scholarly journals Molecular Insights into the Classification of Luminal Breast Cancers: The Genomic Heterogeneity of Progesterone-Negative Tumors

2019 ◽  
Vol 20 (3) ◽  
pp. 510 ◽  
Author(s):  
Gianluca Lopez ◽  
Jole Costanza ◽  
Matteo Colleoni ◽  
Laura Fontana ◽  
Stefano Ferrero ◽  
...  
Keyword(s):  
Cancer Genomics ◽  
Molecular Taxonomy ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Breast Cancers ◽  
Cancer Genes ◽  
Kaplan Meier ◽  
Er Positive ◽  
Cancer Genome Atlas ◽  
Student’S T

Estrogen receptor (ER)-positive progesterone receptor (PR)-negative breast cancers are infrequent but clinically challenging. Despite the volume of genomic data available on these tumors, their biology remains poorly understood. Here, we aimed to identify clinically relevant subclasses of ER+/PR− breast cancers based on their mutational landscape. The Cancer Genomics Data Server was interrogated for mutational and clinical data of all ER+ breast cancers with information on PR status from The Cancer Genome Atlas (TCGA), Memorial Sloan Kettering (MSK), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) projects. Clustering analysis was performed using gplots, ggplot2, and ComplexHeatmap packages. Comparisons between groups were performed using the Student’s t-test and the test of Equal or Given Proportions. Survival curves were built according to the Kaplan–Meier method; differences in survival were assessed with the log-rank test. A total of 3570 ER+ breast cancers (PR− n = 959, 27%; PR+ n = 2611, 73%) were analyzed. Mutations in well-known cancer genes such as TP53, GATA3, CDH1, HER2, CDH1, and BRAF were private to or enriched for in PR− tumors. Mutual exclusivity analysis revealed the presence of four molecular clusters with significantly different prognosis on the basis of PIK3CA and TP53 status. ER+/PR− breast cancers are genetically heterogeneous and encompass a variety of distinct entities in terms of prognostic and predictive information.

scholarly journals Genomic, Transcriptomic, Epigenetic, and Immune Profiling of Mucinous Breast Cancer

2019 ◽  
Vol 111 (7) ◽  
pp. 742-746 ◽  
Author(s):  
Bastien Nguyen ◽  
Isabelle Veys ◽  
Sophia Leduc ◽  
Yacine Bareche ◽  
Samira Majjaj ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Genomics ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Architecture ◽  
Microscopic Evaluation ◽  
Er Positive ◽  
Cancer Genome Atlas ◽  
Mucinous Breast Cancer ◽  
Genome Atlas

Abstract Although invasive ductal breast cancer (IDC) represents the most common histological type of breast cancer, minor subtypes exist such as mucinous breast cancer (MuBC). MuBC are distinguished by tumor cells floating in extracellular mucin. MuBC patients are generally older and associated with a favorable prognosis. To unravel the molecular architecture of MuBC, we applied low-pass whole-genome sequencing and microscopic evaluation of stromal tumor infiltrating lymphocytes to 30 MuBC from a retrospective institutional cohort. We further analyzed two independent datasets from the International Cancer Genomics Consortium and The Cancer Genome Atlas. Genomic data (n = 26 MuBC, n = 535 estrogen receptor [ER] positive/HER2-negative IDC), methylation data (n = 28 MuBC, n = 529 ER-positive/HER2-negative IDC), and transcriptomic data (n = 27 MuBC, n = 467 ER-positive/HER2-negative IDC) were analyzed. MuBC was characterized by low tumor infiltrating lymphocyte levels (median = 0.0%, average = 3.4%, 95% confidence interval = 1.9% to 4.9%). Compared with IDC, MuBC had a lower genomic instability (P = .01, two-sided Mann-Whitney U test) and a decreased prevalence of PIK3CA mutations (39.7% in IDC vs 6.7% in MuBC, P = .01 in the International Cancer Genomics Consortium; and 34.8% vs 0.0%, P = .02 in The Cancer Genome Atlas, two-sided Fisher’s exact test). Finally, our report identifies aberrant DNA methylation of MUC2 as a possible cause of extracellular production of mucin in MuBC.

scholarly journals TRIM27 interacts with Iκbα to promote the growth of human renal cancer cells through regulating the NF-κB pathway

