Telomere-associated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC)

Journal Pre-proof Telomere-associated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC)

Camila Baldin Storti, Rogério Antônio de Oliveira, Márcio de Carvalho, Erica Nishida Hasimoto, Daniele Cristina Cataneo, Antonio José Maria Cataneo, Júlio De Faveri, Elton José R. Vasconcelos, Patrícia Pintor dos Reis, Maria Isabel Nogueira Cano PII:

S0014-4800(19)30746-4

DOI:

https://doi.org/10.1016/j.yexmp.2019.104354

Reference:

YEXMP 104354

To appear in:

Experimental and Molecular Pathology

Received date:

12 October 2019

Revised date:

28 November 2019

Accepted date:

6 December 2019

Please cite this article as: C.B. Storti, R.A. de Oliveira, M. de Carvalho, et al., Telomereassociated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC), Experimental and Molecular Pathology(2019), https://doi.org/ 10.1016/j.yexmp.2019.104354

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© 2019 Published by Elsevier.

Journal Pre-proof Telomere-associated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC) Camila Baldin Storti 1, Rogério Antônio de Oliveira 2, Márcio de Carvalho3, Erica Nishida Hasimoto4, Daniele Cristina Cataneo4, Antonio José Maria Cataneo4, Júlio De Faveri5, Elton José R. Vasconcelos 6, Patrícia Pintor dos Reis 4,7, Maria Isabel Nogueira Cano1*

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Genetics Dept.1, Biostatics Dept.2, Biosciences Institute; Faculty of Veterinary Medicine and Animal Science3; Department of Surgery and Orthopedics 4, Department of Pathology5, Experimental Research Unity (UNIPEX) 7, Faculty of Medicine, Sao Paulo State University (UNESP), Botucatu, SP, Brazil; Leeds Omics, University of Leeds, United Kingdom6.

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Abbreviations: BRCA2, breast cancer 2; DAXX, Death-Domain Associated Protein; DDR, DNA damage repair; DKC1, dyskerin; DNMT3B and DNMT3A, DNA methyltransferases A and B; HSP90AA1, Heat Shock Protein; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; MRE11, MRE11 homolog, double-strand break repair nuclease; ncRNA, non coding RNA; NSCLC, non-small cell lung cancer; POT1, protection of telomeres;RAD51, RAD51 recombinase; RPA, Replication Protein A; RUVBL1, Pontin; RUVBL2, Repetin; SUV39H1, Suppressor of Variegation 3-9 Homolog 1; TCGA, The Cancer Genome Atlas; TERT, telomerase reverse transcriptase; TERC, telomerase RNA; TERRA, telomeric repeat-containing RNA.

Abstract In the past decade, research efforts were made to identify molecular biomarkers useful as therapeutic targets in Non-Small Cell Lung Cancer (NSCLC), the most frequent type of lung carcinoma. NSCLC presents different histological subtypes being the most prevalent LUSC (Lung Squamous Cell Cancer) and LUAD (Lung Adenocarcinoma), and only a subset of LUAD patients’ present tumors expressing known targetable genetic

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alterations. Telomeres and its components, including telomerase, the enzyme that replenishes telomeres, have been considered potential cancer biomarkers due to their crucial role in cell proliferation and genome stability. Our study aims to quantify expression changes affecting telomere-associated genes and ncRNAs associated with telomere regulation and maintenance in NSCLC. We first assessed the transcriptome (RNA-Seq) data of NSCLC patients from The Cancer Genome Atlas (TCGA) and then we tested the expression of telomere-associated genes and telomeric ncRNAs (TERC, telomerase RNA component, and TERRA, telomere repeat-containing RNA) in Brazilian NCSLC patient samples by quantitative RT-PCR, using matched normal adjacent tissue samples as the control. We also estimated the mean size of terminal restriction fragments (TRF) of some Brazilian NSCLC patients using telomeric Southern blot. The TCGA analysis identified alterations in the expression profile of TERT and telomere damage repair genes, mainly in the LUSC subtype. The study of Brazilian NSCLC samples by RT-qPCR showed that LUSC and LUAD express high amounts of TERT and that although the mean TRF size of tumor samples was shorter compared to normal cells, telomeres in NSCLC are probably maintained by telomerase. Also, the expression analysis of Brazilian NSCLC samples identified statistically significant alterations in the expression of genes involved with telomere damage repair, as well as in TERC and TERRA, mainly in the LUSC subtype. We, therefore, concluded that telomere maintenance genes are significantly deregulated in NSCLC, repres enting potential biomarkers in the LUSC subtype.

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Keywords: Non-Small Cell Lung Cancer; LUSC; LUAD; telomeres; telomere-associated genes; telomeric ncRNAs; molecular biomarkers

1. Introduction Lung cancer is a leading cause of cancer mortality worldwide, with an estimated 1.6 million patient deaths every year (Torre et al., 2015). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common histological subtypes of non-small cell lung cancer(NSCLC), which accounts for 85% of lung cancer cases

Journal Pre-proof (Molina et al., 2008). LUSC and LUAD have been considered distinct diseases since they originate from different cells and regions of the lung as well as harbor various genetic alterations, implying different therapeutic strategies for patient treatment, mainly when the therapy is based on specific molecular targets (Campbell et al., 2016; Cancer Genome Atlas Research Network, 2014; Faruki et al., 2017; Herbst et al., 2018; Reck and Rabe, 2017; Sun et al., 2017; TCGA, 2012; Villalobos and Wistuba, 2017). The

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development of targeted therapies has changed the management of NSCLC, significantly

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improving patient outcomes. However, only a subset of lung adenocarcinoma patients

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present tumors expressing known targetable genetic alterations such as the tyrosine

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kinase receptor (RTKs) genes, mutations in the epidermal growth factor (EGFR) and

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rearrangements among the anaplastic lymphoma kinase (ALK) and ROS proto-oncogene 1(ROS1), among others (Herbst et al., 2018). In contrast, molecular alterations in RTKs

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are rarely identified in LUSC subtype, and research to identify molecular biomarkers

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useful as therapeutic targets in LUSC remains crucial (Reck and Rabe, 2017).

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Telomeres have been recognized as very promising targets for anticancer therapies due to their essential function in the maintenance of genome integrity and stability (Ivancich et al., 2017; Jafri et al., 2016; Ruden and Puri, 2013; Sun et al., 2015). Telomeres are located at the ends of eukaryotic chromosomes and consist of repetitive G-rich DNA associated with proteins and maintained by the action of telomerase (Chan and Blackburn, 2004). Telomerase is a ribonucleoprotein (RNP) minimally composed of the telomerase reverse transcriptase (TERT) and the non-coding telomerase RNA

Journal Pre-proof component (TERC), which contains the template sequence for telomere replication (Greider and Blackburn, 1989). Also, telomere maintenance involves a highly regulated network of protein interactions where the shelterin complex plays a vital role. Shelterin is a six-protein complex that regulates telomerase activity and protects telomere against fusions and degradation. Other non-telomeric proteins implicated in DNA damage repair (DDR), replication and biogenesis of the telomerase complex also play crucial roles in

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telomere length maintenance by their interactions with the shelterin components

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(Chan and Blackburn, 2004; Collins, 2006; De Lange, 2005; Gilson and Géli, 2007;

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Lazzerini-Denchi and Sfeir, 2016; O’Sullivan and Karlseder, 2010).In addition, long non-

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coding RNAs transcribed from the subtelomeric/telomeric regions (TERRA, telomere

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repeat-containing RNA) are also involved in telomere length control by regulating telomerase activity (Azzalin et al., 2007). The impairment of any factor of this intricate

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network can lead to telomere dysfunction and subsequently would trigger cellular

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senescence or cancer (O’Sullivan and Karlseder, 2010).

