1. Meta-analysis of all patients
Literature search: 253 candidate genes
GeneChip® HTA 2.0: Japan cohort (stage I+II, N=107)
Survival analysis of 256 genes using HTA 2.0 data: Univariable cox regression analysis
20 genes
Technical validation of 20 genes using qRT-PCR: Japan cohort (stage I+II, N=107)
Survival analysis of 20 genes using qRT-PCR data: Univariable cox regression analysis:
Japan cohort
7 genes: DUSP6, ALDH1A1, FBN2, CD99, CUL3, ACTN4, SMNDC1
2 genes: DUSP6, ACTN4
Survival analysis of 20 genes using qRT-PCR data: Univariable cox regression analysis:
NCI-MD /Norway cohort (stage I+II, N=91)
Generation of two-gene classifier in Japan Cohort: Coefficients generated from cox regression models on continuous expression values of DUSP6 and ACTN4 (stage I+II, N=121)
Survival analysis of two-gene classifier for relapse-free survival: Japan cohort (stage I+II, N=121)
Survival analysis of two-gene classifier for cancer-specific survival: NCI-MD/Norway Cohort (stage I+II, N = 91)
US-MD Anderson cohort
(stage I+II, N = 46, stageI, N=30)
US-Duke cohort
(stage I+II, N=44, stage I, N = 33)
France cohort
(stage I+II, N=56, stage I, N = 49 )
Sweden cohort
(stage I+II, N=48, stage I, N = 37 )
Korea cohort
(stage I+II, N=57, stage I, N=45)
US-Michigan cohort
(stage I+II, N = 107, stage I, N = 73)
Relapse free survival (RFS)
Overall survival (OS)
Validation of two-gene signature in published cohorts
Meta-analysis of all patients
Stage I+II N=24 (RFS) & N=255 (OS)
Stage I N=134 (RFS) & N=192 (OS)
Supplementary Figure S1. Outline of the study design for the identification of candidate coding genes, classifier development in two test cohorts and subsequent validation in six published cohorts.

2. r=0.76
P<0.001
r=0.53
r=0.72
r=0.55
r=0.77
r=0.56
r=0.71
r=0.97
r=0.58
r=0.92
r=0.22
P=0.025
r=0.64
r=0.84
r=0.87
r=0.45
r=0.49
r=0.88
r=0.65
r=0.51
P<0.001
Supplementary Figure S2. Technical validation of the HT array 2.0 experiments showing Pearson’s correlation between HT array 2.0 expression values and qRT-PCR expression values for each across all tumors that were examined.

3. Japan cohort stage I NCI-MD/Norway cohort stage IB
NCI-MD/Norway cohort
stage I
Supplementary Figure S3. Kaplan-Meier analysis of the two-gene classifier in stage I lung SCC in (A) Japan cohort (N=59, 5 year RFS) and (B) NCI-MD/Norway cohort (N=50, 5-year cancer-specific mortality).

4. US-MD Anderson cohort : stage I+IIB
Korea cohort: stage I+II
Supplementary Figure S4. Kaplan-Meier analysis of the two-gene classifier in (A) early stage (stage I+II) (N = 46, 5-year RFS) of US-MD Anderson cohort, (B) early stage (stage I+II)(N = 57, 5-year RFS) of Korea cohort.

5. (Korea, US-MD Anderson) (France, Sweden, US-Duke, US-Michigan)
Combined two cohorts
Stage I B
(France, Sweden, US-Duke, US-Michigan)
Combined four cohorts
Stage I
Supplementary Figure S5. Kaplan-Meier analysis of the two-gene classifier in stage Ilung SCC in (A) combined two published cohorts that reported RFS outcome(N = 75, 5-year RFS) and (B) combined four published cohort that reported OS outcome (N = 192, 5-year OS).

6. A
Group A
Group B
Group C
non-relapse
relapse B
Patients at risk
Group A
Group B
Group C
Supplementary Figure S6. Transcription signature associated with ACTN4 and DUSP6 identifies patients at high risk for recurrence. (A) Hierarchical clustering of patients (columns) and transcripts (rows) based on 1,563 transcripts differentially expressed between tumors with High or Low expression of both of ACTN4 and DUSP6. (B) Kaplan-Meier analysis for relapse-free survival according to the three groups obtained by clustering.

7. -log (P-value)
DUSP
ACTN4
ACTN4 DUSP6
Supplementary Figure S7. Canonical Pathways associated with High expression of ACTN4, DUSP6 or both in patient tumors, revealed by Ingenuity Pathway Analysis (IPA).