Thyroid Adenocarcinoma: Correlation between mRNAseq expression and clinical features

Maintained by Juok Cho (Broad Institute)

Overview

Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 17948 genes and 5 clinical features across 116 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

14 genes correlated to 'AGE'.

KBTBD2|25948 , DUSP6|1848 , CD97|976 , MST1P9|11223 , DDIT4L|115265 , ...

25 genes correlated to 'GENDER'.

DDX3Y|8653 , RPS4Y1|6192 , ZFY|7544 , USP9Y|8287 , UTY|7404 , ...

2301 genes correlated to 'HISTOLOGICAL.TYPE'.

PDHA1|5160 , GOT2|2806 , ITGA3|3675 , COQ9|57017 , KCNIP3|30818 , ...

19 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

FLJ37543|285668 , DNAH14|127602 , ORC1L|4998 , CUL7|9820 , C14ORF180|400258 , ...

162 genes correlated to 'NEOADJUVANT.THERAPY'.

SH2D1B|117157 , L3MBTL|26013 , KDM5C|8242 , SSR2|6746 , ZNF512|84450 , ...

Results

Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature	Statistical test	Significant genes	Associated with		Associated with
AGE	Spearman correlation test	N=14	older	N=4	younger	N=10
GENDER	t test	N=25	male	N=13	female	N=12
HISTOLOGICAL TYPE	ANOVA test	N=2301
RADIATIONS RADIATION REGIMENINDICATION	t test	N=19	yes	N=5	no	N=14
NEOADJUVANT THERAPY	t test	N=162	yes	N=52	no	N=110

Clinical variable #1: 'AGE'

14 genes related to 'AGE'.

Table S1. Basic characteristics of clinical feature: 'AGE'


AGE	Mean (SD)	47.71 (16)
	Significant markers	N = 14
	pos. correlated	4
	neg. correlated	10

List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S2. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

	SpearmanCorr	corrP	Q
KBTBD2\|25948	-0.4693	1.073e-07	0.00193
DUSP6\|1848	-0.4622	1.765e-07	0.00317
CD97\|976	-0.4568	2.543e-07	0.00456
MST1P9\|11223	-0.4565	2.604e-07	0.00467
DDIT4L\|115265	0.4531	3.262e-07	0.00585
ZCCHC12\|170261	-0.449	4.291e-07	0.0077
TMEM49\|81671	-0.4474	4.761e-07	0.00854
LOC401431\|401431	0.4438	6.059e-07	0.0109
NDEL1\|81565	-0.4436	6.125e-07	0.011
GSTM4\|2948	0.4262	1.841e-06	0.033

Figure S1. Get High-res Image As an example, this figure shows the association of KBTBD2|25948 to 'AGE'. P value = 1.07e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #2: 'GENDER'

25 genes related to 'GENDER'.

Table S3. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	81
	MALE	35

	Significant markers	N = 25
	Higher in MALE	13
	Higher in FEMALE	12

List of top 10 genes differentially expressed by 'GENDER'

Table S4. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

	T(pos if higher in 'MALE')	ttestP	Q	AUC
DDX3Y\|8653	58.99	1.24e-62	2.23e-58	1
RPS4Y1\|6192	46.45	8.673e-62	1.56e-57	1
ZFY\|7544	52.36	1.202e-59	2.16e-55	1
USP9Y\|8287	53.54	2.669e-56	4.79e-52	1
UTY\|7404	54.49	2.087e-49	3.74e-45	1
NLGN4Y\|22829	39	1.549e-46	2.78e-42	1
PRKY\|5616	21.24	3.833e-40	6.88e-36	0.9981
KDM5D\|8284	50.93	7.721e-39	1.39e-34	1
CYORF15A\|246126	42.66	4.364e-31	7.83e-27	1
TSIX\|9383	-17.46	6.628e-25	1.19e-20	0.9994

Figure S2. Get High-res Image As an example, this figure shows the association of DDX3Y|8653 to 'GENDER'. P value = 1.24e-62 with T-test analysis.

Clinical variable #3: 'HISTOLOGICAL.TYPE'

2301 genes related to 'HISTOLOGICAL.TYPE'.

