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BACKGROUND: HER2-positive breast cancer is traditionally treated with neoadjuvant systemic therapy (NST), but optimal treatment sequencing is less clear in patients with small tumors. We investigated clinicopathologic and oncologic outcomes in early stage HER2-positive breast cancer. PATIENTS AND METHODS: An institutional database was queried to identify patients with cT1-2 (≤ 3 cm) N0M0, HER2-positive breast cancer treated from 2015 to 2020 and compared upfront surgery and NST cohorts. Logistic regression was performed to identify factors predicting upstaging. Survival outcomes by group were compared using log-rank tests. RESULTS: Of 256 patients identified, 170 (66.4%) received upfront surgery and 86 (33.6%) NST. The NST cohort was younger and had more cT2 and grade 3 tumors and negative sentinel nodes. There was no significant difference in type of breast surgery or receipt of axillary lymphadenectomy. After upfront surgery, 4 (2.4%) patients had upstaging to pT > 3 cm and 18 (10.6%) to pN1-3. No factors predicted upstaging. After NST, 47 (54.7%) achieved pathologic complete response and 3 (3.5%) had upstaging to ypN1-3 with older age (OR 1.08, p = 0.004) and hormone receptor-positive status (OR 7.07, p = 0.002) identified as predictors. At median follow-up of 3.55 years, 10 (3.9%) patients had recurrence and 5 (2.0%) patients died. There were no significant differences in oncologic outcomes between groups. CONCLUSIONS: Patients with cT1-2 (≤ 3 cm)N0 HER2-positive breast cancer selected for NST have higher-risk disease. Low rates of pathologic upstaging were observed with no difference in surgical treatments and overall excellent oncologic outcomes in both groups. These findings may guide decision-making regarding treatment sequencing for patients with early stage HER2-positive disease.
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When an ultrasonic pulse propagates in a thin plate, nonlinear Lamb waves with higher harmonics and a zero-frequency component (ZFC) will be generated because of the nonlinearity of materials. The ZFC, also known as the static displacement or static component, has its unique application on the evaluation of early-stage damages in the elastic symmetrical undulated plate. In this study, analysis of the excitation mechanism of the ZFC and the second harmonic component (SHC) was theoretically and numerically investigated, and the material early-stage damage of a symmetrical undulated was characterized by studying the propagation of nonlinear Lamb waves. Both the ZFC and SHC can be effectively employed in monitoring the material damages of the undulated plate in its early stage. However, several factors must be considered for the propagation of the SHC in an undulated plate because of the geometric curvature and interference between the second harmonics during propagation, preventing efficient application of this technique. If the fundamental wave can propagate in the plate regardless of the plate boundary conditions, an accumulative effect always exists for the ZFC in a thin plate, indicating that the ZFC is independent of the structural geometry. This study reveals that the ZFC-based inspection technique is more efficient and powerful in characterizing the damages of a symmetrical undulated plate in the early stage of service compared to the second harmonic method.
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Pancreatic cancer is associated with a poor prognosis, even in the early stages, mainly due to metastatic progression. New diagnostic techniques that predict unfavorable outcomes are needed in order to improve treatment strategies. Circulating tumor cells (CTCs) are showing promising results as a predictive biomarker for various tumors. In this editorial we comment on the article by Zhang et al, who published the first systematic review and meta-analysis evaluating the prognostic value of CTCs as biomarkers in early-stage pancreatic cancer patients undergoing surgery. CTCs were detected in peripheral or central venous system blood, before or during surgery. Positive CTCs showed a correlation with decreased overall survival and decreased relapse-free, disease-free and progression-free survival in this meta-analysis. However, the heterogeneity was significant. The authors suggest that this result was related to the separation methods used between studies, but other differences such as the margin status or the neoadjuvant and adjuvant treatments used are also important to consider. CTCs may be a potential prognostic biomarker in pancreatic cancer patients, but it is necessary to compare and standardize the platforms used to isolate CTCs, to compare different biomarkers from liquid biopsy and to determine the impact on prognosis when therapeutic changes are made based on CTCs levels.
