SERPINB7, TMEM158, and SERPINE1 signature as predictors of non-small-cell lung cancer prognosis after intravenous vitamin C treatment

SERPINB7, TMEM158, and SERPINE1 signature as predictors of non-small-cell lung cancer prognosis after intravenous vitamin C treatment | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article SERPINB7, TMEM158, and SERPINE1 signature as predictors of non-small-cell lung cancer prognosis after intravenous vitamin C treatment Junwen Ou, Qiulin Liao, Yanping Du, Wentao Xi, Qiong Meng, Kexin Li, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1472206/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Vitamin C (VitC) has been proposed as a potential anti-cancer agent for prolonging progression-free survival (PFS) and overall survival (OS) in non-small-cell lung cancer (NSCLC) patients. However, VitC has only been shown to be effective for some patients, and the mechanism in those who have benefitted from it remains unknown. We aimed to explore whether gene expression could predict IVC benefit for patients with NSCLC. Methods: H1299 and PC9 cells were treated with VitC and high-throughput sequencing was used for screening differential genes. Data from the Kaplan-Meier Plotter and the Human Protein Atlas databases were used for analysis of patient prognoses. In a retrospective study, 153 NSCLC patients from our Cancer Center were selected and divided into a control group (n = 81) and VitC group (n = 72) for immunohistochemical staining and prognosis analysis. Results: As a result, ZNF507, DLX4, and DDIT4 were found to be upregulated, and SERPINB7, TMEM158 and SERPINE1 downregulated in NSCLC cell lines following VitC treatment. Combined patient data from the cohort analysis and online databases revealed that the downregulated genes, but not upregulated genes, presented an unfavorable prognostic predictor of OS in NSCLC patients. Further analysis showed that the combined three genes were more efficient at predicting survival than individually (AUC=0.77, 95%CI, 0.63-0.90). Moreover, high expression of SERPINB7, TMEM158, and SERPINE1 in resected tumour- tissues before VitC treatment was found to be associated with prolonged OS in patients with NSCLC who were treated with VitC. Conclusion: Overall, these data revealed that SERPINB7, TMEM158, and SERPINE1 formed a novel NSCLC prognosis gene set and could serve as a potential therapeutic target as well as predictive factor for VitC treatment in patients with NSCLC. Trial registration: Retrospectively registered (No: 2/2021-PRE-48) on July 13, 2021. Intravenous vitamin C non-small cell lung cancer predictor/prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Lung cancer remains the most common cancer type and the leading cause of cancer mortality in China [ 1 ], accounting for 17.9% of newly diagnosed cancer cases and 23.8% of all deaths [ 2 ]. Nearly 85% of lung cancers are non-small-cell lung cancer (NSCLC), which has a 5-year survival rate of less than 20% [ 3 ]. The majority of NSCLC patients were found to have advanced disease [ 4 ]. As cancer is a heterogeneous disease, the use of personalized medicine for individual patients has become the new focus for successfully implemented anticancer therapies. Vitamin C (VitC), as a natural compound of low toxicity and high tolerance, can decrease the proliferation of lung cancer cell lines via causing cell cycle arrest and promoting apoptosis [ 5 – 8 ]. Clinical studies [ 9 , 10 ] have suggested that when concomitant with chemotherapy, intravenous VitC (IVC) can enhance the efficacy and reduce the toxicity of chemotherapy. This was also demonstrated in our previous retrospective clinical study involving gemcitabine and carboplatin treatment in breast cancer patients, which showed an increased response rate of patients to chemotherapy drugs and prolonged progression-free survival (PFS) and overall survival (OS) (1g/kg.d, every other day, 25 treatments) [ 11 ]. A separate prospective clinical study showed that IVC (1g/kg.d, three times a week, 25 treatments) can significantly prolong PFS and OS, as well as moderate cancer-related inflammation in advanced NSCLC patients [ 12 ]. However, cancer is a chronic disease with high heterogeneity [ 13 ], and as such VitC should not be regarded with a ‘one-size-fits-all’ approach in cancer treatment [ 5 ]. We found that the therapeutic effect of IVC varied greatly among patients with advanced NSCLC [ 12 ]. Using the RECIST 1.1 criteria, some patients were found to have a partial response after 25 IVC treatments, with 5 patients even surviving for more than 5 years, whereas some patients had progressive disease [ 12 ]. We speculate that IVC treatments work only for some people with NSCLC. Thus, exploring biomarkers for identifying patients who may benefit from IVC will allow therapeutic strategies to be designed more accurately and efficiently. In this study, potential VitC-regulated genes were first screened from NSCLC cell lines through high-throughput sequencing. Through analysis of pathological specimens and clinical data of such genes in NSCLC patients receiving VitC treatment, a total of 3 genes (SERPINB7, TMEM158, and SERPINE1) were identified as not only a novel NSCLC prognosis gene set, but also as serving as a potential therapeutic target and predictive factor for VitC treatment in patients with NSCLC. This may provide a feasible method for selecting the most appropriate NSCLC patients for VitC treatment. Materials And Methods Cell culture and RNA-seq The human NSCLC cell lines H1299 (CRL-5803) and PC9 (H086) were purchased from ATCC and cultured in RPMI1640 medium supplemented with 10% foetal bovine serum and 1% penicillin and streptomycin. H1299 and PC9 cells were exposed to VitC (0.5mM and 1mM) for 24 hours and then used for RNA-seq analysis. Total RNA was extracted from the indicated cells using TRIzol reagent (Invitrogen, AM9738), and the RNA quantity and quality were measured using a NanoDrop ND-1000. Libraries were constructed according to standard Illumina protocols. The quality of the RNA and complementary DNA was monitored using an Agilent Bioanalyzer 2100, and sequencing was performed on an Illumina HiSeq 4000 by KangChen Biotech Company (Shanghai). Online database Clinical data relating to human NSCLC patients, including OS and PFS, was obtained from the Kaplan-Meier Plotter (K-M Plotter) and the Human Protein Atlas (HPA) databases. The survival studies from the K-M Plotter were evaluated according to the web tool developer’s instructions ( http://kmplot.com/analysis/ ) as previously described [ 14 ]. Briefly, the gene probes of the target gene were selected from the K-M Plotter database as the only JetSet best probe set, which was then used to create Kaplan-Meier survival curves to determine the correlation between their expression and patient survival in NSCLC by using the median setting. The survival studies of patients from the HPA database were performed according to the instructions as previously described [ 15 ]. Study population Clinical samples were obtained from patients with pathologically confirmed NSCLC at the Cancer Center at Clifford Hospital of Jinan University in Guangzhou, China. Subjects were enrolled between May 2016 and April 2021 and were randomly selected for survival analysis. The inclusion criteria were as follows: 1) histologically confirmed NSCLC; 2) tissue sections available for immunohistochemical staining; 3) confirmation of recurrent and/or metastatic NSCLC based on at least two imaging technologies (e.g., enhanced computed tomography (CT) scan); 4) availability of complete medical records and precise follow-up data; and 5) treatment with anticancer therapy regimens such as surgery, radiation, chemotherapy, targeted therapy and/or immunotherapy. All subjects were divided into two groups, the control group (N = 81) and the VitC group (N = 72). The control group comprised patients who only received general anticancer therapy regimens, whereas in the VitC group, patients received anticancer therapy regimens along with IVC treatment (1 g/kg.d, three times a week, 15 to 30 treatments in total according to the patient’s condition). Each millilitre of VitC contained 3 g sodium VitC and water for injection, with the pH adjusted to 6.5-8.0 with sodium bicarbonate. VitC was infused for 120 min with 900 mmol/L osmotic pressure during the same period. The patients receiving IVC treatment also fulfilled the above 1) ~ 5) inclusion criteria. A range of demographic and clinicopathological data, including sex, age, tumour characteristics, and TNM stage, were collected on the study subjects. Specifically, data was gathered on tumour number and size; circular protein CEA, CF21-1, SCC level; and the presence or absence of pleural invasion. For this study, OS was defined as the duration from enrollment to death from any cause. For