MicroRNA-4776-5p acts as a radiosensitizer and predicts the prognosis of patients with head and neck cancer receiving radiotherapy

doi:10.21203/rs.3.rs-3731963/v1

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MicroRNA-4776-5p acts as a radiosensitizer and predicts the prognosis of patients with head and neck cancer receiving radiotherapy

https://doi.org/10.21203/rs.3.rs-3731963/v1

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Background

Head and neck cancer (HNC) is the most common worldwide. Radiation therapy plays an important role in treating HNC. MicroRNAs (miRNAs) have been associated with tumor progression and radiosensitivity. However, their mechanisms remain largely unknown, and the evidence remains limited. This study aimed to identify miRNAs associated with the radiosensitivity of head and neck tumor cells, leading to the poor prognosis of patients with HNC receiving radiation therapy. The miRNA expression profiles and clinical information of patients with HNC were obtained from The Cancer Genome Atlas. The miRNAs were identified through an integrated bioinformatics analysis and validated through in vitro and in vivo studies.

Results

MiR-4776-5p was identified as a radiosensitizer and predictor of the prognosis of patients with HNC receiving radiotherapy. Eleven of 16 genes targeted by miR-4776-5p were found to regulate mechanisms related to radiosensitivity via functional annotation.

Conclusion

In this study, we identified a miRNA, miR-4776-5p, related to the clinical outcome of patients with HNSC receiving RT alone, which could be potentially selected as a miRNA-based therapeutic target to block radioresistant characteristics and lead to better treatment outcomes for HNC.

head and neck cancer

radiotherapy

microRNA

radiosensitivity

Cancers arising from the mucosal lining of the oral cavity, pharynx, and larynx are collectively known as head and neck cancers (HNCs). HNC is the seventh most common cancer worldwide, with more than 660,000 cases and 320,000 deaths annually (1). Among the HNCs, 90% are squamous cell carcinoma (HNSC), and the rest are adenocarcinomas. The standard treatments currently used for HNSC include surgery, radiotherapy (RT), chemotherapy, targeted therapy, and immunotherapy. While the outcome improves, it remains unsatisfactory. RT can either be a definitive treatment or adjuvant therapy. Postoperative adjuvant RT has been shown to increase the five-year cancer-specific and overall survival (OS) of patients with lymph node-positive HNSC compared to surgery alone (2). Patients with specific risk factors, such as extracapsular extension, perineural infiltration, vascular embolism, and lymphatic invasion, are suggested for postoperative RT or concurrent postoperative RT with chemotherapy to achieve better outcomes (3). However, there remains a group of patients whose cancers are prone to progression after this type of intensive treatment. Treatment failure after RT is correlated to the radioresistance of tumor cells. Therefore, a biomarker is needed to select those patients who respond poorly to RT and act as a potential radiosensitizer.

MicroRNAs (miRNAs) are endogenous RNAs with lengths of 19–23 nucleotides that play important regulatory roles by targeting messenger RNAs for post-translational modification. MiRNAs effectively repress the multiple target genes through imperfect sequence bases, with complementarity between miRNAs and their targets (4). Abnormal miRNA expression is found in various tumors, contributing to tumor development, tumor progression, and events leading to treatment resistance (5). The deregulation of miRNAs in tumors can be targeted by potential therapeutics using either miRNA replacement therapy with miRNA mimics or inhibiting miRNA function with anti-miRNAs (6). For example, lipid nanoparticle encapsulated miRNA-34 mimics showed promising anti-tumor activity when given to animal tumor models of prostate (7), liver (8), and lung (9) cancers and are currently being tested in a phase I clinical trial (NCT01829971) on several solid and hematological malignancies (6).

MiRNA modulation of the tumor response to ionizing radiation has been reported in several studies (10, 11). Growing evidence focuses only on HNCs (12). However, most miRNAs were identified using microarray methods, and few predict the prognosis of clinical patients. While some studies identified miRNAs using high-throughput screening with large sample sizes, they lacked supporting evidence from in vitro and in vivo studies (13, 14). In this study, we identified a miRNA related to the clinical outcome of patients with HNSC receiving RT alone from The Cancer Genome Atlas (TCGA) database and validated it using in vitro and in vivo experiments. This miRNA could be potentially selected as a miRNA-based therapeutic target to block radioresistant characteristics and lead to better treatment outcomes for HNC.

2.1 Data collection and processing

The smRNA and RNA sequencing profiles and clinical information of the TCGA-HNSC dataset were taken from our previous studies: the YM500 and Driver DB databases. RNA-seq and clinical data, such as the primary tumor and normal and metastatic tissues, were retrieved and annotated from the TCGA data portal (https://portal.gdc.cancer.gov/). The smRNA-seq data was downloaded from CGHub (https://cghub.ucsc.edu/) and then processed using the miR-seq pipeline of YM500 [58] and annotated with miRBase database R21 [59] and DASHR database v1.0 [60]. This study curated 20,495 genes and 2588 miRNAs for analysis.

