This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17130 genes and 10 clinical features across 189 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.
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3 genes correlated to 'AGE'.
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USP35 , GDNF , TAC1
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5 genes correlated to 'GENDER'.
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KIF4B , GPX1 , POLDIP3 , PAFAH1B2 , RIMBP3
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3 genes correlated to 'PATHOLOGY.N'.
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APOL1 , CASP1 , UBE2L6
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236 genes correlated to 'PATHOLOGICSPREAD(M)'.
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FAM86B2 , ETV5 , DMKN , TMOD2 , KCNK4 , ...
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138 genes correlated to 'COMPLETENESS.OF.RESECTION'.
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HSD17B11 , SUSD2 , SGSM3 , IDH3B , SEC16A , ...
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3 genes correlated to 'NUMBER.OF.LYMPH.NODES'.
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CASP1 , APOL1 , UBE2L6
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No genes correlated to 'Time to Death', 'HISTOLOGICAL.TYPE', 'PATHOLOGY.T', and 'TUMOR.STAGE'.
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=3 | older | N=3 | younger | N=0 |
GENDER | t test | N=5 | male | N=1 | female | N=4 |
HISTOLOGICAL TYPE | t test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=3 | higher pN | N=3 | lower pN | N=0 |
PATHOLOGICSPREAD(M) | ANOVA test | N=236 | ||||
TUMOR STAGE | Spearman correlation test | N=0 | ||||
COMPLETENESS OF RESECTION | ANOVA test | N=138 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=3 | higher number.of.lymph.nodes | N=3 | lower number.of.lymph.nodes | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0.1-129.1 (median=6.3) |
censored | N = 148 | |
death | N = 24 | |
Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 65.23 (14) |
Significant markers | N = 3 | |
pos. correlated | 3 | |
neg. correlated | 0 |
Table S3. Get Full Table List of 3 genes significantly correlated to 'AGE' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
USP35 | 0.3754 | 1.103e-07 | 0.00189 |
GDNF | 0.3442 | 1.321e-06 | 0.0226 |
TAC1 | 0.3435 | 1.391e-06 | 0.0238 |
Figure S1. Get High-res Image As an example, this figure shows the association of USP35 to 'AGE'. P value = 1.1e-07 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V2ex.png)
Table S4. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 90 | |
MALE | 99 | |
Significant markers | N = 5 | |
Higher in MALE | 1 | |
Higher in FEMALE | 4 |
Table S5. Get Full Table List of 5 genes differentially expressed by 'GENDER'
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
---|---|---|---|---|
KIF4B | -9.84 | 1.173e-18 | 2.01e-14 | 0.8425 |
GPX1 | -9.05 | 1.929e-16 | 3.3e-12 | 0.8345 |
POLDIP3 | -7.58 | 1.849e-12 | 3.17e-08 | 0.7938 |
PAFAH1B2 | -5.5 | 1.229e-07 | 0.0021 | 0.721 |
RIMBP3 | 5.43 | 1.957e-07 | 0.00335 | 0.7085 |
Figure S2. Get High-res Image As an example, this figure shows the association of KIF4B to 'GENDER'. P value = 1.17e-18 with T-test analysis.
![](V3ex.png)
Table S6. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
HISTOLOGICAL.TYPE | Labels | N |
COLON ADENOCARCINOMA | 165 | |
COLON MUCINOUS ADENOCARCINOMA | 24 | |
Significant markers | N = 0 |
Table S7. Basic characteristics of clinical feature: 'PATHOLOGY.T'
PATHOLOGY.T | Mean (SD) | 2.9 (0.68) |
N | ||
T0 | 1 | |
T1 | 5 | |
T2 | 32 | |
T3 | 124 | |
T4 | 27 | |
Significant markers | N = 0 |
Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.N'
PATHOLOGY.N | Mean (SD) | 0.53 (0.73) |
N | ||
N0 | 116 | |
N1 | 45 | |
N2 | 27 | |
Significant markers | N = 3 | |
pos. correlated | 3 | |
neg. correlated | 0 |
Table S9. Get Full Table List of 3 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
APOL1 | 0.3897 | 3.257e-08 | 0.000558 |
CASP1 | 0.3756 | 1.092e-07 | 0.00187 |
UBE2L6 | 0.3521 | 7.223e-07 | 0.0124 |
Figure S3. Get High-res Image As an example, this figure shows the association of APOL1 to 'PATHOLOGY.N'. P value = 3.26e-08 with Spearman correlation analysis.
