Colon/Rectal Adenocarcinoma: Correlation between mRNA expression and clinical features

Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)

Overview

Introduction

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

Summary

Testing the association between 17814 genes and 9 clinical features across 223 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

38 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

PRAC , CEACAM5 , GPX2 , LGALS4 , ZNF529 , ...

30 genes correlated to 'GENDER'.

DDX3Y , EIF1AY , JARID1D , RPS4Y1 , RPS4Y2 , ...

386 genes correlated to 'HISTOLOGICAL.TYPE'.

SLC11A1 , PLAGL2 , C20ORF177 , PDGFRL , ZNF529 , ...

1 gene correlated to 'PATHOLOGY.T'.

RBP7

1 gene correlated to 'PATHOLOGY.N'.

LUZP2

4 genes correlated to 'PATHOLOGICSPREAD(M)'.

KCNC2 , FLJ44894 , ZNF273 , MFNG

2 genes correlated to 'NEOADJUVANT.THERAPY'.

MYO10 , ELAVL2

No genes correlated to 'Time to Death', and 'AGE'.

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
Time to Death	Cox regression test	N=0
AGE	Spearman correlation test	N=0
PRIMARY SITE OF DISEASE	t test	N=38	rectum	N=26	colon	N=12
GENDER	t test	N=30	male	N=14	female	N=16
HISTOLOGICAL TYPE	ANOVA test	N=386
PATHOLOGY T	Spearman correlation test	N=1	higher pT	N=1	lower pT	N=0
PATHOLOGY N	Spearman correlation test	N=1	higher pN	N=1	lower pN	N=0
PATHOLOGICSPREAD(M)	ANOVA test	N=4
NEOADJUVANT THERAPY	t test	N=2	yes	N=2	no	N=0

Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1. Basic characteristics of clinical feature: 'Time to Death'


Time to Death	Duration (Months)	0.9-52 (median=5)
	censored	N = 98
	death	N = 15

	Significant markers	N = 0

Clinical variable #2: 'AGE'

No gene related to 'AGE'.

Table S2. Basic characteristics of clinical feature: 'AGE'


AGE	Mean (SD)	69.45 (11)
	Significant markers	N = 0

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

38 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S3. Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'


PRIMARY.SITE.OF.DISEASE	Labels	N
	COLON	153
	RECTUM	68

	Significant markers	N = 38
	Higher in RECTUM	26
	Higher in COLON	12

List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S4. Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

	T(pos if higher in 'RECTUM')	ttestP	Q	AUC
PRAC	7.52	4.268e-12	7.6e-08	0.7813
CEACAM5	7.33	5.253e-12	9.36e-08	0.7743
GPX2	7.26	6.735e-12	1.2e-07	0.7876
LGALS4	7.22	1.489e-11	2.65e-07	0.7568
ZNF529	6.33	1.349e-09	2.4e-05	0.6845
HSP90B3P	-6	1.173e-08	0.000209	0.732
MLH1	5.93	1.182e-08	0.000211	0.6718
PPP1R1B	5.7	4.525e-08	0.000806	0.7362
CFTR	5.72	4.526e-08	0.000806	0.7652
PDZK1IP1	5.78	4.667e-08	0.000831	0.7427

Figure S1. Get High-res Image As an example, this figure shows the association of PRAC to 'PRIMARY.SITE.OF.DISEASE'. P value = 4.27e-12 with T-test analysis.

Clinical variable #4: 'GENDER'

30 genes related to 'GENDER'.

Table S5. Basic characteristics of clinical feature: 'GENDER'


GENDER	Labels	N
	FEMALE	107
	MALE	116

	Significant markers	N = 30
	Higher in MALE	14
	Higher in FEMALE	16

List of top 10 genes differentially expressed by 'GENDER'

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

	T(pos if higher in 'MALE')	ttestP	Q	AUC
DDX3Y	25.36	2.249e-67	4.01e-63	0.9712
EIF1AY	22.87	1.045e-59	1.86e-55	0.9641
JARID1D	22.57	3.627e-59	6.46e-55	0.9705
RPS4Y1	22.36	1.145e-57	2.04e-53	0.9425
RPS4Y2	21.49	9.222e-55	1.64e-50	0.9647
CYORF15A	20.81	5.304e-53	9.45e-49	0.954
UTY	18.83	2.168e-46	3.86e-42	0.9451
CYORF15B	17.17	6.976e-42	1.24e-37	0.9328
ZFY	16.82	2.958e-41	5.27e-37	0.9303
NLGN4Y	12.26	9.627e-26	1.71e-21	0.8677

Figure S2. Get High-res Image As an example, this figure shows the association of DDX3Y to 'GENDER'. P value = 2.25e-67 with T-test analysis.

