The recent discovery of relevant biomarkers has reshaped our approach to therapy selection for patients with non-small cell lung cancer. The unprecedented outcomes demonstrated with tyrosine kinase inhibitors in molecularly defined cohorts of patients has underscored the importance of genetic profiling in this disease. Despite published guidelines on biomarker testing, successful tumor genotyping faces significant hurdles at both academic and community-based practices. Oncologists are now faced with interpreting large-scale genomic data from multiple tumor types, possibly making it difficult to stay current with practice standards in lung cancer. In addition, physicians' lack of time, resources, and face-to-face opportunities can interfere with the multidisciplinary approach that is essential to delivery of care. Finally, several challenges exist in optimizing the amount and quality of tissue for molecular testing. Recognizing the importance of biomarker testing, a series of advisory boards were recently convened to address these hurdles and clarify best practices. We reviewed these challenges and established recommendations to help optimize tissue acquisition, processing, and testing within the framework of a multidisciplinary approach.
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http://dx.doi.org/10.1634/theoncologist.2015-0114 | DOI Listing |
Chempluschem
December 2024
Centre for Inorganic Chemistry, Chemistry, Bv 120, e/ 60 y 64, Nº1465, 1900, La Plata, ARGENTINA.
The redox imbalance, caused by depletion or generation of reactive oxygen species (ROS), is a key mechanism by which metal complexes exert anticancer effects. Carbidopa has shown the ability to inhibit the MDA-MB-231 cell line, a highly aggressive triple-negative human breast adenocarcinoma, by inducing reductive stress. The metal complex of carbidopa with zinc (ZnCarbi) was designed to modify carbidopa's structure and exhibited increased cytotoxicity against MDA-MB-231 cells.
View Article and Find Full Text PDFInt Urol Nephrol
December 2024
Department of Thoracic Surgery, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, 610041, Sichuan Province, China.
This paper evaluated the bibliometric study by Li et al. (Int Urol Nephrol, 2024) on machine learning in renal medicine. Although the study claims to summarize the forefront trends and hotspots in this field, several key issues require further clarification to effectively guide future research.
View Article and Find Full Text PDFDiscov Oncol
December 2024
Department of Thoracic Surgery, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, No. 1500 Zhouyuan Road, Pudong New Area, Shanghai, China.
Lung adenocarcinoma (LUAD) is a common histologic lung cancer with high morbidity and mortality, and most patients have distant metastases at diagnosis. RasGEF Domain Family Member 1C (RASGEF1C) could regulated Alzheimer's disease. However, its function in various cancers, including LUAD, is poorly understood.
View Article and Find Full Text PDFSupport Care Cancer
December 2024
Department of Oncology, University of Calgary, Calgary, Canada.
Purpose: Lung cancer remains one of the most diagnosed cancers in Canada and continues to be the leading cause of cancer deaths in Canada, responsible for 25% of all cancer deaths. Prior studies consistently report poor experiences of people with lung cancers. The study purpose was to explore the reasons for consistently poorer reported experience of people with lung cancer compared to people with gastrointestinal cancers, who previously have reported positive cancer care experiences within the same context, and to better understand key differences that influence patient experience.
View Article and Find Full Text PDFMed Phys
December 2024
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
Background: Rapid planning is of tremendous value in proton pencil beam scanning (PBS) therapy in overcoming range uncertainty. However, the dose calculation of the dose influence matrix (D) in robust PBS plan optimization is time-consuming and requires substantial acceleration to enhance efficiency.
Purpose: To accelerate the D calculations in PBS therapy, we developed an AI-D engine integrated into our in-house treatment planning system (TPS).
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