health problem in Asia. Predicting the future burden of TC in Asian countries is essential for disease prevention.

METHODS

Data were obtained from the Global Burden of Disease 2019 for five Asian countries. We applied Bayesian age-period-cohort models to predict morbidity and mortality to 2035 and calculated age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR). Furthermore, the estimated annual percentage change was calculated to evaluate the variation of ASIR and ASMR.

RESULTS

By 2035, predictions suggest that cases of TC will reach 75.56 × 103 in China, 70.22 × 103 in India, 15.78 × 103 in the Republic of Korea, 9.01 × 103 in Japan and 5.55 × 103 in Thailand, respectively. Except Japan, a significant upward trend of ASIR of TC will be observed in five Asian countries. The deaths from TC will increase in five countries and India will become the highest reaching 14.07 × 103 . The ASMR will rise to 0.83/100 000 in India and 1.06/100 000 in the Republic of Korea, while it will drop to 0.35/100 000 in China, 0.43/100 000 in Japan and 0.50/100 000 in Thailand. In further predictions projected by sex, the growth rate of ASIR is reported higher in males than in females among most countries. ASMR of male will exceed that of females in China and Thailand by 2035.

CONCLUSION

The disease burden caused by TC will further increase in five Asian countries, especially for men. It is necessary to develop more rational and timely disease prevention and manage strategies facing this disease trend.

A non-invasive method for concurrent detection of multiple early-stage cancers in women

Untargeted serum metabolomics was combined with machine learning-powered data analytics to develop a test for the concurrent detection of multiple cancers in women. A total of fifteen cancers were tested where the resulting metabolome data was sequentially analysed using two separate algorithms. The first algorithm successfully identified all the cancer-positive samples with an overall accuracy of > 99%. This result was particularly significant given that the samples tested were predominantly from early-stage cancers. Samples identified as cancer-positive were next analysed using a multi-class algorithm, which then enabled accurate discernment of the tissue of origin for the individual samples. Integration of serum metabolomics with appropriate data analytical tools, therefore, provides a powerful screening platform for early-stage cancers.

Enhancing colposcopy training using a widely accessible digital education tool in China

BACKGROUND

Colposcopy is a cornerstone of cervical cancer prevention; however, there is a global shortage of colposcopists. It is challenging to train a sufficient number of colposcopists through in-person methods, which hinders our ability to adequately diagnose and manage positive cases. A digital platform is needed to make colposcopy training more efficient, scalable, and sustainable; however, current online training programs are generally based on didactic curricula that do not incorporate image analysis training. In addition, long-term assessments of online training are not readily available. Therefore, innovative digital training and an assessment of its effectiveness are needed.

OBJECTIVE

This study aimed to evaluate the short- and long-term effects of DECO (an online Digital Education Tool for Colposcopy) on trainees' colposcopy competencies and confidence.

STUDY DESIGN

DECO can be used both on laptops and smartphones and comprises 4 training modules (image interpretation; terminology learning; video teaching; and collection of guidelines and typical cases) and 2 test modules. DECO was tested through a pre-post study between September and November 2022. Participants were recruited in China, and DECO training lasted 12 days. Trainees initially learned basic theory before completing training using 200 image-based cases. Pretest, posttest, and follow-up testing included 20 distinct image-based questions, and was conducted on Days 0, 13, and 60. Primary outcomes were competence and confidence scores. Secondary measures were response distributions for colposcopic diagnoses, biopsies, and DECO training satisfaction. Multilevel modeling was used to determine improvement from baseline to posttraining and follow-up for the outcomes of interest.

RESULTS

Among 402 participants recruited, 96.8% (n=389) completed pretesting, 84.1% (n=338) posttesting, and 75.1% (n=302) follow-up testing. Colposcopic competence and confidence increased across this study. Diagnostic scores improved on average from 55.3 (53.7-56.9) to 70.4 (68.9-71.9). The diagnostic accuracy for normal/benign lesions, low-grade squamous intraepithelial lesions, and high-grade squamous intraepithelial lesions or worse increased by 16.9%, 13.1%, and 16.9%, respectively. Mean confidence scores increased from 48.1 (45.6-50.6) to 56.2 (54.5-57.9). These improvements remained evident 2 months after training. Trainees were also satisfied with DECO overall. Most found DECO to be scientific (82.5%), easy to use (75.2%), and clinically useful (98.4%), and would recommend it to colleagues (93.2%).

CONCLUSION

DECO is a useful, acceptable digital education tool that improves colposcopy competencies and confidence. DECO could make colposcopy training more efficient, scalable, and sustainable because there are no geographic or time limitations. Therefore, DECO could be used to alleviate the shortage of trained colposcopists around the world.

ProsTAV, a novel blood-based test for biopsy decision management in significant prostate cancer

BACKGROUND

Current pathways in early diagnosis of prostate cancer (PCa) can lead to unnecessary biopsy procedures. Here, we used telomere analysis to develop and evaluate ProsTAV®, a risk model for significant PCa (Gleason score >6), with the objective of improving the PCa diagnosis pathway.