the patients alive, OS was censored at the last contact date. PFS was defined as the duration from enrollment to first recurrence. For the patients alive and recurrence-free, PFS was censored at the last contact date. All patients provided written informed consent. All samples were anonymously coded in accordance with local ethical guidelines (as requested by the Declaration of Helsinki) with written informed consent and a protocol approved by the Ethics Committee of the Clifford Hospital affiliated to Jinan University [No: 2/2021-PRE-48]. Information regarding the most recent follow-up and survival status was collected for all patients until April 30, 2021. Immunohistochemistry staining The streptavidin-peroxidase method was used for immunohistochemistry (IHC). All of the immunohistochemical reagents were purchased from SIGMA and INVITROGEN (SERPINB7: SIGMA, DA-21008; SERPINE1: INVITROGEN, PA5-90025; TMEM158: SIGMA, DA-21010; DLX4: SIGMA, DA-21003; DDIT4: SIGMA, DA-21004; ZNF507: SIGMA, DA-21009). The primary antibodies, rabbit anti-human polyclonal antibodies, were used at a working concentration of 1:50. The detection methods were carried out strictly according to the kit instructions. Known positive sections were used as a positive control, and sections treated with PBS instead of primary antibody were used as a negative control. Brown granules in the cytoplasm of cells defined positive staining. The analysis was performed by two independent observers who were blinded to the patient information. Any disagreements were discussed to reach a mutual consensus or referred to a third observer if needed. To quantify the density of the expression of the above genes in NSCLC, InForm 2.0.1 image analysis software was used. Patients were divided into high and low expression groups according to the median expression of their genes. In the combined expression pattern analysis model, a high pattern meant that all 3 genes included in the analysis belonged to the high expression group; a low pattern meant that all 3 genes belonged to the low expression group; and a medium pattern encompassed the remaining cases. Quantification and statistical analysis Cumulative survival time was calculated by the Kaplan-Meier method and the log-rank test. Univariate and multivariate analyses were performed using the Cox proportional hazard regression model to identify the prognostic factors for OS and PFS. Time-dependent receiver operating characteristic (ROC) curve analysis was also used to confirm the predictive survival performance of a multifactor signature. The area under the ROC curve (AUC) was calculated to evaluate the predictive accuracy of each marker for estimating survival. Significance was defined as P < 0.05. IBM SPSS statistics software and GraphPad Prism were used for all statistical analyses. Results IVC improved survival time of NSCLC patients In this retrospective study, a total of 153 NSCLC patients from the two groups were included. The control group consisted of 81 NSCLC patients who received anticancer therapy regimens but no IVC treatment, while the VitC group included 72 NSCLC patients who received IVC therapy in addition to anticancer therapy regimens. For each group, the patients’ baseline demographic and clinicopathological features are shown in Table 1 . The subjects enrolled in the VitC group were matched with the patients in the control by patient age, gender, and baseline tumour- characteristics. Table 1 Patient Characteristics Characteristics Control group (N = 81) VitC group (N = 72) P -value Age, yr Median 64 59 0.45 Range 39–85 27–88 Gender Male 55 49 0.99 Female 26 23 Tumour- number Single 56 46 0.50 Multiple 25 26 Tumour- size ≤ 5cm 21 32 0.17 > 5cm 60 40 TNM stage I-II 30 34 0.25 III-IV 51 38 Pleural invasion Presence 22 14 0.34 Absence 59 58 CF21-1 Median 4.5 3.65 0.49 Range 1.26–43.93 1.09–65.1 SCC Median 1.33 1.44 0.28 Range 0.24-5 0.32–17.72 CEA Median 4.46 4.22 0.26 Range 0.99–70.27 1.06–10668 All patients in the study were followed up until April 2021. In total, 48 patients survived and 33 patients died in the control group, while in the VitC group 53 patients survived and 19 patients died ( Supplementary Fig. 1 ). The median OS in the VitC group was 59.2 months, which was significantly longer than that of the control group, which had a median OS of 25.6 months ( Supplementary Fig. 2, P = 0.022). VitC-regulated genes in cell lines RNA-seq data showed that as compared to the control, 48 genes were upregulated and 43 genes were downregulated in H1299 cells treated with VitC, while 641 genes were upregulated and 398 genes were downregulated in VitC-treated PC9 cells (Fig. 1 a). A Venn diagram showed that 3 genes (ZNF507, DLX4, and DDIT4) were upregulated in both cell lines following treatment with VitC, whereas 3 genes (SERPINB7, TMEM158, and SERPINE1) were downregulated (Fig. 1 b). VitC-regulated genes related to OS and PFS from online database To uncover the clinical significance of the potential VitC treatment target genes, the K-M Plotter was used and a prognosis analysis was performed. The resulting data showed that the expression levels of SERPINB7, TMEM158, and SERPINE1 were negatively correlated with OS in NSCLC patients (Fig. 2 a-c), and that SERPINB7 and TMEM158, but not SERPINE1, were negatively correlated with PFS (Fig. 2 d-f). Next, an identical prognostic analysis was performed with ZNF507, DLX4, and DDIT4 in the K-M Plotter. The data showed that ZNF507 was positively correlated with the OS of patients with NSCLC ( Supplementary Fig. 3a ), while DLX4 and DDIT4 were negatively ( Supplementary Fig. 3b-c ). In the PFS analysis, DLX4 was found to be negatively correlated with PFS, while no correlation was found with either ZNF507 or DDIT4 ( Supplementary Fig. 3d-f ). Clinical and gene expression data from the HPA was also used to perform an analysis of OS. The data showed that SERPINB7, TMEM158, and SERPINE1 were negatively correlated with OS in NSCLC patients (Fig. 3 a-c), which was consistent with the K-M Plotter analysis. However, ZNF507, DLX4, and DDIT4 were inconsistent with the K-M Plotter analysis (ZNF507, no significance; DLX4, positively; DDIT4, negatively; Supplementary Fig. 4 ). VitC-regulated genes from study population To further explore the prognostic significance of VitC-regulated genes, samples from the cohort of NSCLC patients was used for immunohistochemical staining and prognosis analysis. Representative images of high and low expressions of SERPINB7 (cut off of SERPINB7 is 15%; Fig. 4 a), TMEM158 (cut off of TMEM158 is 70%; Fig. 4 d), and SERPINE1 (cut off of SERPINE1 is 85%; Fig. 4 g) are shown in tissue sections. In the control group, patients were further divided into two subgroups according to the median value of the above genes. The data showed that patients with low expression of SERPINB7 (Fig. 4 b), TMEM158 ( Fig. 4 e), and SERPINE1 ( Fig. 4 h) were associated with increased OS. SERPINE1 (Fig. 4 i) was associated with increased PFS, but not in SERPINB7(Fig. 4 c) and TMEM158 (Fig. 4 f). Next, patients were divided into “low”, “medium,” and “high” groups according to the median values of the combined expression patterns of the genes. The low pattern patients were found to experience longer OS (Fig. 4 j) and PFS (Fig. 4 k) than the high pattern patients. Patients with a medium pattern had similar time to low pattern. Multivariate analysis revealed that a low pattern was an independent prognostic factor for OS in patients with NSCLC (Table 2 ). The combination of SERPINB7, TMEM158, and SERPINE1 showed improved prognostic stratification of NSCLC survival compared to that of any of the three genes individually (Table 2 ). The expression levels of DDIT4, DLX4, and ZNF507 ( Supplementary Fig. 5a, 5d, 5g ) were also quantified and their impact on patient survival further analysed. Ultimately, no correlation was found between the expression levels of DDIT4, DLX4, or ZNF507 with OS ( Supplementary Fig. 5b, 5e, 5h ) and PFS ( Supplementary Fig. 5c, 5f, 5i ). Table 2 Univariate and multivariate analyses of variables associated with survival and recurrence Variables OS PFS Univariate P Multivariate Univariate P Multivariate HR 95% CI P HR 95% CI P Sex (male vs. female) 0.025 NA 0.256 Age (high vs. low) 0.094 0.086 TNM stage (I-II vs. III-IV) 0.0001 8.97 3.05–208.32 0.003 < 0.0001 NA Tumour size (high vs. low) 0.010 NA 0.020 NA Tumour number (single vs. multiple) 0.130 0.189 Pleural invasion (absent vs. present) 0.064 0.028 NA CF21-1 (high vs. low) 0.109 0.224 SCC (high vs. low) 0.161 0.087 CEA (high vs. low) 0.645 0.583 TMEM158 (low vs. high) 0.046 NA 0.080 SERPINB7 (low vs. high) 0.033 NA 0.173 SERPINE1 (low vs. high) 0.009 NA 0.002 NA Signature (low vs. medium vs. high) < 0.0001 9.77 2.55–59.31 0.002 0.003 NA Note: The Cox proportional hazards regression model was used. Variables that were