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OBJECTIVE: The 5-year survival rate of early-stage non-small cell lung cancer (NSCLC) is still not optimistic. We aimed to construct prognostic tools using clinicopathological (CP) and serum 8-miRNA panel to predict the risk of overall survival (OS) in early-stage NSCLC. MATERIALS AND METHODS: A total of 799 patients with early-stage NSCLC, treated between April 2008 and September 2019, were included in this study. A sub-group of patients with serum samples, 280, were analyzed for miRNA profiling. The primary endpoint of the study was OS. The CP panel for prognosis was developed using multivariate and forward stepwise selection analyses. The serum 8-miRNA panel was developed using the miRNAs that were significant for prognosis, screened using real-time quantitative PCR (qPCR) followed by differential, univariate and Cox regression analyses. The combined model was developed using CP panel and serum 8-miRNA panel. The predictive performance of the panels and the combined model was evaluated using the area under curve (AUC) values of receiver operating characteristics (ROC) curves and Kaplan-Meier survival analysis. RESULT: The prognostic panels and the combined model (comprising CP panel and serum 8-miRNA panel) was used to classify the patients into high-risk and low-risk groups. The OS rates of these two groups were significantly different (P<0.05). The two panels had higher AUC than the two guidelines, and the combined model had the highest AUC. The AUC of the combined model (AUC=0.788; 95 %CI 0.706-0.871) was better than that of the National Comprehensive Cancer Network (NCCN) guideline (AUC=0.601; 95 %CI 0.505-0.697) and Chinese Society of Clinical Oncology (CSCO) guideline (AUC=0.614; 95 %CI 0.520-0.708). CONCLUSION: The combined model based on CP panel and serum 8-miRNA panel allows better prognostic risk stratification of patients with early-stage NSCLC to predict risk of OS.
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OBJECTIVE: This study assessed the health-related quality of life (HRQo) of women surviving a borderline ovarian tumor (BOT) in comparison with early-stage ovarian cancer survivors treated surgically alone and with a matched cancer-free population. METHODS: Survivors of BOT and ovarian cancer were invited in two Dutch cross-sectional, population-based studies. Ovarian cancer survivors with tumor stage I who were treated surgically only were included. A random sample from the cancer-free population was matched on sex, age and education to the sample of BOT survivors. The EORTC QLQ-C30 (version 3.0) and the EORTC QLQ-OV28 were completed by the cancer-free population and the BOT and ovarian cancer survivors in study 1 and 2. The Hospital Anxiety and Depression Scale (HADS) was only completed by the cancer-free population and the survivors of BOT and ovarian cancer in study 1. BOT survivors were compared to early-stage ovarian cancer survivors and the general population using linear regression analyses and effect sizes regarding clinical importance. RESULTS: 83 BOT (42%), 88 early-stage ovarian cancer survivors (52%), and 82 women from the general population were included. In most HRQoL domains, BOT survivors were not significantly different from early-stage ovarian cancer survivors and the cancer-free population, except that BOT survivors reported significantly less insomnia than early-stage ovarian cancer survivors and more dyspnea than the cancer-free population (small clinical difference). CONCLUSION: In general, BOT survivors' HRQoL lies between the HRQoL of early-stage ovarian cancer survivors and of the cancer-free population, but clinical effect sizes between the groups were mostly only trivial.
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The development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al. Clinical Development Success Rates and Contributing Factors 2011-2020, 2021). To increase the probability of success and ensure robust drug supply beyond approval, it is essential to assess the developability profile of new potential drug candidates as early and broadly as possible in development (Jain et al. MAbs, 2023. https://doi.org/10.1016/j.copbio.2011.06.002 ). Predicting these properties in silico is expected to be the next leap in innovation as it would enable significantly reduced development timelines combined with broader screens at lower costs. However, developing predictive algorithms typically requires substantial datasets generated under very defined conditions, a limiting factor especially for new classes of therapeutic proteins that hold immense clinical promise. Here we describe a strategy for assessing the developability of a novel class of small therapeutic Anticalin® proteins using machine learning in conjunction with a knowledge-driven approach. The knowledge-driven approach considers developability attributes such as aggregation propensity, charge variants, immunogenicity, specificity, thermal stability, hydrophobicity, and potential post-translational modifications, to calculate a holistic developability score. Based on sequence-derived descriptors as input parameters we established novel statistical models designed to predict the developability scores for Anticalin proteins. The best models yielded low root mean square errors across the entire dataset and were further validated by removing input data from individual screening campaigns and predicting developability scores for those drug candidates. The adoption of the described workflow will enable significantly streamlined preclinical development of Anticalin drug candidates and could potentially be applied to other therapeutic protein scaffolds.
