Correlation between mRNA expression and clinical features
PANCANCER cohort with 12 disease types (Primary solid tumor)
21 April 2013 | analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1TT4NX8
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): PANCANCER cohort with 12 disease types (Primary solid tumor cohort) - 21 April 2013: Correlation between mRNA expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1TT4NX8
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 17814 genes and 19 clinical features across 1593 samples, statistically thresholded by Q value < 0.05, 16 clinical features related to at least one genes.

- 3018 genes correlated to 'Time to Death'.

- KLHL14 , ASS1 , IGSF11 , UPK1B , C4ORF32 , ...

- 3682 genes correlated to 'AGE'.

- GREB1 , COL18A1 , DUOX2 , LDOC1 , GALNTL1 , ...

- 17315 genes correlated to 'PRIMARY.SITE.OF.DISEASE'.

- KLHL14 , ZG16 , SLC22A2 , PDZD3 , EMX2 , ...

- 8993 genes correlated to 'GENDER'.

- ESR1 , RSPO1 , DDX3Y , RPS4Y1 , EIF1AY , ...

- 206 genes correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.

- PPP1R9A , VASN , MARCH7 , CCDC135 , POGZ , ...

- 16971 genes correlated to 'HISTOLOGICAL.TYPE'.

- KLHL14 , PDZD3 , EMX2 , NPR1 , FUT4 , ...

- 5911 genes correlated to 'PATHOLOGY.T'.

- C13ORF3 , NR3C1 , CDCA7 , LIFR , C20ORF151 , ...

- 16 genes correlated to 'PATHOLOGY.N'.

- TNFRSF10C , FAM73A , MGC50559 , ZNF273 , GABARAP , ...

- 30 genes correlated to 'PATHOLOGICSPREAD(M)'.

- KCNC2 , TCF7 , HCN1 , C8ORF30A , SPACA3 , ...

- 7395 genes correlated to 'TUMOR.STAGE'.

- FGF18 , WT1 , KITLG , RBM38 , ELL2 , ...

- 5814 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- CYP3A5 , CYP3A7 , CYP3A4 , TCF21 , MAP2K7 , ...

- 9 genes correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

- PSME4 , C1ORF64 , LMNB2 , LONP1 , SLC25A1 , ...

- 1 gene correlated to 'YEAROFTOBACCOSMOKINGONSET'.

- MMP10

- 2 genes correlated to 'LYMPH.NODE.METASTASIS'.

- GUCA2A , ASZ1

- 2319 genes correlated to 'COMPLETENESS.OF.RESECTION'.

- NPR1 , WIT1 , DOK5 , THRSP , KLHL14 , ...

- 5 genes correlated to 'NEOPLASM.DISEASESTAGE'.

- PGC , BMPER , LRP4 , GPER , PRSS2

- No genes correlated to 'NUMBERPACKYEARSSMOKED', 'DISTANT.METASTASIS', and 'NUMBER.OF.LYMPH.NODES'.

Results
Overview of the results

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=3018 | shorter survival | N=1360 | longer survival | N=1658
AGE | Spearman correlation test | N=3682 | older | N=1748 | younger | N=1934
PRIMARY SITE OF DISEASE | ANOVA test | N=17315 |  |  |  |
GENDER | t test | N=8993 | male | N=4112 | female | N=4881
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=206 | higher score | N=129 | lower score | N=77
HISTOLOGICAL TYPE | ANOVA test | N=16971 |  |  |  |
PATHOLOGY T | Spearman correlation test | N=5911 | higher pT | N=3176 | lower pT | N=2735
PATHOLOGY N | Spearman correlation test | N=16 | higher pN | N=3 | lower pN | N=13
PATHOLOGICSPREAD(M) | ANOVA test | N=30 |  |  |  |
TUMOR STAGE | Spearman correlation test | N=7395 | higher stage | N=3996 | lower stage | N=3399
RADIATIONS RADIATION REGIMENINDICATION | t test | N=5814 | yes | N=2865 | no | N=2949
NUMBERPACKYEARSSMOKED | Spearman correlation test | N=0 |  |  |  |
TOBACCOSMOKINGHISTORYINDICATOR | ANOVA test | N=9 |  |  |  |
YEAROFTOBACCOSMOKINGONSET | Spearman correlation test | N=1 | higher yearoftobaccosmokingonset | N=0 | lower yearoftobaccosmokingonset | N=1
DISTANT METASTASIS | ANOVA test | N=0 |  |  |  |
LYMPH NODE METASTASIS | ANOVA test | N=2 |  |  |  |
COMPLETENESS OF RESECTION | ANOVA test | N=2319 |  |  |  |
NUMBER OF LYMPH NODES | Spearman correlation test | N=0 |  |  |  |
NEOPLASM DISEASESTAGE | ANOVA test | N=5 |  |  |  |

Clinical variable #1: 'Time to Death'

3018 genes related to 'Time to Death'.