associated with OS or PFS in the univariate analysis were adopted as covariates in the multivariate analysis and entered into the equation by using the forward likelihood ratio method. Patients with NSCLC in the VitC group were further enrolled for survival analysis. Pathological samples obtained prior to VitC treatment were further divided into two subgroups according to the median values of SERPINB7, TMEM158, and SERPINE1, respectively. The data showed longer OS in patients with high levels of SERPINB7 (59 months vs. 9 months, P = 0.039; Fig. 5 a), TMEM158 (59 months vs. 10 months, P = 0.011; Fig. 5 b), and SERPINE1 (59 months vs. 29 months, P = 0.005; Fig. 5 c), but not longer PFS (Fig. 5 d-f). However, DDIT4, DLX4, and ZNF507 were not found to be associated with OS or PFS ( Supplementary Fig. 6 ). As was done in the control group, patients in the VitC group were also divided into “low”, “medium” and “high” groups according to the median values of the combined expression patterns of the genes. High pattern patients were found to experience longer OS (median OS: 59 months vs. 13 months, P = 0.0034, Fig. 5 g), but not in PFS (Fig. 5 h) than low pattern patients. Further analysis revealed a larger AUC for the combined signature than SERPINB7, TMEM158, or SERPINE1 individually in predicting the OS (SERPINB7: AUC = 0.57, P = 0.29, 95% CI, 0.44–0.71; TMEM158: AUC = 0.58, P = 0.24, 95% CI, 0.45–0.71; SERPINE1: AUC = 0.59, P = 0.19, 95% CI, 0.46–0.72; The combination: AUC = 0.77, P = 0.0015, 95% CI, 0.63–0.90) and PFS (SERPINB7: AUC = 0.59, P = 0.16, 95% CI, 0.47–0.72; TMEM158: AUC = 0.54, P = 0.52, 95% CI, 0.41–0.67; SERPINE1: AUC = 0 .58, P = 0.26, 95% CI, 0.44–0.71; The combination: AUC = 0.76, P = 0.0014, 95% CI, 0.62–0.90) of IVC treated patients (Fig. 5 i, 5 j). In this retrospective study, OS was found to be significantly prolonged in the IVC group compared to the control group. Analysis of combined patient data from an online database and the NSCLC cohort analysis revealed that patients without IVC treatment and with low expression of SERPINB7, TMEM158, and SERPINE1 were associated with increased OS. However, patients in the IVC group with high expression of SERPINB7, TMEM158, and SERPINE1 in tumour tissues before IVC treatment were associated with prolonged OS (Fig. 6 ). Discussion Clinical studies have suggested that IVC can increase efficacy and reduce toxic side effects from chemotherapy when used in conjunction with chemotherapy. In a phase II study, chemical therapy (IV carboplatin and IV paclitaxel) coupled with IVC showed a 28.6% (4 out of the 14 patients) partial response (PR) in advanced-stage NSCLC patients [ 10 ], indicating the potential efficacy of IVC in NSCLC therapy. Our previous prospective clinical study found that the combination of high concentration of IVC and hyperthermia markedly improved PFS and OS in patients with stage III-IV NSCLC after a median follow-up of 24 months [ 12 ]. In addition, quality of life (QoL) was significantly increased in the VitC group despite the advanced stage of disease. The 3-month disease control rate after treatment was 42.9% in the VitC group and 16.7% in the control group (P < 0.05) [ 12 , 16 ]. Overall, IVC can not only enhance chemotherapy but also hyperthermia therapeutic effect in advanced NSCLC patients. IVC can selectively kill cancer cells by multiple targets and mechanisms, including generation of a large number of hydrogen peroxide (H2O2); activating TETs as a cofactor and leading to enhanced DNA demethylation and hydroxylmethylation; and downregulating the expression level of HIF1α [ 17 – 19 ]. A growing number of discoveries about VitC in the treatment of cancer will identify more potential therapeutic targets. This study showed that VitC regulated the expression of SERPINB7, TMEM158, and SERPINE1, which were associated with OS of NSCLC patients. Thus far, only a few studies have explored the relationship between SERPINB7 and cancer. In one study, Bianconi [ 20 ] showed that SERPINB7 is a predictor of poor gemcitabine treatment effects in pancreatic cancer. In other research, Chou [ 21 ] demonstrated the function of SERPINB7 in suppressing the invasiveness and motility of NSCLC cells. However, the mechanism of SerpinB7 remains unknown. SERPINE1 gene encoded plasminogen activator inhibitor 1 (PAI-1) [ 22 ]. PAI-1, a protein associated with tumour cell proliferation, invasion, migration, and release of tumour growth factors and cytokines, has been reported to be significantly correlated with node metastasis and shorter disease-free survival of NSCLC patients [ 23 , 24 ], which is consistent with the phenomenon observed in the NSCLC cohort. Previous studies implied that inhibition of PAI-1 increased the chemotherapeutic effect and radiosensitivity through regulating the PI3K/AKT signaling pathway [ 25 – 27 ]. In the future, further research is necessary to determine whether the effect of VitC on NSCLC is achieved by encoding PAI-1 through SERPINE1. TMEM158 is known as the RIS-1 protein and is recognized as a transmembrane protein that is regulated in response to Ras activation. Studies have found that TMEM158 increased chemoresistance against cisplatin in NSCLC patients and stimulated cancer cell proliferation, migration, and invasion through activation of the PI3K/AKT signalling pathways [ 28 , 29 ]. The current findings, combined with consistent reports in previous studies, support the robust evidence for the general application of IVC in NSCLC therapy. Given these data, IVC may represent an easily implementable addition to current anti-cancer therapies. Further large-scale clinical studies are warranted to determine the overall efficacy of IVC in NSCLC patients. Finally, regulations of SERPINB7, TMEM158, and SERPINE1 in both NSCLC cell lines and clinical histopathology may represent both a target and a biomarker for predicting responses to IVC in NSCLC therapy. In conclusion, this study identified SERPINB7, TMEM158, and SERPINE1 as not only a novel NSCLC prognosis gene set, but also as a potential therapeutic target and predictive factor for IVC treatment in patients with NSCLC, which provides a feasible method to improve the therapeutic effects of VitC. Abbreviations NSCLC non-small-cell lung cancer OS overall survival VitC Vitamin C IVC intravenous VitC PFS progression-free survival K-M plotter Kaplan-Meier plotter HPA Human Protein Atlas CT computed tomography TNM tumour-node-metastasis CEA carcinoembryonic antigen CYFRA21-1 human cytokeratin 19 fragment Antigen SCC squamous cell carcinoma antigen IHC immunohistochemistry ROC receiver operating characteristic AUC area under the ROC curve N.S. no significance PAI-1 Plasminogen activator inhibitor 1 ROS reactive oxygen species CI confidence interval HR hazard ratio. Declarations Acknowledgements We thank all patients in this study, as well as the study team at the Cancer Center, Pathology Department, and Imaging Department of Clifford Hospital, Jinan University. Authors’ contributions Ou was responsible for the the study design, integrity of the data, and the writing of the manuscript. Liao, Du, Xi, Meng, and Li contributed substantially to data collection, statistical analysis, pathology and image interpretation. All authors approved the final manuscript. Funding This study was financed by Guangdong Science and Technology Department [Grant number: 2020A1515011263], and Bureau of Science, Industry, Commerce and Information technology of Panyu District, Guangzhou [Grant number: 2020-Z04-003]. Availability of data and materials All data generated or analyzed during this study are included in this published article and its supplementary information files. Ethics approval and consent to participate All samples were anonymously coded in accordance with local ethical guidelines (as requested by the Declaration of Helsinki) with written informed consent and a protocol approved by the Ethics Committee of the Clifford Hospital affiliated to Jinan University [No: 2/2021-PRE-48]. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1 Cancer Center, Clifford Hospital, Jinan University, Guangzhou, P.R. China; 2 Pathology Department, Clifford Hospital, Jinan University, Guangzhou, P.R. China; 3 Imaging Department, Clifford Hospital, Jinan University, Guangzhou, P.R. China. References Cao W, Chen HD, Yu YW, Li N, Chen WQ. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J (Engl). 2021;134:783-91. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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Mohammed Ael S, Eguchi H, Wada S, Koyama N, Shimizu M, Otani K, et al. TMEM158 and FBLP1 as novel marker genes of cisplatin sensitivity in non-small cell lung cancer cells. Exp Lung Res. 2012;38:463-74. Fu Y, Yao N, Ding D, Zhang X, Liu H, Ma L, et al. TMEM158 promotes pancreatic cancer aggressiveness by activation of TGFβ1 and PI3K/AKT signaling pathway. J Cell Physiol. 