Analysis Overview
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
04 October 2018 | None
Maintainer Information
Maintained by Broad Institute GDAC (Broad Institute of MIT & Harvard)
Overview
Introduction

This is an overview of Uterine Corpus Endometrioid Carcinoma analysis pipelines from FireCloud run "04 October 2018".

Summary

Note: These results are offered to the community as an additional reference point, enabling a wide range of cancer biologists, clinical investigators, and genome and computational scientists to easily incorporate TCGA into the backdrop of ongoing research. While every effort is made to ensure that FireCloud input data and algorithms are of the highest possible quality, these analyses have not been reviewed by domain experts.

Results

- Sequence and Copy Number Analyses

- Analysis of mutagenesis by APOBEC cytidine deaminases (P-MACD).
  View Report | There are 100 tumor samples in this analysis. The Benjamini-Hochberg-corrected p-value for enrichment of the APOBEC mutation signature in 0 samples is <=0.05. Out of these, 0 have enrichment values >2, which implies that in such samples at least 50% of APOBEC signature mutations have been in fact made by APOBEC enzyme(s).

- Mutation Analysis (MutSig 2CV v3.1)
  View Report |

- Mutation Signature Analysis
  View Report | Our analysis idenfied 3 solution(s) of mutational signatures across 100 samples by BayesNMF method.

- SNP6 Copy number analysis (GISTIC2)
  View Report | There were 100 tumor samples used in this analysis: 41 significant arm-level results, 48 significant focal amplifications, and 63 significant focal deletions were found.

- Correlations to Clinical Parameters

- Correlation between aggregated molecular cancer subtypes and selected clinical features
  View Report | Testing the association between subtypes identified by 3 different clustering approaches and 17 clinical features across 100 patients, 3 significant findings detected with P value < 0.05 and Q value < 0.25.

- Correlation between APOBEC signature variables and clinical features
  View Report | Testing the association between 3 variables and 17 clinical features across 100 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one variables.

- Correlation between copy number variation genes (focal events) and selected clinical features
  View Report | Testing the association between copy number variation 110 focal events and 17 clinical features across 100 patients, 98 significant findings detected with Q value < 0.25.

- Correlation between copy number variations of arm-level result and selected clinical features
  View Report | Testing the association between copy number variation 72 arm-level events and 17 clinical features across 100 patients, 76 significant findings detected with Q value < 0.25.

- Correlation between gene mutation status and selected clinical features
  View Report | Testing the association between mutation status of 388 genes and 17 clinical features across 100 patients, no significant finding detected with Q value < 0.25.

- Correlation between mRNAseq expression and clinical features
  View Report | Testing the association between 18424 genes and 17 clinical features across 100 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

- Correlation between mutation rate and clinical features
  View Report | Testing the association between 2 variables and 18 clinical features across 100 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 1 clinical feature related to at least one variables.

- Clustering Analyses

- Clustering of Protein-coding gene expression: consensus hierarchical
  View Report | Median absolute deviation (MAD) was used to select 2500 most variable genes. Consensus ward linkage hierarchical clustering of 100 samples and 2500 genes identified 5 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Other Analyses

- Aggregate_Analysis_Features
  View Report | 99 samples and 1161 features are included in this feature table. The figures below show which genomic pair events are co-occurring and which are mutually-exclusive.

- Methylation__EPIC_Clustering_CNMF
  View Report | The most robust consensus NMF clustering of 96 samples using the 6355 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

- Methylation__EPIC_Clustering_Consensus_Plus
  View Report | Median absolute deviation (MAD) was used to select 2500 most variable genes. Consensus ward linkage hierarchical clustering of 96 samples and 2500 genes identified 7 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Other Correlation Analyses

- Correlation between copy number variation genes (focal events) and molecular subtypes
  View Report | Testing the association between copy number variation 110 focal events and 3 molecular subtypes across 100 patients, 97 significant findings detected with P value < 0.05 and Q value < 0.25.

- Correlation between copy number variations of arm-level result and molecular subtypes
  View Report | Testing the association between copy number variation 72 arm-level events and 3 molecular subtypes across 100 patients, 67 significant findings detected with P value < 0.05 and Q value < 0.25.

- Correlation between gene mutation status and molecular subtypes
  View Report | Testing the association between mutation status of 388 genes and 3 molecular subtypes across 100 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.

Methods & Data
Input

- Summary Report Date = Thu Nov 1 13:44:43 2018

- Protection = FALSE

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