METHODS

This retrospective, multicentric study analyzed telomeres from patients with serum PSA 3-10 ng/mL. High-throughput quantitative fluorescence in-situ hybridization was used to evaluate telomere-associated variables (TAVs) in peripheral blood mononucleated cells. ProsTAV® was developed by multivariate logistics regression based on three clinical variables and six TAVs. The predictive capacity and accuracy of ProsTAV® were summarized by receiver operating characteristic (ROC) curves and its clinical benefit with decision curves analysis.

RESULTS

Telomeres from 1043 patients were analyzed. The median age of the patients was 63 years, with a median PSA of 5.2 ng/mL and a percentage of significant PCa of 23.9%. A total of 874 patients were selected for model training and 169 patients for model validation. The area under the ROC curve of ProsTAV® was 0.71 (95% confidence interval [CI], 0.62-0.79), with a sensitivity of 0.90 (95% CI, 0.88-1.0) and specificity of 0.33 (95% CI, 0.24-0.40). The positive predictive value was 0.29 (95% CI, 0.21-0.37) and the negative predictive value was 0.91 (95% CI, 0.83-0.99). ProsTAV® would make it possible to avoid 33% of biopsies.

CONCLUSIONS

ProsTAV®, a predictive model based on telomere analysis through TAV, could be used to increase the prediction capacity of significant PCa in patients with PSA between 3 and 10 ng/mL.

Computer Vision Identifies Recurrent and Nonrecurrent Ductal Carcinoma in Situ Lesions with Special Emphasis on African-American Women

Although nonrecurrent and recurrent forms of ductal carcinoma in situ (DCIS) of the breast are observed, no evidence-based test can make this distinction. The current retrospective case-control study used archival DCIS samples stained with anti-phospho-Ser226-glucose transporter type 1 and anti-phosphofructokinase type L antibodies. Immunofluorescence micrographs were used to create machine learning models of recurrent and nonrecurrent biomarker patterns, which were evaluated in cross-validation studies. Clinical performance was assessed by holdout studies using patients whose data were not used in training. Micrographs were stratified according to the recurrence probability of each image. Recurrent patients were defined by at least one image with a probability of recurrence ≥98%, whereas nonrecurrent patients had none. These studies found no false-negatives, identified true-positives, and uniquely identified true-negatives. Roughly 20% of the microscope fields of recurrent lesions were computationally recurrent. Strong prognostic results were obtained for both white and African-American women. This machine tool provides the first means to accurately predict recurrent and nonrecurrent patient outcomes. Data indicate that at least some false-positive findings were true-positive findings that benefited from surgical intervention. The intracellular locations of phospho-Ser226-glucose transporter type 1 and phosphofructokinase type L likely participate in cancer recurrences by accelerating glucose flux, a key feature of the Warburg effect.

Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.

Breast cancer incidence in Yogyakarta, Indonesia from 2008-2019: A cross-sectional study using trend analysis and geographical information system

BACKGROUND

Breast cancer is a significant public health concern worldwide, including in Indonesia. Little is known about the spatial and temporal patterns of breast cancer incidence in Indonesia. This study aimed to analyze temporal and spatial variations of breast cancer incidence in Yogyakarta Province, Indonesia.

METHODS

The study used breast cancer case data from the Yogyakarta Population-Based Cancer Registry (PBCR) from 2008 to 2019. The catchment areas of the PBCR included the 48 subdistricts of 3 districts (Sleman, Yogyakarta City, and Bantul). Age-standardized incidence rates (ASR) were calculated for each subdistrict. Joinpoint regression was used to detect any significant changes in trends over time. Global Moran's and Local Indicators of Spatial Association (LISA) analyses were performed to identify any spatial clusters or outliers.

RESULTS

The subdistricts had a median ASR of 41.9, with a range of 15.3-70.4. The majority of cases were diagnosed at a late stage, with Yogyakarta City having the highest proportion of diagnoses at stage 4. The study observed a significant increasing trend in breast cancer incidence over the study period the fastest of which is in Yogyakarta City with an average annual percentage change of 18.77%, with Sleman having an 18.21% and Bantul having 8.94% average changes each year (p <0.05). We also found a significant positive spatial autocorrelation of breast cancer incidence rates in the province (I = 0.581, p <0.001). LISA analysis identified 11 subdistricts which were high-high clusters in the central area of Yogyakarta City and six low-low clusters in the southeast region of the catchment area in the Bantul and Sleman Districts. No spatial outliers were identified.

CONCLUSIONS

We found significant spatial clustering of BC ASR in the Yogyakarta Province, and there was a trend of increasing ASR across the region. These findings can inform resource allocation for public health efforts to high-risk areas and develop targeted prevention and early detection strategies. Further res is needed to understand the factors driving the observed temporal and spatial patterns of breast cancer incidence in Yogyakarta Province, Indonesia.