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Simulación por Computador , Aprendizaje Automático , Proteínas , Humanos , Proteínas/química , Algoritmos , Descubrimiento de Drogas/métodos , Diseño de FármacosRESUMEN
BACKGROUND: Breast cancer is the most common cancer-affecting women globally, with disproportionally high mortality rates in lower-income countries, including Ethiopia. The stage at diagnosis is a well-defined predictive system that determines the likelihood of breast cancer mortality. Early-stage breast cancer at diagnosis is associated with better treatment outcomes as compared with late stage. Although there are numerous primary studies on women with breast cancer with different proportions of early-stage breast cancer, there is currently no summary data on what proportion of breast cancer was diagnosed at early-stage in Ethiopia. This study focused on a pooled proportion of early-stage breast cancer at diagnosis in Ethiopia. METHODS: By using key terms, Medline through Pub-Med, Google Scholar, Science Direct, HINARI and Medley were searched about breast cancer in Ethiopia, and a total of 288 articles were retrieved. After screening the articles and quality of each article was assessed using Newcastle-Ottawa Scale. Finally, 41 articles were used for the final pooled proportion. A random effects model was used to estimate the pooled prevalence and heterogeneity of included studies that were then assessed by using prediction interval. RESULTS: Pooled proportion of early-stage breast cancer at diagnosis in Ethiopian hospitals was found to be 36% with a 95% confidence interval ranging from 31 to 41% and a 95% prediction interval ranging from 28 to 45%. CONCLUSION: Most breast cancer patients (64%) in Ethiopia are diagnosed at a late-stage. This contributes to the high mortality rates of breast cancer among women in Ethiopia. Therefore, in line with recommendations by the World Health Organization, we recommend that there should be an emphasis in Ethiopia to focus on early detection of breast cancer.
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Neoplasias de la Mama , Detección Precoz del Cáncer , Estadificación de Neoplasias , Femenino , Humanos , Neoplasias de la Mama/epidemiología , Neoplasias de la Mama/diagnóstico , Neoplasias de la Mama/mortalidad , Neoplasias de la Mama/patología , Detección Precoz del Cáncer/estadística & datos numéricos , Etiopía/epidemiología , PrevalenciaRESUMEN
The use of proton therapy (PT) in early-stage non-small cell lung cancer (ES-NSCLC) remains controversial, with insufficient evidence to determine its superiority over photon therapy (XRT). We conducted a systematic review of PT trials in ES-NSCLC, analyzing dosimetry, efficacy, and safety across to inform clinical decision-making. Our study showed that PT reduced lung and heart dosimetric parameters compared to XRT, with significant differences in lung V5, lung V10 and mean heart dose (MHD). In terms of efficacy, there were no significant differences in 1-year OS, 3-year OS and 3-year PFS between PT and XRT. For toxicity, no significant difference was observed in treatment-related adverse events (TRAEs) and radiation pneumonitis (RP). Single-arm analysis of PT found that V5, V10, V20 of lung and heart V5 were 13.4%, 11.3%, 7.9% and 0.7%, respectively. The mean lung dose and MHD were 4.15 Gy and 0.17 Gy, respectively. The single-arm pooled 1-, 2-, 3- and 5-year OS rates for PT were 95.3%, 82.5%, 81.3% and 69.3%, respectively. PFS rate and local control rate at 3 years were 68.1% and 91.2%, respectively. The rates of TRAEs of grade ≥ 3 and grade ≥ 2 were 2.8% and 19.8%, respectively. The grade ≥ 2 RP occurred at a rate of 8.7%. In conclusion, PT had acceptable efficacy and safety, and was better at protecting organs at risk than XRT in ES-NSCLC. However, the survival and safety benefit of PT was not significant compared to XRT.
