Cancer Biol Med 2020. doi: 10.20892/j.issn.2095-3941.2019.0279

ORIGINAL ARTICLE

Identification of a potential tumor suppressor gene, UBL3, in non-small cell lung cancer

Xinchun Zhao1,2,3, Yongchun Zhou4, Qian Hu2,5, Sanhui Gao2,3, Jie Liu2,3, Hong Yu2,5, Yanfei Zhang2,3, Guizhen Wang2,3, Yunchao Huang4, Guangbiao Zhou2,3

1School of Life Sciences, University of Science and Technology of China, Hefei 230026, China; 2State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; 3State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; 4Department of Thoracic Surgery, the Third Affiliated Hospital of Kunming Medical University, Kunming 650106, China; 5School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China

ABSTRACT Objective: Oncogenes have been shown to be drivers of non-small cell lung cancer (NSCLC), yet the tumor suppressing genes

involved in lung carcinogenesis remain to be systematically investigated. This study aimed to identify tumor suppressing ubiquitin

pathway genes (UPGs) that were critical to lung tumorigenesis.

Methods: The 696 UPGs were silenced by an siRNA screening in NSCLC cells; the potential tumor suppressing UPGs were analyzed,

and their clinical significance was investigated.

Results: We reported that silencing of 11 UPGs resulted in enhanced proliferation of NSCLC cells, and four UPGs (UBL3, TRIM22,

UBE2G2, and MARCH1) were significantly downregulated in tumor samples compared to that in normal lung tissues and their

expression levels were positively associated with overall survival (OS) of NSCLC patients. Among these genes, UBL3 was the most

significant one. UBL3 expression was decreased in tumor samples compared to that in paired normal lung tissues in 59/86 (68.6%)

NSCLCs, was correlated with TNM stage and sex of NSCLC patients, and was significantly higher in non-smoking patients than

in smoking patients. Silencing UBL3 accelerated cell proliferation and ectopic expression of UBL3 suppressed NSCLC in vitro and

in vivo.

Conclusions: These results showed that UBL3 represented a tumor suppressor in NSCLC and may have potential for use in

therapeutics and for the prediction of clinical outcome of patients.

KEYWORDS Lung cancer; ubiquitin pathway genes; UBL3; tumor suppressor; prognosis

Introduction

Lung cancer is the most common cause of cancer-related

mortality, which kills 1.8 million people worldwide each

year1. Lung cancer comprises small cell lung cancer (SCLC)

and non-small cell lung cancer (NSCLC). NSCLC divides

into large cell carcinoma, lung adenocarcinoma (LUAD),

and lung squamous cell carcinoma (LUSC)2. Comprehensive

sequencing efforts over the past decade have confirmed that

lung cancer is a disease of the genome3-5. Abnormalities in

oncogenes and tumor suppressors act as drivers to initiate the

onset and progression of NSCLCs. However, druggable driver

molecules are found in only a minority of patients; hence,

efforts should be made to uncover the driver genes in the

majority of lung cancers2.

The ubiquitin (Ub)-dependent modification system is

one of the protein degradation systems within the cell and is

involved in a variety of cellular processes. In this process, Ub

is activated by a Ub-activating enzyme, E1, and transferred

to a Ub-conjugating enzyme, E2, which attaches Ub to a tar-

get protein through the ε-amino group of a lysine residue

with the help of a Ub-protein ligase, E3. The ubiquitinated

target protein is then recognized and degraded by the 26S

proteasome6. Ub-like proteins (UBLs) usually have a UBL

domain and have been reported to act as post-translational

Correspondence to: Guangbiao ZhouE-mail: gbzhou@cicams.ac.cnORCID ID: https://orcid.org/0000-0002-6327-2316Received August 11, 2019; accepted October 24, 2019.Available at www.cancerbiomed.org©2020 Cancer Biology & Medicine. Creative Commons Attribution-NonCommercial 4.0 International License

Cancer Biol Med Vol 17, No 1 February 2020 77

modifiers. The modification of proteins by UBLs proceeds

through an enzyme cascade similar to that used by Ub. As

most UBLs have far fewer known substrates than are known

for Ub, they require a more limited number of E2-type conju-

gating enzymes and E3-type ligases7. Small Ub-like modifier

(SUMO)8 and neuronal precursor cell-expressed develop-

mentally downregulated protein-8 (Nedd8)9 are two well-

known UBLs and have been reported to play important roles

in cancer. Both SUMO and Nedd8 are two well-studied UBLs:

SUMO is involved in several cellular activities, including cell

cycle control, nuclear transport and responses to viral infec-

tions, and Nedd8 functions in the regulation of E3 ubiqui-

tin-protein ligases. These two UBLs are implicated in tum-

origenesis8,9. Some oncogenic Ub-pathway genes (UPGs)

have been reported in NSCLCs10-12, but the roles of tumor

suppressing UPGs in this deadly disease remain to be eluci-

dated. In this study, we conducted a systematic silencing of

the E1, E2, E3, and deubiquitinases in NSCLC cells to identify

tumor suppressing UPGs that were crucial for lung cancer cell

proliferation.

Materials and methods

Patient samples

The study was approved by the local Research Ethics

Committees of all the participating sites; all lung cancer sam-

ples were collected with informed consent. The diagnosis of

lung cancer was confirmed by at least two pathologists. Tissue

samples were obtained at the time of surgery and quickly fro-

zen in liquid nitrogen. Tumor samples contained a tumor cel-

lularity of greater than 60%, and the matched control samples

contained no tumor cells.

Cell culture and siRNA library

The NSCLC cell lines A549, H1975, and H460 were obtained

from the American Type Culture Collection (ATCC; Manassas,

VA, USA). These cells were cultured in Dulbecco’s Modified

Eagle’s Medium (DMEM) or Roswell Park Memorial Institute

(RPMI) 1640 medium supplemented with 10% fetal bovine

serum (FBS), 100 U/mL penicillin, and 100 μg/mL strepto-

mycin (GIBCO BRL, Grand Island, NY, USA). Human siG-

ENOME SMARTpool siRNA libraries, containing 696 UPGs

(Catalog numbers G-004705-05, G-005615-05, G-005625-05,

G-005635-05), were purchased from Thermo Scientific

Dharmacon (Lafayette, CO, USA). The small interfering RNAs

(siRNAs) were transfected into cells using DharmFECT trans-

fection reagent (#T-2001-01), and cell viability was assessed by

CellTiter-Glo Reagent (Promega, Fitchburg, WI, USA) accord-

ing to the manufacturer’s instructions. Each SMARTpool

experiment was performed in duplicate. The Z-score was cal-

culated as follows: z = (x − m)/s, where x is the raw score to be

standardized, m is the mean of the plate, and s is the standard

deviation (SD) of the plate13. The Z-score of a gene reflects its

requirement for cell proliferation, and a Z-score of ≤ -2 indi-

cates that the gene is required for cell proliferation; silencing

of the gene significantly inhibits cell proliferation. However, a

Z score of ≥ 2 indicates that the gene inhibits lung cancer cell

proliferation and that inhibition of the gene significantly pro-

motes cell proliferation.

