Project description:Malignant gliomas are the most common malignant primary brain tumors and one of the most challenging forms of cancers to treat. Despite advances in conventional treatment, the outcome for patients remains almost universally fatal. This poor prognosis is due to therapeutic resistance and tumor recurrence after surgical removal. However, over the past decade, molecular targeted therapy has held the promise of transforming the care of malignant glioma patients. Significant progress in understanding the molecular pathology of gliomagenesis and maintenance of the malignant phenotypes will open opportunities to rationally develop new molecular targeted therapy options. Recently, therapeutic strategies have focused on targeting pro-growth signaling mediated by receptor tyrosine kinase/RAS/phosphatidylinositol 3-kinase pathway, proangiogenic pathways, and several other vital intracellular signaling networks, such as proteasome and histone deacetylase. However, several factors such as cross-talk between the altered pathways, intratumoral molecular heterogeneity, and therapeutic resistance of glioma stem cells (GSCs) have limited the activity of single agents. Efforts are ongoing to study in depth the complex molecular biology of glioma, develop novel regimens targeting GSCs, and identify biomarkers to stratify patients with the individualized molecular targeted therapy. Here, we review the molecular alterations relevant to the pathology of malignant glioma, review current advances in clinical targeted trials, and discuss the challenges, controversies, and future directions of molecular targeted therapy.
Project description:Multiple myeloma (MM) is an incurable malignancy of plasma cells that grow within a permissive bone marrow microenvironment (BMM). The bone marrow milieu supports the malignant transformation both by promoting uncontrolled proliferation and resistance to cell death in MM cells, and by hampering the immune response against the tumor clone. Hence, it is expected that restoring host anti-MM immunity may provide therapeutic benefit for MM patients. Already several immunotherapeutic approaches have shown promising results in the clinical setting. In this review, we outline recent findings demonstrating the potential advantages of targeting the immunosuppressive bone marrow niche to restore effective anti-MM immunity. We discuss different approaches aiming to boost the effector function of T cells and/or exploit innate or adaptive immunity, and highlight novel therapeutic opportunities to increase the immunogenicity of the MM clone. We also discuss the main challenges that hamper the efficacy of immune-based approaches, including intrinsic resistance of MM cells to activated immune-effectors, as well as the protective role of the immune-suppressive and inflammatory bone marrow milieu. Targeting mechanisms to convert the immunologically "cold" to "hot" MM BMM may induce durable immune responses, which in turn may result in long-lasting clinical benefit, even in patient subgroups with high-risk features and poor survival.
Project description:Development of "immune-based targeted therapy" in oncology has limited experience with signal pathway modulation. However, as we have become better versed in understanding immune function related to anticancer response, "hints" of specific targets associated with sensitivity and resistance have been identified with targeted immune therapy. This brief review summarizes the relationship of several targeted immune therapeutics and activity associated clinical responsiveness.
Project description:Background: Malignant pleural effusion (MPE) is a common condition that indicates advanced malignancy, incurability and short life expectancy. While MPE incidence is increasing worldwide, prognostic biomarkers to plan treatment and to understand the underlying mechanisms of disease progression remain unidentified. Objective: To discover, validate, and prospectively assess biomarkers of survival and pleurodesis response in MPE. To combine clinical, radiologic, and pleural fluid biologic parameters in order to build a score that forecasts survival. Conclusions: The PROMISE score is the first prospectively validated prognostic model for MPE that combines biological and clinical parameters to accurately estimate 3-month mortality.
Project description:BackgroundLung cancer is the most commonly diagnosed cancer worldwide. Its survival rate can be significantly improved by early screening. Biomarkers based on radiomics features have been found to provide important physiological information on tumors and considered as having the potential to be used in the early screening of lung cancer. In this study, we aim to establish a radiomics model and develop a tool to improve the discrimination between benign and malignant pulmonary nodules.MethodsA retrospective study was conducted on 875 patients with benign or malignant pulmonary nodules who underwent computed tomography (CT) examinations between June 2013 and June 2018. We assigned 612 patients to a training cohort and 263 patients to a validation cohort. Radiomics features were extracted from the CT images of each patient. Least absolute shrinkage and selection operator (LASSO) was used for radiomics feature selection and radiomics score calculation. Multivariate logistic regression analysis was used to develop a classification model and radiomics nomogram. Radiomics score and clinical variables were used to distinguish benign and malignant pulmonary nodules in logistic model. The performance of the radiomics nomogram was evaluated by the area under the curve (AUC), calibration curve and Hosmer-Lemeshow test in both the training and validation cohorts.ResultsA radiomics score was built and consisted of 20 features selected by LASSO from 1288 radiomics features in the training cohort. The multivariate logistic model and radiomics nomogram were constructed using the radiomics score and patients' age. Good discrimination of benign and malignant pulmonary nodules was obtained from the training cohort (AUC, 0.836; 95% confidence interval [CI]: 0.793-0.879) and validation cohort (AUC, 0.809; 95% CI: 0.745-0.872). The Hosmer-Lemeshow test also showed good performance for the logistic regression model in the training cohort (P = 0.765) and validation cohort (P = 0.064). Good alignment with the calibration curve indicated the good performance of the nomogram.ConclusionsThe established radiomics nomogram is a noninvasive preoperative prediction tool for malignant pulmonary nodule diagnosis. Validation revealed that this nomogram exhibited excellent discrimination and calibration capacities, suggesting its clinical utility in the early screening of lung cancer.
