LINE-1 Retrotransposition Promotes the Development and Progression of Lung Squamous Cell Carcinoma by Disrupting the Tumor Suppressor Gene FGGY

Author Manuscript Published OnlineFirst on July 9, 2019; DOI: 10.1158/0008-5472.CAN-19-0076 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Rui Zhang1,2,#, Fan Zhang3,#, Zeguo Sun3,#, Pengpeng Liu1,2, Xiao Zhang1,2, Yingnan Ye 1,2, Beiqi Cai4, Martin J. Walsh5, Xiubao Ren2,6, Xishan Hao1,2,6, Weijia Zhang3,*, Jinpu Yu1,2*

1 Cancer Molecular Diagnostics Core, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center of Caner, Key Laboratory of Cancer Prevention and Therapy, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin 300060, China

2 Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China

3 Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, USA

4 Department of Imaging, Nanjing Bayi Hospital, Nanjing 210002, China

5 Departments of Pharmacological Sciences, Genetics and Genomic Sciences and the Mount Sinai Center for RNA Biology and Medicine, Icahn School of Medicine at Mount Sinai, New York, USA

6 Department of Immunology, Biotherapy Center, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center of Caner, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin 300060, China

# These authors contribute equally to the work.

* Correspondence to:

Jinpu Yu, Ph.D.

E-mail: [email protected]

Tel: +86-22-23340123

Fax: 022-23340123-6325

Downloaded from cancerres.aacrjournals.org on October 1, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on July 9, 2019; DOI: 10.1158/0008-5472.CAN-19-0076 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Weijia Zhang, Ph.D.

E-mail: [email protected]

Tel: 2122412883

Running title: L1 promotes LUSC development by disruption of FGGY

Keywords: Retrotransposition; LINE-1; LUSC; FGGY; reverse transcription inhibitors

Statement of conflict of interest: The authors declare no potential conflicts of interest.

Financial Support: This work was supported by National Natural Science Foundation of China (Grant No. 81702280, 81472473, 81872143), National Science and Technology support Program of China (Grant No. 2015BAI12B15, 2018ZX09201015), National Key Research and Development program of China: The Net construction of human genetic resource Bio-bank in North China (2016YFC1201703), Projects of Science and Technology of Tianjin (Grant No. 13ZCZCSY20300, 18JCQNJC82700) and Key project of Tianjin Health and Family Planning Commission (Grant No. 16KG126), Tianjin Medical University Cancer Institute and Hospital Research Program (No. B1618).

Abstract

Somatic Long Interspersed element-1 (LINE-1) retrotransposition (RT) is a genomic process that relates to gene disruption and tumor occurrence. However, the expression and function of LINE-1 RT in lung squamous cell carcinoma (LUSC) remains unclear. We analyzed the transcriptomes of LUSC samples in The Cancer Genome Atlas (TCGA) and observed LINE-1 RT in 90% of tumor samples. Thirteen LINE-1 RTs of high occurrence were identified and further validated from an independent Chinese LUSC cohort. Among them, LINE-1-FGGY (L1-FGGY) was identified as the most frequent LINE-1 RT in the Chinese cohort and significantly correlated with poor clinical outcome. L1-FGGY occurred with smoke-induced hypomethylation of the LINE-1 promoter and contributed to the development of local immune evasion and dysfunctional metabolism. Over-expression of L1-FGGY or knock-down of FGGY promoted cell proliferation and invasion in vitro, facilitated tumorigenesis in vivo, and dysregulated cell energy metabolism and cytokine/chemotaxin transcription. Importantly, specific reverse transcription inhibitors, nevirapine (NVR) and efavirenz (EFV), dramatically countered L1-FGGY abundance, inhibited tumor growth, recovered metabolism dysfunction, and improved the local immune evasion. In conclusion, hypomethylation-induced L1-FGGY expression is a frequent genomic event that promotes the development and progression of LUSC and represents a promising predictive biomarker and therapeutic target in LUSC.

Precis: LINE-1-FGGY is a prognosis predictive biomarker and potential therapeutic target to overcome local immune evasion in lung squamous cell carcinoma.

Introduction

Lung cancer is one of the most common human malignancies with high incidence and mortality worldwide (1,2). The 5-year survival rate of lung cancer is only about 18.1%, which is directly related to the late diagnosis of advanced cancer (2). Non-small cell lung cancer (NSCLC) accounts for the majority (>85%) of all lung cancers, including lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and large cell lung cancer (3,4). Among them, LUSC is strongly associated with smoking (3), and about 30% of NSCLC patients in China are LUSC histology, similar to US (5). However, the actual patient number is higher due to the proportionality of the larger Chinese population. Therefore, there is an urgent need to identify optimal treatments for LUSC within the Chinese population and aboard. To date, LUSC patients have little benefit from targeted therapies unlike LUAD patients, which may be due to the higher mutation rate but lack of actionable driver gene mutations in LUSC patients (6). Therefore, as the standard treatments, platinum-based chemotherapy and tyrosine kinase inhibitor-based (TKI-based) targeted therapy only achieve limited efficacy on LUSC (7). However, recently reported trials indicated that immunotherapy might be a promising regimen for LUSC.

The checkpoint inhibitors-based immunotherapy has been proved to improve overall survival (OS) and progression-free survival (PFS) of LUSC patients (8,9), which completely transformed the therapeutic landscape of LUSC with impressive therapeutic outcomes, but lack of predictive biomarkers limited the efficacy of immunotherapy agents. It’s reported that tumor mutation burden (TMB), a parameter to assess tumor genomic instability (TGI), is a feasible predictive biomarker, since patients with higher TMB benefited more from immunotherapy in NSCLC (10,11). However, TMB is not sufficient to accurately predict the clinical efficacy of immunotherapy (12), which indicated that more genomic biomarkers than genetic mutations will be valuable in predicting patients’ survival more precisely in LUSC.