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Molecular alterations in TERT and some of the shelterin components like TRF1 (Telomere Repeat Factor 1), TRF2 (Telomere Repeat Factor 2), RAP1 (Repressor Activator 1), and POT1 (Protection of Telomeres 1) were previously reported in lung cancer (García-Beccaria et al., 2015; Hsu et al., 2007; Karami et al., 2016; Lin et al., 2006; Ruden and Puri, 2013; Wei et al., 2015). However, more knowledge is required to understand how telomere dysfunction is implicated in lung cancer development. Therefore, our study aims were to quantify the expression profile of telomere-

Journal Pre-proof associated genes and lncRNAs of the two major subtypes of lung cancer- LUAD and LUSC, focusing on understanding the similarities and molecular differences involving these two tumor subtypes. For this purpose, we performed transcriptomic analysis (RNA-Seq) using The Cancer Genome Atlas (TCGA) data of both LUAD and LUSC and compared the results with the expression profile of Brazilian NSCLC patients using quantitative RT-PCR (RT-

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qPCR). Our data showed that LUSC and LUAD are telomerase positive tumors and that

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critical telomere-associated genes and telomeric lncRNAs are differentially expressed in

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both NSCLC subtypes. Also, a subset of genes is altered mainly in LUSC. These results

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2. Methods

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among telomere-associated genes.

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pave the way for further approaches involving the discovery of LUSC-specific biomarkers

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2.1. Patients and tissue samples

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For the RNA-Seq analysis, we assessed the transcriptome of tumor samples and matched adjacent normal tissues from NSCLC patients (both LUAD and LUSC), available at The Cancer Genome Atlas database (TCGA). To obtain more accurate differentially expressed genes (DEG) results, we decided to use only the set of tumor samples (TCGA sample type code 01A or 01B) that had their adjacent normal tissue counterpart also sequenced (TCGA sample type code 11A), and then ran the Exact Test statistical function from the EdgeR Bioconductor package (as described in the Methods section 2.4). After

Journal Pre-proof filtering samples through this idea, we ended up with 114 sample pairs for LUAD and 98 for LUSC, which were then individually and thoroughly assessed regarding tumor category. After that, we decided to rule out samples that fell into any of the following categories: “Prior malignancy”, “History of unacceptable prior treatment related to a prior/other

malignancy”,

“BCR

Notification”,

“Synchronous

malignancy”,

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“Neoadjuvant therapy”. It yielded us to a final list of 86 sample pairs for LUAD (43

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tumors with their respective paired normal adjacent tissue), and 84 samples pairs for

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LUSC (42 tumors with their respective paired normal adjacent tissue), totalizing 85

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NSCLC patients analyzed herein. The 85 pairs of TCGA sample IDs along with their

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respective htseq.counts.gz file names that were used for the DEG analysis are provided

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in Suppl. Table 1 and Suppl. Table 2. To clearly distinguish between tumor and normal sample clusters for both LUAD and LUSC selected samples, multi-dimensional scaling

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and Suppl. Fig. 1B).

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(MDS) analysis was performed by EdgeR before running the DEG analysis (Suppl. Fig. 1A

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For RT-qPCR analysis, 26 untreated NSCLC patients were analyzed. All Brazilian patients (non-TCGA) included in this study have a history of tobacco consumption (range: 50-80 pack/year). In this analysis, we used fresh frozen primary tumors and adjacent normal tissues samples (16 LUSC and8paired adjacent normal tissues; 10 LUAD and7paired adjacent normal tissues) collected from Hospital das Clinicas, Faculty of Medicine, Botucatu, Sao Paulo, Brazil (Suppl. Table 3). All lung samples were previously

Journal Pre-proof analyzed, and the histopathological diagnosis confirmed their subtypes as LUSC and LUAD.

2.2. RNA Extraction, Reverse Transcription, and Quantitative Real-Time Total RNA was extracted from tissue samples using the RNeasy Qiagen kit (Qiagen) and treated with DNase I (RNAse-free DNAse set, Qiagen) according to the

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manufacturer’s instructions. The RNA samples were quantified by spectrophotometer

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(Nano-Drop ND-8000 spectrophotometer, Thermo Scientific), and the RNA integrity was

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evaluated by the Bioanalyzer 2100 and Agilent RNA 6000 Nano kit (Agilent

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Technologies). The cDNA synthesis was performed with 1μg of total RNA for 10 min at

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25°C, followed by 120 min at 37°C and 5 min at 85°C to inactive the enzyme, using the High Capacity cDNA Reverse Transcription Kit (Thermo Fisher) and following

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manufacturer’s instructions. Negative controls were included in each cDNA synthesis

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reaction to ensure no contamination. RNA Universal Reference (Agilent Technologies)

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was used as a positive control in all assays. RT-qPCR reaction was performed with 5ng of cDNA and 300nM of each primer in a QuantStudio 12K (Life Technologies) using Power SYBR Green Master Mix (Applied Biosystems). The thermal cycling profile for all targets started with 10 min incubation at 95°C, followed by 40 cycles at 95°C for 15 sec and 60°C for 1 min. A melting curve was included in all experiments to determine PCR product specificity. Samples were amplified in triplicate, relative gene quantification was calculated using the DeltaDelta Ct method, and the normalization of the data was

Journal Pre-proof obtained through the geometric mean of the Ct values of the endogenous controls (genes B2M and RPS13). Primer sequences (Suppl. Table 4) were designed using Primer Express Software v3.

2.3. Statistical analysis of Quantitative Real-Time data To DEGs, we used the nonparametric Wilcoxon-Mann-Whitney test for unpaired

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data obtained from tumor tissue samples (26) and normal lung tissue adjacent to the

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tumor (15) of NSCLC patients. P<0.05 was assumed as statistically significant. Statistical

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analyses were performed using Minitab software v. 16.0. We also obtained the

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expression level for individual samples by calculating the median of biological replicates

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followed by a log 10 transformation for each gene and plotted as a heatmap using the

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heatmap.2 function from the gplots Rlibrary.

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2.4. RNA-Seq data analysis

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RNA-Seq data were obtained from The Cancer Genome Atlas (TCGA). The htseq format files were downloaded from the portal https://gdc-portal.nci.nih.gov/ (Suppl. Table 1 and Suppl. Table 2). Differential expression analyses were performed within the R environment using the EdgeR package (v3.18.1) from Bioconductor. The ‘exact Test’ function from EdgeR was applied with a False Discovery Rate (FDR) threshold of 0.01 to robustly and reliably identify DEGs.

Journal Pre-proof 2.5. Telomere length measurement Terminal restriction fragment (TRF) analysis was performed using the TeloTAGGG Telomere Length Assay kit (Roche) following the manufacturer’s instructions. Genomic DNA was isolated from tumor and normal tissue samples using the DNeasy® Blood &Tissue kit (Qiagen). Briefly, 3ug of genomic DNA was digested with HinfI and RsaI to obtain the telomeric fragments that were fractionated on 1% agarose gel in 1X TBE for

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4.5 h. For Southern blotting, DNA fragments were transferred to Hybond + nylon

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membranes and hybridized with a 5’ digoxigenin end-labeled telomeric probe.

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Telomeric fragments were detected by chemiluminescence and TRFs calculated

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according to the formula: TFR = 𝛴 (𝑂𝐷𝑖)/𝛴 (𝑂𝐷𝑖)/ (𝐿𝑖), where ODi corresponds to

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3. Results and Discussion

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the chemiluminescent signal and Li is the length of the fragment at the given position.

