A hepatocellular carcinoma diagnosis and prognosis marker and its application

Abstract

The present invention relates to the field of bioengineering technology, and discloses a hepatocellular carcinoma diagnosis and prognosis marker and its application, including a hepatocellular carcinoma diagnosis and prognosis marker biomarker, wherein the biomarker is TMEM64, and the expression of TMEM64 is correlated with NK cells, CD8 + The immune cell infiltration levels of T cells and pDCs were significantly negatively correlated, and the GSEA enrichment analysis found that the Wnt / β-catenin, JAK / STAT3, KRAS and P53 signaling pathways were significantly enriched in cells in the high TMEM64 expression group. The present invention found that TMEM64 expression was elevated in liver cancer tissues and cell lines, and its high expression level was associated with poor prognosis of patients; TMEM64 has good diagnostic value for liver cancer. TMEM64 can be used as a good diagnostic and prognostic marker for hepatocellular carcinoma; TMEM64 can promote the proliferation and invasion of liver cancer cells, may be involved in regulating the malignant progression of liver cancer, and is expected to become a molecular marker and potential therapeutic target for the diagnosis and prognosis of liver cancer.

Description

Technical Field

[0001] The present invention relates to the field of bioengineering technology, and in particular to a hepatocellular carcinoma diagnosis and prognosis marker and application thereof. Background Art

[0002] Liver cancer is the sixth most common and third most deadly malignant tumor worldwide. Most liver cancer patients are asymptomatic in the early stages and are diagnosed in the advanced stages, potentially missing the best surgical options. The recurrence rate remains high after surgery, and the prognosis is extremely poor. Early diagnosis and treatment are crucial for improving patients' five-year survival rates. Therefore, the discovery of new diagnostic molecular markers and prognostic predictors is crucial for accurately identifying patients with early-stage liver cancer, enabling improved treatment and a higher five-year survival rate.

[0003] Transmembrane proteins (TMEMs) are a family of proteins that can cross cell membranes multiple times and participate in regulating intercellular signaling. The development and progression of many human diseases are associated with dysfunctional TMEMs. Currently, a large number of TMEMs have been found to be dysregulated in malignant tumors, potentially involved in regulating various pathways involved in tumor invasion and metastasis. Their expression is often significantly correlated with poor patient prognosis. Studies have reported that TMEM106C is highly expressed in liver cancer tissues and is associated with the malignant characteristics and poor prognosis of liver cancer. It may serve as a prognostic marker and potential therapeutic target for liver cancer. TMEM64, a gene located on chromosome 8, belongs to the transmembrane protein family. Studies have shown that TMEM64 can promote prostate tumor progression by regulating WNT3A expression. Currently, there is limited research on TMEM64, and its function in liver cancer has not been reported, requiring further exploration. Therefore, a prognostic marker for hepatocellular carcinoma and its application are proposed. Summary of the Invention

[0004] In order to solve the technical problem that the role of TMEM64 in liver cancer is unclear, the present invention provides a hepatocellular carcinoma diagnosis and prognosis marker and its application.

[0005] The present invention is implemented by the following technical solutions: a biomarker for diagnosis and prognosis of hepatocellular carcinoma, wherein the biomarker is TMEM64;

[0006] The accession number of TMEM64 in the TCGA database (The Cancer Genome Atlas, TCGA) is: >NC_000008.11:c90646083-90621995; its content is: TMEM64 [organism = Homo sapiens] [Gene ID = 169200] [chromosome = 8];

[0007] The accession number of TMEM64 in the GTEx (Genotype-Tissue Expression, GTEx) database is: >NC_060932.1:c91770093-91746004; its content is: TMEM64 [organism=Homo sapiens][GeneID=169200][chromosome=8].

[0008] As a further improvement of the above scheme, the expression of TMEM64 is related to NK cells, CD8 + The immune cell infiltration levels of T cells and pDCs were significantly negatively correlated.

