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ny therapeutic approach (surgery, RT or CHT). What are the main findings? A total of 1197 citations were identified by the Medline search and additional records; based on our inclusion criteria, 18 studies were included with a total of 285 adult patients. We documented the lack of any clinical trial. What are the conclusions? The available literature data are limited to series/retrospective studies, including heterogeneous patients, i.e., astrocytoma as well as ependymoma or pediatric/adult age, with scanty data on the outcomes of interest. No clinical trials have been run. Due to the rarity of this disease, multicentric clinical trials with molecular investigations are mandatory to better manage such a rare disease.Soft-tissue sarcomas are biologically heterogenous tumors arising from connective tissues with over 100 subtypes. Although sarcomas account for <1% of all adult malignancies, retroperitoneal sarcomas are a distinct subgroup accounting for <10% of all sarcomatous tumors. There have been considerable advancements in the understanding and treatment of retroperitoneal sarcoma in the last decade, with standard treatment consisting of upfront primary surgical resection. The evidence surrounding the addition of radiation therapy remains controversial. There remains no standard with regards to systemic therapy, including immunotherapy. PhleomycinD1 Adjunctive therapy remains largely dictated by expert consensus and preferences at individual centers or participation in clinical trials. In this 2021 review, we detail the anatomical boundaries of the retroperitoneum, clinical characteristics, contemporary standard of care and well as recent advancements in retroperitoneal sarcoma care. Ongoing international collaborations are encouraged to advance our understanding of this complex disease.
To identify the most predictive parameters of ovarian malignancy and develop a machine learning (ML) based algorithm to preoperatively distinguish between a benign and malignant pelvic mass.
Retrospective study of 70 predictive parameters collected from 140 women with a pelvic mass. The women were split into a 31 "training" to "testing" dataset. Feature selection was performed using Gini impurity through an embedded random forest model and principal component analysis. Nine unique ML classifiers were assessed across a variety of model-specific hyperparameters using 25 bootstrap resamples of the training data. Model predictions were then combined into an ensemble stack by LASSO regression. The final ensemble stack and individual classifiers were then applied to the testing dataset to assess model performance.
Feature selection identified HE4, CA125, and transferrin as three predictive parameters of malignancy. Assessment of the ensemble stack on the testing dataset outperformed all individual ML classifiers in predicting malignancy. The ensemble stack demonstrated an accuracy of 97.1%, a receiver operating characteristic (ROC) area under the curve (AUC) of 0.951, and a sensitivity of 93.3% with a specificity of 100%.
Combining the measurement of three distinct biomarkers with the stacking of multiple ML classifiers into an ensemble can provide valuable preoperative diagnostic predictions for patients with a pelvic mass.
Combining the measurement of three distinct biomarkers with the stacking of multiple ML classifiers into an ensemble can provide valuable preoperative diagnostic predictions for patients with a pelvic mass.Patients with metastatic soft tissue sarcoma (STS) have a poor prognosis and few available systemic treatment options. Trabectedin is currently being investigated as a potential adjunct to immunotherapy as it has been previously shown to kill tumor-associated macrophages. In this retrospective study, we sought to identify biomarkers that would be relevant to trials combining trabectedin with immunotherapy. We performed a single-center retrospective study of sarcoma patients treated with trabectedin with long-term follow-up. Multiplex gene expression analysis using the NanoString platform was assessed, and an exploratory analysis using the lasso-penalized Cox regression and kernel association test for survival (MiRKAT-S) methods investigated tumor-associated immune cells and correlated their gene signatures to patient survival. In total, 147 sarcoma patients treated with trabectedin were analyzed, with a mean follow-up time of 5 years. Patients with fewer prior chemotherapy regimens were more likely to stay on could guide clinicians in future treatment decisions.Problem. Image biomarker analysis, also known as radiomics, is a tool for tissue characterization and treatment prognosis that relies on routinely acquired clinical images and delineations. Due to the uncertainty in image acquisition, processing, and segmentation (delineation) protocols, radiomics often lack reproducibility. Radiomics harmonization techniques have been proposed as a solution to reduce these sources of uncertainty and/or their influence on the prognostic model performance. A relevant question is how to estimate the protocol-induced uncertainty of a specific image biomarker, what the effect is on the model performance, and how to optimize the model given the uncertainty. Methods. Two non-small cell lung cancer (NSCLC) cohorts, composed of 421 and 240 patients, respectively, were used for training and testing. Per patient, a Monte Carlo algorithm was used to generate three hundred synthetic contours with a surface dice tolerance measure of less than 1.18 mm with respect to the original GTV. These augmented realizations. Moreover, the