2.2 DE and survival analyses

The DE analysis aimed to identify miRNAs significantly differentially expressed between primary tumor and adjacent normal samples. The R package DEseq (version 1.28.0) [58] was used to filter candidate miRNAs based on an adjusted p-value < 0.05 and log₂ fold-change values > 3 and efficiently identify oncogenic expression between tumor samples and normal samples. Furthermore, miRNA candidates with normalized mean counts (baseMean) < 1 were filtered out to eliminate those with excessively low expression levels. The survival analysis aimed to define clinically relevant candidates. The R package survival (version 2.41–3) was used to calculate the Cox proportional hazard models between two predefined groups, providing survival estimates for time-to-event datasets.

2.3 Identification of target genes and functional annotation

We performed the following two analytical steps to confirm the relationships between miRNAs and target genes. In the first step, correlations between gene and miRNA expression levels were assessed using Pearson’s, Spearman’s, and Kendall’s coefficients. This approach considered linear and non-linear correlations, enhancing the sensitivity for detecting the miRNA candidates’ potential target genes. Genes and miRNAs with at least one correlation coefficient < − 0.3 were considered. In the second step, 12 additional bioinformatic tools were used to predict interactions between miRNAs and their corresponding target genes. As previously described [58], only genes satisfying the following criteria were considered a target: (1) a correlation coefficient < − 0.3 in the first step, 2) an interaction supported by > 3 bioinformatic tools. The GeneCards database (58) was used to functionally annotate the target genes.

2.4 In vitro study

2.4.1 Cell culture, miRNA transfection, and irradiation

Fadu cells (American Type Culture Collection: HTB-43TM) were maintained in minimal essential medium supplemented with 10% fetal bovine serum and 1% antibiotics and maintained at 37°C in a humidified atmosphere containing 5% carbon dioxide. Cells were transfected with selected miR-4776-5p mimics and NC (mirVana miRNA mimics; Thermo Fisher Scientific) at a final concentration of 40 nM using Lipofectamine 3000 (Invitrogen) according to the manufacturer’s instructions and maintained until the study time points. Irradiation was delivered by 6-MV X-rays from a linear accelerator (Clinac iX; Varian Medical System) with a 6 Gy/min dose rate.

2.4.2 Quantitative real-time PCR

After transfection with the synthetic mimics, cells were collected at 24 h in Trizol reagent to extract their total RNA. Next, miRNAs were reverse transcribed using the miRCURY LNA RT kit to obtain complementary DNAs. Then, miR-4776-5p’s expression level was determined by quantitative real-time PCR using specifically designed primers (Applied Biosystems) and the miRCURY LNA SYBR Green PCR Kit (Applied Biosystems) on a CFX ConnectTM Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA). Its relative expression level was compared to the RNU6 endogenous control and normalized to cells transfected with scramble miRNA (NC group) using the 2^−ΔΔCt method.

2.4.3 Cell viability after RT

Fadu cells transfected with synthetic mimics were irradiated with different doses to test their intrinsic response to RT. Briefly, Fadu cells were plated in each well of 96-well plates at a density of 5000 cells per well in 200 µL of culture medium and maintained at 37°C. After 24 h, cells were transfected with synthetic mimics and incubated for 24 h. Cells were irradiated with 2 and 4 Gy and developed using Cell Counting Kit-8 (Biotools, Taiwan) on day 3 after RT. The amount of formazan dye in the surviving cells, which is directly proportional to the number of living cells, was determined by measuring the optical density at 450 nm of five independent experiments.

2.4.4 Colony formation assay

The transfected Fadu cells were trypsinized and suspended in 1× phosphate-buffered saline (PBS) before being exposed to radiation (0–6 Gy). The cells were inoculated into 6-well plates at different densities depending on the irradiation treatment’s potency ( 400–3200 cells/well). After 10 days, the cells were fixed and stained with crystal violet in 70% ethanol. The number of colonies, defined as clumps of > 50 cells, was counted. The survival fraction was calculated as the ratio of colonies in the treated group to the untreated group. Six wells were set up for each condition.

2.4.5 Immunohistochemistry staining

For γH2AX immunostaining, after 30 min, 1 h, 4 h, 8 h, and 24 h of radiation exposure, Fadu cells were fixed for 15 min at room temperature with 4% paraformaldehyde and washed twice with PBST (1× PBS with 0.1% Tween-20). After washing, cells were incubated with Permeabilization buffer (0.3% Triton X-100 in PBS) for 10 min at room temperature and then with blocking buffer (3% bovine serum albumin in PBS) for 1 h at room temperature. After washing, the slides were incubated with primary rabbit anti-γH2AX antibody (Merck) diluted in blocking buffer at 4°C overnight and then incubated for 30 min at room temperature with an anti-rabbit antibody coupled with fluorescein isothiocyanate (BD). After washing, the slides were mounted with a medium containing 4’,6-diamidino-2-phenylindole (Life Technologies) to stain their nuclei. Images were automatically acquired using an ImageXpress Micro Confocal System (Molecular Devices, San Jose, CA, USA). At least 250 nuclei were captured, and the number of γH2AX foci/nuclei was determined using the MetaXpress software (Molecular Devices).