[0009] As a further improvement of the above scheme, the GSEA enrichment analysis found that the Wnt / β-catenin, JAK / STAT3, KRAS and P53 signaling pathways were significantly enriched in the high TMEM64 expression group cells.

[0010] A biological product for diagnosis and prognosis of hepatocellular carcinoma, comprising TMEM64.

[0011] As a further improvement of the above solution, the biological product includes: reagents, kits, and chips.

[0012] A drug for treating liver cancer, comprising: the TMEM64, or an inhibitor of the TMEM64.

[0013] As a further improvement of the above scheme, TMEM64 is used as the target.

[0014] As a further improvement of the above scheme, the inhibitor comprises:

[0015] si-TMEM64#1, whose sequence is: 5′-GCUAUUGUAGCUUGUGAAATT-3′;

[0016] si-TMEM64#2, whose sequence is: 5′-CCUACCCAGCUUCUGAAUUTT-3′.

[0017] As a further improvement of the above solution, the liver cancer treatment drug has at least the following functions:

[0018] Inhibit the proliferation and invasion of liver cancer.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The present invention analyzed the expression level of TMEM64 in liver cancer using a database and found that the expression level of TMEM64 in liver cancer was significantly higher than that in adjacent tissues. TMEM64 has good diagnostic value for liver cancer, and high expression of TMEM64 is associated with poor overall survival in liver cancer patients. Further analysis found that TMEM64 expression level is an independent risk factor for overall survival in liver cancer patients, indicating that TMEM64 is a predictive indicator for the diagnosis and prognosis of liver cancer.

[0021] 2. Enrichment analysis of differentially expressed genes in TMEM64 revealed significant enrichment in pathways related to tumor invasion and metastasis. A nomogram based on OS-independent factors was constructed to predict patients' 1-, 3-, and 5-year prognosis. Subsequently, in vitro experiments investigated the effects of TMEM64 on liver cancer cells and found that knocking down TMEM64 significantly inhibited the proliferation and invasion of HCCLM3 cells, while overexpressing TMEM64 promoted the proliferation and invasion of Huh7 cells.

[0022] 3. Through bioinformatics analysis and in vitro experiments, we will study the expression level, diagnosis, prognosis and biological functions of TMEM64 in liver cancer, providing data support for subsequent liver cancer treatment;

[0023] 4. This study found that TMEM64 expression is elevated in liver cancer tissues and cell lines, and its high expression level is associated with poor prognosis in patients. TMEM64 has good diagnostic value for liver cancer. TMEM64 can promote the proliferation and invasion of liver cancer cells and may be involved in regulating the malignant progression of liver cancer. It is expected to become a molecular marker for the diagnosis and prognosis of liver cancer and a potential therapeutic target. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The figure shows the expression level of TMEM64 in different types of tumors and hepatocellular carcinoma;

[0025] Figure 1 A is a statistical graph showing the expression levels of TMEM64 in various tumors compared with normal tissues in the TCGA and GTEx databases;

[0026] Figure 1 B is a statistical graph of the expression levels of TMEM64 in liver cancer and unpaired normal tissues from the TCGA and GTEx databases;

[0027] Figure 1 C is the expression diagram of TMEM64 in hepatocellular carcinoma and matched normal tissues in the TCGA database;

[0028] Figure 1 D is the ROC curve for the classification of hepatocellular carcinoma and normal liver tissue in the TCGA database;

[0029] Figure 2 This is an analysis chart of the prognostic value of TMEM64 expression in patients with liver cancer evaluated by the Kaplan-Meier method;

[0030] Figure 2 A is an expression graph of the overall survival rate of patients with high and low TMEM64 expression in hepatocellular carcinoma;

[0031] Figure 2 B is the overall survival diagram based on multivariate Cox analysis;

[0032] Figure 3 This is an analytical graph of the prognostic value of TMEM64 in different subgroups of liver cancer patients;