Diagnostic Scrutiny and Patterns of Elevated Cancer Risk: Uncovering Overdiagnosis Through Standardized Incidence Ratios

Certain medical diagnoses and environmental or occupational exposures may be associated with elevated risk of cancer diagnosis, either through causal mechanisms or via increased detection of a subclinical reservoir through increased diagnostic scrutiny (overdiagnosis). The present study aimed to investigate the distribution of elevated cancer risks associated with different diagnoses and exposures. A systematic literature search was conducted to identify studies published in the last 30 years that examined the standardized incidence ratio (SIR) associated with exposures and risk factors. Meta-SIRs for each cancer type were calculated. The distribution of elevated cancer risks was then compared between cancer types previously reported to be susceptible to overdiagnosis and those that have not been associated with overdiagnosis. The review of 108 studies identified four patterns: SIR generally elevated for 1) only overdiagnosis-susceptible cancer types, 2) both overdiagnosed and non-overdiagnosed cancer types, 3) select cancers in accordance with risk factor or exposure, and 4) SIRs that did not exhibit a distinct increase in any cancer type. The distribution of elevated cancer risks may serve as a signature of whether the underlying risk factor or exposure is a carcinogenic process or a mechanism of increased diagnostic scrutiny uncovering clinically occult diseases. The identification of increased cancer risk should be viewed with caution, and analyzing the pattern of elevated cancer risk distribution can potentially reveal conditions that appear to be cancer risk factors but are in fact the result of exposure to medical surveillance or other healthcare activities that lead to the detection of indolent tumors.

Circulating tumour cells for early detection of clinically relevant cancer

Given that cancer mortality is usually a result of late diagnosis, efforts in the field of early detection are paramount to reducing cancer-related deaths and improving patient outcomes. Increasing evidence indicates that metastasis is an early event in patients with aggressive cancers, often occurring even before primary lesions are clinically detectable. Metastases are usually formed from cancer cells that spread to distant non-malignant tissues via the blood circulation, termed circulating tumour cells (CTCs). CTCs have been detected in patients with early stage cancers and, owing to their association with metastasis, might indicate the presence of aggressive disease, thus providing a possible means to expedite diagnosis and treatment initiation for such patients while avoiding overdiagnosis and overtreatment of those with slow-growing, indolent tumours. The utility of CTCs as an early diagnostic tool has been investigated, although further improvements in the efficiency of CTC detection are required. In this Perspective, we discuss the clinical significance of early haematogenous dissemination of cancer cells, the potential of CTCs to facilitate early detection of clinically relevant cancers, and the technological advances that might improve CTC capture and, thus, diagnostic performance in this setting.

Disparities in survival improvement for U.S. childhood and adolescent cancer between 1995 and 2019: An analysis of population-based data

BACKGROUND

Although treatment advances have increased childhood and adolescent cancer survival, whether patient subgroups have benefited equally from these improvements is unclear.

METHODS

Data on 42,865 malignant primary cancers diagnosed between 1995 and 2019 in individuals ≤ 19 years were obtained from 12 Surveillance, Epidemiology, and End Results registries. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for cancer-specific mortality by age group (0-14 and 15-19 years), sex, and race/ethnicity were estimated using flexible parametric models with a restricted cubic spline function in each of the periods: 2000-2004, 2005-2009, 2010-2014 and 2015-2019, versus 1995-1999. Interactions between diagnosis period and age group (children 0-14 and adolescents 15-19 years at diagnosis), sex, and race/ethnicity were assessed using likelihood ratio tests. Five-year cancer-specific survival rates for each diagnosis period were further predicted.

RESULTS

Compared with the 1995-1999 cohort, the risk of dying from all cancers combined decreased in subgroups defined by age, sex and race/ethnicity with HRs ranging from 0.50 to 0.68 for the 2015-2019 comparison. HRs were more variable by cancer subtype. There were no statistically significant interactions by age group (P_interaction=0.05) or sex (P_interaction=0.71). Despite non-significant differences in cancer-specific survival improvement across different races and ethnicities (P_interaction=0.33) over the study period, minorities consistently experienced inferior survival compared with non-Hispanic Whites.

CONCLUSIONS

The substantial improvements in cancer-specific survival for childhood and adolescent cancer did not differ significantly by different age, sex, and race/ethnicity groups. However, persistent gaps in survival between minorities and non-Hispanic Whites are noteworthy.

3D Bioprinting of an Endothelialized Liver Lobule-like Construct as a Tumor-Scale Drug Screening Platform

3D cell culture models replicating the complexity of cell-cell interactions and biomimetic extracellular matrix (ECM) are novel approaches for studying liver cancer, including in vitro drug screening or disease mechanism investigation. Although there have been advancements in the production of 3D liver cancer models to serve as drug screening platforms, recreating the structural architecture and tumor-scale microenvironment of native liver tumors remains a challenge. Here, using the dot extrusion printing (DEP) technology reported in our previous work, we fabricated an endothelialized liver lobule-like construct by printing hepatocyte-laden methacryloyl gelatin (GelMA) hydrogel microbeads and HUVEC-laden gelatin microbeads. DEP technology enables hydrogel microbeads to be produced with precise positioning and adjustable scale, facilitating the construction of liver lobule-like structures. The vascular network was achieved by sacrificing the gelatin microbeads at 37 °C to allow HUVEC proliferation on the surface of the hepatocyte layer. Finally, we used the endothelialized liver lobule-like constructs for anti-cancer drug (Sorafenib) screening, and stronger drug resistance results were obtained when compared to either mono-cultured constructs or hepatocyte spheroids alone. The 3D liver cancer models presented here successfully recreate liver lobule-like morphology, and may have the potential to serve as a liver tumor-scale drug screening platform.

