1
|
Li M, Mao S, Li L, Wei M. Hypoxia-related LncRNAs signature predicts prognosis and is associated with immune infiltration and progress of head and neck squamous cell carcinoma. Biochem Biophys Rep 2022; 31:101304. [PMID: 35818500 PMCID: PMC9270212 DOI: 10.1016/j.bbrep.2022.101304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/17/2022] [Accepted: 06/26/2022] [Indexed: 12/21/2022] Open
Abstract
Background Disclosing prognostic information is necessary to enable good treatment selection and improve patient outcomes. Previous studies suggest that hypoxia is associated with an adverse prognosis in patients with HNSCC and that long non-coding RNAs (lncRNAs) show functions in hypoxia-associated cancer biology. Nevertheless, the understanding of lncRNAs in hypoxia related HNSCC progression remains confusing. Methods Data were downloaded from TCGA and GEO database. Bioinformatic tools including R packages GEOquery, limma, pheatmap, ggplot2, clusterProfiler, survivalROC and survcomp and LASSO cox analysis were utilized. Si-RNA transfection, CCK8 and real-time quantified PCR were used in functional study. Results GEO data (GSE182734) revealed that lncRNA regulation may be important in hypoxia related response of HNSCC cell lines. Further analysis in TCGA data identified 314 HRLs via coexpression analysis between differentially expressed lncRNAs and hypoxia-related mRNAs. 23 HRLs were selected to build the prognosis predicting model using lasso Cox regression analyses. Our model showed excellent performance in predicting survival outcomes among patients with HNSCC in both the training and validation sets. We also found that the risk scores were related to tumor stage and to tumor immune infiltration. Moreover, LINC01116 were selected as a functional study target. The knockdown of LINC01116 significantly inhibited the proliferation of HNSCC cells and effected the hypoxia induced immune and the NF-κB/AKT signaling. Conclusions Data analysis of large cohorts and functional experimental validation in our study suggest that hypoxia related lncRNAs play an important role in the progression of HNSCC, and its expression model can be used for prognostic prediction. NcRNAs regulations showed significance in hypoxia related response in HNSCC. 314 lncRNAs coexpressed with hypoxia marker genes were identified as HRLs. An effective HRLs prognosis prediction model had been constructed and validated. Immune cells and pathways paly roles in hypoxia related progress of HNSCC. LINC01116 regulates HNSCC through hypoxia related immune and NF-κB/AKT signaling.
Collapse
Affiliation(s)
- Minhan Li
- School of Stomatology, Shandong University, Jinan, Shandong, China
| | - Shaowei Mao
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, China
| | - Lixing Li
- Department of General Surgery, Shanghai Xuhui District Central Hospital, Shanghai, China
| | - Muyun Wei
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, China
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
- Corresponding author. School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, China
| |
Collapse
|
2
|
Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney. DISEASE MARKERS 2022; 2022:4752184. [PMID: 35756490 PMCID: PMC9217527 DOI: 10.1155/2022/4752184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 05/10/2022] [Accepted: 05/25/2022] [Indexed: 11/17/2022]
Abstract
Background Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis. Methods We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis. Results A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p < 0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048-1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043-1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients. Conclusions The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.
Collapse
|
3
|
Trevisani F, Floris M, Vago R, Minnei R, Cinque A. Long Non-Coding RNAs as Novel Biomarkers in the Clinical Management of Papillary Renal Cell Carcinoma Patients: A Promise or a Pledge? Cells 2022; 11:cells11101658. [PMID: 35626699 PMCID: PMC9139553 DOI: 10.3390/cells11101658] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/12/2022] [Accepted: 05/13/2022] [Indexed: 12/22/2022] Open
Abstract
Papillary renal cell carcinoma (pRCC) represents the second most common subtype of renal cell carcinoma, following clear cell carcinoma and accounting for 10–15% of cases. For around 20 years, pRCCs have been classified according to their mere histopathologic appearance, unsupported by genetic and molecular evidence, with an unmet need for clinically relevant classification. Moreover, patients with non-clear cell renal cell carcinomas have been seldom included in large clinical trials; therefore, the therapeutic landscape is less defined than in the clear cell subtype. However, in the last decades, the evolving comprehension of pRCC molecular features has led to a growing use of target therapy and to better oncological outcomes. Nonetheless, a reliable molecular biomarker able to detect the aggressiveness of pRCC is not yet available in clinical practice. As a result, the pRCC correct prognosis remains cumbersome, and new biomarkers able to stratify patients upon risk of recurrence are strongly needed. Non-coding RNAs (ncRNAs) are functional elements which play critical roles in gene expression, at the epigenetic, transcriptional, and post-transcriptional levels. In the last decade, ncRNAs have gained importance as possible biomarkers for several types of diseases, especially in the cancer universe. In this review, we analyzed the role of long non-coding RNAs (lncRNAs) in the prognosis of pRCC, with a particular focus on their networking. In fact, in the competing endogenous RNA hypothesis, lncRNAs can bind miRNAs, resulting in the modulation of the mRNA levels targeted by the sponged miRNA, leading to additional regulation of the target gene expression and increasing complexity in the biological processes.