[0033] Figure 3 A is the overall survival curve of patients with liver cancer with high TMEM64 expression in the T1-T3 subgroup;

[0034] Figure 3 B is the overall survival curve of patients with liver cancer with high TMEM64 expression in the N0 subgroup;

[0035] Figure 3 C is the overall survival curve of patients with liver cancer with high TMEM64 expression in the M0 subgroup;

[0036] Figure 3 D is the overall survival curve of patients with liver cancer with high TMEM64 expression in stage I to III subgroups;

[0037] Figure 3 E is the overall survival curve of patients with liver cancer with high TMEM64 expression in the G1-G3 subgroup;

[0038] Figure 3 F is the overall survival curve of patients with liver cancer with high TMEM64 expression in the BMI>25kg / m2 subgroup;

[0039] Figure 3 G is the overall survival curve of patients with liver cancer with high TMEM64 expression in the subgroup aged > 60 years;

[0040] Figure 3 H is the overall survival curve of patients with liver cancer with high TMEM64 expression in the subgroup with a body weight of >70 kg;

[0041] Figure 3 I is the overall survival curve of the male subgroup of patients with liver cancer with high TMEM64 expression;

[0042] Figure 4 This is an analysis of the correlation between TMEM64 expression and immune cell infiltration levels in hepatocellular carcinoma;

[0043] Figure 4 A is a comparison of NK immune cell infiltration levels between high and low TMEM64 expression groups;

[0044] Figure 4 B is a comparison of the CD8+ T immune cell infiltration levels between the high and low TMEM64 expression groups;

[0045] Figure 4 C is a comparison of the pDC immune cell infiltration levels between the high and low TMEM64 expression groups;

[0046] Figure 4 D is the correlation diagram between the relative enrichment of NK immune cells and TMEM64 expression;

[0047] Figure 4 E is CD8 + Correlation diagram between the relative enrichment of T immune cells and TMEM64 expression;

[0048] Figure 4 F is the correlation diagram between the relative enrichment of pDC immune cells and TMEM64 expression;

[0049] Figure 5 The figure shows the analysis of TMEM64-related differentially expressed genes (DEGs) and TMEM64 functional enrichment analysis in hepatocellular carcinoma;

[0050] Figure 5 A is the volcano plot of differentially expressed genes;

[0051] Figure 5 B is a heat map of the correlation between TMEM64 expression and the top 10 differentially expressed genes;

[0052] Figure 5 C is the GO enrichment analysis diagram of DEG;

[0053] Figure 5 D is the KEGG enrichment analysis diagram of DEG;

[0054] Figure 5 E is the gene set enrichment analysis diagram of DEGs;

[0055] Figure 6 The present invention provides an analysis chart of the nomogram and calibration curve for predicting the 1-year, 3-year, and 5-year overall survival rates of patients with hepatocellular carcinoma; wherein:

[0056] Figure 6 A is a nomogram for predicting 1-year, 3-year, and 5-year overall survival rates of hepatocellular carcinoma;

[0057] Figure 6B is the calibration curve of the 1-year nomogram prediction;

[0058] Figure 6 C is the calibration curve of the 3-year nomogram prediction;

[0059] Figure 6 D is the calibration curve of the 5-year nomogram prediction;

[0060] Figure 7 This is an analysis of the ability of TMEM64 knockout to inhibit the proliferation and invasion of hepatocellular carcinoma cells;

[0061] Figure 7 A is an analysis chart of RT-qPCR detection of the mRNA expression level of TMEM6 knocked down in HCCLM3 cells using two si-TMEM64#1 and si-TMEM64#2;

[0062] Figure 7 B is a western blot analysis for detecting the protein expression level of TMEM64 knocked down in HCCLM3 cells using two si-TMEM64#1 and si-TMEM64#2;

[0063] Figure 7 C is a cell clone formation assay analysis diagram used to detect the effect of TMEM64 knockout on HCCLM3 cell proliferation;

[0064] Figure 7 D is a CCK-8 assay analysis diagram used to detect the effect of TMEM64 knockdown on HCCLM3 cell proliferation;

[0065] Figure 7 E is an analysis diagram of the Transwell assay to evaluate the effects of TMEM64 knockdown on HCCLM3 cell migration and invasion abilities;

[0066] Figure 7 F is an analysis diagram of the cell scratch assay to evaluate the effect of TMEM64 knockdown on the migration ability of HCCLM3 cells.