Cell cycle

To assess the cell cycle distribution, cells were harvested and

washed in phosphate-buffered saline (PBS), fixed in 70%

ethanol and incubated at 4 °C overnight. Cells were centri-

fuged and washed with PBS containing 1% FBS, followed by

treatment with 1% RNase A for 15 min at 37 °C and staining

with 50 μg/mL propidium iodide (Sigma-Aldrich, St. Louis,

MO, USA). The fluorescence intensity was measured by flow

cytometry (FACSVantage Diva, BD Biosciences, San Jose, CA,

USA).

Antibodies

The antibodies used included mouse anti-β-actin (#A5441;

Sigma-Aldrich; 1:5000 for Western blot), mouse anti-HA

(#AE008; ABclonal, Cambridge, MA, USA; 1:2000 for Western

blot), rabbit anti-ubiquitin-like 3 (UBL3) (#A4028; Abclonal;

1:1000 for Western blot and 1:100 for immunohistochemistry

(IHC)), rabbit anti-Ki67 (#ab15580; Abcam, Cambridge, MA,

USA; 1:400 for IHC), rabbit anti-p27 (#sc-528; Santa Cruz

Biotechnology, Santa Cruz, CA, USA; 1:1000 for Western blot),

rabbit anti-Cyclin D1 (#2922; Cell Signaling Technology, Beverly,

MA, USA; 1:1000 for Western blot), and mouse anti-Cyclin E

(#4129; Cell Signaling Technology; 1:1000 for Western blot).

The siRNA and plasmid transfection

The siRNA was purchased from GenePharma Co.,

Ltd. (Shanghai, China), and the sequences were as fol-

lows: UUCUCCGAACGUGUCACGUTT (siNC);

78 Zhao et al. UBL3 in non-small cell lung cancer

GAGAGUAAUUGUUGUGUAA (#siUBL3-1); and

CGGCGGAUAUGAUAAAUUU (#siUBL3-2). The HA-UBL3

vector was constructed based on the pCS2 plasmid. Cells were

transfected with siRNA or plasmids using Lipofectamine 3000

reagent (Invitrogen, Carlsbad, CA, USA).

Lentivirus-mediated cell transfection and transduction

For lentiviral particle production, pCDH-UBL3 constructs

were co-transfected with psPAX2 and pMD2G into HEK293T

cells. The culture medium was replaced with fresh medium

after 6 h, and supernatant was harvested 48 h and 72 h

post-transfection. A549-luciferase cells were infected with

viral particles in the presence of 8 μg/mL Polybrene®. One

week after infection, cells were sorted by flow cytometry.

Western blot

Cells were lysed in RIPA buffer supplemented with protease

inhibitor cocktail (Sigma-Aldrich). Proteins (20 μg) were sub-

jected to 10%–15% sodium dodecyl sulfate polyacrylamide gel

electrophoresis (SDS-PAGE), electrophoresed, and transferred

to nitrocellulose membranes. After blocking with 5% nonfat

milk in Tris-buffered saline, membranes were washed and incu-

bated with the indicated primary and secondary antibodies.

Immunoreactions were detected using a Luminescence Image

Analyzer LAS 4000 (GE, Fairfield, CO, USA).

Animal studies

Animal studies were approved by the Institutional Review

Board of the Chinese Academy of Medical Sciences

Cancer Institute and Hospital, with the approval ID of

NCC2019A188. The methods were performed in accordance

with the approved guidelines. Six-week-old SCID-beige mice

were maintained under specific pathogen-free (SPF) condi-

tions. The mice were numbered, injected into the lateral tail

veins with A549-luciferase cells (5 × 105) stably expressing

pCDH-UBL3 or pCDH-control plasmid, and randomized

into groups (n = 13 per group). After 45 days, tumors were

monitored with the IVIS Spectrum Imaging System (Caliper

Life Sciences; Hopkinton, MA, USA). For IHC, sections

were fixed in formalin and embedded in paraffin, incubated

with primary antibodies overnight and incubated with the

indicated secondary antibodies. Immunoreactions were

detected using 3,3′-diaminobenzidine (DAB, Zhongshan

Golden Bridge Biotechnology Co., Ltd., Beijing, China) and

hematoxylin.

Online data availability

The Oncomine14 cancer microarray database (www.

oncomine.org), including the Hou Lung, Selamat Lung,

Su Lung, StearmanLung, Landi Lung, Okayama Lung, Lee

lung, Kuner Lung, and Zhu Lung datasets, with the accession

codes GSE19188, GSE32867, GSE7670, GSE2514, GSE10072,

GSE31210, GSE8894, GSE10245, and GSE14814, respectively,

were used. The transcriptome data and clinical data of 517

patients with LUAD and 501 patients with LUSC were down-

loaded from the Cancer Genomics Hub (https://xenabrowser.

net/datapages/). TCGA database was accessed using the acces-

sion code phs000178. The online survival analysis software

containing the microarray data of patients with NSCLC15

(http://kmplot.com/analysis/index.php?p=service&can-

cer=lung) was used. The correlation of UBL3 expression with

OS was evaluated by entering UBL3 into the database and ana-

lyzed by setting different clinical parameters, and the Kaplan-

Meier survival plots and log-rank P values were obtained from

the webpage. The baseline demographic characteristics of the

patients are shown by Gyorffy et al.15.

Statistical analysis

All statistical analyses were conducted using GraphPad Prism

7 (GraphPad Software, La Jolla, CA, USA). All experiments

were repeated at least three times, and the data were presented

as the mean ± SD unless otherwise noted. Differences between

groups of data were evaluated for significance using Student’s

t-test for unpaired data or one-way analysis of variance

(ANOVA). The survival curve for each group was estimated by

the Kaplan-Meier method and log-rank test. P values less than

0.05 indicated statistical significance.

