Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disease caused by the mutations in the NF1 gene, with an incidence of approximately 1/3 000. Affecting multiple organs and systems throughout the body, NF1 caused a wide variety of clinical symptoms. A comprehensive multidisciplinary diagnostic and treatment model is needed to meet the diverse needs of NF1 patients and improve their quality of life. In recent years, the emergence of targeted therapies has further benefited NF1 patients, and the number of clinical consultations has increased dramatically. However, due to the rarity of the disease itself and insufficient attention previously, the standardized, systematic, and precise diagnosis and treatment model of NF1 still needs to be further improved. In this paper, we reviewed the current status of comprehensive diagnosis and treatment of NF1 in China, combine with our long-term experiences in diagnosis and treatment of this disease. Meanwhile, we propose future directions and several suggestions for the comprehensive diagnosis and treatment model for Chinese NF1 patients.
Along with the popularity of low-dose computed tomography lung cancer screening, an increasing number of early-stage lung cancers are detected. Radical lobectomy with systematic nodal dissection (SND) remains the standard-of-care for operable lung cancer patients. However, whether SND should be performed on non-metastatic lymph nodes remains controversy. Unnecessary lymph node dissection can increase the difficulty of surgery while also causing additional surgical damage. In addition, non-metastatic lymph nodes have been recently reported to play a key role in immunotherapy. How to reduce the surgical damage of mediastinal lymph node dissection for early-stage lung cancer patients is pivotal for modern concept of "minimally invasive surgery for lung cancer 3.0". The selective mediastinal lymph node dissection strategy aims to dissect lymph nodes with tumor metastasis while preserving normal mediastinal lymph nodes. Previous studies have shown that combination of specific tumor segment site, radiology and intraoperative frozen pathology characteristics can accurately predict the pattern of mediastinal lymph node metastasis. The personalized selective mediastinal lymph node dissection strategy formed from this has been successfully validated in a recent prospective clinical trial, providing an important basis for early-stage lung cancer patients to receive more personalized selective lymph node dissection with "precision surgery" strategies.
Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidity and mortality worldwide. For patients with advanced non-small cell lung cancer who have undergone epidermal growth factor receptor (EGFR) gene mutations, targeted drugs can be used for targeted therapy. There are many methods for detecting EGFR gene mutations, but each method has its own advantages and disadvantages. This study aims to predict the risk of EGFR gene mutation by exploring the association between the histological features of the whole slides pathology of non-small cell lung cancer hematoxylin-eosin (HE) staining and the patient's EGFR mutant gene. The experimental results show that the area under the curve (AUC) of the EGFR gene mutation risk prediction model proposed in this paper reached 72.4% on the test set, and the accuracy rate was 70.8%, which reveals the close relationship between histomorphological features and EGFR gene mutations in the whole slides pathological images of non-small cell lung cancer. In this paper, the molecular phenotypes were analyzed from the scale of the whole slides pathological images, and the combination of pathology and molecular omics was used to establish the EGFR gene mutation risk prediction model, revealing the correlation between the whole slides pathological images and EGFR gene mutation risk. It could provide a promising research direction for this field.
ObjectiveTo summarize the application of circulating free DNA (cfDNA) in the diagnosis and treatment of hepatocellular carcinoma (HCC). MethodThe relevant literature on the application of cfDNA in the diagnosis and treatment of HCC both domestic and international was reviewed and summarized. ResultsThe cfDNA is an emerging biomarker in recent years. At present, the different detection methods had been reported in a large number of studies to detect abnormal methylation, hot spot mutation, gene copy number variation, quantitative detection of cfDNA concentration, etc. It was found that the cfDNA could be used in the management process of early diagnosis, treatment guidance, and efficacy evaluation of HCC patients. ConclusionscfDNA detection is a good tool in the diagnosis and treatment of HCC, which can help clinicians make-decisions and bring more possibilities for the diagnosis and treatment of HCC, which is of great significance for changing the current diagnosis and treatment of HCC. However, there are still many challenges in cost control, technology optimization, and standardization of evaluation indicators. With the continuous progress of molecular biology technology and artificial intelligence, the application of cfDNA in diagnosis and treatment of HCC will be further expanded, its advantages will be better played, and the related shortcomings will be gradually solved.
