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Journal of Thoracic Disease logoLink to Journal of Thoracic Disease
. 2015 Aug;7(8):1398–1405. doi: 10.3978/j.issn.2072-1439.2015.07.25

Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma

Cheng Zhan 1, Li Yan 2, Lin Wang 1, Yang Sun 3, Xingxing Wang 4, Zongwu Lin 1, Yongxing Zhang 1, Yu Shi 1,, Wei Jiang 1,, Qun Wang 1
PMCID: PMC4561256  PMID: 26380766

Abstract

Background

Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy.

Methods

Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining.

Results

A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers.

Conclusions

The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data.

Keywords: Lung cancer, immunohistochemical marker, receiver operating characteristic (ROC) curve analysis, The Cancer Genome Atlas (TCGA)

Introduction

As the most frequently diagnosed cancer and the leading cause of tumor death, lung cancer was estimated to account for more than 1.8 million new cases and nearly 1.6 million deaths worldwide in 2012, with a sharp rising from 2008 (1,2). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the two major pathologic subtypes of lung cancer, constituting the vast majority of diagnosed lung cancers, but there are a lot of differences in their molecular profiling and characteristics, as well as therapeutic methods (3-5). Therefore, to accurately distinguish these two subtypes is important for the diagnosis and treatment of lung cancer.

Recently the main method used to distinguish LUAD and LUSC is hematoxylin-eosin (HE) staining of the tumor tissue sections observed under a light microscope. But in tumors with unclear structures caused by low differentiation, necrosis, or serious extrusion, small biopsies or cytologies with a limited number of tumor cells, it is difficult to make a precise diagnosis relying on HE staining alone. At this time, combining immunohistochemical results can refine the diagnosis, thus immunohistochemical staining is now recommended and widely applied in clinical practices (4-6).

At present, there are a number of reliable immunohistochemical markers that have been adopted to distinguish LUAD from LUSC, including thyroid transcription factor-1 (TTF-1, also called NKX2-1), napsin-A (NAPSA), tumor protein p63 (TP63), and cytokeratin (CK) 5/6 (3-5,7-10). These markers are highly sensitive, specific, and can be easily detected, the expression is significantly different between LUAD and LUSC. However, due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher sensitivity, specificity and application value. In the current study, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we identified and validated a number of genes which can be used as candidate immunohistochemical markers in distinguishing LUAD from LUSC.

Materials and methods

Ethics statement

This study was approved by the Ethics Committee of Zhongshan Hospital, Fudan University, Shanghai, China (Approval No. 2014-101). All work conformed to the provisions of the Declaration of Helsinki. Written informed consent was obtained from all patients participating in this research at the time of hospitalization.

Data acquisition and differently expressed gene screening

Level 3 RNA sequencing (RNA-Seq) V2 data of human LUAD and LUSC samples, which was released by TCGA before April 15, 2014, were obtained from the TCGA data portal (https://tcga-data.nci.nih.gov/tcga/tcgaHome2.jsp), including 490 LUAD samples and 490 LUSC samples. RNA-Seq by expectation maximization (RSEM) values were used to represent the levels of expression of these genes. The data are presented as means and standard deviations (SD).

All genes recorded in the TCGA data were filtered using the following criteria:

  1. mean (LUAD) ≥1,000 and mean (LUAD)/mean (LUSC) ≥4;

  2. mean (LUSC) ≥1,000 and mean (LUSC)/mean (LUAD) ≥4.

Here, mean (LUAD) and mean (LUSC) denote the mean of the RSEM value of the gene in the LUAD and LUSC samples, respectively. When a gene met one of the two conditions above, it was then entered in the subsequent analyses. Through these criteria, we attempted to identify those genes which were highly elevated and could be easily detected, with tremendous differences between the LUAD and LUSC samples.