2020;235:2761-75. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1472206","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":92520757,"identity":"bd117e01-7272-4a8c-a6e3-f61c7e880310","order_by":0,"name":"Junwen Ou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYHCCBDDJz9584MCHH6Rokew5lnhwZg8pdhnM8DE+zMFGhEp+iYRn0oVtNnkGEjwfDjPwMMjzix3Ar0VyRkKa9My2tGJz6d4NhwssGAxnzk4g4J4bQC282w4n7pxzdsPhGTwMCQa3idPyP3HDjZwHh3nYiNdyAKSFgTgtkj0Pkq15/yUnzuw5ZgAMZAnCfuFnz0m8zXPGLrGfvfnxhw8/bOT5pQloYWDgQVEhQUg5CLAfIEbVKBgFo2AUjGQAAEXuSNO2KOnUAAAAAElFTkSuQmCC","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Junwen","middleName":"","lastName":"Ou","suffix":""},{"id":92520758,"identity":"92476499-24ef-4b23-899c-43dd34c86203","order_by":1,"name":"Qiulin Liao","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiulin","middleName":"","lastName":"Liao","suffix":""},{"id":92520759,"identity":"83fc9908-7a18-4d90-af1a-aa77260a3894","order_by":2,"name":"Yanping Du","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanping","middleName":"","lastName":"Du","suffix":""},{"id":92520760,"identity":"ac133020-0ac9-4118-b44b-f487d0ca4548","order_by":3,"name":"Wentao Xi","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wentao","middleName":"","lastName":"Xi","suffix":""},{"id":92520761,"identity":"a848d01c-8f0e-48fa-9d42-03459d1ae46c","order_by":4,"name":"Qiong Meng","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiong","middleName":"","lastName":"Meng","suffix":""},{"id":92520762,"identity":"eaf161d6-1ab9-4dc9-8fbd-ca5f02027141","order_by":5,"name":"Kexin Li","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kexin","middleName":"","lastName":"Li","suffix":""},{"id":92520763,"identity":"99bf01be-334e-45ab-8a8d-505896fb4c02","order_by":6,"name":"Qichun Cai","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qichun","middleName":"","lastName":"Cai","suffix":""},{"id":92520764,"identity":"b53489fc-6b79-4d98-87ae-37cf50fdd763","order_by":7,"name":"Clifford L.K. Pang","email":"","orcid":"","institution":"Clifford Hospital, Jinan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Clifford","middleName":"L.K.","lastName":"Pang","suffix":""}],"badges":[],"createdAt":"2022-03-21 04:14:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1472206/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1472206/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19533647,"identity":"d7df26fb-4fb9-4673-bc13-c383c87ab439","added_by":"auto","created_at":"2022-03-23 15:17:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109660,"visible":true,"origin":"","legend":"\u003cp\u003eVitC regulates gene expression in NSCLC cells. \u003cstrong\u003e(a)\u003c/strong\u003e Volcano plots showing the differentially expressed genes from VitC-treated H1299 and PC9 cells compared with placebo-treated cells. \u003cstrong\u003e(b)\u003c/strong\u003e Venn diagram showing genes that are upregulated and downregulated in both H1299 and PC9 cells treated with VitC.\u003c/p\u003e","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/03a133e17df01245d0cbe5d4.png"},{"id":19533088,"identity":"97276ae0-c45c-4d47-b235-e81d05c4faeb","added_by":"auto","created_at":"2022-03-23 15:14:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123037,"visible":true,"origin":"","legend":"\u003cp\u003eSERPINB7, TMEM158, and SERPINE1 are unfavourable prognostic predictors in patients with NSCLC (K-M Plotter). \u003cstrong\u003e(a-c)\u003c/strong\u003e The relationship between the expression of three genes in tumour tissue and OS in patients with NSCLC. \u003cstrong\u003e(d-f) \u003c/strong\u003eThe relationship between the expression of three genes in tumour tissue and PFS in patients with NSCLC. Log-rank (Mantel-Cox) test. Red lines indicate high expression; blue lines indicate low expression. *, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05; **,\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.01; ***, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; N.S., no significance.\u003c/p\u003e","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/2622a7ff24c59476ae78a4a3.png"},{"id":19533087,"identity":"b76b3a3e-52e2-4c26-ac7b-54f9785ee050","added_by":"auto","created_at":"2022-03-23 15:14:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47205,"visible":true,"origin":"","legend":"\u003cp\u003eSERPINB7, TMEM158 and SERPINE1 are unfavourable prognostic predictors in patients with NSCLC (HPA). \u003cstrong\u003e(a-c)\u003c/strong\u003e The relationship between the expression of three genes in tumour tissue and OS in patients with NSCLC. Red lines indicate high expression; blue lines indicate low expression. *, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05; **, \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01; ***, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; N.S., no significance.\u003c/p\u003e","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/793eee0fe9c839bc007a17a8.png"},{"id":19533648,"identity":"e216a8d2-821c-468d-89e2-c2f8fd0e0278","added_by":"auto","created_at":"2022-03-23 15:17:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":203901,"visible":true,"origin":"","legend":"\u003cp\u003eSERPINB7, TMEM158, and SERPINE1 are prognostic biomarkers for patients with NSCLC. \u003cstrong\u003e(a)\u003c/strong\u003e Representative IHC images of SERPINB7. \u003cstrong\u003e(b, c) \u003c/strong\u003eOS and PFS for patients with NSCLC who were divided into two groups according to the median values of SERPINB7. \u003cstrong\u003e(d)\u003c/strong\u003e Representative IHC images of TMEM158. \u003cstrong\u003e(e, f) \u003c/strong\u003eOS and PFS for patients with NSCLC who were divided into two groups according to the median values of TMEM158. \u003cstrong\u003e(g) \u003c/strong\u003eRepresentative IHC images of SERPINE1. \u003cstrong\u003e(h, i) \u003c/strong\u003eOS and PFS for patients with NSCLC who were divided into two groups according to the median values of SERPINE1. \u003cstrong\u003e(j, k) \u003c/strong\u003eOS and PFS for patients with NSCLC who were divided into three groups according to the median values of the combined expression patterns of the genes. *, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05; **, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; ***, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; N.S., no significance.\u003c/p\u003e","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/b27f448d012a691bb0eb8efe.png"},{"id":19533083,"identity":"292be3ef-4f98-4ab0-b1b1-d6442ec968c8","added_by":"auto","created_at":"2022-03-23 15:14:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110036,"visible":true,"origin":"","legend":"\u003cp\u003eSERPINB7, TMEM158, and SERPINE1 are potential therapeutic targets for VitC. \u003cstrong\u003e(a-c) \u003c/strong\u003eOS between patients treated with VitC with high and low expressions of SERPINB7, TMEM158 and SERPINE1. \u003cstrong\u003e(d-f) \u003c/strong\u003ePFS between patients treated with VitC with high and low expressions of SERPINB7, TMEM158 and SERPINE1. \u003cstrong\u003e(g, h) \u003c/strong\u003eOS and PFS between patients treated with VitC with low, medium and high expression of the combined expression patterns of the genes. \u003cstrong\u003e(i, j) \u003c/strong\u003eROC curve analysis was used to evaluate the predictive accuracy of each marker or combined genes for OS and PFS. Log-rank (Mantel-Cox) test. *, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.05;**, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.01; .N.S., no significance.\u003c/p\u003e","description":"","filename":"OnlineFig5.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/0fcc3b31c64af37b1fd57ef3.png"},{"id":19533085,"identity":"53ce08e4-d68b-4c2e-8740-109710418d67","added_by":"auto","created_at":"2022-03-23 15:14:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":256976,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of this study. \u003csup\u003e*\u003c/sup\u003elow and high expression of genes was detected prior to anticancer therapies.\u0026nbsp;\u003c/p\u003e","description":"","filename":"OnlineFig6.png","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/82bf80a04d47cc1e1fd2cab9.png"},{"id":19639863,"identity":"657f45a1-8481-4d97-8e4f-911c83db4501","added_by":"auto","created_at":"2022-03-26 04:59:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2265848,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/ebec202c-2b5f-42d9-ae35-b10e91b8941d.pdf"},{"id":19533089,"identity":"a665f792-571c-4b2d-bbf9-485f381bc271","added_by":"auto","created_at":"2022-03-23 15:14:29","extension":"doc","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":14648832,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.doc","url":"https://assets-eu.researchsquare.com/files/rs-1472206/v1/e8037d7beddcc9dc0eeca47b.