high η setup classification was uncertain in its predictions for 50% of the subjects in the testing set (for 80% agreement rate), whereas the low η setup was uncertain only in 10% of the cases. Discussion. Estimating image biomarker model performance based only on the original GTV segmentation, without considering segmentation, uncertainty may be deceiving. The model might result in a significant stratification performance, but can be unstable for delineation variations, which are inherent to manual segmentation. Simulating segmentation uncertainty using the method described allows for more stable image biomarker estimation, selection, and model development. The segmentation uncertainty estimation method described here is universal and can be extended to estimate other protocol uncertainties (such as image acquisition and pre-processing).PIK3CA mutations are believed to contribute to the pathogenesis of human papillomavirus (HPV)-associated head and neck squamous cell carcinomas (HNSCC). This study aims to establish the frequency of PIK3CA mutations in a Portuguese HNSCC cohort and to determine their association with the HPV status and patient survival. A meta-analysis of scientific literature also revealed widely different mutation rates in cohorts from different world regions and a trend towards improved prognosis among patients with PIK3CA mutations. DNA samples were available from 95 patients diagnosed with HNSCC at the Portuguese Institute of Oncology in Lisbon between 2010 and 2019. HPV status was established based on viral DNA detected using real-time PCR. The evaluation of PIK3CA gene mutations was performed by real-time PCR for four mutations (H1047L; E542K, E545K, and E545D). Thirty-seven cases were found to harbour PIK3CA mutations (39%), with the E545D mutation (73%) more frequently detected. There were no significant associations between the mutational status and HPV status (74% WT and 68% MUT were HPV (+); p = 0.489) or overall survival (OS) (3-year OS WT 54% and MUT 65%; p = 0.090). HPV status was the only factor significantly associated with both OS and disease-free survival (DFS), with HPV (+) patients having consistently better outcomes (3-year OS HPV (+) 65% and HPV (-) 36%; p = 0.007; DFS HPV (+) 83% and HPV (-) 43%; p = 0.001). There was a statistically significant interaction effect between HPV status and PIK3CA mutation regarding DFS (Interaction test p = 0.026). In HPV (+) patients, PIK3CA wild-type is associated with a significant 4.64 times increase in the hazard of recurrence or death (HR = 4.64; 95% CI 1.02-20.99; p = 0.047). Overall, PIK3CA gene mutations are present in a large number of patients and may help define patient subsets who can benefit from therapies targeting the PI3K pathway. The systematic assessment of PIK3CA gene mutations in HNSCC patients will require further methodological standardisation.
Hepatitis C virus (HCV) has been shown to be associated with human papillomavirus (HPV)-positive head and neck cancers. However, studies regarding HPV infection and the risk of new-onset hepatocellular carcinoma (HCC) among chronic hepatitis C (CHC) patients are limited. We examined the risk of HCC in CHC patients with or without HPV infection.
In total, 9905 CHC patients from 2000 to 2016 constituted the whole cohort. HPV was defined as being diagnosed after HCV. The CHC cohort with HPV (
= 1981) and age-, sex-, inception point-, comorbidity-, and medication-matched non-HPV (
= 7924) were followed up until HCC, death, or 2018. HCC patients were extracted from the Taiwan Registry for Catastrophic Illness Database. We adopted the propensity score match and inverse probability of treatment weighting (IPTW) to eliminate bias. Cox proportional hazard regression analyses were performed to calculate HCC risk.
After a full adjustment, HPV was not associated with HCC risk (aHR, 0.74; 95% CI, 0.58-0.96 in the main model, and aHR, 0.76; 95% CI, 0.66-0.87 in IPTW, respectively). Almost all subgroup analyses verified this finding (HRs < 1.0).
Among CHC patients older than 18 years old, those with HPV infection were associated with a lower risk of subsequent HCC.
Among CHC patients older than 18 years old, those with HPV infection were associated with a lower risk of subsequent HCC.Burkitt lymphoma (BL) is a malignant B cell neoplasm that accounts for almost half of pediatric cancers in sub-Saharan African countries. Although the BL endemic prevalence is attributable to the combination of Epstein-Barr virus (EBV) infection with malaria and environmental carcinogens exposure, such as the food contaminant aflatoxin B1 (AFB1), the molecular determinants underlying the pathogenesis are not fully understood. Consistent with the role of epigenetic mechanisms at the interface between the genome and environment, AFB1 and EBV impact the methylome of respectively leukocytes and B cells specifically. Here, we conducted a thorough investigation of common epigenomic changes following EBV or AFB1 exposure in B cells. Genome-wide DNA methylation profiling identified an EBV-AFB1 common signature within the TGFBI locus, which encodes for a putative tumor suppressor often altered in cancer. Subsequent mechanistic analyses confirmed a DNA-methylation-dependent transcriptional silencing of TGFBI involving the recruitment of DNMT1 methyltransferase that is associated with an activation of the NF-κB pathway. Our results reveal a potential common mechanism of B cell transformation shared by the main risk factors of endemic BL (EBV and AFB1), suggesting a key determinant of disease that could allow the development of more efficient targeted therapeutic strategies.
