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Research Papers:

Time-course differential lncRNA and mRNA expressions in radioresistant hypopharyngeal cancer cells

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Oncotarget. 2017; 8:40994-41010. https://doi.org/10.18632/oncotarget.17343

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Jieyu Zhou, Shengda Cao, Wenming Li, Dongmin Wei, Zhentao Wang, Guojun Li, Xinliang Pan and Dapeng Lei _

Abstract

Jieyu Zhou1,2,*, Shengda Cao1,*, Wenming Li1, Dongmin Wei1, Zhentao Wang2, Guojun Li3,4, Xinliang Pan1 and Dapeng Lei1

1Department of Otorhinolaryngology, Qilu Hospital, Shandong University, Key Laboratory of Otolaryngology, NHFPC - Shandong University, Jinan, Shandong, 250012, P.R. China

2Department of Otorhinolaryngology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University, School of Medicine, Shanghai, 200011, P.R. China

3Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA

4Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA

*These authors contributed equally to this work

Correspondence to:

Xinliang Pan, email: panxinl915@126.com

Dapeng Lei, email: leidapeng@sdu.edu.cn

Keywords: hypopharyngeal squamous cell carcinoma, radioresistance, lncRNA, mRNA, microarray

Received: December 05, 2016     Accepted: April 10, 2017     Published: April 21, 2017

ABSTRACT

Radioresistance remains a major problem in the treatment of patients with hypopharyngeal squamous cell carcinoma (HSCC). Long noncoding RNAs (lncRNAs) have important roles in the development, invasion, and metastasis of various tumors, including HSCC, but little is known about the role of lncRNAs in cancer radioresistance. The aim of this study was to identify radioresistance-related lncRNAs and mRNAs in radioresistant (RS) hypopharyngeal cancer subclone RS-FaDu cells. In this study, we performed microarray analysis to find the differences in time-course lncRNA and mRNA expression profiles between RS-FaDu and parent FaDu cells after 4 Gy radiation therapy, whose reliability was confirmed by validation experiment. Among these consistently dysregulated lncRNAs, we found that some lncRNAs (e.g., TCONS_00018436) might control resistance of HSCC cells to radiation. Furthermore, our bioinformatics analyses from mRNA/lncRNA microarray data showed that certain lncRNAs or mRNAs potentially are involved in radioresistance of HSCC. Our results from this study laid the foundation for further investigating the roles of these lncRNAs and mRNAs as promising candidates in the occurrence and development of HSCC radioresistance.


Time-course differential lncRNA and mRNA expressions in radioresistant hypopharyngeal cancer cells | Zhou | Oncotarget

INTRODUCTION

Hypopharyngeal squamous cell carcinoma (HSCC), which originates from the mucosa of the hypopharynx, has one of the poorest prognoses among head and neck cancers [1]. Currently, the standard treatment strategy for HSCC is surgery followed by radiotherapy [1]. Significant advances in radiotherapeutic strategies for HSCC, such as intensity-modulated radiotherapy (IMRT), image-guided radiotherapy (IGRT), and helical tomotherapy (TOMO), have been made in recent years [1, 2]. However, local recurrence and distant metastases after radiotherapy due to tumor radioresistance remain a serious obstacle to successful treatment of HSCC, and the 5-year survival rate remains at approximately 25% to 40% [3]. Although mechanisms of radioresistance have been extensively studied [4, 5], the underlying molecular pathways and targets involved in HSCC radioresistance are not fully understood. Currently, there are few strategies available for overcoming this clinical problem.

In the past decade, advances in genome-wide analysis of gene expression have revealed that the majority of genes in the genome are transcribed into non-coding RNAs (ncRNAs) [6]. Long non-coding RNAs (lncRNAs) are ncRNAs longer than 200 nucleotides [7], and they have important roles in chromatin modification and transcriptional and post-transcriptional processing [8, 9]. Specifically, lncRNAs have been demonstrated to promote the development, invasion, and metastasis of many tumors by a variety of mechanisms [10, 11]. Notably, several studies have shown that lncRNAs are extremely important for controlling cancer radioresistance [1215], but the roles of lncRNAs in HSCC radioresistance are still unknown.

Accumulating evidence demonstrates that lncRNAs are widely involved in the regulation of proliferation, DNA damage response, apoptosis, and the cell cycle in cancer cells [1622], all of which are closely associated with the development of radioresistance [23]. Moreover, the roles of several lncRNAs, such as MALAT1 [13, 24], TUG1 [14], NEAT1 [25], and BOKAS [26], in radioresistance have been identified, although their detailed mechanisms remain largely unclear. Radioresistance is the leading cause of recurrence and poor prognosis in HSCC patients. Hence, it is of vital significance to figure out whether or not lncRNAs can become biomarkers for radioresistant HSCC and explore the molecular mechanisms underlying HSCC radioresistance.

It is very unlikely that a single molecule or gene is responsible for radioresistance in HSCC; therefore, to provide useful information for elucidating the molecular mechanisms that lncRNAs and mRNAs are involved in HSCC radioresistance, we used microarray techniques to perform large-scale analyses of lncRNA and mRNA expressions to comprehensively search for mechanisms of HSCC radioresistance. We initially generated a radioresistant HSCC subclone (RS-FaDu) from the parental FaDu cell line via long-term fractionated irradiation. Subsequently, we investigated differences in time-course lncRNA and mRNA expression profiles between RS-FaDu and parent FaDu cells after radiation therapy by microarray and bioinformatics analyses.

RESULTS

Establishment and validation of radioresistant HSCC subclone cell line

Radioresistance was measured by clonogenic survival assay following exposure to a range of radiation doses (0–6 Gy). As shown in Figure 1A, RS-FaDu and FaDu cells showed no difference in clonogenic formation ability when the radiation dose was 0 Gy. However, the RS-FaDu cells had significantly more and larger surviving colonies than did the control FaDu cells when the radiation dose was 4 Gy or 6 Gy. Clonogenic survival curves showed the surviving colony numbers of FaDu cells were significantly lower than those of RS-FaDu cells (**P < 0.01, both) at 4 Gy and 6 Gy (Figure 1B).

Radioresistance measurement by clonogenic survival assay and apoptosis assay.

Figure 1: Radioresistance measurement by clonogenic survival assay and apoptosis assay. (A) RS-FaDu and parental FaDu cells irradiated with different radiation doses (0, 2, 4, and 6 Gy) and the crystal violet-stained colonies were photographed at 12 days after irradiation. (B) Colonies containing more than 50 cells for survival colonies and scoring. (C) RS-FaDu and FaDu cells irradiated with 4 Gy. The apoptosis detection by FCM Annexin V/PI staining. The proportions of Annexin V+/PI− and Annexin V+/PI+ cells for early- and late-stage apoptosis. (D) At 0 h after irradiation with 4 Gy, there was no difference between RS-FaDu and FaDu in their fractions of apoptosis cells. At 24 h, 48 h, or 72 h after irradiation, the fraction of apoptosis cells in RS-FaDu cells was lower than that in FaDu cells. All experiments were performed in triplicate wells; points, mean; bars, SD. **P < 0.01.

To further verify the radioresistant phenotype of RS-FaDu, RS-FaDu and FaDu cells were also examined by apoptosis assays. RS-FaDu and FaDu cells were treated with 4 Gy. Their fractions of apoptosis cells did not differ at 0 h, but at 24, 48, or 72 h after irradiation, the fractions of apoptotic RS-FaDu cells were much lower than those of FaDu cells (**P < 0.01, Figure 1C, 1D). These results indicated that RS-FaDu cells were much more radioresistant than their parent FaDu cells. These data indicated that the RS-FaDu subclone cell line was successfully established.

LncRNA and mRNA profiles

Hierarchical clustering is an unsupervised classification method that can separate multiple groups without the use of the group information. In microarray data analysis, cluster analysis grouped samples together based on expression intensity revealed differences between clustering group and true group results for removal of outlier samples. The dendrogram showed the relationships among lncRNA (Figure 2A) and mRNA (Figure 2B) expression patterns between RS-FaDu cells and FaDu cells at 0, 2, and 48 h, respectively, after 4 Gy radiation exposure.