Patient selection

Fifty patients with LUAD who underwent curative surgery between Jan 1 and Feb 19, 2014, and 50 other patients with LUSC who underwent curative surgery between Jan 1 and Apr 25, 2014, in the Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, were included in this research. All of the cases were clearly confirmed by pathologic evaluation. Immunohistochemistry results of TTF1, CK7, NAPSA, surfactant protein A (SPA), TP63, HCK proto-oncogene, Src family tyrosine kinase (HCK) and P40 in the specimens were obtained from the pathologists’ original reports. Sections of paraffinembedded tumor tissues were obtained from all cases involved.

Immunohistochemistry

Immunohistochemical staining was performed using an EnVisionTM HRP-polymer anti-mouse/rabbit IHC Kit (KeyGEN BioTECH, Nanjing, Jiangsu, China) according to the manufacturer’s guidelines. Briefly, the primary antibodies specific for melanophilin (MLPH, 1:100 dilution), transmembrane channel-like 5 (TMC5, 1:100 dilution), surfactant associated 3 (SFTA3, 1:100 dilution), desmoglein 3 (DSG3, 1:100 dilution), desmocollin 3 (DSC3, 1:100 dilution) and calmodulin-like 3 (CALML3, 1:100 dilution) were applied to detect the expressions of these genes. Stained specimens were then viewed independently at 100× independently by two investigators. Expression of these genes was determined by semiquantitatively assessing the percentage of marked tumor cells and the staining intensity as previously reported (11,12). Finally, we separated the specimens according to expression in four groups (negative, weak, moderate, and strong).

The primary antibodies [anti-MLPH (HPA014685), anti-TMC5 (HPA042037), anti-SFTA3 (HPA059427), anti-DSC3 (HPA049265) and anti-CALML3 (HPA044999)] were obtained from Sigma-Aldrich (St. Louis, MO, USA). Anti-DSG3 (ab183743) was obtained from Abcam (Cambridge, MA, USA).

Statistical analysis

Data were analyzed using IBM SPSS for Windows, version 20 (Armonk, NY, USA). ROC curve analysis was used to identify the candidate genes for distinguishing LUAD from LUSC. The Mann-Whitney U test was used to evaluate the differences in genes and markers between LUAD and LUSC samples.

Results

After differently expressed gene screening, 228 genes were filtered out for the next analysis. One hundred and ten genes were elevated in LUAD compared with LUSC, the other 118 genes were upregulated in LUSC (Tables S1 and S2).

Then, ROC curve analysis was used to evaluate the effectiveness of these 228 genes when applied to distinguish LUAD from LUSC based on the TCGA data (Tables S1 and S2). Part of the genes with the highest area under curve (AUC) values in LUAD and LUSC can be found in Tables 1 and 2, respectively. The higher AUC value is indicative of greater sensitivity and specificity. MLPH, SFTA2, TMC5, SFTA3, DSG3, KRT5, DSC3 and CALML3 rank highest in these two tables.

Table 1. Fifteen genes greatly elevated in LUAD with highest AUC values.

Gene LUAD LUSC Fold-change (LUAD/LUSC) AUC value
MLPH 3,961±3,315 521±769 7.60 0.953
SFTA2 2,833±3,115 161±327 17.59 0.946
TMC5 3,045±2,381 428±646 7.11 0.943
SFTA3 3,073±2,704 271±761 11.33 0.937
DDAH1 2,446±1,405 544±462 4.50 0.934
RORC 1,213±952 130±232 9.31 0.933
TMEM125 1,873±1,362 297±351 6.29 0.931
SMPDL3B 1,482±1,421 238±284 6.22 0.930
ALDH3B1 2,509±2,619 378±646 6.62 0.930
ACSL5 4,050±3,178 604±775 6.70 0.926
NKX2-1 3,246±2,233 309±940 10.50 0.926
ATP11A 7,025±5,571 1,356±1,261 5.18 0.924
CGN 3,626±2,448 796±777 4.55 0.922
FMO5 1,174±1,575 86±136 13.51 0.921
MUC1 22,301±16,816 3,137±3,945 7.11 0.921

LUAD, lung adenocarcinoma; AUC: area under curve; LUSC: lung squamous cell carcinoma.

