LUAD/00: Correlation between molecular cancer subtypes to clinical
Overview
Introduction

This pipeline checks the correlation between cancer subtypes identified by different molecular portraits to selected clinical features.

Summary

Testing the association between 2 clustering variables and 5 clinical features across 25 samples, no significant finding detected with P value <= 0.05 and Q value <= 0.25.

  • CNMF clustering analysis on mRNA expression data identified 3 subtypes that are not correlated to any clinical features.

  • 3 subtypes identified in current cancer cohort by 'mRNA HierClus consensus subtypes'. These subtypes are not correlated to any clinical features.

  • No gene mutations related to clinical features.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association results between 2 clustering variables and 5 clinical features. Shown in the table are P values (Q values). Thresholded by P value <= 0.05 and Q value <= 0.25, no significant finding detected.

Clinical
Features 		mRNA
CNMF
subtypes 		mRNA
HierClus
consensus
subtypes
Time to Death survival 0.274
(1.00) 		0.315
(1.00)
AGE continuous 0.666
(1.00) 		0.635
(1.00)
GENDER binary 0.562
(1.00) 		0.817
(1.00)
PATHOLOGY T binary 0.296
(1.00) 		0.256
(1.00)
PATHOLOGY N multiclass(3) 0.35
(1.00) 		0.349
(1.00)
Clustering Variable #1: 'mRNA CNMF subtypes'

Table 2.  Get Full Table Description of clustering Variable #1: 'mRNA CNMF subtypes'

Cluster Labels 1 2 3
Number of samples 13 8 4
'mRNA CNMF subtypes' versus 'Time to Death'

P value = 0.274 (Kaplan-Meier), Q value = 1

Table 3.  Clustering Variable #1: 'mRNA CNMF subtypes' versus Clinical Variable #1: 'Time to Death'

N nEvent Duration Range (Median), Month
ALL 22 2 0.5 - 56.8 (13.2)
subtype1 10 0 6.0 - 56.8 (8.2)
subtype2 8 1 0.5 - 37.0 (8.9)
subtype3 4 1 20.6 - 45.2 (38.9)
'mRNA CNMF subtypes' versus 'AGE'

P value = 0.666 (ANOVA), Q value = 1

Table 4.  Clustering Variable #1: 'mRNA CNMF subtypes' versus Clinical Variable #2: 'AGE'

nSamples Mean (Std.Dev)
ALL 25 64.2 (10.0)
subtype1 13 63.8 (11.1)
subtype2 8 62.6 (9.1)
subtype3 4 68.2 (9.2)
'mRNA CNMF subtypes' versus 'GENDER'

P value = 0.562 (Chi-square), Q value = 1

Table 5.  Clustering Variable #1: 'mRNA CNMF subtypes' versus Clinical Variable #3: 'GENDER'

nSamples FEMALE MALE
ALL 12 13
subtype1 5 8
subtype2 5 3
subtype3 2 2
'mRNA CNMF subtypes' versus 'PATHOLOGY.T'

P value = 0.296 (Chi-square), Q value = 1

Table 6.  Clustering Variable #1: 'mRNA CNMF subtypes' versus Clinical Variable #4: 'PATHOLOGY.T'

nSamples T1 T2+T3
ALL 8 16
subtype1 5 7
subtype2 3 5
subtype3 0 4
'mRNA CNMF subtypes' versus 'PATHOLOGY.N'

P value = 0.35 (Chi-square), Q value = 1

Table 7.  Clustering Variable #1: 'mRNA CNMF subtypes' versus Clinical Variable #5: 'PATHOLOGY.N'

nSamples N0 N1 N2
ALL 15 4 4
subtype1 9 2 1
subtype2 5 1 1
subtype3 1 1 2
Clustering Variable #2: 'mRNA HierClus consensus subtypes'

Table 8.  Get Full Table Description of clustering Variable #2: 'mRNA HierClus consensus subtypes'

Cluster Labels 1 2 3
Number of samples 4 9 12
'mRNA HierClus consensus subtypes' versus 'Time to Death'

P value = 0.315 (Kaplan-Meier), Q value = 1

Table 9.  Clustering Variable #2: 'mRNA HierClus consensus subtypes' versus Clinical Variable #1: 'Time to Death'

N nEvent Duration Range (Median), Month
ALL 22 2 0.5 - 56.8 (13.2)
subtype1 4 1 20.6 - 45.2 (38.9)
subtype2 9 1 0.5 - 37.0 (13.2)
subtype3 9 0 6.0 - 56.8 (8.1)
'mRNA HierClus consensus subtypes' versus 'AGE'

P value = 0.635 (ANOVA), Q value = 1

Table 10.  Clustering Variable #2: 'mRNA HierClus consensus subtypes' versus Clinical Variable #2: 'AGE'

nSamples Mean (Std.Dev)
ALL 25 64.2 (10.0)
subtype1 4 68.2 (9.2)
subtype2 9 62.3 (8.5)
subtype3 12 64.2 (11.5)
'mRNA HierClus consensus subtypes' versus 'GENDER'

P value = 0.817 (Chi-square), Q value = 1

Table 11.  Clustering Variable #2: 'mRNA HierClus consensus subtypes' versus Clinical Variable #3: 'GENDER'

nSamples FEMALE MALE
ALL 12 13
subtype1 2 2
subtype2 5 4
subtype3 5 7
'mRNA HierClus consensus subtypes' versus 'PATHOLOGY.T'

P value = 0.256 (Chi-square), Q value = 1

Table 12.  Clustering Variable #2: 'mRNA HierClus consensus subtypes' versus Clinical Variable #4: 'PATHOLOGY.T'

nSamples T1 T2+T3
ALL 8 16
subtype1 0 4
subtype2 3 6
subtype3 5 6
'mRNA HierClus consensus subtypes' versus 'PATHOLOGY.N'

P value = 0.349 (Chi-square), Q value = 1

Table 13.  Clustering Variable #2: 'mRNA HierClus consensus subtypes' versus Clinical Variable #5: 'PATHOLOGY.N'

nSamples N0 N1 N2
ALL 15 4 4
subtype1 1 1 2
subtype2 6 1 1
subtype3 8 2 1
Methods & Data
Input

Input Data

  • Cluster data file = LUAD.mergedcluster.txt

  • Clinical data file = LUAD.clin.merged.picked.txt

  • Number of samples = 25

  • Number of clustering variables = 2

  • Number of filtered clinical features = 5

  • Minimum size criteria to remove small clusters = 3