Cancer Control最新文献

Purpose: This prospective study aimed to investigate estrogen-induced carcinogenesis by assessing the background levels of abasic sites (apurinic/apyrimidinic sites, AP sites) in Taiwanese breast cancer patients following 5 years of postoperative treatment without recurrence (5-year survivors) (n = 70). The study also sought to compare the extent of these DNA lesions with those found in healthy controls and in breast cancer patients prior to treatment.

Methods: Abasic sites were measured using an aldehyde reactive probe and quantified as the total number of abasic sites per total nucleotides. Characterization of the abasic sites in subjects recruited for this study was conducted using the abasic site cleavage assay using putrescine or T7 exonuclease (T7 Exo) and/or exonuclease III (Exo III).

Results: The number of abasic sites detected in 5 year survivors (26.7 ± 10.2 per 10⁶ total nucleotides, n = 70) was significantly reduced by 46.9% compared to those in breast cancer patients before treatment (50.3 ± 59.2 per 10⁶ total nucleotides, P < 0.001), and was similar to the levels observed in healthy controls (23.3 ± 13.5 per 10⁶ total nucleotides, P > 0.05). Further investigation into the specific types of abasic sites indicated that the number of abasic sites excisable by putrescine in controls, breast cancer patients, and 5-year survivors were 63.3%, 78.6%, and 67.7%, respectively. These findings suggest the involvement of oxidative stress rather than depurination/depyrimidination of DNA adducts in the formation of abasic sites. Further analyses were performed using exonuclease cleavage assay to characterize the specific types of abasic sites including 5'-cleaved, 3'-cleaved, intact, and residual abasic sites. Results demonstrated that the proportion of residual abasic sites detected in controls, breast cancer patients, and 5-year survivors were estimated to be 32.7%, 48.8%, and 34.0%, respectively.

Conclusion: Overall, these findings suggest clear evidence of treatment-related effects on the reduction of levels of abasic sites as well as on the profile of abasic sites in 5 year survivors.

Objective: To obtain breast cancer survival estimates in Manizales, Colombia, considering socioeconomic level, health insurance regime and residential area, while adjusting for age, histology and stage at diagnosis.

Methods: Analytical cohort study based on breast cancer incident cases recorded by the Population-based Manizales Cancer Registry between 2008-2015. Patients were followed-up for 60 months. Cause-specific survival was calculated using the Kaplan-Meier method for variables of interest, with the Wilcoxon-Breslow-Gehan test for differences. Cox multivariate regression models were fitted.

Results: 856 breast cancer cases were included. The 5-year cause-specific survival for the entire cohort was 78.2%. It was higher in women with special/exception health insurance, high socioeconomic level, <50 years old, ductal carcinoma, and stages I and II. Residential area did not impact survival. In Cox models, the subsidized health insurance regime (HR: 4.87 vs contributory) and low socioeconomic level (HR: 2.45 vs high) were predictors of the hazard of death in women with breast cancer, adjusted for age, histology, stage and interactions age-stage and insurance-stage. A positive interaction (synergistic effect modification) between health insurance regime and stage regarding to survival was observed.

Conclusion: Socioeconomic factors significantly contribute to the inequities in breast cancer survival, independent of the stage at diagnosis. This suggests the need for comprehensive interventions to remove barriers to accessing the health system. This research provides evidence of survival gaps mediated by certain social determinants of health and generates data on the overall performance of the Colombian health system.

Background: APOBEC-1 complementation factor (A1CF) and Apolipoprotein B mRNA editing enzyme, catalytic polypeptide-1 (APOBEC-1) constitute the minimal proteins necessary for the editing of apolipoprotein B (apoB) mRNA in vitro. Unlike APOBEC-1 and apoB mRNA, the ubiquitous expression of A1CF in human tissues suggests its unique biological significance, with various factors such as protein kinase C, thyroid hormones, and insulin regulating the activity and expression of A1CF. Nevertheless, few studies have provided an overview of this topic.