Figure 2:

Figure 2: LncRNA (A) and mRNA (B) expression profiling by human lncRNA microarray. The sample tree on the top of the figure shows sample group information, which reflects relationships among samples. In the dendrogram, red indicates high relative expression, and blue indicates low relative expression. M, E, and F refer to 0 hr, 2 hrs, and 48 hrs after exposure to 4 Gy irradiation, respectively. The Arabic numerals presented the experiment repeats.

A scatter plot is a visualization method to show the differentially expressed lncRNAs (Figure 3, A1–C1) and mRNAs (Figure 3, D1–F1). The values plotted on the X and Y axes were the averaged normalized signal values of groups of samples (log2 scaled). The X-axis represents the control group (FaDu), while the Y-axis represents the case group (RS-FaDu). All lncRNAs/mRNAs that were not differentially expressed were around the line Y = X and labelled black. Points that were above and apart from Y = X were upregulated lncRNAs/mRNAs and labelled red, and points that were below and apart from Y = X were downregulated lncRNAs/mRNAs and labelled green, respectively. A volcano plot is another visualization method to show differences in lncRNA (Figure 3, A2–C2) and mRNA (Figure 3, D2–F2) expression between the case group (RS-FaDu) and the control group (FaDu). The X-axis in the volcano plot represents FC (after log2 transformation) and the Y-axis represents P-value (after log transformation). The lncRNAs/mRNAs on the top left were downregulated lncRNAs/mRNAs (FC ≥ 2.0, P value < 0.05). The lncRNAs/mRNAs on the top right were upregulated lncRNAs/mRNAs (FC ≥ 2.0, P value < 0.05). Upregulated lncRNAs/mRNAs and downregulated lncRNAs/mRNAs were labelled red and green, respectively. After the RS-FaDu and FaDu cells were treated with 4 Gy of irradiation, their lncRNA expression levels differed significantly in 575, 361, and 1714 lncRNAs (data not shown) at 0, 2, and 48 h, respectively. Of those, 302 were upregulated and 273 were downregulated at 0 h; 113 were upregulated and 248 were downregulated at 2 h; and 759 were upregulated and 955 were downregulated at 48 h, respectively. In addition, we identified 1249, 781, and 2521 (data not shown) mRNAs that were significantly differentially expressed at 0, 2, and 48 h, respectively. Of those, 387 were upregulated and 862 were downregulated at 0 h; 227 were upregulated and 554 were downregulated at 2 h; and 1089 were upregulated and 1432 were downregulated at 48 h. Volcano plot filtering was also used to identify the 10 most upregulated and downregulated lncRNAs (Table 1) and mRNAs (Table 2) in RS-FaDu cells at 0, 2, and 48 h after 4 Gy radiation, respectively.

Differences in lncRNA and mRNA expression profiles between RS-FaDu cells and parental FaDu cells.

Figure 3: Differences in lncRNA and mRNA expression profiles between RS-FaDu cells and parental FaDu cells. (A1F1) Scatter plots. Scatter plot showed the differentially expressed lncRNAs (A1–C1) and mRNAs (D1–F1). The values on the X and Y axes from the averaged normalized signal values of groups of samples (log2 scaled). X-axis for control group (FaDu), and Y-axis for case group (RS-FaDu). All the lncRNAs/mRNAs without differential expression around the line Y = X in black. Points above Y = X and apart from Y = X are upregulated lncRNAs/mRNAs in red, and points below Y = X and apart from Y = X are downregulated lncRNAs/mRNAs in green, respectively. The threshold for differentially expressed genes was set at FC ≥ 2.0. (A2F2) Volcano plots for the differences in lncRNA (A2–C2) and mRNA (D2–F2) expression between the case group (RS-FaDu) and control group (FaDu). The X-axis in the volcano plot represents FC (after log2 transformation) and the Y-axis in the plot represents P-value (after log transformation). The lncRNAs/mRNAs on the top left show downregulated lncRNAs/mRNAs (FC ≥ 2.0, P < 0.05). The lncRNAs/mRNAs on the top right show upregulated lncRNAs/mRNAs (FC ≥ 2.0, P < 0.05). Upregulated lncRNAs/mRNAs and downregulated lncRNAs/mRNAs are shown in red and green, respectively. MS vs. M, 0 h; ES vs. E, 2 h; FS vs. F, 48 h.

Table 1: Ten most upregulated and downregulated lncRNAs in RS-FaDu cells at 0, 2, and 48 h after 4 Gy radiation

Probe name

FC (abs)