Table S1. Basic characteristics of clinical feature: 'Time to Death'

Time to Death | Duration (Months) | 0.1-223.4 (median=23)
| censored | N = 1000
| death | N = 437
| Significant markers | N = 3018
| associated with shorter survival | 1360
| associated with longer survival | 1658

List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

Table S2. Get Full Table List of top 10 genes significantly associated with 'Time to Death' by Cox regression test

| HazardRatio | Wald_P | Q | C_index
--- | --- | --- | --- | ---
KLHL14 | 1.26 | 0 | 0 | 0.6
ASS1 | 1.32 | 0 | 0 | 0.621
IGSF11 | 1.36 | 0 | 0 | 0.641
UPK1B | 1.21 | 0 | 0 | 0.636
C4ORF32 | 0.77 | 0 | 0 | 0.38
ZRSR1 | 0.55 | 0 | 0 | 0.349
MDS1 | 1.37 | 0 | 0 | 0.621
GALNT12 | 1.31 | 0 | 0 | 0.616
MUC4 | 1.22 | 0 | 0 | 0.635
NUBP1 | 0.46 | 0 | 0 | 0.354

Figure S1. Get High-res Image As an example, this figure shows the association of KLHL14 to 'Time to Death'. four curves present the cumulative survival rates of 4 quartile subsets of patients. P value = 0 with univariate Cox regression analysis using continuous log-2 expression values.

Clinical variable #2: 'AGE'

3682 genes related to 'AGE'.

Table S3. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 61.39 (13)
| Significant markers | N = 3682
| pos. correlated | 1748
| neg. correlated | 1934

List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

Table S4. Get Full Table List of top 10 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
GREB1 | -0.288 | 1.648e-31 | 2.94e-27
COL18A1 | -0.2771 | 3.469e-29 | 6.18e-25
DUOX2 | 0.2769 | 3.755e-29 | 6.69e-25
LDOC1 | -0.2689 | 1.588e-27 | 2.83e-23
GALNTL1 | -0.2672 | 3.515e-27 | 6.26e-23
OBSL1 | -0.2646 | 1.107e-26 | 1.97e-22
FOXF1 | 0.262 | 3.685e-26 | 6.56e-22
CYP2C18 | 0.2605 | 6.935e-26 | 1.23e-21
BBOX1 | -0.2573 | 2.842e-25 | 5.06e-21
SH3BP5 | -0.2572 | 3.097e-25 | 5.51e-21

Figure S2. Get High-res Image As an example, this figure shows the association of GREB1 to 'AGE'. P value = 1.65e-31 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #3: 'PRIMARY.SITE.OF.DISEASE'

17315 genes related to 'PRIMARY.SITE.OF.DISEASE'.

Table S5. Basic characteristics of clinical feature: 'PRIMARY.SITE.OF.DISEASE'

PRIMARY.SITE.OF.DISEASE | Labels | N
| BREAST | 526
| COLON | 152
| ENDOMETRIAL | 54
| KIDNEY | 72
| LUNG | 186
| OMENTUM | 2
| OVARY | 529
| PERITONEUM (OVARY) | 2
| RECTUM | 68
| Significant markers | N = 17315

List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

Table S6. Get Full Table List of top 10 genes differentially expressed by 'PRIMARY.SITE.OF.DISEASE'

| ANOVA_P | Q
--- | --- | ---
KLHL14 | 0 | 0
ZG16 | 0 | 0
SLC22A2 | 0 | 0
PDZD3 | 0 | 0
EMX2 | 0 | 0
NPR1 | 0 | 0
FUT4 | 0 | 0
ACF | 0 | 0
FXYD2 | 0 | 0
UPK1B | 0 | 0

Figure S3. Get High-res Image As an example, this figure shows the association of KLHL14 to 'PRIMARY.SITE.OF.DISEASE'. P value = 0 with ANOVA analysis.

Clinical variable #4: 'GENDER'

8993 genes related to 'GENDER'.