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In this study, we evaluated the expression profile of telomere-associated genes

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and telomeric lncRNA in samples of NSCLC patients. RNA-Seq data from42 LUSC and 43LUAD samples, along with their respective adjacent normal tissue samples were downloaded from TCGA, and their gene expression profiles were further determined as described in the Material and Methods section. Our goal was to verify whether there were detectable differences in the expression profiles of telomere-associated genes in LUAD and LUSC subtypes of lung cancer. We also aimed at assessing whether changes in

Journal Pre-proof the expression levels of some of those genes are recurrent in the development of LUSC and or LUAD. There are few studies in the literature about alterations in the expression profile of telomere-associated genes in NCSLC. However, none of these studies has identified differences that would occur preferentially in one or both subtypes of the disease (LUSC and LUAD). In the present work, we individually compared the expression profile of

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genes encoding telomeric proteins (e.g., shelterin components and telomerase), non-

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telomeric proteins (involved with DNA repair, epigenetics, and DNA replication) and

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telomeric lncRNAs (TERC, and TERRA) in both subtypes. As shown below, our results

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open a new avenue and bring insights for the discovery of molecular biomarkers that

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would help differentiate LUSC and LUAD subtypes. The results obtained using TCGA data are summarized in Tables 1 and 2 and Suppl. Figure 3. RT-qPCR assays using samples

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from Brazilian NSCLC patients were used to validate these results and to analyze

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alterations in the expression profile of genes encoding telomeric proteins and telomeric

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lncRNAs (Tables 3 and 4, and Fig. 2).

3.1. LUAD and LUSC are telomerase positive tumors TERT is the catalytic subunit of the telomerase enzyme, essential for telomeres replication and genome maintenance (Greider and Blackburn, 1989). The transcriptome

Journal Pre-proof data analyses of LUAD and LUSC subtypes (TCGA dataset) revealed that TERT was significantly upregulated in both LUSC and LUAD, with a log2FC of 5.253 and 5.313, respectively, and FDR < 0.01 (Table 1, Table 2, and Suppl. Fig. 2). These results were validated by RT-qPCR using samples obtained from a cohort of Brazilian patients with LUSC

(p= 0.000) and LUAD (p = 0.001) (Table 3),and corroborated previous data

showing that 85-90% of malignant tumors express and reactivate telomerase (Hanahan

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and Weinberg, 2000; Kim et al., 1994), including NSCLC (Wei et al., 2015), which

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expresses high levels of TERT (Brennan et al., 2011; Counter et al., 1998; Hsu et al.,

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2003; Osaki et al., 2013; Wu et al., 2003). Thus, telomerase has been proposed as a

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potential target against NSCLC, since chronic NSCLC patients who presented T cells

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memory were benefited by immunotherapy with GV1001, a vaccine against telomerase (Shtivelman et al., 2014).

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We also analyzed the telomere length profile of Brazilian NSCLC patients by

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Southern blot and confirmed that telomerase is reactivated and probably responsible

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for maintaining telomeres in these cancer cells (Fig. 1). In this experiment, telomeres are represented by a "smear" that corresponds to DNA fragments obtained after digestion with frequently cutting restriction enzymes whose sites are positioned at the subtelomeric regions in different chromosomes. Using this methodology, we estimated the mean size of the telomeres restriction fragments (TRF) from 11 tumor samples and 4 adjacent normal tissue samples (see Suppl. Table 3 for details about patient samples). The mean TRF size for tumor samples was 6.7 kb and for adjacent normal cells was 7.9

Journal Pre-proof kb (Suppl. Table 5), strongly suggesting and as demonstrated before (Hsu et al., 2007), that telomeres size in NSCLC are shortened compared to normal cells, which is also a common feature shared by the majority of cancer cells(Kim et al., 1994; Jafri et al., 2016).

3.2. POT1 and TERC are upregulated in the LUSC subtype

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POT1 is a crucial component of the shelterin complex and fundamental for

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telomere protection and telomerase recruitment to telomeres (Celli and de Lange,

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2005). Changes in POT1 expression in NSCLC patients were previously demonstrated

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without any specific distinction between the two main histological subtypes (Lin et al.,

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2006). However, other studies show that NSCLC patients present SNP haplotypes of POT1, which suggests an association with the risk of developing the disease. SNP

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rs10244817, for example, was found in Chinese NSCLC patients (Hosgood et al., 2009),

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and SNP rs116895242 was found to be associated with lung cancer in people of

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European origin. Although the effect of these mutations in gene stability remains unknown (Karami et al., 2016), in Familial Melanoma, Familial Glioma, and Chronic Lymphocytic Leukemia, variants of POT1 impair telomere protection and confer a telomere elongation effect, which in combination with other genetic aberrations favors tumor incidence. Also, elevated POT1 expression is associated with poor prognosis in Multiple Myeloma (MM) patients, strongly suggesting that high levels of POT1 are

Journal Pre-proof directly implicated in disease progression (Bainbridge et al., 2015; Martínez and Blasco, 2015; Ramsay et al., 2013; Robles-Espinoza et al., 2014; Shi et al., 2014). The TCGA transcriptomic analyses of LUAD and LUSC samples shown here revealed that there was a slight upregulation in POT1 expression between tumor and normal lung tissue (log2FC of 0.659 and 0.491 for LUSC and LUAD, respectively, with FDR < 0.01 in both subtypes) (Table 1, Table 2, and Suppl. Fig. 2). Here is worth to

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remind that we arbitrarily established a log2FC threshold of 1 for upregulation (and -1

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for downregulation), suggesting that at least, in this case, POT1 did not appear as

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upregulated. Our validation analysis of POT1 mRNA expression in tumors and normal

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lung tissue samples from the Brazilian patients showed that POT1 was significantly

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upregulated in LUSC (p=0.037) (Table 3, and Fig. 2), whereas no significant difference (p=0.380) was observed for LUAD (Table 3, and Fig. 2). Our results suggest that POT1

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may be a molecular marker in Brazilian LUSC patients. A similar result was obtained

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when we analyzed TERC expression.

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TERC is a long non-coding RNA that contains a template sequence that is used by telomerase to replicate telomeres (Gilson and Géli, 2007; Martínez and Blasco, 2015). Together with TERT, TERC forms part of the minimal telomerase complex enough for "in vitro" telomere replication, although "in vivo" TERC and TERT interact with other protein components to form the telomerase ribonucleoprotein complex and to regulate telomere maintenance (Gilson and Géli, 2007; Londoño-Vallejo and Wellinger, 2012).

Journal Pre-proof The TCGA transcriptomic analyses, showed no differential expression for TERC on both LUSC and LUAD samples, whereas the RT-qPCR results showed that TERC is upregulated only in Brazilian LUSC samples (p = 0.000)since no significant changes were seen in LUAD samples (Table 4, and Fig. 2). This result is in agreement with the data obtained by Soder et al. (1998), suggesting that TERC is differentially regulated during the oncogenesis process in LUSC (Soder et al., 1998). High expression levels of TERC in

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LUSC subtype cell lines were also detected (Yokoi et al., 2003), suggesting that TERC

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transcript may indeed be differentially regulated during the oncogenesis process in the

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histological subtypes of lung carcinoma.

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3.3. DKC1 and the AAA+ ATPases RUVBL1, RUVBL2 and HSP90AA are upregulated in LUSC

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In addition to TERT and TERC, other several factors are also essential for the

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correct assembly of the telomerase RNP and telomerase activity. This includes the

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protein Dyskerin (DKC1), a component of the telomerase RNP responsible for stabilizing the interactions between TERT and TERC in the complex (Alawi and Lin, 2011). Our study demonstrated that the expression of DKC1is also upregulated in LUSC. First, we assessed TCGA data, which showed log2FC= 1.901 for LUSC and log2FC=1.112 for LUAD compared to their respective matched normal sample (FDR < 0.01 for both subtypes) (Table 1, Table 2, and Suppl. Fig. 2). In our RT-qPCR assays, the samples obtained from NSCLC Brazilian patients confirmed that DKC1is upregulated in LUSC (p= 0.001), but not in

Journal Pre-proof LUAD (p= 0.770) (Table 3, and Fig. 2). Despite the lack of information about DKC1 in NSCLC, Fernandez-Garcia et al. (2013) described that DKC1expression is elevated in several lung cancer cell lines (e.g., A549, H23, H157, H1299, H460, and H727) (Fernandez-Garcia et al., 2013). High expression ofDKC1 was mostly detected in other tumor types such as hepatocellular carcinoma (Liu et al., 2012), prostate (Sieron et al., 2009), colon (Witkowska et al., 2010) and breast (Montanaro et al., 2008), suggesting

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that DKC1 can play an essential and general role in the tumorigenesis process.