Results

Identification of 11 tumor suppressing UPGs in NSCLCs

To systematically identify UPGs that are crucial for lung can-

cer cell proliferation, we conducted a systematic silencing of

the UPGs in NSCLC cell lines. The 696 siRNAs for UPGs in

the Dharmacon human siGENOME SMARTpool library were

Cancer Biol Med Vol 17, No 1 February 2020 79

transfected into the NSCLC lines A549 and H1975. Cell viabil-

ity was measured 72 h after transfection, and robust Z-scores

from duplicate experiments for each SMARTpool were deter-

mined13. While genes with a Z score ≤ -2 have been analyzed

in other work16, UPGs with a Z-score ≥ 2 (indicating that

cell proliferation was increased when the gene was silenced)

were assessed here and 11 UPGs were identified (Figure

1A and Supplementary Figure S1). These included UBL3,

USP26, UBL4, UBE2G2, FBXO42, RNF10, TRIM6, LOC51136,

RNF113A, MARCH1, and TRIM22.

Unveiling UBL3 in NSCLCs

We analyzed the expression levels of the above UPGs in

The Cancer Genome Atlas (TCGA) datasets containing 58

paired LUADs and 50 paired LUSCs (Supplementary Table

S1; Figure 1B and 1C), and reported that the expressions

of five genes (UBL3, TRIM22, UBE2G2, MARCH1, and

RNF10) were downregulated in these NSCLCs. The associ-

ation between the expression levels of these five genes and

the OS of the patients was analyzed using online survival

analysis software15 (http://kmplot.com/analysis/index.

php?p=service&cancer=lung). We found that the expression

of four genes, UBL3, TRIM22, UBE2G2, and MARCH1, was

positively associated with the OS of the patients, and the

median OS of patients with high levels of these genes was

significantly longer than that of patients with low levels of

these genes (Figure 1D–G). In TCGA datasets, the expres-

sion levels of the four genes in tumors were lower than those

in normal tissues at the mRNA level (Figure 1H), and UBL3

TRIM22

TumorNormal108 108

14

12

10

8

6

UBE2G2

TumorNormal108 108

12

11

10

9

8

MARCH1

TumorNormal108 108

10

6

8

4

2

0

UBL3

TumorNormal108n =

Paired108

14

12

10

8

6

RNAs

eqV2

log2

(x+

1)A549 H1975

TRIM22UBL4AUSP26RNFT1TRIM6RNF10

MARCH1UBE2G2FBXO42

RNF113AUBL3

UBL3TRIM22UBE2G2

MARCH1RNF10

FBXO42RNFT1TRIM6

RNF113AUBL4AUSP26

58 paired LUADs 50 paired LUSCs

1g (fold change)

108 paired NSCLCs

Z-Score

4.03.53.02.52.0

Prob

abili

ty

Prob

abili

ty

Time (month) Time (month)

Expression ExpressionLow (n = 963)High (n = 963)

Low (n = 963)High (n = 963)

UBL3

TRIM

22

UBE2G2

MARCH1RNF1

0

FBXO42

RNFT1USP

26TR

IM6

RNF113A

UBL4A

UBE2G2 MARCHI P = 9.8e-06P = 9.7e-101.0

0.8

0.6

0.4

0.2

0.0

1.0201482

2.0

Fold

cha

nge

(tum

or/n

orm

al)

1.51.00.5

0

0.8

0.6

0.4

0.2

0.0

1.0

0.8

0.6

0.4

0.2

0.0

Low (n = 572)Expression Expression

High (n = 573)Low (n = 574)High (n = 571)

Prob

abili

ty

Prob

abili

ty

1.0

0.8

0.6

0.4

0.2

0.00 50 100 150 200 0 50 100 150 200

0 50 100 150 200 0 50 100 150 200

TRIM22UBL3 P = 2.9e-11

10–1

P = 3.3e-16

Time (month) Time (month)

A B

C D E

F G H

*** *** *** ***

Figure 1 Identification of UBL3 as a potential tumor suppressor in non-small cell lung cancer (NSCLC) cells. (A) Heat map showing 11 candidates with Z-scores ≥ 2 in both A549 and H1975 cells. (B, C) Heat map and scatter plot of the expression of the 11 candidates in 58 paired lung adenocarcinoma (LUAD) tissues and 50 paired lung squamous cell carcinoma (LUSC) tissues. The fold change indicates the tumor/normal ratio. (D–G) The association between the expression levels of the four genes and the prognosis of patients as determined by online survival analysis software. (H) The expression levels of the four genes in TCGA datasets. ***P < 0.0001.

80 Zhao et al. UBL3 in non-small cell lung cancer

Hou lungA B C D E F

G

L

N P Q

M O

H I J K

Selamat lung Su lung Stearman lung Landi lung Okayama lungN

orm

aliz

ed U

BL3

expr

essi

on

Nor

mal

ized

UBL

3 ex

pres

sion

NSCLC LUSCLUAD LUAD LUSC

Case

s w

ith c

opy

num

ber l

oss

UBL

3 pr

otei

n le

vel

(nor

mal

ized

to a

ctin

)

RNAs

eqV2

log2

(x+

1)

RNAs

eqV2

log2

(x+

1)

RNAs

eqV2

log2

(x+

1)

RNAs

eqV2

log2

(x+

1)

RNAs

eqV2

log2

(x+

1)

Tumor1018 110 517 59 501 51 58 58 50 50

Normal Tumor Normal Tumor Normal Tumor Normal Tumor NormalPaired Paired

45 45Tumor NormalPaired

n =

14 14Tumor NormalPaired

n =

32 32Tumor NormalPaired

n =

Tumor

3

2

1

0

–1

–2

–3

15

10

5

15

10

5

15

10

5

14

8

10

12

6

14

8

10

12

6

6

5

4

3

2

1

4

3

2

1

0

3

1

2

0

–1

–2

5

3

4

2

1

0

7

5

6

4

3

1

65 58 58 27 30 20 19 58 49Normal Tumor Normal Tumor Normal Tumor Normal Tumor

226TumorNormal

20Normal

n =

n = 72

Imm

unor

eact

ivity

sco

re

Case 1, UBL3 Case 1, UBL3 14 P = 0.355

12

10

8

6

4

2

0

UBE2G

2

FBXO42

RNF1

0UBL

3TR

IM6

TRIM

22

RNF1

13A

USP26

UBL4A

RNFT

1

G11 G13 G15 G17

T N T N T N T N

G57 G67 G73 105

Tum

orN

orm

alT N T N T N T N

UBL3

Actin

UBL3

Actin

NSCLC (n = 1017)