Retrotransposition (RT) is one mechanism of chromosomal rearrangements with

the specific insertion of transposons into genome via reverse transcription of the transposon (13). Somatic RT has been identified as a frequent genomic event which play fundamental roles in early development and genome evolution (14,15), as well as carcinogenesis (16). Among the RT elements, long interspersed element-1 (LINE-1) is the only currently known active autonomous transposon in humans, which occupies ~17% of the entire human genome (17). LINE-1 propagates itself through an RNA intermediate, which has the potential to disrupt the coding sequence of endogenous genes and alter gene expression via insertion into a genomic region (18). Additionally, increased LINE-1 copy numbers provide more chances for recombination events to occur between retrotransposons, which can lead to chromosomal breaks and rearrangements (19). LINE-1-triggered genomic instabilities provide fuel to drive tumor occurrence since 47% of human neoplasms was reported immunoreactive to LINE-1, including invasive breast carcinomas, high-grade ovarian carcinomas, and pancreatic ductal adenocarcinomas (20).

The mechanism how somatic LINE-1 RT alters the expression of neighboring genes remains controversial (18,19) because somatic LINE-1 insertions lead to cancer by either activating proto-oncogenes or inhibiting tumor-suppressor genes. In breast cancer, the LINE-1 insertion was found to cause the rearrangement and amplification of MYC gene resulting in the initiation breast ductal adenocarcinoma (21). But in colon cancer, the LINE-1 insertion disturbed the last coding exon of APC gene and inhibited its function to initiate colon cancer (22). Although it was reported that in lung cancer patients, LINE-1 RTs in circulating DNA were hypomethylated (23), and even LINE-1 hypomethylation was associated to specific clinico-pathological features, including histology, p53 immunoreactivity and smoking habit (24), however, none study focusing on the function and mechanism of somatic LINE-1 RT in lung cancer, especially in LUSC has ever been reported.

In this study, we analyzed the transcriptomes of LUSC samples in The Cancer Genome Atlas (TCGA), to characterize the most common somatic LINE-1 RTs in LUSC and further validated in an independent Chinese LUSC cohort. We found 5

LINE-1-FGGY (L1-FGGY) was the most frequent LINE-1 RT significantly correlating with poor clinical outcome which occurred with smoke-induced hypomethylation and contributed to the development of local immune evasion. Further study indicated that the oncogenic roles of L1-FGGY by disrupting the expression and function of tumor suppressor gene FGGY via promoting cell proliferation and invasion in vitro, facilitating tumorigenesis in vivo, and inducing the dysregulation of cell energy metabolism and cytokine/chemotaxin transcription, which could be fully recovered by specific reverse transcription inhibitors. Therefore, L1-FGGY is not only a prognosis predictive biomarker, but also a potential therapeutic target to overcome local immune evasion in order to achieve more clinical benefits from immunotherapy in LUSC.

Materials and Methods

Cell lines

NCI-H520, SK-MES-1, and BEAS-2B were purchased from Cellcook Co., Ltd. with cell authentication via STR multi-amplification method. A549, H1299, NCI-H460, NCI-H446, and HEK293T were obtained from Chinese Academy of Medical Sciences tumor cell libraries. Mycoplasma for the cells cultured in our laboratory was tested using Mycoplasma Detection Kit according to the manufacturer’s protocol in every three months.

Mice

Female NOD-SCID mice, which were 7-week old and weighed about 17~18 g, were obtained from the Beijing Vital River Laboratory Animal Technology Co., Ltd. All mice were housed in a SPF animal facility.

Patient information

This study selected 109 cases of LUSC patients from a well-informed cohort of patients which were treated with partial lung resection surgery at the Department of Lung Cancer of Tianjin Medical University Cancer Institute and Hospital from October 2004 to October 2006 (Table 1) (25). Among these 109 cases, 52 cases of LUSC samples were coupled with matched para-carcinoma tissues. All para-carcinoma lung tissues sectioned at least 5 cm from the tumor’s boundary to avoid any potential of tumor cell infiltration. All smoking information was collected and recorded when the patient was hospitalized for the first time. And we defined the patients who never smoked after he reached adulthood as “negative smokers”, while the patients who ever smoked after adulthood as “positive smokers”. No prior treatments, including chemotherapy or radiotherapy, were conducted before lung resection surgery was performed. Postoperative follow-up time was 67–96 months. Written informed consents were obtained from the patients and this project was approved by the Ethics Committee of Tianjin Medical University. All experiments

were performed in accordance with the principles of the Declaration of Helsinki.

Lentivirus construction

For L1-FGGY insertion lentivirus construction, the L1-FGGY fragment was amplified by PCR using the complementary DNA (cDNA) of NCI-H520 cells as template. Then the amplified L1-FGGY fragment was inserted into pHBLV-CMV-MCS-EF1-ZsGreen-T2A-Puro lentiviral vectors (Hanbio Co., Ltd.) and the constructed positive plasmid was confirmed by DNA sequencing. The recombinant lentivirus with L1-FGGY sequence was generated by co-transfection in NCI-H520 cells as previously described (26) and the empty lentivector lenti-puromycin was used as negative control. For FGGY knock-down lentivirus construction, specific shRNA sequence based on the sequence of FGGY (Gene ID: 55277, on NCBI) was designed. The synthesized FGGY shRNA and control shRNA were inserted into plvx-U6-CMV-RFP-P2A-BSD lentiviral vectors respectively. The lentivirus was generated as described above.

Cell culture and cell treatment

NCI-H520, A549, H1299, NCI-H460, and NCI-H446 were cultured in RPMI1640 (Gibco BRL). SK-MES-1 was cultured in Eagle's Minimum Essential Medium. HEK293T and BEAS-2B cells were cultured in DMEM. All medium contained 10% FBS and 1% penicillin/ streptomycin. All of the above cells were cultured at 37°,

under 5% CO2. The general length of time between collection/thawing and use in our laboratory was no more than 6 months. For reverse transcriptase inhibitors treatment experiments, NVR and EFV (TargetMol) were dissolved in dimethyl sulfoxide (DMSO, Sigma Aldrich) to make stock regent respectively. 5h after cells seeded, NVR was diluted to 350 μM and EFV was diluted to 15 μM, followed by replacing the cell medium. The same DMSO volume (0.2% final concentration) was added to control cells. Fresh NVR or EFV-containing medium was changed every 48h.