Table 2. Fifteen genes greatly elevated in LUSC with highest AUC values.

Gene LUAD LUSC Fold-change (LUSC/LUAD) AUC value
DSG3 88±777 8,728±8,556 98.77 0.973
KRT5 1,227±10,342 116,689±96,742 95.03 0.972
DSC3 128±789 7,515±6,291 58.62 0.970
CALML3 141±1,096 10,039±11,031 71.17 0.964
SERPINB13 22±191 2,166±3,217 95.70 0.956
KRT6B 310±1,208 17,808±27,334 57.45 0.954
KRT6C 136±529 7,372±12,063 54.13 0.954
KRT6A 2,297±8,724 87,096±81,359 37.91 0.951
PVRL1 1,204±1,177 11,200±7,063 9.30 0.950
LOC642587 59±213 1,247±1,247 20.99 0.949
PERP 6,258±4,951 31,500±21,939 5.03 0.947
TP63 325±914 10,976±9,139 33.72 0.946
TRIM29 861±1,930 11,291±7,291 13.10 0.945
ATP1B3 1,866±1,138 9,231±6,592 4.94 0.945
FAT2 125±383 3,737±3,587 29.82 0.943

LUSC: lung squamous cell carcinoma; AUC: area under curve; LUAD, lung adenocarcinoma.

Because the appropriate primary antibody of human SFTA2 could not be obtained when we performed this study, and KRT5 is one part of CK5/6 which has been frequently used to distinguish the subtypes of lung cancer, we selected MLPH, TMC5, SFTA3, DSG3, DSC3, and CALML3 for the next immunohistochemical staining. As Figure 1 and Figure 2 show, the expression distribution profiles of these six genes were quite different in LUAD and LUSC, and the sensitivity and specificity for distinguishing between the two types of lung cancer was high.

Figure 1.

Figure 1

The distribution of expression of the six genes in LUAD and LUSC. LUAD, lung adenocarcinoma; LUSC: lung squamous cell carcinoma.

Figure 2.

Figure 2

The ROC curves of the six genes when they were used in distinguishing LUAD from LUSC. (A) The ROC curves of MLPH, TMC5, and SFTA3; (B) the ROC curves of DSG3, DSC3, and CALML3. ROC, receiver operating characteristic; LUAD, lung adenocarcinoma; LUSC: lung squamous cell carcinoma.

As Figure 3 and Table 3 show, the results of immunohistochemical staining further confirmed the elevation of MLPH, TMC5, and SFTA3 in LUAD, and DSG3, DSC3, and CALML3 in LUSC. Then the immunohistochemical results were compared to the markers used in our hospital clinic; the staining scores were obtained from the pathologists’ original reports. As Table 3 shows, the sensitivity and specificity of the six genes could be more than 80% and higher than some markers frequently used.

Figure 3.

Figure 3

The immunohistochemical staining results of the six genes in LUAD and LUSC. Scale bar: 50 µm. LUAD, lung adenocarcinoma; LUSC: lung squamous cell carcinoma.

Table 3. The immunohistochemical staining results.

Gene and markers LUAD
LUSC
P value Threshold
(LUAD/LUSC)
Sensitivity (%) Specificity (%)
Negative Weak Moderate Strong Negative Weak Moderate Strong
LUAD
MLPH 1 20 23 6 44 5 1 0 <0.001 weak/negative 98 88
TMC5 2 17 31 0 43 7 0 0 <0.001 weak/negative 96 86
SFTA3 0 6 39 5 38 12 0 0 <0.001 weak/negative 88 100
TTF1 0 24 21 5 44 6 0 0 <0.001 weak/negative 100 88
CK7 0 11 28 11 42 5 3 0 <0.001 weak/negative 100 84
NAPSA 3 39 5 3 47 3 0 0 <0.001 weak/negative 94 94
SPA 24 26 0 0 47 3 0 0 <0.001 weak/negative 52 94
LUSC
DSG3 40 10 0 0 5 11 29 5 <0.001 negative/weak 90 98
DSC3 35 12 3 0 5 9 24 12 <0.001 negative/weak 90 97
CALML3 38 11 1 0 0 5 17 28 <0.001 weak/moderate 90 98
TP63 41 9 0 0 3 24 20 3 <0.001 negative/weak 94 86
HCK 3 37 10 0 0 7 13 30 <0.001 weak/moderate 86 80
P40 50 0 0 0 17 33 0 0 <0.001 negative/weak 66 100