632

800700600500400300200100

0

3.08

6

42

2.0

1.5

1.0

0.5

0

2.52.01.51.01.00.80.60.40.2

0

Figure 2 The expression of UBL3 in patients with NSCLC in the Oncomine and TCGA datasets. The expression of UBL3 in the Hou Lung (A), Selamat Lung (B), Su Lung (C), Stearman lung (D), Landi Lung (E), and Okayama lung (F) Oncomine datasets and the NSCLC (G), lung adenocarcinoma (LUAD) (H), and lung squamous cell carcinoma (LUSC) (I) of TCGA datasets is shown. (J, K) UBL3 expression levels in tumor tissues and the counterpart adjacent normal lung tissues from the TCGA LUAD (J) and LUSC (K) datasets. (L) Copy number loss analysis of 10 candidates in the TCGA database. (M–Q) The expression of UBL3 was tested by quantitative reverse transcription polymerase chain reaction (qRT-PCR) (M), Western blot (N, O), and immunohistochemistry (P, Q) assays of lung cancer patients of our cohort. Size bar, 0.5 mm. The densitometry analysis of the Western blot results (O) and the immunoreactivity score of UBL3 were calculated (Q). P values, Student’s t-test. ***P < 0.0001.

Cancer Biol Med Vol 17, No 1 February 2020 81

Table 1 Summary of the baseline demographic characteristics of the 86 patients

Characteristics Cases, n UBL3-low, n (%) P

Total 86 59 (68.6)

Gender

Male 48 36 (75) 0.402

Female 20 13 (65)

Not recorded 18 10 (55.6)

Age (years)

< 65 47 33 (70.2) 0.691

≥ 65 20 15 (75)

Not recorded 19 11 (57.9)

Smoking status

Smoker 39 27 (69.2) 0.547

Non-smoker 29 22 (75.9)

Not recorded 18 10 (55.6)

Histology

LUAD 39 29 (74.4) 0.729

LUSC 23 18 (78.3)

LUAD + LUSC 4 0 (0)

SCLC 2 2 (100)

Not recorded 18 10 (55.6)

TNM Stage

I-II 36 23 (63.9) 0.150

III-IV 30 24 (80)

Not recorded 20 12 (60)

LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma. P values were calculated using a two-sided Fisher’s exact test. “UBL3-low” indicates that the levels of UBL3 were lower in tumor tissues than in normal tissues.

represented the most significant one (Figure 1H). Therefore,

UBL3 was selected for further investigation.

The expression of UBL3 in NSCLC

To evaluate the expression of UBL3 in NSCLC, the Oncomine

Cancer Microarray Database14 (www.oncomine.org) was

explored. In the Hou Lung17, Selamat Lung18, Su lung19,

Stearman Lung20, Landi Lung21, and Okayama Lung22 data-

sets, the UBL3 mRNA levels were significantly reduced in

tumor tissues compared to those in the counterpart normal

lung tissues (Figure 2A–F). We investigated UBL3 RNA levels

in TCGA dataset containing 1, 018 NSCLC tumor samples and

110 normal lung specimens and found significantly reduced

expression of UBL3 in NSCLC tumor samples compared to

that in normal lung tissue samples (Figure 2G). In both lung

adenocarcinoma (LUAD, n = 517) and lung squamous cell car-

cinoma (LUSC, n = 501), the expression of UBL3 was signif-

icantly higher in normal tissues than in tumor lung samples

(Figure 2H and 2I; P < 0.0001). In paired tumor adjacent sam-

ples from TCGA datasets, UBL3 expression in tumor tissues

was lower than that in the adjacent lung samples (Figure 2J

and 2K, P < 0.0001). In addition, the UBL3 copy number loss

was found in 632 (62.1%) of 1,017 TCGA patients (Figure 2L).

We tested the expression of UBL3 in 86 NSCLCs (Table 1) by

quantitative reverse transcription polymerase chain reaction

(qRT-PCR) (Figure 2M), Western blot analysis (Figure 2N

and 2O), and immunohistochemistry (IHC) (Figure 2P

and 2Q), and observed a decrease in UBL3 expression in

tumor tissues of 59/86 (68.6%) patients, demonstrating the

suppressed expression of UBL3 in NSCLCs.

UBL3 expression and prognosis of smoker patients with NSCLC

The association between the UBL3 expression levels and

tobacco smoking status of the patients was explored in TCGA

and Oncomine databases. In TCGA datasets, the expression of

UBL3 was significantly higher in non-smoking NSCLC patients

than in former and current smoking NSCLCs (Figure 3A).

In the Oncomine Lee Lung dataset23, UBL3 in non-smoking

patients was also higher than in smoking patients with NSCLC

(Figure 3B). We analyzed the potential association between

UBL3 expression and patient prognosis using the online

survival analysis software. The results showed that smoking

patients with NSCLC with high levels of UBL3 had a favora-

ble prognosis, but non-smoking patients with high levels of

UBL3 had much better prognosis (Figure 3C and 3D). These

results suggest that the expression of UBL3 in NSCLC may be

modulated by tobacco smoke and related carcinogens and thus

involved in lung carcinogenesis. This possibility could be fur-

ther investigated in the future.

The association between UBL3 expression and clinical characteristics

We also explored the association between UBL3 expression

levels and TNM stage in patients in TCGA database, and the

82 Zhao et al. UBL3 in non-small cell lung cancer

data showed that the expression of UBL3 was significantly

higher in stage I NSCLCs than in stage II and III NSCLCs

(Figure 3E). The prognostic significance of UBL3 was fur-

ther analyzed using stage-matched samples. Among stage I

and stage II patients, those with higher expression of UBL3

had much longer survival time than those with lower levels

of UBL3 (Figure 3F). Among patients with stage III NSCLCs

(Figure 3F, right panel), those with higher UBL3 had slightly

but not statistically significantly shorter OS than those with

lower expression of UBL3. The expression of UBL3 was sig-

nificantly higher in female NSCLC patients than in male

NSCLC patients in TCGA dataset (Figure 3G). In Oncomine

datasets24,25, UBL3 expression in female patients was also

higher than in male patients (Figure 3H and 3I), although

the difference was not statistically significant, and was pos-

sibly attributed to less smoking in women than in men.

