Cancer communications (London, England)
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Cancer Commun (Lond) · Aug 2020
ReviewSingle-cell RNA sequencing in breast cancer: Understanding tumor heterogeneity and paving roads to individualized therapy.
Single-cell RNA sequencing (scRNA-seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA-seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive, automated, and cost-effective single-cell isolation methods with higher throughput as well as ongoing technological development of scRNA-seq protocols. Among the variety of current approaches with distinct features, researchers can choose the most suitable method to carry out their research. ⋯ This review provides a brief introduction on the currently available scRNA-seq approaches along with their corresponding strengths and weaknesses and may act as a reference for the selection of suitable methods for research. We also discuss the current applications of scRNA-seq in breast cancer research for tumor heterogeneity analysis, individualized therapy, and the other research directions mentioned above by reviewing corresponding published studies. Finally, we discuss the limitations of current scRNA-seq technologies and technical problems that remain to be overcome.
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Cancer Commun (Lond) · Apr 2020
ReviewEmerging role of deep learning-based artificial intelligence in tumor pathology.
The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)-based AI, in tumor pathology. The DL-based algorithms have been developed to conduct all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction, as well as the identification of pathological features, biomarkers and genetic changes. ⋯ However, there are still some challenges relating to the implementation of AI, including the issues of algorithm validation and interpretability, computing systems, the unbelieving attitude of pathologists, clinicians and patients, as well as regulators and reimbursements. Herein, we present an overview on how AI-based approaches could be integrated into the workflow of pathologists and discuss the challenges and perspectives of the implementation of AI in tumor pathology.
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Cancer Commun (Lond) · Jan 2020
Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram.
Lung 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. ⋯ The 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.
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Cancer Commun (Lond) · Nov 2019
The ACTIVE study protocol: apatinib or placebo plus gefitinib as first-line treatment for patients with EGFR-mutant advanced non-small cell lung cancer (CTONG1706).
Gefitinib, as the first epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI) approved for the treatment of advanced non-small cell lung cancer (NSCLC), has been proved to significantly improve the progression-free survival (PFS) in the first-line setting but suffers from resistance 7-10 months after treatment initiation. Apatinib (YN968D1), a potent vascular endothelial growth factor receptor (VEGFR) 2-TKI, specifically binds to VEGFR2 and leads to anti-angiogenetic and anti-neoplastic effect. Concurrent inhibition of VEGFR and EGFR pathways represents a rational approach to improve treatment responses and delay the onset of treatment resistance in EGFR-mutant NSCLC. This ACTIVE study aims to assess the combination of apatinib and gefitinib as a new treatment approach for EGFR-mutant NSCLC as a first-line setting. ⋯ The present study will be the first to evaluate the efficacy and safety profile of the combination of apatinib plus gefitinib as a first-line therapy for patients with EGFR-positive advanced non-squamous NSCLC. Importantly, this trial will provide comprehensive evidence on the treatment of EGFR-TKIs combined with antiangiogenic therapy. Trial registration Clinicaltrials.gov NCT02824458. Registered 23 June 2016.