Detection of cell proliferation, Cell apoptosis analysis, Wound healing assay, and

Trans-well invasion assay

All these detection of cellular functions was performed according to the manufacturer’s protocol as previously described (27). And the experiments were repeated at least 3 times.

In vivo tumorigenicity study

After the mice construction, the tumor sizes of each NOD-SCID mouse were monitored every 2 days. Each group contains 5 mice. And the experiments were repeated at least 3 times. The tumor volume (V) was calculated by the formula: V=3.14×L×W×H/6 (L: length, W: width, H: height). For drug treatment experiments, animals were then subjected to treatment with either NVR (50 mg/kg/day) or EFV (20 mg/kg/day) every day. Simultaneously, the mice with no treatment and the mice with DMSO treatment were cultivated as controls. The animal protocol used in this study was approved by the Ethics Committee for Animal Experiments of the Tianjin Medical University Cancer Hospital and Institute, and was approved by the Wistar Institutional Animal Care and Use Committee (IACUC). The Wistar IACUC guideline was followed in determining the time for ending the survival experiments (tumor burden exceeds 10% of body weight).

RNA extraction, RT-PCR and qPCR analysis for gene expression

RNA extraction, cDNA synthesis, RT-PCR and regular qPCR analysis were performed following the manufacturer’s protocol as previously described (27). The sequences of primers are shown in Table S1. To confirm the bands detected in the PCR assay were the genes as predicted, we purified and sequenced the PCR products (Invitrogen). High-throughput qPCR analysis were performed on Smartchip (Differential gene technology Co., Ltd.) following the manufacturer’s protocols. All experiments were performed in triplicates and were calculated for △CT. Relative

-△CT expression quantity of mRNA was calculated as 2 (△CT= CTtarget gene - CTreference

gene.).

qMSP analysis for the methylation levels of LINE-1 RTs

Genomic DNA was obtained and purified from frozen LUSC tissues in quantities sufficient for bisulfite treatment. Bisulfite conversion was carried out on 500 ng genomic DNA using EpiTect Bisulfite Kit (Qiagen), according to the manufacturer’s protocol as described above (28). The experiments were repeated at least 3 times.

Immunohistochemistry

All procedures were performed as described above (29). The antibodies we used here are as follows: anti-CD3 (Abcam), anti-CD68 (Santa Cruz), anti-CD33 (Abcam), anti-FGGY (Bioss), anti-ki67 (Cell Signaling Technology), anti-N-cadherin (Zsbio), anti-β-catenin (Zsbio), anti-PD-L1 (BioSS), anti-CD11b (Abcam), and a biotinylated secondary goat anti-mouse IgG antibody (Santa Cruz), labeled with streptavidin-horseradish peroxidase (HRP) using a DAB staining kit (Maixin Biotechnology) according to the manufacturer’s instructions. For negative controls, IgG1 was used to substitute for each primary antibody. Positively stained cells were counted in 5 fields at 200× magnification, and the sum of the cells was calculated as positive cell counts.

Detection of somatic LINE-1 RTs in TCGA LUSC datasets

We downloaded paired-end RNA-Seq data of LUSC samples (tumor and paired adjacent normal tissue) from TCGA upon approval of TCGA commission. The somatic insertion of LINE-1 RTs into a gene was detected by using deFuse (30) (http://shahlab.ca/projects/defuse/). Briefly, the detection of read pairs that discordantly map to two distinct genes generates a first set of gene insertion candidates. Subsequently, the exact insertion junction is determined for each candidate by searching for reads spanning the breakpoint, i.e. reads that partially map to both genes. The results produced by deFuse were further filtered to reduce the number of false positives: predictions had to be supported by at least eight reads spanning an insertion breakpoint and five reads split by an insertion breakpoint.

Pegasus tool (31) (http://sourceforge.net/p/pegasus-fus) was then used for the functional characterization of RNA-Seq gene insertion candidates with one end mapped to LINE-1 RT consensus sequences from Repbase data base (32) by BLAST and quantification of their oncogenic potential. After annotation by Pegasus tool, we reserved those LINE-1 RTs which occurred only in the cancer samples, but not in any normal samples.

RNA library preparation and sequencing

Library preparation and sequencing steps were commissioned to Novogene Co., Ltd. The Novogene pipeline included the production of strand-specific mRNA libraries and quality control. The libraries were sequenced on Illumina® (NEB) following manufacturer’s recommendations. The RNA sequencing data has been uploaded to GEO database (accession number: GSE124625).

Differential expression analysis and KEGG enrichment analysis

Prior to differential gene expression analysis, the read counts were adjusted by edgeR program package through one scaling normalized factor. Differential expression analysis of two conditions was performed using the edgeR R package (3.18.1). The P values were adjusted using the Benjamini & Hochberg method. Corrected P-value of 0.05 and absolute fold change of 2 were set as the threshold for significantly differential expression. Here we used clusterProfiler R package to test the statistical enrichment of differential expression genes in KEGG pathways.

GSEA to detect immune markers

We collected 12 immune cell data sets, including 6 single cell data sets from 10x Genomics (33), 1 single cell data set from Todd et. al. (34) and 5 sorted pure cell data sets (35). For each cell type, we compared its expression values against each other cell and selected genes with log fold change > 0 and p value < 0.01 as markers for each data sets. For markers appeared more than two times in those data sets, we selected markers with meta p value less than 0.01 and mean log fold changes larger than 2 as

meta markers. We get 967 meta markers for 8 cell types. We then performed GSEA analysis based on these meta markers for each immune cell type.

Statistical analysis

Data were analyzed using SPSS 17.0 and GraphPad Prism 5.0 software. Measurement data were presented as median (interquartile range) and compared through χ2 test. Quantitative data were presented as mean ± standard deviation and compared through ANOVA and LSD tests. Spearman’s rank order test and linear regression analysis were performed to assess the correlations between expression levels detected by qPCR. Univariate Cox regression and multivariate Cox regression analyses were used to identify common genes associated with OS. Cumulative survival was determined via Kaplan–Meier method. Univariate survival analysis between the different LINE-1 RTs and the OS of LUSC patients was conducted through the two-sided log-rank test. Statistical significance was set at p<0.05.

Results

High occurrence of somatic LINE-1 RTs in LUSC tissues

In order to identify somatic LINE-1 RTs in LUSC, we obtained data from 50 individual cases of paired-end RNA-sequencing data of paired LUSC samples from TCGA. Discovery of the LINE-1 RTs is described by the procedure depicted in the schematic diagram (Figure 1A). Briefly, the deFUSE program (30) was first used to identify fusion events from RNA transcripts compared to the reference genome followed by annotation with the Pegasus tool (31). The somatic LINE-1 RTs that occurred only in tumor were discovered by aligning the sequences of the fusion partners against the LINE-1 consensus sequences from the Repbase database (32). Figure 1B illustrates the L1-FGGY with 47 reads capturing transcripts containing LINE-1 insertions within the FGGY locus. The 5' untranslated region (5’UTR) of L1-HS (human-specific L1; a LINE-1 subfamily) was inserted into the beginning of exon 13 of gene FGGY (NM_001113411). We observed that 90% (45/50) of LUSC samples possessed somatic LINE-1 RTs with various rates of insertion ranging from 1 to 24 insertions per individual (Figure 1C). We had identified a total of 39 LINE-1 RTs in 50 paired LUSC samples, which occurred only in the cancer samples, but not in any normal samples, and the three most frequent LINE-1 RTs include L1-SMYD3 (56%), L1-CBWD2 (42%), and L1-FGGY (38%) (Figure 1D). We then analyzed these 13 LINE-1 RTs in additional 398 unpaired LUSC samples, and detected the top 3 LINE-1 RTs also displayed comparably high frequency (Figure 1E). The RT events occurred most frequently on chromosome 1, 2, 3, and 12 (Figure 1F) and the majority of RT events were found within the coding regions (Figure 1G).

Next, we performed quantitative-polymerase chain reaction (qPCR) to validate the transcripts of the top 13 LINE-1 RTs in an independent Chinese cohort of 52 pairs of LUSC tumors and matched normal adjacent tissues collected from the Tianjin Medical University Cancer Institute and Hospital. The results showed that out of the 13 LINE-1 RTs, the expression of 12 insertions was significantly higher in LUSC

tissues than the matched adjacent normal tissues (Figure 1H, Table 1), which confirmed the findings of the RT events detected in the TCGA LUSC samples.

Somatic LINE-1 RTs correlated with specific clinico-pathological features in LUSC patients

We further checked these 13 LINE-1 RTs in several lung cancer cell lines (LUAD, A549 and H1299; LUSC, NCI-H520; large cell, NCI-H460; and small, NCI-H446) and two normal cell lines (human epithelial HEK293T and human lung epithelial cell BEAS-2B). Both qPCR and reverse transcription-polymerase chain reaction (RT-PCR) results revealed that 11 of 13 LINE-1 RTs were also detected in the cancer cell lines tested but not in the normal cell lines (Figure S1A-B). PCR products of these LINE-1 RTs were sequenced and 8 products matched the expected LINE-1 RTs (Figure S1C).

We then explored association of somatic LINE-1 RTs, performed with the patients’ OS in 109 cases of LUSC samples. The patients were stratified into two groups by the expression level of LINE-1 RTs by qPCR and survival analysis with Kaplan-Meier method to reveal that high expression of the three highly recurrent LINE-1 RTs correlated with poor survival outcomes (Figure 2A), whereas, other LINE-1 insertions did not (Figure S2). Then we explored the association of the 3 somatic LINE-1 RTs with the stages I-II patients’ OS which gives a more homogenous population. The results consistently showed high expression of them was correlated with poor survival outcomes (Figure 2B).

We further analyzed the association between each LINE-1 RT and other clinicopathology (Table S2). We found that high expression of the 3 LINE-1 RTs was correlated with larger tumor size, 5 LINE-1 RTs with central-type primary tumors, and 5 LINE-1 RTs with smoking history (Figure 2C, Table S2). We further detected that smoking status rather than smoking dose significantly affected the expression levels of 5 LINE-1 RTs (Figure S3A). Collectively, these findings reveal that LINE-1 RTs

strongly corresponds with large central-type tumors and smoking history, but not smoking dose.

Furthermore, we correlated the expression of the three most common LINE-1 RTs with immunocyte content in tumor tissues in situ. The immunohistochemical staining (IHC) analysis showed that less CD3+ T cells were detected in L1-FGGY+ and L1-SVEP1+ (Figure 2D) tissues and more CD68+ macrophages and CD33+ myeloid-derived cells (Figure 2E-F) were detected only in L1-FGGY+ tissues. We further found that smoking status rather than smoking dose significantly affected the distribution of immunocytes (Figure S3B). This finding provide evidence that local immune evasion was associated with certain LINE-1 RTs.

Among these 3 LINE-1 RTs, L1-FGGY corresponded the most strongly with smoking history, large tumor size, central tumor location, local immune evasion, as well as poorer prognosis, suggesting L1-FGGY in directing LUSC. Because of these inherent features of L1-FGGY, it was selected for further testing for the underlying function in epigenetic regulation and oncogenic role.

L1-FGGY corresponded with smoke-induced LINE-1 promoter hypomethylation, lipid metabolism dysregulation and immune microenvironment alteration

In order to explore which pathways were affected by L1-FGGY, we performed RNA sequencing on 20 LUSC tumor samples (10 L1-FGGY+ vs. 10 L1-FGGY-). We identified 1529 (826 up and 703 down) dysregulated genes in L1-FGGY+ tissues at an adjusted p value of 0.05. The enrichment analysis indicated that many signaling pathways were upregulated in L1-FGGY+ tissues (Figure 3A), most of which were metabolic pathways, especially lipid-related metabolism. We also performed gene set enrichment analysis (GSEA) to assess the dysregulation of immune cells in tumor tissues by L1-FGGY using immune cell specific markers. The results showed CD4+ T cells were significantly downregulated in L1-FGGY+ tissues (Figure 3B), suggesting

immune evasion by L1-FGGY in tumors. Then we further checked association of the transcription of cytokines with L1-FGGY. We observed that IFNL4, TNFRSF11A, TNFSF12, IL17RD, IL34, and IL27RA were downregulated in L1-FGGY+ tissues (Figure 3C), which were mostly reported to promote the functions of T cells and activate tumor cell immune response. While IL1A and IL6R were upregulated in L1-FGGY+ tissues (Figure 3C), which could promote the enrichment of myeloid-derived suppressor cells (MDSCs) and induce immune evasion.

To confirm the alteration of lipid-related metabolic pathways based on the RNA sequencing data, we examined the top upregulated genes involved in these metabolic pathways, in 60 LUSC tissues (30 L1-FGGY+ vs. 30 L1-FGGY-). The results showed the genes involved in cytochrome P450, arachidonic acid (AA) metabolism, and glycerolipid metabolism were upregulated in L1-FGGY+ tissues (Figure 3D). We then further performed IHC staining and less CD3+ T cells were detected, and the expression of PD-L1 was increased in L1-FGGY+ tissues (Figure 3E). Then we also validated the abnormal transcription of cytokines related with the immunosuppressive micromilieu. We found that T cell activation-related cytokines, including interferon-γ (IFN-γ), IL-17, and IL-27, were downregulated, while immune suppression-related cytokines, including IL-1α, IL-6, and IL-34, were upregulated in L1-FGGY+ tissues (Figure 3F).

Then we tested the correlation between the expression of L1-FGGY and the methylation ratio of LINE-1 promoter of the 60 tumor samples mentioned above by quantitative methylation-specific PCR (qMSP). Spearman’s rank correlation showed a significant negative correlation between LINE-1 methylation levels and the abundance of L1-FGGY expression (Figure 3G). Then we assessed the association between LINE-1 methylation and clinicopathology parameters. We found the reduced LINE-1 methylation was significantly associated with clinical stage of disease, lymph node activation/metastasis, and smoking history (Figure 3H). And further analysis showed high L1-FGGY expression was significantly associated with clinical stage of disease and smoking history (Figure 3I), implicating smoke-induced hypomethylation of 16

LINE-1 promoter led to L1-FGGY upregulation and more activity in tumors.

Collectively, these results indicated that L1-FGGY corresponds with smoke-induced LINE-1 promoter hypomethylation, as well as with lipid metabolism upregulation and immune evasion.

L1-FGGY inhibited the transcription of FGGY gene

Insertion of LINE-1 RT into a gene via a target-primed reverse transcription (TPRT) mechanism (36) may interrupt the gene structure and alter its expression (37). To test whether the L1-FGGY influenced FGGY expression, we examined the expression correlation between L1-FGGY and FGGY in 52 pairs of LUSC tissues and matched normal tissues. The results showed higher expression of FGGY over L1-FGGY in normal tissues, however, higher expression of L1-FGGY over FGGY (Figure 4A) in LUSC tissues. Furthermore, Spearman’s rank correlation showed a significant negative correlation between L1-FGGY and FGGY expression in the 109 LUSC tumor samples (Figure 4B). In normal lung tissues, we detected FGGY expression, but could not detect L1-FGGY expression (Figure 4C). Furthermore, we found relatively high expression of FGGY among normal cell lines HEK293T and BEAS-2B, and lung cancer cell lines with undetectable L1-FGGY in A549, H1299, and NCI-H446. Conversely, relatively low expression of FGGY was detected in lung cancer cell lines with abundance for L1-FGGY in NCI-H520 and NCI-H460, which indicated the reversed correlation of L1-FGGY and FGGY in multiple cell lines (Figure 4D).

We further validated the lower transcription levels of FGGY in LUSC tissues compared to matched normal tissues (Figure 4E) in TCGA dataset. Lastly, we observed that, in contrast to L1-FGGY, low expression of FGGY was associated with poor OS (Figure 4F) and the large tumor size (Figure 4G, Table S3) in our cohort.

Collectively, these data suggest the expression of FGGY is suppressed by LINE-1

RT which could lead to the tumor progression and poor outcomes.

Over-expression of L1-FGGY or knock-down of FGGY exhibited an oncogenic role in vitro and vivo

In order to investigate the underlying biological role of L1-FGGY and FGGY in carcinogenesis and cell proliferation in LUSC NCI-H520 cell line, we over-expressed L1-FGGY (H520OV-L1-FGGY) by a recombinant lentivirus carrying synthetic L1-FGGY core sequences and suppressed FGGY expression with shRNA (H520sh-FGGY). First, we confirmed over-expression of L1-FGGY in H520OV-L1-FGGY cells compared with the control cell line infected with empty vector (H520OV-CTRL) (Figure 5A), which suppressed the transcription of FGGY (Figure 5B left panel) by insertion into endogenous FGGY locus through homologous recombination (Figure S4), similar to the results in H520sh-FGGY compared to H520sh-CTRL (Figure 5B right panel).

We next validated upregulation of lipid metabolism-related genes in H520OV-L1-FGGY and H520sh-FGGY cells by qPCR assay. We first validated the upregulation of the genes in AA metabolism and cytochrome P450 metabolism (Figure 5C). Then, we detected the genes related to glucose and lipid metabolism which mediates ATP generating in cells. The genes involved in fatty acid oxidation were upregulated and genes involved in glucose aerobic oxidation and glycolysis were altered slightly (Figure 5C).

Then we further explored the role of FGGY in carcinogenesis. We found a greater proliferation rate in H520OV-L1-FGGY and H520sh-FGGY (Figure 5D) than the control cell lines via the Cell Counting Kit 8 (CCK8) proliferation assay. Consistently, a reduced apoptotic rate was found in H520OV-L1-FGGY and H520sh-FGGY (Figure 5E) using the Annexin-V apoptosis assay. These results implied that LINE-1 inserted into FGGY significantly stimulated cell proliferation and reduced cell apoptosis through suppressing FGGY.

The migration and invasion capacities of H520OV-L1-FGGY and H520sh-FGGY were evaluated via the wound healing assays and by the trans-well invasion assay preformed. We found that the wound closure rate (WCR) of H520OV-L1-FGGY and H520sh-FGGY (Figure 5F) were significantly higher than corresponding control cell lines. Consistently, more of those cells expressing H520OV-L1-FGGY and H520sh-FGGY (Figure 5G) migrate across the matrigel layer after 48h. Furthermore, the enriched transcription of Epithelial-mesenchymal transition-related (EMT-related) biomarker was detected using qPCR assay. The conventionally used epithelium cell biomarker of E-cadherin was reduced, but other well-described mesenchymal cell biomarkers of N-cadherin and β-catenin and EMT-related transcription factors (snail, slug, zeb1, and Twist) were increased in those cells expressing H520OV-L1-FGGY and H520sh-FGGY (Figure 5H). The qPCR results also showed that immune suppression-related cytokines, including IL-1α, IL-6, IL-33, and IL-34, were upregulated, while T cell activation-related cytokines, including IFN-γ, IFN-λ, IL-17, and IL-27, were downregulated in H520OV-L1-FGGY and H520sh-FGGY cells (Figure 5I). These results imply that LINE-1 inserted into FGGY promotes cell invasion and migration by stimulating the EMT phenotype, accompanied by influencing the transcription of cytokines in tumor cells.

Next, we tested if L1-FGGY would affect carcinogenesis in vivo. Cell transduced with the H520OV-L1-FGGY and H520sh-FGGY lentiviral constructs and their control cells were injected into NOD-SCID mice subcutaneously as xenografts. After 24 days, the average volumes of tumors generated by engrafted tumor cells from the H520OV-L1-FGGY and H520sh-FGGY groups (Figure 5J) were at least two fold greater volumes when compared to the control groups. Consistently, the growth rates of tumors in H520OV-L1-FGGY mice were much greater than those in H520OV-CTRL mice (Figure 5J). To further validate our observations in NCI-H520, we repeated the experiments in another LUSC cell line, SK-MES-1 to further validate our observations in NCI-H520. We found consistent results in SK-MES-1, in which forced over-expression of L1-FGGY or knock-down of FGGY promoted cell

proliferation and migration, reduced cell apoptosis, as well as implicated with dysregulation of lipid metabolism and cytokine transcription (Figure S5).

Taken together, these findings implied that L1-FGGY could significantly suppress FGGY expression, stimulate cell proliferation, inhibit cell apoptosis, promote cell invasion and EMT, and thereby predicted to facilitate carcinogenesis. Besides, L1-FGGY also seemed to be implicated in cell energy metabolism and cytokine transcription.

Reverse transcriptase inhibitors inhibited the proliferation of LUSC cells and impaired the growth of LUSC xenografts in vitro and vivo via recovering FGGY

Reverse transcriptase inhibitors such as nevirapine (NVR) and efavirenz (EFV) block the enzymatic activity of endogenous reverse transcriptase and regarded as potential specific inhibitors for LINE-1 RTs (38). We tested the antitumor effort of NVR and EFV in LUSC. In the CCK8 experiment we show that both inhibitors could effectively reduce the proliferation of NCI-H520 cells (Figure 6A upper panel). In order to discover the toxicity of NVR and EFV in the normal lung cell line, we then performed CCK8 experiment in BEAS-2B cell. The results showed that NVR did not influence the proliferation rate though EFV showed some inhibition on the proliferation of BEAS-2B (Figure 6A lower panel), which indicated NVR is safer and has less toxicity than EFV. And both NVR and EFV further increase cell apoptosis (Figure 6B). Furthermore, both NVR and EFV decrease the invasive potential of NCI-H520 cells (Figure 6C). Upon NVR and EFV treatment, the RNA level of both β-catenin and slug is reduced and accompanied by increases in the RNA level of E-cadherin (Figure 6D). Collectively, our data indicate that the reverse transcriptase inhibitors attenuate cell proliferation and invasion by inhibiting L1-FGGY leading to upregulation of FGGY expression.

NCI-H520 cells were engrafted subcutaneously in the NOD-SCID mice which

were subjected to either NVR (50 mg/kg/day) or EFV (20 mg/kg/day) treatment. After 22 days, the average volume of tumors in inhibitors-treated mice were characterized as being much smaller than those in either untreated or DMSO treated mouse groups (Figure 6E left panel). The tumor growth curves indicate that both inhibitors markedly reduce the growth of the xenografts shown (Figure 6E right panel). We determine that NVR inhibits tumor growth more effectively than EFV. Moreover, both inhibitors display comparable drug safety since neither significant body weight lose or mortality occurred during the treatment.

Furthermore, transcription of multiple EMT gene markers in xenografts was examined. As expected, the qPCR analysis demonstrated that the epithelial cell marker E-cadherin was elevated after the treatment, while the mesenchymal cell markers N-cadherin, β-catenin, snail, slug, zeb1, and Twist1 were reduced (Figure 6F). Similarly, the mRNA level of L1-FGGY was reduced (Figure 6G), while the mRNA level of FGGY increased dramatically after both inhibitors treatment (Figure 6H), consistent with increased protein expression by IHC analysis. Transcription of the lipid-related genes and fatty acid oxidation-related genes in xenografts was reduced after the treatment (Figure 6I), which was opposite to increased transcription in H520OV-L1-FGGY and H520sh-FGGY cells. Similarly, the mRNA level of IFN-γ, IFN-λ, IL-17, and IL-27, was increased after the treatment, while the RNA level of IL-1α, IL-6, IL-33, and IL-34 was reduced (Figure 6J).

Further staining by IHC reveal that less Ki67+, N-cadherin+, and β-catenin+ cells (Figure 6K) were detected with both inhibitors from the two groups of treated mice. Meanwhile, we noticed that NVR and EFV could also decrease the expression of PD-L1 on tumor cells. And even CD11b+ MDSCs were reduced in the mice treated with the two inhibitors (Figure 6K). Collectively, these data clearly suggest that the reverse transcriptase inhibitors reduce tumor growth and appears to reflect the local immune evasion in vivo by suppressing L1-FGGY leading to increased FGGY expression.

Discussion

Somatic LINE-1 RT has been detected in multiple types of tumors (39-41). However, the expression and function of LINE-1 RT in LUSC was unclear. Considering most of LINE-1 studies were exclusively based on DNA-seq (39,42), in this study we carried out a new approach to analyze somatic LINE-1 RT at transcriptomic level, which enabled us to explore their functions and mechanisms in a quantitative manner.

Based on the RNA sequencing data from TCGA and Chinese cohort, we identified L1-FGGY as being the most frequent LINE-1 RT in Chinese LUSC patients which significantly correlated with poor clinical outcome. We observed the significant correlation between smoking history and high occurrence of L1-FGGY in LUSC. Tobacco exposure is the leading cause of cancers (43). Multiple studies suggest the relationship between tobacco exposure and the occurrence and even worse outcome of lung cancer (44,45). Furthermore, we confirmed a correlation between smoking history and LINE-1 hypomethylation. Therefore, we proposed a hypothesis that tobacco smoking induces hypomethylation of CpG islands at LINE-1 promoter region in lung epithelium cells and, in turn, activates LINE-1 insertion into tumor suppressor genes, such as FGGY, to facilitate carcinogenesis.

Recently, a study by Jung H, etal. had discovered multiple immune pathways were significantly negatively correlated with LINE-1 insertion counts, including immunoregulatory interactions between a lymphoid and a non-lymphoid cell, toll-like receptors (TLRs) cascade, STAT6 mediated induction of chemokines, and IFN signaling (46). Their study uncovered the correlation between LINE-1 RTs and suppressive immune signatures in gastrointestinal cancers, which is consistent with our findings in LUSC. FGGY is a novel tumor suppressor gene which was known to encode a protein that phosphorylates carbohydrates and associates with obesity and sporadic amyotrophic lateral sclerosis (47). But less information about FGGY in carcinogenesis has been provided yet. Here we found the LINE-1 insertion could

inhibit the transcription of FGGY gene probably via homologous recombination.

We firstly compared the energy metabolism since tumor cells might enhance energy intake through increasing glucose uptake and aerobic glycolysis (48). But no alteration of glucose glycolysis in L1-FGGY+ tumors was detected. Meanwhile, a number of lipid metabolism-related genes changed dramatically. It was reported FGGY suppression caused lipid metabolism disturbance and diet-induced obesity in mice (49). Therefore, we compared the genes involved in fatty acid oxidation which significantly increased in H520OV-L1-FGGY cells and H520sh-FGGY cells, which are consistent with previous report (50,51). Hence we hypothesize that L1-FGGY+ cells utilized fatty acid oxidation to provide energy for tumor cell growth and invasion.

Secondly, we studied local immune evasion. L1-FGGY inhibited the infiltration of T cells, promoted the recruitment of immunosuppressive cells, and enhanced the expression of PD-L1 on tumor cells. Recent studies have shown that dysfunctional AA metabolism affected the immune system significantly. It’s been reported that the cancer cell-derived AA metabolite LTB4 suppressed anti-tumorigenic cytotoxic CD8+ T-cells and recruited multiple immunosuppressive cells (52). We found enhanced AA metabolism-related signaling pathways and multiple inflammatory cytokines/chemotaxins in L1-FGGY+ tumors. Among them, type I IFN was regulated by AA in a dose-dependent manner (53) and considered as a critical molecule to induce PD-L1 upregulation in tumors (54). IL-6 and IL-1α were preferentially attracted and activated tumor-associated macrophages (TAMs) and MDSCs which subsequently suppress cytotoxic CD8+ T-cell activity (55,56).

Therefore, we summarized the findings and complemented our hypothesis in Figure S6. Tobacco smoking induced more L1-FGGY in lung epithelium cells, which disrupted the transcription and expression of FGGY, as well as FGGY-related adipose metabolism, thus generated more energy via enhancing fatty acid oxidation, to enhance the cell proliferation and invasion. On the other hand, metabolic disorder caused tumor microenvironment abnormality, leading to alterations in

cytokine/chemotaxin profiles, followed by T cell suppression, immunosuppressive cell recruitment and PD-L1 upregulation.

In order to evaluate the therapeutic value of somatic LINE-1 RT, the inhibitors targeting the reverse transcription enzyme during the RT process as FDA approved anti-retroviral drugs for HIV infection treatments (57) were applied. NVR and EFV share common chemical properties and biochemical effects by binding the hydrophobic pocket in the subunit of many reverse transcriptases (58). These inhibitors were reported to reduce cell proliferation (59). Here we found that NVR and EFV efficiently inhibited cell proliferation and invasion in vitro, as well as impaired tumor growth in vivo. Furthermore, NVR and EFV interfered the expression pattern of cytokines, decreased the expression of PD-L1, and inhibited the infiltration of immunosuppressive cells. Considering higher anti-tumor efficiency and less toxicity of NVR, we proposed NVR as a more promising candidate drug, which could even convert immunosuppressive TME into immunoactive. Therefore, combining treatment of reverse transcriptase inhibitors probably improves the therapeutic efficacy of checkpoint inhibitors in LINE-1 positive LUSC patients.

