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24. Cardiac magnetic resonance imaging parameters show association between myocardial abnormalities and severity of chronic kidney disease

Author

Jia, Xi, primary, Han, Xiaoyu, additional, Wang, Yuqin, additional, He, Fangfang, additional, Zhou, Xiaoyue, additional, Zheng, Yuting, additional, Guo, Yingkun, additional, Xu, Rong, additional, Liu, Jia, additional, Li, Yumin, additional, Gu, Jin, additional, Cao, Yukun, additional, Zhang, Chun, additional, and Shi, Heshui, additional

Published
2022
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32. sj-doc-2-tct-10.1177_15330338221141541 - Supplemental material for A Novel Risk Factor for Para-Aortic Lymph Node Recurrence After Definite Pelvic Radiotherapy in Stage IIIB Cervical Cancer

Author

Zhang, Guangyu, Wang, Cong, Ma, Changdong, Miao, Li, He, Fangfang, and Fu, Chunli

Subjects
110320 Radiology and Organ Imaging, FOS: Clinical medicine, Biochemistry, 111299 Oncology and Carcinogenesis not elsewhere classified
Abstract

Supplemental material, sj-doc-2-tct-10.1177_15330338221141541 for A Novel Risk Factor for Para-Aortic Lymph Node Recurrence After Definite Pelvic Radiotherapy in Stage IIIB Cervical Cancer by Guangyu Zhang, Cong Wang, Changdong Ma, Li Miao, Fangfang He and Chunli Fu in Technology in Cancer Research & Treatment

Published
2022
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33. A Novel Risk Factor for Para-Aortic Lymph Node Recurrence After Definite Pelvic Radiotherapy in Stage IIIB Cervical Cancer.

Author

Zhang, Guangyu, Wang, Cong, Ma, Changdong, Miao, Li, He, Fangfang, and Fu, Chunli

Subjects
CERVICAL cancer, LYMPH nodes, DISEASE risk factors, LYMPHATIC metastasis, MULTIVARIATE analysis, PAPILLOMAVIRUS diseases
Abstract

Background: Studies determining which patients with International Federation of Gynecology and Obstetrics (FIGO) stage IIIB disease benefit from prophylactic extended-field irradiation (EFRT), which can reduce para-aortic lymph node (PALN) failure rates, are limited. The study was designed to evaluate the value of the controlling nutritional status (CONUT) score as a risk factor for predicting PALN recurrence and identifying potential indications of prophylactic EFRT. Methods: From 2010 to 2015, a retrospective review was conducted among patients with FIGO stage IIIB cervical cancer who were treated with definitive pelvic radiotherapy or concurrent chemoradiotherapy. We analyzed para-aortic lymph node metastasis-free survival (PALNMFS) using Kaplan-Meier curves. Multivariate analyses were performed using Cox regression models. Results: A total of 116 patients with FIGO stage IIIB cervical cancer were included in the study and the median follow-up was 42.2 months (range: 3.5-104.2 months). Multivariate analysis revealed that the CONUT score (HR: 3.141; 95% CI: 2.321-5.436; P <.001) and ≥3 pelvic lymph node metastases (HR: 2.235; 95% CI: 1.428-11.242; P <.001) were independent risk predictors of PALNMFS. Compared with the low CONUT group (score<3), the high CONUT group (score≥3) was associated with a significantly worse 3-year disease-free survival rate (46.9 vs 69.5%, P =.001), a significantly lower 3-year overall survival rate (68.5 vs 79.7%, P =.016) and a significantly lower PALNMFS rate (74.8 vs 96.4%, P <.001). Conclusions: A high CONUT score (score≥3) and ≥3 pelvic metastatic lymph nodes were significant predictors of PALNMFS after pelvic radiation in FIGO stage IIIB cervical cancer patients. Patients with these risk factors might benefit from prophylactic EFRT. [ABSTRACT FROM AUTHOR]

Published
2022
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36. Additional file 7 of Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers

Author

Chan, David W., Lam, Wai-Yip, Chen, Fushun, Yung, Mingo M. H., Chan, Yau-Sang, Chan, Wai-Sun, He, Fangfang, Liu, Stephanie S., Chan, Karen K. L., Li, Benjamin, and Ngan, Hextan Y. S.

Abstract

Additional file 7: Fig. S3. Heatmap visualization of DNA methylation levels in the PI3K-AKT, RAS, MAPK, and WNT signaling pathways and Kaplan–Meier estimates of OS using the methylation signature of genes.