[0067] Figure 8 The present invention provides an analytical map showing that TMEM64 overexpression can promote the proliferation and invasion of hepatocellular carcinoma cells; wherein:

[0068] Figure 8 A is a RT-qPCR analysis of the transfection efficiency of TMEM64 overexpression plasmid in Huh7 cells;

[0069] Figure 8 B is a western blot analysis of the transfection efficiency of TMEM64 overexpression plasmid in Huh7 cells;

[0070] Figure 8 C is a cell clone formation experimental analysis diagram to detect the effect of overexpression of TMEM64 on the proliferation of Huh7 cells;

[0071] Figure 8 D is a CCK-8 assay analysis of the effect of overexpression of TMEM64 on Huh7 cell proliferation;

[0072] Figure 8 E is an analysis diagram of the effect of overexpression of TMEM64 on the proliferation of Huh7 cells detected by EdU experiment;

[0073] Figure 8 F is an analysis of the effect of overexpression of TMEM64 on the migration and invasion ability of Huh7 cells detected by cell scratch assay;

[0074] Figure 8 G is an analysis diagram of the effect of overexpression of TMEM64 on the migration ability of Huh7 cells detected by Transwell assay. DETAILED DESCRIPTION

[0075] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0076] Example 1:

[0077] Detection of TMEM64 expression level in liver cancer

[0078] Based on the TCGA database, the expression level of TMEM64 in pan-cancer was analyzed and it was found that TMEM64 was highly expressed in various malignant tumors (P<0.001). Figure 1 As shown in A; In addition, the expression level of TMEM64 in liver cancer was significantly higher than that in adjacent paracancerous tissues in both unpaired and paired samples (P<0.001). Figure 1 BC; The receiver operating characteristic curve (ROC) showed that TMEM64 had a good diagnostic value for liver cancer, and the area under the ROC curve (AUC) was 0.723 (95% confidence interval [CI] = 0.672-0.773). Figure 1 As shown in D.

[0079] Example 2:

[0080] Kaplan-Meier analysis was used to evaluate the prognostic value of TMEM64 expression in patients with liver cancer

[0081] According to the median expression of TMEM64, HCC patients were divided into TMEM64 high expression group (n=187) and low expression group (n=186); Figure 2 A shows that compared with the TMEM64 low expression group, the patients in the MCTS1 high expression group had a worse OS (OS: hazard ratio [HR] = 1.58, 95% CI = 1.11–2.25, P = 0.011); Figure 2 As shown in B, multivariate Cox proportional hazards regression analysis showed that the expression level of TMEM64 was an independent risk factor for overall survival of patients with liver cancer (OS: hazard ratio [HR] = 1.693, 95% CI = 1.087–2.638, P = 0.02);

[0082] Table 1 shows the univariate and multivariate Cox proportional hazards regression analysis of overall survival in patients with liver cancer:

[0083]

[0084]

[0085] Among them, high expression of TMEM64 and tumor T stage T1-T3 are independent risk factors for poor prognosis in patients with liver cancer.

[0086] Example 3:

[0087] The Kaplan-Meier method was used to evaluate the prognostic value of TMEM64 expression levels in different subgroups of liver cancer patients

[0088] like Figure 3 As shown in the results, compared with patients with low TMEM64 expression, patients with liver cancer with high TMEM64 expression had significantly worse prognosis in T1-T3, N0, M0, stage I-III, G1-G3, BMI>25kg / m2, age>60 years, weight>70kg, and male subgroups (all P values ​​< 0.05).