Peripheral Blood Mononuclear Cell derived Biomarker detection using eXplainable Artificial Intelligence (XAI) provides better diagnosis of Breast Cancer

The incidence and mortality rate of breast cancer increases yearly by an average of 1.44 % and 0.23 %, respectively. Till 2021, there were 7.8 million women who had been diagnosed with breast cancer within 5 years. Biopsies of tumors are often expensive and invasive and raise the risk of serious complications like infection, excessive bleeding, and puncture damage to nearby tissues and organs. Early detection biomarkers are often variably expressed in different patients and may even be below the detection level at an early stage. Hence PBMC that shows alteration in gene profile as a result of interaction with tumor antigens may serve as a better early detection biomarker. Also, such alterations in immune gene profile in PBMCs are more prone to detection despite variability in different breast cancer mutants.This study aimed to identify potential diagnostic biomarkers for breast cancer using eXplainable Artificial Intelligence (XAI) on XGBoost machine learning (ML) models trained on a binary classification dataset containing the expression data of PBMCs from 252 breast cancer patients and 194 healthy women.After effectively adding SHAP values further into the XGBoost model, ten important genes related to breast cancer development were discovered to be effective potential biomarkers. Our studies showed that SVIP, BEND3, MDGA2, LEF1-AS1, PRM1, TEX14, MZB1, TMIGD2, KIT, and FKBP7 are key genes that impact model prediction. These genes may serve as early, non-invasive diagnostic and prognostic biomarkers for breast cancer patients.

Potential of artificial intelligence in the risk stratification for and early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is the third most lethal cancer in the United States, with a 5-year life expectancy of 11%. Most symptoms manifest at an advanced stage of the disease when surgery is no longer appropriate. The dire prognosis of PDAC warrants new strategies to improve the outcomes of patients, and early detection has garnered significant attention. However, early detection of PDAC is most often incidental, emphasizing the importance of developing new early detection screening strategies. Due to the low incidence of the disease in the general population, much of the focus for screening has turned to individuals at high risk of PDAC. This enriches the screening population and balances the risks associated with pancreas interventions. The cancers that are found in these high-risk individuals by MRI and/or EUS screening show favorable 73% 5-year overall survival. Even with the emphasis on screening in enriched high-risk populations, only a minority of incident cancers are detected this way. One strategy to improve early detection outcomes is to integrate artificial intelligence (AI) into biomarker discovery and risk models. This expert review summarizes recent publications that have developed AI algorithms for the applications of risk stratification of PDAC using radiomics and electronic health records. Furthermore, this review illustrates the current uses of radiomics and biomarkers in AI for early detection of PDAC. Finally, various challenges and potential solutions are highlighted regarding the use of AI in medicine for early detection purposes.

Overdiagnosis Due to Screening Mammography for Breast Cancer among Women Aged 40 Years and Over: A Systematic Review and Meta-Analysis

The current systematic review and meta-analysis was conducted to estimate the incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older. A PRISMA systematic search appraisal and meta-analysis were conducted. A systematic literature search of English publications in PubMed, Web of Science, EMBASE, Scopus, and Google Scholar was conducted without regard to the region or time period. Generic, methodological, and statistical data were extracted from the eligible studies. A meta-analysis was completed by utilizing comprehensive meta-analysis software. The effect size estimates were calculated using the fail-safe N test. The funnel plot and the Begg and Mazumdar rank correlation tests were employed to find any potential bias among the included articles. The strength of the association between two variables was assessed using Kendall’s tau. Heterogeneity was measured using the I-squared (I2) test. The literature search in the five databases yielded a total of 4214 studies. Of those, 30 articles were included in the final analysis, with sample sizes ranging from 451 to 1,429,890 women. The vast majority of the articles were retrospective cohort designs (24 articles). The age of the recruited women ranged between 40 and 89 years old. The incidence of overdiagnosis due to screening mammography for breast cancer among women aged 40 years and older was 12.6%. There was high heterogeneity among the study articles (I2 = 99.993), and the pooled event rate was 0.126 (95% CI: 15 0.101–0.156). Despite the random-effects meta-analysis showing a high degree of heterogeneity among the articles, the screening tests have to allow for a certain degree of overdiagnosis (12.6%) due to screening mammography for breast cancer among women aged 40 years and older. Furthermore, efforts should be directed toward controlling and minimizing the harmful consequences associated with breast cancer screening.

