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The aim of this study is to clarify whether NPLOC4 is a poor prognostic factor for multiple malignancies and a potential immunotherapy target.

Cancer is the leading cause of death in the 21st century and is a threat to the life and health of all mankind. Hematoma is generally treated with chemotherapy, targeted therapy and immunotherapy. Solid tumors are mainly treated by surgical resection. However, systemic treatment will be applied by some patients to reduce tumor grade who cannot receive surgery, and some patients who have undergone surgery will also apply systemic treatment in order to prevent postoperative recurrence and metastasis. It is noteworthy that immunotherapy regimen utilize the patient's own highly specific and safe immune ability to exert anti-tumor effects, gradually becoming the preferred treatment for some tumors, indicating its further potential. Even though, for primary drug resistance, the response rate to anti-PD-L1/PD-1 therapy is only 10-40%, and for acquired resistance, melanoma patients are considered to have the best response to immunotherapy of all types of tumor patients, and 60% of such patients still develop drug resistance and postoperative recurrence. In this view, a large proportion of patients show insensitivity to immunotherapy. The tumor immunosuppressive microenvironment (TIME), which has a huge impact on the insensitivity of cancer patients to immunotherapy actually. Enrichment of immunosuppressive cells and molecules in tumor microenvironment, hindering the activation of cytotoxic immune cells and the effectiveness of immunotherapy. Therefore, it is necessary and urgent to identify the molecules that make a crucial influence on the establishment and maintenance of the immune microenvironment. In particular, powerful tumor therapeutic targets, having the ability to affect the tumor immune microenvironment, which not only can target inhibitors be used alone to eliminate tumors, but also can be used in combination with clinically important immune agents. NPLOC4, part of UFD1-NPL4 complex and P97/VCP-NPL4-UFD1 AAA ATPase complex, which binds ubiquitinated proteins to activate proteasomal degradation and is responsible for exporting misfolded proteins from the endoplasmic reticulum (ER) to the cytoplasm, affecting the growth and progression of certain malignancies. Several studies showed that NPLOC4 has the potential to play an important role in tumor immunity, but there is a lack of research to further explore it.

1.Analyze the expression level and cell sublocalization information of NPLOC4 in a variety of tumors. 2.Analyze the correlation between NPLOC4 and the prognosis of cancer patients. 3.Analyze the connection between NPLOC4 and immune cells, immune molecules in the tumor immune microenvironment. 4.Verify the expression of NPLOC4 in hepatocellular carcinoma tissues and cells. 5.Analyze the expression of NPLOC4 in each immune and stromal cells in the liver cancer microenvironment.

Data Collection RNA expression and clinical data from Genotype-Tissue [removed]GTEx) and The Cancer Genome Atlas (TCGA) were obtained from the UCSC Xena database (https://xenabrowser.net/datapages/). The CPTAC (http://ualcan.path.uab.edu/analysis-prot.html) database was used to explore the protein levels of NPLOC4 in human tumors and normal tissues. The expression of NPLOC4 in tumor cell lines was evaluated by using the database Cancer Cell Line Encyclopedia (CCLE) (https://sites.broadinstitute.org/ccle). The tissue Immunohistochemical (IHC) and cell sublocalization immunofluorescence of various tumors and normal tissues downloaded from the human Protein Atlas database (https://www.proteinatlas.org/). The methylation data of 33 TCGA tumors was obtained from cbioportal (https://www.cbioportal.org/datasets). Data for single cell analysis were obtained from the TISCH2 database (http://tisch.comp-genomics.org/). Prognostic analysis Univariate Cox regression analyses were implemented to estimate the significance of NPLOC4 in predicting overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in pan-cancer. Kaplan-Meier analysis was performed to evaluate the OS, DSS, and PFI of patients from TCGA cohort. Tumor Microenvironment Characterization Three TME phenotypes were defined, and the TME score was constructed using principal component analysis algorithms according to previous work [21]. Immune Cell Infiltration We obtained and evaluated the immune cell infiltration score of TCGA cohort from the ImmuCellAI database (http://bioinfo.life.hust.edu.cn/ImmuCellAI#!/), and TIMER2 database (http://timer.cistrome.org/). All types of cancer patients were divided into two groups with high and low NPLOC4 expression groups based on the median NPLOC4 expression level to compare the extent of immune cell infiltration. Gene set variation analysis Correlation analysis of NPLOC4 was performed using TCGA data. Pearson’s correlation coefficient was calculated. GSVA was conducted using the R package “GSVA” to calculate the pathway score of each sample based on the MSigDB database v7.1 (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp) with the following parameters: nPerm = 1,000, minGSSize = 10, maxGSSize = 1,000, and p-value-cutoff = 0.05. Correlation of NPLOC4 with half maximal inhibitory concentration (IC50) of anti-tumor drugs We analyzed the relationship between NPLOC4 expression and the IC50 of anti-tumor drugs using the data of genomics of drug sensitivity in cancer (GDSC2) database (https://www.cancerrxgene.org/). Human tissue samples The experiments involving human samples in this research were in accordance with the principles of the Helsinki Declaration and approved by the Institutional Review Committee of Nanfang Hospital, Southern Medical University, Guangdong Province, China (NFEC-201208-K3). The participants provided their written informed consent to participate in this study. A total of 16 HCC tissues and paired non-cancer tissues were collected for qRT-PCR. A total of 3 HCC tissues and paired non-cancer tissues were collected for IHC. Cell lines SNU182, PLC, 7721 and MIHA were purchased form Procell (Wuhan, China). SNU182, 7721, and MIHA were cultured in RPMI 1640 medium (Gibico, USA) obtained 10