The staining scores of TTF1, CK7, NAPSA, SPA, TP63, HCK and P40 were obtained from the pathologists’ original reports. The threshold indicates the criteria to distinguish LUAD from LUSC when the sum of the sensitivity and specificity reaches a peak. e.g., “weak/negative” means if the sample’s staining score ranks from weak to strong it will be identified as LUAD, and negative as LUSC. LUAD, lung adenocarcinoma; LUSC: lung squamous cell carcinoma.

Discussion

Combining differently expressed gene screening and ROC curve analysis, we identified the differently expressed genes with the highest AUC values based on TCGA data, which might be suitable to be applied as markers in distinguishing LUAD from LUSC. To validate our analyses, the expression of six candidate genes was detected in lung cancer samples by immunohistochemical staining. The staining results confirmed the potentials of these six genes in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data.

Our analyses revealed that the expression distribution profiles of MLPH, TMC5, SFTA3, DSG3, DSC3, and CALML3 were markedly different between LUAD and LUSC, and their sensitivity and specificity were not less than many commonly used markers. And we believed that the sensitivity and specificity would be improved after wide use in clinical practices. DSG3 and DSC3 are both transmembrane glycoproteins that belong to calcium-dependent cell adhesion molecules, and their diagnostic values in distinguishing LUSC from LUSC have been frequently reported (13-18). DSG3 and DSC3 are also greatly elevated in other squamous tumors and reduced in many other adenocarcinomas (19-21). The downregulation of DSG3 and DSC3 is in part due to DNA methylation and associated with poor prognosis in tumors (13,15,22-24). Although our results showed the potential diagnostic abilities of MLPH, TMC5, SFTA3, and CALML3, their expressions and functions in lung cancer have received little attention and remain unclear.

Most of the genes recommended as markers in distinguishing LUAD from LUSC also ranked tops in our tables according to the order of the AUC values, such as TTF-1 (NKX2-1), NAPSA, TP63 and S100 calcium binding protein A7 (S100A7) (Tables 1, 2, S1, and S2) (4-6). Another commonly used marker, CK5/6, detects the proteins coded by keratin (KRT) 5, KRT6A, and KRT6B, all three genes ranked high in Table 2 (4-6). Many other genes ranked high in our tables such as mucin 1 (MUC1), carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6), tripartite motif containing 29 (TRIM29) and S100 calcium binding protein A2 (S100A2), were also reported that they could be used in distinguishing LUAD from LUSC (17,25,26).

With the rapid development of microarrays and RNA-Seq in recent years, more and more high-throughput data have been accumulated. How to effectively identify suitable biomarkers from these data for disease diagnosis and sub-classification is now receiving a lot of attention. Therefore, we hope our method to investigate candidate markers by combing differently expressed gene screening and ROC curve analysis, will be widely applied and further improved in the future.

Acknowledgements

The results published here are based upon data generated by the TCGA Research Network (http://cancergenome.nih.gov/).

Funding: This analysis is supported by the National Natural Science Foundation of China (Grant Nos. 81401875, 81472225) (http://www.nsfc.gov.cn/) and the Natural Science Foundation of Shanghai, China (Grant No. 14ZR1406000) (http://www.stcsm.gov.cn/).

Supplementary

Table S1. The ROC curve analyze results of genes greatly elevated in LUAD.