Collectively, we established a novel strategy to analyze RTs at the transcriptomic level and identified somatic LINE-1 RTs, especially L1-FGGY, associated with the development and progression of LUSC. It’s the first time that L1-FGGY was proposed as a candidate biomarker which not only enhanced the proliferation and invasion potential of tumor cells, but also affected local immune homeostasis via disrupting cell energy metabolism. Finally, we proposed a practical therapeutic strategy to overcome L1-FGGY-mediated carcinogenesis using FDA approved anti-retroviral drugs, NVR and EFV. Although more extensive experiments need to be conducted to elucidate the concrete mechanisms, L1-FGGY is feasible as a promising predictive biomarker and therapeutic target in LUSC.

Acknowledgments

We thank for the help from Cancer Biobank of Tianjin Medical University Cancer Institute and Hospital. And Dr. Fan Zhang’s current address is as follows: HIT Center for Life Sciences, School of Life Science and Technology, Harbin Institute of Technology, 150080 Harbin, China.

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Table 1. The basic clinical pathological information of all patients.

Clinical pathological parameters Number of patients

Total 109

Gender Male 89 Female 20 Age <60 years 46 ≥60 years 63 Stage Ⅰ-Ⅱ 64 Ⅲ-Ⅳ 45 T stage 1-3 98 4 11 N stage 0 66 1 14 2 29 M stage 0 97 1 12 Metastatic site Negative 97 Lung 1 Bone 4 Brain 1 Others 6 Location Central 58 Periphery 51 Smoking Negative 14 Positive 95 KPS ≤60 15 >60 94

Figure legends

Figure 1. High occurrence of somatic LINE-1 RTs in LUSC tissues. (A) Bioinfomatic workflow to identify LINE-1 RTs in LUSC. (B) L1-FGGY with 47 supporting reads in one sample. (C) Somatic LINE-1 RT counts across LUSC samples. (D) Thirteen LINE-1 RTs in paired LUSC samples. (E) Thirteen LINE-1 RTs in unpaired LUSC samples. (F) Genome location distribution of LINE-1 RTs. (G) Gene location distribution of LINE-1 RTs. (H) The qPCR results of the 13 LINE-1 RTs in an independent Chinese cohort.

Figure 2. Somatic LINE-1 RTs correlated with specific clinical pathological features in LUSC patients. (A) The OS was compared between L1-FGGY+ and L1-FGGY-, L1-ATP8B1+ and L1-ATP8B1-, L1-SVEP1+ and L1-SVEP1- patients respectively. (B) The association of 3 LINE-1 RTs with the stages I-II patients’ OS was compared. (C) Tumor T stages, tumor locations, and smoking histories were compared. (D) CD3+ T cell; (E) CD68+ macrophage; (F) CD33+ myeloid-derived cell infiltrated number were compared.

Figure 3. L1-FGGY corresponded with smoke-induced LINE-1 promoter hypomethylation, lipid metabolism dysregulation and immune microenvironment alteration. (A) The KEGG analysis between L1-FGGY+ and L1-FGGY- tissues (N=10). (B) GSEA analysis showed the distribution of immune cells. (C) The expression of cytokines was compared. (D) Upregulated genes validation implicated in lipid-related metabolism (N=30). (E) IHC staining results of CD3+ T cells and PD-L1+ tumor cells. (F) Validation of altered cytokines. (G) Spearman’s rank correlation between LINE-1 methylation level and L1-FGGY expression. (H) LINE-1 methylation was compared between different groups. (F) L1-FGGY expression was compared.

Figure 4. L1-FGGY inhibited the transcription of FGGY gene. (A) The relative expression of FGGY and L1-FGGY detected in the adjacent normal tissues and LUSC tissues. (B) Spearman’s rank correlation between L1-FGGY and FGGY. (C) The relative expression of L1-FGGY and FGGY in normal lung tissues. (D) The reversed correlation between L1-FGGY and FGGY in cell lines. (E) Normalized expression of FGGY between normal lung tissues and LUSC tissues (N=50) from TCGA data. (F) The OS was compared between FGGY+ and FGGY- patients in our cohort. (G) The different tumor T stages were compared.

Figure 5. Over-expression of L1-FGGY or knock-down of FGGY exhibited an oncogenic role in vitro and vivo. (A) L1-FGGY expression in H520OV-CTRL and H520OV-L1-FGGY cells. (B) FGGY expression in different cells. (C) The expression of lipid metabolism-related genes. The results for H520OV-L1-FGGY were relative 34

expression values compared to H520OV-CTRL, and the results for H520sh-FGGY were relative expression values compared to H520sh-CTRL. (D) Cell proliferation results. (E) Cell apoptosis results. (F) Representative images in wound healing assays. (G) Representative images in trans-well invasion assays. (H) The expression of EMT marker genes. (I) The expression of cytokines. (J) Representative image of the forming tumors and the size of them at various time points upon injection.

Figure 6. Reverse transcriptase inhibitors inhibited the proliferation of LUSC cells in vitro and vivo via recovering FGGY. (A) NCI-H520 cells were treated with reverse transcriptase inhibitors NVR or EFV, followed by CCK8 detection. (B) Cell apoptosis results. (C) Representative images in trans-well invasion assays. (D) The expression of EMT marker genes. All the results for NVR and EFV-treated NCI-H520 cells were relative expression values compared to DMSO treated cells. (E) NCI-H520 cells were inoculated subcutaneously in the NOD-SCID mice which were subjected to either NVR or EFV treatment. Representative image of the forming tumors and the size of them at various time points upon injection. (F) The expression of EMT marker genes. All the results for mice subjected into DMSO, NVR and EFV were relative expression values compared to the mice with no treatment. (G) L1-FGGY expression. (H) FGGY expression. (I) The expression of lipid metabolism-related gene. (J) The expression of cytokines. (K) IHC staining results. The data are shown as mean ± SD. * and ** indicate p<0.05 and p<0.01 between the groups as indicated.

LINE-1 Retrotransposition Promotes the Development and Progression of Lung Squamous Cell Carcinoma by Disrupting the Tumor Suppressor Gene FGGY

Rui Zhang, Fan Zhang, Zeguo Sun, et al.

Cancer Res Published OnlineFirst July 9, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-19-0076

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2019/07/09/0008-5472.CAN-19-0076.DC1

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