Jie Zhang

Jie Zhang

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 November 2018 in Thoracic Cancer
Verified
Journal Article
Open access
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JZJie Zhang
Jie Zhang
CWChunyan Wu
Chunyan Wu
WDWei Ding
Wei Ding
ZZZhihong Zhang
Zhihong Zhang
XQXueshan Qiu
Xueshan Qiu
JZJie Zhang
Jie Zhang
Background: The study was conducted to investigate the clinicopathological features and prevalence of ROS1 gene fusion in Chinese patients with non‐small cell lung cancer (NSCLC).Methods: The presence of ROS1 fusion was assessed by quantitative real‐time PCR. Associations between ROS1 fusion and clinical characteristics were analyzed.Results: In total, 6066 patients with pathologically confirmed NSCLC and ROS1 fusion test results were enrolled. The average age was 60.89 ± 10.60 years and fusion was detected in 157 (2.59%) patients. Fusion frequency was significantly correlated with age, gender, smoking status (all P < 0.001), pathology type (P = 0.017), and lymph node metastasis stage (P = 0.027). ROS1 fusion‐positive patients were significantly younger (55.68 ± 11.34 vs. negative 61.02 ± 10.44 years; P < 0.01). Fusion frequency was higher in women (3.71% vs. men 1.81%), never‐smokers (3.33% vs. smokers 1.21%), and patients with adenocarcinoma (2.77% vs. squamous lung cancer 0.93%) and at advanced node stages (1.31%, 1.40%, 2.07%, and 3.23% for N0, N1, N2, and N3, respectively). No significant correlation between ROS1 fusion status and pathological stage was found in subgroups classified by pathological, tumor, or metastasis stage (P > 0.05). Age, smoking status, and lymph node stage were statistically significantly correlated with ROS1 fusion frequency (all P < 0.05); gender and pathology type were not significantly correlated with ROS1 fusion status after adjusting for smoking status.Conclusion: An overall ROS1 fusion frequency of 2.59% was confirmed in this study. ROS1 fusion was more prevalent among younger patients, never‐smokers, and those at advanced node stages.

10 June 2018 in bioRxiv
Verified
Preprint
Open access
PDF file
MZMingchao Zhang
Mingchao Zhang
YLYujia Li
Yujia Li
JZJie Zhang
Jie Zhang
HTHaohua Teng
Haohua Teng
JZJie Zhang
Jie Zhang
WYWeihai Ying
Weihai Ying
Early and non-invasive diagnosis is critical for enhancing the survival rates of lung cancer. In current study we determined the green autoflorescence (AF) of the pulmonary parenchyma of lung cancer patients, using 488 nm and 500 - 550 nm as excitation wavelength and emission wavelength, respectively. Our study has suggested that decreased green AF intensity of pulmonary parenchyma may be a potential diagnostic biomarker for lung cancer: First, the green AF intensity of the cancerous tissues is less than 40% of those of distant non-neoplastic tissues and peri-neoplastic tissues; second, the green AF intensity of both the distant non-neoplastic tissues and cancerous tissues of squamous carcinoma is significantly lower than that of adenocarcinoma; third, the AF intensity of the peri-neoplastic tissues of the lung cancer patients is negatively correlated with the stages of lung cancer; and fourth, our study on the AF spectrum of pulmonary parenchyma has suggested that the AF may result from the AF of the keratins or FAD of the pulmonary parenchyma. Collectively, our study has suggested that decreased green AF intensity of pulmonary parenchyma may become a novel biomarker for non-invasive diagnosis of lung cancer. The green AF intensity may also be used to non-invasively differentiate squamous carcinoma and adenocarcinoma, as well as the stages of lung cancer. Moreover, our diagnostic approach for lung cancer may be used for image-guided surgery of lung cancer for lesions that have not been identified by CT.