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chengwu Xiao ◽  
Wei Zhang ◽  
Meimian Hua ◽  
Huan Chen ◽  
Bin Yang ◽  
...  
Keyword(s):  
Cell Lines ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Mrna Levels ◽  
Loss Of Function ◽  
Protein Levels ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background The tripartite motif (TRIM) family proteins exhibit oncogenic roles in various cancers. The roles of TRIM27, a member of the TRIM super family, in renal cell carcinoma (RCC) remained unexplored. In the current study, we aimed to investigate the clinical impact and roles of TRIM27 in the development of RCC. Methods The mRNA levels of TRIM27 and Kaplan–Meier survival of RCC were analyzed from The Cancer Genome Atlas database. Real-time PCR and Western blotting were used to measure the mRNA and protein levels of TRIM27 both in vivo and in vitro. siRNA and TRIM27 were exogenously overexpressed in RCC cell lines to manipulate TRIM27 expression. Results We discovered that TRIM27 was elevated in RCC patients, and the expression of TRIM27 was closely correlated with poor prognosis. The loss of function and gain of function results illustrated that TRIM27 promotes cell proliferation and inhibits apoptosis in RCC cell lines. Furthermore, TRIM27 expression was positively associated with NF-κB expression in patients with RCC. Blocking the activity of NF-κB attenuated the TRIM27-mediated enhancement of proliferation and inhibition of apoptosis. TRIM27 directly interacted with Iκbα, an inhibitor of NF-κB, to promote its ubiquitination, and the inhibitory effects of TRIM27 on Iκbα led to NF-κB activation. Conclusions Our results suggest that TRIM27 exhibits an oncogenic role in RCC by regulating NF-κB signaling. TRIM27 serves as a specific prognostic indicator for RCC, and strategies targeting the suppression of TRIM27 function may shed light on future therapeutic approaches.

scholarly journals Radiosensitivity index emerges as a potential biomarker for combined radiotherapy and immunotherapy

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yang-Hong Dai ◽  
Ying-Fu Wang ◽  
Po-Chien Shen ◽  
Cheng-Hsiang Lo ◽  
Jen-Fu Yang ◽  
...  
Keyword(s):  
Dna Repair ◽  
Interferon Γ ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Macrophage Polarisation ◽  
Molecular Features ◽  
Kaplan Meier ◽  
M1 Macrophage ◽  
Potential Biomarker ◽  
Cancer Genome Atlas

AbstractIn the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.

scholarly journals MEX3A and MEX3B as Potential Prognostic Indicators in Stomach Adenocarcinoma

2021 ◽  
Author(s):  
Junwei Zou ◽  
Yong Huang ◽  
Zhaoying Wu ◽  
Hao Xie ◽  
Rongsheng Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Rna Splicing ◽  
Rna Binding ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Tumor Pathogenesis ◽  
Kaplan Meier Plotter

Abstract Stomach adenocarcinoma(STAD) is one of the deadliest cancers in the world. The expression levels of family members of mex-3 RNA that bound MEX3A (member A) and MEX3B (member B) were high expressions in different cancers and interconnected to deficient prognosis. The present research assessed the potential regarding the expression of MEX3A and MEX3B in STAD by analysing the facts of STAD (viz. The Cancer Genome Atlas). TCGA, MEX3A and MEX3B in the cancers were analyzed using TIMER2.0, Kaplan Meier Plotter, and cBioPortal. The data was visualized using version 4.0.3 of R. We found MEX3A and MEX3B had various expressions regarding major cancer and relevant common tissues. Especially, high expression of MEX3A and MEX3B had relationships with the OS (namely overall survival) with deficiency and RFS (viz. relapse-free survival) concerning STAD. The expressions of MEX3B had correlations to T stage with P being 0.012 and to the race with P being 0.049. MEX3B was highly expressed in T3 and T4 stages, and was highly expressed in the white race. MEX3A mutation had a better survival without diseases, with P being 0.0205. However, the situation was different with non-overall survival, with P being 0.194, in comparison with the patients who did not have MEX3A change. MEX3A and MEX3B on tumor pathogenesis might be related to "RNA splicing" and "spliceosomal complex" and "single-stranded RNA binding". We further investigated the association between MEX3A and MEX3B and immune cells. The mast cells of the most connections to MEX3A (R=-0.300, P<0.001) and the NK cells were positively correlation with MEX3B (R=0.590, P<0.001). It showed that they might be potential prognostic molecular biomarkers in patients with STAD.

scholarly journals A Statistical Framework for Evolutionary Analysis of Recurrent Somatic Mutations in Cancers

2020 ◽  
Author(s):  
Xun Gu
Keyword(s):  
Somatic Mutations ◽  
Cancer Genomics ◽  
Computational Procedure ◽  
The Cancer Genome Atlas ◽  
Component Model ◽  
Evolutionary Analysis ◽  
Cancer Genes ◽  
Component Mixture ◽  
Two Component ◽  
Empirical Bayesian Method

AbstractCurrent cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored, faciltating enormous high throuput analyses to explore the underlying mechanisms that may contribute to malignant initiation or progression. In the context of over-dominant passenger mutations (unrelated to cancers), the challenge is to identify somatic mutations that are cancer-driving. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model that enables to accomplish the following analyses. (i) We formulated a quasi-likelihood approach to test whether the two-component model is significantly better than a single-component model, which can be used for new cancer gene predicting. (ii) We implemented an empirical Bayesian method to calculate the posterior probabilities of a site to be cancer-driving for all sites of a gene, which can be used for new driving site predicting. (iii) We developed a computational procedure to calculate the somatic selection intensity at driver sites and passenger sites, respectively, as well as site-specific profiles for all sites. Using these newly-developed methods, we comprehensively analyzed 294 known cancer genes based on The Cancer Genome Atlas (TCGA) database.

scholarly journals CYSTM1: A Novel Biomarker for Hepatocellular Carcinoma Prognosis

