High-risk human papillomavirus seems not involved in DES-related and of limited importance in nonDES related clear-cell carcinoma of the cervix

2011 ◽  
Vol 122 (2) ◽  
pp. 297-302 ◽  
Author(s):  
Mariëlle Kocken ◽  
Astrid Baalbergen ◽  
Peter J.F. Snijders ◽  
Johan Bulten ◽  
Wim G.V. Quint ◽  
...  
2021 ◽  
Vol 11 ◽  
Author(s):  
Zhuolun Sun ◽  
Changying Jing ◽  
Xudong Guo ◽  
Mingxiao Zhang ◽  
Feng Kong ◽  
...  

Kidney renal clear cell carcinoma (KIRC) has long been identified as a highly immune-infiltrated tumor. However, the underlying role of pyroptosis in the tumor microenvironment (TME) of KIRC remains poorly described. Herein, we systematically analyzed the prognostic value, role in the TME, response to ICIs, and drug sensitivity of pyroptosis-related genes (PRGs) in KIRC patients based on The Cancer Genome Atlas (TCGA) database. Cluster 2, by consensus clustering for 24 PRGs, presented a poor prognosis, likely because malignancy-related hallmarks were remarkably enriched. Additionally, we constructed a prognostic prediction model that discriminated well between high- and low-risk patients and was further confirmed in external E-MTAB-1980 cohort and HSP cohort. By further analyzing the TME based on the risk model, higher immune cell infiltration and lower tumor purity were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher ICI expression, indicating that these patients may be more prone to profit from ICIs. The sensitivity to anticancer drugs that correlated with model-related genes was also identified. Collectively, the pyroptosis-related prognosis risk model may improve prognostic information and provide directions for current research investigations on immunotherapeutic strategies for KIRC patients.


2018 ◽  
Vol 28 (9) ◽  
pp. 1812-1820 ◽  
Author(s):  
Menghan Zhu ◽  
Nan Jia ◽  
Yanyan Nie ◽  
Jun Chen ◽  
Yahui Jiang ◽  
...  

ObjectiveHigh-risk endometrial cancers (ECs), including high-grade EC, serous carcinoma (SC), clear cell carcinoma, and carcinosarcoma, account for 50% of deaths due to ECs. Therapies for these cancers are limited, and patient-derived tumor xenograft (PDTX) models are useful tools for preclinical drug evaluation, biomarker identification, and personalized medicine strategies. Here, we used and compared 2 methods to establish PDTX models.MethodsFresh tumor tissues collected from 18 primary high-risk EC patients (10 high-grade ECs, 6 SCs, 1 clear cell carcinoma, and 1 carcinosarcoma) were engrafted subcutaneously and in the subrenal capsule in NOD/SCID for establishment and Balb/c-nu/nu mice for expansion. Histology and cytokeratin, estrogen receptor, progesterone receptor, and P53 expression were evaluated to assess the similarity of primary tumors and different generations of PDTX tumors. Whole-exome sequencing (WES) and RNA sequencing were used in 2 high-grade EC models to verify whether the genetic mutation profiles and gene expression were similar between primary and PDTX tumors.ResultsThe total tumor engraftment rate was 77.8% (14/18) regardless of the engraft method. The tumor engraftment rate was increased in subrenal capsule models compared with subcutaneous models (62.5% vs 50%, P = 0.464). The time to tumor formation varied significantly from 2 to 11 weeks. After subrenal capsular grafting, grafted tumors could be successfully transplanted to subcutaneous sites. We observed good similarity between primary tumors and corresponding different passages of xenografts.ConclusionsThe combination of 2 engrafting methods increases the tumor engraftment rate. The high tumor engraftment rate ensures the establishment of a high-risk EC biobank, which is a powerful resource for performing preclinical drug-sensitivity tests and identifying biomarkers for response or resistance.


2021 ◽  
Vol 12 ◽  
Author(s):  
Junwan Lu ◽  
Changrui Qian ◽  
Yongan Ji ◽  
Qiyu Bao ◽  
Bin Lu

Bromodomain (BRD) proteins exhibit a variety of activities, such as histone modification, transcription factor recruitment, chromatin remodeling, and mediator or enhancer complex assembly, that affect transcription initiation and elongation. These proteins also participate in epigenetic regulation. Although specific epigenetic regulation plays an important role in the occurrence and development of cancer, the characteristics of the BRD family in renal clear cell carcinoma (KIRC) have not been determined. In this study, we investigated the expression of BRD family genes in KIRC at the transcriptome level and examined the relationship of the expression of these genes with patient overall survival. mRNA levels of tumor tissues and adjacent tissues were extracted from The Cancer Genome Atlas (TCGA) database. Seven BRD genes (KAT2A, KAT2B, SP140, BRD9, BRPF3, SMARCA2, and EP300) were searched by using LASSO Cox regression and the model with prognostic risk integration. The patients were divided into two groups: high risk and low risk. The combined analysis of these seven BRD genes showed a significant association with the high-risk groups and lower overall survival (OS). This analysis demonstrated that total survival could be predicted well in the low-risk group according to the time-dependent receiver operating characteristic (ROC) curve. The prognosis was determined to be consistent with that obtained using an independent dataset from TCGA. The relevant biological functions were identified using Gene Set Enrichment Analysis (GSEA). In summary, this study provides an optimized survival prediction model and promising data resources for further research investigating the role of the expression of BRD genes in KIRC.