2.5 In vivo study

To examine the miRNA’s effect on the tumor’s response to RT, we subcutaneously injected 8-week-old male mice (BALB/c nu/nu; National Science Council Animal Center, Taipei, Taiwan) with 3×10⁶ viable transfected Fadu cells in 100 µL of PBS. After implantation, the xenografts’ tumor volume was measured using a caliper according to the formula π/6 × (large diameter) × (small diameter)². Tumor-bearing mice received local irradiation at 13 Gy once their tumor volume reached 150 mm³. To assess the tumor’s response to irradiation, we continuously measured the tumor volume to determine its growth rate until it reached 1200 mm³. Our previous study described the irradiation protocol in detail (59). Briefly, tumor-bearing mice were anesthetized with a 1:1 mixture of ketamine (50 mg/kg; Merial Laboratoire de Toulouse, Toulouse, France) and xylazine (20 mg/kg; Bayer HealthCare Animal Health, Leverkusen, Germany) and restrained during irradiation. Their tumors were covered with a 1 cm bolus on the surface and irradiated with 6 MV X-rays from a linear accelerator with a 2–3 Gy/min dose rate. All animal experiments were performed with the approval of the Institutional Animal Care and Use Committee of Chang Gung Memorial Hospital (approval number: CGU110-071).

2.6 Statistical analyses of the in vivo and invitro studies

Statistical analyses used a Student’s t-test to compare two groups for each biological experiment. Results with a p-value < 0.05 were considered statistically significant.

3.1. Identify clinically radiosensitive miRNAs in patients with HNC

To identify a candidate miRNA acting as a radiosensitizer for HNC cells, we performed an integrative study combining a clinical cohort with bench data (Fig. 1). First, TCGA-HNSC data for 528 patients were obtained. Only 432 patients had their RT status recorded, which was “yes” for 294 patients and “no” for 138 patients (Table 1 and Supplemental Table 1). To focus on radiosensitizers only, patients who have received any other systemic therapy (e.g., chemotherapy or targeted therapy) were excluded. Of the 294 patients who had received RT, 128 had received RT alone.

Next, 2588 miRNAs were used as potential candidates. After differential expression (DE) analysis, 277 miRNAs showed a significant difference between tumor and adjacent normal tissue in these patients. Using the OS and progression-free interval (PFI) as endpoints in survival analysis, 12 miRNAs were significantly related to the disease progression of the patients with HNSC receiving RT alone. A hazard ratio <1 was used to select miRNAs associated with better prognosis (radiosensitizer). MiRNAs meeting this criterion in the subgroup of patients treated without RT were excluded. Finally, miRNA 4776-5p (miR-4776-5p) was identified as a candidate for further functional annotation and validation experiments. The Kaplan–Meier survival plot showed that mir-4776-5p expression was significantly associated with clinical prognosis in the HNSC-RT(+) group but not in the HNSC-RT(-) group, potentially indicating the prognostic role of mir-4776-5p was due to radiosensitivity rather than tumor behavior (Fig. 2).

Table 1 Basic characteristics of patients receiving RT only.

3.2 Identify the target genes and functions regulated by miR-4776-5p

To investigate the mechanism through which miR-4776-56 acts as a radiosensitizer, we systematically identified its target genes and their functions in a systematic approach (see the identification of targeted genes and functional annotation in the Material and Methods section for details). Briefly, the targeted genes negatively correlated with the miRNA’s expression level. The results were also confirmed by at least three target prediction tools that had been used in our previous studies (15,16). Sixteen genes were identified and functionally annotated (Supplemental Table 2): AP1M1, ATAD3B, CLEC11A, CMTM3, COLGALT1, FBX044, KDELR1, MCTS1, MRPL17, MTCH1, PARVB, PLOD1, PRAF2, RPS27L, SH2D2A, and VKORC1. Their functions relating to radiosensitivity, including the immune system, mitochondria, signal transduction, apoptosis, vascular endothelial growth factor (VEGF) pathways, cell proliferation, DNA damage response, and hypoxia, are summarized as a regulatory network in Fig. 3.

3.3 MiR-4776-5p suppresses DNA repair and sensitizes HNSC cells to ionizing radiation

To explore the effect of miR-4776-5p on Fadu cells’ DNA damage and repair efficiency, we examined the extent of DNA double-strand breaks (DSBs) induced by RT. H2AX phosphorylation is a well-known marker for assessing the formation of DSBs and following repairing kinetics. Therefore, we quantified the number of gH2AX foci at different time points after RT in cells transfected with miR-4776-5p or negative control (NC). As shown in Fig. 4, 2 Gy RT led to a remarkable increase in gH2AX foci 30 min post-RT in Fadu cells transfected with miR-4776-5p mimic or NC miRNA. The miR-4776-5p miRNA maintained the gH2AX foci number until 8 h post-RT compared to the NC miRNA, indicating inefficient DNA repair machinery. In addition, a clonogenic assay was performed following the transfection of Fadu cells with miR-4776-5p or NC miRNAs to evaluate the effect of miR-4776-5p overexpression on their radiosensitivity. The survival curve significantly decreased with increasing RT doses in cells transfected with miR-4776-5p compared to the NC miRNA (p < 0.001). These results suggested that miR-4776-5p enhanced the radiosensitivity of Fadu cells, which may involve the persistence of DNA repair and suppression of cell viability.

