Projections of cancer mortality by 2025 in central China: A modeling study of global burden of disease 2019

Advancing Colorectal Cancer Diagnostics from Barium Enema to AI-Assisted Colonoscopy

Colorectal cancer (CRC) remains a major global health burden, necessitating continuous advancements in diagnostic methodologies. Traditional screening techniques, including barium enema and fecal occult blood tests, have been progressively replaced by more precise modalities, such as colonoscopy, liquid biopsy, and artificial intelligence (AI)-assisted imaging. Objective: This review explores the evolution of CRC diagnostic tools, from conventional imaging methods to cutting-edge AI-driven approaches, emphasizing their clinical utility, cost-effectiveness, and integration into multidisciplinary healthcare settings. Methods: A comprehensive literature search was conducted using the PubMed, Medline, and Scopus databases, selecting studies that evaluate various CRC diagnostic tools, including endoscopic advancements, liquid biopsy applications, and AI-assisted imaging techniques. Key inclusion criteria include studies on diagnostic accuracy, sensitivity, specificity, clinical outcomes, and economic feasibility. Results: AI-assisted colonoscopy has demonstrated superior adenoma detection rates (ADR), reduced interobserver variability, and enhanced real-time lesion classification, offering a cost-effective alternative to liquid biopsy, particularly in high-volume healthcare institutions. While liquid biopsy provides a non-invasive means of molecular profiling, it remains cost-intensive and requires frequent testing, making it more suitable for post-treatment surveillance and high-risk patient monitoring. Conclusions: The future of CRC diagnostics lies in a hybrid model, leveraging AI-assisted endoscopic precision with molecular insights from liquid biopsy. This integration is expected to revolutionize early detection, risk stratification, and personalized treatment approaches, ultimately improving patient outcomes and healthcare efficiency.

Bioactive peptides with potential anticancer properties from various food protein sources: status of recent research, production technologies, and developments

Recently, bioactive peptides, from natural resources, have attracted remarkable attention as nutraceutical treasures and the health benefits of their consumption have extensively been studied. Therapies based on bioactive peptides have been recognized as an innovative and promising alternative method for dangerous diseases such as cancer. Indeed, there has been enormous interest in nutraceuticals and bioactive-based chemopreventive molecules as a potential opportunity to manage chronic diseases, including cancer at different stages, rather than the traditionally used therapies. The relative safety and efficacy of these peptides in targeting only the tumor cells without affecting the normal cells make them attractive alternatives to existing pharmaceuticals for the treatment, management, and prevention of cancer, being able to act as potential physiological modulators of metabolism during their intestinal digestion. Novel bioactive peptides derived from food sources can be beneficial as anticancer nutraceuticals and provide a basis for the pharmaceutical development of food-derived bioactive peptides. Bioactive peptides can be generated through different protein hydrolysis methods and purified using advanced chromatographic techniques. Moreover, establishing bioactive peptides' efficacy and mechanism of action can provide alternative methods for cancer prevention and management. Most of the research on anticancer peptides is carried out on cell lines with very limited research being investigated in animal models or human clinical models. In this context, this review article comprehensively discusses anticancer peptides': production, isolation, therapeutic strategies, mechanism of action, and application in cancer therapy.

An integrated bioinformatics approach to early diagnosis, prognosis and therapeutics of non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the most deadly tumors characterized by poor survival rates. Advances in therapeutics and precise identification of biomarkers can potentially reduce the mortality rate. Thus, this study aimed to identify a set of common and stable gene biomarkers through integrated bioinformatics approaches that might be effective for NSCLC early diagnosis, prognosis, and therapies. Four gene expression profiles (GSE19804, GSE19188, GSE10072, and GSE32863) downloaded from the Gene Expression Omnibus database to identify common differential expressed genes (DEGs). A total of 213 overlapping DEGs (oDEGs) between NSCLC and healthy samples were identified by using statistical LIMMA method. Then 6 common top-ranked key genes (KGs) (CENPF, CAV1, ASPM, CCNB2, PRC1, and KIAA0101) were selected by using four network-measurer methods in the protein- protein interaction network. The GO functional and KEGG pathway enrichment analysis were performed to reveal some significant functions and pathways associated with NSCLC progression. Transcriptional and post-transcriptional factors of KGs were identified through the regulatory interaction network. The prognostic power and expression level of KGs were validated by using the independent data through the Kaplan-Meier and Box plots, respectively. Finally, 4 KGs-guided repositioning candidate drugs (ZSTK474, GSK2126458, Masitinib, and Trametinib) were proposed. The stability of three top-ranked drug-target interactions (CAV1 vs. ZSTK474, CAV1 vs. GSK2126458, and ASPM vs. Trametinib) were investigated by computing their binding free energies for 140 ns MD-simulation based on MM-PBSA approach. Therefore, the findings of this computational study may be useful for early prognosis, diagnosis and therapies of NSCLC.

