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Discharge kinetics regarding hydroxypropyl methylcellulose regulating substance release and also hydrodynamic modifications involving matrix capsule.
l analysis of the metastatic process.The emergence of whole slide imaging technology allows for pathology diagnosis on a computer screen. The applications of digital pathology are expanding, from supporting remote institutes suffering from a shortage of pathologists to routine use in daily diagnosis including that of lung cancer. Through practice and research large archival databases of digital pathology images have been developed that will facilitate the development of artificial intelligence (AI) methods for image analysis. Currently, several AI applications have been reported in the field of lung cancer; these include the segmentation of carcinoma foci, detection of lymph node metastasis, counting of tumor cells, and prediction of gene mutations. Although the integration of AI algorithms into clinical practice remains a significant challenge, we have implemented tumor cell count for genetic analysis, a helpful application for routine use. Our experience suggests that pathologists often overestimate the contents of tumor cells, and the use of AI-based analysis increases the accuracy and makes the tasks less tedious. However, there are several difficulties encountered in the practical use of AI in clinical diagnosis. These include the lack of sufficient annotated data for the development and validation of AI systems, the explainability of black box AI models, such as those based on deep learning that offer the most promising performance, and the difficulty in defining the ground truth data for training and validation owing to inherent ambiguity in most applications. All of these together present significant challenges in the development and clinical translation of AI methods in the practice of pathology. Additional research on these problems will help in resolving the barriers to the clinical use of AI. Helping pathologists in developing knowledge of the working and limitations of AI will benefit the use of AI in both diagnostics and research.The use of molecular diagnostics in the diagnosis and management of patients with advanced lung cancer has become widespread. Although molecular classification has increasingly been incorporated in the pathologic classification of certain types of human tumors (particularly within the hematologic, glial, and bone/soft tissue malignancies), genetic findings have not been formally incorporated into the pathologic classification of lung cancer, which presently relies solely on the assessment of histologic and immunophenotypic characteristics. Whether molecular classification should be adopted in lung cancer would depend on the diagnostic, prognostic, and predictive impacts of such classification-and whether these impacts confer significant values additive to those derived from the routine histologic and immunophenotypic assessment. We provide a brief overview on the genetics of lung cancer, including adenocarcinoma, squamous cell carcinoma, and neuroendocrine tumors (small cell carcinoma, large cell neuroendocrine carcinoma, and carcinoid tumors). We consider the values of molecular information with some examples, in terms of the current diagnostic, prognostic, and predictive impacts. Finally, we discuss the conceptual and technical challenges of adopting a molecular classification for lung cancer in clinical management for patients. While there are conceptual and technical hurdles to tackle in implementing molecular classification in the pathologic classification of lung cancer, such integrated histologic-molecular diagnosis may allow one to personalize and optimize therapy for patients with advanced lung cancer.Large cell neuroendocrine carcinoma (LCNECs) and small cell lung carcinomas (SCLCs) are high-grade neuroendocrine carcinomas of the lung with very aggressive behavior and poor prognosis. Their histological classification as well as their therapeutic management has not changed much in recent years, but genomic and transcriptomic analyses have revealed different molecular subtypes raising hopes for more personalized treatment. Indeed, four subtypes of SCLCs have been recently described, SCLC-A driven by the master gene ASCL1, SCLC-N driven by NEUROD1, SCLC-Y by YAP1 and SCLC-P by POU2F3. Whereas SCLC standard of care is based on concurrent chemoradiation for limited stages and on chemotherapy alone or chemotherapy combined with anti-PD-L1 checkpoint inhibitors for extensive stage SCLC, SCLC-A variants could benefit from DLL3 or BCL2 inhibitors, and SCLC-N variants from Aurora kinase inhibitors combined with chemotherapy, or PI3K/mTOR or HSP90 inhibitors. In addition, a new SCLC variant (SCLC-IM) with high-expression of immune checkpoints has been also reported, which could benefit from immunotherapies. PARP inhibitors also gave promising results in combination with chemotherapy in a subset of SCLCs. Regarding LCNECs, they represent a heterogeneous group of tumors, some of them exhibiting mutations also found in SCLC but with a pattern of expression of NSCLC, while others harbor mutations also found in NSCLC but with a pattern of expression of SCLC, questioning their clinical management as NSCLCs or SCLCs. Overall, we are probably entering a new area, which, if personalized treatments are effective, will also lead to the implementation in practice of molecular testing or biomarkers detection for the selection of patients who can benefit from them.Lung cancer accounts for most cancer-related deaths worldwide and has an overall 5-year survival rate of ~15%. Cell lines have played important roles in the study of cancer biology and potential therapeutic targets, as well as pre-clinical testing of novel drugs. However, most