Regulation

lncRNA ID

Chr

Strand

Gene

Class

Time

p7538

6.58

up

ENST00000587434.1

17

+

ENSG00000267601.1

Antisense

0 h

p28462

5.94

up

ASO3704

ASO3704

Intergenic

0 h

p8064

4.75

up

ENST00000563172.1

18

+

ENSG00000261780.2

Intergenic

0 h

p19771

4.63

up

TCONS_00023442

15

+

XLOC_011287

Intergenic

0 h

p37817_v4

4.62

up

ENST00000607175.1

6

ENSG00000272468.1

0 h

p35075_v4

4.54

up

ENST00000594101.1

3

+

ENSG00000242086.3

Intergenic

0 h

p35072_v4

4.51

up

ENST00000597871.1

3

+

ENSG00000242086.3

Intergenic

0 h

p11909

4.41

up

ENST00000519700.1

3

+

ENSG00000242770.2

Intergenic

0 h

p6707

4.38

up

ENST00000578710.1

17

ENSG00000264673.1

Intergenic

0 h

p35069_v4

4.30

up

ENST00000438608.1

3

+

ENSG00000242086.3

Intergenic

0 h

p33918

19.81

down

hox-HOXD10-35

2

+

hox-HOXD10-35

Intronic

0 h

p33919

17.23

down

hox-HOXD10-36

2

+

hox-HOXD10-36

Intronic

0 h

p28077

14.53

down

nc-HOXD10-9

2

+

nc-HOXD10-9

Intronic

0 h

p5033

13.80

down

ENST00000556653.1

14

+

ENSG00000258914.1

Intergenic

0 h

p28072

12.49

down

nc-HOXD10-13

2

+

nc-HOXD10-13

Intronic

0 h

p10912

12.20

down

ENST00000430181.1

21

+

ENSG00000235890.1

Intronic

0 h

p28071

11.64

down

nc-HOXD10-12

2

+

nc-HOXD10-12

Intronic

0 h

p6908

10.93

down

ENST00000433510.1

17

ENSG00000233283.2

Intergenic

0 h

p8814

9.47

down

ENST00000601506.1

19

+

ENSG00000269495.1

Antisense

0 h

p33495

8.82

down

ENST00000589927.1

19

+

ENSG00000186526.7

Antisense

0 h

p29588

13.61

up

TCONS_00018436

10

XLOC_008730

Intergenic

2 h

p29587

12.47

up

TCONS_00017927

10

XLOC_008730

Intergenic

2 h

p22664

7.26

up

TCONS_00010875

5

XLOC_004700

Intergenic

2 h

p5789

6.87

up

ENST00000567091.1

16

ENSG00000260394.2

Divergent

2 h

p3381

6.81

up

ENST00000547963.1

12

ENSG00000249550.2

Intergenic

2 h

p3379

5.93

up

ENST00000550905.1

12

ENSG00000249550.2

Intergenic

2 h

p5993

5.64

up

ENST00000567668.1

16

ENSG00000260609.1

Intergenic

2 h

p19771

5.11

up

TCONS_00023442

15

+

XLOC_011287

Intergenic

2 h

p737

5.03

up

ENST00000453572.1

1

ENSG00000232184.1

Intronic

2 h

p22663

5.01

up

TCONS_00010233

5

XLOC_004700

Intergenic

2 h

p8814

23.31

down

ENST00000601506.1

19

+

ENSG00000269495.1

Antisense

2 h

p8817

15.69

down

ENST00000596286.1

19

+

ENSG00000268739.1

Antisense

2 h

p28076

12.71

down

nc-HOXD10-8

2

+

nc-HOXD10-8

Antisense

2 h

p33919

12.04

down

hox-HOXD10-36

2

+

hox-HOXD10-36

Intronic

2 h

p33918

11.42

down

hox-HOXD10-35

2

+

hox-HOXD10-35

Intronic

2 h

p28072

10.30

down

nc-HOXD10-13

2

+

nc-HOXD10-13

Intronic

2 h

p33495

10.15

down

ENST00000589927.1

19

+

ENSG00000186526.7

Antisense

2 h

p28071

10.01

down

nc-HOXD10-12

2

+

nc-HOXD10-12

Intronic

2 h

p8609

8.80

down

ENST00000595892.1

19

+

ENSG00000269640.1

Divergent

2 h

p28077

8.48

down

nc-HOXD10-9

2

+

nc-HOXD10-9

Intronic

2 h

p40301_v4

21.79

up

XR_427456.1

3

+

48 h

p3438

14.16

up

ENST00000545853.1

12

ENSG00000256732.1

Intergenic

48 h

p18725

13.84

up

TCONS_00020973

12

XLOC_010243

Intergenic

48 h

p33351

12.63

up

ENST00000420462.1

1

ENSG00000242663.1

Antisense

48 h

p11893

12.18

up

ENST00000462011.1

3

+

ENSG00000244464.1

Intergenic

48 h

p37817_v4

11.39

up

ENST00000607175.1

6

ENSG00000272468.1

48 h

p26490

11.25

up

uc004aej.3

9

BC065763

Intergenic

48 h

p26072

10.39

up

uc002oet.3

19

+

BC024306

Intergenic

48 h

p29587

10.28

up

TCONS_00017927

10

XLOC_008730

Intergenic

48 h

p14418

10.03

up

ENST00000584911.1

6

ENSG00000223414.2

Intergenic

48 h

p28077

88.86

down

nc-HOXD10-9

2

+

nc-HOXD10-9

Intronic

48 h

p33919

69.03

down

hox-HOXD10-36

2

+

hox-HOXD10-36

Intronic

48 h

p8814

52.88

down

ENST00000601506.1

19

+

ENSG00000269495.1

Antisense

48 h

p28072

49.57

down

nc-HOXD10-13

2

+

nc-HOXD10-13

Intronic

48 h

p28076

45.45

down

nc-HOXD10-8

2

+

nc-HOXD10-8

Antisense

48 h

p28071

41.28

down

nc-HOXD10-12

2

+

nc-HOXD10-12

Intronic

48 h

p33495

38.99

down

ENST00000589927.1

19

+

ENSG00000186526.7

Antisense

48 h

p33920

33.10

down

hox-HOXD11-34

2

+

hox-HOXD11-34

Intronic

48 h

p25262

26.48

down

XR_108533.1

3

LOC100505902

Intergenic

48 h

p33918

23.62

down

hox-HOXD10-35

2

+

hox-HOXD10-35

Intronic

48 h

Table 2: Ten most upregulated and downregulated mRNAs in RS-FaDu cells at 0, 2 and 48 h after 4 Gy radiation

Probe name

FC (abs)

Regulation

Genbank accession

Gene symbol

Time

A_21_P0005630

23.64873

up

NR_121672

LINC00824

0 h

A_33_P3258346

9.20869

up

NM_017523

XAF1

0 h

A_33_P3384287

9.20060

up

NM_002579

PALM

0 h

A_33_P3238533

8.80111

up

NM_001105528

CCDC178

0 h

A_23_P87013

7.73073

up

NM_001001522

TAGLN

0 h

A_33_P3381948

7.55051

up

NM_001080436

WTIP

0 h

A_23_P1029

7.11102

up

NM_017459

MFAP2

0 h

A_33_P3640690

6.67747

up

NM_001128128

ZEB1

0 h

A_24_P557479

6.51224

up

NM_017523

XAF1

0 h

A_33_P3237552

6.43079

up

NM_032843

FIBCD1

0 h

A_33_P3290780

52.36956

down

NM_001185156

IL24

0 h

A_33_P3260654

26.23980

down

EU030678

0 h

A_24_P684183

18.09698

down

NM_025257

SLC44A4

0 h

A_23_P304897

15.30950

down

NM_000623

BDKRB2

0 h

A_23_P128744

13.02192

down

NM_000710

BDKRB1

0 h

A_23_P122937

12.17637

down

NM_014800

ELMO1

0 h

A_21_P0009192

11.46747

down

0 h

A_23_P65189

11.36208

down

NM_000209

PDX1

0 h

A_23_P39315

10.78665

down

NM_021187

CYP4F11

0 h

A_23_P404494

10.34955

down

NM_002185

IL7R

0 h

A_21_P0005630

73.61931

up

NR_121672

LINC00824

2 h

A_33_P3238533

61.95869

up

NM_001105528

CCDC178

2 h

A_23_P69030

11.65424

up

NM_001850

COL8A1

2 h

A_33_P3245439

9.52713

up

NM_001250

CD40

2 h

A_23_P209055

8.46069

up

NM_001771

CD22

2 h

A_33_P3293675

7.34682

up

NM_006598

SLC12A7

2 h

A_24_P917886

7.22717

up

XM_006709947

MUC5AC

2 h

A_33_P3382177

7.02720

up

NM_003255

TIMP2

2 h

A_32_P530933

6.34961

up

NM_015617

PYGO1

2 h

A_23_P159721

6.29696

up

NM_004224

GPR50

2 h

A_33_P3393971

27.56643

down

NM_000299

PKP1

2 h

A_23_P23296

24.91828

down

NM_000299

PKP1

2 h

A_23_P143029

21.06592

down

NM_021192

HOXD11

2 h

A_24_P245379

13.24701

down

NM_002575

SERPINB2

2 h

A_33_P3220911

12.74436

down

NM_004335

BST2

2 h

A_33_P3226810

12.12693

down

NM_003810

TNFSF10

2 h

A_23_P404494

10.63455

down

NM_002185

IL7R

2 h

A_24_P236935

10.10874

down

NM_001012964

KLK6

2 h

A_21_P0011633

9.24221

down

NM_000526

KRT14

2 h

A_23_P39315

9.24213

down

NM_021187

CYP4F11

2 h

A_33_P3238533

132.03939

up

NM_001105528

CCDC178

48 h

A_21_P0005630

41.69042

up

NR_121672

LINC00824

48 h

A_23_P161190

30.52496

up

NM_003380

VIM

48 h

A_23_P70468

29.94054

up

NM_012367

OR2B6

48 h

A_33_P3340014

18.30612

up

NM_016157

TRO

48 h

A_33_P3514487

16.05847

up

NM_198481

VSTM1

48 h

A_24_P211849

13.71514

up

NM_001166220

TBX20

48 h

A_23_P421379

12.63051

up

NM_000612

IGF2

48 h

A_23_P69030

12.08606

up

NM_001850

COL8A1

48 h

A_23_P41804

11.93085

up

NM_033120

NKD2

48 h

A_23_P39315

39.50620

down

NM_021187

CYP4F11

48 h

A_23_P143029

38.05859

down

NM_021192

HOXD11

48 h

A_23_P50710

31.23669

down

NM_001082

CYP4F2

48 h

A_33_P3393971

26.30644

down

NM_000299

PKP1

48 h

A_23_P23296

24.31587

down

NM_000299

PKP1

48 h

A_24_P42693

23.02732

down

NM_021187

CYP4F11

48 h

A_23_P108280

20.67472

down

NM_023944

CYP4F12

48 h

A_24_P684183

19.34901

down

NM_025257

SLC44A4

48 h

A_23_P138541

14.88679

down

NM_003739

AKR1C3

48 h

A_23_P300781

13.48931

down

NM_013316

CNOT4

48 h

Venn diagrams of the numbers and percentages of differentially expressed genes are shown in Figure 4. The results showed that there were 20 (2.0%) common differentially upregulated lncRNAs (Figure 4A) and 65 (5.4%) common differentially downregulated lncRNAs (Figure 4B) for the three groups (Supplementary Table 1). In addition, the numbers of common upregulated (Figure 4C) and downregulated (Figure 4D) differentially expressed mRNAs were 59 (4.3%) and 153 (7.0%), respectively (Supplementary Table 2).