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The nature of microRNA (miRNA) dysfunction in carcinogenesis remains controversial because of the complex connection between miRNA structural diversity and biological processes. Here, we found that oncofetal IGF2BP3 regulates the selective production of a subset of 3'-isoforms (3'-isomiRs), including miR-21-5p and Let-7 family, which induces significant changes in their cellular seed occupancy and structural components, establishing a cancer-specific gene expression profile. The D-score, reflecting dominant production of a representative miR-21-5p+C (a 3'-isomiR), discriminated between clinical early-stage lung adenocarcinoma (LUAD) cases with low and high recurrence risks, and was associated with molecular features of cell cycle progression, epithelial-mesenchymal transition pressure, and immune evasion. We found that IGF2BP3 controls the production of miR-21-5p+C by directing the nuclear Drosha complex to select the cleavage site. IGF2BP3 was also involved in the production of 3'-isomiRs of miR-425-5p and miR-454-3p. IGF2BP3-regulated these three miRNAs are suggested to be associated with the regulation of p53, TGF-ß, and TNF pathways in LUAD. Knockdown of IGF2BP3 also induced a selective upregulation of Let-7 3'-isomiRs, leading to increased cellular Let-7 seed occupancy and broad repression of its target genes encoding cell cycle regulators. The D-score is an index that reflects this cellular situation. Our results suggest that the aberrant regulation of miRNA structural diversity is a critical component for controlling cellular networks, thus supporting the establishment of a malignant gene expression profile in early stage LUAD.
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Adenocarcinoma del Pulmón , Regulación Neoplásica de la Expresión Génica , Neoplasias Pulmonares , MicroARNs , Proteínas de Unión al ARN , MicroARNs/genética , MicroARNs/metabolismo , Humanos , Proteínas de Unión al ARN/metabolismo , Proteínas de Unión al ARN/genética , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/patología , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/metabolismo , Adenocarcinoma del Pulmón/patología , Línea Celular Tumoral , Ribonucleasa III/metabolismo , Ribonucleasa III/genética , Transición Epitelial-Mesenquimal/genéticaRESUMEN
Atom probe tomography (APT) is commonly used to study solute clustering and precipitation in materials. However, standard techniques used to identify and characterize clusters within atom probe data, such as the density-based spatial clustering applications with noise (DBSCAN), often underperform with respect to small clusters. This is a limitation of density-based cluster identification algorithms, due to their dependence on the parameter Nmin, an arbitrary lower limit placed on detectable cluster sizes. Therefore, this article attempts to consider the characterization of clustering in atom probe data as an outlier detection problem of which k-nearest neighbors local outlier factor and learnable unified neighborhood-based anomaly ranking algorithms were tested against a simulated dataset and compared to the standard method. The decision score output of the algorithms was then auto thresholded by the Karcher mean to remove human bias. Each of the major models tested outperforms DBSCAN for cluster sizes of <25 atoms but underperforms for sizes >30 atoms using simulated data. However, the new combined k-nearest neighbors (k-NN) and DBSCAN method presented was able to perform well at all cluster sizes. The combined k-NN and seven methods are presented as a new approach to identifying clusters in APT.
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This study unveils the "green" metal-organic framework (MOF) structuring mechanism by decoding proton transfer in water during ZIF-8 synthesis. Combining in situ small- to wide-angle X-ray scattering, multiscale simulations, and quantum calculations, we reveal that the ZIF-8 early-stage nucleation and crystallization process in aqueous solution unfolds in three distinct stages. In stage I, imidazole ligands replace water in zinc-water cages, triggering an "acidity flip" that promotes proton transfer. This leads to the assembly of structures from single zinc ions to 3D amorphous cluster nuclei. In stage II, amorphous nuclei undergo a critical transformation, evolving into crystalline nuclei and subsequently forming mesoscale-ordered structures and crystallites. The process proceeds until the amorphous precursors are completely consumed, with the transformation kinetics governed by an energy barrier that determines the rate-limiting step. In stage III, stable crystallite nanoparticles form in solution, characterized by a temperature-dependent thermal equilibrium of molecular interactions at the crystal-solution interface. Beyond these core advancements, we explore the influence of encapsulated pepsin and nonencapsulated lysozyme on ZIF-8 formation, finding that their amino acid proton transfer capacity and concentration influence the resulting biomolecule-MOF composite's shape and encapsulation efficiency. The findings contribute to understanding the molecular mechanisms behind biomimetic mineralization and have potential implications for engineering proteins within amorphous MOF nuclei as protein embryo growth sites.
