This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.
Testing the association between 171 genes and 11 clinical features across 331 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.
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3 genes correlated to 'HISTOLOGICAL.TYPE'.
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RAD50|RAD50-M-C , ANXA1|ANNEXIN_I-R-V , MRE11A|MRE11-R-C
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1 gene correlated to 'PATHOLOGY.T'.
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PTGS2|COX-2-R-C
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1 gene correlated to 'PATHOLOGY.N'.
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IRS1|IRS1-R-V
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1 gene correlated to 'PATHOLOGICSPREAD(M)'.
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IGFBP2|IGFBP2-R-V
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3 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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LCK|LCK-R-V , SETD2|SETD2-R-NA , PECAM1|CD31-M-V
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2 genes correlated to 'COMPLETENESS.OF.RESECTION'.
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NCOA3|AIB1-M-V , EGFR|EGFR_PY1068-R-V
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1 gene correlated to 'NUMBER.OF.LYMPH.NODES'.
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IRS1|IRS1-R-V
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No genes correlated to 'Time to Death', 'AGE', 'GENDER', 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 | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=0 | ||||
HISTOLOGICAL TYPE | t test | N=3 | colon mucinous adenocarcinoma | N=2 | colon adenocarcinoma | N=1 |
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=1 | ||||
TUMOR STAGE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=3 | yes | N=2 | no | N=1 |
COMPLETENESS OF RESECTION | ANOVA test | N=2 | ||||
NUMBER OF LYMPH NODES | Spearman correlation test | N=1 | higher number.of.lymph.nodes | N=1 | lower number.of.lymph.nodes | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 0.1-135.5 (median=8) |
censored | N = 226 | |
death | N = 40 | |
Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 67.25 (13) |
Significant markers | N = 0 |
Table S3. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 156 | |
MALE | 175 | |
Significant markers | N = 0 |
Table S4. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'
HISTOLOGICAL.TYPE | Labels | N |
COLON ADENOCARCINOMA | 290 | |
COLON MUCINOUS ADENOCARCINOMA | 40 | |
Significant markers | N = 3 | |
Higher in COLON MUCINOUS ADENOCARCINOMA | 2 | |
Higher in COLON ADENOCARCINOMA | 1 |
Table S5. Get Full Table List of 3 genes differentially expressed by 'HISTOLOGICAL.TYPE'
T(pos if higher in 'COLON MUCINOUS ADENOCARCINOMA') | ttestP | Q | AUC | |
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RAD50|RAD50-M-C | -4.5 | 3.564e-05 | 0.0061 | 0.7039 |
ANXA1|ANNEXIN_I-R-V | 3.9 | 0.0002585 | 0.044 | 0.689 |
MRE11A|MRE11-R-C | 3.94 | 0.0002612 | 0.0441 | 0.6969 |
Figure S1. Get High-res Image As an example, this figure shows the association of RAD50|RAD50-M-C to 'HISTOLOGICAL.TYPE'. P value = 3.56e-05 with T-test analysis.
![](V4ex.png)
Table S6. Basic characteristics of clinical feature: 'PATHOLOGY.T'
PATHOLOGY.T | Mean (SD) | 2.91 (0.6) |
N | ||
T0 | 1 | |
T1 | 5 | |
T2 | 53 | |
T3 | 232 | |
T4 | 37 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
Table S7. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.T' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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PTGS2|COX-2-R-C | 0.2152 | 8.518e-05 | 0.0146 |
Figure S2. Get High-res Image As an example, this figure shows the association of PTGS2|COX-2-R-C to 'PATHOLOGY.T'. P value = 8.52e-05 with Spearman correlation analysis.
![](V5ex.png)
Table S8. Basic characteristics of clinical feature: 'PATHOLOGY.N'
PATHOLOGY.N | Mean (SD) | 0.57 (0.76) |
N | ||
N0 | 196 | |
N1 | 80 | |
N2 | 54 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
Table S9. Get Full Table List of one gene significantly correlated to 'PATHOLOGY.N' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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IRS1|IRS1-R-V | 0.2101 | 0.0001205 | 0.0206 |
Figure S3. Get High-res Image As an example, this figure shows the association of IRS1|IRS1-R-V to 'PATHOLOGY.N'. P value = 0.00012 with Spearman correlation analysis.
![](V6ex.png)
Table S10. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 258 | |
M1 | 36 | |
M1A | 6 | |
M1B | 1 | |
MX | 26 | |
Significant markers | N = 1 |
Table S11. Get Full Table List of one gene differentially expressed by 'PATHOLOGICSPREAD(M)'
ANOVA_P | Q | |
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IGFBP2|IGFBP2-R-V | 0.000185 | 0.0316 |
Figure S4. Get High-res Image As an example, this figure shows the association of IGFBP2|IGFBP2-R-V to 'PATHOLOGICSPREAD(M)'. P value = 0.000185 with ANOVA analysis.
![](V7ex.png)
Table S12. Basic characteristics of clinical feature: 'TUMOR.STAGE'
TUMOR.STAGE | Mean (SD) | 2.42 (0.9) |
N | ||
Stage 1 | 47 | |
Stage 2 | 135 | |
Stage 3 | 98 | |
Stage 4 | 43 | |
Significant markers | N = 0 |
3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S13. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 3 | |
YES | 328 | |
Significant markers | N = 3 | |
Higher in YES | 2 | |
Higher in NO | 1 |
Table S14. Get Full Table List of 3 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'
T(pos if higher in 'YES') | ttestP | Q | AUC | |
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LCK|LCK-R-V | 9.75 | 1.296e-18 | 2.22e-16 | 0.6972 |
SETD2|SETD2-R-NA | 5.51 | 9.342e-08 | 1.59e-05 | 0.5366 |
PECAM1|CD31-M-V | -10.85 | 2.531e-07 | 4.28e-05 | 0.8049 |
Figure S5. Get High-res Image As an example, this figure shows the association of LCK|LCK-R-V to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.3e-18 with T-test analysis.
![](V9ex.png)
Table S15. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'
COMPLETENESS.OF.RESECTION | Labels | N |
R0 | 239 | |
R2 | 16 | |
RX | 16 | |
Significant markers | N = 2 |
Table S16. Get Full Table List of 2 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'
ANOVA_P | Q | |
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NCOA3|AIB1-M-V | 0.0001266 | 0.0217 |
EGFR|EGFR_PY1068-R-V | 0.0002002 | 0.034 |
Figure S6. Get High-res Image As an example, this figure shows the association of NCOA3|AIB1-M-V to 'COMPLETENESS.OF.RESECTION'. P value = 0.000127 with ANOVA analysis.
![](V10ex.png)
Table S17. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'
NUMBER.OF.LYMPH.NODES | Mean (SD) | 1.96 (4.5) |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
Table S18. Get Full Table List of one gene significantly correlated to 'NUMBER.OF.LYMPH.NODES' by Spearman correlation test
SpearmanCorr | corrP | Q | |
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IRS1|IRS1-R-V | 0.2401 | 1.865e-05 | 0.00319 |
Figure S7. Get High-res Image As an example, this figure shows the association of IRS1|IRS1-R-V to 'NUMBER.OF.LYMPH.NODES'. P value = 1.86e-05 with Spearman correlation analysis. The straight line presents the best linear regression.
![](V11ex.png)
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Expresson data file = COAD-TP.rppa.txt
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Clinical data file = COAD-TP.clin.merged.picked.txt
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Number of patients = 331
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Number of genes = 171
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Number of clinical features = 11
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.