Venn diagram for the common and exclusively expressed lncRNAs and mRNAs from each group.

Figure 4: Venn diagram for the common and exclusively expressed lncRNAs and mRNAs from each group. FaDu and RS-FaDu cells at 0, 2, and 48 h after irradiation with 4 Gy. Different lncRNAs and mRNAs between FaDu and RS-FaDu as determined by microarray analysis for overlapping signature. (A) The overlapping results of upregulated differentially expressed lncRNAs. (B) The overlapping results of downregulated differentially expressed lncRNAs. (C) The overlapping results of upregulated differentially expressed mRNAs. (D) The overlapping results of downregulated differentially expressed mRNAs. MS vs. M, 0 h; ES vs. E, 2 h; FS vs. F, 48 h.

Validation of differential lncRNA expression by qRT-PCR

The qRT-PCR was used to confirm the reliability and validity of microarray data. We selected four lncRNAs (ENST00000470135, TCONS_00010875, TCONS_00018436, and hox-HOXD10-35) for validation since these lncRNAs had consistent up- or downregulations at the three time points and their FC values were prominent at some time points. Additionally, four mRNAs (CKMT1A, GPNMB, FBLN5, and GDA) were validated as well due likely to their potential roles in irradiation response or radioresistance. The relative expression levels of the target RNAs were given as ratios of β-actin transcript levels in the same RNA samples. As shown in Figure 5, the expression levels of these eight genes were consistent with the microarray results, indicating the reliability of the microarray data and correlation of these genes with radioresistance.

Validation of differential lncRNA expressions by qRT-PCR.

Figure 5: Validation of differential lncRNA expressions by qRT-PCR. (A) ENST00000470135; (B) hox-HOXD10-35; (C) TCONS_00010875; (D) TCONS_00018436; (E) CKMT1A; (F) GPNMB; (G) FBLN5; (H) GDA. After normalization to ACTB, data were presented as mean ± SD. n = 3, *P < 0.05, **P < 0.01.

Potential roles of TCONS_00018436 in regulation of radioresistance of HSCC

We then assessed the expression of the four validated lncRNAs in primary tumor tissues of HSCC patients versus their recurrent ones after postoperative radiotherapy, using qRT-PCR. The expression of the three lncRNAs showed no remarkable difference between two groups of samples (Figure 6A6C), while the significant upregulation of TCONS_00018436 in relapsed tumor samples was found (Figure 6D, *P < 0.05). Further, after we stably knocked down TCONS_00018436 in FaDu-RS cells using lentiviral transfection, both transfected FaDu-RS cells (FaDu-RS-sh) and FaDu-RS cells were treated with 4 Gy, 6 Gy and 8 Gy irradiation, respectively. The apoptotic cells at 48 h after irradiation were determined by Annexin V-FITC/PI and flow cytometry. As shown in Figure 6E, depletion of TCONS_00018436 significantly sensitized RS-FaDu cells to the indicated doses of radiation (*P < 0.05), indicating that upregulated TCONS_00018436 might control radioresistance of HSCC cells during exposure to radiation. However, the underlying mechanism remains to be further investigated.

Potential roles of TCONS_00018436 in radioresistance of HSCC cells.

Figure 6: Potential roles of TCONS_00018436 in radioresistance of HSCC cells. The relative expression of ENST00000470135 (A), hox-HOXD10-35 (B), TCONS_00010875 (C) and TCONS_00018436 (D) in primary vs. recurrent HSCC tissue samples were measured by qRT-PCR. Their expression in each sample was normalized to the mean expression of their respective primary samples. Data were presented as mean ± SD. n = 13, *P < 0.05. (E) FaDu-RS cells and those stably transfected with shRNA of TCONS_00018436 were both treated with 4 Gy, 6 Gy, and 8 Gy irradiation, respectively. The fractions of apoptotic cells were determined by using Annexin V/PI dual staining after 48 h. Data were presented as mean ± SD. n = 3, *P < 0.05.

Bioinformatics analyses

In order to identify potential protein regulators involved in radioresistance of HSCC, we performed pathway enrichment analysis by functionally annotating and differentially expressed mRNAs in FaDu vs. FaDu-RS cells at 0, 2, and 48 h after irradiation. The detailed information on significantly enriched pathway terms and dysregulated mRNAs at the three time points involved in them was presented in Supplementary Tables 3–5, respectively. The most significant 30 terms sorted by corrected P-value were separately listed in three histograms, according to the time points after irradiation shown in Supplementary Figure 1. This analysis approach may help identify altered expression of mRNAs involved in pathways associated with radioresistance, whose dysregulation might have an impact on sensitivity of HSCC to radiation.

An increasing number of lncRNAs have been shown to regulate expression of target genes in cis or in trans. Thus, we found significant correlations between dysregulated lncRNAs and mRNAs at 0, 2, and 48 h after irradiation, respectively. After lncRNA and mRNA correlation, cis-prediction and trans-prediction were both applied to the data. The final lncRNA prediction results are the combination of results from these two prediction parts at 0, 2, and 48 h as shown in Tables 35, respectively. These pathway enrichment analysis may provide some mRNA candidates that are potentially associated with radioresistance. Furthermore, we might further identify the lncRNAs in regulating the expressions of nearby or distant genes which encode these mRNAs based on the prediction results.

Table 3: lncRNA target prediction of RS-FaDu vs. FaDu at 0 h

lncRNA

mRNA

Correlation

P-value

Direction (lncRNA-mRNA)

cisregulation

transregulation

p3758

A_33_P3421178

0.999026552

0.000001421

down-down

Sense

p13056

A_21_P0012973

0.993822774

0.000057119

up-up

Sense

p25219

A_33_P3368495

0.998540055

0.000003196

down-down

miRNA sequestration

p7538

A_33_P3382177

0.999529708

0.000000332

up-up

Antisense

p35072_v4

A_19_P00315941

0.997663892

0.000008180

up-up

Sense

p12195

A_19_P00316857

0.994153893

0.000051166

up-up

Sense

p26166

A_24_P557479

−0.997108515

0.000012529

down-up

miRNA sequestration

p29619

A_21_P0007233

0.992506995

0.000084007

down-down

Sense

p38695_v4

A_23_P148919

−0.99696864

0.000013770

up-down

miRNA sequestration

p192

A_23_P148919

0.994529457

0.000044808

down-down

Antisense

p1665

A_33_P3278211

0.994573678

0.000044088

down-down

Sense

p30074

A_33_P3289416

0.990995817

0.000121248

down-down

miRNA sequestration

p10587

A_24_P115199

−0.99188824

0.000098434

up-down

miRNA sequestration

p8323

A_24_P115199

−0.997557313

0.000008943

up-down

miRNA sequestration

p687

A_21_P0001239

0.991689858

0.000103301

down-down

Sense

p686

A_21_P0001239

0.999058836

0.000001328

down-down

Sense

p34021_v4

A_21_P0001239

0.998331716

0.000004172

down-down

Sense

p7388

A_33_P3341836

0.997644418

0.000008317

up-up

miRNA sequestration

p687

A_32_P212373

0.991025177

0.000120460

down-down

Sense

p686

A_32_P212373

0.998954092

0.000001640

down-down

Sense

p34021_v4

A_32_P212373

0.998577934

0.000003032

down-down

Sense

p686

A_21_P0001238

0.994752897

0.000041226

down-down

Sense

p34021_v4

A_21_P0001238

0.992305807

0.000088573

down-down

Sense

p38695_v4

A_33_P3414487

−0.99790579

0.000006574

up-down

miRNA sequestration

p10433

A_23_P210425

0.993170163

0.000069811

up-up

Antisense

p4963

A_23_P304897

0.994892042

0.000039070

down-down

Intronic

p6222

A_24_P80135

0.997657113

0.000008227

down-down

miRNA sequestration

p15211

A_23_P320878

0.993544033

0.000062385

down-down

miRNA sequestration

Table 4: LncRNA target prediction of RS-FaDu vs. FaDu at 2 h

lncRNA

mRNA

Correlation

P-value

Direction (lncRNA-mRNA)