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Spontaneous osteonecrosis of the knee (SONK) is a poorly understood but debilitating disease, that is a common cause of unilateral acute knee pain and swelling. The term "SONK" has been replaced by the term "subchondral insufficiency fracture" in the latest pathology and imaging literature. Few studies investigated the pathogenesis of SONK by examining the histological changes of the tissues. Very recently, the development of SONK was associated with a meniscal root tear. In terms of the preferred imaging, plain radiographs can confirm the diagnosis in late stages; however, magnetic resonance imaging (MRI) scan is often required. Regarding the treatment, conservative management is usually the treatment of choice in early stages, including a period of non-weightbearing or the use of medications, such as nonsteroidal anti-inflammatory drug (NSAIDS) or bisphosphonates. However, when SONK progresses, often a surgical intervention is required, such as knee replacement, but also minimally invasive techniques, such as arthroscopic intervention, have been described. We present a case of early SONK and discuss the possible pathogenesis of SONK, the clinical presentation, the radiological findings, and we focus on the importance of early diagnosis and early off-load period that is required to prevent further progression of the disease.
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Background: Recent publications underscore the need for updated recommendations addressing less radical surgery for <2 cm tumors, induction chemotherapy, or immunotherapy for locally advanced stages of cervical cancer, as well as for the systemic therapy for recurrent or metastatic cervical cancer. Aim: To summarize the current evidence for the diagnosis, treatment, and follow-up of cervical cancer and provide evidence-based clinical practice recommendations. Methods: Developed according to AGREE II standards, the guidelines classify scientific evidence based on the Agency for Health Technology Assessment and Tariff System criteria. Recommendations are graded by evidence strength and consensus level from the development group. Key Results: (1) Early-Stage Cancer: Stromal invasion and lymphovascular space involvement (LVSI) from pretreatment biopsy identify candidates for surgery, particularly for simple hysterectomy. (2) Surgical Approach: Minimally invasive surgery is not recommended, except for T1A, LVSI-negative tumors, due to a reduction in life expectancy. (3) Locally Advanced Cancer: concurrent chemoradiation (CCRT) followed by brachytherapy (BRT) is the cornerstone treatment. Low-risk patients (fewer than two metastatic nodes or FIGO IB2-II) may consider induction chemotherapy (ICT) followed by CCRT and BRT after 7 days. High-risk patients (two or more metastatic nodes or FIGO IIIA, IIIB, and IVA) benefit from pembrolizumab with CCRT and maintenance therapy. (4) Metastatic, Persistent, and Recurrent Cancer: A PD-L1 status from pretreatment biopsy identifies candidates for Pembrolizumab with available systemic treatment, while triplet therapy (Atezolizumab/Bevacizumab/chemotherapy) becomes a PD-L1-independent option. Conclusions: These evidence-based guidelines aim to improve clinical outcomes through precise treatment strategies based on individual risk factors, predictors, and disease stages.
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Purpose: Single vocal cord irradiation (SVCI) is a promising technique to maintain excellent oncologic control and potentially improve upon toxicities for treatment of early-stage glottic squamous cell carcinomas. We sought to investigate whether pencil beam scanning (PBS) proton therapy could improve upon the already favorable dose gradients demonstrated with volumetric modulated arc therapy (VMAT) SVCI. Patients and Methods: A 64-year-old gentleman was treated in our department with 6X-flattening filter-free VMAT SVCI to 58.08 Gy in 16 fractions for a T1a well-differentiated squamous cell carcinoma of the left true vocal cord and tolerated it well with good local control. Comparative PBS plans were created in Raystation for the Varian ProBeam with clinical target volume (CTVs) generated to mimic the prescription target volume extent of the VMAT planning target volumes when accounting for PBS plan robustness (±3 mm translational shifts, 3.5% density perturbation). A 3-field single-field optimization plan was selected as dosimetrically preferable. Dosimetric variables were compared. Results: Several organs at risk doses improved with PBS, including the maximum and mean dose to ipsilateral carotids, maximum and mean dose to contralateral carotid, maximum dose to the spinal cord, maximum and mean dose to inferior constrictor/cricopharyngeus, maximum and mean dose to the uninvolved vocal cord, and mean dose to the thyroid gland. There are tradeoffs in skin dose depending on location relative to the target-with the highest and lowest isodoses extending more into the skin with the VMAT plan but with the moderate isodose lines covering a wider area with the PBS plan, but we deemed it tolerable regardless. Conclusion: SVCI is a promising strategy for maintaining the oncologic effectiveness of whole-larynx photon radiation while potentially improving upon the historic toxicity profile. The favorable dose distribution with PBS with respect to organs at risk dosimetry for PBS may allow for further improvements upon VMAT SVCI strategies. Clinical implementation of PBS SVCI may be considered.