Clinical variable #5: 'HISTOLOGICAL.TYPE'

386 genes related to 'HISTOLOGICAL.TYPE'.

Table S7. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'


HISTOLOGICAL.TYPE	Labels	N
	COLON ADENOCARCINOMA	127
	COLON MUCINOUS ADENOCARCINOMA	24
	RECTAL ADENOCARCINOMA	58
	RECTAL MUCINOUS ADENOCARCINOMA	7

	Significant markers	N = 386

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

Table S8. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

	ANOVA_P	Q
SLC11A1	2.234e-12	3.98e-08
PLAGL2	3.095e-12	5.51e-08
C20ORF177	1.135e-11	2.02e-07
PDGFRL	1.209e-11	2.15e-07
ZNF529	8.193e-11	1.46e-06
AGR2	8.375e-11	1.49e-06
DUSP4	8.525e-11	1.52e-06
SLC19A3	1.039e-10	1.85e-06
PRAC	1.314e-10	2.34e-06
HPSE	1.504e-10	2.68e-06

Figure S3. Get High-res Image As an example, this figure shows the association of SLC11A1 to 'HISTOLOGICAL.TYPE'. P value = 2.23e-12 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

One gene related to 'PATHOLOGY.T'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.T'


PATHOLOGY.T	Mean (SD)	2.79 (0.64)
		N
	T1	9
	T2	46
	T3	149
	T4	17

	Significant markers	N = 1
	pos. correlated	1
	neg. correlated	0

List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S10. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

	SpearmanCorr	corrP	Q
RBP7	0.3128	2.105e-06	0.0375

Figure S4. Get High-res Image As an example, this figure shows the association of RBP7 to 'PATHOLOGY.T'. P value = 2.11e-06 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S11. Basic characteristics of clinical feature: 'PATHOLOGY.N'


PATHOLOGY.N	Mean (SD)	0.59 (0.8)
		N
	N0	136
	N1	43
	N2	44

	Significant markers	N = 1
	pos. correlated	1
	neg. correlated	0

List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S12. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

	SpearmanCorr	corrP	Q
LUZP2	0.3107	2.224e-06	0.0396

Figure S5. Get High-res Image As an example, this figure shows the association of LUZP2 to 'PATHOLOGY.N'. P value = 2.22e-06 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGICSPREAD(M)'

4 genes related to 'PATHOLOGICSPREAD(M)'.

Table S13. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'


PATHOLOGICSPREAD(M)	Labels	N
	M0	185
	M1	34
	M1A	1

	Significant markers	N = 4

List of 4 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S14. Get Full Table List of 4 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

	ANOVA_P	Q
KCNC2	1.081e-10	1.93e-06
FLJ44894	1.59e-06	0.0283
ZNF273	2.13e-06	0.0379
MFNG	2.188e-06	0.039

Figure S6. Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 1.08e-10 with ANOVA analysis.

Clinical variable #9: 'NEOADJUVANT.THERAPY'

2 genes related to 'NEOADJUVANT.THERAPY'.

Table S15. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'


NEOADJUVANT.THERAPY	Labels	N
	NO	8
	YES	215

	Significant markers	N = 2
	Higher in YES	2
	Higher in NO	0

List of 2 genes differentially expressed by 'NEOADJUVANT.THERAPY'

Table S16. Get Full Table List of 2 genes differentially expressed by 'NEOADJUVANT.THERAPY'

	T(pos if higher in 'YES')	ttestP	Q	AUC
MYO10	8.53	4.588e-07	0.00817	0.8302
ELAVL2	6.3	1.433e-06	0.0255	0.7483

Figure S7. Get High-res Image As an example, this figure shows the association of MYO10 to 'NEOADJUVANT.THERAPY'. P value = 4.59e-07 with T-test analysis.

Methods & Data

Input

Expresson data file = COADREAD.medianexp.txt
Clinical data file = COADREAD.clin.merged.picked.txt
Number of patients = 223
Number of genes = 17814
Number of clinical features = 9

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

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.

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References

[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)

[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)

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

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

[5] 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)