Technology in Cancer Research & Treatment最新文献

Introduction: Exosomes play significant roles in transferring cargo materials like proteins, RNAs (including miRNAs), and DNA. However, the role of serum exosome shuttled RNAs and miRNAs in head and neck cancer (HNC) remains unclear. This study assessed the diagnostic and prognostic significance of exosomal miR-17, miR-20a, and TGFBR2 in HNC patients. Methods: Exosomes were isolated, from 400 confirmed HNC patients and 400 healthy controls, and characterized by NTA, TEM, Immunolabelling, and ELISA. Quantitative PCR was used to check the expressions of exosomal molecules. Oxidative stress was also measured through ELISA in cancer patients and healthy controls. Results: Data analysis revealed significant dysregulation in the expressional levels of miR-17 (p < .0001), miR-20a (p = .0003), and TGFBR2 (p = .0005), which were found associated with aggressiveness and poor survival of HNC patients. Spearman correlation revealed a positive statistically significant association between miR-20a versus miR-17 (r = 0.534; p < .01), while a negative correlation was found between TGFBR2 versus miR-17 (r = -0.240; p = .015). Significantly decreased levels of peroxidase (POD) (p < .0001) and an increased level of 8-Oxoguanine (p < .0001) were observed. Conclusion: The results showed that these exosomal miRNAs and target gene may serve as potential and noninvasive diagnostic and prognostic markers for head and neck cancer patients.

IntroductionBreast radiotherapy is associated with a higher risk of cardiac diseases. Although deep inspiration breath-hold (DIBH) reduces the heart dose, it is underutilized. The selection of proper candidates for DIBH remains an unresolved issue. This study compared dosimetric parameters between free breathing (FB) and DIBH, monitored myocardial enzymes, and aimed to identify factors that can predict cardiac injury thus developing a method to identify proper patients for DIBH.MethodsThis is a prospective cohort study, enrolling 58 patients with left-sided breast cancer following breast-conserving surgery. All patients underwent computed tomography scans in both FB and DIBH states. A comparative analysis of dosimetric features between DIBH and FB was conducted. Myocardial enzyme was monitored until six months post-radiation therapy. T-tests were used to assess differences between the DIBH and the FB. Pearson correlation and receiver operating characteristic (ROC) analysis was conducted to identify factors associated with the subclinical acute cardiac injury.ResultsThe mean heart dose (MHD) of the DIBH group significantly dropped as compared to the FB group (3.81 Gy vs 1.65 Gy p = 0.001). Cardiac V40, V30, V25, V10, and V5 volumes also significantly reduced. 9(15.51%) patients exhibited increased myocardial enzyme, with cTnI being the most sensitive indicator. The heart dose was a predictor for the cardiac enzyme's elevation. The ROC curve analysis revealed an area under the curve of 0.6. With an MHD threshold of 2 Gy, both sensitivity and specificity exceeded 0.7.ConclusionDIBH significantly diminishes radiation exposure to the heart and LAD compared with FB. Cardiac enzyme analysis facilitates the early detection of cardiac injury following radiation therapy. An MHD threshold of less than 2 Gy is associated with a reduced risk of subclinical cardiac injury, potentially obviating the need for DIBH, which optimizes clinical efficiency and economic viability.

Cancer remains a major global health burden, with incidence rates rising globally. The Arab world, which is often regarded as an underrepresented population in literature, shows distinct patterns in cancer incidences, genetics, and outcomes in comparison with Western populations. This review aims to highlight key genomic studies conducted in the Arab world. We describe the epidemiological and genetic landscape of cancer in the Arab populations, focusing on lung, breast, and colorectal cancers, given their prominence and distinctive patterns in the region. We utilised data from GLOBOCAN 2022 and published genomic studies to assess subregional incidence trends, identify significant mutations, and explore hereditary and early-onset cancers profiles. Breast, lung, and colorectal cancers dominate the cancer profile in the region, with disparities in genetic alterations when compared to global trends. Variation in EGFR mutation frequencies in lung cancer across diverse ethnicities in the MENA region is representative of the extreme heterogeneity in the Arab region. Variations in BRCA1/2 mutation frequency, and unique founder mutations highlight breast cancer's particular regional genetic traits. Similarly, colorectal cancer studies show variations in mutational profiles, such as a low incidence of BRAF mutations and distinct epigenetic characteristics that represent region-specific disease pathways. Early-onset cancers, particularly breast and colorectal cancers, occur at higher rates than in Western populations and often diverge from the typical germline mutation patterns reported globally. The review emphasises the importance of conducting localised genetic studies in improving personalised medicine and public health strategies. Despite these efforts, significant gaps remain, particularly in understanding early-onset cancers and hereditary cancer genetic disorders, which are overrepresented in the region. Further research on the genetic basis of cancer in Arab populations is essential for advancing personalised treatment and improving cancer outcomes in these under-researched groups.

IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in predicting preoperative axillary lymph node metastasis using primary breast cancer and lymph node features derived from contrast-enhanced mammography (CEM) and ultrasound (US) breast imaging reporting and data systems (BI-RADS).MethodsThis retrospective study included patients diagnosed with primary breast cancer. Two experienced radiologists extracted the BI-RADS features from the largest cross-section of the lesions and axillary lymph nodes based on CEM and US images, creating three datasets. Each dataset will train six base models to predict axillary lymph nodes, with pathological results serving as the gold standard. The top three models were used to train the five ensemble models. Additionally, SHapley Additive exPlanations (SHAP) was used to interpret the optimal model. The receiver-operating characteristic curve (ROC) and AUC were used to evaluate model performance.ResultsThis study involved 292 female patients, of whom 99 had axillary lymph node metastasis and 193 did not. The combination of CEM and ultrasound BI-RADS demonstrated the best performance in predicting axillary lymph node metastasis. Among these, the LightGBM achieved the highest AUC (0.762) and specificity (86.67%, while the ensemble model using RF as the meta-model had an AUC (0.754) and specificity (83.33%. The most important variables identified by SHAP were the long diameters of the lymph nodes in the CEM recombined image, along with their complete morphology in the low-energy image.ConclusionThe machine learning model using CEM and US BI-RADS features accurately predicted axillary lymph node metastasis before surgery, thereby serving as a valuable tool for clinical decision-making in patients with breast cancer.

ObjectiveTo systematically investigate the impact of adjusting the relative weight of the built-in Stereotactic Radiosurgery Normal Tissue Objective (SRS-NTO) on dosimetric quality, plan complexity, and delivery efficiency in HyperArc™ stereotactic radiosurgery (SRS) for brain oligometastases.MethodsIn this retrospective planning study, a cohort of 20 patients with 1-3 brain oligometastases was analyzed. For each case, six distinct HyperArc plans were designed and optimized using the Varian Eclipse™ Treatment Planning System. To precisely isolate its impact, the relative weight of the SRS-NTO to the PTV objective was systematically varied across six levels-50%, 75%, 100% (default), 125%, 150%, and 200%-while all other planning parameters were held constant. A comprehensive comparative evaluation was then performed to assess the plans across four key domains: (i) dosimetric quality, evaluated by metrics including the Paddick Conformity Index (CI), Gradient Index (GI), and dose to Organs at Risk (OARs); (ii) plan complexity, characterized by various modulation and aperture-based indices; (iii) delivery efficiency, primarily quantified by the total Monitor Units (MUs); and (iv) physical deliverability, verified via Gamma analysis.ResultsIncreasing NTO weight did not significantly alter dosimetric quality; key metrics for CI, GI, and OAR sparing remained statistically equivalent (p > .05). Conversely, higher NTO weights prompted a significant reduction in total MUs (p < .001) that reached an optimum at the 150% setting, and enhanced plan deliverability, evidenced by significantly higher Gamma passing rates under stricter verification criteria. An inflection point was observed beyond the 150% setting, with higher weights leading to degraded plan complexity and efficiency. Strategies within the 125% to 150% range demonstrated a superior balance, achieving optimal dosimetric trends while maximizing gains in efficiency and precision.ConclusionIn HyperArc SRS for brain oligometastases, moderately increasing the SRS-NTO weight from the default 100% into the 125% to 150% range is a superior clinical strategy. This adjustment significantly enhances treatment efficiency and delivery precision by reducing plan complexity, without compromising dosimetric quality, thereby achieving a superior overall performance.

Colorectal cancer ranks as one of the most common malignancies globally, with mortality rates second only to lung cancer. Despite improvements in diagnostic and therapeutic approaches, long-term survival rates for colorectal cancer patients remain unsatisfactory. The onset and progression of this disease involve intricate molecular mechanisms, influenced by a range of biological factors. Zinc finger proteins play a critical role in these processes, impacting tumor development and patient prognosis. This review summarizes current research on zinc finger proteins in colorectal cancer, highlighting key findings and advancements in understanding their role in tumor biology.

Background and AimPredictors of neutrophil-to-lymphocyte ratio (NLR) and traditional clinical variables for hepatocellular carcinoma (HCC) prognosis after locoregional therapies were useful while exhibited modest prognostic performances. We dig out the potential of circulating immune features for HCC prognosis prediction.Methods244 patients with early-stage HCC who were treated with thermal ablation and performed the peripheral blood mononuclear cells (PBMCs) tests were included. Patients were randomly assigned in 3:1 ratio to discovery (n = 183) and validation (n = 62) sets. Three models, including clinical (Clin-model), NLR-Clin-model and Immune-NLR-Clin-model were constructed using Cox regression model. Concordance index (c-index), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used for performance evaluation.ResultsThe Immune-NLR-Clin-model exhibited the best performance of 0.706 (95% CI:0.644-0.768) and 0.702 (95% CI:0.566-0.837) in discovery and validation sets, respectively. At 36-month prediction, the IDI and continuous-NRI show trend of improvement, with the IDI was 0.050 (95%CI: -0.5%-12.5%) (P < .0270) and the continuous-NRI was 0.147 (95%CI: -0.5%-36.6%) (P = .060) in discovery cohort. Treg, CD8⁺ and NLR from the immune-related combined model were selected to build TREND score. The median overall survival in TREND-low risk and high risk were 98.08 and 62.00 months, respectively (P < .0001). The discrimination ability approached significantly in validation set (P = .3200).ConclusionsCirculating immune features may be helpful components aiding NLR for HCC predictive models.