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"SERPINB7, TMEM158, and SERPINE1 signature as predictors of non-small-cell lung cancer prognosis after intravenous vitamin C treatment","fulltext":[{"header":"Background","content":"\u003cp\u003eLung cancer remains the most common cancer type and the leading cause of cancer mortality in China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], accounting for 17.9% of newly diagnosed cancer cases and 23.8% of all deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nearly 85% of lung cancers are non-small-cell lung cancer (NSCLC), which has a 5-year survival rate of less than 20% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The majority of NSCLC patients were found to have advanced disease [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs cancer is a heterogeneous disease, the use of personalized medicine for individual patients has become the new focus for successfully implemented anticancer therapies. Vitamin C (VitC), as a natural compound of low toxicity and high tolerance, can decrease the proliferation of lung cancer cell lines via causing cell cycle arrest and promoting apoptosis [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Clinical studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] have suggested that when concomitant with chemotherapy, intravenous VitC (IVC) can enhance the efficacy and reduce the toxicity of chemotherapy. This was also demonstrated in our previous retrospective clinical study involving gemcitabine and carboplatin treatment in breast cancer patients, which showed an increased response rate of patients to chemotherapy drugs and prolonged progression-free survival (PFS) and overall survival (OS) (1g/kg.d, every other day, 25 treatments) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A separate prospective clinical study showed that IVC (1g/kg.d, three times a week, 25 treatments) can significantly prolong PFS and OS, as well as moderate cancer-related inflammation in advanced NSCLC patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, cancer is a chronic disease with high heterogeneity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and as such VitC should not be regarded with a \u0026lsquo;one-size-fits-all\u0026rsquo; approach in cancer treatment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. We found that the therapeutic effect of IVC varied greatly among patients with advanced NSCLC [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Using the RECIST 1.1 criteria, some patients were found to have a partial response after 25 IVC treatments, with 5 patients even surviving for more than 5 years, whereas some patients had progressive disease [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We speculate that IVC treatments work only for some people with NSCLC. Thus, exploring biomarkers for identifying patients who may benefit from IVC will allow therapeutic strategies to be designed more accurately and efficiently.\u003c/p\u003e \u003cp\u003eIn this study, potential VitC-regulated genes were first screened from NSCLC cell lines through high-throughput sequencing. Through analysis of pathological specimens and clinical data of such genes in NSCLC patients receiving VitC treatment, a total of 3 genes (SERPINB7, TMEM158, and SERPINE1) were identified as not only a novel NSCLC prognosis gene set, but also as serving as a potential therapeutic target and predictive factor for VitC treatment in patients with NSCLC. This may provide a feasible method for selecting the most appropriate NSCLC patients for VitC treatment.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and RNA-seq\u003c/h2\u003e \u003cp\u003eThe human NSCLC cell lines H1299 (CRL-5803) and PC9 (H086) were purchased from ATCC and cultured in RPMI1640 medium supplemented with 10% foetal bovine serum and 1% penicillin and streptomycin. H1299 and PC9 cells were exposed to VitC (0.5mM and 1mM) for 24 hours and then used for RNA-seq analysis. Total RNA was extracted from the indicated cells using TRIzol reagent (Invitrogen, AM9738), and the RNA quantity and quality were measured using a NanoDrop ND-1000. Libraries were constructed according to standard Illumina protocols. The quality of the RNA and complementary DNA was monitored using an Agilent Bioanalyzer 2100, and sequencing was performed on an Illumina HiSeq 4000 by KangChen Biotech Company (Shanghai).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOnline database\u003c/h2\u003e \u003cp\u003eClinical data relating to human NSCLC patients, including OS and PFS, was obtained from the Kaplan-Meier Plotter (K-M Plotter) and the Human Protein Atlas (HPA) databases. The survival studies from the K-M Plotter were evaluated according to the web tool developer\u0026rsquo;s instructions (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"http://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) as previously described [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Briefly, the gene probes of the target gene were selected from the K-M Plotter database as the only JetSet best probe set, which was then used to create Kaplan-Meier survival curves to determine the correlation between their expression and patient survival in NSCLC by using the median setting. The survival studies of patients from the HPA database were performed according to the instructions as previously described [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003e Clinical samples were obtained from patients with pathologically confirmed NSCLC at the Cancer Center at Clifford Hospital of Jinan University in Guangzhou, China. Subjects were enrolled between May 2016 and April 2021 and were randomly selected for survival analysis. The inclusion criteria were as follows: 1) histologically confirmed NSCLC; 2) tissue sections available for immunohistochemical staining; 3) confirmation of recurrent and/or metastatic NSCLC based on at least two imaging technologies (e.g., enhanced computed tomography (CT) scan); 4) availability of complete medical records and precise follow-up data; and 5) treatment with anticancer therapy regimens such as surgery, radiation, chemotherapy, targeted therapy and/or immunotherapy. All subjects were divided into two groups, the control group (N\u0026thinsp;=\u0026thinsp;81) and the VitC group (N\u0026thinsp;=\u0026thinsp;72). The control group comprised patients who only received general anticancer therapy regimens, whereas in the VitC group, patients received anticancer therapy regimens along with IVC treatment (1 g/kg.d, three times a week, 15 to 30 treatments in total according to the patient\u0026rsquo;s condition). Each millilitre of VitC contained 3 g sodium VitC and water for injection, with the pH adjusted to 6.5-8.0 with sodium bicarbonate. VitC was infused for 120 min with 900 mmol/L osmotic pressure during the same period. The patients receiving IVC treatment also fulfilled the above 1)\u0026thinsp;~\u0026thinsp;5) inclusion criteria.\u003c/p\u003e \u003cp\u003eA range of demographic and clinicopathological data, including sex, age, tumour characteristics, and TNM stage, were collected on the study subjects. Specifically, data was gathered on tumour number and size; circular protein CEA, CF21-1, SCC level; and the presence or absence of pleural invasion. For this study, OS was defined as the duration from enrollment to death from any cause. For the patients alive, OS was censored at the last contact date. PFS was defined as the duration from enrollment to first recurrence. For the patients alive and recurrence-free, PFS was censored at the last contact date. All patients provided written informed consent. All samples were anonymously coded in accordance with local ethical guidelines (as requested by the Declaration of Helsinki) with written informed consent and a protocol approved by the Ethics Committee of the Clifford Hospital affiliated to Jinan University [No: 2/2021-PRE-48]. Information regarding the most recent follow-up and survival status was collected for all patients until April 30, 2021.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry staining\u003c/h2\u003e \u003cp\u003eThe streptavidin-peroxidase method was used for immunohistochemistry (IHC). All of the immunohistochemical reagents were purchased from SIGMA and INVITROGEN (SERPINB7: SIGMA, DA-21008; SERPINE1: INVITROGEN, PA5-90025; TMEM158: SIGMA, DA-21010; DLX4: SIGMA, DA-21003; DDIT4: SIGMA, DA-21004; ZNF507: SIGMA, DA-21009). The primary antibodies, rabbit anti-human polyclonal antibodies, were used at a working concentration of 1:50. The detection methods were carried out strictly according to the kit instructions. Known positive sections were used as a positive control, and sections treated with PBS instead of primary antibody were used as a negative control.