![](V6ex.png)
Table S10. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 127 | |
M1 | 19 | |
M1A | 5 | |
M1B | 1 | |
MX | 33 | |
Significant markers | N = 236 |
Table S11. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'
ANOVA_P | Q | |
---|---|---|
FAM86B2 | 2.889e-155 | 4.95e-151 |
ETV5 | 6.553e-83 | 1.12e-78 |
DMKN | 2.33e-56 | 3.99e-52 |
TMOD2 | 5.794e-55 | 9.92e-51 |
KCNK4 | 5.352e-54 | 9.17e-50 |
MTUS2 | 2.801e-44 | 4.8e-40 |
CLTCL1 | 6.361e-44 | 1.09e-39 |
PDSS2 | 1.485e-43 | 2.54e-39 |
TUBG2 | 8.325e-40 | 1.43e-35 |
TXNRD3IT1 | 8.372e-36 | 1.43e-31 |
Figure S4. Get High-res Image As an example, this figure shows the association of FAM86B2 to 'PATHOLOGICSPREAD(M)'. P value = 2.89e-155 with ANOVA analysis.
![](V7ex.png)
Table S12. Basic characteristics of clinical feature: 'TUMOR.STAGE'
TUMOR.STAGE | Mean (SD) | 2.37 (0.93) |
N | ||
Stage 1 | 31 | |
Stage 2 | 76 | |
Stage 3 | 48 | |
Stage 4 | 25 | |
Significant markers | N = 0 |
Table S13. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 114 | |
R2 | 2 | |
RX | 21 | |
Significant markers | N = 138 |
Table S14. Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'
ANOVA_P | Q | |
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HSD17B11 | 6.691e-20 | 1.15e-15 |
SUSD2 | 1.457e-19 | 2.5e-15 |
SGSM3 | 1.791e-19 | 3.07e-15 |
IDH3B | 5.774e-19 | 9.89e-15 |
SEC16A | 1.507e-18 | 2.58e-14 |
KIAA0415 | 3.8e-18 | 6.51e-14 |
FER | 4.26e-18 | 7.3e-14 |
PFDN6 | 7.426e-18 | 1.27e-13 |
WDR46 | 7.426e-18 | 1.27e-13 |
FA2H | 1.081e-17 | 1.85e-13 |
Figure S5. Get High-res Image As an example, this figure shows the association of HSD17B11 to 'COMPLETENESS.OF.RESECTION'. P value = 6.69e-20 with ANOVA analysis.
![](V9ex.png)
Table S15. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'
NUMBER.OF.LYMPH.NODES | Mean (SD) | 2 (5) |
Significant markers | N = 3 | |
pos. correlated | 3 | |
neg. correlated | 0 |
Table S16. Get Full Table List of 3 genes significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test
SpearmanCorr | corrP | Q | |
---|---|---|---|
CASP1 | 0.3921 | 1.606e-07 | 0.00275 |
APOL1 | 0.3633 | 1.394e-06 | 0.0239 |
UBE2L6 | 0.3626 | 1.473e-06 | 0.0252 |
Figure S6. Get High-res Image As an example, this figure shows the association of CASP1 to 'NUMBER.OF.LYMPH.NODES'. P value = 1.61e-07 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V10ex.png)
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Expresson data file = COAD-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = COAD-TP.clin.merged.picked.txt
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Number of patients = 189
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Number of genes = 17130
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Number of clinical features = 10
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
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
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
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
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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.