Thyroid Adenocarcinoma: Correlation between copy number variation genes and molecular subtypes
(follicular cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv) genes and molecular subtypes.

Summary

Testing the association between copy number variation of 4 peak regions and 6 molecular subtypes across 75 patients, 7 significant findings detected with Q value < 0.25.

  • Del Peak 1(3q13.31) cnvs correlated to 'CN_CNMF'.

  • Del Peak 5(10q23.31) cnvs correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • Del Peak 7(22q11.21) cnvs correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • Del Peak 8(Xq22.3) cnvs correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 4 regions and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 7 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
Del Peak 7(22q11 21) 17 (23%) 58 5.76e-15
(1.38e-13) 		0.00531
(0.117) 		0.0608
(0.851) 		0.00669
(0.134) 		0.0984
(1.00) 		0.669
(1.00)
Del Peak 5(10q23 31) 6 (8%) 69 5.42e-06
(0.000125) 		0.102
(1.00) 		0.00608
(0.128) 		0.351
(1.00) 		0.165
(1.00) 		0.0202
(0.324)
Del Peak 1(3q13 31) 3 (4%) 72 0.00871
(0.165) 		0.0267
(0.4) 		0.113
(1.00) 		0.102
(1.00) 		0.346
(1.00) 		0.175
(1.00)
Del Peak 8(Xq22 3) 3 (4%) 72 0.00871
(0.165) 		0.456
(1.00) 		0.0148
(0.251) 		0.768
(1.00) 		0.613
(1.00) 		0.596
(1.00)
'Del Peak 1(3q13.31) mutation analysis' versus 'CN_CNMF'

P value = 0.00871 (Fisher's exact test), Q value = 0.17

Table S1.  Gene #1: 'Del Peak 1(3q13.31) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 8 19
DEL PEAK 1(3Q13.31) MUTATED 0 2 1
DEL PEAK 1(3Q13.31) WILD-TYPE 48 6 18

Figure S1.  Get High-res Image Gene #1: 'Del Peak 1(3q13.31) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'Del Peak 5(10q23.31) mutation analysis' versus 'CN_CNMF'

P value = 5.42e-06 (Fisher's exact test), Q value = 0.00012

Table S2.  Gene #2: 'Del Peak 5(10q23.31) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 8 19
DEL PEAK 5(10Q23.31) MUTATED 0 5 1
DEL PEAK 5(10Q23.31) WILD-TYPE 48 3 18

Figure S2.  Get High-res Image Gene #2: 'Del Peak 5(10q23.31) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'Del Peak 5(10q23.31) mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.00608 (Fisher's exact test), Q value = 0.13

Table S3.  Gene #2: 'Del Peak 5(10q23.31) mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 17 25 18 11
DEL PEAK 5(10Q23.31) MUTATED 4 0 0 2
DEL PEAK 5(10Q23.31) WILD-TYPE 13 25 18 9

Figure S3.  Get High-res Image Gene #2: 'Del Peak 5(10q23.31) mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'Del Peak 7(22q11.21) mutation analysis' versus 'CN_CNMF'

P value = 5.76e-15 (Fisher's exact test), Q value = 1.4e-13

Table S4.  Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 8 19
DEL PEAK 7(22Q11.21) MUTATED 0 0 17
DEL PEAK 7(22Q11.21) WILD-TYPE 48 8 2

Figure S4.  Get High-res Image Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'Del Peak 7(22q11.21) mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.00531 (Fisher's exact test), Q value = 0.12

Table S5.  Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 17 29 21 8
DEL PEAK 7(22Q11.21) MUTATED 2 13 2 0
DEL PEAK 7(22Q11.21) WILD-TYPE 15 16 19 8

Figure S5.  Get High-res Image Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'Del Peak 7(22q11.21) mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00669 (Fisher's exact test), Q value = 0.13

Table S6.  Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 23 24 24
DEL PEAK 7(22Q11.21) MUTATED 5 10 1
DEL PEAK 7(22Q11.21) WILD-TYPE 18 14 23

Figure S6.  Get High-res Image Gene #3: 'Del Peak 7(22q11.21) mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'Del Peak 8(Xq22.3) mutation analysis' versus 'CN_CNMF'

P value = 0.00871 (Fisher's exact test), Q value = 0.17

Table S7.  Gene #4: 'Del Peak 8(Xq22.3) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 8 19
DEL PEAK 8(XQ22.3) MUTATED 0 2 1
DEL PEAK 8(XQ22.3) WILD-TYPE 48 6 18

Figure S7.  Get High-res Image Gene #4: 'Del Peak 8(Xq22.3) mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

  • Copy number data file = All Lesions File (all_lesions.conf_##.txt, where ## is the confidence level). The all lesions file is from GISTIC pipeline and summarizes the results from the GISTIC run. It contains data about the significant regions of amplification and deletion as well as which samples are amplified or deleted in each of these regions. The identified regions are listed down the first column, and the samples are listed across the first row, starting in column 10.

  • Molecular subtype file = THCA-follicular.transferedmergedcluster.txt

  • Number of patients = 75

  • Number of copy number variation regions = 4

  • Number of molecular subtypes = 6

  • Exclude regions that fewer than K tumors have alterations, K = 3

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.

References
[1] 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)
[2] 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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