Published
2021
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37. Additional file 9 of Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers

Author

Chan, David W., Lam, Wai-Yip, Chen, Fushun, Yung, Mingo M. H., Chan, Yau-Sang, Chan, Wai-Sun, He, Fangfang, Liu, Stephanie S., Chan, Karen K. L., Li, Benjamin, and Ngan, Hextan Y. S.

Abstract

Additional file 9: Fig. S5. (A) Table summarizing the IC50 values of a 48-h treatment with cisplatin, azacytidine, decitabine, and thioguanine in the six ovarian cancer cell lines using the XTT assay. IC50 values were determined at the drug concentration leading to a 50% viability reduction compared to the control. (B) Annexin V-PI staining of A2780cp and A2780s cells after a 48-h treatment with different concentrations of cisplatin, azacytidine, decitabine, and thioguanine by flow cytometry. Data analysis was performed with CytExpert software. (C) Population of apoptotic cells in each treatment condition from Annexin V-PI staining. The apoptotic cell population was represented by the cell population in the lower right quadrant (early apoptotic) and upper right quadrant (late apoptotic). (D) Cell cycle analysis of A2780cp and A2780s cells after 48 h of treatment with different concentrations of cisplatin, azacytidine, decitabine, and thioguanine by flow cytometry. Data analysis was performed with Modfit LT software. (E) Distribution of cells in different phases of the cell cycle in each treatment condition. Populations of cells distributed in G0/G1, S, G2/M and SubG1 phases are presented in different colored peaks.

Published
2021
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38. Additional file 5 of Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers

Author

Chan, David W., Lam, Wai-Yip, Chen, Fushun, Yung, Mingo M. H., Chan, Yau-Sang, Chan, Wai-Sun, He, Fangfang, Liu, Stephanie S., Chan, Karen K. L., Li, Benjamin, and Ngan, Hextan Y. S.

Abstract

Additional file 5: Fig. S1. Kaplan–Meier estimate of OS using methylation signature genes (CLDN16, LZTFL1, FARS2, SGMS2, ABHD2, RNF144A, and HPS4).

Published
2021
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39. Additional file 6 of Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers

Author

Chan, David W., Lam, Wai-Yip, Chen, Fushun, Yung, Mingo M. H., Chan, Yau-Sang, Chan, Wai-Sun, He, Fangfang, Liu, Stephanie S., Chan, Karen K. L., Li, Benjamin, and Ngan, Hextan Y. S.

Abstract

Additional file 6: Fig. S2. Boxplot visualization of comparison of the DNA methylation level of tumor grading. EOC samples were marked by tumor stage, tumor subtype, recurrence, and survival status.

Published
2021
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40. Additional file 8 of Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers

Author

Chan, David W., Lam, Wai-Yip, Chen, Fushun, Yung, Mingo M. H., Chan, Yau-Sang, Chan, Wai-Sun, He, Fangfang, Liu, Stephanie S., Chan, Karen K. L., Li, Benjamin, and Ngan, Hextan Y. S.

Abstract

Additional file 8: Fig. S4. Gene ontology (GO) enrichment analysis of the overall functional relevance of genes associated with DMPs using the clusterProfiler package in R.

Published
2021
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50. DPre: computational identification of differentiation bias and genes underlying cell type conversions.

Author

Steffens, Simon, Fu, Xiuling, He, Fangfang, Li, Yuhao, Babarinde, Isaac A, and Hutchins, Andrew P

Subjects
INTERNET servers, CELL differentiation, GROWTH factors, SOURCE code, CELL populations, GENES, BIBLIOTHERAPY
Abstract

Summary Cells are generally resistant to cell type conversions, but can be converted by the application of growth factors, chemical inhibitors and ectopic expression of genes. However, it remains difficult to accurately identify the destination cell type or differentiation bias when these techniques are used to alter cell type. Consequently, there is demand for computational techniques that can help researchers understand both the cell type and differentiation bias. While advanced tools identifying cell types exist for single cell data and the deconvolution of mixed cell populations, the problem of exploring partially differentiated cells of indeterminate transcriptional identity has not been addressed. To fill this gap, we developed driver-predictor, which relies on scoring per gene transcriptional similarity between RNA-Seq datasets to reveal directional bias of differentiation. By comparing against large cell type transcriptome libraries or a desired target expression profile, the tool enables the user to visualize both the changes in transcriptional identity as well as the genes accounting for the cell type changes. This software will be a powerful tool for researchers to explore in vitro experiments that involve cell type conversions. Availability and implementation Source code is open source under the MIT license and is freely available on https://github.com/LoaloaF/DPre. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2020
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