Telomerase: A prominent oncological target for development of chemotherapeutic agents

Telomerase is a ribonucleoprotein (RNP) responsible for the maintenance of chromosomal integrity by stabilizing telomere length. Telomerase is a widely expressed hallmark responsible for replicative immortality in 80-90% of malignant tumors. Cancer cells produce telomerase which prevents telomere shortening by adding telomeres sequences beyond Hayflick's limit; which enables them to divide uncontrollably. The activity of telomerase is relatively low in somatic cells and absent in normal cells, but the re-activation of this RNP in normal cells suppresses p53 activity which leads to the avoidance of senescence causing malignancy. Here, we have focused explicitly on various anti-telomerase therapies and telomerase-inhibiting molecules for the treatment of cancer. We have covered molecules that are reported in developmental, preclinical, and clinical trial stages as potent telomerase inhibitors. Apart from chemotherapy, we have also included details of immunotherapy, gene therapy, G-quadruplex stabilizers, and HSP-90 inhibitors. The purpose of this work is to discuss the challenges behind the development of novel telomerase inhibitors and to identify various perspectives for designing anti-telomerase compounds.

Increased Early Cancer Diagnosis: Unveiling Immune-Cancer Biology to Explain Clinical "Overdiagnosis"

Even though clinically small 'early' cancers represent many millions of cells biologically, when removed surgically, these often never recur or regrow, nor reduce the individual's lifespan. However, some early cancers remain quiescent and indolent; while others grow and metastasize, threatening life. Distinguishing between these different clinical behaviours using clinical/pathological criteria is currently problematic. It is reported that many suspicious lesions and early cancers are being removed surgically that would not threaten the patient's life. This has been termed 'overdiagnosis', especially in the sphere of cancer screening. Although a controversial and emotive topic, it poses clinical and public health policy challenges. The diagnostic differentiation between 'non-lethal' and 'lethal' tumor forms is generally impossible. One perspective gathering evidential support is that a dynamic balance exists between the immune response and malignant processes governing 'lethality', where many more cancers are produced than become clinically significant due to the immune system preventing their progression. Higher medical screening "diagnosis" rates may reflect lead-time effects, with more 'non-progressing' cancers detected when an early immune-cancer interaction is occurring. We present a model for this immune-cancer interaction and review 'excess' or 'overdiagnosis' claims that accompany increasingly sensitive diagnostic and screening technologies. We consider that immune tools should be incorporated into future research, with potential for immune system modulation for some early cancers.

Radiomic Machine-Learning Analysis of Multiparametric Magnetic Resonance Imaging in the Diagnosis of Clinically Significant Prostate Cancer: New Combination of Textural and Clinical Features

BACKGROUND

The aim of our study was to develop a radiomic tool for the prediction of clinically significant prostate cancer.

METHODS

From September 2020 to December 2021, 91 patients who underwent magnetic resonance imaging prostate fusion biopsy at our institution were selected. Prostate cancer aggressiveness was assessed by combining the three orthogonal planes-Llocal binary pattern the 3Dgray level co-occurrence matrix, and other first order statistical features with clinical (semantic) features. The 487 features were used to predict whether the Gleason score was clinically significant (≥7) in the final pathology. A feature selection algorithm was used to determine the most predictive features, and at the end of the process, nine features were chosen through a 10-fold cross validation.

RESULTS

The feature analysis revealed a detection accuracy of 83.5%, with a clinically significant precision of 84.4% and a clinically significant sensitivity of 91.5%. The resulting area under the curve was 80.4%.

CONCLUSIONS

Radiomic analysis allowed us to develop a tool that was able to predict a Gleason score of ≥7. This new tool may improve the detection rate of clinically significant prostate cancer and overcome the limitations of the subjective interpretation of magnetic resonance imaging, reducing the number of useless biopsies.

Mediating Role of Lifestyle Behaviors in the Association between Education and Cancer: Results from the European Prospective Investigation into Cancer and Nutrition

BACKGROUND

Many studies have shown that socioeconomic position (SEP) is associated with the incidence of malignant tumors at different sites. This study aims to estimate the association between educational level (as proxy for SEP) and cancer incidence and to understand whether the observed associations might be partially explained by lifestyle behaviors.

METHODS

The analyses were performed on data from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, globally and by sex. We used Cox proportional hazards models together with mediation analysis to disentangle the total effect (TE) of educational level [measured through the Relative Index of Inequality (RII)] on cancer incidence into pure direct (PDE) and total indirect (TIE) effect, unexplained and explained by mediators, respectively. PDE and TIE were then combined to compute the proportions mediated (PM).

RESULTS

After an average of 14 years of follow-up, 52,422 malignant tumors were ascertained. Low educated participants showed higher risk of developing stomach, lung, kidney (in women), and bladder (in men) cancers, and, conversely, lower risk of melanoma and breast cancer (in post-menopausal women), when compared with more educated participants. Mediation analyses showed that portions of the TE of RII on cancer could be explained by site-specific related lifestyle behaviors for stomach, lung, and breast (in women).

