This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17421 genes and 11 clinical features across 299 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.
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2 genes correlated to 'Time to Death'.
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ZNF266 , WIPI1
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4 genes correlated to 'AGE'.
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SLC35D3 , HAND1 , XKR6 , PRSS27
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5 genes correlated to 'GENDER'.
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KIF4B , FRG1B , SLC22A3 , NLRP2 , RPA1
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7 genes correlated to 'PATHOLOGY.N'.
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SLC47A2 , AVPI1 , FAM185A , ARHGAP27 , ESRRA , ...
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7 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
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FLII , ZCCHC17 , RTN4IP1 , CKS2 , RPL7L1 , ...
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3 genes correlated to 'NUMBERPACKYEARSSMOKED'.
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PHOSPHO2 , RAB21 , MMADHC
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5 genes correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.
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C17ORF82 , THAP11 , SLC12A7 , ACCN4 , KCNC3
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No genes correlated to 'PATHOLOGY.T', 'TUMOR.STAGE', 'STOPPEDSMOKINGYEAR', and 'YEAROFTOBACCOSMOKINGONSET'.
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=2 | shorter survival | N=1 | longer survival | N=1 |
AGE | Spearman correlation test | N=4 | older | N=4 | younger | N=0 |
GENDER | t test | N=5 | male | N=2 | female | N=3 |
PATHOLOGY T | Spearman correlation test | N=0 | ||||
PATHOLOGY N | Spearman correlation test | N=7 | higher pN | N=7 | lower pN | N=0 |
TUMOR STAGE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=7 | yes | N=1 | no | N=6 |
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=3 | higher numberpackyearssmoked | N=0 | lower numberpackyearssmoked | N=3 |
STOPPEDSMOKINGYEAR | Spearman correlation test | N=0 | ||||
TOBACCOSMOKINGHISTORYINDICATOR | ANOVA test | N=5 | ||||
YEAROFTOBACCOSMOKINGONSET | Spearman correlation test | N=0 |
Time to Death | Duration (Months) | 0.1-210.9 (median=14.8) |
censored | N = 179 | |
death | N = 117 | |
Significant markers | N = 2 | |
associated with shorter survival | 1 | |
associated with longer survival | 1 |
AGE | Mean (SD) | 61.14 (12) |
Significant markers | N = 4 | |
pos. correlated | 4 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
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SLC35D3 | 0.3072 | 5.932e-08 | 0.00103 |
HAND1 | 0.2824 | 6.878e-07 | 0.012 |
XKR6 | 0.2808 | 8.002e-07 | 0.0139 |
PRSS27 | 0.2672 | 2.774e-06 | 0.0483 |
GENDER | Labels | N |
FEMALE | 81 | |
MALE | 218 | |
Significant markers | N = 5 | |
Higher in MALE | 2 | |
Higher in FEMALE | 3 |
T(pos if higher in 'MALE') | ttestP | Q | AUC | |
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KIF4B | -11.42 | 1.288e-21 | 2.24e-17 | 0.8553 |
FRG1B | -5.97 | 2.708e-08 | 0.000472 | 0.7198 |
SLC22A3 | 5.3 | 2.257e-07 | 0.00393 | 0.5962 |
NLRP2 | 5.07 | 1.269e-06 | 0.0221 | 0.6906 |
RPA1 | -4.91 | 1.524e-06 | 0.0265 | 0.5609 |
PATHOLOGY.T | Mean (SD) | 2.92 (1) |
N | ||
T1 | 23 | |
T2 | 77 | |
T3 | 59 | |
T4 | 101 | |
Significant markers | N = 0 |
PATHOLOGY.N | Mean (SD) | 1.03 (0.96) |
N | ||
N0 | 99 | |
N1 | 32 | |
N2 | 96 | |
N3 | 5 | |
Significant markers | N = 7 | |
pos. correlated | 7 | |
neg. correlated | 0 |
SpearmanCorr | corrP | Q | |
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SLC47A2 | 0.356 | 2.457e-08 | 0.000428 |
AVPI1 | 0.3295 | 2.805e-07 | 0.00489 |
FAM185A | 0.3168 | 8.333e-07 | 0.0145 |
ARHGAP27 | 0.3158 | 9.112e-07 | 0.0159 |
ESRRA | 0.3039 | 2.415e-06 | 0.0421 |
VAMP8 | 0.3031 | 2.559e-06 | 0.0446 |
BTNL8 | 0.3018 | 2.853e-06 | 0.0497 |
TUMOR.STAGE | Mean (SD) | 3.29 (0.98) |
N | ||
Stage 1 | 16 | |
Stage 2 | 47 | |
Stage 3 | 40 | |
Stage 4 | 152 | |
Significant markers | N = 0 |
7 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 75 | |
YES | 224 | |
Significant markers | N = 7 | |
Higher in YES | 1 | |
Higher in NO | 6 |
T(pos if higher in 'YES') | ttestP | Q | AUC | |
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FLII | 5.7 | 4.461e-08 | 0.000777 | 0.693 |
ZCCHC17 | -5.65 | 1.054e-07 | 0.00184 | 0.7057 |
RTN4IP1 | -5.29 | 4.899e-07 | 0.00853 | 0.6849 |
CKS2 | -5.17 | 8.851e-07 | 0.0154 | 0.6911 |
RPL7L1 | -5.08 | 1.176e-06 | 0.0205 | 0.6839 |
EHMT2 | -5.02 | 1.234e-06 | 0.0215 | 0.6693 |
TMEM57 | -5.01 | 1.786e-06 | 0.0311 | 0.6988 |
NUMBERPACKYEARSSMOKED | Mean (SD) | 50.21 (38) |
Significant markers | N = 3 | |
pos. correlated | 0 | |
neg. correlated | 3 |
SpearmanCorr | corrP | Q | |
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PHOSPHO2 | -0.3744 | 9.191e-07 | 0.016 |
RAB21 | -0.3667 | 1.596e-06 | 0.0278 |
MMADHC | -0.3597 | 2.59e-06 | 0.0451 |
STOPPEDSMOKINGYEAR | Mean (SD) | 1994.58 (14) |
Significant markers | N = 0 |
5 genes related to 'TOBACCOSMOKINGHISTORYINDICATOR'.
TOBACCOSMOKINGHISTORYINDICATOR | Labels | N |
CURRENT REFORMED SMOKER FOR < OR = 15 YEARS | 82 | |
CURRENT REFORMED SMOKER FOR > 15 YEARS | 53 | |
CURRENT SMOKER | 95 | |
LIFELONG NON-SMOKER | 58 | |
Significant markers | N = 5 |
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Expresson data file = HNSC-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = HNSC-TP.clin.merged.picked.txt
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Number of patients = 299
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Number of genes = 17421
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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.