Objective: We conducted a literature review to describe the molecular mechanisms of A1CF and its relevance to human diseases.

Method: In the PubMed database, we used the keywords 'A1CF' and 'APOBEC-1 complementation factor' to collect peer-reviewed articles published in English from 2000 to 2023. Two authors independently reviewed the articles and reached the consensus.

Result: After reviewing 127 articles, a total of 61 articles that met the inclusion criteria were included in the present review. Studies revealed that A1CF is involved in epigenetic regulation of reproductive cells affecting embryonic development, and that it is closely associated with the occurrence of gout due to its editing properties on apoB. A1CF can also affect the process of epithelial-mesenchymal transition in renal tubular epithelial cells and promote liver regeneration by controlling the stability of IL-6 mRNA, but no influence on cardiac function was found. Furthermore, increasing evidence suggests that A1CF may promote the occurrence and development of breast cancer, lung cancer, renal cell carcinoma, hepatocellular carcinoma, endometrial cancer, and glioma.

Conclusion: This review clarifies the association between A1CF and other complementary factors and their impact on the development of human diseases, aiming to provide guidance for further research on A1CF, which can help treat human diseases and promote health.

Objective: This study explored the relationship between perceptions of health mis/disinformation on social media and belief that progress has been made in curing cancer.

Methods: We analyzed cross-sectional, retrospective data collected from 4246 adult social media users in the 2022 Health Information National Trends Survey (HINTS 6). The outcome variable was the belief in whether progress has been made in curing cancer. The primary predictor variable was the perception of health mis/disinformation on social media, categorized as 'Substantial' and '< Substantial'. We also examined whether the relationship varied by health care system trust, frequency of social media use, and education. The analysis controlled for demographic, socioeconomic, and health-related factors.

Results: Perception of substantial social media health mis- and disinformation was associated with a lower likelihood of believing progress has been made in curing cancer (odds ratios = 0.74, 95% CI = 0.59-0.94). Persons who perceived substantial social media health mis-and disinformation and had low trust in the health care system were less likely to believe progress has been made in curing cancer: 36% (95% CI: 28-45%). Persons who perceived substantial social media health mis-and disinformation and used social media less than daily were less likely to believe progress has been made in curing cancer: 44% (95% CI: 36-52%). Persons without a college degree who perceived substantial social media health mis-and disinformation were less likely to agree that progress has been made in curing cancer: 44% (95% CI: 39-50%).

Conclusion: Exposure to misinformation on social media may be associated with negative attitudes about advances in curing cancer, particularly among social media users with low trust in the health care system trust, less frequent social media users, or those without a college degree.

Background: The quality of cancer care affects patient outcomes. It is therefore important to understand what factors and/or barriers shape a cancer patient's decision about where to seek care. We sought to understand factors influencing decision-making for historically marginalized communities in a large metropolitan area with multiple options for cancer care, including a National Cancer Institute (NCI)-designated comprehensive cancer center.

Methods: We conducted semi-structured interviews with cancer patients from economically marginalized neighborhoods in Washington D.C., and with healthcare professionals who work with patients from these areas. Participants were recruited through flyers, social media posts, and word of mouth. Two researchers analyzed the data using a combination of inductive and deductive approaches supported by the ATLAS. ti software.

Results: A total of 15 interviews were conducted. Analysis revealed 3 major factors influencing where patients decide to seek care: health insurance, transportation, and prioritization of needs. Participants repeatedly identified navigating the bureaucracy of insurance enrollment and high medical costs as prohibitive to seeking care. Transportation was often mentioned in terms of convenience of use and proximity to the care center. Prioritization of needs refers to circumstances such as unstable housing, poverty, and mental illness, that some patients prioritize over seeking quality cancer care. Across these themes 2 findings arose: a discrepancy between stated and actual factors in choosing an oncologist, and the extent to which a cancer patient is able to choose their oncologist.

Conclusion: This study helps explain some of the factors that influence how cancer patients in urban settings choose an oncology center, and the barriers which prohibit access.

Aims of the study: This study aimed to understand how cancer patients decide where to seek treatment.

Background: The objective of this study is to develop a predictive model for the assessment of cervical lymph node metastasis risk in papillary thyroid carcinoma (PTC).

Methods: A retrospective study was conducted on 212 patients with PTC who underwent initial surgical treatment from August 2022 to April 2023 in 2 hospitals. Data were randomly split into 7:3 training-validation sets. Logistic regression was used for feature selection and predictive model creation. Model performance was assessed using receiver operating characteristic (ROC) and calibration curves. Clinical utility was determined using decision curves.

Results: Among the 212 patients with PTC, 104 cases (49.1%) exhibited cervical lymph node metastasis, while 108 cases (50.9%) did not. Multivariate logistic regression analysis revealed that age (OR = 0.95), FT3 (OR = 0.41), tumor maximum diameter ≥0.9 cm (OR = 1.85), intratumoral microcalcifications (OR = 1.84), and suspicious lymph node on ultrasound (OR = 2.96) were independent risk factors for lymph node metastasis in PTC patients (P < 0.05). The constructed model for predicting the risk of cervical lymph node metastasis demonstrated a training set ROC curve area under the curve (AUC) of 0.742 (95% CI: 0.664 - 0.821), with a cut-off value of 0.615, specificity of 87.8%, and sensitivity of 51.4%. The validation set exhibited an AUC of 0.648 (95% CI: 0.501 - 0.788), with a cut-off value of 0.644, specificity of 91.2%, and sensitivity of 43.3%. Including the BRAF V600 E mutation did not improve the model's diagnostic performance significantly. Decision curve analysis indicated clinical feasibility of the model.

Conclusion: The predictive model developed in this study effectively predicts lymph node metastasis risk in PTC patients by incorporating ultrasound features, demographic characteristics, and serum parameters. However, including the BRAF V600 E mutation does not significantly improve the model's diagnostic performance.

Background: Lung cancer is the most common cancer in the world and has become one of the malignancies with the highest incidence and mortality; more than half of patients die within one year of being diagnosed with lung cancer. In recent years, the concept of "patient-centered" service has gained popularity, and patients' subjective feelings have gradually been used in clinical decision-making. Therefore, this study determined the application of visual patient report outcomes in the field of lung cancer, in order to provide reference for specific clinical practice.

Methods: Using the Web of Science core collection as the main analysis content, Citespace and VOSviewer were used to conduct this scientometric study.

Results: A total of 499 literatures that met the inclusion criteria were retrieved. The most prolific institution was The University of Texas MD Anderson Cancer Center, and the United States dominates this field.

Conclusion: The measurement of patient-reported outcomes is considered the gold standard for effectively evaluating patients' perceptions of clinical interventions or diseases. It is recommended that patient-reported outcomes be integrated into routine care for cancer patients in order to enhance communication between patients and healthcare providers.

Patient or public contribution: Not applicable. All data in this paper are obtained from the web of science database.

Objectives: Accurate survival predictions and early interventional therapy are crucial for people with clear cell renal cell carcinoma (ccRCC).

Methods: In this retrospective study, we identified differentially expressed immune-related (DE-IRGs) and oncogenic (DE-OGs) genes from The Cancer Genome Atlas (TCGA) dataset to construct a prognostic risk model using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. We compared the immunogenomic characterization between the high- and low-risk patients in the TCGA and the PUCH cohort, including the immune cell infiltration level, immune score, immune checkpoint, and T-effector cell- and interferon (IFN)-γ-related gene expression.