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Other components of the telomerase RNP complex are the ATPases Pontin

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(RUVBL1) and Repetin (RUVBL2). They both act in the biogenesis of the complex and are

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also involved in several cellular processes, such as regulation of the transcription

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process, chromatin remodeling, DNA repair, and cell cycle regulation (Mao and Houry, 2017; Venteicher et al., 2008). There are many pieces of evidence about the role of

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these proteins in the oncogenesis process, and their increased expression was primarily

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described in several types of cancers, such as hepatocellular carcinoma (Berasain, 2010;

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Breig et al., 2017; Haurie et al., 2009; Raymond et al., 2015), rectal (Lauscher et al., 2012, 2007; Milone et al., 2016), gastric (Cui et al., 2016; Li et al., 2010), kidney (Ren et al., 2013; Zhang et al., 2015) and myeloid leukemia (Breig et al., 2014; Osaki et al., 2013). Alterations in the expression levels of these ATPases were also reported in NSCLC (Dehan et al., 2007; Velmurugan et al., 2017; Yuan et al., 2016), and SCLC -Small Cell Lung Cancer (Ocak et al., 2014; Uribarri et al., 2014). Therefore, these ATPases have been considered as essential biomarkers for the diagnosis and prognosis of various

Journal Pre-proof types of cancers, including lung cancer (Mao and Houry, 2017). In our study, we also found RUVBL1 and RUVBL2 highly expressed in NSCLC samples, mainly in the LUSC subtype. The transcriptomic analyses using data obtained from the TCGA, showed LUSC samples presenting log2FC= 1.676for RUVBL1and log2FC= 1.033 for RUVBL2 (both genes with FDR < 0.01), whereas LUAD samples showed log2FC= 0.845 for RUVBL1 and no alterations in RUVBL2 expression, meaning that there are no significant differences

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between LUAD and normal samples (Table 1, Table 2, and Suppl. Fig. 2). The validation

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of these results using RT-qPCR in samples obtained from NSCLC Brazilian patients

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confirmed the TCGA data results, showing that the levels of RUVBL1 (p= 0.002) and

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RUVBL2 (p = 0.008) for LUSC were significantly different from LUAD (RUBBL1 and

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RUVBL2 showed p= 0.626) (Table 3, and Fig. 2).

Another necessary factor for the correct functioning of the telomerase RNP

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complex is the Heat Shock Protein - HSP90AA1, an ATPase that regulates the activity,

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stability, and subcellular localization of the telomerase complex (Collins, 2006). Our RT-

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qPCR results detected that Hsp90AA1 is upregulated in LUSC (p= 0.012), but no significant alterations were seen in LUAD samples (p=0.922) obtained from the Brazilian patient cohort (Table 3, and Fig. 2).The transcriptome data analyses (TCGA) showed no significant difference in both LUAD (log2FC= 0.370, FDR < 0.01) and LUSC (log2FC= 0.0751, FDR < 0.01) samples compared to their corresponding normal lung tissues (Table 1, Table 2, and Suppl. Fig. 2).

Journal Pre-proof The literature is scarce in studies evaluating the expression of HSP90AA1 in lung cancer, although the upregulation of HSP90 isoform b was previously detected in NSCLC tumors (Collins, 2006; Wang et al., 2005) as well as increased expression of GRP94 and TRAP1 HSP90 isoforms was observed in SCLC patients (Lee et al., 2015; Wang et al., 2005). Our results, although preliminary, reinforce the above findings and suggest that HSP90s are probably directly involved with the development of lung cancer and may be

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considered potential prognostic markers since their upregulation is associated with poor

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patient survival and advanced disease stage (Collins, 2006; Wang et al., 2005).

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3.4. Alterations in the expression of genes encoding the epigenetic markers DNMT3B,

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DNMT3A and SUV39H1 were detected in LUSC

DNMT3B and DNMT3A genes encode DNA methyltransferases involved in DNA

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methylation processes at subtelomeric regions and regulation of telomere length

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(Gonzalo et al., 2006), whereas the SUV39H1 (Suppressor of Variegation 3-9 Homolog 1)

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encodes a histone methyltransferase that trimethylates lysine 9 of histone H3, involved in epigenetic regulation of telomeres through the organization of heterochromatin, gene silencing, genomic stability and control of telomere length (García-Cao et al., 2003). Analysis of the transcriptome of NSCLC patients (TCGA dataset) showed that the expression of DNMTs is high in LUSC (DNMT3B, log2FC= 3.260 and DNMT3A, log2FC= 1.343, with FDR < 0.01), whereas in LUAD samples onlyDNMT3B was upregulated

Journal Pre-proof (log2FC= 2.020, FDR < 0.01), since DNMT3A showed no significant difference (log2FC= 0.806, FDR < 0.01) considering our threshold (log2FC ≥ 1.000) (Table 1, Table 2, and Suppl. Fig. 2). Validation analyses in the Brazilian patient cohort showed that both DNMTs were upregulated in LUSC (DNMT3B p= 0.003 and DNMT3A p=0.043), whereas these genes did not show alterations in LUAD (DNMT3B p= 0.051 and DNMT3A p=0.329) (Table 3, and Fig. 2). Increased expression of DNMTs was shown in several cancer types,

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including myeloid leukemia, hepatocellular carcinoma, breast and colorectal cancer

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(Zhang and Xu, 2017), and a single study demonstrated that depletion of DNMT3A in

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mice led to lung cancer progression (Gao et al., 2011; Zhang and Xu, 2017). Our results

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showed that DNMT3B might be involved in the development of both NSCLC subtypes,

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and alterations in the expression of DNMT3A would be useful to differentiate LUSC from LUAD.

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Besides, SUV39H1 was also found upregulated in LUSC samples obtained from

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both TCGA (log2FC=1.377 and FDR < 0.01) and Brazilian patient samples, as validated by

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RT-qPCR (p=0.000) when compared to normal cells. In contrast, SUV39H1 expression was not altered in both LUAD samples from TCGA (log2FC=0.603, FDR < 0.01) and Brazilian patients samples validated by RT-qPCR (p= 1.000) (Table 1, Table 2, and Suppl. Fig. 2). Liu et al. (2015) have shown that inhibition of SUV39H1 by chaetocin (a histone methyltransferase inhibitor) inhibited gene silencing and induced NSCLC cells to apoptosis, highlighting that in NSCLC, SUV39H1 can act by controlling processes of cell proliferation and apoptosis (Kim et al., 2013). SUV39H1 also showed increased

Journal Pre-proof expression in gliomas (Spyropoulou et al., 2014) and is directly involved in the development of acute myeloid leukemia (Di Croce, 2002). Therefore, the elevated expression of SUV39H1 observed in LUSC samples provides further evidence about the importance of this protein for oncogenesis in NSCLC, especially in the LUSC subtype.