\u003c/p\u003e \u003cp\u003eBrown granules in the cytoplasm of cells defined positive staining. The analysis was performed by two independent observers who were blinded to the patient information. Any disagreements were discussed to reach a mutual consensus or referred to a third observer if needed. To quantify the density of the expression of the above genes in NSCLC, InForm 2.0.1 image analysis software was used. Patients were divided into high and low expression groups according to the median expression of their genes. In the combined expression pattern analysis model, a high pattern meant that all 3 genes included in the analysis belonged to the high expression group; a low pattern meant that all 3 genes belonged to the low expression group; and a medium pattern encompassed the remaining cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eQuantification and statistical analysis\u003c/h2\u003e \u003cp\u003eCumulative survival time was calculated by the Kaplan-Meier method and the log-rank test. Univariate and multivariate analyses were performed using the Cox proportional hazard regression model to identify the prognostic factors for OS and PFS. Time-dependent receiver operating characteristic (ROC) curve analysis was also used to confirm the predictive survival performance of a multifactor signature. The area under the ROC curve (AUC) was calculated to evaluate the predictive accuracy of each marker for estimating survival. Significance was defined as P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. IBM SPSS statistics software and GraphPad Prism were used for all statistical analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIVC improved survival time of NSCLC patients\u003c/h2\u003e \u003cp\u003eIn this retrospective study, a total of 153 NSCLC patients from the two groups were included. The control group consisted of 81 NSCLC patients who received anticancer therapy regimens but no IVC treatment, while the VitC group included 72 NSCLC patients who received IVC therapy in addition to anticancer therapy regimens. For each group, the patients\u0026rsquo; baseline demographic and clinicopathological features are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The subjects enrolled in the VitC group were matched with the patients in the control by patient age, gender, and baseline tumour- characteristics.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVitC group\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u0026ndash;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u0026ndash;88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumour- number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumour- size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNM stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePleural invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCF21-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u0026ndash;43.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09\u0026ndash;65.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u0026ndash;17.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u0026ndash;70.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026ndash;10668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e All patients in the study were followed up until April 2021. In total, 48 patients survived and 33 patients died in the control group, while in the VitC group 53 patients survived and 19 patients died (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). The median OS in the VitC group was 59.2 months, which was significantly longer than that of the control group, which had a median OS of 25.6 months (\u003cb\u003eSupplementary Fig.\u0026nbsp;2, P\u003c/b\u003e\u0026thinsp;=\u0026thinsp;0.022).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eVitC-regulated genes in cell lines\u003c/h2\u003e \u003cp\u003eRNA-seq data showed that as compared to the control, 48 genes were upregulated and 43 genes were downregulated in H1299 cells treated with VitC, while 641 genes were upregulated and 398 genes were downregulated in VitC-treated PC9 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). A Venn diagram showed that 3 genes (ZNF507, DLX4, and DDIT4) were upregulated in both cell lines following treatment with VitC, whereas 3 genes (SERPINB7, TMEM158, and SERPINE1) were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVitC-regulated genes related to OS and PFS from online database\u003c/h2\u003e \u003cp\u003eTo uncover the clinical significance of the potential VitC treatment target genes, the K-M Plotter was used and a prognosis analysis was performed. The resulting data showed that the expression levels of SERPINB7, TMEM158, and SERPINE1 were negatively correlated with OS in NSCLC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-c), and that SERPINB7 and TMEM158, but not SERPINE1, were negatively correlated with PFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-f).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, an identical prognostic analysis was performed with ZNF507, DLX4, and DDIT4 in the K-M Plotter. The data showed that ZNF507 was positively correlated with the OS of patients with NSCLC (\u003cb\u003eSupplementary Fig.\u0026nbsp;3a\u003c/b\u003e), while DLX4 and DDIT4 were negatively (\u003cb\u003eSupplementary Fig.\u0026nbsp;3b-c\u003c/b\u003e). In the PFS analysis, DLX4 was found to be negatively correlated with PFS, while no correlation was found with either ZNF507 or DDIT4 (\u003cb\u003eSupplementary Fig.\u0026nbsp;3d-f\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eClinical and gene expression data from the HPA was also used to perform an analysis of OS. The data showed that SERPINB7, TMEM158, and SERPINE1 were negatively correlated with OS in NSCLC patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-c), which was consistent with the K-M Plotter analysis. However, ZNF507, DLX4, and DDIT4 were inconsistent with the K-M Plotter analysis (ZNF507, no significance; DLX4, positively; DDIT4, negatively; \u003cb\u003eSupplementary Fig.\u0026nbsp;4\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVitC-regulated genes from study population\u003c/h2\u003e \u003cp\u003eTo further explore the prognostic significance of VitC-regulated genes, samples from the cohort of NSCLC patients was used for immunohistochemical staining and prognosis analysis. Representative images of high and low expressions of SERPINB7 (cut off of SERPINB7 is 15%; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), TMEM158 (cut off of TMEM158 is 70%; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed), and SERPINE1 (cut off of SERPINE1 is 85%; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg) are shown in tissue sections. In the control group, patients were further divided into two subgroups according to the median value of the above genes. The data showed that patients with low expression of SERPINB7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), TMEM158 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee), and SERPINE1 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eh) were associated with increased OS. SERPINE1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei) was associated with increased PFS, but not in SERPINB7(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) and TMEM158 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e Next, patients were divided into \u0026ldquo;low\u0026rdquo;, \u0026ldquo;medium,\u0026rdquo; and \u0026ldquo;high\u0026rdquo; groups according to the median values of the combined expression patterns of the genes. The low pattern patients were found to experience longer OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ej) and PFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ek) than the high pattern patients. Patients with a medium pattern had similar time to low pattern. Multivariate analysis revealed that a low pattern was an independent prognostic factor for OS in patients with NSCLC (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The combination of SERPINB7, TMEM158, and SERPINE1 showed improved prognostic stratification of NSCLC survival compared to that of any of the three genes individually (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The expression levels of DDIT4, DLX4, and ZNF507 (\u003cb\u003eSupplementary Fig.\u0026nbsp;5a, 5d, 5g\u003c/b\u003e) were also quantified and their impact on patient survival further analysed. Ultimately, no correlation was found between the expression levels of DDIT4, DLX4, or ZNF507 with OS (\u003cb\u003eSupplementary Fig.\u0026nbsp;5b, 5e, 5h\u003c/b\u003e) and PFS (\u003cb\u003eSupplementary Fig.