Table S7. Basic characteristics of clinical feature: 'GENDER'

GENDER | Labels | N
| FEMALE | 1304
| MALE | 289
| Significant markers | N = 8993
| Higher in MALE | 4112
| Higher in FEMALE | 4881

List of top 10 genes differentially expressed by 'GENDER'

Table S8. Get Full Table List of top 10 genes differentially expressed by 'GENDER'

| T(pos if higher in 'MALE') | ttestP | Q | AUC
--- | --- | --- | --- | ---
ESR1 | -36.23 | 6.789e-167 | 1.21e-162 | 0.8781
RSPO1 | -31.56 | 9.619e-167 | 1.71e-162 | 0.8493
DDX3Y | 53.31 | 9.336e-164 | 1.66e-159 | 0.9839
RPS4Y1 | 51.76 | 1.437e-155 | 2.56e-151 | 0.9717
EIF1AY | 48.93 | 2.175e-151 | 3.87e-147 | 0.9839
RPS4Y2 | 48.54 | 8.57e-148 | 1.53e-143 | 0.9816
ERBB4 | -32.63 | 1.134e-147 | 2.02e-143 | 0.8588
JARID1D | 44.53 | 5.72e-147 | 1.02e-142 | 0.9762
SCGB2A2 | -29.47 | 7.483e-146 | 1.33e-141 | 0.8574
CYORF15A | 43.55 | 3.378e-139 | 6.01e-135 | 0.9813

Figure S4. Get High-res Image As an example, this figure shows the association of ESR1 to 'GENDER'. P value = 6.79e-167 with T-test analysis.

Clinical variable #5: 'KARNOFSKY.PERFORMANCE.SCORE'

206 genes related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S9. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 60.22 (34)
| Significant markers | N = 206
| pos. correlated | 129
| neg. correlated | 77

List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

Table S10. Get Full Table List of top 10 genes significantly correlated to 'KARNOFSKY.PERFORMANCE.SCORE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
PPP1R9A | 0.5916 | 4.259e-10 | 7.59e-06
VASN | 0.5749 | 1.671e-09 | 2.98e-05
MARCH7 | -0.5551 | 7.711e-09 | 0.000137
CCDC135 | 0.5548 | 7.875e-09 | 0.00014
POGZ | 0.5503 | 1.102e-08 | 0.000196
INSIG2 | -0.5485 | 1.255e-08 | 0.000223
ZNF503 | 0.5479 | 1.318e-08 | 0.000235
TLE1 | 0.5448 | 1.642e-08 | 0.000292
ADK | -0.5439 | 1.761e-08 | 0.000314
PCYT1A | -0.5421 | 1.996e-08 | 0.000355

Figure S5. Get High-res Image As an example, this figure shows the association of PPP1R9A to 'KARNOFSKY.PERFORMANCE.SCORE'. P value = 4.26e-10 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #6: 'HISTOLOGICAL.TYPE'

16971 genes related to 'HISTOLOGICAL.TYPE'.

Table S11. Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE | Labels | N
| COLON ADENOCARCINOMA | 126
| COLON MUCINOUS ADENOCARCINOMA | 24
| ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA | 41
| INFILTRATING DUCTAL CARCINOMA | 110
| INFILTRATING LOBULAR CARCINOMA | 12
| KIDNEY CLEAR CELL RENAL CARCINOMA | 72
| LUNG ADENOCARCINOMA MIXED SUBTYPE | 1
| LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 30
| LUNG BASALOID SQUAMOUS CELL CARCINOMA | 5
| LUNG CLEAR CELL ADENOCARCINOMA | 1
| LUNG PAPILLARY SQUAMOUS CELL CARICNOMA | 1
| LUNG SQUAMOUS CELL CARCINOMA- NOT OTHERWISE SPECIFIED (NOS) | 148
| MIXED HISTOLOGY (PLEASE SPECIFY) | 5
| MIXED SEROUS AND ENDOMETRIOID | 1
| OTHER SPECIFY | 10
| RECTAL ADENOCARCINOMA | 58
| RECTAL MUCINOUS ADENOCARCINOMA | 7
| SEROUS CYSTADENOCARCINOMA | 533
| SEROUS ENDOMETRIAL ADENOCARCINOMA | 12
| Significant markers | N = 16971

List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S12. Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

| ANOVA_P | Q
--- | --- | ---
KLHL14 | 0 | 0
PDZD3 | 0 | 0
EMX2 | 0 | 0
NPR1 | 0 | 0
FUT4 | 0 | 0
ACF | 0 | 0
FXYD2 | 0 | 0
SPINK4 | 0 | 0
SFTPC | 0 | 0
SLC12A2 | 0 | 0

Figure S6. Get High-res Image As an example, this figure shows the association of KLHL14 to 'HISTOLOGICAL.TYPE'. P value = 0 with ANOVA analysis.