[0089] Example 4:

[0090] Testing the correlation between TMEM64 expression level and immune cell infiltration level in liver cancer tissues

[0091] like Figure 4 As shown in AC, the enrichment scores of NK cells, CD8 + T cells, and pDCs in liver cancer tissues in the TMEM64 high expression group were significantly lower than those in the TMEM64 low expression group; Figure 4 As shown in DF, the expression of TMEM64 was significantly negatively correlated with the immune cell infiltration levels of NK cells (r=-0.138, P=0.007), CD8+ T cells (r=-0.114, P=0.027) and pDCs (r=-0.321, P<0.001).

[0092] Example 5:

[0093] Functional enrichment analysis of TMEM64-related differentially expressed genes

[0094] First, the expression of related differential genes in the TMEM64 high expression group and low expression group were compared, such as Figure 5 As shown in A;

[0095] like Figure 5 As shown in B, the top ten differentially expressed genes are HS3ST4, MAGEA4, AC016717.2, ANKFN1, CYP11B2, SH3GL3, AC062015.1, PPDPFL, CCR3, and ISM2.

[0096] GO enrichment analysis showed that the biological processes significantly enriched by DEGs included regulation of chemical synaptic transmission, signal release, receptor ligand activity, and regulation of transsynaptic signal transmission, such as Figure 5 As shown in C;

[0097] KEGG pathway enrichment analysis showed that the pathways significantly enriched by DEGs included the interaction between neuroactive ligands and receptors, Wnt signaling pathway, and MAPK signaling pathway, such as Figure 5 As shown in D;

[0098] GSEA enrichment analysis found that Wnt / β-catenin, JAK / STAT3, KRAS and P53 signaling pathways were significantly enriched in the high TMEM64 expression group. Figure 5 As shown in E.

[0099] Example 6:

[0100] Construction and validation of TMEM64 expression-based nomograms and calibration curves

[0101] To accurately predict the prognosis of patients with liver cancer, a nomogram based on OS independent factors was generated based on the relevant clinical variables (TMEM64 expression level and T stage) in the multivariate Cox risk regression analysis to predict the patients' 1-year, 3-year, and 5-year prognosis;

[0102] In the Nomogram, the higher the total number of points, the worse the prognosis, e.g. Figure 6 As shown in Figure A; In addition, the calibration curve was used to evaluate the predictive effect of the nomogram; the bootstrap-corrected C index of the nomogram was 0.644 (95% CI = 0.618–0.67), indicating that the model had moderate predictive accuracy for the OS of patients with liver cancer, among which the model accuracy and consistency of the 5-year OS of patients were better, as shown in Figure 4. Figure 6 As shown in B–D.

[0103] Example 7:

[0104] Knockdown of TMEM64 inhibits the proliferation and invasion of HCCLM3 cells

[0105] The knockdown efficiency of si-TMEM64#1 and si-TMEM64#2 was verified using RT-qPCR and Western blots. Figure 7 As shown in AB, the knockdown efficiency of si-TMEM64#1 was the most obvious;

[0106] The results of cell clone formation, CCK-8 and EdU experiments showed that knocking down TMEM64 could significantly inhibit the proliferation of HCCLM3 cells. Figure 7 As shown in CE;

[0107] Cell scratch and Transwell assays showed that the migration and invasion abilities of HCCLM3 cells in the si-TMEM64#1 and si-TMEM64#2 groups were significantly reduced compared with those in the control group. Figure 7 As shown in FG.

