Thyroid Adenocarcinoma: Correlation between gene mutation status and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.

Summary

Testing the association between mutation status of 19 genes and 5 clinical features across 201 patients, 3 significant findings detected with Q value < 0.25.

- BRAF mutation correlated to 'HISTOLOGICAL.TYPE'.

- HRAS mutation correlated to 'HISTOLOGICAL.TYPE'.

- NRAS mutation correlated to 'HISTOLOGICAL.TYPE'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 19 genes and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.

|  | Clinical Features | AGE | GENDER | HISTOLOGICAL TYPE | RADIATIONS RADIATION REGIMENINDICATION | NEOADJUVANT THERAPY
| nMutated (%) | nWild-Type | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test
BRAF | 115 (57%) | 86 | 0.445 (1.00) | 0.517 (1.00) | 4.71e-18 (4.47e-16) | 0.0144 (1.00) | 0.577 (1.00)
HRAS | 10 (5%) | 191 | 0.732 (1.00) | 0.721 (1.00) | 0.000153 (0.0142) | 1 (1.00) | 1 (1.00)
NRAS | 16 (8%) | 185 | 0.818 (1.00) | 0.132 (1.00) | 9.52e-06 (0.000895) | 0.604 (1.00) | 1 (1.00)
POLDIP2 | 5 (2%) | 196 | 0.917 (1.00) | 0.11 (1.00) | 0.604 (1.00) | 0.267 (1.00) | 1 (1.00)
EMG1 | 4 (2%) | 197 | 0.686 (1.00) | 0.574 (1.00) | 1 (1.00) | 1 (1.00) | 1 (1.00)
EIF1AX | 3 (1%) | 198 | 0.432 (1.00) | 0.165 (1.00) | 0.0366 (1.00) | 1 (1.00) | 1 (1.00)
ZNF845 | 3 (1%) | 198 | 0.0965 (1.00) | 0.57 (1.00) | 0.559 (1.00) | 1 (1.00) | 1 (1.00)
CCDC15 | 5 (2%) | 196 | 0.139 (1.00) | 1 (1.00) | 0.121 (1.00) | 1 (1.00) | 1 (1.00)
TG | 9 (4%) | 192 | 0.359 (1.00) | 1 (1.00) | 0.0109 (0.999) | 1 (1.00) | 0.129 (1.00)
CHEK2 | 3 (1%) | 198 | 0.53 (1.00) | 1 (1.00) | 0.0985 (1.00) | 1 (1.00) | 1 (1.00)
PPM1D | 5 (2%) | 196 | 0.545 (1.00) | 1 (1.00) | 0.842 (1.00) | 1 (1.00) | 1 (1.00)
ZNF799 | 3 (1%) | 198 | 0.946 (1.00) | 1 (1.00) | 0.559 (1.00) | 1 (1.00) | 1 (1.00)
SLC26A11 | 3 (1%) | 198 | 0.392 (1.00) | 0.165 (1.00) | 0.723 (1.00) | 1 (1.00) | 1 (1.00)
KRAS | 3 (1%) | 198 | 0.888 (1.00) | 0.57 (1.00) | 0.0985 (1.00) | 1 (1.00) | 1 (1.00)
ARID1B | 5 (2%) | 196 | 0.52 (1.00) | 1 (1.00) | 0.219 (1.00) | 1 (1.00) | 1 (1.00)
COL5A3 | 4 (2%) | 197 | 0.666 (1.00) | 0.574 (1.00) | 0.289 (1.00) | 1 (1.00) | 1 (1.00)
DNMT3A | 4 (2%) | 197 | 0.665 (1.00) | 1 (1.00) | 0.626 (1.00) | 1 (1.00) | 1 (1.00)
ARFGEF2 | 4 (2%) | 197 | 0.0446 (1.00) | 1 (1.00) | 0.626 (1.00) | 1 (1.00) | 1 (1.00)
ZFHX3 | 4 (2%) | 197 | 0.71 (1.00) | 0.574 (1.00) | 0.289 (1.00) | 0.22 (1.00) | 0.0588 (1.00)

'BRAF MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 4.71e-18 (Fisher's exact test), Q value = 4.5e-16

Table S1. Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients | OTHER | THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
--- | --- | --- | --- | ---
ALL | 8 | 108 | 64 | 21
BRAF MUTATED | 1 | 84 | 11 | 19
BRAF WILD-TYPE | 7 | 24 | 53 | 2

Figure S1. Get High-res Image Gene #1: 'BRAF MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

'HRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000153 (Fisher's exact test), Q value = 0.014

Table S2. Gene #2: 'HRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients | OTHER | THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
--- | --- | --- | --- | ---
ALL | 8 | 108 | 64 | 21
HRAS MUTATED | 1 | 0 | 9 | 0
HRAS WILD-TYPE | 7 | 108 | 55 | 21

Figure S2. Get High-res Image Gene #2: 'HRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

'NRAS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 9.52e-06 (Fisher's exact test), Q value = 0.00089

Table S3. Gene #3: 'NRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients | OTHER | THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL | THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED) | THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)
--- | --- | --- | --- | ---
ALL | 8 | 108 | 64 | 21
NRAS MUTATED | 1 | 1 | 14 | 0
NRAS WILD-TYPE | 7 | 107 | 50 | 21

Figure S3. Get High-res Image Gene #3: 'NRAS MUTATION STATUS' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Methods & Data
Input

- Mutation data file = THCA.mutsig.cluster.txt

- Clinical data file = THCA.clin.merged.picked.txt

- Number of patients = 201

- Number of significantly mutated genes = 19

- Number of selected clinical features = 5

- Exclude genes that fewer than K tumors have mutations, K = 3

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' function in R

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[2] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[3] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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