This pipeline computes the correlation between cancer subtypes identified by different molecular patterns and selected clinical features.
Testing the association between subtypes identified by 6 different clustering approaches and 8 clinical features across 69 patients, one significant finding detected with P value < 0.05 and Q value < 0.25.
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3 subtypes identified in current cancer cohort by 'Copy Number Ratio CNMF subtypes'. These subtypes do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'METHLYATION CNMF'. These subtypes do not correlate to any clinical features.
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CNMF clustering analysis on sequencing-based mRNA expression data identified 2 subtypes that do not correlate to any clinical features.
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Consensus hierarchical clustering analysis on sequencing-based mRNA expression data identified 3 subtypes that do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'MIRSEQ CNMF'. These subtypes do not correlate to any clinical features.
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4 subtypes identified in current cancer cohort by 'MIRSEQ CHIERARCHICAL'. These subtypes correlate to 'AGE'.
Clinical Features |
Statistical Tests |
Copy Number Ratio CNMF subtypes |
METHLYATION CNMF |
RNAseq CNMF subtypes |
RNAseq cHierClus subtypes |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
Time to Death | logrank test |
0.372 (1.00) |
0.51 (1.00) |
0.253 (1.00) |
0.336 (1.00) |
0.796 (1.00) |
0.793 (1.00) |
AGE | ANOVA |
0.894 (1.00) |
0.0545 (1.00) |
0.407 (1.00) |
0.676 (1.00) |
0.0652 (1.00) |
0.00445 (0.187) |
GENDER | Fisher's exact test |
0.404 (1.00) |
0.502 (1.00) |
0.141 (1.00) |
0.171 (1.00) |
0.3 (1.00) |
0.141 (1.00) |
DISTANT METASTASIS | Chi-square test |
0.516 (1.00) |
0.483 (1.00) |
0.616 (1.00) |
0.842 (1.00) |
0.781 (1.00) |
0.879 (1.00) |
LYMPH NODE METASTASIS | Chi-square test |
0.444 (1.00) |
0.5 (1.00) |
1 (1.00) |
1 (1.00) |
0.259 (1.00) |
0.671 (1.00) |
COMPLETENESS OF RESECTION | Chi-square test |
0.49 (1.00) |
0.499 (1.00) |
0.363 (1.00) |
0.272 (1.00) |
0.418 (1.00) |
0.132 (1.00) |
TUMOR STAGECODE | ANOVA | ||||||
NEOPLASM DISEASESTAGE | Chi-square test |
0.509 (1.00) |
0.44 (1.00) |
0.577 (1.00) |
0.217 (1.00) |
0.149 (1.00) |
0.423 (1.00) |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 17 | 25 | 26 |
P value = 0.372 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 62 | 26 | 0.1 - 90.7 (13.7) |
subtype1 | 16 | 7 | 0.1 - 90.7 (7.2) |
subtype2 | 22 | 8 | 0.4 - 79.4 (22.5) |
subtype3 | 24 | 11 | 0.3 - 83.6 (14.3) |
P value = 0.894 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 63 | 61.6 (14.4) |
subtype1 | 16 | 60.3 (15.7) |
subtype2 | 22 | 62.6 (14.2) |
subtype3 | 25 | 61.6 (14.3) |
P value = 0.404 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 24 | 44 |
subtype1 | 4 | 13 |
subtype2 | 11 | 14 |
subtype3 | 9 | 17 |
P value = 0.516 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 45 | 1 | 22 |
subtype1 | 10 | 1 | 6 |
subtype2 | 17 | 0 | 8 |
subtype3 | 18 | 0 | 8 |
P value = 0.444 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
subtype1 | 12 | 0 | 5 |
subtype2 | 19 | 0 | 5 |
subtype3 | 15 | 1 | 10 |
P value = 0.49 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 46 | 8 | 1 | 8 |
subtype1 | 11 | 3 | 1 | 1 |
subtype2 | 17 | 2 | 0 | 2 |
subtype3 | 18 | 3 | 0 | 5 |
P value = 0.509 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IIIC | STAGE IVB |
---|---|---|---|---|---|---|---|
ALL | 29 | 12 | 2 | 12 | 2 | 1 | 1 |
subtype1 | 8 | 5 | 0 | 2 | 0 | 0 | 1 |
subtype2 | 11 | 3 | 2 | 4 | 1 | 0 | 0 |
subtype3 | 10 | 4 | 0 | 6 | 1 | 1 | 0 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 20 | 18 | 30 |
