This pipeline computes the correlation between cancer subtypes identified by different molecular patterns and selected clinical features.
Testing the association between subtypes identified by 5 different clustering approaches and 6 clinical features across 527 patients, 7 significant findings detected with P value < 0.05.
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CNMF clustering analysis on array-based mRNA expression data identified 3 subtypes that correlate to 'AGE'.
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Consensus hierarchical clustering analysis on array-based mRNA expression data identified 3 subtypes that correlate to 'AGE'.
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CNMF clustering analysis on array-based miR expression data identified 4 subtypes that correlate to 'Time to Death'.
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Consensus hierarchical clustering analysis on array-based miR expression data identified 3 subtypes that correlate to 'Time to Death' and 'AGE'.
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3 subtypes identified in current cancer cohort by 'METHLYATION CNMF'. These subtypes correlate to 'Time to Death' and 'AGE'.
Clinical Features |
Statistical Tests |
mRNA CNMF subtypes |
mRNA cHierClus subtypes |
miR CNMF subtypes |
miR cHierClus subtypes |
METHLYATION CNMF |
Time to Death | logrank test | 0.157 | 0.056 | 0.000614 | 0.00455 | 0.000342 |
AGE | ANOVA | 0.0257 | 0.0276 | 0.101 | 0.000872 | 2.71e-09 |
GENDER | Fisher's exact test | 0.444 | 0.501 | 0.555 | 0.14 | 0.963 |
KARNOFSKY PERFORMANCE SCORE | ANOVA | 0.839 | 0.487 | 0.943 | 0.785 | 0.109 |
RADIATIONS RADIATION REGIMENINDICATION | Fisher's exact test | 0.247 | 0.0937 | 0.572 | 0.806 | 0.15 |
NEOADJUVANT THERAPY | Fisher's exact test | 0.78 | 0.667 | 0.897 | 0.973 | 0.534 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 177 | 172 | 170 |
P value = 0.157 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 519 | 403 | 0.1 - 127.6 (9.9) |
subtype1 | 177 | 145 | 0.2 - 127.6 (10.0) |
subtype2 | 172 | 129 | 0.2 - 108.8 (9.2) |
subtype3 | 170 | 129 | 0.1 - 92.6 (10.7) |
P value = 0.0257 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 519 | 57.7 (14.5) |
subtype1 | 177 | 57.3 (12.8) |
subtype2 | 172 | 55.8 (16.4) |
subtype3 | 170 | 60.0 (13.7) |
P value = 0.444 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 205 | 314 |
subtype1 | 70 | 107 |
subtype2 | 62 | 110 |
subtype3 | 73 | 97 |
P value = 0.839 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 389 | 77.1 (14.4) |
subtype1 | 137 | 77.5 (15.0) |
subtype2 | 126 | 77.3 (13.0) |
subtype3 | 126 | 76.5 (15.0) |
P value = 0.247 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 350 | 169 |
subtype1 | 121 | 56 |
subtype2 | 108 | 64 |
subtype3 | 121 | 49 |
P value = 0.78 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 246 | 273 |
subtype1 | 81 | 96 |
subtype2 | 85 | 87 |
subtype3 | 80 | 90 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 223 | 127 | 169 |
P value = 0.056 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 519 | 403 | 0.1 - 127.6 (9.9) |
subtype1 | 223 | 182 | 0.1 - 90.6 (10.4) |
subtype2 | 127 | 94 | 0.1 - 92.6 (9.8) |
subtype3 | 169 | 127 | 0.2 - 127.6 (9.4) |
P value = 0.0276 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 519 | 57.7 (14.5) |
subtype1 | 223 | 57.7 (13.4) |
subtype2 | 127 | 60.3 (13.8) |
subtype3 | 169 | 55.7 (16.0) |
P value = 0.501 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 205 | 314 |
subtype1 | 90 | 133 |
subtype2 | 54 | 73 |
subtype3 | 61 | 108 |
P value = 0.487 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 389 | 77.1 (14.4) |
subtype1 | 165 | 77.6 (14.4) |
subtype2 | 98 | 75.6 (15.4) |
subtype3 | 126 | 77.6 (13.5) |
P value = 0.0937 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 350 | 169 |
subtype1 | 157 | 66 |
subtype2 | 90 | 37 |
subtype3 | 103 | 66 |
P value = 0.667 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 246 | 273 |
subtype1 | 103 | 120 |
subtype2 | 58 | 69 |
subtype3 | 85 | 84 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 144 | 159 | 74 | 105 |
P value = 0.000614 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 482 | 379 | 0.1 - 127.6 (10.3) |
subtype1 | 144 | 116 | 0.1 - 51.3 (10.6) |
subtype2 | 159 | 124 | 0.1 - 127.6 (10.6) |
subtype3 | 74 | 57 | 0.1 - 53.8 (8.4) |
subtype4 | 105 | 82 | 0.1 - 92.6 (10.8) |
P value = 0.101 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 482 | 57.5 (14.6) |
subtype1 | 144 | 59.7 (11.4) |
subtype2 | 159 | 55.5 (17.0) |
subtype3 | 74 | 57.9 (15.3) |
subtype4 | 105 | 57.4 (13.7) |
P value = 0.555 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 187 | 295 |
subtype1 | 56 | 88 |
subtype2 | 68 | 91 |
subtype3 | 27 | 47 |
subtype4 | 36 | 69 |
P value = 0.943 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 368 | 77.6 (14.1) |
subtype1 | 112 | 77.6 (14.4) |
subtype2 | 114 | 77.5 (14.1) |
subtype3 | 62 | 76.9 (14.4) |
subtype4 | 80 | 78.4 (13.8) |
P value = 0.572 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 329 | 153 |
subtype1 | 103 | 41 |
subtype2 | 108 | 51 |
subtype3 | 46 | 28 |
subtype4 | 72 | 33 |
P value = 0.897 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 231 | 251 |
subtype1 | 68 | 76 |
subtype2 | 80 | 79 |
subtype3 | 35 | 39 |
subtype4 | 48 | 57 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 170 | 180 | 132 |
P value = 0.00455 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 482 | 379 | 0.1 - 127.6 (10.3) |
subtype1 | 170 | 137 | 0.1 - 92.6 (9.8) |
subtype2 | 180 | 145 | 0.1 - 127.6 (10.0) |
subtype3 | 132 | 97 | 0.1 - 108.8 (10.7) |
P value = 0.000872 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 482 | 57.5 (14.6) |
subtype1 | 170 | 59.2 (12.6) |
subtype2 | 180 | 58.9 (13.3) |
subtype3 | 132 | 53.5 (17.6) |
P value = 0.14 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 187 | 295 |
subtype1 | 59 | 111 |
subtype2 | 80 | 100 |
subtype3 | 48 | 84 |
P value = 0.785 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 368 | 77.6 (14.1) |
subtype1 | 129 | 78.3 (13.5) |
subtype2 | 136 | 77.1 (15.5) |
subtype3 | 103 | 77.4 (13.1) |
P value = 0.806 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 329 | 153 |
subtype1 | 114 | 56 |
subtype2 | 122 | 58 |
subtype3 | 93 | 39 |
P value = 0.973 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 231 | 251 |
subtype1 | 82 | 88 |
subtype2 | 87 | 93 |
subtype3 | 62 | 70 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 81 | 124 | 75 |
P value = 0.000342 (logrank test)
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 280 | 208 | 0.1 - 127.6 (10.0) |
subtype1 | 81 | 57 | 0.1 - 92.6 (10.0) |
subtype2 | 124 | 98 | 0.1 - 77.6 (9.3) |
subtype3 | 75 | 53 | 0.2 - 127.6 (12.4) |
P value = 2.71e-09 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 280 | 57.5 (14.9) |
subtype1 | 81 | 57.1 (11.9) |
subtype2 | 124 | 62.7 (12.6) |
subtype3 | 75 | 49.5 (17.5) |
P value = 0.963 (Fisher's exact test)
nPatients | FEMALE | MALE |
---|---|---|
ALL | 114 | 166 |
subtype1 | 34 | 47 |
subtype2 | 50 | 74 |
subtype3 | 30 | 45 |
P value = 0.109 (ANOVA)
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 213 | 75.4 (15.0) |
subtype1 | 63 | 77.1 (16.8) |
subtype2 | 93 | 72.9 (14.9) |
subtype3 | 57 | 77.4 (12.3) |
P value = 0.15 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 206 | 74 |
subtype1 | 64 | 17 |
subtype2 | 84 | 40 |
subtype3 | 58 | 17 |
P value = 0.534 (Fisher's exact test)
nPatients | NO | YES |
---|---|---|
ALL | 116 | 164 |
subtype1 | 31 | 50 |
subtype2 | 56 | 68 |
subtype3 | 29 | 46 |
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Cluster data file = GBM.mergedcluster.txt
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Clinical data file = GBM.clin.merged.picked.txt
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Number of patients = 527
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Number of clustering approaches = 5
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Number of selected clinical features = 6
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Exclude small clusters that include fewer than K patients, K = 3
consensus non-negative matrix factorization clustering approach (Brunet et al. 2004)
Resampling-based clustering method (Monti et al. 2003)
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R
For continuous numerical clinical features, one-way analysis of variance (Howell 2002) was applied to compare the clinical values between tumor subtypes using 'anova' function in R
For binary clinical features, two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.