Collapse
Affiliation(s)
- Francesco Trevisani
- Urological Research Institute, San Raffaele Scientific Institute, 20132 Milano, Italy;
- Unit of Urology, San Raffaele Scientific Institute, 20132 Milano, Italy
- Biorek s.r.l., San Raffaele Scientific Institute, 20132 Milano, Italy;
- Correspondence:
| | - Matteo Floris
- Nephrology, Dialysis, and Transplantation Division, G. Brotzu Hospital, University of Cagliari, 09134 Cagliari, Italy; (M.F.); (R.M.)
| | - Riccardo Vago
- Urological Research Institute, San Raffaele Scientific Institute, 20132 Milano, Italy;
| | - Roberto Minnei
- Nephrology, Dialysis, and Transplantation Division, G. Brotzu Hospital, University of Cagliari, 09134 Cagliari, Italy; (M.F.); (R.M.)
| | - Alessandra Cinque
- Biorek s.r.l., San Raffaele Scientific Institute, 20132 Milano, Italy;
| |
Collapse
|
4
|
Dang R, Jin M, Nan J, Jiang X, He Z, Su F, Li D. A Novel Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Patients with Papillary Renal Cell Carcinoma. Int J Gen Med 2022; 15:207-222. [PMID: 35023959 PMCID: PMC8747765 DOI: 10.2147/ijgm.s341034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 12/15/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose Papillary renal cell carcinoma (PRCC) is a common renal cell carcinoma. Recent studies have reported that ferroptosis is involved in the occurrence and development of tumors. Long non-coding RNAs can be used as independent biomarkers for the diagnosis and prognosis of a variety of tumors. Methods Gene expression profile and clinical information of patients with PRCC were obtained from The Cancer Genome Atlas (TCGA) database. Lasso penalized Cox regression and univariate Cox regression analysis were utilized for model construction. The Kaplan–Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Immune cell infiltration and immune function were compared between the high-risk and low-risk groups. Chemotherapy sensitivity analysis was also performed. Results We constructed a prognostic signature consisting of 15 ferroptosis-related lncRNAs. The K-M curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the lncRNA signature was 0.930, exhibiting robust prognostic capacity. The high-risk group had a greater degree of immune cell infiltration than the low-risk group. Significant differences in inflammation promotion, parainflammation, and type I IFN response were noted between the low-risk and high-risk groups (p < 0.01). The expression levels of immune checkpoints including CD80, IDO1, and LAG3 were significantly higher in the high-risk group than in the low-risk group (p < 0.05). Chemotherapy sensitivity analysis showed that MNX1-AS1, ZFAS1, MIR4435-2HG, and ADAMTS9-AS1 were significantly correlated with the sensitivity of some chemotherapy drugs (p < 0.05). Conclusion We demonstrated that a ferroptosis-related lncRNA prognostic signature could be a novel biomarker for PRCC.
