Late-stage Diagnosis Research Articles

The Role of Race/Ethnicity on the Association between Neighborhood Deprivation and Breast Cancer Outcomes among Kentucky Breast Cancer Patients years 2010-2022.

Kentucky is within the top five leading states for breast mortality nationwide. This study investigates the association between neighborhood socioeconomic disadvantage and breast cancer outcomes, including surgical treatment, radiation therapy, chemotherapy, and survival, and how associations vary by race and ethnicity in Kentucky. We conducted a retrospective cohort analysis using data from the Kentucky Cancer Registry (KCR) for breast cancer patients diagnosed between 2010 and 2017, with follow-up through December 31, 2022. We linked KCR data with census tract data to examine the relationship of Area Deprivation Index (ADI) on breast cancer outcomes. Logistic regression and Cox Proportional Hazards models analyzed binary outcomes and time-to-event data, respectively. Women in the most disadvantaged (ADI 4th quartile) neighborhoods were more likely to be diagnosed at later stages (OR: 1.26, 95% CI: 1.12-1.41) and 34% more likely to die from breast cancer (HR: 1.34, 95% CI: 1.14-1.57) after adjusting for age, race, tobacco use, tobacco pack years, marital status, insurance status, family history, stage at diagnosis, breast cancer subtype, and residence in Appalachia when compared to women living in the least disadvantaged neighborhoods (ADI 1st quartile). Women in disadvantaged neighborhoods had significantly higher odds of late-stage diagnosis and breast cancer death, regardless of race, indicating that neighborhood factors contribute to breast cancer disparities. Socioeconomic and neighborhood factors may contribute to breast cancer outcomes, suggesting the necessity for targeted interventions. Future research should explore the effectiveness of such interventions and investigate additional social determinants contributing to disparities.

Mechanisms of apoptosis-related non-coding RNAs in ovarian cancer: a narrative review.

Ovarian cancer remains a major challenge in oncology due to its complex biology and late-stage diagnosis. Recent advances in molecular biology have highlighted the crucial role of non-coding RNAs (ncRNAs) in regulating apoptosis and cancer progression. NcRNAs, including microRNAs, long non-coding RNAs, and circular RNAs, have emerged as significant players in the molecular networks governing ovarian cancer. Despite these insights, the precise mechanisms by which ncRNAs influence ovarian cancer pathology are not fully understood. This complexity, combined with the heterogeneity of the disease and the development of treatment resistance, poses substantial obstacles to effective therapeutic development. Additionally, the lack of reliable early detection methods further complicates treatment strategies. This manuscript reviews the current state of research on ncRNAs in ovarian cancer, discusses the challenges in translating these findings into clinical applications, and outlines potential future directions. Emphasis is placed on the need for integrated approaches to unravel the intricate roles of ncRNAs, improve early detection, and develop personalized treatment strategies to address the diverse and evolving nature of ovarian cancer. While these findings provide valuable insights, it is crucial to recognize that many results are based on preclinical studies and require further validation to establish their clinical applicability.