Gene LUAD LUSC Fold-change (LUAD/LUSC) AUC value
MLPH 3,961±3,315 521±769 7.60 0.953
SFTA2 2,833±3,115 161±327 17.59 0.946
TMC5 3,045±2,381 428±646 7.11 0.943
SFTA3 3,073±2,704 271±761 11.33 0.937
DDAH1 2,446±1,405 544±462 4.50 0.934
RORC 1,213±952 130±232 9.31 0.933
TMEM125 1,873±1,362 297±351 6.29 0.931
SMPDL3B 1,482±1,421 238±284 6.22 0.930
ALDH3B1 2,509±2,619 378±646 6.62 0.930
ACSL5 4,050±3,178 604±775 6.70 0.926
NKX2-1 3,246±2,233 309±940 10.50 0.926
ATP11A 7,025±5,571 1,356±1,261 5.18 0.924
CGN 3,626±2,448 796±777 4.55 0.922
FMO5 1,174±1,575 86±136 13.51 0.921
MUC1 22,301±16,816 3,137±3,945 7.11 0.921
KCNK5 1,458±1,260 212±262 6.86 0.921
PRR15L 1,306±1,207 187±334 6.96 0.915
SLC44A4 2,905±2,552 387±636 7.50 0.907
CLDN3 2,127±2,016 356±930 5.97 0.907
ST3GAL5 1,751±1,535 318±304 5.49 0.906
CD55 9,112±9,307 2,068±2,001 4.41 0.898
LPCAT1 17,427±17,015 3,703±5,206 4.71 0.895
CEACAM6 41,068±39,526 4,992±11,717 8.23 0.889
SELENBP1 4,213±4,536 697±820 6.04 0.889
GPR116 5,436±5,921 842±1,175 6.46 0.887
SLC34A2 42,409±40,305 5,358±10,219 7.91 0.886
HPN 1,351±1,788 219±406 6.16 0.885
TESC 1,759±3,143 126±754 13.92 0.882
PLEKHA6 1,199±943 269±402 4.45 0.882
FOLR1 3,586±4,963 305±641 11.76 0.881
NAPSA 35,629±37,838 3,240±6,098 11.00 0.879
LMO3 2,516±2,520 318±722 7.91 0.878
STEAP4 4,339±4,707 753±1,528 5.76 0.877
B3GNT7 2,440±3,524 421±761 5.79 0.875
VSTM2L 1,714±2,342 213±496 8.03 0.874
MUC21 2,461±4,873 103±613 23.87 0.873
RHOBTB2 3,058±3,121 731±806 4.18 0.873
DPP4 3,010±3,391 389±1,004 7.74 0.872
MACC1 1,519±1,287 369±402 4.12 0.872
ABCC3 5,208±3,908 1,169±1,428 4.45 0.869
FGL1 1,227±4,239 50±553 24.17 0.868
SPINK1 3,748±10,070 134±1,321 27.86 0.868
C16orf89 5,412±8,524 326±626 16.60 0.866
ATP8A1 1,186±1,289 289±329 4.10 0.863
AHCYL2 3,891±4,065 782±626 4.97 0.861
CYP2B7P1 3,261±9,555 259±714 12.58 0.856
PON3 1,042±1,294 235±662 4.43 0.855
TMPRSS2 2,486±2,505 565±827 4.40 0.853
AGR2 11,318±15,822 1,998±3,064 5.66 0.852
C1orf116 5,471±5,568 931±814 5.88 0.850
C4orf31 1,549±1,809 301±725 5.13 0.850
RNASE1 13,190±15,196 2,749±2,810 4.80 0.846
ALPK3 1,139±1,068 224±372 5.08 0.846
HOPX 7,935±12,980 1,136±1,974 6.98 0.845
DPCR1 1,687±14,092 17±40 99.16 0.835
