(NRAS_Hotspot_Mutants cohort)
This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17071 genes and 6 clinical features across 42 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes.
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2 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.
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SNX1 , ARCN1
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11 genes correlated to 'LYMPH.NODE.METASTASIS'.
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NUBP2 , PPCS , CRTC2 , RTKN2 , FOXL2 , ...
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26 genes correlated to 'NEOPLASM.DISEASESTAGE'.
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C20ORF27 , ABCA7 , PLS1 , DPEP1 , RABAC1 , ...
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No genes correlated to 'Time to Death', 'AGE', and 'GENDER'.
Complete statistical result table is provided in Supplement Table 1
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 | ||||
PRIMARY SITE OF DISEASE | ANOVA test | N=2 | ||||
GENDER | t test | N=0 | ||||
LYMPH NODE METASTASIS | ANOVA test | N=11 | ||||
NEOPLASM DISEASESTAGE | ANOVA test | N=26 |
Time to Death | Duration (Months) | 2.6-314.5 (median=48.9) |
censored | N = 20 | |
death | N = 22 | |
Significant markers | N = 0 |
AGE | Mean (SD) | 58.07 (15) |
Significant markers | N = 0 |
PRIMARY.SITE.OF.DISEASE | Labels | N |
DISTANT METASTASIS | 8 | |
REGIONAL CUTANEOUS OR SUBCUTANEOUS TISSUE (INCLUDES SATELLITE AND IN-TRANSIT METASTASIS) | 9 | |
REGIONAL LYMPH NODE | 25 | |
Significant markers | N = 2 |
GENDER | Labels | N |
FEMALE | 15 | |
MALE | 27 | |
Significant markers | N = 0 |
LYMPH.NODE.METASTASIS | Labels | N |
N0 | 26 | |
N1A | 3 | |
N1B | 4 | |
N2A | 1 | |
N2B | 2 | |
N3 | 3 | |
Significant markers | N = 11 |
ANOVA_P | Q | |
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NUBP2 | 3.288e-21 | 5.61e-17 |
PPCS | 2.783e-15 | 4.75e-11 |
CRTC2 | 2.365e-11 | 4.04e-07 |
RTKN2 | 9.674e-09 | 0.000165 |
FOXL2 | 1.025e-07 | 0.00175 |
IL20RB | 1.811e-07 | 0.00309 |
AKR7L | 2.994e-07 | 0.00511 |
PRG2 | 4.733e-07 | 0.00808 |
ZAR1L | 1.363e-06 | 0.0233 |
TFIP11 | 1.676e-06 | 0.0286 |
NEOPLASM.DISEASESTAGE | Labels | N |
I OR II NOS | 1 | |
STAGE I | 3 | |
STAGE IA | 4 | |
STAGE IB | 5 | |
STAGE II | 4 | |
STAGE IIA | 3 | |
STAGE IIB | 4 | |
STAGE IIC | 2 | |
STAGE III | 1 | |
STAGE IIIA | 1 | |
STAGE IIIB | 6 | |
STAGE IIIC | 5 | |
Significant markers | N = 26 |
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Expresson data file = SKCM-NRAS_Hotspot_Mutants.meth.for_correlation.filtered_data.txt
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Clinical data file = SKCM-NRAS_Hotspot_Mutants.clin.merged.picked.txt
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Number of patients = 42
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Number of genes = 17071
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Number of clinical features = 6
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 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 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 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.