experimental therapies that have cleared preclinical testing using established cell lines have failed phase III clinical trials. This suggests that such models may not adequately recapitulate patient tumor biology and clinical outcome predictions. Here, we discuss and compare different pre-clinical lung cancer models, including established cell lines, patient-derived cell lines, xenografts and organoids, summarize the methodology for generating these models, and review their relative advantages and limitations in different oncologic research applications. We further discuss additional gaps in patient-derived pre-clinical models to better recapitulate tumor biology and improve their clinical predictive power.The basis of current and future lung cancer immunotherapy depends mainly on our knowledge of the molecular mechanisms of interactions between cancer and immune cells (ICs), as well as on interactions occurring between the different populations of intra-tumor ICs. These interactions are very complex, as virtually all immune cell types, including macrophages, neutrophils, mast cells, natural killer (NK) cells, dendritic cells and T and B lymphocytes can infiltrate lung cancer tissues at the same time. Moreover these interactions lead to progressive emergence of an imbalance in ICs. Initially ICs have an anti-tumor effect but then induce immune tolerance and eventually tumor progression and dissemination. All the cells of innate and adaptive intra-tumor immunity engage in this progressive phenotypic switch. A majority of non-small cell lung carcinoma (NSCLC) patients do not benefit from the expected positive responses associated with current immunotherapy. Thus, there is urgent need to better understand the different roles of the associated cancer ICs. This review summarizes some of the new insights into this domain, with particular focus on the myeloid cell population associated with tumors, the tertiary lymphoid structures (TLSs), the role of the P2 purinergic receptors (P2R) and ATP, and the new concept of the "liquid microenvironment" implying blood circulating ICs.Lung cancer is the leading cause of cancer-related mortality worldwide. Patients with locally advanced non-small cell lung cancer (NSCLC) have lower overall survival. Studies have shown that some patients with unresectable stage III NSCLC develop disease progression after initial chemoradiotherapy, and new treatment is needed to improve the prognosis of these patients. The rapid development of therapy has greatly changed and continued to renew the treatment strategy of advanced NSCLC. However, the clinical treatment for patients with the wild-type gene remains problematic, and chemotherapy with platinum are not yet considered satisfactory. L-Ascorbic acid 2-phosphate sesquimagnesium Herein, we are reporting a case of a patient with wild-type gene mutation locally advanced NSCLC who was treated with neoadjuvant therapy by using combined targeted anti-PD-1 immunotherapy and chemotherapy. The percentage of tumor cells with membranous PD-L1 staining (tumor proportion score) was 90% or greater. After receiving all three cycles of treatment, the patient underwent video-assisted right upper lung lobectomy and wedge resection plus radical mediastinal lymph node dissection. Pathological section samples showed a pathological complete response. This experience has led us to believe that the subgroup of patients with unresectable advanced NSCLC may benefit from this strategy and may have an opportunity for radical surgery.Immune-mediated endocrinopathies are among the most frequent immune-related adverse events (irAEs) with immune checkpoint inhibitors (ICIs) targeting programmed death-ligand 1 (PD-L1)/PD-1. However, the development of auto-immune diabetes is an uncommon event during PD(L)-1 blockade, either as monotherapy or in combination therapy. Here we report a case of a 75-year-old male with a mediastinal recurrence from a stage IA squamous cell carcinoma of the lung previously treated with stereotactic body radiotherapy (SBRT) who early developed a severe diabetic ketoacidosis (DKA) caused by new-onset auto-immune diabetes, with positive glutamic acid decarboxylase (GAD65) autoantibodies, during durvalumab consolidation therapy after concurrent chemoradiation. The patient had no personal or family history of diabetes or auto-immune diseases and was admitted after the second cycle of durvalumab to the intensive care unit (ICU) with severe DKA. During his hospitalization, insulin and fluid therapy were started and the patlly irreversible and cause life-long morbidity, which must be taken into consideration when deciding on further lines of treatment.Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors are the preferred initial treatment for ALK rearranged non-small cell lung cancer (NSCLC). While initial responses to next-generation inhibitors are robust, acquired resistance is expected for nearly all patients. Resistance is often mediated by point mutations along the solvent front. Use of the acquired mutational profile to guide therapy is still investigational and largely based on preclinical data demonstrating sensitivity of resistant cell lines to available kinase inhibitors. Here, we describe outcomes after development of an ALK L1196Q mutation. We present a patient with stage IV ALK rearranged lung cancer received who received first line crizotinib at 250 mg twice daily, then at progression, second line alectinib at 600 mg twice daily. When radiographic evidence of progression was noted, a biopsy was performed. Next generation sequencing (NGS) identified an acquired ALK L1196Q mutation. The patient was treated with third line brigatinib, at 90 mg daily and escalating to 180 mg daily, and achieved a partial response that is still ongoing, one year later.
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