Results: A prognostic risk model was constructed based on 9 DE-IRGs and 3 DE-OGs and validated in the training and testing TCGA datasets. The high-risk group exhibited significantly poor overall survival compared with the low-risk group in the training (P < 0.0001), testing (P = 0.016), and total (P < 0.0001) datasets. The prognostic risk model provided accurate predictive value for ccRCC prognosis in all datasets. Decision curve analysis revealed that the nomogram showed the best net benefit for the 1-, 3-, and 5-year risk predictions. Immunogenomic analyses of the TCGA and PUCH cohorts showed higher immune cell infiltration levels, immune scores, immune checkpoint, and T-effector cell- and IFN-γ-related cytotoxic gene expression in the high-risk group than in the low-risk group.

Conclusion: The 12-gene prognostic risk model can reliably predict overall survival outcomes and is strongly associated with the tumor immune microenvironment of ccRCC.

Purpose: Hepatic metastasis frequently occurs in patients who have undergone radical pancreatic resection for pancreatic cancer. Besides chemotherapy, various local treatment approaches targeting hepatic lesions have been explored. However, research on radiofrequency ablation (RFA) as a localized therapy for hepatic metastasis is limited. Therefore, we conducted this retrospective study to provide clinical evidence.

Methods: This is a single-center, retrospective, cohort study. After radical pancreaticoduodenectomy, 32 patients developed metachronous hepatic metastasis with fewer than 3 lesions, the largest of which was less than 3 cm in diameter. These patients underwent combined treatment with chemotherapy and RFA. After 8 weeks of chemotherapy, patients received RFA for hepatic lesions. Additional chemotherapy was administered, and the patients' tumor status and survival were monitored. The primary endpoint of this study was overall survival (OS). Factors affecting OS were analyzed using the Cox risk model.

Results: Among the 32 patients, the mean OS was 28.4 months. Univariate and multivariate Cox regression analysis revealed that the time (in months) of liver metastasis (HR = 0.04, 95% CI: 0.01 to 0.19; P < 0.001), the number of liver metastases (HR = 7.08, 95% CI: 1.85 to 27.08, P = 0.004), and PD (progressive disease) response to the second round of chemotherapy (HR = 29.50, 95% CI: 1.46 to 597.27; P = 0.027) were independent predictors of poorer survival.

Conclusion: Combined therapy with RFA and chemotherapy is safe in patients with hepatic metastasis after radical pancreaticoduodenectomy. Early recurrence (≤12 months), three liver metastatic lesions, and a poor response to the second round of chemotherapy were associated with poor survival.

This study aimed to explore advances in biomarkers related to anti-angiogenic therapy in patients with non-small cell lung cancer (NSCLC), thereby enhancing treatment selection, advancing personalized and precision medicine to improve treatment outcomes and patient survival rates. This article reviews key discoveries in predictive biomarkers for anti-angiogenic therapy in NSCLC in recent years, such as (1) liquid biopsy predictive biomarkers: studies have identified activated circulating endothelial cells (aCECs) via liquid biopsy as potential predictive biomarkers for the efficacy of anti-angiogenic therapy; (2) imaging biomarkers: advanced imaging technologies, such as dynamic contrast-enhanced integrated magnetic resonance positron emission tomography (MR-PET), are used to assess tumor angiogenesis in patients with NSCLC and evaluate the clinical efficacy of anti-angiogenic drugs; (3) genetic predictive biomarkers: research has explored polymorphisms of Vascular Endothelial Growth Factor Receptor-1 (VEGFR-1) and vascular endothelial growth factor-A (VEGF-A), as well as how plasma levels of VEGF-A can predict the outcomes and prognosis of patients with non-squamous NSCLC undergoing chemotherapy combined with bevacizumab. Despite progress in identifying biomarkers related to anti-angiogenic therapy, several challenges remain, including limitations in clinical trials, heterogeneity in NSCLC, and technical hurdles. Future research will require extensive clinical validation and in-depth mechanistic studies to fully exploit the potential of these biomarkers for personalized treatment.