CONCLUSIONS

Cancer incidence in Europe is determined at least in part by a socioeconomically stratified distribution of risk factors.

IMPACT

These observational findings support policies to reduce cancer occurrence by altering mediators, such as lifestyle behaviors, particularly focusing on underprivileged strata of the population.

Hepatocellular carcinoma detection via targeted enzymatic methyl sequencing of plasma cell-free DNA

BACKGROUND

Epigenetic variants carried by circulating tumor DNA can be used as biomarkers for early detection of hepatocellular carcinoma (HCC) by noninvasive liquid biopsy. However, traditional methylation analysis method, bisulfite sequencing, with disadvantages of severe DNA damage, is limited in application of low-amount cfDNA analysis.

RESULTS

Through mild enzyme-mediated conversion, enzymatic methyl sequencing (EM-seq) is ideal for precise determination of cell-free DNA methylation and provides an opportunity for HCC early detection. EM-seq of methylation control DNA showed that enzymatic conversion of unmethylated C to U was more efficient than bisulfite conversion. Moreover, a relatively large proportion of incomplete converted EM-seq reads contains more than 3 unconverted CH site (CH = CC, CT or CA), which can be removed by filtering to improve accuracy of methylation detection by EM-seq. A cohort of 241 HCC, 76 liver disease, and 279 normal plasma samples were analyzed for methylation value on 1595 CpGs using EM-seq and targeted capture. Model training identified 283 CpGs with significant differences in methylation levels between HCC and non-HCC samples. A HCC screening model based on these markers can efficiently distinguish HCC sample from non-HCC samples, with area under the curve of 0.957 (sensitivity = 90%, specificity = 97%) in the test set, performing well in different stages as well as in serum α-fetoprotein/protein induced by vitamin K absence-II negative samples.

CONCLUSION

Filtering of reads with ≥ 3 CHs derived from incomplete conversion can significantly reduce the noise of EM-seq detection. Based on targeted EM-seq analysis of plasma cell-free DNA, our HCC screening model can efficiently distinguish HCC patients from non-HCC individuals with high sensitivity and specificity.

Polysaccharides from Chinese materia medica: Perspective towards cancer management

Cancer has always been a focus of global attention, and the difficulty of treatment and poor prognosis have always plagued humanity. Conventional chemotherapeutics and treatment with synthetic disciplines will cause adverse side effects and drug resistance. Therefore, searching for a safe, valid, and clinically effective drug is necessary. At present, some natural compounds have proved to have the potential to fight cancer. Polysaccharides obtained from Chinese materia medica are good anti-cancer ingredients. Polysaccharides are macromolecular compounds of equal or distinct monosaccharides with an α- or β-glycosidic bonds. The anti-cancer activity has been fully demonstrated in vivo and in vitro. However, Chinese materia medica polysaccharides are only used as adjuvant therapy for cancer-related diseases. Hence, this review mainly discusses the chemical composition, biological activity, absorption in vivo, and clinical application of Chinese materia medica polysaccharides. Also, we discussed the anti-cancer mechanism. We also discussed the current research's limitations on treating cancer with Chinese materia medica polysaccharides and insights into future research.

Status quo of Extracellular Vesicle isolation and detection methods for clinical utility

Extracellular vesicles (EVs) are nano-sized particles that hold tremendous potential in the clinical space, as their biomolecular profiles hold a key to non-invasive liquid biopsy for cancer diagnosis and prognosis. EVs are present in most bodily fluids, hence are easily obtainable from patients, advantageous to that of traditional, invasive tissue biopsies and imaging techniques. However, there are certain constraints that hinder clinical use of EVs. The translation of EV biomarkers from "bench-to-bedside" is encumbered by the methods of EV isolation and subsequent biomarker detection currently implemented in laboratories. Although current isolation and detection methods are effective, they lack practicality, with their requirement for high bodily fluid volumes, low equipment availability, slow turnaround times and high costs. The high demand for techniques that overcome these limitations has resulted in significant advancements in nanotechnological devices. These devices are designed to integrate EV isolation and biomarker detection into a one-step method of direct EV detection from bodily fluids. This provides promise for the acceleration of EVs into current clinical standards. This review highlights the importance of EVs as cancer biomarkers, the methodological obstacles currently faced in clinical studies and how novel nanodevices could advance clinical translation.