C5orf4 1,037±1,551 230±450 4.51 0.834
XAGE1D 3,375±4,395 413±1,514 8.16 0.817
SLC26A9 1,281±2,386 116±229 10.99 0.816
TREM1 1,139±1,735 248±357 4.58 0.807
C4BPA 5,525±10,596 733±1,371 7.53 0.807
CLIC6 3,400±3,554 658±1,120 5.16 0.806
RASD1 2,210±3,304 393±728 5.62 0.800
SFTPB 195,735±252,122 29,275±45,424 6.69 0.799
TSPAN8 2,050±5,256 220±659 9.32 0.799
AGR3 1,328±1,793 205±376 6.47 0.799
SUSD2 4,164±7,302 600±1,568 6.93 0.790
MFSD4 1,158±1,461 172±214 6.72 0.790
PIGR 20,188±41,363 1,719±3,039 11.74 0.788
HPGD 2,926±6,201 489±1,115 5.98 0.788
FGB 5,412±24,204 312±3,894 17.32 0.788
MSLN 10,685±21,563 1,039±6,275 10.28 0.785
SERPINA1 24,209±47,249 5,747±8,054 4.21 0.781
GCNT3 1,071±2,121 195±496 5.47 0.777
MUC5B 22,738±53,189 1,754±8,646 12.96 0.775
FGA 8,319±35,185 500±4,168 16.61 0.772
TFPI2 3,447±14,530 525±4,287 6.56 0.764
ALOX15B 1,444±2,164 327±623 4.41 0.763
AMY1A 1,596±6,215 220±473 7.25 0.754
HLA-DQB2 1,216±3,432 259±462 4.70 0.751
CLDN2 1,224±4,183 63±287 19.17 0.748
PGC 33,835±138,066 389±1,462 86.86 0.748
PPP1R1B 1,452±2,143 299±789 4.85 0.747
CACNA2D2 1,313±2,012 221±376 5.93 0.746
AQP5 1,562±3,262 125±322 12.49 0.745
FGG 10,438±37,227 1,092±7,279 9.55 0.739
PAEP 1,822±6,186 78±975 23.27 0.738
CTSE 6,809±12,689 1,058±1,650 6.44 0.735
MUC13 1,434±3,740 175±955 8.16 0.731
AZGP1 2,531±6,377 583±3891 4.34 0.730
CEACAM5 20,407±34,340 4,095±12,219 4.98 0.723
SLC7A2 2,658±4,735 515±909 5.16 0.723
CYP4B1 2,242±4,144 444±875 5.05 0.721
LGALS4 1,133±4,373 17±96 64.50 0.715
TFF3 3,040±8,131 457±1,565 6.65 0.713
VSIG1 1,259±4,284 73±352 17.04 0.712
SCGB3A1 10,328±58,644 585±1,433 17.63 0.711
CRLF1 2,809±6,631 319±1,329 8.80 0.695
S100P 5,442±10,667 1,111±3,795 4.90 0.693
GPR110 1,332±1,797 306±564 4.34 0.688
PLUNC 10,603±42,374 851±3,069 12.46 0.683
MUC6 1,217±8,355 75±611 16.22 0.681
CALCA 3,578±19,341 224±3,022 15.96 0.679
SCGB3A2 8,546±23,575 1,224±2,096 6.98 0.670
CLDN18 2,013±7,033 307±823 6.55 0.653
TFF1 1,249±5,541 34±230 36.46 0.647
CPS1 5,079±15,544 436±3515 11.63 0.593
HP 4,502±22,250 1,056±2,141 4.26 0.591
PCSK2 1,817±10,039 100±397 18.01 0.568
MSMB 1,343±7,980 175±874 7.67 0.560
PCSK1 1,049±6,553 142±1,047 7.36 0.340