cisregulation

transregulation

p20305

A_33_P3266898

−0.996352571

0.000019931

up-down

miRNA sequestration

p30194

A_33_P3266898

−0.996726605

0.000016055

up-down

miRNA sequestration

p33576

A_32_P131031

0.992702048

0.000079696

down-down

Intergenic (10 k)

p36121_v4

A_21_P0004245

0.990861638

0.000124883

down-down

Sense

p8814

A_24_P236935

0.995770285

0.000026798

down-down

Antisense

p687

A_24_P915692

0.990515655

0.000134503

down-down

miRNA sequestration

p24838

A_33_P3278211

0.998051663

0.000005690

down-down

Sense

p1665

A_33_P3278211

0.998814061

0.000002109

down-down

Sense

p37870_v4

A_33_P3289416

−0.990915820

0.000123409

up-down

miRNA sequestration

p25347

A_24_P940149

−0.996508538

0.000018264

up-down

miRNA sequestration

p25347

A_32_P152437

0.996042331

0.000023464

up-up

miRNA sequestration

p30340

A_24_P602871

0.995141025

0.000035357

down-down

miRNA sequestration

p25605

A_23_P329112

0.996929698

0.000014126

up-down

miRNA sequestration

p25347

A_23_P329112

0.994658656

0.000042719

up-down

miRNA sequestration

p11034

A_24_P66027

0.991916997

0.000097738

down-down

Antisense

p28133

A_24_P115199

0.997640377

0.000008345

down-down

miRNA sequestration

p30155

A_24_P115199

0.990576762

0.000132778

down-down

miRNA sequestration

p33798

A_23_P60339

−0.994723656

0.000041686

up-down

miRNA sequestration

p687

A_32_P212373

0.992913328

0.000075153

down-down

Sense

p686

A_32_P212373

0.994692846

0.000042174

down-down

Sense

p34021_v4

A_32_P212373

0.991057378

0.000119598

down-down

Sense

p20305

A_23_P208389

0.996581866

0.000017505

up-up

miRNA sequestration

p34907_v4

A_33_P3333554

0.990605549

0.000131969

down-down

miRNA sequestration

p10433

A_23_P210425

0.998311004

0.000004277

up-up

Antisense

p30335

A_23_P157022

0.991277419

0.000113793

down-down

miRNA sequestration

p15938

A_21_P0005906

0.995291866

0.000033198

down-down

Intergenic (10 k)

p34907_v4

A_33_P3378430

0.991616881

0.000105120

down-down

miRNA sequestration

p20305

A_32_P31618

−0.992612720

0.000081656

up-down

miRNA sequestration

p15519

A_33_P3233273

0.990760089

0.000127670

down-down

Intergenic (10 k)

Table 5: LncRNA target prediction of RS-FaDu vs. FaDu at 48 h

lncRNA

mRNA

Correlation

P-value

Direction (lncRNA-mRNA)

cisregulation

transregulation

p24892

A_33_P3250133

0.993774158

0.000058021

up-up

miRNA sequestration

p36462_v4

A_24_P111242

−0.997243502

0.000011387

down-up

miRNA sequestration

p2627

A_21_P0014268

0.996216336

0.000021447

up-up

Sense

p25293

A_23_P38813

−0.997569809

0.000008852

up-down

miRNA sequestration

p24618

A_23_P38813

0.996136217

0.000022364

down-down

miRNA sequestration

p37916_v4

A_23_P38813

−0.991608950

0.000105319

up-down

miRNA sequestration

p44617_v4

A_23_P38813

−0.993806999

0.000057411

up-down

miRNA sequestration

p25051

A_23_P38813

−0.995045168

0.000036765

up-down

miRNA sequestration

p28498

A_23_P38813

−0.994453852

0.000046054

up-down

miRNA sequestration

p122

A_23_P38813

−0.994491445

0.000045433

up-down

miRNA sequestration

p3143

A_23_P38813

0.997519222

0.000009224

down-down

miRNA sequestration

p11437

A_23_P38813

−0.995453161

0.000030964

up-down

miRNA sequestration

p37026_v4

A_23_P38813

−0.994529667

0.000044805

up-down

miRNA sequestration

p23798

A_23_P38813

0.992085159

0.000093719

down-down

miRNA sequestration

p29606

A_23_P38813

−0.998223527

0.000004731

up-down

miRNA sequestration

p28658

A_23_P38813

−0.993772836

0.000058046

up-down

miRNA sequestration

p24771

A_21_P0014060

0.995431495

0.000031259

up-up

Sense

p34907_v4

A_24_P319364

−0.996770625

0.000015626

down-up

miRNA sequestration

p29827

A_33_P3336622

0.994560238

0.000044306

up-up

miRNA sequestration

p29606

A_33_P3336622

0.993785701

0.000057806

up-up

miRNA sequestration

p26063

A_33_P3390723

0.990423713

0.000137119

up-up

miRNA sequestration

p24892

A_23_P45799

−0.997314248

0.000010810

up-down

miRNA sequestration

p34907_v4

A_24_P129232

−0.992791851

0.000077749

down-up

miRNA sequestration

p18271

A_24_P684183

−0.990582868

0.000132606

up-down

miRNA sequestration

p44617_v4

A_24_P684183

−0.990879668

0.000124391

up-down

miRNA sequestration

p18272

A_24_P684183

−0.993001983

0.000073287

up-down

miRNA sequestration

p8313

A_23_P165186

0.990188970

0.000143912

up-up

Bidirectional

p7538

A_33_P3382177

0.990676885

0.000129976

up-up

Antisense

p41822_v4

A_32_P126698

0.993882119

0.000056028

up-up

miRNA sequestration

p25293

A_23_P149099

−0.991073247

0.000119175

up-down

miRNA sequestration

p18271

A_23_P149099

−0.991096396

0.000118558

up-down

miRNA sequestration

p823

A_23_P149099

−0.992591892

0.000082117

up-down

miRNA sequestration

p23798

A_23_P149099

0.993960353

0.000054606

down-down

miRNA sequestration

p25999

A_23_P149099

−0.991209023

0.000115582

up-down

miRNA sequestration

p25051

A_24_P382630

−0.998198512

0.000004865

up-down

miRNA sequestration

p28498

A_24_P382630

−0.991372680

0.000111325

up-down

miRNA sequestration

p16320

A_23_P62679

−0.995317469

0.000032838

up-down

miRNA sequestration

p13683

A_33_P3233841

0.993630385

0.000060729

up-up

Antisense

p21313

A_19_P00317856

0.993327189

0.000066641

up-up

Sense

miRNA sequestration

p36492_v4

A_33_P3221748

0.995546108

0.000029712

up-up

Sense

p19344

A_24_P250535

0.991880869

0.000098613

up-up

miRNA sequestration

p8693

A_24_P250535

0.991653359

0.000104209

up-up

miRNA sequestration

p14566

A_19_P00319254

0.991633933

0.000104694

down-down

Sense

p22664

A_23_P41804

0.995620949

0.000028722

up-up

Intergenic (10 k)

p22663

A_23_P41804

0.997949994

0.000006299

up-up

Intergenic (10 k)

p37916_v4

A_33_P3215277

0.992325400

0.000088123

up-up

miRNA sequestration

p28498

A_33_P3215277

0.993349818

0.000066190

up-up

miRNA sequestration

p20125

A_33_P3256490

0.993114016

0.000070962

up-up

miRNA sequestration

p2107

A_33_P3256490

0.996526411

0.000018078

up-up

miRNA sequestration

p33596

A_23_P347468

0.990934613

0.000122899

down-down

miRNA sequestration

p4313

A_33_P3239084

0.991022154

0.000120541

down-down

miRNA sequestration

p26099

A_23_P381368

0.992698802

0.000079767

down-down

Intergenic (10 k)