3.5. Upregulation of RAD51 and BRCA2 but not RPA was detected in NSCLC

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RAD51 (RAD51 Recombinase) and BRCA2 (Breast cancer 2) are homologous

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recombination factors, inherently involved in DNA repair by homologous recombination

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and with mechanisms of fragments exchange between sister chromatids (Lazzerini-

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Denchi and Sfeir, 2016). Also, BRCA2 acts as a facilitator for the access of RAD51 to

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telomeres in the S and G2 phases of the cell cycle (Badie et al., 2010). High expression of RAD51 has been correlated to a poor disease prognosis in

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several types of cancer, such as NSCLC, breast, head and neck, pancreas, leukemia,

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colorectal (Breathnach et al., 2001; Christodoulopoulos et al., 1999; Li et al., 2017; Heiko

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Maacke et al., 2000; Qiao et al., 2005; Söderlund et al., 2007). Elevated RAD51 expression has also been associated with increased resistance of NSCLC cancer cells to chemotherapeutic agents, such as compounds containing platinum (e.g., cisplatin) and gefitinib (an EGFR, Epidermal Growth Factor Receptor, inhibitor) (Ko et al., 2008b; Qiao et al., 2005; Takenaka et al., 2007), to the resistance of leukemia to treatment and the increase of invasive capacity of breast cancer cells (Christodoulopoulos et al., 1999; Heiko Maacke et al., 2000). The majority of anticancer drugs induces DNA damage

Journal Pre-proof leading to cell cycle arrest or cell death, but the resistance of cancer cells to therapeutic agents has been associated with increased efficacy of DNA repair mechanisms , considered one of the main barriers to cancer therapy (Hoeijmakers, 2001; Synowiec et al., 2008). In agreement, previous studies showed that the survival of patients with NSCLC was lower in patients with efficient DNA repair system (Bosken et al., 2002) as well as NSCLC cell lines require high doses of cisplatin (Henning and Stürzbecher, 2003).

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Moreover, RAD51 plays a crucial role in DDR by homologous recombination, explaining

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why it is directly involved with increased resistance of cells to cancer treatment

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(Henning and Stürzbecher, 2003; Lai et al., 1995; Takenaka et al., 2007).

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In our study RAD51 was upregulated in the transcriptome of both LUSC (log2FC=

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3.576, FDR < 0.01) and LUAD (log2FC= 2.147, FDR < 0.01) (TCGA dataset) (Table 1, Table 2, and Suppl. Fig. 2) and in the Brazilian LUSC patients (p=0.000).In contrast, RAD51 was

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not upregulated in Brazilian LUAD patients (p= 0.097) (Table 3 and Fig. 2). All of these

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studies, including the results obtained in the present work, showed the importance of

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RAD51 for the oncogenic process in NSCLC, although more studies are needed. RAD51 has a great potential to be considered a prognostic marker in NSCLC patients, being useful to identify patients with the greatest risk of tumor progression and disease recurrence, and in the identification of patients that are resistant to chemotherapy (Ko et al., 2008b, 2008a; Qiao et al., 2005; Takenaka et al., 2007). In its turn, BRCA2 usually facilitates the access of RAD51 to telomeres (Badie et al., 2010) and was found upregulated in the transcriptome of LUSC (log2FC= 1.620, FDR

Journal Pre-proof < 0.01) and LUAD (log2FC= 1.199, FDR < 0.01) samples from TCGA (Table 1, Table 2, and Suppl. Fig. 2). In the NSCLC Brazilian samples, BRCA2 mRNA levels estimated by RT-qPCR was upregulated in LUSC (p=0.000) but not in LUAD (p= 0.845) (Table 3, and Fig. 2). RPA (Replication Protein A) is a heterotrimeric complex formed by RPA1 (70 KDa), RPA2 (32KDa) and RPA3

(14KDa), playing important roles in different DNA

metabolism pathways such as replication, recombination, and telomere maintenance

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(Gilson and Géli, 2007; Wold, 1997). The subunit RPA1 is overexpressed in

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mononucleated cells of Multiple Myeloma (MM) patients but not in the premalignant

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form of MM (Monoclonal Gammopathy of Undetermined Significance, GMSI) (Panero

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et al., 2015). Increased expression of RPA1 was also detected in lymphocytes of patients

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with chronic lymphocytic leukemia (Hoxha et al., 2014; Poncet et al., 2008), and high expression of RPA1 and RPA2 was described in esophagus tumors (Dahai et al., 2013),

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colon (Givalos et al., 2007) and bladder carcinoma (Levidou et al., 2011). Higher

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expression of RPA1 was also associated with a poor prognosis of patients with

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esophageal cancer (Dahai et al., 2013), as well as elevated expression of RPA1 and RPA2 was related to a poor prognosis in colon cancer (Givalos et al., 2007). There is no published data about alterations of RPA expression in NSCLC. Here we show that among the three subunits, only RPA3 was upregulated in LUSC samples from Brazilian patients (p=0.000), but not in LUAD (p= 0.380) (Table 3, and Fig. 2). The TCGA transcriptomic analyses showed no significant difference, considering our arbitrary threshold (log2FC ≥ 1), in the expression of the three subunits comparing normal and tumor samples in LUSC

Journal Pre-proof (log2FC= 0.934 for RPA3, FDR < 0.01, and log2FC=0.926 for RPA1, FDR < 0.01) and LUAD samples (log2FC=0.774, FDR < 0.01 for RPA3 and log2FC= 0.426 for RPA1, FDR < 0.01) (Table 1, Table 2, and Suppl. Fig. 2). Both results, although too preliminary, suggest that RPA does not play a major role in NSCLC oncogenesis.

3.6. MRE11 and DAXX are upregulated in Brazilian patients with LUSC (Death-Domain Associated

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We also investigate the mRNA levels of DAXX

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Protein) and MRE11 (MRE11 homolog, double-strand break repair nuclease), proteins

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that play different roles in DDR at telomeres (Lazzerini-Denchi and Sfeir, 2016). Analysis

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of gene expression using RT-qPCR showed that the genes encoding both proteins are

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upregulated in Brazilian patients with LUSC (DAXX p=0.017 and MRE11 p=0.010) (Table 3, and Fig. 2), whereas LUAD patients didn’t show a significant difference when

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compared with normal samples (DAXX p=0.558 and MRE11 p=0.845) (Table 3, and Fig.

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2). The TCGA data for DAXX and MRE11 also did not show a relevant difference in the

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expression of both genes compared with the respective normal samples. In the analyses of LUSC subtype, MRE11 showed log2FC= 0.714 (FDR < 0.01), and DAXX showed log2FC= 0.529 (FDR < 0.01) and in LUAD subtype, MRE11 showed log2FC= 0.420 (FDR < 0.01), and DAXX showed FDR > 0.01 (Table 1, Table 2, and Suppl. Fig. 2). Noteworthy that up to date, there is no available data in the literature about the role of these genes in NSCLC, especially in LUSC. Nevertheless, there are reports showing upregulation of DAXX and MRE11 genes in different cancer types. For example, DAXX is upregulated in ovarian

Journal Pre-proof cancer (Pan et al., 2013) and esophageal squamous carcinoma (Ko et al., 2018), whereas MRE11 was found upregulated in multiple myeloma (Panero et al., 2015).

3.7. Upregulation of TERRA in LUSC In humans, TERRA is an RNAPII (RNA polymerase II) lncRNA transcribed from some subtelomeric regions of the C-rich telomeric strand towards the end of the

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chromosomes (Azzalin et al., 2007; Nergadze et al., 2009; Pfeiffer and Lingner, 2012;

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Schoeftner and Blasco, 2008). TERRA transcripts were first detected in chromosomes

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loci 1q, 2q, 10q, 13q, and 15q and further in the chromosome locus 20q (Montero J.J.,

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López de Silanes I., Graña O., 2016). It seems that only the transcripts originated from

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20q show TERRA characteristics, and its ablation resulted in a high rate of telomere loss

Silanes I., Graña O., 2016).

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and induction of massive local DDR, which affected cell viability (Montero J.J., López de

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It is still not well defined what regulates the number of TERRA transcripts in the

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cells, and in tumor cells, it seems to depend on the tumor developmental stage and the structure of the telomeric chromatin (Arora et al., 2012). What is already well recognized is that TERRA is involved in the regulation of telomere length and replication, in modulating the actions of exonuclease 1 and telomerase, in the response of DNA damage at telomeres and alterations in the composition of telomeric chromatin during the cell cycle (Arora et al., 2012; Azzalin et al., 2007).