Deciphering Trends in Cancer Mortality: A Comprehensive Analysis of Brazilian Data From 1979 to 2021 With Emphasis on Breast and Prostate Cancers

Background

This study examined cancer mortality trends in Brazil from 1979 to 2021, emphasizing breast and prostate cancers.

Methods

Utilizing data from the Brazilian Mortality Information System and the Brazilian Institute of Geography and Statistics, it analyzed cancer deaths nationally and regionally, highlighting gender-specific and regional disparities.

Results

The research finds that cancer death rates have been growing at an average of 12% per year, contrasting with the population growth rate of 2.2%. This trend is more pronounced in the southern and southeastern regions of Brazil. A comparison of cancer mortality rates between Brazil, the USA, and China reveals that while the Brazilian and Chinese rates exhibit slower growth, the US rate shows a continuous decline since the 1990s.

Conclusions

The study adopts a novel approach by focusing on growth rates and employing polynomial interpolation, revealing a deceleration in cancer death growth over the last 15 years across all malignant neoplasms. The study also contextualizes these findings within Brazil's cancer control policies, tracing the evolution of preventive measures and treatment advancements. It highlights the significant role of the National Cancer Institute and the Unified Health System in implementing effective strategies. The decreasing trend in cancer mortality rates in Brazil, despite population growth, illustrates the effectiveness of comprehensive cancer control and prevention measures, underlining their importance in public health policy.

Trends in breast cancer mortality attributable to metabolic risks in Chinese women from 1990 to 2019: an age-period-cohort analysis

Objective

Metabolic risks (MRs) are the primary determinants of breast cancer (BC) mortality among women. This study aimed to examine the changing trends in BC mortality associated with MRs and explore how they related to age, time period, and birth cohorts in Chinese women aged 25 and above.

Methods

Data were sourced from the Global Burden of Disease Study 2019 (GBD2019). The BC mortality trajectories and patterns attributable to MRs were assessed using Joinpoint regression. The age-period-cohort (APC) model was employed to evaluate cohort and time period effects.

Results

The age-standardized mortality rate (ASMR) of BC mortality linked to MRs displayed an escalating trend from 1990 to 2019, demonstrating an average annual percentage change (AAPC) of 1.79% (95% CI: 1.69~1.87). AAPCs attributable to high fasting plasma glucose (HFPG) and high body mass index (HBMI) were 0.41% (95% CI: 0.32~0.53) and 2.75% (95% CI: 2.68~2.82), respectively. APC analysis revealed that BC mortality due to HBMI in women aged 50 and above showed a rise with age and mortality associated with HFPG consistently demonstrated a positive correlation with age. The impact of HBMI on BC mortality significantly outweighed that of HFPG. The risk of BC mortality linked to HBMI has steadily increased since 2005, while HFPG demonstrated a trend of initial increase followed by a decrease in the period effect. Regarding the cohort effect, the relative risk of mortality was greater in the birth cohort of women after the 1960s of MRs on BC mortality, whereas those born after 1980 displayed a slight decline in the relative risk (RR) associated with BC mortality due to HBMI.

Conclusion

This study suggests that middle-aged and elderly women should be considered as a priority population, and control of HBMI and HFPG should be used as a primary tool to control metabolic risk factors and effectively reduce BC mortality.

Abatement of the binding of human hexokinase II enzyme monomers by in-silico method with the design of inhibitory peptides

The hexokinase II enzyme is bound to the (VDAC1) channel in the form of a dimer and prevents the release of cell death factors from mitochondria to the cytoplasm. Studies have shown that blocking the binding of hexokinase II enzyme to (VDAC1) led to the initiation of apoptosis in cancer cells. No peptide has been designed so far to inhibit hexokinase II. The aim of this study was to inhibit the dimerization of enzyme subunits in order to inhibition the formation of (VDAC1) and the hexokinase II complex. In this study, the molecular dynamics simulation of the enzyme in monomer and dimer states was investigated in terms of RMSF, RMSD and radius of gyration. The following process involves extracting and designing variable-length peptides from the interacting segments of enzyme monomers. Using molecular dynamics simulation, the stability of the peptide was determined in terms of RMSD. Molecular docking was used to investigate the interaction between the designed peptides. Finally, the inhibitory effect of peptides on subunit association was measured using dynamic light scattering (DLS) technique. Our results showed that the designed peptides, which mimic common amino acids in dimerization, interrupt the bona fide form of the enzyme subunits. The result of this study provides a new way to disrupt the assembly process and thereby decreased the function of the hexokinase II.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00201-8.