Artificial intelligence for digital breast tomosynthesis: Impact on diagnostic performance, reading times, and workload in the era of personalized screening

The ultimate goals of the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic performance, and the reduction of interval cancer rates. In this review, after outlining the journey from computer-aided detection/diagnosis systems to AI applied to digital mammography (DM), we summarize the results of studies where AI was applied to DBT, noting that long-term advantages of DBT screening and its crucial ability to decrease the interval cancer rate are still under scrutiny. AI has shown the capability to overcome some shortcomings of DBT in the screening setting by improving diagnostic performance and by reducing recall rates (from -2 % to -27 %) and reading times (up to -53 %, with an average 20 % reduction), but the ability of AI to reduce interval cancer rates has not yet been clearly investigated. Prospective validation is needed to assess the cost-effectiveness and real-world impact of AI models assisting DBT interpretation, especially in large-scale studies with low breast cancer prevalence. Finally, we focus on the incoming era of personalized and risk-stratified screening that will first see the application of contrast-enhanced breast imaging to screen women with extremely dense breasts. As the diagnostic advantage of DBT over DM was concentrated in this category, we try to understand if the application of AI to DM in the remaining cohorts of women with heterogeneously dense or non-dense breast could close the gap in diagnostic performance between DM and DBT, thus neutralizing the usefulness of AI application to DBT.

Copper-cysteamine nanoparticle-mediated microwave dynamic therapy improves cancer treatment with induction of ferroptosis

Photodynamic Therapy (PDT) holds a great promise for cancer patients, however, due to the hypoxic characteristics of most solid tumors and the limited penetration depth of light in tissues, the extensive clinical application of PDT is limited. Herein, we report microwave induced copper-cysteamine (Cu-Cy) nanoparticles-based PDT as a promising cancer treatment to overcome cancer resistance in combination with ferroptosis. The treatment efficiency of Cu-Cy-mediated microwave dynamic therapy (MWDT) tested on HCT15 colorectal cancer (CRC) cells via cell titer-blue cell viability assay and live/dead assay reveal that Cu-Cy upon MW irradiation can effectively destroy HCT15 CRC cells with average IC-50 values of 20 μg/mL. The cytotoxicity of Cu-Cy to tumor cells after MW stimulation can be alleviated by ferroptosis inhibitor. Furthermore, Cu-Cy mediated MWDT could deplete glutathione peroxide 4 (GPX4) and enhance lipid peroxides (LPO) and malondialdehyde (MDA). Our findings demonstrate that MW-activated Cu-Cy killed CRC cells by inducing ferroptosis. The superior in vivo antitumor efficacy of the Cu-Cy was corroborated by a HCT15 tumor-bearing mice model. Immunohistochemical experiments showed that the GPX4 expression level in Cu-Cy + MW group was significantly lower than that in other groups. Overall, these findings demonstrate that Cu-Cy nanoparticles have a safe and promising clinical application prospect in MWDT for deep-seated tumors and effectively inhibit tumor cell proliferation by inducing ferroptosis, which provides a potential solution for cancer resistance.

Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers

Gastrointestinal (GI) cancers, consisting of a wide spectrum of pathologies, have become a prominent health issue globally. Despite medical imaging playing a crucial role in the clinical workflow of cancers, standard evaluation of different imaging modalities may provide limited information. Accurate tumor detection, characterization, and monitoring remain a challenge. Progress in quantitative imaging analysis techniques resulted in "radiomics", a promising methodical tool that helps to personalize diagnosis and treatment optimization. Radiomics, a sub-field of computer vision analysis, is a bourgeoning area of interest, especially in this era of precision medicine. In the field of oncology, radiomics has been described as a tool to aid in the diagnosis, classification, and categorization of malignancies and to predict outcomes using various endpoints. In addition, machine learning is a technique for analyzing and predicting by learning from sample data, finding patterns in it, and applying it to new data. Machine learning has been increasingly applied in this field, where it is being studied in image diagnosis. This review assesses the current landscape of radiomics and methodological processes in GI cancers (including gastric, colorectal, liver, pancreatic, neuroendocrine, GI stromal, and rectal cancers). We explain in a stepwise fashion the process from data acquisition and curation to segmentation and feature extraction. Furthermore, the applications of radiomics for diagnosis, staging, assessment of tumor prognosis and treatment response according to different GI cancer types are explored. Finally, we discussed the existing challenges and limitations of radiomics in abdominal cancers and investigate future opportunities.

Impact of early detection on cancer curability: A modified Delphi panel study

Expert consensus on the potential benefits of early cancer detection does not exist for most cancer types. We convened 10 practicing oncologists using a RAND/UCLA modified Delphi panel to evaluate which of 20 solid tumors, representing >40 American Joint Committee on Cancer (AJCC)-identified cancer types and 80% of total cancer incidence, would receive potential clinical benefits from early detection. Pre-meeting, experts estimated how long cancers take to progress and rated the current curability and benefit (improvement in curability) of an annual hypothetical multi-cancer screening blood test. Post-meeting, experts rerated all questions. Cancers had varying estimates of the potential benefit of early cancer detection depending on estimates of their curability and progression by stage. Cancers rated as progressing quickly and being curable in earlier stages (stomach, esophagus, lung, urothelial tract, melanoma, ovary, sarcoma, bladder, cervix, breast, colon/rectum, kidney, uterus, anus, head and neck) were estimated to be most likely to benefit from a hypothetical screening blood test. Cancer types rated as progressing quickly but having comparatively lower cure rates in earlier stages (liver/intrahepatic bile duct, gallbladder, pancreas) were estimated to have medium likelihood of benefit from a hypothetical screening blood test. Cancer types rated as progressing more slowly and having higher curability regardless of stage (prostate, thyroid) were estimated to have limited likelihood of benefit from a hypothetical screening blood test. The panel concluded most solid tumors have a likelihood of benefit from early detection. Even among difficult-to-treat cancers (e.g., pancreas, liver/intrahepatic bile duct, gallbladder), early-stage detection was believed to be beneficial. Based on the panel consensus, broad coverage of cancers by screening blood tests would deliver the greatest potential benefits to patients.