Journal Pre-proof Here, we evaluated the expression levels of TERRA 15q, TERRA 1q-2q-10q-13q, and TERRA 20q, in tumor and normal adjacent tissue samples from patients with NSCLC. Changes in the expression of TERRA 1q-2q-10q-13q (p = 0.005) were detected only in LUSC samples compared to normal tissues. No significant alterations were detected in the expression level of TERRA 20q (p = 0.006) and TERRA 15q (p= 0.298) expression (Table 4, and Fig. 2) in LUSC and LUAD samples, although the results obtained for

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TERRA20q in LUSC (p = 0.066) are in the borderline for the considered p-value ≤0.05,

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strongly suggesting that there may be a tendency for these tumor cells to show elevated

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expression of TERRA 20q (median = 4.897) compared to normal (median = 0.939).

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However, the low number of samples here studied may have affected this analysis,

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although alterations in TERRA expression in NSCLC would be necessary for tumor

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4. Conclusions

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maintenance.

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In this study, we investigated the expression profile of important genes encoding telomeric factors such as telomeric proteins, lncRNAs, and proteins involved with DDR at telomeres, on the attempt to find potential biomarkers that would help us to differentiate the NSCLC histological subtypes (LUSC and LUAD) at the telomere-targeted molecular level. We first assessed the transcriptome of tumor samples and matched adjacent normal tissues from NSCLC patients available at TCGA repository, and further, we performed RT-qPCR assays to validate the results using tumor and normal samples

Journal Pre-proof from Brazilian NSCLC patients. We identified significant alterations in the expression of genes involved with telomere damage repair as well as in TERT, TERC, and TERRA, mostly in LUSC samples, concluding that telomere maintenance genes are differentially expressed in NSCLC and would be potential biomarkers for the LUSC subtype. By thoroughly assessing the transcriptional profile of a selected list of telomerefunctionally-related genes in both LUSC and LUAD, the present work paves the way for

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further integrative omics approaches aimed at scrutinizing potential telomere-targeted

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biomarkers for NSCLC.

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Acknowledgments

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This work was supported by São Paulo Research Foundation, FAPESP (grants 2015/18641-5 and 2012/50161-8 to MICANO and 2011/13213-7 to PP Reis). CBS was a

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References

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Figure Legends

Figure 1. Telomere restriction fragment profile of NSCLC Brazilian patients. Southern blot was done with genomic DNA obtained from tumor samples and matched adjacent

Journal Pre-proof normal tissue. DNA was restricted digested with HinfI and RsaI, and DNA fragments were separated onto1% ethidium bromide-stained agarose gel. Lane 1, LUSC (patient 92T); lanes 2 and 3, LUAD (patient 60T, and 52T); lanes 4 and 5, adjacent normal samples; lanes 6-8 LUSC (patients 98T, 28T and 24T); lane 9, LUAD (patient 20T); lanes 10-13 LUSC (patients 16T, 12T, 8T, and 4T); lanes 14 and 15, adjacent normal samples; molecular weight marker is a mixture of DIG MW III and VII (Roche). Southern blotting

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hybridization and chemiluminescent detection were performed using the TeloTAGGG

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Telomere Length assay (Roche). The red lines indicate the position of the larger

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telomeric fragment in each sample.

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Figure 2. RT-qPCR panel for selected telomere-associated genes using samples from Brazilian NSCLC patients of the subtypes LUSC and LUAD. The expression level for

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individual samples was obtained by calculating the median of biological replicates of

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three independent experiments, followed by a log 10 transformation for each gene (rows)

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per sample groups (columns), and then plotted as a heatmap. Statistics for identifying DEGs were based on non-paired and non-parametric analyses (Wilcoxon-Mann-Whitney, p<0.05). Genes are ordered by hierarchical clustering from their expression values across sample groups. The analyses were performed with 16 LUSC and 8 matched normal adjacent tissue samples, and 10 LUAD and 7 matched normal adjacent tissue samples. Black and red asterisks indicate genes that are upregulated in LUSC (16) and LUAD (01), respectively. Relative gene quantification was calculated using the DeltaDelta Ct method

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Supplementary Figure 1. Multi-dimensional scaling (MDS) analysis. MDS was performed by EdgeR before running the differential expression analysis between tumor and normal adjacent samples for both LUAD (A) and LUSC (B).

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Supplementary Figure 2. Expression profile of telomere-associated genes from NSCLC

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patients available at TCGA. Expression of each gene (log2 Fold Change) was plotted

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within the R environment using the ‘heatmap.2’ function from the ‘gplots’ library (p≤

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0.01 e FDR ≤ 0.01). The transcripts were ordered using no hierarchical clustering.

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Upregulated transcripts (log 2FC ≥ 1) are in yellow and down-regulated transcripts (log 2FC ≤ -1) are in blue. Black and red asterisks indicate, respectively the genes that are

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upregulated in LUSC (14) and in LUAD (6).

Journal Pre-proof Author Contribution Statement

Camila Baldin Storti: Formal analysis; Investigation; Methodology; Validation; Roles/Writing – original draft; Writing – review & editing. Rogério Antônio de Oliveira: Data curation; Formal analysis; Methodology; Validation; Roles/Writing – original draft Márcio de Carvalho: Methodology; Validation; Formal analysis

Daniele Cristina Cataneo: Resources; Validation

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Antonio José Maria Cataneo: Resources; Validation

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Erica Nishida Hasimoto: Resources; Validation

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Júlio De Faveri: Resources; Validation

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Elton José R. Vasconcelos: Conceptualization; Data curation; Formal analysis; Software; Validation; Writing – review & editing.

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Patrícia Pintor dos Reis: Conceptualization; Data curation; Formal analysis; Funding acquisition; Supervision; Writing – review & editing.

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Maria Isabel Nogueira Cano: Conceptualization; Data curation; Funding acquisition; Project administration; Supervision; Writing – review & editing.

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Table 1. Differentially expressed telomere-associated genes in LUSC (TCGA dataset) Ensembl ID

Gene description

Log2 FC P-value

FDR

TERT

ENSG00000164362.17

Tel omerase reverse tra nscriptase

5.253

2.35E-24

5.51E-23

RAD51

ENSG00000051180.15

RAD51 recombinase

3.576

5.10E-97

9.08E-94

DNMT3B

ENSG00000088305.17

DNA methyl transferase 3 beta

3.260

1.50E-35

7.51E-34

DKC1

ENSG00000130826.14

Dys kerin pseudouridine s ynthase 1

1.901

3.47E-45

3.16E-43

RUVBL1 (Pontin)

ENSG00000175792.10

RuvB l i ke AAA ATPa se 1

1.676

1.83E-49

2.20E-47

BRCA2

ENSG00000139618.13

BRCA2, DNA repa ir associated

1.620

1.10E-25

2.85E-24

RBBP8 (CTLP)

ENSG00000101773.15

RB bi nding protein 8, endonuclease

1.604

2.25E-23

4.89E-22

PARP1

ENSG00000143799.11

1.438

3.49E-36

1.86E-34

SUV39H1

ENSG00000101945.15

Pol y(ADP-ri bose) polymerase 1 Suppressor of va riegation 3-9 homolog 1

1.377

1.44E-39

9.56E-38

DNMT3A KMT5C (SUV420H2)

ENSG00000119772.15

DNA methyl transferase 3 a lpha

1.343

8.33E-25

2.01E-23

ENSG00000133247.12

Lys i ne methyltransferase 5C

1.276

2.64E-15

2.94E-14

DNMT1

ENSG00000130816.13

DNA methyl transferase 1

1.238

1.75E-28

5.56E-27

ATR

ENSG00000175054.13

ATR s eri ne/threonine kinase

1.037

1.01E-24

2.41E-23

RUVBL2 (Reptin)