[0108] Example 8:

[0109] Overexpression of TMEM64 promotes the proliferation and invasion of Huh7 cells

[0110] Compared with the empty vector group, the expression level of TMEM64 in Huh7 cells was significantly increased after transfection of TMEM64 overexpression plasmid. Figure 8 As shown in AB;

[0111] The results of CCK-8, cell clone formation and EdU experiments showed that overexpression of TMEM64 could significantly promote the proliferation of Huh7 cells. Figure 8 As shown in CE;

[0112] Cell scratch and Transwell assays showed that the migration and invasion abilities of Huh7 cells in the TMEM64 overexpression group were significantly enhanced compared with those in the control group. Figure 8 As shown in FG.

[0113] Example 9:

[0114] Database analysis

[0115] mRNA expression profiles and clinical data of HCC patients were collected from the TCGA database (n=377) and the GTEx database. Level 3 HTSeq FPKM format data were normalized to transcripts per million reads (TPM). RNA sequencing data in TPM format were obtained from the UCSC Xena3 database and the GTEx database for analysis.

[0116] The TMEM64 gene is identified in the TCGA database as: >NC_000008.11:c90646083-90621995; its content is: TMEM64 [organism = Homo sapiens] [Gene ID = 169200] [chromosome = 8];

[0117] The TMEM64 gene is accessed in the GTEx database as: >NC_060932.1:c91770093-91746004; its content is: TMEM64 [organism = Homo sapiens] [GeneID = 169200] [chromosome = 8];

[0118] Kaplan-Meier curves and log-rank tests were used to compare patient survival differences, with the cutoff value set at the median expression level of TMEM64. Univariate and multivariate Cox regression analyses were used to assess the impact of clinical variables on patient outcomes. Prognostic variables with P < 0.05 in the univariate Cox regression analysis were included in the multivariate Cox analysis.

[0119] The R package DESeq2 was used to analyze and calculate differentially expressed genes (DEGs), and the adjusted P value was set to <0.05 and |log2 fold change (FC)|>1 as the threshold for DEGs. Spearman correlation analysis was used to assess the correlation between the expression of the top 10 DEGs and TMEM64.

[0120] Functional enrichment analysis of DEGs was performed using the R package GOplot and the R package clusterProfiler, and adjusted P values ​​< 0.05 and false discovery rates (FDR) < 0.25 were considered statistically significantly enriched functions or pathways;

[0121] The R package rms was used to construct nanograms and calibration curves. Independent risk factors for overall survival (OS) in patients with liver cancer were assessed using a Cox proportional hazards regression model. A nanogram was constructed to predict 1-, 3-, and 5-year OS in patients with liver cancer, combining TMEM64 expression levels with clinical variables in a multivariate Cox regression model. Calibration curves were used to evaluate the performance of the nomogram.

[0122] Example 10:

[0123] Experimental Materials

[0124] Hepatocellular carcinoma cell lines HCCLM3 and Huh7 were obtained from the Cell Resource Center of the Chinese Academy of Sciences; total RNA extraction reagent TRIzol and transfection reagent Lipofectamine TM 3000 was purchased from Invitrogen, USA, and the RT-qPCR kit was from Beijing Tiangen Biochemical Technology Co., Ltd.; Transwell chambers and the 6-well and 96-well plates used in the experiment were purchased from Corning, USA, and Matrigel was purchased from BD; the Cell Counting Kit-8 (CCK-8) kit was from Shanghai Beibo Biotechnology Co., Ltd., and the 5-Ethynyl-2'-deoxyuridine (EdU) kit was purchased from Guangzhou Ruibo Biotechnology Co., Ltd.; TMEM64 siRNA and overexpression plasmids were designed and constructed by Shanghai Jima Pharmaceutical Technology Co., Ltd., where the siRNA sequences for knockdown of TMEM64 were: si-TMEM64#1: 5′-GCUAUUGUAGCUUGUGAAATT-3′, si-TMEM64#2: 5′-CCUACCCAGCUUCUGAAUUTT-3′; the main reagents used in the Western blot experiment were as follows: BCA kit (Shanghai Biyuntian Biotechnology Co., Ltd.), TMEM64 antibody (Abcam), β-tubulin (Cell Signaling Technology) and ultrasensitive ECL luminescent liquid (Abbkine).

