Ying Li

Anhui Medical University

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Sufang Qiu

Fujian Medical University

Daniel C. Link

Washington University in St. Louis

Sridhar Nonavinkere Srivatsan

Washington University in St. Louis

Shondra M. Pruett‐Miller

St. Jude Children's Research Hospital

Esther A. Obeng

St. Jude Children's Research Hospital

Wayne A. Warner

Washington University in St. Louis

Zongwei Huang

Fujian Provincial Cancer Hospital

Dalin He

First Affiliated Hospital of Xi'an Jiaotong University

Yuhao Chen

Shanxi Medical University

Fei Xiao

Central Hospital of Zibo

Cooperative Institutions

Harbin Medical University

Chinese Academy of Sciences

Nanjing Medical University

The University of Texas Health Science Center at San Antonio

Sun Yat-sen University

Shanghai Jiao Tong University

Huazhong University of Science and Technology

Future Earth

Chinese Academy of Medical Sciences & Peking Union Medical College

Central South University

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INTS11 regulates hematopoiesis by promoting PRC2 function

Science Advances (2021)

Peng Zhang Pinpin Sui Shi Chen Ying Guo Ying Li

INTS11, the catalytic subunit of the Integrator (INT) complex, is crucial for the biogenesis of small nuclear RNAs and enhancer RNAs. However, the role of INTS11 in hematopoietic stem and progenitor cell (HSPC) biology is unknown. Here, we report that INTS11 is required for normal hematopoiesis and hematopoietic-specific genetic deletion of Ints11 leads to cell cycle arrest and impairment of fetal and adult HSPCs. We identified a novel INTS11-interacting protein complex, Polycomb repressive complex 2 (PRC2), that maintains HSPC functions. Loss of INTS11 destabilizes the PRC2 complex, decreases the level of histone H3 lysine 27 trimethylation (H3K27me3), and derepresses PRC2 target genes. Reexpression of INTS11 or PRC2 proteins in Ints11-deficient HSPCs restores the levels of PRC2 and H3K27me3 as well as HSPC functions. Collectively, our data demonstrate that INTS11 is an essential regulator of HSPC homeostasis through the INTS11-PRC2 axis.

PRC2

Polycomb-group proteins

10.1126/sciadv.abh1684

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Construction and Validation of an Early Identification Model for Refractory Mycoplasma pneumoniae-Positive Lobar Pneumonia

Journal of Pediatric Infectious Diseases (2024)

Bi Zhou Xiaodong Tang DaWei Mi Ying Li Haiyan Liu

Abstract Objective This study analyzed the relationship between clinical parameters and prognosis in children with Mycoplasma pneumoniae (MP)-positive lobar pneumonia and developed an early identification model. Methods Relevant clinical parameters were collected. Patients were then categorized into two groups based on their length of hospital stay: 116 cases in the refractory group (≥10 days) and 94 cases in the non-refractory group (<10 days). A univariate analysis of variance and binary logistic regression were utilized to develop a predictive model, accompanied by the construction of a nomogram. The model's performance was assessed using receiver operating characteristic (ROC) curves, diagnostic calibration curves, and decision curve analysis (DCA) curves. Furthermore, clinical data from 100 additional cases of MP-positive lobar pneumonia in children treated at other centers were gathered for external validation of the model. Results Binary logistic regression analysis identified four independent risk factors for prolonged disease duration in children with MP-positive lobar pneumonia: erythrocyte sedimentation rate (ESR), globulin, lactate dehydrogenase (LDH), and SF. We constructed a nomogram model based on these risk factors. In the training set, the area under the curve (AUC) was 0.869 (95% CI: 0.822–0.917), with a sensitivity of 68.54% and a specificity of 82.61%. For the test set, the AUC increased to 0.918 (95% CI: 0.866–0.971), demonstrating a sensitivity of 91.67% and a specificity of 78.69%. The DeLong test results indicated that the difference in AUC between the two datasets was not statistically significant (D = − 1.724, p = 0.086). Calibration curve analysis confirmed that the nomogram model exhibited a good fit in both the training set (Hosmer–Lemeshow test, χ2 = 8.120, p = 0.421) and the validation set (Hosmer–Lemeshow test, χ2 = 14.601, p = 0.067). DCA further demonstrated that the model performed significantly across a range of threshold probabilities. Conclusion The nomogram model developed for predicting refractory MP-positive lobar pneumonia in children has significant clinical value and can guide personalized treatment strategies.