Analysis with online survival analysis software indicated that

LUAD patients with lower UBL3 expression had significantly

TCGAP = 0.003

3

2

1

0

–1

–2

2

3

1

0

–1

–2

6 4

6

8

10

–2

–1

0

2

1

8

10

12

14

8 1.0

0.8

0.6

0.4

0.2

0.0

1.0

0.8

0.6

0.4

0.2

0.0

1.0

0.8

0.6

0.4

0.2

0.0

1.0

0.8

0.6

0.4

0.2

0

1.0

0.8

0.6

0.4

0.2

0.0

6

4

2

P = 0.026

Lee lung

NSCLC, smokersP = 0.043

NSCLC, non-smokersP = 9.1e-06

Nor

mal

ized

UBL

3 ex

pres

sion

Prob

abili

ty

Prob

abili

ty

Expression Expression

Low (n = 410)High (n = 410)

Low (n=102)High (n = 103)

CurrentSmoke Smoker100

Never Former3111

Never38143

Nor

mal

ized

UBL

3 ex

pres

sion

Prob

abili

ty

TCGA, NSCLCP = 0.01

ExpressionLow (n = 288)High (n = 289)

ExpressionLow (n = 122)High (n = 122)

ExpressionLow (n = 35)High (n = 35)

Time (month)0 50 100 150 200

0 50 100 150 200 0 50 100 150

0 50 100 150 200 250Time (month)

0 50 100 150Time (month)

0 50 100 150Time (month)

0 50 100 150Time (month)

ExpressionLow (n = 3 60)High (n = 360)

TCGA, NSCLC Kuner lung Zhu lung

LUADP = 3.7e-09

TCGA, LUADP = 0.30

Low (n = 239)High (n = 240)

Nor

mal

ized

UBL

3 ex

pres

sion

RNAs

eqV2

log2

(x+

1)

Female Male Female Male Female Male393n = 579 14 44 23 67

P = 0.06 P = 0.056

Prob

abili

ty

Stage 1P = 3.7e-09

Stage I II III IVn = 105 38 37 6

Stage 2P = 0.015

Stage 3P = 0.35

Time (month) Time (month)

A B C D

E F

G H I J K

n =

Figure 3 The association between UBL3 expression and clinical characteristics. The expression of UBL3 in smoking and non-smoking patients with NSCLC in TCGA dataset (A) and Oncomine Lee Lung dataset (B). UBL3 expression and prognosis of smoking (C) and non-smoking (D) patients with NSCLC as determined by online survival analysis software. (E) The expression of UBL3 in patients with NSCLC at different stages. (F) Overall survival (OS) of patients with NSCLCs at different stages with high or low expression of UBL3. (G) Expression of UBL3 in female and male patients with NSCLC in TCGA (G) and the Oncomine datasets Kuner Lung (H) and Zhu Lung (I). The Kaplan-Meier survival curve of LUAD patients with high or low levels of UBL3 expression as determined by online survival analysis software (J) and TCGA database analysis (K). ***P < 0.0001.

Cancer Biol Med Vol 17, No 1 February 2020 83

worse prognosis than those with higher UBL3 expression

(Figure 3J). Similarly, in TCGA datasets, LUAD patients with

lower UBL3 expression had poorer prognosis, although the

difference was not statistically significant (Figure 3K). These

data demonstrated that UBL3 might play a role in the patho-

genesis of NSCLC.

Knockdown of UBL3 promotes lung cancer cell proliferation

We found that silencing UBL3 accelerated cell proliferation,

with Z-scores of 4.22 and 3.42 in A549 and H1975 cells, respec-

tively (Figure 1A and Supplementary Figure S1). We verified

00 0

1

2

3

4

5

5

10P = 0.02

P = 0.05 P = 0.02

A549 A549

Foci formation Soft-ager

+– +–H460H1975 HA-UBL3

HA

Actin

Cyclin E

Cyclin D1

p27

Actin

Actin

Foci formation

Soft-agar

P = 0.038P = 0.044

P = 0.35P = 0.05

0

2

4

6

8

0

2

4

6

8

10P = 0.04

SiNC

siN

C

SiUBL3-1#

siU

BL3-

1#si

UBL

3-2#

15

0

5

10

15

0

0

100

200

No.

of c

olon

ies

No.

of c

olon

ies

300

0

100

200

300

4005

10

20

15

20

25

24 48 72 0 24 48 72

A549 H1975

A549 H460

H1975

HA-vectorHA-UBL3

Time post transfection (h)

Viab

le c

ells

(×10

5 )

Viab

le c

ells

(×10

5 )

0

0 40 80

00

20

40

60

80

Num

ber

100

0

20

40

60

80

Num

ber

100

40 80 0 100 200Channels (FL2-A)

0 50 200

120 0 40 80 1200 30

G1: 75.44%G2/M: 11.45%S: 13.11%

G1G2S

G1: 67.94%G2/M: 17.39%S: 14.67%

G1: 60.96%G2/M: 11.88%S: 27.17%

G1: 62.82%G2/M: 11.87%S: 25.31%

A549: siNC

G1: 63.19%G2/M: 6.21%S: 30.6%

G1: 67.6%G2/M: 10.28%S: 22.02%

60 80 120

24 48 72 0 24 48 72Time post transfection (h)

NC 1# 2# NC 1# 2#

A549NC 1# 2#

Actin

UBL3

UBL3

siUBL3

siUBL3-1# siUBL3-2#

A549 H1975NC 1# 2# NC 1# 2#siUBL3

UBL3

siUBL3

NC 1# 2#siUBL3

Rela

tive

cell

num

ber

(×10

5 )

Rela

tive

cell

num

ber

(×10

5 )

0

2

4

8

6

0

2

4

6

A B

D

F

G

E

C

Figure 4 UBL3 inhibits NSCLC cell proliferation. (A) A549 and H1975 cells were transfected with siUBL3 (1# and 2#) and lysed 72-h later for the detection of UBL3 expression by Western blot assays (upper panel) and assessment of cell viability (lower panel). Error bars, SD. (B) A549 and H1975 cells were transfected with siUBL3-1, and cell proliferation was assessed by a Trypan Blue dye exclusion assays. (C, D) A549 and H460 cells were transfected with HA-tagged UBL3, and cell proliferation was assessed by a Trypan Blue exclusion assay. (E) Foci formation and soft agar assays of A549 cells transfected with siUBL3. Error bars, SD; P values, Student’s t-test. (F) A549 and H1975 cells were transfected with siUBL3 and the cell cycle distribution was assessed by propidium iodide staining of DNA followed by flow cytometric analysis. (G) A549 and H1975 cells were transfected with siUBL3, lysed 72 h later, and the lysates were subjected to Western blot assay using indicated antibodies.