Exprecssion and subcellular location analysis of NPLOC4 in pan-cancer To determine NPLOC4 expression profiles in pan-cancer, we firstly conducted expression analysis of NPLOC4 in 33 types of tumors and 31 types of normal corresponding tissues from TCGA and GTEx database. It was found that the expression of NPLOC4 in tumor tissue was higher than that of the corresponding normal tissue in majority of tumors, as these 19 kinds of tumor: BLCA, BRCA, CESC, CHOL, DLBC, ESCA, GBM, HNSC, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, SKCM, STAD, THYM. On the contrary, there were still 8 tumors: ACC, KICH, LAML, PRAD, READ, TGCT, THCA, UCEC, in which NPLOC4 was down-regulated in tumor than normal tissues (Fig. 1A). The combinatory analysis was not able to conduct due to the lack of normal tissue data for MESO and UVM in GTEx. Analysis of the expression level of NPLOC4 in normal tissues indicated that NPLOC4 expressed highest in muscle, and lowest in pancrea (Fig. 1B). For cancer tissues, NPLOC4 expression was highest in ESCA, and lowest in KICH (Fig. 1C). It was found that in cancer cell line, the expression of NPLOC4 was highest in GBM cells, and lowest in DLBC cells (Fig. 1D). Furthermore, analysis of pan-cancer using the CPTAC datasets showed that the protein expression of NPLOC4 was higher in tumor than normal tissues in colon cancer, lung cancer, pancreatic cancer, head and neck cancer, and liver cancer. Conversely, NPLOC4 was down-regulated in tumor tissues in renal clear cell carcinoma, and glioblastoma (Fig. 1E). For further ascertaining the expression of NPLOC4 comprehensively, we evaluated NPLOC4 expression in tumors and their paired adjacent tissues, which showed that in 11 kinds of tumors NPLOC4 were up-regulated in tumor tissue than paired adjacent tissue (Figure S1A-K), and only KICH had the opposite result (Figure S1L). Then, we compared the expression of NPLOC4 among different TNM stages manifesting NPLOC4 had higher expression in types of tumors at advanced stages (stage III/IV): COAD and UCEC (Figure S2A-B), while NPLOC4 expression was higher in OV, and MESO at early stages (stage I/II) (Figure S2-D). Moreover, we explored the NPLOC4 expression by HPA database for the IHC, indicating that the cancer tissues of colorectal cancer, lung cancer and liver cancer have higher expression than their corresponding normal tissues (Fig. 2A-C). Interestingly, in a variety of tumors, the mRNA expression of NPLOC4 was negatively correlated with methylation, and we speculated that the high expression of NPLOC4 in tumors may be associated with hypomethylation (Figure S3A-X). We also examined the subcellular localization of NPLOC4 using the HPA database, which showed that NPLOC4 was mainly expressed in the nucleus and cytoplasm (Fig. 2D-F). High expression of NPLOC4 is related to poor prognosis of various cancer types In order to explore whether the expression level of NPLOC4 correlated with patient survival, we assessed the role of NPLOC4 in the OS, DFI, DSS, and PFI of patients by Univariate Cox regression analyses. The result of OS analysis suggested that NPLOC4 acted as a risk factor for patients with LGG, KICH, LIHC, MESO, LUAD, SKCM, PCPG, ACC, BLCA, LUSC, UVM, and LAML. On the contrary, NPLOC4 acted as a protective factor for patients with READ (Fig. 3A). The result of DFI analysis showed that NPLOC4 was a risk factor for patients with LUSC, PRAD, ACC, and LIHC (Fig. 3B), and the result of DSS analysis suggested that high NPLOC4 expression indicated poor prognosis for patients with LGG, KICH, LUSC, MESO, PCPG, LIHC, ACC, UVM, and UCEC (Fig. 3C). Additionally, the result of PFI analysis showed that NPLOC4 might be associated with disease progression in LGG, LUSC, ACC, LIHC, UVM MESO, KICH, PRAD, BLCA, and UCEC (Fig. 3D). Moreover, to validate the results mentioned-above, we evaluated the OS, DSS, PFI of patients with cancer in TCGA cohort by Kaplan-Meier method, which demonstrating similar results with Univariate Cox regression analyses generally (Figure S4A-U). NPLOC4 is associated with tumor immune microenvironment Tumor cells, immune cells and stromal cells constitutes the dominant cell classes in TME. Tumor Purity Score and Estimate Score reflect the influence of the tumor microenvironment on tumor progression to some extent. To further explore the impact of NPLOC4 on tumor, we assessed the correlation between NPLOC4 and Tumor Purity Score, Estimate Score, which showed that NPLOC4 was negatively correlated with Estimate Score in 10 kinds of tumors: BRCA, SARC, THCA, LIHC, GBM, THYM, LUAD, ESCA, TGCT, LUSC, and positively correlated with Estimate Score in just 4 types of tumors: UVM, LAML, READ, COAD (Fig. 4A). In addition, NPLOC4 was positively associated