p28109

A_23_P381368

0.998436798

0.000003663

down-down

miRNA sequestration

p5755

A_24_P56894

0.990801171

0.000126538

up-up

miRNA sequestration

p16320

A_24_P56894

0.991795931

0.000100684

up-up

miRNA sequestration

p2195

A_23_P134935

0.995584780

0.000029198

up-up

miRNA sequestration

p18273

A_23_P76749

0.991517681

0.000107619

up-up

miRNA sequestration

p18273

A_23_P336929

0.990945545

0.000122604

up-up

miRNA sequestration

p3234

A_24_P380022

−0.990116941

0.000146030

up-down

miRNA sequestration

p16320

A_33_P3319593

−0.991594493

0.000105682

up-down

miRNA sequestration

p37870_v4

A_33_P3319593

−0.993768247

0.000058131

up-down

miRNA sequestration

p36411_v4

A_24_P941217

−0.992930705

0.000074786

down-up

miRNA sequestration

p25274

A_24_P941217

0.993605918

0.000061196

up-up

miRNA sequestration

p30340

A_23_P209320

−0.991624411

0.000104932

down-up

miRNA sequestration

p34907_v4

A_33_P3424297

0.991763098

0.000101490

down-down

miRNA sequestration

p30340

A_33_P3424297

0.990792516

0.000126776

down-down

miRNA sequestration

p8323

A_33_P3418394

0.996071022

0.000023125

up-up

miRNA sequestration

p11437

A_33_P3418394

0.992377207

0.000086939

up-up

miRNA sequestration

p1517

A_21_P0014248

0.993602194

0.000061267

up-up

Sense

p14566

A_19_P00322225

0.991838124

0.000099652

down-down

Sense

p26790

A_24_P940149

0.993717158

0.000059087

down-down

Antisense

p17915

A_23_P416305

−0.993783331

0.000057850

down-up

miRNA sequestration

p750

A_21_P0010797

0.996064600

0.000023201

up-up

Sense

p29253

A_32_P173058

0.992308714

0.000088506

up-up

miRNA sequestration

p36497_v4

A_19_P00319372

0.993618413

0.000060957

up-up

Intronic

p36069_v4

A_19_P00319372

0.994980191

0.000037734

up-up

Sense

p3143

A_23_P383031

0.994487956

0.000045490

down-down

miRNA sequestration

p18271

A_24_P409042

−0.993703568

0.000059343

up-down

miRNA sequestration

p24618

A_24_P409042

0.997488035

0.000009457

down-down

miRNA sequestration

p18273

A_24_P409042

−0.991108770

0.000118230

up-down

miRNA sequestration

p25051

A_24_P409042

−0.994189287

0.000050548

up-down

miRNA sequestration

p18272

A_24_P409042

−0.994084150

0.000052392

up-down

miRNA sequestration

p7539

A_24_P409042

−0.991072129

0.000119205

up-down

miRNA sequestration

p18273

A_23_P397856

−0.993936073

0.000055045

up-down

miRNA sequestration

p6823

A_24_P254346

−0.995095345

0.000036024

up-down

miRNA sequestration

p41766_v4

A_23_P97021

−0.991498540

0.000108105

up-down

miRNA sequestration

p29786

A_23_P97021

−0.995760159

0.000026926

up-down

miRNA sequestration

p9299

A_23_P97021

−0.990583844

0.000132579

up-down

miRNA sequestration

p28283

A_23_P97021

−0.991229915

0.000115034

up-down

miRNA sequestration

p18271

A_24_P373286

0.992099626

0.000093377

up-up

miRNA sequestration

p24976

A_23_P86182

0.994761294

0.000041094

down-down

miRNA sequestration

p16298

A_32_P90080

0.997392142

0.000010193

down-down

miRNA sequestration

p7391

A_23_P371885

0.995164968

0.000035010

up-up

miRNA sequestration

p16320

A_21_P0013080

−0.991724549

0.000102441

up-down

miRNA sequestration

p37870_v4

A_21_P0013080

−0.990354772

0.000139097

up-down

miRNA sequestration

p4547

A_23_P329112

−0.990672972

0.000130084

down-up

miRNA sequestration

p11094

A_23_P26704

−0.990068457

0.000147464

up-down

miRNA sequestration

p8313

A_23_P26704

−0.992380572

0.000086862

up-down

miRNA sequestration

p29606

A_23_P26704

−0.996163250

0.000022053

up-down

miRNA sequestration

p15693

A_23_P304682

−0.990624661

0.000131433

up-down

miRNA sequestration

p12560

A_23_P304682

−0.990915532

0.000123416

up-down

miRNA sequestration

p40979_v4

A_33_P3391005

−0.996196971

0.000021667

down-up

miRNA sequestration

p38890_v4

A_32_P831181

−0.996877479

0.000014610

up-down

miRNA sequestration

p3356

A_21_P0014571

0.991097745

0.000118522

up-up

Sense

p12621

A_19_P00317034

0.993856369

0.000056500

down-down

Sense

p5975

A_23_P63660

−0.991237992

0.000114823

up-down

miRNA sequestration

p9442

A_23_P63660

−0.993997587

0.000053935

up-down

miRNA sequestration

p122

A_21_P0001724

0.990393941

0.000137971

up-up

Sense

p24892

A_23_P211748

0.992553680

0.000082965

up-up

miRNA sequestration

p1517

A_23_P161190

0.990268562

0.000141591

up-up

Intergenic (10 k)

p29965

A_23_P208389

−0.999649344

0.000000184

down-up

miRNA sequestration

p20045

A_23_P208389

−0.993224778

0.000068700

down-up

miRNA sequestration

p33596

A_23_P146209

0.994585549

0.000043895

down-down

miRNA sequestration

p34907_v4

A_33_P3333554

0.992145626

0.000092295

down-down

miRNA sequestration

p38352_v4

A_23_P155666

0.997567735

0.000008867

down-down

miRNA sequestration

p36486_v4

A_23_P64792

−0.992286627

0.000089015

down-up

miRNA sequestration

p23949

A_23_P64792

0.992666927

0.000080464

up-up

miRNA sequestration

p25165

A_23_P50897

0.990700732

0.000129312

down-down

Antisense

p10750

A_33_P3303305

0.991255110

0.000114375

down-down

Intronic

p33919

A_23_P337201

0.997063796

0.000012919

down-down

miRNA sequestration

p1358

A_21_P0010738

0.996673835

0.000016577

down-down

Sense

p6352

A_23_P163306

0.993659613

0.000060173

down-down

miRNA sequestration

p18271

A_24_P109652

0.992664902

0.000080508

up-up

miRNA sequestration

p2107

A_21_P0006705

0.998881367

0.000001876

up-up

Sense

p4653

A_23_P304897

0.995441532

0.000031122

down-down

Intronic

p4963

A_23_P304897

0.999067618

0.000001304

down-down

Intronic

p39057_v4

A_33_P3259542

0.993876252

0.000056136

up-up

miRNA sequestration

p26034

A_33_P3259542

0.990129120

0.000145671

up-up

miRNA sequestration

p6898

A_21_P0014351

0.993996895

0.000053948

down-down

Sense

p34009_v4

A_23_P104188

0.992257395

0.000089690

down-down

Intergenic (10 k)

p34993_v4

A_23_P117582

0.992864673

0.000076188

up-up

miRNA sequestration

p25051

A_23_P117582

0.990949567

0.000122495

up-up

miRNA sequestration

DISCUSSION

To investigate the role of lncRNAs in the radioresistance of HSCC, we first observed the expression profiles of lncRNA in our established radioresistant HSCC cell model, i.e. RS-FaDu. The expression levels of lncRNA in the RS-FaDu and the parental FaDu cells were determined by microarray analysis immediately, at 2 h or 48 h after exposure to 4 Gy irradiation. This approach enabled us to observe the time-course differential expression patterns of lncRNA and mRNA in RS-FaDu vs. parental FaDu cells at the early and late stages of their irradiation response. Extracellular stimulation can bring about a rapid change on transcription of related genes. However, it is hard to determine the exact time points of each stage. Borràs-Fresneda, et al. found that a greatly differential transcriptional response in the radioresistant cell line was induced at 4 h after irradiation compared with the radiosensitive one [27]. To make transcriptomic analyses of the radiation response in head and neck squamous cell carcinoma subclones with different radiosensitivity, Michna, et al. even detected gene expression at 0.25, 2, 7, 12, 24, 48, 72 and 96 h after irradiation by microarray [28]. According to their experience, we selected these time points to roughly observe the early and late transcriptional response of FaDu and FaDu-RS cells to irradiation in the current study. Additionally, Li et al also carried out research on the relationship between lncRNA and radioresistance in nasopharyngeal carcinoma through genome-wide analyses [29]. However, the authors did not look at response time, which might effectively narrow our search for target lncRNAs and mRNAs.