84 Zhao et al. UBL3 in non-small cell lung cancer

the effects of siRNA against UBL3 (siUBL3) on lung cancer

cells, and found that siUBL3 treatment resulted in a reduc-

tion of UBL3 protein expression and increased viability of

A549 and H1975 cells (Figure 4A). Knockdown of UBL3 led

to a significant increase in cell growth (Figure 4B). In contrast,

exogenous expression of UBL3 (by transient transfection) sig-

nificantly inhibited the proliferation (Figure 4C) and growth

(Figure 4D) of cells. We further showed that knockdown of

UBL3 promoted the colony-forming activity of A549 cells

(Figure 4E). Silencing UBL3 in H1975 cells led to cell cycle

arrest at the S phase (Figure 4F), downregulation of p27, Cyclin

D1, and upregulation of Cyclin E (Figure 4G), indicating that

UBL3 played a role in the control of the replication checkpoint.

UBL3 inhibits tumor growth in vivo

To investigate the role of UBL3 in tumor growth in vivo, the

pCDH-UBL3 plasmid was transfected into A549-luciferase

cells (Figure 5A), which were then injected into SCID-beige

mice via the tail vein (n = 13 for each group). To characterize

the growth of the xenograft tumors, the luciferase intensity in

the mice was measured by an IVIS Spectrum system 45 days

A549-luc pCDH-vector

pCD

H-U

BL3

pCDH-UBL3

pCDH-UBL3

pCD

H-v

ecto

r

pCDH-vector

pCDH-vector pCDH-UBL3

pCDH-UBL3

pCDH-vector***

A549-luc:

SCID beige mice0

0 20 40 60 800

20

40

60

Num

ber

80

120 0 20 40Channels (FL2-A)

G1: 60.79%G2/M: 21.03%S: 18.18%

G1: 70.08%G2/M: 21.8%S: 8.12%

60 80 120

0

20

40

60

80

100 G1A549-luc

G2/M

S

Perc

enta

ge (%

)

0

20

40

60

80

100

30 60 90

Perc

ent s

urvi

val (

%)

120Time (day)

150

1#

Actin

n = 13UBL3

no. 2# 3# 1# 2# 3#

pCDH-UBL3

pCDH-UBL3 – + pCDH-UBL3

HE UBL3 Ki67

– +0

1

2

5

10

1.0

2.0

3.0

∗∗∗

0

0.5

1.0

1.5

2.0

2.54.0ph/s15

A

C DE

F G

B

Nor

mal

ized

UBL

3ex

pres

sion

Aver

age

inte

nsity

(×10

4 ph/

s/m

m2 )

×104

– +

Figure 5 UBL3 suppresses lung cancer in vivo. (A) qRT-PCR analysis of UBL3 mRNA levels in pCDH-UBL3-expressing A549-luciferase cells. (B) A total of 5 × 105 pCDH-UBL3-expressing A549-luciferase cells were injected into SCID-beige mice and the relative luciferase intensity was determined by an IVIS Spectrum system at the indicated time point (B). Error bars, SD; P values, Student’s t-test. The Kaplan-Meier survival curve of the mice is shown (C). P value, log-rank test. Mice were sacrificed, and lung tissues were lysed for Western blot assays using the indicated antibodies (D) or subjected to hematoxylin-eosin (HE) or immunohistochemical staining (E). Scale bar, 1 mm for HE and 0.5 mm for IHC. (F, G) A549-luc cells with pCDH-vector or pCDH-UBL3 were assessed by propidium iodide staining of DNA followed by flow cytometric analysis (F), and cell cycle distribution was assessed (G).

Cancer Biol Med Vol 17, No 1 February 2020 85

after cell inoculation. We found that UBL3 significantly

decreased the tumor burden (Figure 5B) and extended the life

span of the mice (Figure 5C). Western blot assays of tumor

lysates indicated overexpression of UBL3 in vivo (Figure 5D).

Hematoxylin-eosin (HE) and Ki67 staining of lung sections

confirmed the tumor-inhibitory effect of UBL3 (Figure 5E).

Cell cycle analysis showed that overexpression of UBL3

induced arrest at G1 phase, without accumulation of sub-G1

content (Figure 5F and 5G).

Discussion

In this study, we carried out an siRNA screen for 696 UPGs

found in the human genome, and reported 11 candidates that

were able to promote cell proliferation when they were silenced

in A549 and H1975 cells (Figure 1). In TCGA database, the

expressions of four potential tumor suppressor genes (UBL3,

TRIM22, UBE2G2, and MARCH1) were significantly down-

regulated in tumor samples compared to that in normal lung

tissues. Using online survival analysis software15, we found that

the expression levels of these four genes were positively asso-

ciated with the OS of patients with NSCLC, with UBL3 as the

most significant one. These results provided rationales for us

to further investigate the role of UBL3 in lung carcinogenesis.

UBL3 has been identified in Drosophila melanogaster26 and

is a membrane protein localized by prenylation27. UBL3 acts

as a post-translational modification factor that regulates pro-

tein sorting to small extracellular vesicles (sEVs)28. In melano-

cytic cells, UBL3 may be regulated by MITF29. A genome-wide

association study demonstrated that UBL3 harbors a sus-

ceptibility locus for biliary atresia30. Additionally, UBL3 was

identified to harbor a novel susceptibility locus for BRCA1/2-

negative, high risk breast cancers in Asian women31. UBL3

was upregulated in human prostate cancer cells (LNCaP

cells) exposed to silvestrol32. UBL3 was identified as part of

a 7-gene signature (UBL3, FGF3, BMI1, PDGFRA, PTPRF,

RFC4, and NOL7) for predicting relapse and survival in ear-

ly-stage patients with cervical carcinoma33. Promoter hyper-

methylation and downregulation were found in UBL3 in a

northeast Indian population with esophageal cancer34. An

in-frame fusion of MAP3K8-UBL3 was reported as a distinct

genetic driver in a unique subgroup of spitzoid neoplasms35.

Previous studies showed that UBL3 was abnormally expressed

in BRCA1/2-negative, high risk breast cancers (BRCAX)31,

cervical carcinoma33, and esophageal cancer34. However, the

role of UBL3 in lung cancer remains poorly understood.