[Fig. 4 near here]

3.4 Tumor growth in response to miR-4776-5p overexpression and ionizing radiation

Increasing the miR-4776-5p level in Fadu cells significantly suppressed DSB repair and induced mitotic death. Therefore, we investigated this effect in an in vivo system to determine whether increased radiosensitivity is relevant for tumor growth after ionizing radiation. Specifically, Fadu cells were transfected with miR-4776-5p mimic or scramble NC for 24 h and then inoculated into immune-deficient BALB/C nude mice. Mice with Fadu-NC or Fadu-miR-4776-5p tumors were treated with 13 Gy RT when their tumor volume reached 150 mm³. MiR-4776-5p transfection did not affect the tumor growth rate from Fadu cells since it took nine days for tumors to grow to 600 mm³, the same as in the NC group. Treatment with ionizing radiation attenuated the growth of tumors in the NC group, which took 17 days to reach 600 mm³. However, ionizing radiation also greatly affected the growth of miR-4776-5p-transfected tumors, which took 19 days to reach 600 mm³ and remained the same size for up to 29 days. Compared to the non-RT group, the average tumor growth delay triggered by RT was eight days for the NC group and 20 days for the miR-4776-5p group (Fig. 5). These data again suggest that miR-4776-5p overexpression increases the radiosensitivity of HNSC cells.

HNC is one of the 10 most common cancers worldwide, with a five-year survival of about 40%, even with anti-cancer therapy (1, 17). RT is an important part of the definitive or adjuvant treatment for HNC. Resistance to RT, called radioresistance, is important in HNC treatment failure. MiRNAs are a group of small RNAs (smRNAs) 19–23 nucleotides long that regulate tumor cell growth. To date, several miRNAs have been associated with HNC diagnosis, prognosis, or therapy (18). Several miRNAs have also shown efficacy in regulating tumor radiosensitivity by modulating several pathways (19). However, the results of these studies are inconsistent between bench and clinical conditions, limiting their usefulness in the precision medicine era. Therefore, this study investigated a candidate miRNA that regulated tumor radiosensitivity in vitro and in vivo and predicted the prognosis of patients with HNC receiving RT. We identified miR-4776-5p as a prognostic biomarker in a clinical cohort of patients with HNC only receiving RT through an integrated bioinformatics approach and validated its regulation of radiosensitivity in both in vitro and in vivo studies using HNC tumor cells. Consistent with our findings, this miRNA had been previously reported in a miRNA-gene regulatory network for gastric cancer (20), suggesting that miR-4776-5p has strong potential as a novel radiosensitizer for improving the treatment outcomes of patients with HNC.

To understand the pathways regulated by miR-4775-5p, we first identified its target genes using the miRTarBase database and several bioinformatics tools for miRNA target prediction. Sixteen genes were identified: AP1M1, ATAD3B, CLEC11A, CMTM3, COLGALT1, FBX044, KDELR1, MCTS1, MRPL17, MTCH1, PARVB, PLOD1, PRAF2, RPS27L, SH2D2A, and VKORC1. AP1M1 is an intrinsic part of the clathrin adaptor AP-1 complex. Previous studies suggested that AP1M1 was involved in the progression of liver cancer due to hepatitis B infections (21) and identified it as a biomarker related to central nervous system (CNS) metastasis from breast cancer (22). ATAD3B is a mitochondrial membrane-bound ATPase belonging to the AAA domain-containing protein 3 ATPase family that has been associated with the progression and prognosis of various cancer types, including liver (23), breast (24), and CNS (25). Global proteome analysis of the mitochondria in Raje cells also identified ATAD3B as a potential biomarker of radioresistance (26). CLEC11A is a protein-coding gene that significantly participates in the tumor microenvironment and immune cell communication and can predict protein survival in laryngeal squamous cell carcinoma (LSCC) (27). CMTM3 was associated with cell growth and migration in oral squamous cell carcinoma (28) and pancreatic cancer (29) and has roles in the tumor microenvironment and cancer immunotherapy (30). COLGALT1 was identified as a biomarker for predicting prognosis and immune responses for kidney renal clear cell carcinoma (31). KDELR1 was involved in regulating T cell homeostasis (32) and correlated with the prognosis of glioma (33). MCTS1 was identified as an oncogene in various tumors, including HNSC (34), and correlated with immune cell infiltration (35). MRPL17 was identified as a crucial factor in oral carcinogenesis in an analysis of patients with tongue cancer (36). MTCH1 upregulation was associated with cell proliferation in hepatocellular carcinoma (37). The increasing presentation of MTCH1 neoantigen after ionizing radiation has also been noted (38). PARVB was proposed as a clinically useful biomarker for adjuvant tongue squamous cell carcinoma based on its ability to increase cell migration (39). PLOD1 belongs to the procollagen-lysine, 2-oxoglutarate 5-dioxygenase gene family, which has been associated with multiple cancers, and has a significant role in LSCC development (40). PRAF2 has been associated with the occurrence and progression of several malignant tumors, including esophageal, liver, and brain cancers (41–43). RPS27 encodes an MPS1 protein and has been reported to be involved DNA repair and regulating radiation sensitivity via the MDM2-p53 and MDM2-MRN-ATM axes (44, 45). SH2D2A encodes an adaptor protein thought to function in T-cell signal transduction, and was identified as a radiation response gene in irradiated primary human fibroblast cell lines (46).