Furthermore, we identified lncRNAs and mRNAs that were up- or downregulated at above three time points, and they were considered more likely to be involved in HSCC radioresistance. Subsequent validation experiments not only confirmed the reliability of the microarray data but also provided four lncRNA or mRNA candidates for our future mechanism study. Among these, TCONS_00018436 was considered more promising, due to that its potential role was preliminarily verified by its upregulated expression in relapsed tumor samples posterior to radiotherapy and loss-of-function assays.

Considering that altered response processes might occur at different stages after irradiation, we functionally annotated dysregulated mRNAs and performed bioinformatics analyses according to the respective response times. Among the most significantly enriched pathway terms, several attracted our attention because of their close relationship with radioresistance, such as the p53 signaling pathway at 0 h and at 2 h [30, 31], and the Wnt signaling pathway at 48 h [32]. These results offer us preferential pathways in which to study the mechanisms underlying HSCC radioresistance. From these results, some candidate mRNAs could be identified based on their altered expression profiles of mRNAs as well.

LncRNAs are well known to affect the expression of target genes in cis or in trans through binding promoter regions of specific sequences, recruiting relevant transcription factors, and sequestering the interaction of miRNAs with target mRNAs, etc [3336]. Thus, we identified dysregulated lncRNAs and their predicted mRNA targets on the basis of complementary base sequences and expression changes from our microarray data. According to dysregulation and association of mRNAs with radioresistance-related pathways in the pathway enrichment analysis, their matched lncRNAs could be found in our prediction results. We thought that it was likely a feasible way to search for lncRNA candidates for the further study.

Emerging evidence indicates that lncRNAs might function as competing endogenous RNAs by sponging miRNAs in a variety of cancers [3740]. Notably, the lncRNAs NEAT1 [25] and MALAT1 [13, 24] have been shown to modulate radioresistance via sequestration of related miRNAs in nasopharyngeal carcinoma as well as high-risk human papillomavirus-positive cervical cancer. The regulatory roles of miRNAs are well established in the radioresistance of cancers [4145], suggesting that we should explore the molecular mechanisms of lncRNAs in HSCC radioresistance from the perspective of lncRNA-miRNA-mRNA axes. Using sequence pairing, a number of dysregulated lncRNAs from our microarray data and matched potential miRNA targets were identified (data not shown) in preparation for verifying our hypothesis.

In addition to the exploration of mechanisms underlying HSCC radioresistance, the identification of biomarkers for predicting radioresistant HSCC is of great clinical significance. Recently, a growing number of circulating or tissue-derived lncRNAs have been shown to be correlated with clinicopathological characteristics in patients with cancer [4648], making them promising candidate biomarkers of malignancy. Given the close relationship between lncRNAs and radioresistant HSCC cells discussed above, lncRNAs have the potential to become novel biomarkers for the evaluation of HSCC radioresistance. We further plan to measure the expression levels of candidate lncRNAs in tumor tissues as well as blood samples from HSCC patients and explore the correlation between expression levels and different responses of HSCC patients to routine radiation therapy.

In this study, we for the first time have comprehensively demonstrated the time-course expression profiles of human lncRNAs/mRNAs in radioresistant RS-FaDu cells derived from FaDu cells. Through validation experiments and subsequent preliminary investigation, TCONS_00018436 emerged as a promising candidate for studying the molecular mechanism underlying radioresistance of HSCC. Moreover, a large number of lncRNAs or mRNAs still awaits for being discovered through the bioinformatics analyses. In conclusion, our data laid the foundation for further investigating the roles of these lncRNAs and mRNAs in the occurrence and development of HSCC radioresistance. In addition, novel therapeutic targets and diagnostic biomarkers are likely to be identified in the future on the basis of our data.

MATERIALS AND METHODS

Establishment of a radioresistant cell line

The HSCC FaDu cell line was purchased from the Type Culture Collection of the Chinese Academy of Sciences (Beijing, China). The cells were cultured in MEM (Gibico, Grand Island, NY, USA) with 10% fetal bovine serum (FBS), 2 mM glutamine, 100 units/ml penicillin, and 100 μg/ml streptomycin and incubated at 37°C with humidified 5% CO2.

RS-FaDu cells were created by repeatedly exposing the parental FaDu cells to irradiation [15]. Briefly, FaDu cells were grown in 75-mm2 cell culture plates. After the cells reached 70–80% confluence, they were irradiated with X-rays at room temperature. The X-ray generator (MBR-1505R; Hitachi Medical Co., Tokyo, Japan) was operated at 210 kV and 10 mA, with 0.5 mm Al external filtration. The dose rate was 1.8 Gy/min. The cells were exposed to doses of 2, 4, 6, 8, and 10 Gy and were irradiated with each dose twice (total dose of 60 Gy). An interval of 2 to 4 weeks between each dose allowed the surviving cells to regenerate. The process of irradiation and culture lasted for about 10 months. The HSCC cell clones that recovered after exposure to ionizing radiation were collected for further experiments.

Patient specimens

Primary and recurrent tumor samples were obtained from 13 patients who received radiotherapy followed by surgery in Qilu hospital from March 2013 to October 2015, and then salvage surgery due to local recurrence. After surgery, samples were cleaned with phosphate-buffered saline (PBS) and immediately put into liquid nitrogen at once. At least 24 h later, samples were transferred to −80°C for long-term storage. Characteristics of patients were summarized in Table 6. Prior to this study, written informed contents were signed, and this study was conducted under the approval of the institutional review board of the Ethics Boards of Qilu Hospital.

Table 6: Clinical characteristics of patients

Characteristics

No. Patients

Sex

 Female

0

 Male

13

Age (years old)

(Median 57, Range 49–67)

Drinking

 Regularly

9

 Occasionally

4

 Seldom

0

Smoking

 Regularly

10

 Occasionally

0

 Seldom

3

*Histological Differentiation

 Well-Moderate

2

 Poor

11

*Clinical Stage

 I + II

1

 III + IV

12

*Treatment

 S + X

13

*at the first visit.

S: Surgery; X: radiation.

Clonogenic assay

Both parental FaDu and radioresistant RS-FaDu cells were plated in six-well culture plates and irradiated with a single dose of 0, 2, 4, or 6 Gy, respectively. Plated cell numbers were as follows: 300 cells for 0 Gy, 600 cells for 2 Gy, 900 cells for 4 Gy, and 1200 cells for 6 Gy. Following irradiation, the cells were cultured in a 5% CO2 atmosphere at 37°C, and the medium was changed every 3 days. After 12 days, colonies were fixed with ethanol for 15 min and stained with 0.1% crystal violet for 15 min. Colonies with > 50 cells were scored with a ColCount colony counter (Oxford Optronix, Oxford, United Kingdom). All experiments were performed in triplicate. The survival fraction (SF) was estimated by the following formula: SF = [number of colonies formed/number of cells seeded × plating efficiency of the control group], where plating efficiency was calculated as the ratio between colonies observed and number of cells plated. Dose-response clonogenic survival curves were plotted on a log-linear scale using Graphpad Prism 5 software.