[0125] Example 11:

[0126] 1. Experimental Methods

[0127] Cell culture and transfection

[0128] The cells were cultured in DMEM high-glucose medium (containing 100 U / ml penicillin and 100 μg / ml streptomycin) supplemented with 10% fetal bovine serum in a constant temperature incubator (37°C, 5% CO2). When the cell density reached approximately 60-70%, subsequent procedures were performed according to the Lipofectamine™ 3000 instructions.

[0129] RT-qPCR experiments

[0130] Total RNA was extracted from cultured cells using TRIzol reagent, and then cDNA was synthesized using FastKing one-step genomic cDNA first-strand synthesis premix reagent. The synthesized cDNA was amplified by real-time PCR on the ABIQuantStudio3 system (Applied Biosystems, Singapore) using SuperReal fluorescent quantitative premix reagent. -ΔΔct The relative expression levels of TMEM64 and the internal control GAPDH were calculated by quantitative method; the primer sequences of TMEM64 were: Forward primer: 5′-GGCGTGGCTGAGGTGAGAAA-3′; Reverse primer: 5′-ATGAAGCCCACGACGAAGAG-3′; the primer sequences of GAPDH were: Forward primer: 5′-AATCCCATCACCATCTTCC-3′; Reverse primer: 5′-CATCACGCCACAGTTTCC-3′;

[0131] CCK-8 assay

[0132] The transfected cells and control cells were digested and centrifuged, and 2 × 10 3 The cells were seeded in 96-well plates at 450 nm using a microplate reader at 24, 48, 72, and 96 hours. 10 μl of CCK-8 reagent was added to each well 2 hours before each assay and the cells were placed in an incubator protected from light. The cell proliferation levels at different time periods were calculated.

[0133] Cell clone formation assay

[0134] After transfection, the cells were divided into 2 × 10 3 Each well was evenly seeded in a new 6-well plate and incubated in an incubator for 12 days. When the cells were collected, they were fixed with 4% paraformaldehyde for 30 minutes and stained with 0.1% crystal violet for 1 hour. Finally, the cells were photographed and the level of cell proliferation was statistically analyzed.

[0135] EdU experiments

[0136] The EdU kit from RiboBio was used to detect cell proliferation. The experimental and control groups were seeded uniformly in 96-well plates at 6,000 cells per well. After incubation for 2 hours with 50 mM reagent A, the cells were fixed in 4% paraformaldehyde and stained with Apollo stain for 30 minutes. The cell nuclei were then stained with Hoechst 33342 for half an hour. Finally, the proliferating positive cells were photographed and counted under a fluorescence microscope (200×).

[0137] Transwell experiment

[0138] For the cell invasion assay, 50 μl of matrigel was evenly spread in the upper chamber of the Transwell chamber in advance. The transfected cells and the control group cells were resuspended in serum-free medium and re-counted. The number of cells was calculated as 5×10 4 Cells were transplanted from 100 μl of culture medium containing 10% fetal bovine serum into the upper chamber of the chamber, and 600 μl of culture medium containing 10% fetal bovine serum was added to the lower chamber. The cells were cultured in a cell incubator for 24 hours, fixed with 4% paraformaldehyde, and stained with 0.1% crystal violet for 1 hour. Finally, the cells were photographed under an electron microscope (200×) and the percentage of cell migration was statistically analyzed. Matrigel was not required for the cell migration assay, and the other steps were the same as for the cell invasion assay.