Project description:High density lipoprotein (HDL) is recognized as the major negative risk factor of cardiovascular disease and number of anti-atherogenic functions has been ascribed to HDL. HDL is an assembly of a neutral lipid core and an outer shell consisting of polar lipids and proteins. It has been defined many different ways based on various distinct properties including density flotation, protein composition, molecular size, and electrophoretic migration. Overall the studies characterizing HDL clearly demonstrate that it is a complex heterogeneous mixture of particles. Furthermore several studies convincingly demonstrated that certain populations of HDL particles have a distinct functionality suggesting that HDL may serve as a platform for assembly of protein complexes with very specific biological functions. Indeed recent proteomics studies described over 100 proteins associated with HDL. Here we review approaches to isolation and proteomic analysis of HDL and discuss potential problems associated with isolation methods which may confound our understanding of the relation of the HDL composition and its biological function.
Project description:Whereas the treatment of MM was dependent solely on alkylating agents and corticosteroids during the prior three decades, the landscape of therapeutic measures to treat the disease began to expand enormously early in the current century. The introduction of new classes of small-molecule drugs, such as proteasome blockers (bortezomib and carfilzomib), immunomodulators (lenalidomide and pomalidomide), nuclear export inhibitors (selinexor), and histone deacetylase blockers (panobinostat), as well as the application of autologous stem cell transplantation (ASCT), resulted in a seismic shift in how the disease is treated. The picture changed dramatically once again starting with the 2015 FDA approval of two monoclonal antibodies (mAbs) - the anti-CD38 daratumumab and the anti-SLAMF7 elotuzumab. Daratumumab, in particular, has had a great impact on MM therapy and today is often included in various regimens to treat the disease, both in newly diagnosed cases and in the relapse/refractory setting. Recently, other immunotherapies have been added to the arsenal of drugs available to fight this malignancy. These include isatuximab (also anti-CD38) and, in the past year, the antibody-drug conjugate (ADC) belantamab mafodotin and the chimeric antigen receptor (CAR) T-cell product idecabtagene vicleucel (ide-cel). While the accumulated benefits of these newer agents have resulted in a doubling of the disease's five-year survival rate to more than 5 years and improved quality of life, the disease remains incurable. Almost without exception patients experience relapse and/or become refractory to the drugs used, making the search for innovative therapies all the more essential. This review covers the current scope of anti-myeloma immunotherapeutic agents, both those in clinical use and on the horizon, including naked mAbs, ADCs, bi- and multi-targeted mAbs, and CAR T-cells. Emphasis is placed on the benefits of each along with the challenges that need to be overcome if MM is to be considered curable in the future.
Project description:BackgroundGermline mutations play an important role in the pathogenesis of lung cancer. Nonetheless, research on malignant ground glass opacity (GGO) nodules is limited.MethodsA total of 13 participants with malignant GGO nodules were recruited in this study. Peripheral blood was used for exome sequencing, and germline mutations were analyzed using InterVar. The whole exome sequencing dataset was analyzed using a filtering strategy. KOBAS 3.0 was used to analyze KEGG pathway to further identify possible deleterious mutations.ResultsThere were seven potentially deleterious germline mutations. NM_001184790:exon8: c.C1070T in PARD3, NM_001170721:exon4:c.C392T in BCAR1 and NM_001127221:exon46: c.G6587A in CACNA1A were present in three cases each; rs756875895 frameshift in MAX, NM_005732: exon13:c.2165_2166insT in RAD50 and NM_001142316:exon2:c.G203C in LMO2, were present in two cases each; one variant was present in NOTCH3.ConclusionsOur results expand the germline mutation spectrum in malignant GGO nodules. Importantly, these findings will potentially help screen the high-risk population, guide their health management, and contribute to their clinical treatment and determination of prognosis.
Project description:The aim of this study was to determine whether quantitative analyses ("radiomics") of low-dose computed tomography lung cancer screening images at baseline can predict subsequent emergence of cancer.Public data from the National Lung Screening Trial (ACRIN 6684) were assembled into two cohorts of 104 and 92 patients with screen-detected lung cancer and then matched with cohorts of 208 and 196 screening subjects with benign pulmonary nodules. Image features were extracted from each nodule and used to predict the subsequent emergence of cancer.The best models used 23 stable features in a random forests classifier and could predict nodules that would become cancerous 1 and 2 years hence with accuracies of 80% (area under the curve 0.83) and 79% (area under the curve 0.75), respectively. Radiomics outperformed the Lung Imaging Reporting and Data System and volume-only approaches. The performance of the McWilliams risk assessment model was commensurate.The radiomics of lung cancer screening computed tomography scans at baseline can be used to assess risk for development of cancer.
Project description:Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.