CMTM6 as a candidate risk gene for cervical cancer: Comprehensive bioinformatics study

Background: CKLF like MARVEL transmembrane domain containing 6 (CMTM6) is an important programmed cell death 1 ligand 1 regulator (PD-L1). CMTM6 was reported as an important regulator of PD-L1 by promoting PD-L1 expression in tumor cells against T cells. However, the function of CMTM6 in cervical cancer is not well characterized. In addition, the role of CMTM6 in the induction of epithelial-mesenchymal transition (EMT) in the context of cervical cancer is unknown. Methods: In this study, we evaluated the role of CMTM6, including gene expression analysis, miRNA target regulation, and methylation characteristic, using multiple bioinformatics tools based on The Cancer Genome Atlas (TCGA) database. The expression of CMTM6 in cervical cancer tissues and non-cancerous adjacent tissues was assessed using immunohistochemistry. In vitro and in vivo function experiments were performed to explore the effects of CMTM6 on growth and metastasis of cervical cancer. Results: Human cervical cancer tissues showed higher expression of CMTM6 than the adjacent non-cancerous tissues. In vitro assays showed that CMTM6 promoted cervical cancer cell invasion, migration, proliferation, and epithelial-mesenchymal transition via activation of mitogen-activated protein kinase (MAPK) c-jun N-terminal kinase (JNK)/p38 signaling pathway. We identified transcription factors (TFs), miRNAs, and immune cells that may interact with CMTM6. Conclusion: These results indicate that CMTM6 is a potential therapeutic target in the context of cervical cancer.

Mitigating Cancer Overdiagnosis

Overdiagnosis refers to the detection of cancers that pose no threat to life and would never have been detected in the absence of screening. It is now a major public health concern throughout the world because advancements in screening technology have substantially increased the detection rates of non-lethal cancers. Cancer overdiagnosis leads to unnecessary treatments, putting patients unnecessarily at risk for the potential morbidity and mortality that may arise from those treatments, and it wastes healthcare resources. Patients may also suffer unnecessary anxiety, job discrimination, financial hardships, and other detrimental effects on quality-of-life following cancer overdiagnosis. In this article, I provide examples of cancer overdiagnosis as a consequence of screening for thyroid, breast, and pancreatic cancers. To mitigate the adverse effects of cancer overdiagnosis, we should adopt only those screening strategies that have been shown in randomized trials to reduce cancer mortality, and we should inform patients about the potential benefits and risks of cancer screening, particularly the risk for overdiagnosis.

Cancer overdiagnosis: a challenge in the era of screening

"Screening" is a search for preclinical, asymptomatic disease, including cancer. Widespread cancer screening has led to large increases in early-stage cancers and pre-cancers. Ubiquitous public messages emphasize the potential benefits to screening for these lesions based on the underlying assumption that treating cancer at early stages before spread to other organs should make it easier to treat and cure, using more tolerable interventions. The intuition is so strong that public campaigns are sometimes launched without conducting definitive trials directly comparing screening to usual care. An effective cancer screening test should not only increase the incidence of early-stage preclinical disease but should also decrease the incidence of advanced and metastatic cancer, as well as a subsequent decrease in cancer-related mortality. Otherwise, screening efforts may be uncovering a reservoir of non-progressive and very slowly progressive lesions that were not destined to cause symptoms or suffering during the person's remaining natural lifespan: a phenomenon known as "overdiagnosis." We provide here a qualitative review of cancer overdiagnosis and discuss specific examples due to extensive population-based screening, including neuroblastoma, prostate cancer, thyroid cancer, lung cancer, melanoma, and breast cancer. The harms of unnecessary diagnosis and cancer therapy call for a balanced presentation to people considering undergoing screening, even with a test of accepted benefit, with a goal of informed decision-making. We also discuss proposed strategies to mitigate the adverse sequelae of overdiagnosis.

Tetrahydroquinoline: an efficient scaffold as mTOR inhibitor for the treatment of lung cancer

Efforts have been made to find an efficient scaffold (and its substitution) that can be used for the treatment of lung cancer via mTOR inhibition. A detailed literature search was carried out for previously reported mTOR inhibitors. The present review is focused on lung cancer; therefore, descriptions of some mTOR inhibitors that are currently in clinical trials for the treatment of lung cancer are provided. Based on previous research findings, tetrahydroquinoline was found to be the most efficient scaffold to be explored for the treatment of lung cancer. A possible efficient substitution of the tetrahydroquinoline scaffold could also be beneficial for the treatment of lung cancer.