P value = 0.51 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 61 | 25 | 0.1 - 90.7 (13.6) |
subtype1 | 16 | 8 | 0.4 - 90.7 (22.5) |
subtype2 | 16 | 7 | 0.1 - 66.3 (7.2) |
subtype3 | 29 | 10 | 0.3 - 83.6 (8.3) |
P value = 0.0545 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 63 | 60.7 (15.0) |
subtype1 | 16 | 58.4 (18.3) |
subtype2 | 18 | 55.2 (17.0) |
subtype3 | 29 | 65.5 (9.8) |
P value = 0.502 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 25 | 43 |
subtype1 | 9 | 11 |
subtype2 | 7 | 11 |
subtype3 | 9 | 21 |
P value = 0.483 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 46 | 1 | 21 |
subtype1 | 13 | 0 | 7 |
subtype2 | 13 | 1 | 4 |
subtype3 | 20 | 0 | 10 |
P value = 0.5 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 47 | 1 | 19 |
subtype1 | 15 | 0 | 4 |
subtype2 | 14 | 0 | 4 |
subtype3 | 18 | 1 | 11 |
P value = 0.499 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 45 | 8 | 1 | 9 |
subtype1 | 13 | 3 | 0 | 1 |
subtype2 | 12 | 1 | 1 | 4 |
subtype3 | 20 | 4 | 0 | 4 |
P value = 0.44 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IIIC | STAGE IVB |
---|---|---|---|---|---|---|---|
ALL | 28 | 12 | 2 | 13 | 2 | 1 | 1 |
subtype1 | 7 | 4 | 2 | 4 | 1 | 0 | 0 |
subtype2 | 6 | 4 | 0 | 3 | 1 | 0 | 1 |
subtype3 | 15 | 4 | 0 | 6 | 0 | 1 | 0 |
Cluster Labels | 1 | 2 |
---|---|---|
Number of samples | 16 | 17 |
P value = 0.253 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 29 | 17 | 0.1 - 83.6 (19.8) |
subtype1 | 13 | 7 | 0.1 - 49.0 (11.6) |
subtype2 | 16 | 10 | 0.5 - 83.6 (24.5) |
P value = 0.407 (t-test), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 30 | 59.4 (17.6) |
subtype1 | 14 | 56.4 (20.3) |
subtype2 | 16 | 62.0 (15.1) |
P value = 0.141 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 10 | 23 |
subtype1 | 7 | 9 |
subtype2 | 3 | 14 |
P value = 0.616 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 22 | 1 | 10 |
subtype1 | 11 | 0 | 5 |
subtype2 | 11 | 1 | 5 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | N0 | NX |
---|---|---|
ALL | 24 | 8 |
subtype1 | 11 | 4 |
subtype2 | 13 | 4 |
P value = 0.363 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 18 | 6 | 1 | 6 |
subtype1 | 7 | 4 | 0 | 4 |
subtype2 | 11 | 2 | 1 | 2 |
P value = 0.577 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IVB |
---|---|---|---|---|---|---|
ALL | 10 | 5 | 2 | 7 | 1 | 1 |
subtype1 | 3 | 3 | 1 | 4 | 1 | 0 |
subtype2 | 7 | 2 | 1 | 3 | 0 | 1 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 11 | 5 | 17 |
P value = 0.336 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 29 | 17 | 0.1 - 83.6 (19.8) |
subtype1 | 8 | 6 | 3.0 - 49.0 (15.7) |
subtype2 | 5 | 1 | 0.1 - 34.1 (10.1) |
subtype3 | 16 | 10 | 0.5 - 83.6 (24.5) |
P value = 0.676 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 30 | 59.4 (17.6) |
subtype1 | 9 | 57.4 (21.3) |
subtype2 | 5 | 54.6 (20.6) |
subtype3 | 16 | 62.0 (15.1) |
P value = 0.171 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 10 | 23 |
subtype1 | 4 | 7 |
subtype2 | 3 | 2 |
subtype3 | 3 | 14 |
P value = 0.842 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 22 | 1 | 10 |
subtype1 | 7 | 0 | 4 |
subtype2 | 4 | 0 | 1 |
subtype3 | 11 | 1 | 5 |
P value = 1 (Fisher's exact test), Q value = 1
nPatients | N0 | NX |
---|---|---|
ALL | 24 | 8 |
subtype1 | 7 | 3 |
subtype2 | 4 | 1 |
subtype3 | 13 | 4 |
P value = 0.272 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 18 | 6 | 1 | 6 |
subtype1 | 3 | 4 | 0 | 3 |
subtype2 | 4 | 0 | 0 | 1 |
subtype3 | 11 | 2 | 1 | 2 |
P value = 0.217 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IVB |
---|---|---|---|---|---|---|
ALL | 10 | 5 | 2 | 7 | 1 | 1 |
subtype1 | 2 | 1 | 1 | 4 | 0 | 0 |
subtype2 | 1 | 2 | 0 | 0 | 1 | 0 |
subtype3 | 7 | 2 | 1 | 3 | 0 | 1 |
Cluster Labels | 1 | 2 | 3 |
---|---|---|---|