ENSG00000183207.11

RuvB l i ke AAA ATPa se 2

1.033

1.84E-17

2.50E-16

RPA3

ENSG00000106399.10

Replication protein A3

0.934

6.18E-12

5.01E-11

RPA1

ENSG00000132383.10

Replication protein A1

0.926

2.23E-22

4.49E-21

ENSG00000196419.11

X-ra y repa ir cross complementing 6

0.763

3.32E-17

4.41E-16

ENSG00000110958.14

0.759

3.78E-14

3.79E-13

0.751

3.00E-13

2.76E-12

0.714

4.57E-14

4.53E-13

0.677

7.85E-06

3.28E-05

PTGES3

ro

-p

re

lP

na

ur

Jo

XRCC6 (Ku 70)

of

Gene symbol

HSP90AA1

ENSG00000080824.17

MRE11

ENSG00000020922.11

RTEL1

ENSG00000258366.6

Pros ta glandin E s ynthase 3 Hea t s hock protein 90 a l pha family cl a ss A member 1 MRE11 homolog, double strand brea k repair nuclease Regulator of telomere elongation hel icase 1

XRCC5 (ku 80)

ENSG00000079246.14

X-ra y repa ir cross complementing 5

0.663

8.56E-13

7.52E-12

POT1

ENSG00000128513.13

Protecti on of telomeres 1

0.659

2.08E-11

1.61E-10

CBX5

ENSG00000094916.12

Chromobox 5

0.657

6.34E-08

3.44E-07

RAD52

ENSG00000002016.15

RAD52 homolog, DNA repair protein 0.566

8.44E-05

3.06E-04

Journal Pre-proof

5.69E-09

3.44E-08

0.529

1.75E-10

1.24E-09

ENSG00000012061.14

Dea th domain associated protein ERCC exci sion repair 1, endonuclease non-catalyti c subunit

ERCC1

0.489

4.23E-06

1.83E-05

XRCC4

ENSG00000152422.14

X-ra y repa ir cross complementing 4

0.427

1.14E-04

4.06E-04

TERF1 (TRF1)

ENSG00000147601.12

0.418

1.73E-09

1.11E-08

WRAP53 (TCAB1) ENSG00000141499.15

Tel omeric repeat binding factor 1 WD repeat containing antisense to TP53

0.403

1.61E-04

5.60E-04

STAG2

ENSG00000101972.17

Stroma l a ntigen 2

0.383

1.39E-04

4.89E-04

TNKS

ENSG00000173273.14

0.371

1.39E-04

4.88E-04

PINX1

ENSG00000254093.7

0.370

3.09E-03

8.66E-03

ERCC4

ENSG00000175595.13

Ta nkyrase PIN2/TERF1-interacting telomerase i nhibitor 1 ERCC exci sion repair 4, endonuclease catalytic s ubunit

0.334

2.53E-03

7.20E-03

TINF2 (TIN2)

ENSG00000092330.14

TERF1 i nteracting nuclear fa ctor 2

-0.382

9.78E-05

3.51E-04

TERF2IP (RAP1)

ENSG00000166848.5

-0.505

2.88E-11

2.20E-10

CTC1

ENSG00000178971.12

TERF2 i nteracting protein CST tel omere replication complex component 1

-0.625

2.91E-09

1.81E-08

STN1

ENSG00000107960.9

STN1, CST compl ex s ubunit

-0.776

1.93E-11

1.50E-10

ro

ENSG00000204209.9

of

0.549

-p

DAXX

ACD, s helterin complex s ubunit and tel omerase recruitment factor

re

ENSG00000102977.12

lP

ACD (TPP1)

Jo

ur

na

FC, fold change; FDR, False Discovery Rate

Journal Pre-proof Table 2. Differentially expressed telomere-associated genes in LUAD (TCGA dataset)

TERT

log2 FC

P-value

FDR

Tel omerase reverse ENSG00000164362.17 tra ns criptase

5.313

7.12E-20

3.23E-18

RAD51

ENSG00000051180.15 RAD51 recombinase

2.147

7.67E-26

6.26E-24

DNMT3B

ENSG00000088305.17 DNA methyl transferase 3 beta

2.020

8.70E-17

2.75E-15

BRCA2

1.199

1.75E-11

2.73E-10

DKC1

ENSG00000139618.13 BRCA2, DNA repa ir associated Dys kerin pseudouridine ENSG00000130826.14 s ynthase 1

1.112

1.43E-22

8.69E-21

PARP1

ENSG00000143799.11 Pol y(ADP-ri bose) polymerase 1

1.078

7.30E-19

2.99E-17

RUVBL1 (Pontin)

ENSG00000175792.10 RuvB l i ke AAA ATPa se 1

0.845

9.78E-10

1.17E-08

DNMT3A

ENSG00000119772.15 DNA methyl transferase 3 a lpha 0.806

6.71E-10

8.23E-09

RPA3

ENSG00000106399.10 Replication protein A3

0.774

2.57E-08

2.44E-07

ATR

ENSG00000175054.13 ATR s eri ne/threonine kinase

0.741

4.15E-12

7.07E-11

DNMT1

0.735

1.16E-07

9.82E-07

0.721

2.66E-06

1.71E-05

0.694

2.74E-07

2.14E-06

0.658

6.32E-09

6.65E-08

0.603

4.99E-06

3.02E-05

XRCC5 (ku 80)

ENSG00000130816.13 DNA methyl transferase 1 Regulator of telomere ENSG00000258366.6 el ongation helicase 1 X-ra y repa ir cross ENSG00000152422.14 compl ementing 4 RB bi nding protein 8, ENSG00000101773.15 endonuclease Suppressor of va riegation 3-9 ENSG00000101945.15 homolog 1 X-ra y repa ir cross ENSG00000079246.14 compl ementing 5

0.527

1.19E-07

1.01E-06

CBX5

ENSG00000094916.12 Chromobox 5

0.518

2.89E-06

1.85E-05

ENSG00000128513.13 Protecti on of telomeres 1

0.491

3.23E-06

2.04E-05

Replication protein A2 0.426 MRE11 homolog, double strand ENSG00000020922.11 brea k repair nuclease 0.420 Hea t s hock protein 90 a l pha ENSG00000080824.17 fa mi ly class A member 1 0.370

8.55E-04

2.99E-03

6.07E-07

4.42E-06

1.69E-03

5.46E-03

ENSG00000110958.14 Pros ta glandin E s ynthase 3 RAD50 double strand break ENSG00000113522.12 repa ir protein Tel omeric repeat binding factor ENSG00000132604.9 2 SMG6, nons ense mediated ENSG00000070366.12 mRNA deca y factor

0.329

1.56E-03

5.10E-03

0.275

9.80E-04

3.37E-03

0.255

2.30E-03

7.16E-03

-0.365

6.25E-04

2.27E-03

SUV39H1

POT1 RPA2 MRE11 HSP90AA1 PTGES3 RAD50 TERF2 (TRF2) SMG6 (Est1)

-p

re

lP

na

RBBP8 (CTLP)

ur

XRCC4

Jo

RTEL1

Gene description

of

Ensembl ID

ro

Gene symbol

ENSG00000117748.8

Journal Pre-proof

TINF2 (TIN2)

TERF1 i nteracting nuclear ENSG00000092330.14 fa ctor 2

-0.496

Jo

ur

na

lP

re

-p

ro

of

FC, fold change; FDR, False Discovery Rate

3.33E-06

2.10E-05

Journal Pre-proof Table 3. Relative expression of telomere-associated genes in Brazilian LUSC and LUAD patients

LUSC SUBTYPE Gene ID

Gene description

Sample (n)

Median

Max- Min

Range

P- value

TERT

7015

Tel omera s e revers e

N (8)

0.799

5.537- 0.274

5.267

0.000

tra ns cri pta s e

T (16)

228.877

18176.888- 6.382

18170.506

RAD51 recombi na s e

N (8)

1.015

1.423- 0.669

0.755

14.237

48.634- 3.159

45.475

0.871

2.365- 0.472

1.893

3.982

12.943- 1.223

11.719

0.982

1.705- 0.542

1.164

5.184

27.932- 1.536

26.397

RAD51

5888

of

Gene symbol

6119

Suppressor of va ri ega ti on

N (8)

3-9 homol og 1

T (16)

Repl i ca ti on protei n A3

N (8)

re

RPA3

6839

-p

SUV39H1

ro

T (16)

