Metastatic Tumor Burden and Loci as Predictors of First Line Sunitinib Treatment Efficacy in Patients with Renal Cell Carcinoma

Czarnecka, Anna M.; Brodziak, Anna; Sobczuk, Paweł; Dendek, Cezary; Labochka, Dominika; Korniluk, Jan; Bartnik, Ewa; Szczylik, Cezary

doi:10.1038/s41598-019-44226-y

Cited by 12 publications

(5 citation statements)

References 45 publications

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“…The total mass of tumor tissue, including the tumor cells distributed in bone marrow in patients with cancer, is referred to as a tumor burden [ 127 ]. Tumor burden surveillance is important in all phases of cancer management to prevent metastasis and recurrence [ 128 ].…”

Section: Further Use Of Ctdna In Nsclcmentioning

confidence: 99%

Applications of Liquid Biopsies in Non-Small-Cell Lung Cancer

et al. 2022

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The concept of liquid biopsy as an analysis tool for non-solid tissue carried out for the purpose of providing information about solid tumors was introduced approximately 20 years ago. Additional to the detection of circulating tumor cells (CTCs), the liquid biopsy approach quickly included the analysis of circulating tumor DNA (ctDNA) and other tumor-derived markers such as circulating cell-free RNA or extracellular vesicles. Liquid biopsy is a non-invasive technique for detecting multiple cancer-associated biomarkers that is easy to obtain and can reflect the characteristics of the entire tumor mass. Currently, ctDNA is the key component of the liquid biopsy approach from the point of view of the prognosis assessment, prediction, and monitoring of the treatment of non-small-cell lung cancer (NSCLC) patients. ctDNA in NSCLC patients carries variants or rearrangements that drive carcinogenesis, such as those in EGFR, KRAS, ALK, or ROS1. Due to advances in pharmacology, these variants are the subject of targeted therapy. Therefore, the detection of these variants has gained attention in clinical medicine. Recently, methods based on qPCR (ddPCR, BEAMing) and next-generation sequencing (NGS) are the most effective approaches for ctDNA analysis. This review addresses various aspects of the use of liquid biopsy with an emphasis on ctDNA as a biomarker in NSCLC patients.

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Section: Further Use Of Ctdna In Nsclcmentioning

confidence: 99%

Applications of Liquid Biopsies in Non-Small-Cell Lung Cancer

et al. 2022

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“…Estimating tumour burden and volume of disease in spinal metastases is difficult due to the shape of the vertebrae and presence of multiple vertebral levels. Tumour burden of spinal metastases has been shown to predict prognosis [ 106 , 127 , 128 , 129 ] and treatment efficiency [ 130 ]. With the help of AI, volumetric evaluation of spinal metastases and disease burden can be more efficient, clinically feasible and could aid clinical management.…”

Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis

Ong

Zhu

Zhang

et al. 2022

Cancers

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Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.

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“…A recent prospective study has shown that tumor burden and location of metastasis influence the rate of progression-free survival of patients with metastatic RCC using tyrosine kinase inhibitor (TKI), with pulmonary metastasis as the only positive predictor and skin as the worst predictor [5] , [6] . Although due to the limited investigation of skin metastasis, this case report shows regression of skin metastasis after the administration of pazopanib.…”

Section: Discussionmentioning

confidence: 99%