Colon 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 17848 genes and 9 clinical features across 192 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

- 2 genes correlated to 'AGE'.

- DDX27|55661 , KIAA0406|9675

- 25 genes correlated to 'GENDER'.

- RPS4Y1|6192 , ZFY|7544 , DDX3Y|8653 , XIST|7503 , KDM5D|8284 , ...

- 101 genes correlated to 'HISTOLOGICAL.TYPE'.

- PPP1R9A|55607 , DYNLRB1|83658 , ZIC5|85416 , MOCS3|27304 , POFUT1|23509 , ...

- 1 gene correlated to 'PATHOLOGY.N'.

- CD2BP2|10421

- No genes correlated to 'Time to Death', 'PATHOLOGY.T', 'PATHOLOGICSPREAD(M)', 'TUMOR.STAGE', and 'NEOADJUVANT.THERAPY'.

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=2 | older | N=0 | younger | N=2
GENDER | t test | N=25 | male | N=13 | female | N=12
HISTOLOGICAL TYPE | t test | N=101 | colon mucinous adenocarcinoma | N=49 | colon adenocarcinoma | N=52
PATHOLOGY T | Spearman correlation test | N=0 |  |  |  |
PATHOLOGY N | Spearman correlation test | N=1 | higher pN | N=1 | lower pN | N=0
PATHOLOGICSPREAD(M) | ANOVA test | N=0 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=0 |  |  |  |
NEOADJUVANT THERAPY | t test | 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) | 0.9-71.7 (median=12.4)
| censored | N = 92
| death | N = 16
| Significant markers | N = 0

Clinical variable #2: 'AGE'

2 genes related to 'AGE'.

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

AGE | Mean (SD) | 69.66 (12)
| Significant markers | N = 2
| pos. correlated | 0
| neg. correlated | 2

List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

Table S3. Get Full Table List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
DDX27|55661 | -0.3351 | 2.019e-06 | 0.036
KIAA0406|9675 | -0.3323 | 2.494e-06 | 0.0445

Figure S1. Get High-res Image As an example, this figure shows the association of DDX27|55661 to 'AGE'. P value = 2.02e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'GENDER'

25 genes related to 'GENDER'.

Table S4. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 99
| MALE | 93
| Significant markers | N = 25
| Higher in MALE | 13
| Higher in FEMALE | 12

List of top 10 genes differentially expressed by 'GENDER'

Table S5. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
RPS4Y1|6192 | 26.78 | 2.19e-63 | 3.91e-59 | 0.9974
ZFY|7544 | 26.95 | 7.184e-51 | 1.28e-46 | 0.9919
DDX3Y|8653 | 26.99 | 2.915e-47 | 5.2e-43 | 0.9951
XIST|7503 | -20.01 | 9.653e-40 | 1.72e-35 | 0.9806
KDM5D|8284 | 25.13 | 2.492e-39 | 4.45e-35 | 0.9955
CYORF15A|246126 | 21.19 | 7.879e-38 | 1.41e-33 | 0.9884
TMSB4Y|9087 | 19.26 | 1.606e-34 | 2.87e-30 | 0.975
PRKY|5616 | 15.19 | 2.703e-34 | 4.82e-30 | 0.9331
EIF1AY|9086 | 19.41 | 1.771e-28 | 3.16e-24 | 0.9901
NLGN4Y|22829 | 14.56 | 7.649e-28 | 1.36e-23 | 0.9474

Figure S2. Get High-res Image As an example, this figure shows the association of RPS4Y1|6192 to 'GENDER'. P value = 2.19e-63 with T-test analysis.

Clinical variable #4: 'HISTOLOGICAL.TYPE'

101 genes related to 'HISTOLOGICAL.TYPE'.

Table S6. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 162
| COLON MUCINOUS ADENOCARCINOMA | 27
| Significant markers | N = 101
| Higher in COLON MUCINOUS ADENOCARCINOMA | 49
| Higher in COLON ADENOCARCINOMA | 52

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

Table S7. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') | ttestP | Q | AUC
--- | --- | --- | --- | ---
PPP1R9A|55607 | 7.66 | 9.842e-12 | 1.76e-07 | 0.7523
DYNLRB1|83658 | -8.48 | 1.267e-11 | 2.26e-07 | 0.8425
ZIC5|85416 | 7.92 | 3.9e-11 | 6.96e-07 | 0.8056
MOCS3|27304 | -7.97 | 5.581e-11 | 9.96e-07 | 0.8185
POFUT1|23509 | -7.71 | 1.731e-09 | 3.09e-05 | 0.8445
C20ORF24|55969 | -7.34 | 1.813e-09 | 3.23e-05 | 0.8157
ACTR5|79913 | -6.8 | 3.975e-09 | 7.09e-05 | 0.7757
SDR16C5|195814 | 6.94 | 3.987e-09 | 7.11e-05 | 0.781
PLAGL2|5326 | -7.46 | 4.012e-09 | 7.16e-05 | 0.8484
CHMP4B|128866 | -7.22 | 5.549e-09 | 9.9e-05 | 0.8443

Figure S3. Get High-res Image As an example, this figure shows the association of PPP1R9A|55607 to 'HISTOLOGICAL.TYPE'. P value = 9.84e-12 with T-test analysis.

Clinical variable #5: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T | Mean (SD) | 2.83 (0.63)
|  | N
| T1 | 6
| T2 | 38
| T3 | 128
| T4 | 18
| Significant markers | N = 0

Clinical variable #6: 'PATHOLOGY.N'

One gene related to 'PATHOLOGY.N'.

Table S9. Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N | Mean (SD) | 0.59 (0.79)
|  | N
| N0 | 114
| N1 | 41
| N2 | 36
| Significant markers | N = 1
| pos. correlated | 1
| neg. correlated | 0

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

Table S10. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
CD2BP2|10421 | 0.3592 | 3.347e-07 | 0.00597

Figure S4. Get High-res Image As an example, this figure shows the association of CD2BP2|10421 to 'PATHOLOGY.N'. P value = 3.35e-07 with Spearman correlation analysis.

Clinical variable #7: 'PATHOLOGICSPREAD(M)'

No gene related to 'PATHOLOGICSPREAD(M)'.

Table S11. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 159
| M1 | 28
| M1A | 2
| Significant markers | N = 0

Clinical variable #8: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S12. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 2.37 (0.95)
|  | N
| Stage 1 | 35
| Stage 2 | 73
| Stage 3 | 50
| Stage 4 | 27
| Significant markers | N = 0

Clinical variable #9: 'NEOADJUVANT.THERAPY'

No gene related to 'NEOADJUVANT.THERAPY'.

Table S13. Basic characteristics of clinical feature: 'NEOADJUVANT.THERAPY'

NEOADJUVANT.THERAPY | Labels | N
| NO | 15
| YES | 177
| Significant markers | N = 0

Methods & Data
Input

- Expresson data file = COAD.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

- Number of patients = 192

- Number of genes = 17848

- 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.

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] 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)
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