2021 ◽  
Author(s):  
Jun Du ◽  
Jinguo Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Early Stage ◽  
Human Tumor ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Abstract Background: The expression and molecular mechanism of cysteine rich transmembrane module containing 1 (CYSTM1) in human tumor cells remains unclear. The aim of this study was to determine whether CYSTM1 could be used as a potential prognostic biomarker for hepatocellular carcinoma (HCC).Methods: We first demonstrated the relationship between CYSTM1 expression and HCC in various public databases. Secondly, Kaplan–Meier analysis and Cox proportional hazard regression model were performed to evaluate the relationship between the expression of CYSTM1 and the survival of HCC patients which data was downloaded in the cancer genome atlas (TCGA) database. Finally, we used the expression data of CYSTM1 in TCGA database to predict CYSTM1-related signaling pathways through bioinformatics analysis.Results: The expression level of CYSTM1 in HCC tissues was significantly correlated with T stage (p = 0.039). In addition, Kaplan–Meier analysis showed that the expression of CYSTM1 was significantly associated with poor prognosis in patients with early-stage HCC (p = 0.003). Multivariate analysis indicated that CYSTM1 is a potential predictor of poor prognosis in HCC patients (p = 0.036). The results of biosynthesis analysis demonstrated that the data set of CYSTM1 high expression was mainly enriched in neurodegeneration and oxidative phosphorylation pathways.Conclusion: CYSTM1 is an effective biomarker for the prognosis of patients with early-stage HCC and may play a key role in the occurrence and progression of HCC.

scholarly journals Molecular basis of distinct oestrogen responses in endometrial and breast cancer

2019 ◽  
Vol 26 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Eva Baxter ◽  
Karolina Windloch ◽  
Greg Kelly ◽  
Jason S Lee ◽  
Frank Gannon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcriptional Activation ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Oestrogen Receptor Alpha ◽  
Limited Success ◽  
Cancer Genome Atlas ◽  
Using Data ◽  
Oestrogen Signalling

Up to 80% of endometrial and breast cancers express oestrogen receptor alpha (ERα). Unlike breast cancer, anti-oestrogen therapy has had limited success in endometrial cancer, raising the possibility that oestrogen has different effects in both cancers. We investigated the role of oestrogen in endometrial and breast cancers using data from The Cancer Genome Atlas (TCGA) in conjunction with cell line studies. Using phosphorylation of ERα (ERα-pSer118) as a marker of transcriptional activation of ERα in TCGA datasets, we found that genes associated with ERα-pSer118 were predominantly unique between tumour types and have distinct regulators. We present data on the alternative and novel roles played by SMAD3, CREB-pSer133 and particularly XBP1 in oestrogen signalling in endometrial and breast cancer.

scholarly journals Overexpression of CLEC18B Associates With the Proliferation, Migration, and Prognosis of Glioblastoma

ASN NEURO ◽  
2018 ◽  
Vol 10 ◽  
pp. 175909141878194 ◽  
Author(s):  
Rui-Ming Guo ◽  
Cheng-Bin Zhao ◽  
Peng Li ◽  
Liang Zhang ◽  
Su-Hua Zang ◽  
...  
Keyword(s):  
Inverse Correlation ◽  
The Cancer Genome Atlas ◽  
Cell Counting ◽  
Migration And Invasion ◽  
Loss Of Function ◽  
Lectin Domain ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Interfering Rna

C-type lectin domain family 18 member B (CLEC18B), encoding a superfamily of CLEC, has been found to be expressed in some of cancer cells, which possibly indicates it associated with cancer. However, the defined functional characterizations of CLEC18B in glioblastoma multiforme (GBM) progression still remain unclear. To this end, clinical relevance of CLEC18B expression with GBM patients’ prognosis was analyzed both in The Cancer Genome Atlas dataset of 174 tissues and 40 GBM tumor tissues collected from our hospital by using the Kaplan–Meier survival and the Cox proportional hazard model. The role of CLEC18B in GBM was determined by loss-of-function assay using small interfering RNA approach in vitro. Functional and signaling analyses were also performed to understand how CLEC18B facilitated the aggressiveness of GBM at molecular and cellular levels using Cell Counting Kit-8 assay, wound-healing, transwell, and Western blot analyses. Results from our analyses showed that CLEC18B was markedly elevated in both GBM tissues and cells, and exhibited strong inverse correlation with overall survival in GBM patients. Moreover, CLEC18B was identified as an independent predictor of patient survival. Functionally, knockdown of CLEC18B inhibited the growth, migration, and invasion of GBM cells. Mechanistic studies revealed that silencing of CLEC18B resulted in downregulation of Wnt/β-catenin signaling activity. Collectively, our findings provide clinical, molecular, and cellular evidence of CLEC18B as a promising prognostic biomarker and therapeutic target for GBM.

scholarly journals OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1523
Author(s):  
Huimin Li ◽  
Longxiang Xie ◽  
Qiang Wang ◽  
Yifang Dang ◽  
Xiaoxiao Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Analysis Data ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
Rank Test ◽  
Web Tool ◽  
Kaplan Meier ◽  
Cox Analysis

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan–Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

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