Association between genetic polymorphisms and carotid atherosclerosis in patients treated with radiotherapy for nasopharyngeal carcinoma

Yuan, Chuang; Yip, Shea Ping; Wu, Weiju; Kwong, Dora L.W.; Cheuk, Isabella Wai-Yin; Ying, Michael

doi:10.1186/s13014-015-0341-8

Cited by 6 publications

(1 citation statement)

References 39 publications

(30 reference statements)

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“…Surprisingly, studies have elucidated the link between carotid atherosclerosis and the development of several cancers, including Colorectal adenoma [36,37]. On the other hand, radiotherapy to the neck in patients such as nasopharyngeal carcinoma has also been shown to increase the risk of carotid atherosclerosis [38]. Next, it is necessary to explore the role of TLR2, a core gene found in carotid atherosclerosis, in pan-cancer.…”

Section: Discussionmentioning

confidence: 99%

Machine learning approach for screening key genes of atherosclerosis and perform pan-cancer analysis

Zhan

Jin

et al. 2023

Preprint

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Atherosclerosis is an immunoinflammatory disease caused by lipids which is an important factor in causing coronary heart disease and stroke. Medical researchers around the world are working on more effective ways to diagnose and treat it. This article will introduce a method of machine learning algorithm to screen biomarkers and perform pan-cancer analysis for reference. First, we downloaded the GEO dataset containing information on atherosclerotic patients for differential gene screening. At the same time, we also used TCGA and GTEx databases for pan-carcinogenic analysis of differential genes. Then, we performed WGCNA analysis. The selected module genes were crossed with the differential genes to obtain 122 key genes. Four machine learning algorithms, XGBoost, RandomForest, SVM-REF and GLM, were used to calculate the critical genes and get the junction of the results to obtain 4 hub genes (SLAMF8, TLR2, VAMP8 and VSIG4). Next, we build a diagnostic model and assess the capabilities of this model.At the same time, the ROC curves of the four genes also suggest that their role in the development of atherosclerosis is critical. Next, we performed gene correlation analysis, immune infiltration analysis and RT-PCR verification of the four core genes, and finally screened out TLR2 for pan-carcinoma. Through analysis, we can find that the expression of TLR2 in patients with a variety of tumors is different from that of normal people, and it is strongly associated with the proportion of prognosis of patients with diverse cancers. The results suggest that TLR2 may be a target for intervention in the development of diseases such as atherosclerosis and tumors.

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Section: Discussionmentioning

confidence: 99%

Machine learning approach for screening key genes of atherosclerosis and perform pan-cancer analysis

Zhan

Jin

et al. 2023

Preprint

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Long-Term Outcomes Among Survivors of Childhood Central Nervous System Malignancies: Late Mortality, Subsequent Neoplasms, Endocrine and Neurologic Morbidity

Armstrong

Khan

Chemaitilly

2018

Brain Tumors in Children

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The independent and incremental value of ultrasound carotid plaque length to predict the presence and severity of coronary artery disease: analysis from the carotid plaque length prospective registry

Wen-dong

Shen

et al. 2019

European Heart Journal - Cardiovascular Imaging

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Aims Data regarding the relationship between carotid plaque length (CPL) and coronary artery disease (CAD) are lacking. This study aimed to assess the predictive value of CPL for the severity of CAD. Methods and results We prospectively enrolled 2149 consecutive patients who underwent both first coronary angiography and carotid ultrasonography with measurements of intima-media thickness (IMT), plaque score (PS), and CPL. In total, 1408 (65.5%) patients had CAD (defined as stenosis ≥50%), and 741 (34.5%) patients had no CAD. Patients with CAD had longer maximal CPL than those without CAD (P < 0.001). The severity of CAD, measured by the Gensini score (GS), was closely correlated with max-CPL (rs = 0.560), followed by PS (rs = 0.486) and mean-IMT (rs = 0.292). Multivariate analysis revealed that max-CPL remained independently associated with CAD and high-GS after adjustment for traditional risk factors (TRF). Max-CPL, compared with PS or mean-IMT, had significantly higher discrimination value for predicting high-GS [area under the curve (AUC) 0.819 vs. 0.769 vs. 0.634, P < 0.001]. At a cut-off value for the max-CPL of 6.3 mm, the sensitivity and negative predictive value for high-GS were 84.6% and 89.1%, respectively. Furthermore, the addition of max-CPL significantly improved the discrimination (AUC 0.832 vs. 0.720, P < 0.001) and reclassification (net reclassification improvement = 0.431, P < 0.001) over TRF for high-GS. Conclusion Ultrasound max-CPL provides independent and incremental predictive value for the clinical severity of CAD over TRF and seems a simple useful marker in CAD risk stratification.

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Association between genetic polymorphisms and carotid atherosclerosis in patients treated with radiotherapy for nasopharyngeal carcinoma

Cited by 6 publications

References 39 publications

Machine learning approach for screening key genes of atherosclerosis and perform pan-cancer analysis

Machine learning approach for screening key genes of atherosclerosis and perform pan-cancer analysis

Long-Term Outcomes Among Survivors of Childhood Central Nervous System Malignancies: Late Mortality, Subsequent Neoplasms, Endocrine and Neurologic Morbidity

The independent and incremental value of ultrasound carotid plaque length to predict the presence and severity of coronary artery disease: analysis from the carotid plaque length prospective registry

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