Number of samples | 25 | 12 | 31 |
P value = 0.796 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 61 | 25 | 0.1 - 83.6 (13.6) |
subtype1 | 22 | 11 | 0.1 - 69.6 (14.6) |
subtype2 | 9 | 4 | 1.1 - 83.6 (5.9) |
subtype3 | 30 | 10 | 0.3 - 79.4 (16.4) |
P value = 0.0652 (ANOVA), Q value = 1
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 63 | 60.9 (15.2) |
subtype1 | 24 | 55.8 (15.9) |
subtype2 | 9 | 59.7 (19.4) |
subtype3 | 30 | 65.4 (12.0) |
P value = 0.3 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 25 | 43 |
subtype1 | 11 | 14 |
subtype2 | 2 | 10 |
subtype3 | 12 | 19 |
P value = 0.781 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 45 | 1 | 22 |
subtype1 | 16 | 1 | 8 |
subtype2 | 8 | 0 | 4 |
subtype3 | 21 | 0 | 10 |
P value = 0.259 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
subtype1 | 17 | 0 | 7 |
subtype2 | 11 | 0 | 1 |
subtype3 | 18 | 1 | 12 |
P value = 0.418 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 45 | 8 | 1 | 9 |
subtype1 | 17 | 3 | 1 | 4 |
subtype2 | 5 | 3 | 0 | 1 |
subtype3 | 23 | 2 | 0 | 4 |
P value = 0.149 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IIIC | STAGE IVB |
---|---|---|---|---|---|---|---|
ALL | 28 | 12 | 2 | 13 | 2 | 1 | 1 |
subtype1 | 7 | 5 | 0 | 5 | 2 | 0 | 1 |
subtype2 | 5 | 2 | 2 | 3 | 0 | 0 | 0 |
subtype3 | 16 | 5 | 0 | 5 | 0 | 1 | 0 |
Cluster Labels | 1 | 2 | 3 | 4 |
---|---|---|---|---|
Number of samples | 10 | 9 | 24 | 25 |
P value = 0.793 (logrank test), Q value = 1
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 61 | 25 | 0.1 - 83.6 (13.6) |
subtype1 | 10 | 2 | 0.3 - 79.4 (3.9) |
subtype2 | 7 | 4 | 1.1 - 83.6 (11.6) |
subtype3 | 21 | 11 | 0.1 - 69.6 (19.8) |
subtype4 | 23 | 8 | 2.6 - 66.3 (14.3) |
P value = 0.00445 (ANOVA), Q value = 0.19
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 63 | 60.9 (15.2) |
subtype1 | 10 | 65.5 (6.4) |
subtype2 | 7 | 60.7 (18.5) |
subtype3 | 23 | 52.5 (17.3) |
subtype4 | 23 | 67.4 (10.5) |
P value = 0.141 (Fisher's exact test), Q value = 1
nPatients | FEMALE | MALE |
---|---|---|
ALL | 25 | 43 |
subtype1 | 1 | 9 |
subtype2 | 2 | 7 |
subtype3 | 10 | 14 |
subtype4 | 12 | 13 |
P value = 0.879 (Chi-square test), Q value = 1
nPatients | M0 | M1 | MX |
---|---|---|---|
ALL | 45 | 1 | 22 |
subtype1 | 6 | 0 | 4 |
subtype2 | 6 | 0 | 3 |
subtype3 | 15 | 1 | 8 |
subtype4 | 18 | 0 | 7 |
P value = 0.671 (Chi-square test), Q value = 1
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
subtype1 | 6 | 0 | 4 |
subtype2 | 8 | 0 | 1 |
subtype3 | 15 | 1 | 7 |
subtype4 | 17 | 0 | 8 |
P value = 0.132 (Chi-square test), Q value = 1
nPatients | R0 | R1 | R2 | RX |
---|---|---|---|---|
ALL | 45 | 8 | 1 | 9 |
subtype1 | 8 | 0 | 0 | 0 |
subtype2 | 3 | 3 | 0 | 0 |
subtype3 | 16 | 2 | 1 | 5 |
subtype4 | 18 | 3 | 0 | 4 |
P value = 0.423 (Chi-square test), Q value = 1
nPatients | STAGE I | STAGE II | STAGE III | STAGE IIIA | STAGE IIIB | STAGE IIIC | STAGE IVB |
---|---|---|---|---|---|---|---|
ALL | 28 | 12 | 2 | 13 | 2 | 1 | 1 |
subtype1 | 5 | 2 | 0 | 3 | 0 | 0 | 0 |
subtype2 | 3 | 1 | 2 | 3 | 0 | 0 | 0 |
subtype3 | 9 | 5 | 0 | 3 | 1 | 1 | 1 |
subtype4 | 11 | 4 | 0 | 4 | 1 | 0 | 0 |
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Cluster data file = LIHC-TP.mergedcluster.txt
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Clinical data file = LIHC-TP.clin.merged.picked.txt
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Number of patients = 69
-
Number of clustering approaches = 6
-
Number of selected clinical features = 8
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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
For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R
For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between two tumor subtypes 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.