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Early-stage aggregates of amyloid-forming proteins, specifically soluble oligomers, are implicated in neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Huntington's disease. Protein aggregation is typically monitored by fluorescence using the amyloid-binding fluorophore thioflavin T (ThT). Thioflavin T interacts, however, preferentially with fibrillar amyloid structures rather than with soluble, early-stage aggregates. In contrast, the two fluorophores, aminonaphthalene 2-cyanoacrylate-spiropyran (AN-SP) and triazole-containing boron-dipyrromethene (taBODIPY), were reported to bind preferentially to early-stage aggregates of amyloidogenic proteins. The present study compares ThT with AN-SP and taBODIPY with regard to their ability to monitor early stages of aggregation of four different amyloid-forming proteins, including amyloid-ß (Aß), tau protein, amylin, and α-synuclein. The results show that the three fluorophores vary in their suitability to monitor the early aggregation of different amyloid-forming proteins. For instance, in the presence of Aß and amylin, the fluorescence intensity of AN-SP increased at an earlier stage of aggregation than the fluorescence of ThT, albeit with only a small fluorescence increase in the case of AN-SP. In contrast, in the presence of tau and amylin, the fluorescence intensity of taBODIPY increased at an earlier stage of aggregation than the fluorescence of ThT. Finally, α-synuclein aggregation could only be monitored by ThT fluorescence; neither AN-SP nor taBODIPY showed a significant increase in fluorescence over the course of aggregation of α-synuclein. These results demonstrate the ability of AN-SP and taBODIPY to monitor the formation of early-stage aggregates from specific amyloid-forming proteins at an early stage of aggregation, although moderate increases in fluorescence intensity, relatively large uncertainties in fluorescence values, and limited solubility of both fluorophores limit their usefulness for some amyloid proteins. The capability to monitor early aggregation of some amyloid proteins, such as amylin, might accelerate the discovery of aggregation inhibitors to minimize the formation of toxic oligomeric species for potential therapeutic use.
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BACKGROUND: The aim of this study was to investigate the correlation between m6A methylation regulators and cell infiltration characteristics in tumor immune microenvironment (TIME), so as to help understand the immune mechanism of early-stage lung adenocarcinoma (LUAD). METHODS: The expression and consensus cluster analyses of m6A methylation regulators in early-stage LUAD were performed. The clinicopathological features, immune cell infiltration, survival and functional enrichment in different subtypes were analyzed. We also constructed a prognostic model. Clinical tissue samples were used to validate the expression of model genes through real-time polymerase chain reaction (RT-PCR). In addition, cell scratch assay and Transwell assay were also performed. RESULTS: Expression of m6A methylation regulators was abnormal in early-stage LUAD. According to the consensus clustering of m6A methylation regulators, patients with early-stage LUAD were divided into two subtypes. Two subtypes showed different infiltration levels of immune cell and survival time. A prognostic model consisting of HNRNPC, IGF2BP1 and IGF2BP3 could be used to predict the survival of early-stage LUAD. RT-PCR results showed that HNRNPC, IGF2BP1 and IGF2BP3 were significantly up-regulated in early-stage LUAD tissues. The results of cell scratch assay and Transwell assay showed that overexpression of HNRNPC promotes the migration and invasion of NCI-H1299 cells, while knockdown HNRNPC inhibits the migration and invasion of NCI-H1299 cells. CONCLUSIONS: This work reveals that m6A methylation regulators may be potential biomarkers for prognosis in patients with early-stage LUAD. Our prognostic model may be of great value in predicting the prognosis of early-stage LUAD.