RUVBL1 (Pontin) DNMT3B

RUVBL2

8607

N (8)

1.104

1.677- 0.524

1.154

a s s oci a ted

T (16)

8.657

40.836- 1.490

39.345

Dys keri n ps eudouri di ne

N (8)

0.936

2.439- 0.509

1.930

s yntha s e 1

T (16)

3.296

19.983- 0.988

18.995

N (8)

1.008

2.285- 0.530

1.755

T (16)

4.815

17.575- 0.524

17.050

DNA methyl tra ns fera s e 3

N (8)

1.012

2.664- 0.336

2.328

beta

T (16)

10.753

112.396- 0.529

111.866

RuvB l i ke AAA ATPa s e 2

N (8)

0.829

2.055- 0.475

1.580

T (16)

2.499

12.739- 0.780

11.959

N (8)

0.871

0.402- 3.162

2.760

na

1736

BRCA2, DNA repa i r

ur

DKC1

675

RuvB l i ke AAA ATPa s e 1

Jo

BRCA2

lP

T (16)

1789

10856

4361

MRE11 homol og, doubl e

Samp N

T( 0.000

N

T( 0.000

N

T( 0.000

N

T( 0.000

N

T( 0.001

N

T( 0.002

N

T( 0.003

N

T( 0.008

N

T(

0.010

N

Journal Pre-proof

DNMT3A

TERF1

25913

1788

7013

61.153- 0.437

60.717

Hea t s hock protei n 90

N (8)

1.150

2.045- 0.400

1.644

a l pha fa mi l y cl a s s A member 1

T (16)

2.295

6.726- 0.624

6.102

Dea th domain a s s oci a ted

N (8)

0.900

1.877- 0.645

1.233

protei n

T (16)

2.221

8.431- 0.521

7.910

Protecti on of tel omeres 1

N (8)

0.895

2.319- 0.608

1.711

T (16)

16.500- 0.456

16.044

1.082

2.929- 0.392

2.538

3.563

27.000- 0.284

26.716

1.428

7.173- 0.152

7.020

4.599

17.214- 0.264

16.950

DNA methyl tra ns fera s e 3

N (8)

a l pha

T (16)

Tel omeric repea t bi ndi ng

N (8)

TERF2

fa ctor 1 7014

Tel omeric repea t bi ndi ng

N (8)

1.076

5.936- 0.220

5.717

fa ctor 2

T (16)

3.093

10.698- 0.329

10.369

N (8)

1.053

3.716- 0.385

3.331

T (16)

1.769

12.106- 0.422

11.685

N (8)

0.914

2.463- 0.347

2.115

mRNA deca y fa ctor

T (16)

1.684

65.959- 0.098

65.862

Stroma l a nti gen 2

N (8)

0.825

2.379- 0.324

2.055

T (16)

1.522

27.586- 0.275

27.312

PIN2/TERF1-i ntera cti ng

N (8)

0.884

4.111- 0.333

3.778

tel omera s e i nhi bi tor 1

T (16)

1.666

7.571- 0.204

7.367

(Est1) STAG2

PINX1

ur

23293

Ta nkyra s e 2

SMG6, nons ense mediated

Jo

SMG6

80351

na

(TRF2) TNKS2

10735

54984

T (16)

lP

(TRF1)

1.839

ro

POT1

1616

2.769

-p

DAXX

3320

T (16)

re

HSP90AA1

s tra nd brea k repa i r nucl ea s e

of

MRE11

T( 0.012

N

T( 0.017

N

T( 0.037

N

T( 0.043

N

T( 0.101

N

T( 0.101

N

T( 0.198

N

T( 0.221

N

T( 0.245

N

T(

0.332

N

T(

TEN1

ATRX

100134934

546

(RAD54)

TINF2

51750

26277

N (8)

0.936

2.126- 0.475

1.651

s ubuni t

T (16)

1.269

3.918- 0.3707

3.547

ATRX, chroma ti n

N (8)

1.009

3.463- 0.279

3.184

remodel er

T (16)

1.208

4.620- 0.307

4.312

Regul a tor of tel omere

N (8)

0.966

4.985- 0.206

4.778

el onga ti on hel i ca s e 1

T (16)

1.311

12.761- 0.191

12.570

TERF1 i nteracting nucl ea r

N (8)

0.879

2.471- 0.544

1.928

fa ctor 2

T (16)

12.585- 0.374

12.211

0.982

ro

RTEL1

TEN1, CST compl ex

of

Journal Pre-proof

Jo

ur

na

lP

re

-p

Note: range: difference between the Maximum and Minimum values in the sample groups (Normal or Tumor), N (Normal) and T (Tumor).

0.358

N

T(

0.358

N

T( 0.606

N

T( 0.903

N

T(

Journal Pre-proof

Table 4. Relative expression of telomeric lncRNAs genes in Brazilian LUSC and LUAD patients LUSC Gene symbol Gene ID

Gene description

Samples (n) Median

Max- Min

Range

P-value

TERC

Tel omerase RNA component

Norma l (8) Tumor (16)

1.078 17.544

4.459- 0.216 71.618- 2.361

4.244 69.257

0.000

0.753 3.755

4.409- 0.348 2709.239- 0.524

4.061 2708.714

0.005

4.215- 0.232 905.971- 0.147

3.9831 905.823

0.066

5.115- 0.044 1623.659- 0.126

5.071 1623.533

0.298

Samples (n) Median

Min- Max

Range

P-value

Norma l (7) Tumor (10)

1.070 2.772

2.185- 0.383 74.826- 0.312

1.802 74.514

0.143

1.105 1.630

2.788- 0.323 169.028- 0.120

2.465 168.908

0.696

0.889 2.059

4.201- 0.509 75.127- 0.142

3.692 74.984

0.558

1.218 1.351

2.152- 0.277 41.304- 0.173

1.875 41.131

0.558

7012

Tel omeric repeat-containing RNA, cromos some ends 1q-2q-10q-13q Norma l (8) Tumor (16) Tel omeric repeat- containing RNA, cromos some end 20q Norma l (8) Tumor (16) Tel omeric repeat- containing RNA, cromos some end 15q Norma l (8) Tumor (16)

TERRA 15q

*

LUAD Gene description

TERC

Tel omerase RNA component

*

na

TERRA 15q

ur

*

Tel omeric repeat-containing RNA, cromos some ends 1q-2q-10q-13q Norma l (7) Tumor (10) Tel omeric repeat- containing RNA, cromos some end 20q Norma l (7) Tumor (10) Tel omeric repeat- containing RNA, cromos some end 15q Norma l (7) Tumor (10)

Jo

TERRA 20q

lP

7012

re

Gene symbol Gene ID

TERRA * 1q-2q-10q-13q

0.939 4.897

ro

*

2.856 3.479

-p

TERRA 20q

of

TERRA * 1q-2q-10q-13q

Note: range: difference between the Maximum and Minimum values in the sample groups (Normal or Tumor), (*) without information, N (Normal) and T (Tumor).

Journal Pre-proof Telomere-associated genes and telomeric lncRNAs are biomarker candidates in lung squamous cell carcinoma (LUSC)

of

Camila Baldin Storti, Rogério Antônio de Oliveira, Márcio de Carvalho, Erica Nishida Hasimoto, Daniele Cristina Cataneo, Antonio José Maria Cataneo, Júlio De Faveri, Elton José R. Vasconcelos, Patrícia Pintor dos Reis, Maria Isabel Nogueira Cano

ro

Highlights

-p

. The NSCLC hystological subtypes LUSC and LUAD are telomerase positive tumors

re

. LUSC and LUAD show distinct global expression profile of telomere associated genes

lP

. Expression of telomere damage repair genes are altered in TCGA and Brazilian LUSC samples . Expression of TERC and TERRA are also altered in Brazilian LUSC samples

Jo

ur

na

. Telomere maintenance genes would represent potential biomarkers in the LUSC subtype