Here, we found that UBL3 expression was reduced in tumor

samples from both TCGA and Oncomine datasets and in 86

NSCLC samples from our laboratory (Figure 2, Table 1).

UBL3 expression levels were much lower in patients with

stage II or III NSCLC than in patients with stage I NSCLC

(Figure 3E). LUAD patients with higher levels of UBL3 had

more favorable prognosis than those patients with lower lev-

els of UBL3 (Figure 3). We investigated the function of UBL3

in NSCLC cells and demonstrated that silencing of UBL3 pro-

moted, whereas overexpression of UBL3 suppressed, NSCLC

cell proliferation in vitro and in vivo (Figure 4 and Figure 5).

These data indicated that UBL3 could be a tumor suppressor

in NSCLCs. However, why UBL3 was suppressed in tumor

samples and how it suppressed cell proliferation, warrant fur-

ther investigation.

Tobacco is responsible for about 85% of lung cancer deaths

(1.53 million) each year worldwide1. Tobacco smoke causes

genomic mutations in cancers36; promotes cell proliferation;

inhibits programmed cell death; facilitates angiogenesis, inva-

sion and metastasis; and enhances tumor-promoting inflam-

mation37,38. We found that the expression of UBL3 was sig-

nificantly higher in non-smoking than in smoking patients

and that non-smoking patients with NSCLC with high levels

of UBL3 had much more favorable prognosis than those who

smoked (Figure 3). The effects of tobacco smoke on UBL3

expression need to be investigated in the future.

Collectively, the above results suggested that UBL3 may be

involved in lung carcinogenesis by altering the expression of

oncoproteins/tumor suppressors, thus affecting critical path-

ways to promote cell proliferation and disease progression.

These possibilities and whether UBL3 could be a therapeutic

target for lung cancer warrant further investigation.

Acknowledgments

This work was supported by the National Key Research and

Development Program of China (Grant No. 2016YFC0905501),

the National Natural Science Funds for Distinguished Young

Scholar (Grant No. 81425025), the Key Project of the National

Natural Science Foundation of China (Grant No. 81830093),

the CAMS Innovation Fund for Medical Sciences (Grant No.

CIFMS; 2019-I2M-1-003), and the National Natural Science

Foundation of China (Grant No. 81672765 and 81802796).

The study sponsor had no role in the design of the study; the

data collection, analysis, or interpretation; the writing of the

article; or the decision to submit for publication.

86 Zhao et al. UBL3 in non-small cell lung cancer

Conflict of interest statement

No potential conflicts of interest are disclosed.

References

1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A.

Global cancer statistics 2018: GLOBOCAN estimates of incidence

and mortality worldwide for 36 cancers in 185 countries. CA

Cancer J Clin. 2018; 68: 394-424.

2. Herbst RS, Morgensztern D, Boshoff C. The biology and

management of non-small cell lung cancer. Nature. 2018; 553:

446-54.

3. George J, Lim JS, Jang SJ, Cun Y, Ozretić L, Kong G, et al.

Comprehensive genomic profiles of small cell lung cancer. Nature.

2015; 524: 47-53.

4. Network TCGAR. Comprehensive molecular profiling of lung

adenocarcinoma. Nature. 2014; 511: 543-50.

5. Network TCGAR. Comprehensive genomic characterization of

squamous cell lung cancers. Nature. 2012; 489: 519-25.

6. Reinstein E, Ciechanover A. Narrative review: protein degradation

and human diseases: the ubiquitin connection. An Intern Med.

2006; 145: 676-84.

7. Veen AGvd, Ploegh HL. Ubiquitin-like proteins. Annu Rev

Biochem. 2012; 81: 323-57.

8. Seeler J-S, Dejean A. Sumo and the robustness of cancer. Nat Rev

Cancer. 2017; 17: 184.

9. Zhou L, Jiang Y, Luo Q, Li L, Jia L. Neddylation: a novel modulator

of the tumor microenvironment. Mol Cancer. 2019; 18: 77.

10. Pan J, Deng Q, Jiang C, Wang X, Niu T, Li H, et al. USP37 directly

deubiquitinates and stabilizes c-Myc in lung cancer. Oncogene.

2014; 34: 3957-67.

11. Snoek BC, de Wilt LH, Jansen G, Peters GJ. Role of e3 ubiquitin

ligases in lung cancer. World J Clin Oncol. 2013; 4: 58–69.

12. Liu YQ, Wang XL, Cheng X, Lu YZ, Wang GZ, Li XC, et al.

Skp1 in lung cancer: clinical significance and therapeutic

efficacy of its small molecule inhibitors. Oncotarget. 2015; 6:

34953-67.

13. Malo N, Hanley JA, Cerquozzi S, Pelletier J, Nadon R. Statistical

practice in high-throughput screening data analysis. Nat

Biotechnol. 2006; 24: 167-75.

14. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R,

Yu J, Briggs BB, et al. Oncomine 3.0: genes, pathways, and networks

in a collection of 18,000 cancer gene expression profiles. Neoplasia.

2007; 9: 166-80.

15. Gyorffy B, Surowiak P, Budczies J, Lanczky A. Online survival

analysis software to assess the prognostic value of biomarkers using

transcriptomic data in non-small-cell lung cancer. PLoS One. 2013;

8: e82241.

16. Zhang Y, Zhao X, Zhou Y, Wang M, Zhou G. Identification of an E3

ligase-encoding gene, RFWD3, in non-small cell lung cancer. Front

Med. 2019; https://doi.org/10.1007/s11684-019-0708-6.

17. Hou J, Aerts J, den Hamer B, van Ijcken W, den Bakker M, Riegman

P, et al. Gene expression-based classification of non-small cell lung

carcinomas and survival prediction. PLoS One. 2010; 5: e10312.

18. Selamat SA, Chung BS, Girard L, Zhang W, Zhang Y, Campan

M, et al. Genome-scale analysis of DNA methylation in lung

adenocarcinoma and integration with mRNA expression. Genome

Res. 2012; 22: 1197-211.

19. Su LJ, Chang CW, Wu YC, Chen KC, Lin CJ, Liang SC, et al.

Selection of DDX5 as a novel internal control for Q-RT-PCR from

microarray data using a block bootstrap re-sampling scheme. BMC

Genomics. 2007; 8: 140.

20. Stearman RS, Dwyer-Nield L, Zerbe L, Blaine SA, Chan Z, Bunn PA

Jr, et al. Analysis of orthologous gene expression between human

pulmonary adenocarcinoma and a carcinogen-induced murine

model. Am J Pathol. 2005; 167: 1763-75.