\u0026nbsp;5c, 5f, 5i\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of variables associated with survival and recurrence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eUnivariate\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMultivariate\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eUnivariate\u003c/b\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e\u003cb\u003eMultivariate\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male vs. female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.025\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (high vs. low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNM stage (I-II vs. III-IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.0001\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.05\u0026ndash;208.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.003\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumour size (high vs. low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.010\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumour number (single vs. multiple)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePleural invasion (absent vs. present)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.028\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCF21-1 (high vs. low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCC (high vs. low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA (high vs. low)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMEM158 (low vs. high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.046\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERPINB7 (low vs. high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.033\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSERPINE1 (low vs. high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.009\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.002\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSignature (low vs. medium vs. high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.0001\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.55\u0026ndash;59.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.002\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.003\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eNote: The Cox proportional hazards regression model was used. Variables that were associated with OS or PFS in the univariate analysis were adopted as covariates in the multivariate analysis and entered into the equation by using the forward likelihood ratio method.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePatients with NSCLC in the VitC group were further enrolled for survival analysis. Pathological samples obtained prior to VitC treatment were further divided into two subgroups according to the median values of SERPINB7, TMEM158, and SERPINE1, respectively. The data showed longer OS in patients with high levels of SERPINB7 (59 months vs. 9 months, P\u0026thinsp;=\u0026thinsp;0.039; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), TMEM158 (59 months vs. 10 months, P\u0026thinsp;=\u0026thinsp;0.011; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), and SERPINE1 (59 months vs. 29 months, P\u0026thinsp;=\u0026thinsp;0.005; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), but not longer PFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed-f). However, DDIT4, DLX4, and ZNF507 were not found to be associated with OS or PFS (\u003cb\u003eSupplementary Fig.\u0026nbsp;6\u003c/b\u003e). As was done in the control group, patients in the VitC group were also divided into \u0026ldquo;low\u0026rdquo;, \u0026ldquo;medium\u0026rdquo; and \u0026ldquo;high\u0026rdquo; groups according to the median values of the combined expression patterns of the genes. High pattern patients were found to experience longer OS (median OS: 59 months vs. 13 months, P\u0026thinsp;=\u0026thinsp;0.0034, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eg), but not in PFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eh) than low pattern patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurther analysis revealed a larger AUC for the combined signature than SERPINB7, TMEM158, or SERPINE1 individually in predicting the OS (SERPINB7: AUC\u0026thinsp;=\u0026thinsp;0.57, P\u0026thinsp;=\u0026thinsp;0.29, 95% CI, 0.44\u0026ndash;0.71; TMEM158: AUC\u0026thinsp;=\u0026thinsp;0.58, P\u0026thinsp;=\u0026thinsp;0.24, 95% CI, 0.45\u0026ndash;0.71; SERPINE1: AUC\u0026thinsp;=\u0026thinsp;0.59, P\u0026thinsp;=\u0026thinsp;0.19, 95% CI, 0.46\u0026ndash;0.72; The combination: AUC\u0026thinsp;=\u0026thinsp;0.77, P\u0026thinsp;=\u0026thinsp;0.0015, 95% CI, 0.63\u0026ndash;0.90) and PFS (SERPINB7: AUC\u0026thinsp;=\u0026thinsp;0.59, P\u0026thinsp;=\u0026thinsp;0.16, 95% CI, 0.47\u0026ndash;0.72; TMEM158: AUC\u0026thinsp;=\u0026thinsp;0.54, P\u0026thinsp;=\u0026thinsp;0.52, 95% CI, 0.41\u0026ndash;0.67; SERPINE1: AUC\u0026thinsp;=\u0026thinsp;0 .58, P\u0026thinsp;=\u0026thinsp;0.26, 95% CI, 0.44\u0026ndash;0.71; The combination: AUC\u0026thinsp;=\u0026thinsp;0.76, P\u0026thinsp;=\u0026thinsp;0.0014, 95% CI, 0.62\u0026ndash;0.90) of IVC treated patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ei, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ej).\u003c/p\u003e \u003cp\u003eIn this retrospective study, OS was found to be significantly prolonged in the IVC group compared to the control group. Analysis of combined patient data from an online database and the NSCLC cohort analysis revealed that patients without IVC treatment and with low expression of SERPINB7, TMEM158, and SERPINE1 were associated with increased OS. However, patients in the IVC group with high expression of SERPINB7, TMEM158, and SERPINE1 in tumour tissues before IVC treatment were associated with prolonged OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eClinical studies have suggested that IVC can increase efficacy and reduce toxic side effects from chemotherapy when used in conjunction with chemotherapy. In a phase II study, chemical therapy (IV carboplatin and IV paclitaxel) coupled with IVC showed a 28.6% (4 out of the 14 patients) partial response (PR) in advanced-stage NSCLC patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], indicating the potential efficacy of IVC in NSCLC therapy. Our previous prospective clinical study found that the combination of high concentration of IVC and hyperthermia markedly improved PFS and OS in patients with stage III-IV NSCLC after a median follow-up of 24 months [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, quality of life (QoL) was significantly increased in the VitC group despite the advanced stage of disease. The 3-month disease control rate after treatment was 42.9% in the VitC group and 16.7% in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Overall, IVC can not only enhance chemotherapy but also hyperthermia therapeutic effect in advanced NSCLC patients.\u003c/p\u003e \u003cp\u003eIVC can selectively kill cancer cells by multiple targets and mechanisms, including generation of a large number of hydrogen peroxide (H2O2); activating TETs as a cofactor and leading to enhanced DNA demethylation and hydroxylmethylation; and downregulating the expression level of HIF1α [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A growing number of discoveries about VitC in the treatment of cancer will identify more potential therapeutic targets. This study showed that VitC regulated the expression of SERPINB7, TMEM158, and SERPINE1, which were associated with OS of NSCLC patients.\u003c/p\u003e \u003cp\u003eThus far, only a few studies have explored the relationship between SERPINB7 and cancer. In one study, Bianconi [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] showed that SERPINB7 is a predictor of poor gemcitabine treatment effects in pancreatic cancer. In other research, Chou [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] demonstrated the function of SERPINB7 in suppressing the invasiveness and motility of NSCLC cells. However, the mechanism of SerpinB7 remains unknown.\u003c/p\u003e \u003cp\u003eSERPINE1 gene encoded plasminogen activator inhibitor 1 (PAI-1) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. PAI-1, a protein associated with tumour cell proliferation, invasion, migration, and release of tumour growth factors and cytokines, has been reported to be significantly correlated with node metastasis and shorter disease-free survival of NSCLC patients [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which is consistent with the phenomenon observed in the NSCLC cohort. Previous studies implied that inhibition of PAI-1 increased the chemotherapeutic effect and radiosensitivity through regulating the PI3K/AKT signaling pathway [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In the future, further research is necessary to determine whether the effect of VitC on NSCLC is achieved by encoding PAI-1 through SERPINE1.