[0139] Cell scratch assay

[0140] The treated cells were evenly plated into a 6-well plate. After the cells were almost fully grown, a straight line was scratched in the 6-well plate using a yellow pipette tip. After washing with PBS, the plate was photographed under an electron microscope to record the area of ​​the scratch at 0 h. 2 ml of serum-free medium was added to the 6-well plate and continued to be incubated. After 48 h, the area of ​​the healed scratch was photographed again under an electron microscope (200×) to record the area. The ratio of the healed area was analyzed and calculated, and the migration ability of the two groups of cells was evaluated.

[0141] Western blot experiments

[0142] The cells were lysed and total protein was extracted. Protein concentration was determined using the BCA assay. An appropriate amount of loading buffer was added and the cells were boiled for 10 minutes. Equal amounts of protein from each sample were subjected to SDS-PAGE electrophoresis and wet-transferred to a PVDF membrane. After blocking with TBST buffer containing 5% skim milk powder at room temperature for 2 hours, the PVDF membrane was incubated with proportionally diluted primary antibodies overnight at 4°C. After rinsing three times with TBST, the PVDF membrane was incubated with secondary antibodies at room temperature for 2 hours. Finally, the membrane was exposed and developed using an ultrasensitive ECL colorimetric solution.

[0143] Statistical methods

[0144] GraphPad Prism 8.0 software was used to perform statistical analysis of the experimental results. The counting results between the experimental and control groups were analyzed and evaluated using independent sample t-test. Each experiment was repeated three times. P < 0.05 was considered statistically significant.

[0145] The study analyzed the expression of TMEM64 in liver cancer using a database and found that TMEM64 expression in liver cancer was significantly higher than in adjacent adjacent tissues. Furthermore, high TMEM64 expression was associated with poor overall survival in liver cancer patients. Further analysis revealed that TMEM64 expression was an independent risk factor for overall survival in liver cancer patients, indicating that TMEM64 is a predictor of poor prognosis and clinical metastasis in liver cancer.

[0146] Enrichment analysis of differentially expressed genes in TMEM64 revealed significant enrichment in pathways related to tumor invasion and metastasis. A nomogram based on OS-independent factors was constructed to predict patients' 1-, 3-, and 5-year prognosis. Subsequently, in vitro experiments investigated the effects of TMEM64 on liver cancer cells and found that knocking down TMEM64 significantly inhibited the proliferation and invasion of HCCLM3 cells, while overexpressing TMEM64 promoted the proliferation and invasion of Huh7 cells.

[0147] Through bioinformatics analysis and in vitro experiments, the expression level, prognosis, and biological function of TMEM64 in liver cancer were confirmed, providing data support for subsequent liver cancer research and diagnosis;

[0148] In summary, this study found that TMEM64 expression is elevated in liver cancer tissues and cell lines, and its high expression level is associated with poor prognosis in patients; TMEM64 has good diagnostic value for liver cancer; TMEM64 can promote the proliferation and invasion of liver cancer cells, and may be involved in regulating the malignant progression of liver cancer, and is expected to become a molecular marker for the diagnosis and prognosis of liver cancer and a potential therapeutic target.

[0149] The above embodiments are only preferred embodiments of the present invention and cannot be used to limit the scope of protection of the present invention. Any non-substantial changes and replacements made by technicians in this field on the basis of the present invention fall within the scope of protection required by the present invention.

Claims

1. Use of a primer pair for detecting a biomarker in the preparation of a product for diagnosis and prognosis of hepatocellular carcinoma, characterized in that: The biomarker is TMEM64; The forward primer of the primer pair is: 5′-GGCGTGGCTGAGGTGAGAAA-3′ The reverse primer of the primer pair is: 5′-ATGAAGCCCACGACGAAGAG-3′.

2. The use according to claim 1, characterized in that The expression of TMEM64 is related to NK cells, CD8 + The immune cell infiltration levels of T cells and pDCs were significantly negatively correlated.

3. The use according to claim 1, characterized in that Wnt / β-catenin, JAK / STAT3, KRAS and P53 signaling pathways were significantly enriched in the TMEM64 expression group cells.

Images