Article
Biology
Dan Liu, Lulu Yao, Xiaolei Ding, Huan Zhou
Summary: By analyzing large amounts of data, this study identified 22 key genes that play important roles in the immune regulatory mechanism of lung adenocarcinoma (LUAD) and can predict patient survival time and distant metastasis. Additionally, the study identified cell types that are crucial in the immune microenvironment of LUAD. These findings provide potential prognostic markers and therapeutic targets for LUAD.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Oncology
Xiaoyong Ge, Hui Xu, Siyuan Weng, Yuyuan Zhang, Long Liu, Libo Wang, Zhe Xing, Yuhao Ba, Shutong Liu, Lifeng Li, Yuhui Wang, Xinwei Han
Summary: The updated guidelines highlight the importance of using gene expression-based multigene panels to assess overall survival and improve treatment for lung adenocarcinoma patients. However, the clinical utility of genome-wide expression signatures is still limited due to insufficient data utilization, lack of critical validation, and inappropriate machine learning algorithms.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2023)
Article
Multidisciplinary Sciences
Yang Liu, Qiuhong Wu, Xuejiao Fan, Wen Li, Xiaogang Li, Hui Zhu, Qinghua Zhou, Jinming Yu
Summary: This study identified a novel immune-related long non-coding RNA signature in LUAD, independent of RNA expression levels, which could predict the prognosis of LUAD patients and guide clinical practice.
SCIENTIFIC REPORTS
(2021)
Article
Biotechnology & Applied Microbiology
Junqi Qin, Zhanyu Xu, Kun Deng, Fanglu Qin, Jiangbo Wei, Liqiang Yuan, Yu Sun, Tiaozhan Zheng, Shikang Li
Summary: This study screened and validated a 12-gene prognostic signature for predicting the survival prognosis of lung adenocarcinoma patients. The signature showed a significant difference in survival outcomes between high and low-risk groups, with a relatively high true positive rate when predicting 1-year, 3-year, and 5-year overall survival. Additionally, immune-related pathways were highlighted in the functional enrichment analysis, suggesting potential targeted treatment options for lung cancer patients.
Review
Cell Biology
Xinping Zhu, Masahisa Kudo, Xiangjie Huang, Hehuan Sui, Haishan Tian, Carlo M. Croce, Ri Cui
Summary: Lung cancer, particularly NSCLC, is a major cause of cancer-related deaths globally. Recent advancements in treatment have improved therapeutic efficacy, but the survival rate remains low due to inadequate screening methods and late onset of symptoms. Dysregulation of miRNAs in NSCLC plays a critical role in development, progression, and metastasis, presenting potential for diagnostic and therapeutic applications.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Oncology
Zhengrong Yin, Jingjing Deng, Mei Zhou, Minglei Li, E. Zhou, Jiatong Liu, Zhe Jia, Guanghai Yang, Yang Jin
Summary: In this study, the value of circadian miRNA (cmiRNA) as a prognostic marker for lung adenocarcinoma (LUAD) was explored, and a prognostic signature was developed. The results showed that the signature had good predictive performance for overall and progression-free survival in LUAD, and high-risk patients showed higher sensitivity to chemotherapy and targeted medicine. In addition, a cmiRNA-Cgenes network was constructed, and enrichment analysis was performed.
Review
Medicine, Research & Experimental
Bashdar Mahmud Hussen, Hazha Jamal Hidayat, Abbas Salihi, Dana K. Sabir, Mohammad Taheri, Soudeh Ghafouri-Fard
Summary: MicroRNAs (miRNAs) are small non-coding RNAs that play a critical role in cancer by post-transcriptionally controlling gene expression. They are involved in the initiation, progression, and metastasis of cancer, and can be used to classify genes affecting cancer pathways.
BIOMEDICINE & PHARMACOTHERAPY
(2021)
Article
Multidisciplinary Sciences
Congkuan Song, Zilong Lu, Kai Lai, Donghang Li, Bo Hao, Chenzhen Xu, Shize Pan, Ning Li, Qing Geng
Summary: This study comprehensively analyzed the RNA expression and clinical features of IRGs in over 2000 LUAD patients and developed a novel IRG signature for risk stratification and drug efficacy prediction. The signature effectively categorized patients and had better predictive value in survival assessment. Additionally, significant differences in pathways, tumor microenvironment, genomic and somatic mutation landscape were found between different subgroups.