2022 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Simona Stolnicu ◽  
Georgia Karpathiou ◽  
Esther Guerra ◽  
Claudia Mateoiu ◽  
Armando Reques ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wenkai Han ◽  
Xiaoyan Xu ◽  
Kai Che ◽  
Guofeng Ma ◽  
Danxia Li ◽  
...  

Background. Autophagy plays an essential role in tumorigenesis. At present, due to the unclear role of autophagy in renal clear cell carcinoma, we studied the potential value of autophagy-related genes (ARGs) in renal clear cell carcinoma (ccRCC). Methods. We obtained all ccRCC data from The Cancer Genome Atlas (TCGA). We extracted the expression data of ARGs for difference analysis and carried out biological function analysis on the different results. The autophagy risk model was constructed. The 5-year survival rate was assessed using the model, and the predictive power of the model was evaluated from multiple perspectives. Cox regression analysis was use to assess whether the model could be an independent prognostic factor. Finally, the correlation between the model and clinical indicators is analyzed. Results. The patients were divided into the high-risk group and low-risk group according to the median of autophagy risk score, and the results showed that the prognosis of the low-risk group was better than that of a high-risk group. The validation results of external data sets show that our model has good predictive value for ccRCC patients. The model can be an independent prognostic factor. Finally, the results show that our model has a stable predictive ability. Conclusion. The autophagy gene model we constructed can be used as an excellent prognostic indicator for ccRCC. Our study provides the possibility of individualized and precise treatment for ccRCC patients.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pankaj Ahluwalia ◽  
Meenakshi Ahluwalia ◽  
Ashis K. Mondal ◽  
Nikhil Sahajpal ◽  
Vamsi Kota ◽  
...  

AbstractComplex interactions in tumor microenvironment between ECM (extra-cellular matrix) and cancer cell plays a central role in the generation of tumor supportive microenvironment. In this study, the expression of ECM-related genes was explored for prognostic and immunological implication in clear cell renal clear cell carcinoma (ccRCC). Out of 964 ECM genes, higher expression (z-score > 2) of 35 genes showed significant association with overall survival (OS), progression-free survival (PFS) and disease-specific survival (DSS). On comparison to normal tissue, 12 genes (NUDT1, SIGLEC1, LRP1, LOXL2, SERPINE1, PLOD3, ZP3, RARRES2, TGM2, COL3A1, ANXA4, and POSTN) showed elevated expression in kidney tumor (n = 523) compared to normal (n = 100). Further, Cox proportional hazard model was utilized to develop 12 genes ECM signature that showed significant association with overall survival in TCGA dataset (HR = 2.45; 95% CI [1.78–3.38]; p < 0.01). This gene signature was further validated in 3 independent datasets from GEO database. Kaplan–Meier log-rank test significantly associated patients with elevated expression of this gene signature with a higher risk of mortality. Further, differential gene expression analysis using DESeq2 and principal component analysis (PCA) identified genes with the highest fold change forming distinct clusters between ECM-rich high-risk and ECM-poor low-risk patients. Geneset enrichment analysis (GSEA) identified significant perturbations in homeostatic kidney functions in the high-risk group. Further, higher infiltration of immunosuppressive T-reg and M2 macrophages was observed in high-risk group patients. The present study has identified a prognostic signature with associated tumor-promoting immune niche with clinical utility in ccRCC. Further exploration of ECM dynamics and validation of this gene signature can assist in design and application of novel therapeutic approaches.


2020 ◽  
Author(s):  
Zhuolun Sun ◽  
Changying Jing ◽  
Chutian Xiao ◽  
Mingxiao Zhang ◽  
Zhenqing Wang ◽  
...  

Abstract Background: Kidney renal clear cell carcinoma (KIRC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of KIRC patients.Methods:RNA-sequencing data and clinicopathological data of KIRC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between KIRC and normal tissues were identified using ‘limma’ package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature.Results: A total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of KIRC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for KIRC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the KIRC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the KIRC patients.Conclusion: We constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for clinician to guide clinical decision-making and outcomes research.


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