with Tumor Purity Score in 10 kinds of tumors: TGCT, LUSC, ESCA, THYM, SARC, GBM, THCA, LIHC, SKCM, BRCA, and negatively associated with Tumor Purity Score in just 4 types of tumors: COAD, READ, LAML, UVM (Fig. 4B). Since the Estimate Score is composed of the Immune Score and Stromal Score, we further analyzed correlations between NPLOC4 and Immune Score, Stroma Score, Estimate Score, Tumor Purity Score at the same time (Fig. 4C). Immune Score had negative correlation with NPLOC4 in numerous tumors, meaning that NPLOC4 was associated with tumor suppressive microenvironment. Then we evaluated the correlation between NPLOC4 and immune cell infiltration using ImmuCellAI database and TIMER database. NPLOC4 was associated with multiple tumor-related immune cells in both two databases. It was found that NPLOC4 was significantly positively correlated with Tregs, neutrophils, monocytes and other suppressive immune cells, and negatively correlated with CD8+T, Tgd, NK, MAIT and other active immune cells in ImmuCellAI database (Fig. 5A), similar results were observed in TIMER database (Fig. 5B). In addition to immune cells, immune molecules also have a great influence on tumor immune microenvironment. We further estimated the correlation between NPOLC4 and immunosuppressive genes, immune activating genes (Fig. 6A-B), MHC-related genes, chemokine genes, and chemokine receptor genes (Fig.7A-C), which were all related to immune status and function. The results indicated that NPOLC4 was strongly correlated with tumor immunosuppressive microenvironment. NPLOC4 is highly expressed in HCC tissues Based on the results of expression, prognosis, and correlation analysis in pan-cancer, NPLOC4 played a huge impact on HCC. Therefore, we focused on the analysis and validation of NPLOC4 in HCC. We firstly verified the expression of NPLOC4 in HCC cell lines and hepatocyte (Fig. 8A), and then validated NPLOC4 expression in cancer tissues, non-cancer tissues of 16 HCC patients using qRT-PCR (Fig. 8B), displaying higher RNA expression of cancer tissues than normal tissues, and then we evaluated the protein expression of NPLOC4 in HCC patients via IHC (Fig. 8C), indicating the protein expression of NPLOC4 was up-regulated in HCC tissues compared with normal tissues. NPLOC4 is associated with tumor suppressive microenvironment in HCC In order to clarify the effect of NPLOC4 in the immune microenvironment of HCC, we evaluated the correlation between NPLOC4 and various immune cells. NPLOC4 was closely associated with the infiltration of most immune cells. The expression of NPLOC4 was positively correlated with multiple suppressive immune cells in HCC, such as neutrophils, iTreg cells, nTreg cells, Tr1 cells, etc. On the contrary, the expression of NPLOC4 was negatively correlated with various activating immune cells in HCC, such as CD8+T, Tc cells, NK cells, MAIT cells, Tgd cells, etc (Fig. 9A-P), supported by previously published studies (Figure S5A-E). The immune score and immune infiltration score were both negatively correlated with NPLOC4 [removed]Fig. 9Q-R). Additionally, NPLOC4 had positive correlation with several immune checkpoints (Fig. 9S). To better illustrate the expression features of NPLOC4 in the HCC microenvironment, we used single cell analysis to more intuitively and accurately indicate that NPLOC4 was widely expressed in a variety of cells and clusters in the HCC microenvironment, especially in some cells related to the tumor suppressive microenvironment (Fig. 10A-D), and it could be proved in single cell sequencing analysis results of multiple LIHC datasets (Fig. 10E). In addition to the strong relationship between NPLOC4 and the immune microenvironment, GSVA analysis showed that NPLOC4 was closely related to multiple metabolic pathways (Figure S6A), and drug sensitivity analysis also indicated that sorafenib resistance was correlated with NPLOC4 expression in HCC (Figure S6B-C). Overall, NPLOC4 associates with the composition and maintenance of suppressive microenvironment of HCC, indicating NPLOC4 is a potential therapeutic target to sensitize immunotherapy.

NPLOC4 is highly expressed in a variety of cancers and usually predicts a poor prognosis. The low DNA methylation level of NPLOC4 is likely to be the mechanism of the high expression of NPLOC4 in tumors. NPLOC4 affects a variety of immune cells in tumor immune microenvironment and is closely related to multiple immune-related genes in pan-cancer and HCC. In summary, NPLOC4 is highly expressed in tumor tissues and influences the modification of immune microenvironment. As a potential therapeutic target, NPLOC4 perhaps plays a vital role in tumor immunotherapy.

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