SCIENTIFIC REPORTS
(2022)
Article
Oncology
Aisha Al-Dherasi, Qi-Tian Huang, Yuwei Liao, Sultan Al-Mosaib, Rulin Hua, Yichen Wang, Ying Yu, Yu Zhang, Xuehong Zhang, Chao Huang, Haithm Mousa, Dongcen Ge, Sufiyan Sufiyan, Wanting Bai, Ruimei Liu, Yanyan Shao, Yulong Li, Jingkai Zhang, Leming Shi, Dekang Lv, Zhiguang Li, Quentin Liu
Summary: This study established a prognostic signature consisting of seven genes related to overall survival in LUAD patients. The signature effectively categorized patients into high and low-risk groups and showed good predictive performance in both training and validation cohorts.
CANCER CELL INTERNATIONAL
(2021)
Article
Cell Biology
Yuan Zhou, Lu Tang, Yuqiao Chen, Youyu Zhang, Wei Zhuang
Summary: This study established a risk signature based on immune genes to predict the prognosis of LUAD patients, which was closely associated with the infiltration of neutrophils. The risk signature had a robust performance in accurately predicting survival and was validated in external cohorts.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Juan Chen, Rui Zhou
Summary: This study identified 106 TME-related genes associated with the overall survival of LUAD patients, focusing on immune response, cell adhesion, and extracellular matrix. PTPRC and CD19 emerged as highly interconnected nodes in the PPI network, correlating with immune activity and showing significant prognostic potential as TME-related SurGenes. The prognostic model constructed from these genes demonstrated high predictive ability, with implications for clinical survival prediction in LUAD.
Article
Genetics & Heredity
Si Shi, Shibin Chen, Menghang Wang, Bingchen Guo, Yaowu He, Hong Chen
Summary: This study evaluated the clinical significance of ATIRE events in LUAD and constructed a model for predicting survival. The study found that events involving ATIRE in LUAD were highly functional and clinically relevant.
FRONTIERS IN GENETICS
(2023)
Article
Surgery
Raju Kandimalla, Tadanobu Shimura, Saurav Mallik, Fuminori Sonohara, Susan Tsai, Douglas B. Evans, Song Cheol Kim, Hideo Baba, Yasuhiro Kodera, Daniel Von Hoff, Xi Chen, Ajay Goel
Summary: By performing mRNA-miRNA regulatory network analyses, a panel of miRNAs has been identified for molecular subtype identification and risk stratification of high-risk patients with pancreatic ductal adenocarcinoma (PDAC). The miRNA panel showed significant association with poor survival in PDAC molecular subtypes and can be used as a noninvasive assay for identifying high-risk patients and potential disease monitoring. The predictive accuracy of the miRNA panel can be further improved by incorporating clinicopathological factors.
Article
Cell Biology
Wei Jiang, Jiameng Xu, Zirui Liao, Guangbin Li, Chengpeng Zhang, Yu Feng
Summary: Through analysis of the GSE68465 dataset, we identified 10 LUAC-specific CCRGs and constructed a model. Based on this model, LUAC patients were divided into high- and low-risk groups and the validity was confirmed. Data from CPTAC, HPA, and IHC supported significant dysregulation of these CCRGs in LUAC tissues.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Medicine, Research & Experimental
Ruijun Liu, Zhiyi Guo, Jia Huang, Jiantao Li, Qiang Tan, Qingquan Luo
Summary: This study used bioinformatics analysis to analyze miRNA in lung adenocarcinoma and identified a 7-miRNA signature that can accurately predict survival in this type of cancer.
EXPERIMENTAL BIOLOGY AND MEDICINE
(2022)
Article
Biochemical Research Methods
Ming-Ju Tsai, Jyun-Rong Wang, Shinn-Jang Hoe, Li-Sun Shu, Wen-Lin Huang, Shinn-Ying Ho
Article
Immunology
Yao-Feng Hu, Shinn-Ying Ho
IMMUNOLOGIC RESEARCH
(2020)
Article
Oncology
Lovely Raghav, Ya-Hsuan Chang, Yi-Chiung Hsu, Yu-Cheng Li, Chih-Yi Chen, Tsung-Ying Yang, Kun-Chieh Chen, Kuo-Hsuan Hsu, Jeng-Sen Tseng, Cheng-Yen Chuang, Mei-Hsuan Lee, Chih-Liang Wang, Huei-Wen Chen, Sung-Liang Yu, Sheng-Fang Su, Shin-Sheng Yuan, Jeremy J. W. Chen, Shinn-Ying Ho, Ker-Chau Li, Pan-Chyr Yang, Gee-Chen Chang, Hsuan-Yu Chen
Article
Multidisciplinary Sciences
Srinivasulu Yerukala Sathipati, Shinn-Ying Ho
SCIENTIFIC REPORTS
(2020)
Article
Oncology
Yao-Kuang Wang, Hao-Yi Syu, Yi-Hsun Chen, Chen-Shuan Chung, Yu Sheng Tseng, Shinn-Ying Ho, Chien-Wei Huang, I-Chen Wu, Hsiang-Chen Wang
Summary: The study developed a single-shot multibox detector using a convolutional neural network to diagnose esophageal neoplasms and evaluated its diagnostic accuracy, showing great potential of AI systems in identifying esophageal neoplasms and differentiating histological grades.