Integrating single-cell RNA-Seq and bulk RNA-Seq data to explore the key role of fatty acid metabolism in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a predominant cause of cancer-related mortality globally, noted for its propensity towards late-stage diagnosis and scarcity of effective treatment modalities. The process of metabolic reprogramming, with a specific emphasis on lipid metabolism, is instrumental in the progression of HCC. Nevertheless, the precise mechanisms through which lipid metabolism impacts HCC and its viability as a therapeutic target have yet to be fully elucidated. In the current investigation, single-cell RNA sequencing in conjunction with weighted gene co-expression network analysis (WGCNA) was utilized to delineate lipid metabolism-related genes correlated with the prognostic outcomes of hepatocellular carcinoma (HCC). Data procurement encompassed transcriptomic and clinical datasets from HCC patients, sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories. Subsequent to this, consensus clustering analysis was implemented to stratify patients into distinct subgroups, contingent upon the expression patterns of lipid metabolism genes. Further analytical procedures involved functional enrichment analysis, evaluation of immune infiltration, and examination of the mutation landscape.PTGES3 was identified as a pivotal gene associated with lipid metabolism. Subsequent to its identification, cellular communication analysis was employed to assess the immunological attributes of PTGES3 within the tumor microenvironment. The functional role of PTGES3 was further corroborated through molecular docking simulations and in vitro experimental assays. We identified 27 genes associated with lipid metabolism, 18 of which exhibited significant correlation with overall survival in HCC patients. PTGES3 emerged as a central gene, demonstrating a robust association with immune cell infiltration and unfavorable prognosis. Cellular communication analysis revealed that PTGES3 exhibits the highest communication intensity with T cells, modulating the tumor microenvironment by potentiating the FN1/CD44 + MDK/NCL signaling pathway. Elevated expression of PTGES3 was linked to immunosuppressive cascades, diminished responsiveness to immunotherapy, and inferior overall survival outcomes. Molecular docking analysis indicated that etoposide, methotrexate, and doxorubicin could effectively bind to PTGES3. In vitro experiments confirmed that PTGES3 knockdown significantly impaired the proliferation, invasion, and migration of HCC cells. This study highlights the pivotal role of lipid metabolism in HCC progression and identifies PTGES3 as a potential prognostic biomarker and therapeutic target. These findings offer new insights into the development of targeted therapies for HCC, particularly in patients with high PTGES3 expression.

A Promising Druggable Target for Translational Therapy of Ovarian Cancer: A Molecular Profiling of Therapeutic Innovations, Extracellular Vesicle Acquired Resistance, and Signaling Pathways.

Ovarian cancer (OC) ranks as the fifth leading cause of cancer-related deaths in the United States, posing a significant threat to female health. Late-stage diagnoses, driven by elusive symptoms often masquerading as gastrointestinal issues, contribute to a concerning 70% of cases being identified in advanced stages. While early-stage OC brags a 90% cure rate, progression involving pelvic organs or extending beyond the peritoneal cavity drastically diminishes it. Overcoming chemoresistance and metastasis requires a deep understanding of the associated progression mechanisms for innovative therapies. Extracellular vesicles (EVs), containing proteins, RNAs, DNAs, and metabolites, have surged in recent years, significantly impacting tumor progression, recurrence, immune evasion, and metastasis associated with the ovarian tumor microenvironment. Recent research unveils organ-specific metastatic patterns in OC, providing insights into tumor cell interactions and signaling crosstalk with stromal cells. The review explores the role of EVs behind OC cell metastasis and chemoresistance. Furthermore, the article delves into the role of EVs in the tumor microenvironment, immune evasion, and as biomarkers in context to OC, offering promising therapeutic strategies to enhance survival rates for OC patients. Lastly, the article focuses on an overview of PI3K/AKT/mTOR, MAPK/ERK, and VEGFR signaling pathways in the pathophysiology of ovarian cancer.

Liquid biopsy: an emerging field with new opportunities for cancer diagnosis and prognosis

Cancer grades among the deadliest diseases, globally causing the death of a over million people each year. Early diagnosis has been considered ideal for efficient treatment as during later stages chances of treatment become limited. However, gold standard tissue biopsy has various limitation for instance, late-stage diagnosis and its intrusive operation making it unfit for repeated sampling. Scientists are passionately looking for new technologies and techniques for cancer diagnosis and prognosis. Liquid biopsy has emerged as new diagnostic and prognostic tool for cancer, that relies on body fluids to identify biomarkers for cancer. It offers advantages like non-invasive operation, timely detection, amenable to repeated sampling, and covers the tumor heterogeneity. Wide attention has been garnered by liquid biopsy and is undergoing rapid progress in the list of target biomarkers. The most common are circulating tumor cells, circulating tumor DNA, exosomes, tumor educated platelets, and non-coding RNAs (miRNA, lncRNA etc.). Each of these biomarkers have unique advantages, making liquid biopsy indeed a technology of future for cancer diagnosis with clinical utility. In this article, we tried to provide a thorough introduction of liquid biopsy and its markers, highlighted the common biomarkers that are deployed in liquid biopsy, briefly overview their implications as indispensable diagnostic and prognostic entities for the diverse types of cancer. Moreover, discussed future prospects of this revolutionary technology in the realm of cancer diagnosis and treatment.