Lobar pneumonia

Refractory (planetary science)

10.1055/s-0044-1800820

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Differentially Expressed Trfs in Relapsed & Refractory Diffuse Large B Cell Lymphoma and the Bioinformatic Analysis for Their Potential Clinical Use

Blood (2018)

Qingyuan Qu Yujie Jiang Ying Li Yiqing Cai Ya Zhang

10.1182/blood-2018-99-118134

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Quantitative assessment of target delineation variability for thymic cancers: agreement evaluation of a prospective segmentation challenge

Journal of Radiation Oncology (2015)

Emma B. Holliday Clifton D. Fuller Jayashree Kalpathy‐Cramer Daniel R. Gomez Andreas Rimner

Cohen's kappa

Radiation oncologist

Surgical oncology

10.1007/s13566-015-0230-7

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Supplementary figures and legends from Nonsense-Mediated RNA Decay Is a Unique Vulnerability of Cancer Cells Harboring SF3B1 or U2AF1 Mutations

Abigael Cheruiyot Shan Li Sridhar Nonavinkere Srivatsan Tanzir Ahmed Yuhao Chen

Supplementary figures and legends

Nonsense

Nonsense-Mediated Decay

Vulnerability

10.1158/0008-5472.22428528.v1

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A Qualitative Transcriptional Signature for the Histological Reclassification of Lung Squamous Cell carcinomas and Adenocarcinomas

Research Square (Research Square) (2019)

Xin Li Gengen Shi Qing‐Song Chu Wenbin Jiang Yixin Liu

Abstract Background Targeted therapy for non-small cell lung cancer is histology dependent. However, histological classification by routine pathological assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. Additionally, the effectiveness of immunomarkers is limited by technical inconsistencies of immunostaining and lack of standardization for staining interpretation. Results Using gene expression profiles of pathologically-determined lung squamous cell carcinomas and adenocarcinomas, denoted as pSCC and pADC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to distinguish ADC from SCC. The signature consists of two genes, KRT5 and AGR2, which has the stable REO pattern of KRT5>AGR2 in pSCC and KRT5

Immunostaining

Gene signature

Histology

10.21203/rs.2.9782/v1

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Incorporating structure to predict microRNA targets

Proceedings of the National Academy of Sciences (2005)

Harlan Robins Ying Li Richard W. Padgett

MicroRNAs (miRNAs) are a recently discovered set of regulatory genes that constitute up to an estimated 1% of the total number of genes in animal genomes, including Caenorhabditis elegans , Drosophila , mouse, and humans [Lagos-Quintana, M., Rauhut, R., Lendeckel, W. & Tuschl, T. (2001) Science 294, 853–858; Lai, E. C., Tomancak, P., Williams, R. W. & Rubin, G.M. (2003) Genome Biol. 4, R42; Lau, N. C., Lim, L. P., Weinstein, E. G. & Bartel, D. P. (2001) Science 294, 858–862; Lee, R. C. & Ambros, V. (2001) Science 294, 862-8644; and Lee, R. C., Feinbaum, R. L. & Ambros, V. (1993) Cell 115, 787–798]. In animals, miRNAs regulate genes by attenuating protein translation through imperfect base pair binding to 3′ UTR sequences of target genes. A major challenge in understanding the regulatory role of miRNAs is to accurately predict regulated targets. We have developed an algorithm for predicting targets that does not rely on evolutionary conservation. As one of the features of this algorithm, we incorporate the folded structure of mRNA. By using Drosophila miRNAs as a test case, we have validated our predictions in 10 of 15 genes tested. One of these validated genes is mad as a target for bantam . Furthermore, our computational and experimental data suggest that miRNAs have fewer targets than previously reported.