To determine the mechanisms underlying miR-4776-5p acting as a radiosensitizer, we functionally annotated the 16 genes targeted by miR-4776-5p. Eleven functioned in the DNA damage response, apoptosis, cell proliferation, signal transduction, hypoxia, VEGF pathways, mitochondria, and the immune system. The DNA damage response and apoptosis are recognized as the traditional radiation mechanisms inhibiting tumor cell proliferation (47, 48). Increasing evidence shows the functional associations between signal transduction and cellular responses (49). Hypoxia is a common feature of the tumor microenvironment associated with RT resistance (50). VEGF knockdown enhanced radiosensitivity by inhibiting autophagy (51). Cellular organelles, particularly mitochondria, have been noted to mediate the radiation response in tumors by regulating many cellular processes involved in radioresistance (52). Recent data suggest that radiation kills the local tumor and inhibits the growth of distant metastatic lesions with immunomodulatory properties (the so-called abscopal effect) (53, 54). Therefore, these functions support the suitability of miR-4776-5p as a candidate for regulating radiosensitivity and the potential for further radiobiological research.

While numerous studies have investigated the role of miRNAs in modulating the radiosensitivity of HNCs, few present consistent results between bench and clinical conditions (55). Most previous studies investigated the expression changes of miRNAs in HNC cell lines in vitro, first using microarray detection to identify candidates. Few then validated their candidate miRNAs in clinical samples (56, 57). The recent revolution in high throughput next-generation sequencing methods, which have higher sensitivities than microarray, has led to the creation of several large sequencing databases, including TCGA, with vast amounts of sequencing data and large clinical sample sizes. To our knowledge, only two studies have investigated miRNAs related to the radiosensitivity of patients with HNC in these big databases using integrative bioinformatics approaches (13, 14). Using TCGA data, a five miRNA signature-based nomogram was proposed to predict the RT response of HNSC patients based only on an in silico data analysis (13). Also using the TCGA, Inoue et al. (14) screened human papillomavirus (HPV)-negative oropharyngeal squamous cell carcinoma (OPSC), identifying miRNA-130b as a potential biomarker for the radiosensitivity of HPV-negative OPSCs. However, these two studies had some limitations. First, patients receiving RT may also receive chemotherapy or targeted therapy. It is difficult to determine the change in prognosis due to each treatment. Second, their clinical results were not validated in bench studies confirming that the result was related to radiosensitivity. Therefore, in our study, we screened the miRNAs in patients only receiving RT and validated our in silico result with radiobiological studies in vitro and in vivo. In addition, we also validated our candidate miRNA in a clinical cohort with HNSC not receiving RT. The inconsistency between the RT-only and non-RT groups indicated that miR-4776-5p regulates the radiosensitivity and RT response instead of HNC progression.

The miR-4776-5p biological validation results showed its significant impact on DNA repair efficiency and the survival of HNC cells after irradiation. Quantification of γH2AX foci numbers showed that DSB resolution was significantly impacted in irradiated cells overexpressing miR-4776-5p. Cells overexpressing miR-4776-5p had more foci at 2.5 h after RT than cells treated with miR-NC and showed inefficient DSB repair kinetics in the 24 h after RT. Our results also showed that miR-4776-5p overexpression significantly impacted the survival of HNC cells after RT due to the unrepaired DSBs and failed cell division. Our in vivo study showed that miR-4776-5p overexpression did not affect the tumorigenesis of HNSC cells but enhanced tumor radiosensitivity based on the prolonged growth inhibition of tumor cells transfected with miR-4776-5p.

Acknowledgements

Not applicable.

Authors’ contributions

LYO interprets the results and writes the manuscript. WCC analyses the data. YCF and LYL curate and clean the data. SPC lays out and designs figures. TMH interprets the results and writes figure legends. CFH and CWC revise the final version of the manuscript.