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Adenocarcinoma del Pulmón , Regulación Neoplásica de la Expresión Génica , Neoplasias Pulmonares , Microambiente Tumoral , Humanos , Microambiente Tumoral/inmunología , Microambiente Tumoral/genética , Adenocarcinoma del Pulmón/genética , Adenocarcinoma del Pulmón/inmunología , Adenocarcinoma del Pulmón/patología , Adenocarcinoma del Pulmón/mortalidad , Pronóstico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/inmunología , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/mortalidad , Ribonucleoproteína Heterogénea-Nuclear Grupo C/genética , Ribonucleoproteína Heterogénea-Nuclear Grupo C/metabolismo , Femenino , Masculino , Análisis por Conglomerados , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Metilación , Línea Celular Tumoral , Estadificación de Neoplasias , Adenosina/análogos & derivados , Adenosina/metabolismo , Adenosina/genética , Persona de Mediana Edad , Proteínas de Unión al ARN/genética , Proteínas de Unión al ARN/metabolismoRESUMEN
OBJECTIVE: In 2016, the ESMO-ESGO-ESTRO consensus included LVSI (Lymph-vascular space invasion, LVSI) status as a risk stratification factor for stage I endometrioid endometrial cancer (EEC) patients and as one of the indications for adjuvant therapy. Furthermore, LVSI is included in the new FIGO staging of endometrial cancer (EC) in 2023. However, the data contribution of the Chinese population in this regard is limited. The present study aimed to further comfirm the influence of LVSI on the prognosis of early-stage low-grade EEC in a fifteen-year retrospective Chinese cohort study. METHODS: This retrospective analysis cohort included 702 EEC patients who underwent TAH/BSO surgery, total abdominal hysterectomy, bilateral salpingooophorectomy in Peking University People's Hospital from 2006 to 2020. Patients were stratified based on LVSI expression status as: LVSI negative group and LVSI positive group. Clinical outcome measures related to LVSI, assessed with a univariate and multivariate Cox proportional hazards regression model. RESULTS: 702 EEC patients with stage I and grade 1-2 were analyzed. 58 patients (8.3%) were LVSI-positive and 14 patients (2.0%) was relapse. Recurrence rates in LVSI-negative and LVSI-positive were 1.6% and 6.9%, respectively. 5-year disease-free survival (DFS) rate in LVSI-negative and LVSI-positive were 98.4% and 93.1%, respectively. These rates for 5-year overall (OS) survival in LVSI-negative were 98.9% while it was 94.8% in LVSI-positive. Multivariate analysis showed that LVSI is an independent risk factor for 5-year DFS (HR = 4.60, p = 0.010). LVSI has a similar result for 5-year OS(HR = 4.39, p = 0.028). CONCLUSIONS: LVSI is an independent predictor of relapse and poor prognosis in early-stage low-grade endometrioid endometrial cancer in the Chinese cohort.
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Carcinoma Endometrioide , Neoplasias Endometriales , Invasividad Neoplásica , Estadificación de Neoplasias , Humanos , Femenino , Estudios Retrospectivos , Neoplasias Endometriales/patología , Neoplasias Endometriales/mortalidad , Neoplasias Endometriales/cirugía , Persona de Mediana Edad , Pronóstico , Carcinoma Endometrioide/patología , Carcinoma Endometrioide/cirugía , Carcinoma Endometrioide/mortalidad , Carcinoma Endometrioide/terapia , Tasa de Supervivencia , Estudios de Seguimiento , China/epidemiología , Histerectomía/estadística & datos numéricos , Histerectomía/métodos , Clasificación del Tumor , Anciano , Metástasis Linfática , Vasos Linfáticos/patología , Adulto , Recurrencia Local de Neoplasia/patología , Recurrencia Local de Neoplasia/epidemiología , Recurrencia Local de Neoplasia/cirugía , Pueblos del Este de AsiaRESUMEN
If Europe's health systems make a conscious decision to increase their utilization of technology and techniques that can enhance prevention and expedite early-stage diagnosis, they can effectively address the growing challenges of disease. By embracing these advancements, these health systems can significantly improve their response to emerging health issues.However, at present the effective integration and exploitation of these opportunities remains hesitant and suboptimal, and health and health services underperform accordingly, with patients suffering from the continuing variations in diagnosis and access to innovation. This paper presents a comprehensive study that examines the current state of various influential disciplines and factors in European countries. It specifically focuses on the adoption of Next Generation Screening technologies and the development stage of Public Health Genomics. The assessment of these areas is presented in the context of a rapidly changing policy environment, which provides an opportunity for a fundamental reconsideration of how and where new tools can be integrated into healthcare systems and routine practices. Top of Form.