Table S5. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	OTHER	3
	THYROID PAPILLARY CARCINOMA - CLASSICAL/USUAL	65
	THYROID PAPILLARY CARCINOMA - FOLLICULAR (>= 99% FOLLICULAR PATTERNED)	32
	THYROID PAPILLARY CARCINOMA - TALL CELL (>= 50% TALL CELL FEATURES)	16

	Significant markers	N = 2301

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S6. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
PDHA1\|5160	3.934e-20	7.06e-16
GOT2\|2806	3.811e-19	6.84e-15
ITGA3\|3675	1.303e-18	2.34e-14
COQ9\|57017	4.721e-18	8.47e-14
KCNIP3\|30818	5.276e-18	9.47e-14
ALDH1B1\|219	1.445e-17	2.59e-13
ERBB3\|2065	1.591e-17	2.85e-13
MPZL2\|10205	1.994e-17	3.58e-13
LDLR\|3949	8.447e-17	1.52e-12
BRP44L\|51660	1.088e-16	1.95e-12

Figure S3. Get High-res Image As an example, this figure shows the association of PDHA1|5160 to 'HISTOLOGICAL.TYPE'. P value = 3.93e-20 with ANOVA analysis.

Clinical variable #4: 'RADIATIONS.RADIATION.REGIMENINDICATION'

19 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S7. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'


RADIATIONS.RADIATION.REGIMENINDICATION	Labels	N
	NO	11
	YES	105

	Significant markers	N = 19
	Higher in YES	5
	Higher in NO	14

List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

	T(pos if higher in 'YES')	ttestP	Q	AUC
FLJ37543\|285668	8.88	2.01e-12	3.6e-08	0.8627
DNAH14\|127602	-8.4	1.136e-08	0.000203	0.9169
ORC1L\|4998	-6.54	7.806e-08	0.0014	0.8165
CUL7\|9820	-7.4	1.29e-07	0.00231	0.8857
C14ORF180\|400258	6.14	1.798e-07	0.00322	0.8889
MCM10\|55388	-6.44	2.463e-07	0.00441	0.8043
HCFC1\|3054	-7.15	3.502e-07	0.00627	0.8675
ZNF695\|57116	-6.86	4.161e-07	0.00744	0.8519
GINS1\|9837	-5.59	5.665e-07	0.0101	0.7913
CDC45\|8318	-6.5	8.185e-07	0.0146	0.8444

Figure S4. Get High-res Image As an example, this figure shows the association of FLJ37543|285668 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.01e-12 with T-test analysis.

Clinical variable #5: 'NEOADJUVANT.THERAPY'

162 genes related to 'NEOADJUVANT.THERAPY'.

Table S9. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'


NEOADJUVANT.THERAPY	Labels	N
	NO	3
	YES	113

	Significant markers	N = 162
	Higher in YES	52
	Higher in NO	110

List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S10. Get Full Table List of top 10 genes differentially expressed by 'NEOADJUVANT.THERAPY'

	T(pos if higher in 'YES')	ttestP	Q	AUC
SH2D1B\|117157	17.6	7.888e-32	1.3e-27	0.9492
L3MBTL\|26013	-16.28	3.506e-28	5.79e-24	0.944
KDM5C\|8242	-14.37	1.534e-26	2.53e-22	0.9587
SSR2\|6746	13.67	1.515e-25	2.5e-21	0.9263
ZNF512\|84450	-12.94	5.137e-24	8.49e-20	0.9351
FCRL5\|83416	15.05	2.726e-23	4.5e-19	0.9479
ZNF418\|147686	-13.06	1.889e-20	3.12e-16	0.9558
WBSCR22\|114049	11.16	5.468e-20	9.03e-16	0.8643
C1ORF104\|284618	-13.06	6.095e-20	1.01e-15	0.885
SGSM1\|129049	-11.05	1.029e-19	1.7e-15	0.8938

Figure S5. Get High-res Image As an example, this figure shows the association of SH2D1B|117157 to 'NEOADJUVANT.THERAPY'. P value = 7.89e-32 with T-test analysis.

Methods & Data

Input

Expresson data file = THCA.uncv2.mRNAseq_RSEM_normalized_log2.txt
Clinical data file = THCA.clin.merged.picked.txt
Number of patients = 116
Number of genes = 17948
Number of clinical features = 5

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' 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] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)

[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)

[4] 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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