Clinical variable #7: 'PATHOLOGY.T'

5911 genes related to 'PATHOLOGY.T'.

Table S13. Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T | Mean (SD) | 2.3 (0.85)
|  | N
| T1 | 92
| T2 | 179
| T3 | 178
| T4 | 29
| Significant markers | N = 5911
| pos. correlated | 3176
| neg. correlated | 2735

List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

Table S14. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.T' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
C13ORF3 | 0.5211 | 1.264e-34 | 2.25e-30
NR3C1 | -0.5184 | 3.085e-34 | 5.49e-30
CDCA7 | 0.5156 | 7.924e-34 | 1.41e-29
LIFR | -0.5143 | 1.235e-33 | 2.2e-29
C20ORF151 | 0.5111 | 3.619e-33 | 6.45e-29
NOXO1 | 0.5077 | 1.096e-32 | 1.95e-28
PDSS1 | 0.5062 | 1.784e-32 | 3.18e-28
B3GNT3 | 0.5004 | 1.188e-31 | 2.12e-27
MAL | -0.4987 | 2.023e-31 | 3.6e-27
POF1B | 0.4978 | 2.687e-31 | 4.78e-27

Figure S7. Get High-res Image As an example, this figure shows the association of C13ORF3 to 'PATHOLOGY.T'. P value = 1.26e-34 with Spearman correlation analysis.

Clinical variable #8: 'PATHOLOGY.N'

16 genes related to 'PATHOLOGY.N'.

Table S15. Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N | Mean (SD) | 0.51 (0.77)
|  | N
| N0 | 290
| N1 | 90
| N2 | 60
| N3 | 5
| Significant markers | N = 16
| pos. correlated | 3
| neg. correlated | 13

List of top 10 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

Table S16. Get Full Table List of top 10 genes significantly correlated to 'PATHOLOGY.N' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
TNFRSF10C | -0.2603 | 2.519e-08 | 0.000449
FAM73A | -0.2572 | 3.746e-08 | 0.000667
MGC50559 | -0.2477 | 1.198e-07 | 0.00213
ZNF273 | 0.2452 | 1.624e-07 | 0.00289
GABARAP | -0.2423 | 2.285e-07 | 0.00407
LUZP2 | 0.2388 | 3.561e-07 | 0.00634
CNDP2 | -0.2304 | 8.931e-07 | 0.0159
DHCR7 | 0.2301 | 9.331e-07 | 0.0166
ZFP2 | -0.2294 | 1.007e-06 | 0.0179
DCTN6 | -0.2263 | 1.417e-06 | 0.0252

Figure S8. Get High-res Image As an example, this figure shows the association of TNFRSF10C to 'PATHOLOGY.N'. P value = 2.52e-08 with Spearman correlation analysis.

Clinical variable #9: 'PATHOLOGICSPREAD(M)'

30 genes related to 'PATHOLOGICSPREAD(M)'.

Table S17. Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) | Labels | N
| M0 | 428
| M1 | 44
| M1A | 1
| Significant markers | N = 30

List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S18. Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

| ANOVA_P | Q
--- | --- | ---
KCNC2 | 1.224e-09 | 2.18e-05
TCF7 | 2.424e-08 | 0.000432
HCN1 | 5.782e-08 | 0.00103
C8ORF30A | 1.136e-07 | 0.00202
SPACA3 | 2.624e-07 | 0.00467
F10 | 4.444e-07 | 0.00791
RBM26 | 5.393e-07 | 0.0096
SERPINA4 | 6.055e-07 | 0.0108
NPAS2 | 7.627e-07 | 0.0136
PLOD3 | 9.144e-07 | 0.0163

Figure S9. Get High-res Image As an example, this figure shows the association of KCNC2 to 'PATHOLOGICSPREAD(M)'. P value = 1.22e-09 with ANOVA analysis.

Clinical variable #10: 'TUMOR.STAGE'

7395 genes related to 'TUMOR.STAGE'.