Collapse
Affiliation(s)
- Ruijie Dang
- Department of Oncology, The First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Meiling Jin
- Department of Nephrology, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China
| | - Jingzhu Nan
- Department of Clinical Laboratory, the First Medical Centre, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Xuege Jiang
- Respiratory Diseases Department, Second Medical Center of PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Zheng He
- Department of Clinical Laboratory, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China
| | - Fang Su
- Aeronautical Physiological Identification Training Laboratory, Air Force Medical Center, PLA, Beijing, 100142, People's Republic of China
| | - Diangeng Li
- Department of Scientific Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China
| |
Collapse
|
5
|
Wei J, Zeng Y, Gao X, Liu T. A novel ferroptosis-related lncRNA signature for prognosis prediction in gastric cancer. BMC Cancer 2021; 21:1221. [PMID: 34774009 PMCID: PMC8590758 DOI: 10.1186/s12885-021-08975-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 11/05/2021] [Indexed: 01/21/2023] Open
Abstract
Background Gastric cancer (GC) is a common malignant cancer with a poor prognosis. Ferroptosis has been shown to play crucial roles in GC development. Long non-coding RNAs (lncRNAs) is also associated with tumor progression in GC. This study aimed to screen the prognostic ferroptosis-related lncRNAs and to construct a prognostic risk model for GC. Methods Ferroptosis-related lncRNAs from The Cancer Genome Atlas (TCGA) GC expression data was downloaded. First, single factor Cox proportional hazard regression analysis was used to select seven prognostic ferroptosis-related lncRNAs from TCGA database. And then, the selected lncRNAs were further included in the multivariate Cox proportional hazard regression analysis to establish the prognostic model. A nomogram was constructed to predict individual survival probability. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the risk model. Results We constructed a prognostic ferroptosis-related lncRNA signature in this study. Kaplan-Meier curve analysis revealed a significantly better prognosis for the low-risk group than for the high-risk group (P = 2.036e-05). Multivariate Cox proportional risk regression analysis demonstrated that risk score was an independent prognostic factor [hazard ratio (HR) = 1.798, 95% confidence interval (CI) =1.410–2.291, P < 0.001]. A nomogram, receiver operating characteristic curve, and principal component analysis were used to predict individual prognosis. Finally, the expression levels of AP003392.1, AC245041.2, AP001271.1, and BOLA3-AS1 in GC cell lines and normal cell lines were tested by qRT-PCR. Conclusions This risk model was shown to be a novel method for predicting prognosis for GC patients. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08975-2.
Collapse
Affiliation(s)
- Jianming Wei
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China
| | - Ye Zeng
- Department of Laboratory Medicine, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xibo Gao
- Department of Dermatology, Tianjin Children's Hospital, Tianjin, China
| | - Tong Liu
- Department of General Surgery, Tianjin Medical University General Hospital, Tianjin, China.
| |
Collapse
|
6
|
Zhang H, Qin C, Liu HW, Guo X, Gan H. An Effective Hypoxia-Related Long Non-Coding RNAs Assessment Model for Prognosis of Clear Cell Renal Carcinoma. Front Oncol 2021; 11:616722. [PMID: 33692953 PMCID: PMC7937891 DOI: 10.3389/fonc.2021.616722] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/04/2021] [Indexed: 12/11/2022] Open
Abstract
Hypoxia is a significant clinical feature and regulates various tumor processes in clear cell renal carcinoma (ccRCC). Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) are closely associated with the survival outcomes of ccRCC patients and regulates hypoxia-induced tumor processes. Thus, this study aimed to develop a hypoxia-related lncRNA (HRL) prognostic model for predicting the survival outcomes in ccRCC. LncRNAs in ccRCC samples were extracted from The Cancer Genome Atlas database. Hypoxia-related genes were downloaded from the Molecular Signatures Database. A co-expression analysis between differentially expressed lncRNAs and hypoxia-related genes in ccRCC samples was performed to identify HRLs. Univariate and multivariate Cox regression analyses were performed to select nine optimal lncRNAs for developing the HRL model. The prognostic model showed good performance in predicting prognosis among patients with ccRCC, and the validation sets reached consistent results. The model was also found to be related to the clinicopathologic parameters of tumor grade and tumor stage and to tumor immune infiltration. In conclusion, our findings indicate that the hypoxia-lncRNA assessment model may be useful for prognostication in ccRCC cases. Furthermore, the nine HRLs included in the model might be useful targets for investigating the tumorigenesis of ccRCC and designing individualized treatment strategies.
Collapse
Affiliation(s)
- Han Zhang
- Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.,Department of Oncology, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Chuan Qin
- Department of Gastrointestinal Surgery, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Hua Wen Liu
- Department of Oncology, Chongqing University Three Gorges Hospital, Chongqing, China
| | - Xiong Guo
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hua Gan
- Department of Nephrology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| |
Collapse
|