Funding

This study was supported by grants from the National Science and Technology Council, Taiwan, R.O.C. (MOST 109-2628-E-039-001-MY3, NSTC 111-2622-E-039-004-, NSTC 111-2628-B-007-010-, NSTC 109-2314-B-007-008 -MY3); China Medical University, Taiwan, R.O.C. (CMU111-MF-72, CMU111-IP-04); China Medical University Hospital, Taiwan, R.O.C. (DMR-110-072, DMR-111-075, DMR-113-056); Chang Gung Memorial Hospital, Taiwan, R.O.C. (CMRPG3K1911, CMRPG3M0681-2, CMRPG3L1381-2).

Availability of data and materials

All data are available in the manuscript and they are exhibited in figures and tables.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209–49.
Lavaf A, Genden EM, Cesaretti JA, Packer S, Kao J. Adjuvant radiotherapy improves overall survival for patients with lymph node-positive head and neck squamous cell carcinoma. Cancer: Interdisciplinary International Journal of the American Cancer Society. 2008;112:535–43.
Bernier J, Cooper JS, Pajak T, Van Glabbeke M, Bourhis J, Forastiere A et al., Defining risk levels in locally advanced head and neck cancers: a comparative analysis of concurrent postoperative radiation plus chemotherapy trials of the EORTC (# 22931) and RTOG (# 9501). Head & Neck: Journal for the Sciences and Specialties of the Head and Neck. 2005;27:843 – 50
Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. cell. 2004;116:281 – 97.
MacFarlane L-A, Murphy R. MicroRNA: biogenesis, function and role in cancer. Curr Genom. 2010;11:537–61.
Rupaimoole R, Slack FJ. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases. Nat Rev Drug Discovery. 2017;16:203–22.
Liu C, Kelnar K, Liu B, Chen X, Calhoun-Davis T, Li H, et al. The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44. Nat Med. 2011;17:211–5.
Gougelet A, Sartor C, Bachelot L, Godard C, Marchiol C, Renault G, et al. Antitumour activity of an inhibitor of miR-34a in liver cancer with β-catenin-mutations. Gut. 2016;65:1024–34.
Trang P, Wiggins JF, Daige CL, Cho C, Omotola M, Brown D, et al. Systemic delivery of tumor suppressor microRNA mimics using a neutral lipid emulsion inhibits lung tumors in mice. Mol Ther. 2011;19:1116–22.
Czochor JR, Glazer PM. microRNAs in cancer cell response to ionizing radiation. Antioxid Redox Signal. 2014;21:293–312.
Mueller A-K, Lindner K, Hummel R, Haier J, Watson DI, Hussey DJ. MicroRNAs and their impact on radiotherapy for cancer. Radiat Res. 2016;185:668–77.
Mirestean CC, Iancu RI, Iancu DPT. Micro-RNAs, the Cornerstones of the Future of Radiobiology in Head and Neck Cancers? Curr Oncol. 2022;29:816–33.
Chen L, Wen Y, Zhang J, Sun W, Lui VWY, Wei Y, et al. Prediction of radiotherapy response with a 5-microRNA signature-based nomogram in head and neck squamous cell carcinoma. Cancer Med. 2018;7:726–35.
Inoue H, Hirasaki M, Kogashiwa Y, Kuba K, Ebihara Y, Nakahira M, et al. Predicting the radiosensitivity of HPV-negative oropharyngeal squamous cell carcinoma using miR-130b. Acta Otolaryngol. 2021;141:640–5.
Liu SH, Shen PC, Chen CY, Hsu AN, Cho YC, Lai YL, et al. DriverDBv3: a multi-omics database for cancer driver gene research. Nucleic Acids Res. 2020;48:D863–D70.
Lai YL, Liu CH, Wang SC, Huang SP, Cho YC, Bao BY et al. Identification of a Steroid Hormone-Associated Gene Signature Predicting the Prognosis of Prostate Cancer through an Integrative Bioinformatics Analysis. Cancers (Basel) 2022;14.
Brockstein B, Haraf DJ, Rademaker AW, Kies MS, Stenson KM, Rosen F, et al. Patterns of failure, prognostic factors and survival in locoregionally advanced head and neck cancer treated with concomitant chemoradiotherapy: a 9-year, 337-patient, multi-institutional experience. Ann Oncol. 2004;15:1179–86.
Thomaidou AC, Batsaki P, Adamaki M, Goulielmaki M, Baxevanis CN, Zoumpourlis V et al. Promising Biomarkers in Head and Neck Cancer: The Most Clinically Important miRNAs. Int J Mol Sci 2022;23.
Zhao L, Bode AM, Cao Y, Dong Z. Regulatory mechanisms and clinical perspectives of miRNA in tumor radiosensitivity. Carcinogenesis. 2012;33:2220–7.
Zhu T, Lou Q, Shi Z, Chen G. Identification of key miRNA-gene pairs in gastric cancer through integrated analysis of mRNA and miRNA microarray. Am J Transl Res. 2021;13:253–69.