ROC, receiver operating characteristic; LUAD, lung adenocarcinoma; LUSC: lung squamous cell carcinoma; AUC: area under curve.

Table S2. The ROC curve analyze results of genes greatly elevated in LUSC.

Gene LUAD LUSC Fold-change (LUSC/LUAD) AUC value
DSG3 88±777 8,728±8,556 98.77 0.973
KRT5 1,227±10,342 116,689±96,742 95.03 0.972
DSC3 128±789 7,515±6,291 58.62 0.970
CALML3 141±1,096 10,039±11,031 71.17 0.964
SERPINB13 22±191 2,166±3,217 95.70 0.956
KRT6B 310±1,208 17,808±27,334 57.45 0.954
KRT6C 136±529 7,372±12,063 54.13 0.954
KRT6A 2,297±8,724 87,096±81,359 37.91 0.951
PVRL1 1,204±1,177 11,200±7,063 9.30 0.950
LOC642587 59±213 1,247±1,247 20.99 0.949
PERP 6,258±4,951 31,500±21,939 5.03 0.947
TP63 325±914 10,976±9,139 33.72 0.946
TRIM29 861±1,930 11,291±7,291 13.10 0.945
ATP1B3 1,866±1,138 9,231±6,592 4.94 0.945
FAT2 125±383 3,737±3,587 29.82 0.943
CLCA2 87±691 6,787±7,536 77.23 0.943
SPRR2A 43±546 4,036±8,211 93.51 0.940
JAG1 1,118±1,157 7,365±7,830 6.58 0.939
KRT14 315±3,191 26,428±57,383 83.77 0.939
SERPINB5 358±904 4,421±3,570 12.32 0.937
KRT13 225±2,423 18,866±41,338 83.76 0.934
CSTA 190±403 4,222±5,543 22.20 0.934
PKP1 882±2,176 19,788±16,151 22.42 0.934
DAPL1 15±102 1,098±1,932 69.02 0.933
IRF6 647±369 3,108±1,757 4.80 0.932
KRT16 310±1,070 17,386±35,463 56.03 0.932
SLC6A8 965±1,028 7,254±5,830 7.52 0.929
SPRR2E 13±179 1,158±3,196 84.41 0.929
A2ML1 106±1,345 1,717±3,166 16.10 0.929
GPC1 1,375±1,171 9,223±8,003 6.71 0.926
HR 60±115 1,104±1,530 18.30 0.923
KRT17 2,926±8,839 62,551±69,399 21.37 0.921
COL7A1 442±945 5,390±5,665 12.17 0.919
SLC2A1 4,007±4,652 23,021±18,217 5.74 0.918
ANXA8 240±740 3,194±3,237 13.30 0.916
PTHLH 149±307 3,642±5,287 24.41 0.914
GBP6 71±203 2,247±2,528 31.33 0.913
ABCC5 1,037±1,012 7,355±7,806 7.09 0.912
SPRR1A 36±250 2,333±4,852 63.44 0.912
SNAI2 255±444 1,149±731 4.49 0.911
SLC16A1 597±1,019 2,486±1,753 4.16 0.910
TFRC 3,415±3,639 18,175±19,185 5.32 0.910
FOXE1 80±276 1,593±1,939 19.72 0.908
BMP7 172±530 1,843±1,470 10.70 0.907
ITGA6 1,937±3,063 8,650±7,228 4.46 0.906
NTRK2 173±794 7,764±9,701 44.79 0.905
ST6GALNAC2 287±316 1,438±978 5.00 0.904
CELSR2 487±386 2,204±1,814 4.53 0.904
ODZ2 29±146 1,147±1,729 38.99 0.904
ADAM23 26±90 1,535±2,091 57.10 0.902
GJB6 96±265 2,657±4,069 27.65 0.899
ANXA8L2 133±347 1,201±1,194 8.99 0.897
LGALS7 33±147 1,397±3,297 41.66 0.897
S100A7 79±824 2,320±11,972 29.29 0.896
RHCG 62±554 2,294±5,834 36.71 0.894
NRARP 217±196 1,068±1,082 4.92 0.894
S100A2 1,037±4,073 14,533±20,550 14.01 0.890
ADH7 71±513 2,704±3,930 37.83 0.887
LYPD3 428±839 3,478±4,530 8.12 0.886
