(primary solid tumor cohort)
This pipeline uses various statistical tests to identify RPPAs whose expression levels correlated to selected clinical features.
Testing the association between 171 genes and 9 clinical features across 269 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.
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2 genes correlated to 'AGE'.
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RB1|RB_PS807_S811-R-V , BID|BID-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 '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 , PECAM1|CD31-M-V , SETD2|SETD2-R-NA
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No genes correlated to 'Time to Death', 'GENDER', 'HISTOLOGICAL.TYPE', 'PATHOLOGY.N', and 'TUMOR.STAGE'.
Complete statistical result table is provided in Supplement Table 1
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=1 | younger | N=1 |
GENDER | t test | N=0 | ||||
HISTOLOGICAL TYPE | t test | N=0 | ||||
PATHOLOGY T | Spearman correlation test | N=1 | higher pT | N=1 | lower pT | N=0 |
PATHOLOGY N | Spearman correlation test | 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 |
Time to Death | Duration (Months) | 0.1-105.3 (median=6) |
censored | N = 187 | |
death | N = 19 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 66.58 (13) |
Significant markers | N = 2 | |
pos. correlated | 1 | |
neg. correlated | 1 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
RB1|RB_PS807_S811-R-V | 0.2399 | 7.284e-05 | 0.0125 |
BID|BID-R-C | -0.2394 | 7.519e-05 | 0.0128 |
GENDER | Labels | N |
FEMALE | 127 | |
MALE | 142 | |
Significant markers | N = 0 |
HISTOLOGICAL.TYPE | Labels | N |
COLON ADENOCARCINOMA | 238 | |
COLON MUCINOUS ADENOCARCINOMA | 30 | |
Significant markers | N = 0 |
PATHOLOGY.T | Mean (SD) | 2.91 (0.61) |
N | ||
T0 | 1 | |
T1 | 4 | |
T2 | 45 | |
T3 | 185 | |
T4 | 31 | |
Significant markers | N = 1 | |
pos. correlated | 1 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
---|---|---|---|
PTGS2|COX-2-R-C | 0.2271 | 0.0001873 | 0.032 |
PATHOLOGY.N | Mean (SD) | 0.56 (0.75) |
N | ||
N0 | 160 | |
N1 | 66 | |
N2 | 42 | |
Significant markers | N = 0 |
PATHOLOGICSPREAD(M) | Labels | N |
M0 | 202 | |
M1 | 31 | |
M1A | 6 | |
M1B | 1 | |
MX | 26 | |
Significant markers | N = 1 |
ANOVA_P | Q | |
---|---|---|
IGFBP2|IGFBP2-R-V | 0.0002593 | 0.0443 |
TUMOR.STAGE | Mean (SD) | 2.43 (0.92) |
N | ||
Stage 1 | 40 | |
Stage 2 | 107 | |
Stage 3 | 77 | |
Stage 4 | 38 | |
Significant markers | N = 0 |
3 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 3 | |
YES | 266 | |
Significant markers | N = 3 | |
Higher in YES | 2 | |
Higher in NO | 1 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
---|---|---|---|---|
LCK|LCK-R-V | 11.11 | 1.106e-22 | 1.89e-20 | 0.7531 |
PECAM1|CD31-M-V | -10.82 | 1.561e-08 | 2.65e-06 | 0.8133 |
SETD2|SETD2-R-NA | 4.79 | 2.966e-06 | 0.000501 | 0.5213 |
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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 = 269
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Number of genes = 171
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Number of clinical features = 9
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.