Apoptosis assay

Apoptotic cells were identified by using the Annexin V-FITC and propidium iodide (PI) apoptosis detection kit (BestBio, Shanghai, China) according to the manufacturer’s instructions. Briefly, RS-FaDu and FaDu cells were seeded at a density of 4 × 105 cells in six-well plates and were incubated for 12 h before being treated with 4 Gy of radiation. The cells were then harvested at four different time points after X-ray exposure (0, 24, 48, and 72 h, respectively). After being washed twice with PBS, the cells were resuspended in 400 μL 1 × binding buffer and stained with 5 μL Annexin V-FITC for 15 min and 10 μL PI for 5 min at 4°C in the dark. Apoptosis was analyzed by a Gallios flow cytometer (Beckman Coulter, Brea, CA, USA). The percentage of total apoptosis was calculated as the sum of the early apoptosis (Annexin V+/PI−) and the late apoptosis (Annexin V+/PI+). The experiments were repeated three times and data were analyzed by Kaluza software (version 1.2; Beckman Coulter).

RNA extraction and microarray analysis

RS-FaDu and FaDu cells were seeded at a density of 4 × 105 cells in three six-well plates each. They were treated with 4 Gy of radiation and then cultured under the indicated experimental conditions. Cells were harvested at three different time points after X-ray exposure (0, 2, and 48 h, respectively). Total RNA from each sample was extracted using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s instructions. RNA concentration was quantified by the NanoDrop ND-1000 (NanoDrop Technologies/Thermo Scientific, Wilmington, DE, USA), and RNA integrity was assessed by standard denaturing agarose gel electrophoresis. The sample preparation and microarray hybridization were performed based on the manufacturer’s standard protocols with minor modifications. Briefly, total RNA was purified after removal of rRNA and tRNA (mRNA-ONLY Eukaryotic mRNA Isolation Kit, Epicentre, Madison, WI, USA). Then, each sample was amplified and transcribed into fluorescent cRNA, along the entire length of the transcript without 3’ bias, utilizing a random priming method. The labeled cRNAs were hybridized onto the Agilent Human LncRNA v4.0 (4 × 180 K, Arraystar; Agilent Technologies, Santa Clara, CA, USA). The slides were then washed, and the tiff-format original array images were acquired by the Agilent G2505C Scanner (Agilent Technologies).

Microarray data analysis

The tiff-format original array images were pre-processed via Agilent Feature Extraction software (version 11.0.1.1) and then quantile normalization and differential expression analysis were conducted using the GeneSpring GX software package (version 11.5.1; Agilent Technologies). Cluster analysis and graphical illustration were performed using Cluster 3.0 software. Time-course differentially expressed lncRNAs and mRNAs with statistical significance between the two groups were identified through scatter plot filtering and volcano plot filtering. To filter out outlier samples, we performed hierarchical clustering to show any differences in expression intensity between the clustering group and true group results. The differentially expressed mRNAs were submitted to six pathway databases (KEGG PATHWAY, PID Curated, PID BioCarta, PID Reactome, BioCyc, Reactome, and Panther) for pathway enrichment analysis. After lncRNA and mRNA correlation, lncRNA target prediction included cis-prediction and trans-prediction. To determine cis-prediction, we searched for mRNAs that were in the region of 10 kb around the lncRNA. Trans-prediction was based on sequence alignment, which aligns lncRNA to the 3′UTR of mRNA. Then lncRNA-mRNA pairs that share similar sequences were identified from the trans-prediction results. In the lncRNA target prediction analysis, mRNA targets were predicted from cis-prediction and trans-prediction.

Validation of lncRNA and mRNA expression by quantitative real-time polymerase chain reaction

Quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the microarray data. Briefly, total RNA was reverse-transcribed to cDNA using SuperScript III Reverse Transcriptase (Invitrogen) following the manufacturer’s protocol. qRT-PCR was performed using the SYBR Green chemistry in the GeneAmp PCR System 9700 (ABI Applied Biosystems, Foster City, CA, USA). The forward and reverse primers for validation are listed in Table 7. PCR was performed in a 10-μL reaction volume and consisted of an initial denaturation step at 95°C for 10 min followed by amplification with 40 cycles at 95°C for 10 sec and 60°C for 60 sec. The threshold cycle (CT) was defined as the cycle number at which the fluorescence passed a predetermined threshold. Both target and reference (β-actin) genes were amplified in separate wells in triplicate. Gene expression was calculated using the comparative threshold cycle (2−ΔCT) method.

Table 7: Primers used for qRT-PCR

mRNAs/lncRNAs

Forward primers (5′–3′)

Reverse primers (5′–3′)

bp

ENST00000470135

TTGCCAGCAATTCATCAGAG

GGGATATGCCAACCTTGAGA

151

TCONS_00010875

TCGTTCACACACCCACTCAT

CGAGTGGGCAAGTTAGTGTG

153

TCONS_00018436

CCACCTCAGGATGGAAATGT

TCCCCAACCAAAGTCTTGTC

160

hox-HOXD10-35

GCTCCTTCACCACCAACATT

AAATATCCAGGGACGGGAAC

154

CKMT1A

ACCTGACCCCAGCAGTCTAT

AACACGTTCCACCTCTCGTC

374

GPNMB

AAGATTGCCACTTGATGCCG

TCCCTCATGTAAGCAGAAGGTC

75

FBLN5

CTCACTGTTACCATTCTGGCTC

GACTGGCGATCCAGGTCAAAG

89

GDA

GCTGGAAGTAGCATAGACCTGC

TCTTCTGCAAAGTCGATGTTCTG

95

ACTB

GTGGCCGAGGACTTTGATTG

CCTGTAACAACGCATCTCATATT

73

Lentiviral transfection assay

Lentivirus containing short hairpin RNA (shRNA) of TCONS_00018436 or empty vectors used as control were purchased from GeneChem (Shanghai, China). And the lentiviral transfection assays were performed following manufacture’s instructions. Stably transfected cells were screened by Puromycin (3 mg/mL) purchased from Sigma.

Statistical analysis

Data were presented as mean ± standard deviation (SD) and statistical differences between two experimental groups were determined by using paired t-test or Student’s t-test on SPSS 17.0 software (SPSS Inc., Chicago, IL, USA). Statistical differences in the microarray results were analyzed by fold change (FC) and P-value, and the FC and P-value were calculated based on normalized data. FC was calculated by computing the ratio of mean intensity of the case group to that of the control group, while P-value was calculated using Student’s t-test. The thresholds for differentially expressed genes were set at FC ≥ 2.0 and P-value < 0.05. For the lncRNA and mRNA correlation analysis, the Pearson correlation coefficient was calculated to show the correlation between lncRNA and mRNA expression and P-value was calculated to show the significance of the Pearson correlation coefficient. Correlation > 0.99 or correlation < −0.99, and P-value < 0.05 were adopted to filter out random relationship. In all analyses, a two-sided P-value < 0.05 was considered statistically significant.

Abbreviations

HSCC, hypopharyngeal squamous cell carcinoma; CRT, concomitant chemoradiotherapy; IMRT, intensity-modulated radiotherapy; IGRT, image-guided radiotherapy; TOMO, helical tomotherapy; lncRNA, long noncoding RNA; qRT-PCR, quantitative real-time polymerase chain reaction; GO, gene ontology.

ACKNOWLEDGMENTS AND FUNDING

This work was supported by the Taishan Scholars Program (No. tshw20130950), Shandong Province, and the Department of Science & Technology of Shandong Province (No. ZR2013HM107, ZR2014HM005, 2015GSF118014 and 2015GSF118030), the Science Foundation of Qilu Hospital of Shandong University, the Fundamental Research Funds of Shandong University (No.2014QLKY05), and the Zhenjiang Social Development Science & Technology Funds (SH2014045).

CONFLICTS OF INTEREST

None.

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