Table S19. Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE | Mean (SD) | 2.55 (0.95)
|  | N
| Stage 1 | 206
| Stage 2 | 163
| Stage 3 | 512
| Stage 4 | 120
| Significant markers | N = 7395
| pos. correlated | 3996
| neg. correlated | 3399

List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

Table S20. Get Full Table List of top 10 genes significantly correlated to 'TUMOR.STAGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
FGF18 | 0.5209 | 1.067e-70 | 1.9e-66
WT1 | 0.5115 | 7.953e-68 | 1.42e-63
KITLG | -0.4949 | 5.798e-63 | 1.03e-58
RBM38 | 0.4891 | 2.517e-61 | 4.48e-57
ELL2 | -0.4855 | 2.59e-60 | 4.61e-56
RIMS4 | 0.4826 | 1.629e-59 | 2.9e-55
DOK7 | 0.4818 | 2.551e-59 | 4.54e-55
ZNF503 | 0.4817 | 2.85e-59 | 5.07e-55
KLK8 | 0.4805 | 5.754e-59 | 1.02e-54
KLK6 | 0.4795 | 1.078e-58 | 1.92e-54

Figure S10. Get High-res Image As an example, this figure shows the association of FGF18 to 'TUMOR.STAGE'. P value = 1.07e-70 with Spearman correlation analysis.

Clinical variable #11: 'RADIATIONS.RADIATION.REGIMENINDICATION'

5814 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S21. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 180
| YES | 1413
| Significant markers | N = 5814
| Higher in YES | 2865
| Higher in NO | 2949

List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S22. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
CYP3A5 | 22.2 | 4.3e-77 | 7.66e-73 | 0.7877
CYP3A7 | 20.4 | 1.717e-68 | 3.06e-64 | 0.7635
CYP3A4 | 20.24 | 6.476e-68 | 1.15e-63 | 0.7729
TCF21 | 21.02 | 1.431e-65 | 2.55e-61 | 0.7939
MAP2K7 | 21.32 | 8.132e-65 | 1.45e-60 | 0.8098
AADAC | 20.04 | 4.24e-63 | 7.55e-59 | 0.7714
CCDC71 | 21.22 | 1.383e-62 | 2.46e-58 | 0.8195
REG1A | 19.08 | 5.442e-59 | 9.69e-55 | 0.773
CHMP4B | 20.11 | 6.206e-58 | 1.11e-53 | 0.8105
PDZD3 | 17.13 | 1.326e-57 | 2.36e-53 | 0.6836

Figure S11. Get High-res Image As an example, this figure shows the association of CYP3A5 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.3e-77 with T-test analysis.

Clinical variable #12: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S23. Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED | Mean (SD) | 53.05 (35)
| Significant markers | N = 0

Clinical variable #13: 'TOBACCOSMOKINGHISTORYINDICATOR'

9 genes related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Table S24. Basic characteristics of clinical feature: 'TOBACCOSMOKINGHISTORYINDICATOR'

TOBACCOSMOKINGHISTORYINDICATOR | Labels | N
| CURRENT REFORMED SMOKER FOR < OR = 15 YEARS | 93
| CURRENT REFORMED SMOKER FOR > 15 YEARS | 49
| CURRENT SMOKER | 31
| LIFELONG NON-SMOKER | 11
| Significant markers | N = 9

List of 9 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

Table S25. Get Full Table List of 9 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

| ANOVA_P | Q
--- | --- | ---
PSME4 | 6.816e-08 | 0.00121
C1ORF64 | 1.645e-07 | 0.00293
LMNB2 | 1.211e-06 | 0.0216
LONP1 | 1.573e-06 | 0.028
SLC25A1 | 1.62e-06 | 0.0289
IGFBP7 | 1.965e-06 | 0.035
N6AMT2 | 2.361e-06 | 0.0421
CATSPER3 | 2.469e-06 | 0.044
LAS1L | 2.63e-06 | 0.0468

Figure S12. Get High-res Image As an example, this figure shows the association of PSME4 to 'TOBACCOSMOKINGHISTORYINDICATOR'. P value = 6.82e-08 with ANOVA analysis.

Clinical variable #14: 'YEAROFTOBACCOSMOKINGONSET'

One gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S26. Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET | Mean (SD) | 1959.74 (11)
| Significant markers | N = 1
| pos. correlated | 0
| neg. correlated | 1

List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S27. Get Full Table List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
MMP10 | -0.4473 | 4.812e-07 | 0.00857

Figure S13. Get High-res Image As an example, this figure shows the association of MMP10 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 4.81e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #15: 'DISTANT.METASTASIS'

No gene related to 'DISTANT.METASTASIS'.

Table S28. Basic characteristics of clinical feature: 'DISTANT.METASTASIS'

DISTANT.METASTASIS | Labels | N
| CM0 (I+) | 2
| M0 | 369
| M1 | 8
| MX | 10
| Significant markers | N = 0

Clinical variable #16: 'LYMPH.NODE.METASTASIS'

2 genes related to 'LYMPH.NODE.METASTASIS'.