Novel oncogenes and tumor suppressor genes in Hepatocellular Carcinoma: Carcinogenesis, progression, and therapeutic targets.

Hepatocellular carcinoma (HCC) is the primary malignancy affecting the liver and the leading cause of mortality among individuals with cirrhosis. This complex disease is associated with various risk factors, including environmental, pathological, and genetic influences, which dysregulate gene expression crucial for the cell cycle and cellular/molecular pathways. The disruption of the balance between tumor suppressors and proto-oncogenes amplifies the pathogenic cascade. Given its predilection for diseased or cirrhotic livers and late-stage diagnosis, HCC prognosis is typically poor. Current therapies offer limited benefits, with conventional non-specific cytotoxic agents exhibiting suboptimal efficacy. However, molecularly targeted therapies have emerged as a promising avenue, leveraging the strategic inhibition of carcinogenic molecules to provide heightened specificity and potency compared to cytotoxic chemotherapy. Several clinical trials have demonstrated promising outcomes in advanced HCC with targeted pharmacotherapies. Many genes have been implicated in HCC pathogenesis, underscoring the need to elucidate their molecular functions and roles. This has profound implications for early HCC prognostication via biomarkers and for identifying therapeutic targets to impede neoplastic progression. Notably, evidence highlights the pivotal roles of oncogenes and tumor suppressors in HCC pathophysiology. This discourse examines the potential involvement of ABL1, Annexins, FAK, FOX, and KIF as candidate oncogenes, contrasted with SORBS2, HPCAL1, PCDH10, PLAC8, and CXXC5 as plausible tumor suppressors. Their signaling cascades and relevance to HCC prognosis and progression are delineated to identify targets for improving HCC diagnosis, prognostication, and therapy.

Oral cavity and oropharyngeal cancers in Texas: examining incidence rates in dental health professional shortage areas.

Oral cavity (OC) and oropharyngeal (OP) cancer rates have increased annually rising in the U.S. and Texas. Dental providers could play a key role in lowering OC/OP cancer rates through prevention and screening, but Texas faces a significant shortage of dental health professionals, affecting access to dental care, including OC/OP cancer prevention and early detection. This study aims to explore the link between OC/OP cancer rates and these dental shortage areas in Texas. We analyzed OC/OP cancer incidence in Texas using SEER-Medicare data for patients aged 65 and over from 2012 to 2017. Rates per 100,000 were stratified by age, gender, and dental health provider shortage area (DHPSA) status (yes/no). Zero-Inflated Poisson Regression models were used to adjust for patient characteristics in studying cancer incidence, Late-stage diagnoses were assessed using logistic regression. The incidence rate was 27.3 per 100,000 people in Texas. DHPSA counties had lower incidence rates (24.3 per 100,000) compared to non-DHPSA counties (29.8 per 100,000; p = 0.0423). Among patients with OC/OP diagnoses, those living in a DHPSA county had lower odds of advanced stage diagnoses (aOR: 0.79; CI: 0.64-0.96) than those in non-DHPSA counties. The findings highlight the complex link between dental providers and OC/OP cancer diagnoses, noting differences in indicators of need based on DHPSA location. Limited local dental services may lead to underreported cancer cases. Further research on dental service usage could improve OC/OP outcomes by prioritizing interventions from dental professionals.

Doxycycline Restores Gemcitabine Sensitivity in Preclinical Models of Multidrug-Resistant Intrahepatic Cholangiocarcinoma

Background/Objectives: Intrahepatic cholangiocarcinoma (iCCA) is a malignant liver tumor with a rising global incidence and poor prognosis, largely due to late-stage diagnosis and limited effective treatment options. Standard chemotherapy regimens, including cisplatin and gemcitabine, often fail because of the development of multidrug resistance (MDR), leaving patients with few alternative therapies. Doxycycline, a tetracycline antibiotic, has demonstrated antitumor effects across various cancers, influencing cancer cell viability, apoptosis, and stemness. Based on these properties, we investigated the potential of doxycycline to overcome gemcitabine resistance in iCCA. Methods: We evaluated the efficacy of doxycycline in two MDR iCCA cell lines, MT-CHC01R1.5 and 82.3, assessing cell cycle perturbation, apoptosis induction, and stem cell compartment impairment. We assessed the in vivo efficacy of combining doxycycline and gemcitabine in mouse xenograft models. Results: Treatment with doxycycline in both cell lines resulted in a significant reduction in cell viability (IC50 ~15 µg/mL) and induction of apoptosis. Doxycycline also diminished the cancer stem cell population, as indicated by reduced cholangiosphere formation. In vivo studies showed that while neither doxycycline nor gemcitabine alone significantly reduced tumor growth, their combination led to marked decreases in tumor volume and weight at the study endpoint. Additionally, metabolic analysis revealed that doxycycline reduced glucose uptake in tumors, both as a monotherapy and more effectively in combination with gemcitabine. Conclusions: These findings suggest that doxycycline, especially in combination with gemcitabine, can restore chemotherapy sensitivity in MDR iCCA, providing a promising new strategy for improving outcomes in this challenging disease.

The multi-target mechanism of action of Selaginella doederleinii Hieron in the treatment of nasopharyngeal carcinoma: a network pharmacology and multi-omics analysis

Nasopharyngeal carcinoma (NPC) presents significant treatment challenges due to its complex etiology and late-stage diagnosis. The traditional Chinese medicine Selaginella doederleinii Hieron (S. doederleinii) has shown potentiality in NPC treatment due to its multi-target, multi-pathway anti-cancer mechanisms. First, we identified NPC related target genes from databases like GeneCards, OMIM, and DisGeNET, and performed WGCNA analysis on the GSE53819 dataset to identify several important gene modules related to NPC. Active components and their targets in S. doederleinii were screened from the TCMSP and other databases, identifying 32 overlapping genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these genes are primarily involved in critical biological processes like protein phosphorylation and cell cycle regulation. A protein–protein interaction network was constructed, and cytoHubba identified six key genes (BCL2, MAPK14, ABCB1, PLK1, ATM, HMOX1). Kaplan–Meier analysis and immune infiltration analysis further showed that these key genes are closely related to the prognosis and immune microenvironment of NPC patients. Single-cell RNA sequencing analysis revealed the expression distribution of key genes across different immune cell types and explored their roles in the differentiation process of malignant cells through pseudotime trajectory analysis. Molecular docking and dynamics simulation results indicated that the Berberine-MAPK14 and Matairesinol-PLK1 complexes have high binding affinity and stability. Binding free energy calculations confirmed the stability of these complexes. Based on our comprehensive multi-level analysis, the active components of S. doederleinii may play a significant role in the treatment of NPC through multi-pathway and multi-target synergistic effects.

Gene expression profiling for the diagnosis of male breast cancer

BackgroundMale breast cancer (MBC) is a rare malignancy, but its global incidence has shown a notable increase in recent decades. Factors such as limited health literacy, inadequate health education, and reluctance to seek medical attention contribute to the late-stage diagnosis of most MBC patients. Consequently, there is an urgent need for a highly specific and sensitive diagnostic approach to MBC.MethodsThis retrospective study enrolled 20 patients with 30 surgical or biopsy MBC specimens from August 2020 to August 2023. The 90-gene expression assay was performed to determine the tissue of origin. Predicted tumor types were then compared to the reference diagnosis for accuracy calculation. The differentially expressed genes were identified between male and female breast cancer.ResultThe 90-gene expression assay demonstrated an overall accuracy of 96.7% (29/30) when compared with the pathological diagnosis. For primary, lymph node metastatic, and distant metastatic tumors, the accuracies were 100% (15/15), 90.9% (10/11), and 100% (4/4), respectively. Five genes (RPS4Y1, PI15, AZGP1, PRRX1, and AGR2) were up-regulated, and six (XIST, PIGR, SFRP1, PLA2G2A, S100A2, and CHI3L1) were down-regulated in MBC.ConclusionOur findings highlight the promising performance of the 90-gene expression assay in accurately identifying the tumor origin in MBC. Incorporating this assay into pathological diagnoses has the potential to empower oncologists with precision treatment options, ultimately enhancing the care and outcomes for patients with MBC.

Exploration of the Antitumor Mechanism of Fruquintinib in Colorectal Cancer via Autophagy Regulation

Colorectal cancer (CRC) ranks as the second leading cause of cancer-related mortality worldwide, with treatment challenges largely attributed to late-stage diagnoses, frequent recurrences, and resistance to therapy. In recent years, Fruquintinib, a selective vascular endothelial growth factor receptor (VEGFR) inhibitor, has shown notable effectiveness in advanced CRC by targeting angiogenesis. However, CRC cells often activate autophagy in response to hypoxia and nutrient deprivation caused by anti-angiogenic therapy, which diminishes the therapeutic efficacy of Fruquintinib. Autophagy plays a dual role in CRC by suppressing tumorigenesis through the removal of damaged organelles, while facilitating tumor progression and therapeutic resistance through metabolic adaptation in advanced stages. This complexity underscores the therapeutic promise of strategies targeting autophagy. Current studies reveal that Fruquintinib induces autophagy by inhibiting VEGFR signaling, activating AMPK, and suppressing mTOR, while interacting synergistically with other cell death mechanisms such as apoptosis, ferroptosis, and pyroptosis to enhance its antitumor activity. However, excessive autophagy activation may enable tumor cell survival and promote resistance, highlighting the necessity of precise modulation of autophagy in combination therapies. Moreover, preclinical studies indicate that combining Fruquintinib with autophagy modulators significantly enhances its antitumor effects and delays resistance emergence. This review offers a systematic analysis of Fruquintinib's antitumor mechanisms via autophagy modulation and its potential clinical implications. Based on the reviewed evidence, we propose strategies to optimize Fruquintinib-based combination therapies, including the use of autophagy-related biomarkers, autophagy modulators, and precision medicine approaches tailored to tumor genomic profiles, aiming to enhance treatment outcomes for CRC patients.

Pulmonologists-level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach.

Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage diagnoses. Effective strategies for early detection are therefore of paramount importance. In recent years, machine learning (ML) has demonstrated considerable potential in healthcare by facilitating the detection of various diseases. In this retrospective development and validation study, we developed an ML model based on dynamic ensemble selection (DES) for LC detection. The model leverages standard blood sample analysis and smoking history data from a large population at risk in Denmark. The study includes all patients examined on suspicion of LC in the Region of Southern Denmark from 2009 to 2018. We validated and compared the predictions by the DES model with diagnoses provided by five pulmonologists. Among the 38,944 patients, 9,940 had complete data of which 2,505 (25%) had LC. The DES model achieved an area under the roc curve of 0.77±0.01, sensitivity of 76.2%±2.04%, specificity of 63.8%±2.3%, positive predictive value of 41.6%±1.2%, and F1-score of 53.8%±1.0%. The DES model outperformed all five pulmonologists, achieving a sensitivity 6.5% higher than their average. The model identified smoking status, lactate dehydrogenase, age, total calcium levels, low values of sodium, leucocytes, neutrophil count, and C-reactive protein as the most important factors for LC detection. The results highlight the successful application of the ML approach in detecting LC, surpassing pulmonologists' performance. Incorporating clinical and laboratory data in future risk assessment models can improve decision-making and facilitate timely referrals.

Advancements and challenges in the treatment of esophageal cancer: A comprehensive review

Esophageal cancer (EC) is an aggressive malignancy with a poor prognosis, ranking seventh in incidence and sixth cancer-related deaths globally. EC is classified in two main types, the esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC), with ESCC being more common in Eastern Europe, South Asia, and Africa, while EAC is prevalent in Western Europe and North America. Molecular analysis identifies three subgroups of ESCC, each with distinct genetic mutations and treatment responses. Early-stage EC is often difficult to detect, leading to late-stage diagnoses that necessitate systemic drug therapies, including molecular-targeted therapies and immunotherapies. Immunotherapy, particularly immune checkpoint inhibitor, has shown promising results in improving survival rates for metastatic or persistent EC. It is particularly important to target to multidisciplinary combination therapies, integrating surgery, chemoradiotherapy, targeted therapy and immunotherapy. Additionally, radioimmunotherapy is being explored for its potential to enhance treatment efficacy, especially in advanced and metastatic tumors. However, the pathological complete response rate to neoadjuvant chemoradiotherapy remains suboptimal, highlighting the need for novel treatment strategies. Future research should focus on optimizing treatment combinations and identifying predictive biomarkers to improve clinical outcomes for EC patients.

Low-cost predictive models of dementia risk using machine learning and exposome predictors

Abstract Purpose Diagnosing dementia, affecting over 55 million people globally, is challenging and costly, often leading to late-stage diagnoses. This study aims to develop early, accurate, and cost-effective dementia screening methods using exposome predictors and machine learning. We investigate whether low-cost exposome predictors combined with machine learning models can reliably identify individuals at risk of dementia. Methods We analyzed data from 500,000 UK Biobank participants, selecting 1523 diagnosed with dementia and an equal number of healthy controls, matched by age and sex. A total of 3046 participants were included: 2740 for internal validation and 306 for external validation. We used 128 low-cost exposome factors from baseline visits, imputed missing data, and assessed two predictive models: a classical logistic regression and a machine learning ensemble classifier (XGBoost). Feature importance was estimated within the predictive models. Results The XGBoost model outperformed the logistic regression model, achieving a mean AUC of 0.88 in external validation. We identified novel exposome factors that might be combined as potential markers for dementia, such as facial aging, the frequency of use of sun/ultraviolet light protection, and the length of mobile phone use. Conclusions Machine learning models utilizing exposome data can reliably identify individuals at risk of dementia, with XGBoost showing superior performance. This approach highlights the potential of low-cost, readily available exposome factors as markers for dementia. Future studies should validate these findings in diverse populations and explore the integration of additional exposome factors to enhance prediction accuracy.

Exosomal miR-6126 as a novel therapeutic target for overcoming resistance of anti-cancer effect in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) stands as the sixth most prevalent cancer globally, presenting a substantial health challenge, particularly due to late-stage diagnoses that limit treatment effectiveness. Sorafenib, a multi-kinase inhibitor, is the primary chemotherapeutic agent for advanced HCC, but it only extends survival by 2–3 months. However, drug resistance remains a major clinical challenge, necessitating the exploration of new molecular mechanisms, including the role of microRNAs (miRNAs) in sorafenib resistance. In this study, we aimed to identify miRNAs within exosomes derived from sorafenib-resistant HCC cells to elucidate the molecular mechanisms underlying resistance.MethodsSorafenib-resistant cells were generated by culturing the human HCC cell line Huh7 in a medium containing 20 µM sorafenib for six months. Exosomes were isolated from the conditioned medium 24 h before cell harvest using exosome-depleted serum medium. miRNA sequencing and western blotting were used to analyze the expression profiles of exosomal miRNAs and proteins, respectively. pH measurement was performed to assess pH changes in response to sorafenib treatment and miRNA modulation.ResultsA total of 180 exosomal miRNAs were found to be dysregulated between sorafenib-treated control Huh7 (Huh7S) and sorafenib-resistant Huh7 (Huh7RS) cells, as well as between untreated control Huh7 and Huh7RS cells. Among these, miR-6126 was significantly downregulated in Huh7RS cells compared to Huh7S cells. Functional studies using 2-dimensional (D) and 3D cell culture systems revealed that miR-6126 overexpression reduced sorafenib resistance in Huh7RS cells, while its inhibition increased resistance in Huh7 cells. miR-6126 downregulated key proteins involved in cancer stem cell maintenance, such as CD44 and HK2. Furthermore, the pH level was elevated in cells overexpressing miR-6126 following sorafenib treatment, whereas inhibiting miR-6126 resulted in a lower pH.ConclusionsExosomal miR-6126 plays a pivotal role in sorafenib resistance and tumorigenesis, highlighting its potential as a novel therapeutic target for overcoming drug resistance in HCC.

Cancer Stage Geospatial Analysis to Optimize Educational Activities in Pediatric Oncology and Hematology: A Retrospective Cohort Study.

Enhancing therapy outcomes in pediatric oncology and hematology relies on robust epidemiological surveillance. This study aimed to estimate cancer stage-related survival in pediatric patients with lymphoma and solid tumors by assessing changes over time and identifying spatial clustering of patients diagnosed at advanced stages. This retrospective observational cohort study included pediatric cancer patients treated in a single Greater Poland center, constituting 9% of Polish children from 2004 to 2017. The incidence, cancer stage, and patient coordinates were analyzed. The follow-up period ranged from 5 to 18years. Survival differences across tumor stages were evaluated using Kaplan‒Meier curves, log-rank tests, and trend analysis. Geographical analysis was performed with Kulldorff's scan statistics and the Bernoulli model. Among 1094 diagnosed patients, 511 with lymphoma and solid tumors were eligible. There was a decreasing trend in advanced-stage diagnoses (p = 0.0001), with a nearly twofold increase in low-stage diagnoses (OR = 1.98 [1.22; 3.24], p = 0.0061) from 2009-2011 to 2015-2017. Hazard ratios for neuroblastoma and sarcoma patients were more than fourfold greater, while survival differences were not significant for patients with nephroblastoma, germ cell tumors, or lymphoma. This study shows cancer stage-related survival dynamics. A substantial decrease in advanced-stage diagnoses over time emphasizes improved early detection. Geographical analysis pinpointed clusters with prevalent late-stage diagnoses, offering a practical tool for targeted educational interventions. The study underscores the pivotal impact of cancer stage on survival outcomes, emphasizing the need for ongoing surveillance and tailored interventions to further optimize pediatric oncology and hematology care.

Exploring Metabolic Approaches for Epithelial Ovarian Cancer Therapy.

Epithelial ovarian cancer (EOC) has the highest mortality rate among malignant tumors of the female reproductive system and the lowest survival rate. This poor prognosis is due to the aggressive nature of EOC, its late-stage diagnosis, and the tumor's ability to adapt to stressors through metabolic reprogramming. EOC cells sustain their rapid proliferation by altering the uptake, utilization, and regulation of carbohydrates, lipids, and amino acids. These metabolic changes support tumor growth and contribute to metastasis, chemotherapy resistance, and immune evasion. Targeting these metabolic vulnerabilities has shown promise in preclinical studies, with some therapies advancing to clinical trials. However, challenges remain due to tumor heterogeneity, adaptive resistance mechanisms, and the influence of the tumor microenvironment. This review provides a comprehensive summary of metabolic targets for EOC treatment and offers an overview of the current landscape of clinical trials focusing on ovarian cancer metabolism. Future efforts should prioritize combination therapies that integrate metabolic inhibitors with immunotherapies or chemotherapy. Advances in precision medicine and multi-omics approaches will be crucial for identifying patient-specific metabolic dependencies and improving outcomes. By addressing these challenges, metabolism-based therapies can significantly transform the treatment of this devastating disease.

Survival of Patients with Resected Microsatellite Instability-High, Mismatch Repair Deficient, and Lynch Syndrome-Associated Pancreatic Ductal Adenocarcinomas.

Pancreatic ductal adenocarcinoma (PDAC) remains a challenging disease due to its aggressiveness, late-stage diagnosis, and limited treatment options. Microsatellite instability-high (MSI-H) cancersare susceptible to immune checkpoint inhibitors. Survival outcomes for patients with MSI-H PDAC are unknown as the disease is rare. This study included patients with PDACs surgically resected from 1990 to 2023, and those with germline or sporadic pathogenic variants in DNA mismatch repair genes were identified. The study matched MSI-H, mismatch repair-deficient (MMRd), and Lynch syndrome (LS)-associated PDAC cases (on age, gender, and year of surgery) with microsatellite-stable (MSS), mismatch repair-proficient, or non-LS-associated PDAC cases in a 1:2 ratio. A generalized estimating equation Cox model with a robust sandwich estimator was used to compare overall survival (OS) in the matched cohorts. Of 936 cases, 18 were included. Eight cases were MSI-H/MMRd, two were MSI/IHC-indeterminate, seven were MSS, and one was not tested for MSI. Nine patients had LS (MLH1 [n = 1], MSH2 [n = 4], MSH6 [n = 1], PMS2 [n = 3]), and nine patients had sporadic pathogenic variants in DNA MMR genes (MLH1 [n = 4], MSH6 [n = 5]). After matching to 36 control patients, the MSI-H/MMRd/LS PDACs had a significantly better OS (hazard ratio [HR], 0.36 [95% confidence interval [CI], 0.18-0.73; p = 0.005]; 5-year OS: MSI-H 77% [95% CI 58-100%] vs. MSS 27% [95% CI 15-51%]). Before routine use of immune checkpoint inhibitors, the patients with MSI-H, MMRd, and LS-associated PDACs displayed significantly better survival than the patients with MSS, MMR-proficient, non-LS-associated PDACs. It is expected that survival for this cohort will further improve with increased availability of immunotherapy.

Endothelial Dysfunction Markers in Ovarian Cancer: VTE Risk and Tumour Prognostic Outcomes.

Ovarian cancer (OC) presents daunting lethality rates worldwide, with frequent late-stage diagnosis and chemoresistance, highlighting the need for improved prognostic approaches. Venous thromboembolism (VTE), a major cancer mortality factor, is partially driven by endothelial dysfunction (ED). ED's pro-inflammatory state fosters tumour progression, suggesting a VTE-independent link between ED and cancer. Given this triad's interplay, ED markers may influence OC behaviour and patients' prognosis. Thus, the impact of ED-related genes and single-nucleotide polymorphisms (SNPs) on OC-related VTE and patient thrombogenesis-independent prognosis was investigated. NOS3 upregulation was linked to lower VTE incidence (χ2, p = 0.013), while SELP upregulation was associated with shorter overall survival (log-rank test, p = 0.048). Dismissing patients with VTE before OC diagnosis, SELP rs6136 T allele carriers presented lower progression-free survival (log-rank test, p = 0.038). Nevertheless, due to the SNP minor allele underrepresentation, further investigation is required. Taken together, ED markers seem to exhibit roles that depend on the clinical context, such as tumour-related thrombogenesis or cancer prognosis. Validation with larger cohorts and more in-depth functional studies are needed for data clarification and potential therapeutic strategies exploitation to tackle cancer progression and thrombosis in OC patients.

The effectiveness of health promotion (audiovisual and leaflet) on adolescents' behavior regarding breast self-examination

Introduction: Breast cancer is a leading cause of mortality among women worldwide. Early Breast Self-Examination (BSE) detection can be crucial in reducing late-stage diagnosis and improving survival rates. This study aims to evaluate the effectiveness of audiovisual media and leaflet-based health promotion on adolescents' knowledge, attitudes, and practices regarding breast self-examination. Research Methodology: This type of research is quantitative. The design used is the pre-test-posttest control group design, which is considered relevant to the assessment of health education or training initiatives. The sampling method used is random sampling. The paired t-test was used for data analysis, and the independent t-test was used to compare the variation in knowledge scores between the two treatments. Result: Paired tests showed that the average knowledge score of the V2 group was higher than that of the V1 group (20.934 vs. 10.208) in the pre-test to post-test-1, with a significant increase in knowledge (p<0.05) between the two groups. Similarly, the average knowledge score of the V2 group was higher than that of the V1 group (19.646 vs. 7.183) in the pre-test to post-test-2, and their attitude change was more significant than that of the V1 group (7.980 vs. 2.765). However, in the pre-test to post-test-1, the attitude change between the V1 and V2 groups was insignificant (p>0.05). Likewise, the average attitude change score of the V2 group in the pre-test to post-test-2 was higher than that of the V1 group (6.555 vs. 2.009), although the difference was not statistically significant (p>0.05). Conclusion: This study concludes that the leaflet approach to adolescents' behavior regarding breast self-examination (BSE) substantially impacts improving knowledge and attitudes about the effectiveness of health promotion before and after its implementation.