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Atención a la Salud , Genómica , Secuenciación de Nucleótidos de Alto Rendimiento , Salud Pública , Humanos , Genómica/métodos , Salud Pública/métodos , Secuenciación de Nucleótidos de Alto Rendimiento/métodosRESUMEN
Liquid biopsy is a minimally invasive method for biomarkers detection in body fluids, particularly in blood, which offers an elevated and growing number of clinical applications in oncology. As a result of the improvement in the techniques for DNA analysis, above all next-generation sequencing (NGS) assays, circulating tumor DNA (ctDNA) has become the most informing tumor-derived material for most types of cancer, including non-small cell lung cancer (NSCLC). Although ctDNA concentration is higher in patients with advanced tumors, it can be detected even in patients with early-stage disease. Therefore, numerous clinical applications of ctDNA in the management of early-stage lung cancer are emerging, such as lung cancer screening, the identification of minimal residual disease (MRD), and the prediction of relapse before radiologic progression. Moreover, a high number of clinical trials are ongoing to better define the impact of ctDNA evaluation in this setting. Aim of this review is to offer a comprehensive overview of the most relevant implementations in using ctDNA for the management of early-stage lung cancer, addressing available data, technical aspects, limitations, and future perspectives.
Asunto(s)
Biomarcadores de Tumor , Carcinoma de Pulmón de Células no Pequeñas , ADN Tumoral Circulante , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/sangre , Carcinoma de Pulmón de Células no Pequeñas/diagnóstico , Carcinoma de Pulmón de Células no Pequeñas/genética , Carcinoma de Pulmón de Células no Pequeñas/terapia , ADN Tumoral Circulante/sangre , ADN Tumoral Circulante/genética , Neoplasias Pulmonares/sangre , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/terapia , Biomarcadores de Tumor/sangre , Biomarcadores de Tumor/genética , Biopsia Líquida/métodosRESUMEN
BACKGROUND: This article is aimed to make predictions in terms of prognostic factors and compare prediction methods by using Cox proportional hazards regression analysis (CPH), some machine learning techniques and Accelerated Failure Time (AFT) model for post-treatment survival probabilities according to clinical presentations and pathological information of early-stage breast cancer patients. MATERIAL AND METHODS: The study was carried out in three stages. In the first stage, the CPH method was applied. In the second stage, the AFT model and in the last stage, machine learning methods were applied. The data set consists of 697 breast cancer patients who applied to Marmara University Hospital oncology clinic between 01.01.1994 and 31.12.2009. The models obtained by using various parameters of the patients were compared according to the C index, 5-year survival rate and 10-year survival rate. RESULTS AND CONCLUSION: According to the models obtained as a result of the analyses applied, MetLN and age were obtained as a significant risk factor as a result of CPH method and AFT methods, while MetLN, age, tumor size, LV1 and extracapsular involvement were obtained as risk factors in machine learning methods. In addition, when the c-index values of the handheld models are examined, it is obtained as 69.8 for the CPH model, 70.36 for the AFT model, 72.1 for the random survival forest and 72.8 for the gradient boosting machine. In conclusion, the study highlights the potential of comparing conventional statistical methods and machine-learning algorithms to improve the precision of risk factor determination in early-stage breast cancer prognosis. Additionally, efforts should be made to enhance the interpretability of machine-learning models, ensuring that the results obtained can be effectively communicated and utilized by clinical practitioners. This would enable more informed decision-making and personalized care in the treatment and follow-up processes for early-stage breast cancer patients.