Kou Y, Yan X, Liu Q, Wei X, Zhang B, Li X, et al. HBV upregulates AP-1 complex subunit mu-1 expression via the JNK pathway to promote proliferation of liver cancer cells. Oncol Lett. 2019;18:456–64.
Rojas LK, Trilla-Fuertes L, Gamez-Pozo A, Chiva C, Sepulveda J, Manso L, et al. Proteomics characterisation of central nervous system metastasis biomarkers in triple negative breast cancer. Ecancermedicalscience. 2019;13:891.
Liu X, Li G, Ai L, Ye Q, Yu T, Yang B. Prognostic value of ATAD3 gene cluster expression in hepatocellular carcinoma. Oncol Lett. 2019;18:1304–10.
Ovaska K, Matarese F, Grote K, Charapitsa I, Cervera A, Liu C, et al. Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer. PLoS Comput Biol. 2013;9:e1003100.
Hubstenberger A, Labourdette G, Baudier J, Rousseau D. ATAD 3A and ATAD 3B are distal 1p-located genes differentially expressed in human glioma cell lines and present in vitro anti-oncogenic and chemoresistant properties. Exp Cell Res. 2008;314:2870–83.
Jiang Y, Liu X, Fang X, Wang X. Proteomic analysis of mitochondria in Raji cells following exposure to radiation: implications for radiotherapy response. Protein Pept Lett. 2009;16:1350–9.
Yan L, Hu C, Ji Y, Zou L, Zhao Y, Zhu Y, et al. Identification of Significant Secreted or Membrane-Located Proteins in Laryngeal Squamous Cell Carcinoma. J Immunol Res. 2022;2022:9089397.
Zhang H, Zhang J, Nan X, Li X, Qu J, Hong Y, et al. CMTM3 inhibits cell growth and migration and predicts favorable survival in oral squamous cell carcinoma. Tumour Biol. 2015;36:7849–58.
Zhou Z, Ma Z, Li Z, Zhuang H, Liu C, Gong Y, et al. CMTM3 Overexpression Predicts Poor Survival and Promotes Proliferation and Migration in Pancreatic Cancer. J Cancer. 2021;12:5797–806.
Shen Q, Cong Z, Zhou Y, Teng Y, Gao J, Tang W. CMTM3 as a Potential New Immune Checkpoint Regulator. J Oncol. 2022;2022:2103515.
Liu S, Yu Y, Wang Y, Zhu B, Han B. COLGALT1 is a potential biomarker for predicting prognosis and immune responses for kidney renal clear cell carcinoma and its mechanisms of ceRNA networks. Eur J Med Res. 2022;27:122.
Kamimura D, Katsunuma K, Arima Y, Atsumi T, Jiang JJ, Bando H, et al. KDEL receptor 1 regulates T-cell homeostasis via PP1 that is a key phosphatase for ISR. Nat Commun. 2015;6:7474.
Yuan Y, Yang B, Qi Z, Han Z, Cai J, Song J. KDELR1 Is an Independent Prognostic Predictor and Correlates With Immunity in Glioma. Front Oncol. 2022;12:783721.
Zhu J, Wang X, Shao Z, Sun W, Wu T. Prognostic value of malignant T cell-amplified sequence 1 in head and neck squamous cell carcinoma. Biomark Med. 2021;15:1623–39.
Deng M, Xiong C, He ZK, Bin Q, Song JZ, Li W, et al. MCTS1 as a Novel Prognostic Biomarker and Its Correlation With Immune Infiltrates in Breast Cancer. Front Genet. 2022;13:825901.
Khowal S, Naqvi SH, Monga S, Jain SK, Wajid S. Assessment of cellular and serum proteome from tongue squamous cell carcinoma patient lacking addictive proclivities for tobacco, betel nut, and alcohol: Case study. J Cell Biochem. 2018;119:5186–221.
Chen G, Mo S, Yuan D. Upregulation Mitochondrial Carrier 1 (MTCH1) Is Associated with Cell Proliferation, Invasion, and Migration of Liver Hepatocellular Carcinoma. Biomed Res Int. 2021;2021:9911784.
Tailor A, Estephan H, Parker R, Woodhouse I, Abdulghani M, Nicastri A, et al. Ionizing Radiation Drives Key Regulators of Antigen Presentation and a Global Expansion of the Immunopeptidome. Mol Cell Proteomics. 2022;21:100410.
Eslami A, Miyaguchi K, Mogushi K, Watanabe H, Okada N, Shibuya H, et al. PARVB overexpression increases cell migration capability and defines high risk for endophytic growth and metastasis in tongue squamous cell carcinoma. Br J Cancer. 2015;112:338–44.
Wang J, Liu D, Gu Y, Zhou H, Li H, Shen X, et al. Potential prognostic markers and significant lncRNA-mRNA co-expression pairs in laryngeal squamous cell carcinoma. Open Life Sci. 2021;16:544–57.
Qian Z, Wei B, Zhou Y, Wang Q, Wang J, Sun Y, et al. PRAF2 overexpression predicts poor prognosis and promotes tumorigenesis in esophageal squamous cell carcinoma. BMC Cancer. 2019;19:585.
Wang CH, Liu LL, Liao DZ, Zhang MF, Fu J, Lu SX, et al. PRAF2 expression indicates unfavorable clinical outcome in hepatocellular carcinoma. Cancer Manag Res. 2018;10:2241–8.