10.1073/pnas.0500775102

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Characterization of METTL7B to Evaluate TME and Predict Prognosis by Integrative Analysis of Multi-Omics Data in Glioma

Frontiers in Molecular Biosciences (2021)

Xiaochuan Chen Chao Li Ying Li Shihong Wu Wei Liu

Glioma is the most common and aggressive type of primary brain malignant tumor with limited treatment approaches. Methyltransferase-like 7B (METTL7B) is associated with the pathogenesis of several diseases but is rarely studied in glioma. In this study, 1,493 glioma samples (data from our cohort, TCGA, and CGGA) expressing METTL7B were used to explore its prognostic value and mechanism in the immune microenvironment. Results showed that high expression of METTL7B is associated with poor prognosis and abundant immunosuppressive cells. Further, functional enrichment showed that METTL7B is involved in the negative regulation of immunity and carcinogenic signaling pathways. Moreover, a METTL7B-related prognostic signature constructed based on multi-omics showed a good prediction of the overall survival (OS) time of glioma patients. In conclusion, METTL7B is a potential prognostic biomarker. In addition, the prognostic prediction model constructed in this study can be used in clinical setups for the development of novel effective therapeutic strategies for glioma patients and improving overall survival.

Omics

10.3389/fmolb.2021.727481

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Citations (11)

Downregulated Expression of RIPOR3 Correlated with Immune Infiltrates Predicts Poor Prognosis in Oral Tongue Cancer

Medical Science Monitor (2021)

Kai Zhang Junlong Da Xiaoyao Liu Xinpeng Liu Jianqun Wang

BACKGROUND Tongue cancer is the most prevalent of head and neck squamous cell carcinomas, including base of tongue cancer (BOT) and oral squamous cell carcinoma of the mobile tongue (OTSCC). We aimed to investigate the role of RIPOR3 in tumorigenesis and its development as a potential prognostic biomarker for tongue cancer, especially OTSCC. MATERIAL AND METHODS Associations of expression, clinical pathologic features, and overall survival were analyzed by logistic regression, multivariate Cox analysis, and Kaplan-Meier methods. Gene set enrichment analysis (GSEA) and the CIBERSORT algorithm were performed to determine the correlation between RIPOR3 and tumor immune infiltration. cBioPortal was used for methylation and copy number variation (CNV) analysis. The Human Protein Atlas (HPA) and GSE31056 dataset were used for further external validation. RESULTS RIPOR3 expression in OTSCC was significantly associated with various clinicopathological parameters. Kaplan-Meier survival analysis showed that OTSCC with low RIPOR3 expression had a worse prognosis than that with high RIPOR3 expression. Multivariate analysis revealed that lower RIPOR3 expression was an independent prognostic factor for poor prognosis. GSEA and Neighbor Gene Network analysis showed RIPOR3 expression was related with the modulation and function of the immune-related pathway. Methylation level and CNV analysis showed that the downregulated expression of RIPOR3 was significantly related to hypermethylation but not to CNV. Finally, high RIPOR3 expression was validated at the protein level using the HPA database and GSE31056 dataset. CONCLUSIONS These findings suggested that RIPOR3 might serve as a promising prognostic biomarker and is related to the immune cell infiltration of OTSCC.

10.12659/msm.935055

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N⁶-methyladenosine methyltransferase KIAA1429 elevates colorectal cancer aerobic glycolysis via HK2-dependent manner

Figshare (2022)

Ying Li Liang He Yingkai Wang Yan Tan Fan Zhang

Emerging evidence has emphasized the critical roles played by N⁶-methyladenosine RNA (m⁶A) modification in colorectal carcinoma (CRC) initiation and progression. However, the roles and mechanism of m⁶A and KIAA1429 in CRC progression require further clarification. Here, our research aimed to investigate the functions of KIAA1429 in CRC tumorigenesis. Results indicated that KIAA1429 up-regulation closely correlated to the poor prognosis of CRC patients. Bio-functional assays demonstrated that KIAA1429 promoted the aerobic glycolysis, including glucose uptake, lactate production, ATP generation and extracellular acidification rate (ECAR). Mechanistically, KIAA1429 positively up-regulated HK2 level via increasing its mRNA stability by binding the m⁶A site of HK2 mRNA via m⁶A-independent manner. Collectively, our work indicates that KIAA1429 has the potential to promote CRC carcinogenesis by targeting HK2 via m⁶A-independent manner, providing insight into the critical roles of m⁶A in CRC.

Anaerobic glycolysis

10.6084/m9.figshare.19753833

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