\u003c/p\u003e \u003cp\u003eTMEM158 is known as the RIS-1 protein and is recognized as a transmembrane protein that is regulated in response to Ras activation. Studies have found that TMEM158 increased chemoresistance against cisplatin in NSCLC patients and stimulated cancer cell proliferation, migration, and invasion through activation of the PI3K/AKT signalling pathways [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current findings, combined with consistent reports in previous studies, support the robust evidence for the general application of IVC in NSCLC therapy. Given these data, IVC may represent an easily implementable addition to current anti-cancer therapies. Further large-scale clinical studies are warranted to determine the overall efficacy of IVC in NSCLC patients. Finally, regulations of SERPINB7, TMEM158, and SERPINE1 in both NSCLC cell lines and clinical histopathology may represent both a target and a biomarker for predicting responses to IVC in NSCLC therapy.\u003c/p\u003e \u003cp\u003eIn conclusion, this study identified SERPINB7, TMEM158, and SERPINE1 as not only a novel NSCLC prognosis gene set, but also as a potential therapeutic target and predictive factor for IVC treatment in patients with NSCLC, which provides a feasible method to improve the therapeutic effects of VitC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSCLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-small-cell lung cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVitC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVitamin C\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIVC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintravenous VitC\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePFS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogression-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eK-M plotter\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKaplan-Meier plotter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman Protein Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etumour-node-metastasis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCEA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecarcinoembryonic antigen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCYFRA21-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehuman cytokeratin 19 fragment Antigen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esquamous cell carcinoma antigen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earea under the ROC curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eN.S.\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eno significance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePAI-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlasminogen activator inhibitor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereactive oxygen species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehazard ratio.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all patients in this study, as well as the study team at the Cancer Center, Pathology Department, and Imaging Department of Clifford Hospital, Jinan University.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOu was responsible for the the study design, integrity of the data, and the writing of the manuscript. Liao, Du, Xi, Meng, and Li contributed substantially to data collection, statistical analysis, pathology and image interpretation. All authors approved the final manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financed by Guangdong Science and Technology Department [Grant number: 2020A1515011263], and Bureau of Science, Industry, Commerce and Information technology of Panyu District, Guangzhou [Grant number: 2020-Z04-003].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this\u0026nbsp;published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll samples were anonymously coded in accordance with local ethical guidelines (as requested by the Declaration of Helsinki) with written informed consent and a protocol approved by the Ethics Committee of the Clifford Hospital affiliated to Jinan University\u0026nbsp;[No: 2/2021-PRE-48].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eCancer Center, Clifford Hospital, Jinan University, Guangzhou, P.R. China; \u003csup\u003e2\u003c/sup\u003ePathology Department, Clifford Hospital, Jinan University, Guangzhou, P.R. China; \u003csup\u003e3\u003c/sup\u003eImaging Department, Clifford Hospital, Jinan University, Guangzhou, P.R. China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCao W, Chen HD, Yu YW, Li N, Chen WQ. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin Med J (Engl).\u003cem\u003e\u0026nbsp;\u003c/em\u003e2021;134:783-91.\u003c/li\u003e\n \u003cli\u003eSung 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.\u003c/li\u003e\n \u003cli\u003eMustachio LM, Roszik J. Current Targeted Therapies for the Fight against Non-Small Cell Lung Cancer. 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ACT001, a novel PAI-1 inhibitor, exerts synergistic effects in combination with cisplatin by inhibiting PI3K/AKT pathway in glioma. Cell Death Dis. 2019;10:757.\u003c/li\u003e\n \u003cli\u003eMohammed Ael S, Eguchi H, Wada S, Koyama N, Shimizu M, Otani K, et al. TMEM158 and FBLP1 as novel marker genes of cisplatin sensitivity in non-small cell lung cancer cells. Exp Lung Res. 2012;38:463-74.\u003c/li\u003e\n \u003cli\u003eFu Y, Yao N, Ding D, Zhang X, Liu H, Ma L, et al. TMEM158 promotes pancreatic cancer aggressiveness by activation of TGF\u0026beta;1 and PI3K/AKT signaling pathway. J Cell Physiol. 2020;235:2761-75.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Intravenous vitamin C, non-small cell lung cancer, predictor/prognosis ","lastPublishedDoi":"10.21203/rs.3.rs-1472206/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1472206/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u003c/p\u003e\u003cp\u003eVitamin C\u0026nbsp;(VitC) has been proposed as a potential anti-cancer agent for prolonging progression-free survival (PFS) and overall survival (OS) in non-small-cell lung cancer (NSCLC)\u0026nbsp;patients. However, VitC\u0026nbsp;has only been shown to be effective for some patients,\u0026nbsp;and the mechanism in those who have benefitted from it remains unknown. We aimed to explore whether gene expression could predict IVC benefit for patients with NSCLC. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eH1299 and PC9 cells were treated with VitC and high-throughput sequencing was\u0026nbsp;used for screening differential genes. Data from the Kaplan-Meier Plotter and the Human Protein Atlas\u0026nbsp;databases were used\u0026nbsp;for analysis\u0026nbsp;of patient prognoses. In a retrospective study, 153 NSCLC patients from our Cancer Center were\u0026nbsp;selected and divided into a control\u0026nbsp;group (n = 81) and VitC group (n\u0026nbsp;=\u0026nbsp;72)\u0026nbsp;for immunohistochemical staining and prognosis analysis. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAs a result, ZNF507, DLX4,\u0026nbsp;and DDIT4\u0026nbsp;were found to be upregulated, and SERPINB7, TMEM158 and SERPINE1\u0026nbsp;downregulated in NSCLC\u0026nbsp;cell lines following\u0026nbsp;VitC\u0026nbsp;treatment.\u0026nbsp;Combined patient data from the cohort analysis and\u0026nbsp;online databases revealed that the downregulated genes, but not upregulated genes, presented an unfavorable prognostic\u0026nbsp;predictor of\u0026nbsp;OS\u0026nbsp;in NSCLC patients. Further analysis showed that the combined three genes were more efficient at predicting survival than individually\u0026nbsp;(AUC=0.77, 95%CI, 0.63-0.90). Moreover, high expression of SERPINB7, TMEM158, and SERPINE1 in resected tumour-\u0026nbsp;tissues before VitC treatment was found to be associated with prolonged OS\u0026nbsp;in patients with NSCLC who were treated with VitC. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOverall, these data revealed that SERPINB7, TMEM158, and SERPINE1 formed a novel NSCLC prognosis gene set and could serve as a potential therapeutic target as well as predictive factor for VitC treatment in patients with NSCLC.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e Retrospectively registered (No: 2/2021-PRE-48) on July 13, 2021.\u003c/p\u003e","manuscriptTitle":"SERPINB7, TMEM158, and SERPINE1 signature as predictors of non-small-cell lung cancer prognosis after intravenous vitamin C treatment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-23 15:14:26","doi":"10.21203/rs.3.rs-1472206/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5a248d2-7cf4-4f93-99c0-4f09df9eccfa","owner":[],"postedDate":"March 23rd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-03-26T04:59:05+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-23 15:14:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1472206","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1472206","identity":"rs-1472206","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}