Shimada K, Murase T, Matsue K, Okamoto M, Ichikawa N, Tsukamoto N, et al. Central nervous system involvement in intravascular large B-cell lymphoma: a retrospective analysis of 109 patients. Cancer Sci. 2010;101:1480–6.
Sun S, He H, Ma Y, Xu J, Chen G, Sun Y, et al. Inactivation of ribosomal protein S27-like impairs DNA interstrand cross-link repair by destabilization of FANCD2 and FANCI. Cell Death Dis. 2020;11:852.
Zhao Y, Tan M, Liu X, Xiong X, Sun Y. Inactivation of ribosomal protein S27-like confers radiosensitivity via the Mdm2-p53 and Mdm2-MRN-ATM axes. Cell Death Dis. 2018;9:145.
Kis E, Szatmari T, Keszei M, Farkas R, Esik O, Lumniczky K, et al. Microarray analysis of radiation response genes in primary human fibroblasts. Int J Radiat Oncol Biol Phys. 2006;66:1506–14.
Willers H, Gheorghiu L, Liu Q, Efstathiou JA, Wirth LJ, Krause M, et al. DNA Damage Response Assessments in Human Tumor Samples Provide Functional Biomarkers of Radiosensitivity. Semin Radiat Oncol. 2015;25:237–50.
Little JB. Cellular effects of ionizing radiation. N Engl J Med. 1968;278:369 – 76 concl.
Schmidt-Ullrich RK, Dent P, Grant S, Mikkelsen RB, Valerie K. Signal transduction and cellular radiation responses. Radiat Res. 2000;153:245–57.
Rockwell S, Dobrucki IT, Kim EY, Marrison ST, Vu VT. Hypoxia and radiation therapy: past history, ongoing research, and future promise. Curr Mol Med. 2009;9:442–58.
Chen L, Lin G, Chen K, Wan F, Liang R, Sun Y, et al. VEGF knockdown enhances radiosensitivity of nasopharyngeal carcinoma by inhibiting autophagy through the activation of mTOR pathway. Sci Rep. 2020;10:16328.
McCann E, O'Sullivan J, Marcone S. Targeting cancer-cell mitochondria and metabolism to improve radiotherapy response. Transl Oncol. 2021;14:100905.
Friedman EJ. Immune modulation by ionizing radiation and its implications for cancer immunotherapy. Curr Pharm Des. 2002;8:1765–80.
Hiniker SM, Chen DS, Knox SJ. Abscopal effect in a patient with melanoma. N Engl J Med 2012;366:2035; author reply – 6.
Ahmad P, Sana J, Slavik M, Slampa P, Smilek P, Slaby O. MicroRNAs Involvement in Radioresistance of Head and Neck Cancer. Dis Markers. 2017;2017:8245345.
de Jong MC, Ten Hoeve JJ, Grenman R, Wessels LF, Kerkhoven R, Te Riele H, et al. Pretreatment microRNA Expression Impacting on Epithelial-to-Mesenchymal Transition Predicts Intrinsic Radiosensitivity in Head and Neck Cancer Cell Lines and Patients. Clin Cancer Res. 2015;21:5630–8.
Liu N, Boohaker RJ, Jiang C, Boohaker JR, Xu B. A radiosensitivity MiRNA signature validated by the TCGA database for head and neck squamous cell carcinomas. Oncotarget. 2015;6:34649–57.
Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr Protoc Bioinformatics. 2016;54(1 30):1–1.
Tsai CS, Chen FH, Wang CC, Huang HL, Jung SM, Wu CJ, et al. Macrophages from irradiated tumors express higher levels of iNOS, arginase-I and COX-2, and promote tumor growth. Int J Radiat Oncol Biol Phys. 2007;68:499–507.

No competing interests reported.

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MicroRNA-4776-5p acts as a radiosensitizer and predicts the prognosis of patients with head and neck cancer receiving radiotherapy

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Abstract

Background

Results

Conclusion

Figures

1. Introduction

2. Materials and Methods

2.1 Data collection and processing

2.2 DE and survival analyses

2.3 Identification of target genes and functional annotation

2.4 In vitro study

2.4.1 Cell culture, miRNA transfection, and irradiation

2.4.2 Quantitative real-time PCR

2.4.3 Cell viability after RT

2.4.4 Colony formation assay

2.4.5 Immunohistochemistry staining

2.5 In vivo study

2.6 Statistical analyses of the in vivo and invitro studies

3. Results

3.1. Identify clinically radiosensitive miRNAs in patients with HNC

3.2 Identify the target genes and functions regulated by miR-4776-5p

3.3 MiR-4776-5p suppresses DNA repair and sensitizes HNSC cells to ionizing radiation

3.4 Tumor growth in response to miR-4776-5p overexpression and ionizing radiation

4. Discussion

Declarations

References

Additional Declarations

Supplementary Files

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