SPRR3 75±497 4,179±9,702 55.54 0.884
COL4A5 312±414 1,956±2,391 6.26 0.884
CXCR7 609±1,045 4,107±4,471 6.74 0.883
C3orf58 458±333 1,881±1,718 4.10 0.883
PTPRZ1 222±538 2,422±2,239 10.88 0.882
GPR87 239±399 1,358±1,159 5.68 0.881
RAPGEFL1 302±456 1,882±1,782 6.22 0.880
UGT1A7 8±77 1,054±2,247 128.92 0.880
SPRR2D 87±428 2,165±4,477 24.63 0.878
SPRR1B 178±777 3,747±6,231 20.96 0.878
KRT15 1,280±4,508 20,918±28,994 16.33 0.878
PI3 352±4431 5,523±12,731 15.67 0.876
SFN 3,844±3,146 17,013±14,551 4.43 0.876
FABP5 157±305 1,443±2,707 9.15 0.876
RBP1 360±732 2,217±3,706 6.15 0.873
DST 2,550±2,332 10,378±8,529 4.07 0.873
PITX1 329±586 2,003±2,523 6.08 0.870
FAM84A 302±428 1,341±1,198 4.44 0.865
UPK1B 266±1,452 2,995±5,424 11.24 0.864
ADM 503±728 2,123±2,249 4.22 0.862
SOX2 479±830 43,21±4,483 9.02 0.862
CLDN1 2,085±3,554 15,300±19,672 7.34 0.861
MAGEA4 323±2,589 2,327±4,114 7.19 0.860
NDUFA4L2 632±1,412 4,587±5,094 7.25 0.860
SERPINB4 78±380 1,223±3,002 15.63 0.853
FGFBP1 236±491 2,053±2,791 8.70 0.851
SERPINB3 344±1,591 3,359±6,296 9.75 0.848
NTS 1,909±15,405 8,452±21,005 4.43 0.846
FGFR2 547±653 2,244±2,092 4.10 0.845
RGMA 233±383 1,250±1,463 5.35 0.841
ALDH3B2 288±450 1,176±1,362 4.08 0.838
CYP2S1 568±775 3,034±2,938 5.33 0.833
GPNMB 6,752±7,084 30,334±47,047 4.49 0.831
NDRG4 172±226 1,102±1,372 6.39 0.825
GJB2 862±1,422 6,171±10,796 7.15 0.820
ABCA13 257±471 1,296±1,327 5.04 0.812
FBN2 154±1,446 1,750±3,324 11.34 0.812
CRYAB 187±291 1,272±4,611 6.80 0.811
MMP10 194±1,193 3,002±7,273 15.47 0.808
NRCAM 221±609 1,241±1,578 5.61 0.806
HAS3 1,028±1,839 4,158±4,225 4.04 0.804
IL1RN 449±537 2,017±2,468 4.49 0.804
S100A8 1,344±8,937 1,1440±28,668 8.51 0.802
CNTNAP2 164±561 1,116±1,722 6.78 0.798
COL17A1 1,339±3,023 6,832±10,661 5.10 0.797
AKR1B10 2,145±7,972 9,111±13,901 4.25 0.794
WNT5A 633±563 2,606±2,816 4.12 0.789
CYP4F3 141±485 1,153±1,964 8.14 0.773
LY6D 214±729 3,033±6,896 14.13 0.765
ALDH3A1 1,848±7,693 8,124±17,776 4.40 0.759
IVL 207±501 1,093±2,097 5.26 0.758
CYP4F11 271±579 2,195±3,752 8.09 0.725
GSTM2 458±496 2,044±3,044 4.46 0.703
GSTM3 609±941 2,866±4,641 4.70 0.696
GPC3 540±1,255 2,291±3,642 4.24 0.684
KRT4 228±1,156 2,160±9,487 9.45 0.644
OLFM1 248±296 1,325±2,310 5.33 0.642
GSTM1 257±559 1,626±4,391 6.32 0.557
C4orf7 87±314 1,896±12,269 21.63 0.530

ROC, receiver operating characteristic; LUSC: lung squamous cell carcinoma; LUAD, lung adenocarcinoma; AUC: area under curve.

Footnotes

Conflicts of Interest: The authors have no conflicts of interest to declare.

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