21. Landi MT, Dracheva T, Rotunno M, Figueroa JD, Liu H, Dasgupta

A, et al. Gene expression signature of cigarette smoking and its role

in lung adenocarcinoma development and survival. PLoS One.

2008; 3: e1651.

22. Okayama H, Kohno T, Ishii Y, Shimada Y, Shiraishi K, Iwakawa

R, et al. Identification of genes upregulated in ALK-positive and

EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res.

2012; 72: 100-11.

23. Lee ES, Son DS, Kim SH, Lee J, Jo J, Han J, et al. Prediction of

recurrence-free survival in postoperative non-small cell lung cancer

patients by using an integrated model of clinical information and

gene expression. Clin Cancer Res. 2008; 14: 7397-404.

24. Kuner R, Muley T, Meister M, Ruschhaupt M, Buness A, Xu EC,

et al. Global gene expression analysis reveals specific patterns of

cell junctions in non-small cell lung cancer subtypes. Lung Cancer.

2009; 63: 32-8.

25. Zhu CQ, Ding K, Strumpf D, Weir BA, Meyerson M, Pennell

N, et al. Prognostic and predictive gene signature for adjuvant

chemotherapy in resected non-small-cell lung cancer. J Clin Oncol.

2010; 28: 4417-24.

26. Chadwick BP, Kidd T, Sgouros J, Ish-Horowicz D, Frischauf AM.

Cloning, mapping and expression of UBL3, a novel ubiquitin-like

gene. Gene. 1999; 233: 189-95.

27. Downes BP, Saracco SA, Lee SS, Crowell DN, Vierstra RD.

MUBs, a family of ubiquitin-fold proteins that are plasma

membrane-anchored by prenylation. J Biol Chem. 2006; 281:

27145-57.

28. Ageta H, Ageta-Ishihara N, Hitachi K, Karayel O, Onouchi T,

Yamaguchi H, et al. UBL3 modification influences protein sorting

to small extracellular vesicles. Nat Commun. 2018; 9: 3936.

29. Hoek KS, Schlegel NC, Eichhoff OM, Widmer DS, Praetorius C,

Einarsson SO, et al. Novel MITF targets identified using a two-step

DNA microarray strategy. Pigment Cell Melanoma Res. 2008; 21:

665-76.

30. Garcia-Barcelo MM, Yeung MY, Miao XP, Tang CS, Cheng G, So

MT, et al. Genome-wide association study identifies a susceptibility

locus for biliary atresia on 10q24.2. Human Mol Genetics. 2010; 19:

2917-25.

Cancer Biol Med Vol 17, No 1 February 2020 87

31. Lee JY, Kim J, Kim SW, Park SK, Ahn SH, Lee MH, et al. BRCA1/2-

negative, high-risk breast cancers (BRCAX) for Asian women:

genetic susceptibility loci and their potential impacts. Sci Rep.

2018; 8: 15263.

32. Mi Q, Kim S, Hwang BY, Su BN, Chai H, Arbieva ZH, et al.

Silvestrol regulates g2/m checkpoint genes independent of p53

activity. Anticancer Res. 2006; 26: 3349-56.

33. Huang L, Zheng M, Zhou QM, Zhang MY, Yu YH, Yun JP, et al.

Identification of a 7-gene signature that predicts relapse and

survival for early stage patients with cervical carcinoma. Med

Oncol. 2012; 29: 2911-8.

34. Singh V, Singh LC, Vasudevan M, Chattopadhyay I,

Borthakar BB, Rai AK, et al. Esophageal cancer epigenomics and

integrome analysis of genome-wide methylation and expression

in high risk northeast Indian population. Omics. 2015; 19:

688-99.

35. Quan VL, Zhang B, Mohan LS, Shi K, Isales MC, Panah E, et al.

Activating structural alterations in MAPK genes are distinct genetic

drivers in a unique subgroup of spitzoid neoplasms. Am J Surg

Pathol. 2019; 43: 538-48.

36. Alexandrov LB, Ju YS, Haase K, Van Loo P, Martincorena I,

Nik-Zainal S, et al. Mutational signatures associated with tobacco

smoking in human cancer. Science. 2016; 354: 618-22.

37. Sobus SL, Warren GW. The biologic effects of cigarette smoke on

cancer cells. Cancer. 2014; 120: 3617-26.

38. Hecht SS. Lung carcinogenesis by tobacco smoke. Int J Cancer.

2012; 131: 2724-32.

Cite this article as: Zhao X, Zhou Y, Hu Q, Gao S, Liu J, Yu H, et al. Identification

of a potential tumor suppressor gene, UBL3, in non-small cell lung cancer.

Cancer Biol Med. 2020; 17: 76-87. doi: 10.20892/j.issn.2095-3941.2019.0279

Cancer Biol Med Vol 17, No 1 February 2020 1

Table S1 Summary of the baseline demographic characteristics of the 108 patients with non-small cell lung cancer (NSCLC) in TCGA database

Characteristics Cases, n UBL3-low, n (%) P

Total number 108 76 (70.4)

Age (years)

< 65 41 26 (63.4) 0.216

  ≥ 65 67 50 (74.6)

Gender

Male 51 36 (70.6) 0.009

Female 57 26 (45.6)

Smoking status

Smoker 95 72 (75.8) 0.275

Non-smoker 7 4 (57.1)

Not recorded 6 4 (66.7)

Histology

LUAD 58 30 (51.7) 4.86E-06

LUSC 50 46 (92)

TNM stage

I-II 85 57 (67.1) 0.092

III-IV 21 18 (85.7)

Not recorded 2 1 (50)

Anatomic subdivision of lung neoplasm

Upper 63 43 (68.3) 0.619

Lower 37 27 (73)

Middle 4 4 (100)

Not recorded 4 2 (100)

Vital status

Living 56 32 (57.1) 0.002

Dead 52 44 (84.6)

P values were calculated using a two-sided Fisher’s exact test. “UBL3-low” indicates that the levels of UBL3 were lower in tumor tissues than in normal tissues. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

4.5A549H1975

4

3.5

3

2.5

Z sc

ore

2

1.5

1

0.5

0

UBL3

USP26

UBL4

UBE2G

2

FBXO42

RNF1

0TR

IM6

LOC51

136

RNF1

13A

MARCH1

TRIM

22

Figure S1 The 11 UPGs that have a Z score of ≥ 2.

Supplementary materials