Lung cancer is one of the leading causes of cancer deaths worldwide. Many options including surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy have been applied in the treatment for lung cancer patients. However, how to develop individualized treatment plans for patients and accurately determine the prognosis of patients is still a very difficult clinical problem. In recent years, radiomics, as an emerging method for medical image analysis, has gradually received the attention from researchers. It is based on the assumption that medical images contain a vast amount of biological information about patients that is difficult to identify with naked eyes but can be accessed by computer. One of the most common uses of radiomics is the diagnosis and treatment of non-small cell lung cancer (NSCLC). In this review, we reviewed the current researches on chest CT-based radiomics in the diagnosis and treatment of NSCLC and provided a brief summary of the current state of research in this field, covering various aspects of qualitative diagnosis, efficacy prediction, and prognostic analysis of lung cancer. We also briefly described the main current technical limitations of this technology with the aim of gaining a broader understanding of its potential role in the diagnosis and treatment of NSCLC and advancing its development as a tool for individualized management of NSCLC patients.
With the advancement of thyroid tumor treatment concepts and the progress of standardized treatment processes nationwide, the 5-year survival rate of thyroid tumors in China has risen from 67.5% in 2003 to 84.3% in 2015. As China has been continuously enriching its treatment options for advanced thyroid cancer in recent years, gradually improving the standardized treatment system for early and intermediate thyroid cancer, enhancing multidisciplinary collaboration methods and concepts, and regularizing scientific statistics, the survival rate of thyroid tumors continues to improve. We still need to consider the future development direction and core driving force of China’s thyroid discipline, correctly view the “prosperous” stage of domestic thyroid discipline development, and actively review the future development direction of China’s thyroid discipline.
Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.
ObjectiveTo summarize the application of radiomics in colorectal cancer.MethodsRelevant literatures about the therapeutic decision-making, therapeutic, and prognostic evaluation of colorectal cancer using radiomics were collected to make an review.ResultsRadiomics is of great value in preoperative stages, therapeutic, and prognostic evaluation in colorectal cancer.ConclusionRadiomics is an important part of precision medical imaging for colorectal cancer.
Liddle syndrome and Gordon syndrome are two rare single-gene inherited hypertension diseases. In patients≤40 years, the prevalence of Liddle syndrome is about 1% and Gordon syndrome is uncertain all over the word, for which is often misdiagnosed and mistreated. The therapies of those diseases are targeted at gene mutation sites, as well as combined with modified lifestyle, and can achieve satisfactory diseases control. This paper reports a patient who is diagnosed with Liddle syndrome and Gordon syndrome at the same time. We aimed to consolidate and improve the diagnosis and accurate treatment of those two diseases by sharing, studying and discussing together with clinical doctors.
Cardiovascular disease and cancer are the two leading chronic conditions contributing to global mortality. With the rising incidence of cancer, the prevalence of cancer therapy-related cardiovascular complications has also increased, driving the development of the emerging field of cardio-oncology. The advancement of precision medicine offers new opportunities for the individualized and targeted management of cardiovascular toxicities associated with cancer treatment. Artificial intelligence (AI) has the potential to overcome traditional limitations in medical data integration, dynamic monitoring, and interdisciplinary collaboration, thereby accelerating the application of precision medicine in cardio-oncology. By enabling personalized treatment and reducing cardiovascular complications in cancer patients, AI serves as a critical tool in this domain. This article provides an in-depth interpretation of the "Artificial intelligence to enhance precision medicine in cardio-oncology: a scientific statement from the American Heart Association" aiming to inform the integration of AI into precision medicine in China. The goal is to promote its application in the management of cardiovascular diseases related to cancer therapy and to achieve precision management in this context.