Article
Biochemical Research Methods
Srinivasulu Yerukala Sathipati, Shinn-Ying Ho
Summary: This research proposes an optimization method, COVID-Pred, using a support vector machine to classify coronaviruses based on physicochemical properties. It achieved high accuracy in cross-validation and test results.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Oncology
I-Cheng Lee, Jo-Yu Huang, Ting-Chun Chen, Chia-Heng Yen, Nai-Chi Chiu, Hsuen-En Hwang, Jia-Guan Huang, Chien-An Liu, Gar-Yang Chau, Rheun-Chuan Lee, Yi-Ping Hung, Yee Chao, Shinn-Ying Ho, Yi-Hsiang Huang
Summary: The evolutionary learning-derived prediction models using both clinical and radiomic features significantly improved accuracy in predicting early recurrence of HCC after surgical resection, surpassing other well-known machine learning-derived models.
Article
Genetics & Heredity
Yenching Lin, Srinivasulu Yerukala Sathipati, Shinn-Ying Ho
Summary: This research aims to predict the risk genes of ASD by identifying the temporospatial regions of brain structures and exploring the specificity of ASD gene expression. The study achieved a high accuracy in distinguishing the risk genes of ASD and non-ASD genes, providing valuable insights into the genetic factors specific to different brain regions in ASD patients.
FRONTIERS IN GENETICS
(2021)
Article
Pharmacology & Pharmacy
Min-Ying Lin, Hsin-Hua Hsieh, Jyh-Cheng Chen, Chuan-Lin Chen, Nin-Chu Sheu, Wen-Sheng Huang, Shinn-Ying Ho, Ting-Wen Chen, Yi-Jang Lee, Chun-Yi Wu
Summary: Lu-1(77)-DTPA-pAuNS can accumulate in head and neck squamous cell carcinoma tumors and provide therapeutic efficacy, with lower radiation absorbed dose to the tumor compared to Lu-177-DTPA. The combination of Lu-177-DTPA-pAuNS with photothermal therapy shows enhanced tumor-suppressive effects, indicating potential for use in brachytherapy for HNSCC.
Article
Multidisciplinary Sciences
Srinivasulu Yerukala Sathipati, Sanjay K. Shukla, Shinn-Ying Ho
Summary: This study proposes a spike protein predictor SPIKES, incorporating with a genetic algorithm, to determine the biochemical properties of spike proteins and their specificity to human hosts. The study identifies compositional differences at the amino acid sequence level between human and diverse animal coronaviruses, which may provide insights into the development and transmission of SARS-CoV-2 in humans and other species.
Article
Multidisciplinary Sciences
Srinivasulu Yerukala Sathipati, Ming-Ju Tsai, Sanjay K. Shukla, Shinn-Ying Ho, Yi Liu, Afshin Beheshti
Summary: This study successfully identified a miRNA signature and developed a survival estimation method for patients with bladder urothelial carcinoma (BLC). The miRNA signature can be used to estimate survival and also includes potential biomarkers for diagnosis and prognosis of BLC. This finding is important for understanding BLC and developing miRNA-targeted therapies.
SCIENTIFIC REPORTS
(2022)
Article
Biochemical Research Methods
Srinivasulu Yerukala Sathipati, Ming-Ju Tsai, Tonia Carter, Sanjay K. Shukla, Shinn-Yin Ho
Summary: We present a protocol for identifying physicochemical properties using amino acid sequences of SARS-CoV-2 spike (S) proteins. Our approach, named SPIKES, incorporates a bi-objective combinatorial genetic algorithm to determine host species specificity. The protocol covers data collection, preprocessing, methodology, and analysis of S protein amino acid sequences.
Article
Cell Biology
Srinivasulu Yerukala Sathipati, Shinn-Ying Ho
Summary: The study proposed a novel method using support vector regression and genetic algorithm to identify a miRNA signature associated with survival in ovarian cancer patients. The identified miRNAs were significantly associated with patient survival and enriched in fatty acid biosynthesis and metabolism pathways. The miRNA signature could potentially benefit therapeutic decision making for ovarian cancer management.