Table S29. Basic characteristics of clinical feature: 'LYMPH.NODE.METASTASIS'

LYMPH.NODE.METASTASIS | Labels | N
| N0 | 118
| N0 (I+) | 7
| N0 (I-) | 59
| N1 | 41
| N1A | 62
| N1B | 14
| N1C | 2
| N1MI | 11
| N2 | 24
| N2A | 24
| N3 | 5
| N3A | 16
| NX | 6
| Significant markers | N = 2

List of 2 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

Table S30. Get Full Table List of 2 genes differentially expressed by 'LYMPH.NODE.METASTASIS'

| ANOVA_P | Q
--- | --- | ---
GUCA2A | 6.031e-12 | 1.07e-07
ASZ1 | 3.589e-08 | 0.000639

Figure S14. Get High-res Image As an example, this figure shows the association of GUCA2A to 'LYMPH.NODE.METASTASIS'. P value = 6.03e-12 with ANOVA analysis.

Clinical variable #17: 'COMPLETENESS.OF.RESECTION'

2319 genes related to 'COMPLETENESS.OF.RESECTION'.

Table S31. Basic characteristics of clinical feature: 'COMPLETENESS.OF.RESECTION'

COMPLETENESS.OF.RESECTION | Labels | N
| R0 | 403
| R1 | 39
| R2 | 34
| RX | 7
| Significant markers | N = 2319

List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

Table S32. Get Full Table List of top 10 genes differentially expressed by 'COMPLETENESS.OF.RESECTION'

| ANOVA_P | Q
--- | --- | ---
NPR1 | 2.596e-40 | 4.62e-36
WIT1 | 2.503e-37 | 4.46e-33
DOK5 | 4.72e-35 | 8.41e-31
THRSP | 5.822e-35 | 1.04e-30
KLHL14 | 3.091e-34 | 5.51e-30
WT1 | 1.009e-33 | 1.8e-29
S100A1 | 2.162e-33 | 3.85e-29
LYPD1 | 3.811e-30 | 6.79e-26
MUC16 | 8.048e-29 | 1.43e-24
SCGB1D2 | 1.049e-28 | 1.87e-24

Figure S15. Get High-res Image As an example, this figure shows the association of NPR1 to 'COMPLETENESS.OF.RESECTION'. P value = 2.6e-40 with ANOVA analysis.

Clinical variable #18: 'NUMBER.OF.LYMPH.NODES'

No gene related to 'NUMBER.OF.LYMPH.NODES'.

Table S33. Basic characteristics of clinical feature: 'NUMBER.OF.LYMPH.NODES'

NUMBER.OF.LYMPH.NODES | Mean (SD) | 1.94 (4)
| Significant markers | N = 0

Clinical variable #19: 'NEOPLASM.DISEASESTAGE'

5 genes related to 'NEOPLASM.DISEASESTAGE'.

Table S34. Basic characteristics of clinical feature: 'NEOPLASM.DISEASESTAGE'

NEOPLASM.DISEASESTAGE | Labels | N
| STAGE I | 41
| STAGE IA | 22
| STAGE IB | 2
| STAGE IIA | 136
| STAGE IIB | 83
| STAGE IIIA | 60
| STAGE IIIB | 12
| STAGE IIIC | 14
| STAGE IV | 8
| STAGE X | 11
| Significant markers | N = 5

List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

Table S35. Get Full Table List of 5 genes differentially expressed by 'NEOPLASM.DISEASESTAGE'

| ANOVA_P | Q
--- | --- | ---
PGC | 4.234e-14 | 7.54e-10
BMPER | 2.903e-09 | 5.17e-05
LRP4 | 2.449e-08 | 0.000436
GPER | 1.558e-07 | 0.00277
PRSS2 | 5.544e-07 | 0.00987

Figure S16. Get High-res Image As an example, this figure shows the association of PGC to 'NEOPLASM.DISEASESTAGE'. P value = 4.23e-14 with ANOVA analysis.

Methods & Data
Input

- Expresson data file = PANCAN12-TP.medianexp.txt

- Clinical data file = PANCAN12-TP.clin.merged.picked.txt

- Number of patients = 1593

- Number of genes = 17814

- Number of clinical features = 19

Survival analysis

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

Correlation analysis

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

ANOVA analysis

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

Student's t-test analysis

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

Q value calculation

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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[4] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle