- Research
- Open access
- Published:
Transcriptional analysis of the expression and prognostic value of lipid droplet-localized proteins in hepatocellular carcinoma
BMC Cancer volume 23, Article number: 677 (2023)
Abstract
The accumulation of lipid droplets (LDs) in hepatocytes is the main pathogenesis in nonalcoholic fatty liver disease (NAFLD), which is also the key risk factor for the progression of hepatocellular carcinoma (HCC). LDs behaviors are demonstrated to be associated with HCC advancement, and are tightly regulated by a subset protein localized on the surface of LDs. However, the role of LDs-localized protein in HCC has been rarely investigated. This study is focused on the transcriptional dynamic and prognostic value of LDs-localized protein in HCC. Firstly, we summarized the known LDs-localized proteins, which are demonstrated by immunofluorescence according to previous studies. Next, by the use of GEPIA/UALCAN/The Human Protein Atlas databases, we screened the transcriptional change in tumor and normal liver tissues, and found that 13 LDs-localized proteins may involve in the progression of HCC. Then we verified the transcriptional changes of 13 LDs-localized proteins by the use of HCC samples. Moreover, based on the assays of fatty liver of mice and human NAFLD liver samples, we found that the hepatic steatosis mainly contributed to the transcriptional change of selected LDs-localized proteins, indicating the involvement of these LDs-localized proteins in the negative role of NAFLD in HCC progression. Finally, we focused on the role of PLIN3 in HCC, and revealed that NAFLD status significantly promoted PLIN3 transcription in HCC tissue. Functional studies revealed that PLIN3 knockdown significantly limited the migration and chemosensitivity of hepatoma cells, suggesting the positive role of PLIN3 in HCC progression. Our study not only revealed the transcriptional change and prognostic value of lipid droplet-localized proteins in HCC, but also built the correlation between HCC and hepatic steatosis.
Introduction
Primary liver cancer, which is the seventh most frequently occurring type of cancer in the world, is the second most common reason of cancer mortality. Globally, hepatocellular carcinoma (HCC) is the dominant type of liver cancer, accounting for approximately 75% of the total liver cancer [1]. Because of the poor prognosis in all regions of the world, the incidence and mortality rates of HCC are roughly equivalent [2]. The occurrence and development of HCC can be induced by many factors, mainly including chronic hepatitis B and C (HBV, HCV), alcohol-related chronic liver disease, nonalcoholic fatty liver disease (NAFLD) and some other dietary factors [1]. Although HBV and HCV remain the most important risk factors for HCC at present, the prevalence of them should decline in the coming years due to vaccination and more effective treatment of both HBV and HCV carriers. Therefore, because of the increasing prevalence, NAFLD may gradually overtake the vital factor as the major cause of HCC all over the world [3, 4].
NAFLD usually begins with the accumulation of triglycerides in the liver, then further develops into nonalcoholic steatohepatitis (NASH), progresses to cirrhosis, and finally advances into HCC [5]. Previous studies mainly inclined to investigate the role of NAFLD in HCC tumorgenesis. Recently, the accompanying effects of NAFLD in HCC progression and immunotherapy have been reported increasingly [6]. Moreover, compared with other factors, NAFLD-associated HCC patients have shorter survival time, more advanced tumor stage, higher mortality and worse prognosis [7]. Therefore, it is of great clinical significance and social value to study the pathogenesis of NAFLD-associated HCC and further explore new drug targets for improving its diagnosis and treatment.
The most obvious feature of NAFLD is lipid metabolism dysfunction, which is closely related to a variety of liver diseases, including NAFLD-associated HCC [8, 9]. As important parts of lipid metabolism, LDs are existing as highly dynamic organelles, which are involved in the storage, transportation and metabolism of lipids [10]. LDs play important roles in the occurrence and development of NAFLD, and their continuous accumulation can further cause oxidative stress and inflammatory reaction in the liver, lead to sustained liver damage, and progress to more advanced states, such as NASH, fibrosis, and even HCC [11]. Notably, LDs accumulation in NAFLD-induced hepatoma or hepatoma occurrence accompanying NAFLD is common in the clinical practice, and it has been considered as main risk factors in HCC progression. Furthermore, it can also provide lipid substrate and energy sources for proliferation, migration and invasion of cancer cells [12]. In addition, some studies have shown that the accumulation of LDs can reduce drug-induced apoptosis and immunogenic cell death, leading to the chemoresistance of cancer cells [13, 14]. For now, although LDs have been considered to be important in the occurrence and development of HCC [15], the specific roles of LDs localized proteins in HCC are rarely investigated.
The function of LDs in cells is partly depends on LDs localized proteins, which can be divided into four categories: structural proteins, membrane transporters, enzymes and other proteins, such as histones, ribosomal proteins and signaling proteins [16]. The biological processes that LDs localized proteins participate in include lipid metabolism, redox metabolism, autophagy, gene transcription, ubiquitination, membrane transportation and immunity [17]. Some studies have shown that the abnormal expression of LDs localized proteins could lead to the aberrant accumulation and disorder function of LDs, which have been considered as new hallmarks of cancer [18, 19]. Although some studies have revealed that some LDs localized proteins has aberrant transcription and prognostic value in HCC, such as ACSL3 [20], HSD17B13 [21] or Rab10 [22], there are still few studies focusing on the panoramic value of LDs localized proteins in HCC progression, especially in NAFLD-accompanying HCC.
In this study, we firstly summarized the immunofluorescence-verified LDs localized proteins according to previous studies. Then we analyzed the transcriptional change and prognostic value of these LDs localized proteins, and found that 13 of them differentially expressed in HCC tissues, and had a high correlation with the prognosis of HCC patients. Moreover, we found the hepatic steatosis may contribute to the transcriptional change of the selected proteins. Furthermore, we took PLIN3 as the object to explore its function in the behavior of hepatoma cells. It has been found that PLIN3 could affect the invasion and chemosensitivity of hepatoma cells, indicating the participation of PLIN3 and other LDs localized proteins in HCC progression. Our studies not only provided evidences of the potential function of LDs localized proteins in hepatoma, but also revealed that these LDs localized proteins may be the key risk factors in the progression of NAFLD-accompanying hepatoma. Targeting to these LDs localized proteins may be a new therapeutic strategy for the precision medicine of NAFLD-accompanying HCC in the future.
Materials and methods
Literature search for selecting lipid droplet-associated factors
To determine the proteins present in lipid droplets, we conducted a comprehensive review of scholarly literature using the Google Scholar and PubMed databases. Our search utilized the keyword “lipid droplet localized protein” and was last updated in December 2022. Our selection criteria for protein inclusion extended beyond MS-identification and encompassed immunofluorescence evidence demonstrating co-localization of the protein and lipid droplets. Through careful analysis and interpretation of the articles retrieved, we were able to identify and select 38 proteins exhibiting immunofluorescence evidence of co-localization with lipid droplets.
GEPIA (Gene expression profiling interactive analysis)
The gene expression profiling in HCC tumor and normal tissues and overall survival analysis were obtained from the GEPIA platform (http://gepia.cancer-pku.cn/), which is an online resource for gene expression analysis based on bulk tumor an normal samples based on TCGA and GTEx databases [23]. Our analysis included 369 liver cancer samples and 50 normal liver tissue samples. The mRNA expression profiles of selected LDs localized proteins were generated between liver cancer and normal tissues, and the statistical analysis was performed through the plug-in units of GEPIA. Furthermore, they were also analyzed for overall survival (OS) by using the Kaplan-Meier survival plots tool in the GEPIA platform.
UALCAN
UALCAN (http://ualcan.path.uab.edu), an interactive online database based on RNA-seq and clinical data of 31 cancer types for in-depth analysis of TCGA database [24]. Our research used UALCAN to analyze the mRNA expression of the selected LDs localized proteins in different tumor grades and tumor stages of HCC patients. Differences in transcriptional expression were compared by Student’s t-test, and the statistically significant was represented by *p < 0.05, **p < 0.01, and ***p < 0.001.
Survival analysis
An investigation was conducted on the prognostic value of 12 genes selected for HCC patients, utilizing the TCGA database. The TCGA database of liver hepatocellular carcinoma (LIHC) contains RNA-Seq data for 374 HCC patients and 50 normal tissues (https://portal.gdc.cancer.gov/) for gene expression and immune system infiltrates. We determined the correlations between mRNA levels of LD-associated proteins expression and the survival of HCC patients using the KM Plotter (http://www.kmplot.com) (accessed on 18 December 2021) databases. Additionally, a time-dependent receiver operating characteristic (ROC) analysis (including 1-, 3-, and 5-year survival) was conducted to evaluate selected gene sensitivity and specificity using the R package “survival ROC” based on the TAGA dataset.
Patients and specimens
The liver tissue cohort (liver normal tissues, NAFL tissues, HCC tissues with or without NAFL) in this study was obtained from the patients who underwent surgical resection at the Third Affiliated Hospital of Sun Yat-sen University from January 2013 to December 2016. The patients neither had any history of other malignancies nor received any treatment when enrolled. All experimental procedures complied with the experimental management regulations of the State Council of the People’s Republic of China, and strictly follow China’s GCP, the “Declaration of Helsinki” and relevant Chinese laws and regulations. The usage of the clinical samples and methods in this study was carried out in accordance with the approved guidelines by the Third Affiliated Hospital of Sun Yat-Sen University, and written informed consent to participate in the study was obtained from all subjects. Informed consent forms were signed by all study participants. The protocol was approved by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University. All of the collected tissues were used for RNA extraction and qRT-PCR, immunohistochemistry, and western blot, respectively.
RNA extraction and qRT-PCR analysis
RNA from fresh frozen tissues was extracted by TRIzol™ reagent (Thermo Fisher, 15,596,026, USA). Reverse transcription was performed with Random Hexamer Primer and RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher, k1622, USA) according to the manufacturer’s instruction, and the resulting cDNAs were subjected to qRT-PCR analysis with FastStart SYBR Green Master (Roche, 04673484001, Germany) in LightCycler 96 Real-Time PCR system (Roche, D10013, Germany). The amplification primers were purchased from Sangon Biotech, China. The expression levels were normalized to those of RPL13A. The amplification primers were as follow:
Gene Name | Forward Primer (5’ to 3’) | Reverse Primer (5’ to 3’) |
---|---|---|
ACSL3 | GCCGAGTGGATGATAGCTGC | ATGGCTGGACCTCCTAGAGTG |
AIFM2 | GTGAGCGGGTGAGCAATCT | CTTGATGCCGGTGCAGAGAA |
CIDEB | CAGCGACCTTTCCGTGTCT | GGGTCTCCAATGCTTTGGCT |
G0S2 | CCTGATGGAGACTGTGTGCAG | CCTGCTGCTTGCCTTTCTC |
HILPDA | AAGCATGTGTTGAACCTCTACC | TGTGTTGGCTAGTTGGCTTCT |
HSD17B7 | ATCTGGACATCATCTCGCAGT | AAGAGCTGTAGGGTTCCTTGC |
HSD17B13 | CTCATCCCATATTGTTCCAGCAA | AGGCCATAATCTTGTGCTTGG |
LPCAT1 | TTACCTTCAAACCTGGTGCATT | CGTGAGCCACAGGATTTCC |
LSS | ACATTGAGGATAAGTCCACCGT | TCGTACCAGGTCAGGATCGTC |
PLIN1 | TGTGCAATGCCTATGAGAAGG | AGGGCGGGGATCTTTTCCT |
PLIN2 | ATGGCATCCGTTGCAGTTGAT | GGACATGAGGTCATACGTGGAG |
PLIN3 | GCCCAAGAGATGGTGTCTAGC | CCGGTCACTACGGACTTTGT |
RAB10 | CTGCTCCTGATCGGGGATTC | TGATGGTGTGAAATCGCTCCT |
RPL13A | GCCATCGTGGCTAAACAGGTA | GTTGGTGTTCATCCGCTTGC |
Immunohistochemistry (IHC) and Immune scores
Representative immunohistochemistry of selected LDs localized proteins between liver cancer and normal liver tissues was obtained from The Human Protein Atlas (http://www.proteinatlas.org/).
PLIN3 IHC staining was performed as described before [25]. In brief, the liver sections were deparaffinized, hydrated, and incubated with 3% hydrogen peroxide solution to quench the endogenous peroxidase activity, followed by antigen retrieval in 10 mM citrate buffer (pH = 6.0) at 95℃ and blocked in 5% BSA (Solarbio, SW3015, China) at room temperature to prevent nonspecific binding. Subsequently, the sections were incubated with the primary rabbit polyclonal antibody anti-PLIN3 (20 µg/ml, Abcam, ab47638, UK) overnight at 4℃. The secondary antibody (HRP-conjugated goat anti-rabbit IgG, 1:500 dilution, Beyotime, A0208, China) was added at room temperature, and then the sections were developed with 3, 3’-diaminobenzidine (DAB) (Beyotime, P0203, Chine) for staining.
The immune scores were blindly calculated by different individuals using the staining intensity multiplied by the cell percentage (+) %*1 + (++) %*2 + (+++) %*3. + indicates a weak staining signal; ++ indicates a medium staining signal; +++, indicates a strong staining signal.
Western blot analysis
Total protein of each sample (tissues or cell lysates) was obtained by using RIPA lysis buffer (Solarbio, R0010, China) and quantified by performing BCA protein assay kit (Solarbio, PC0020, China). After denaturation, an equal amount of protein from each sample was separated on SDS-PAGE gel and transferred to a methanol-activated PVDF membrane (Merk Millipore, ISEQ00010, USA) by electroblotting. The membrane was then blocked in 5% nonfat milk powder in 10 mM PBS buffer at 4℃ overnight. The blocked membrane was then incubated sequentially with the diluted primary antibodies PLIN3, (Abcam, ab47638, UK); c-PARP (Cell Signaling Technology, 5625, USA); c-Caspase 3 (Cell Signaling Technology, 9664, UK); β-Actin (Proteintech, 66009-1-Ig, China); β-tubulin, (Proteintech, 10094-1-AP, China) and HRP-conjugated second antibody (Beyotime, A0208, China). Finally, the immunoreactive protein bands were detected by BeyoECL Plus kit (Beyotime, P0018S, China) according to the manufacturer’s instructions. The original western blot bands were provided in the supplemental information.
Cell culture and transfection
Human HCC cell lines, HepG2 and LM3 were obtained from the Cell Bank of the Chinese Academy of Science, Shanghai, China. They were cultured in DMEM medium (Procell, PM150210, China) containing 10% fetal bovine serum (ExCell, FSP500, China) and 100 U/ml penicillin/streptomycin (Hyclone, SV30010, USA) in a 5% CO2 humidified incubator at 37℃.
PLIN3 silencing was achieved by the transfection of a specific lentiviral vector containing a short hairpin RNA (shRNA) targeting PLIN3 (Hanbio Tech, China) combined with Lipofiter™ (Hanbio Tech, China). The selection for PLIN3 sh-RNA or negative control transfected cells were processed by using puromycin at 2 µg/ml. The target sequences for PLIN3 were exhibited as follows:
NC: 5’-TTCTCCGAACGTGTCACGTAA-3’;
PLIN3-sh1: 5’-ACCGTGTGGCCAGCATGCCTCTGAT-3’;
PLIN3-sh2: 5’-CCAAGGAGAGCTACCCGCACATCAA-3’.
Cell proliferation, Migration and Invasion assays
Cell proliferation performed by Cell Counting Kit-8 (CCK-8) assay, 4 × 103 HepG2 and LM3 negative control cells or PLIN3 knockdown cells were respectively cultured in 96-well plates and incubated with Cell Counting Kit-8 (Beyotime, C0038, China) for 2 h at 37℃. Cell viability was measured with the absorbance at the wavelength of OD450 nm on a spectrophotometer at 0 h, 24 and 48 h. The chemosensitivity of PLIN3 knockdown cells was tested by the treatment with sorafenib (Selleck, S7397, China), doxorubicin (Selleck, E2516, China), or cisplatin (Selleck, S1166, China) at 0 µM, 0.1 µM, 1 µM, 10 µM and 50 µM for 48 h, and the cell viability was measured as described before.
Cell migration and invasion assays were performed by using the transwell chambers with 8-µm pores (Corning, 3422, USA) coated without or with the Matrigel (BD, 356,234, USA) (1:40 diluted by DMEM medium) respectively. 3 × 104 cells mixed in DMEM medium without FBS were plated into the upper sections, and DMEM medium with 10% FBS was loaded in the lower chambers. The chambers were then incubated for 24 h and after the fixation with paraformaldehyde for 20 min, the cells were stained with crystal violet for 15 min and then counted by using optical microscope.
NASH model
Total 12 six-week old C57BL/6 mice were randomly divided into control and experimental groups (6 per group) treated with CSAA (Dyets, 518,754, USA) and CDAA (Dyets, 518,753, USA) feed respectively. After one week acclimatization, the experimental group was to be fed with the transitional feed for one week. During this transitional stage, the CSAA and CDSS feeds were mixed at 2:1 on the first three days, 1:1 on the fourth to fifth days, 1:2 on the sixth to seventh days, and CDAA feed was completely added after this period. At the 6th week after transitional feeding, the animals of each group were sampled. The pathological feature and steatosis of the mouse livers were confirmed by H&E staining and Oil red staining, respectively. Furthermore, mRNA expression of the selected LDs localized proteins was examined by the transcriptome.
Statistical analysis
Data were analyzed by Student’s t-test using the GraphPad Prism 7 (San Diego, USA). The significance was set at *p < 0.05, **p < 0.01, and ***p < 0.001.
Results
The summarization of LDs localized proteins verified by immunofluorescence
Although many studies identified the LDs-associated proteins by using of mass spectrum, only few proteins have been demonstrated to localize on the surface of LDs, which is key to participate in the regulation of LDs’ dynamic. To identify the verified protein localized on lipid droplet, we performed a literature mining in the previous publications related to lipid droplet-associated proteins verified by immunofluorescence (last search date: December 2022) (Table 1). Next, we performed transcriptional analysis of these proteins which differentially expressed in HCC.
Transcriptional level of lipid droplets localized genes in liver hepatocellular carcinoma
To identify the role of LDs localized proteins, we performed a transcriptional analysis of these proteins in the GEPIA database and selected 13 LDs localized proteins which were differentially expressed in liver normal and tumor tissues. Based on GEPIA platform, we further analyzed the transcriptional levels of selected lipid droplets localized genes in patients with HCC. Data from GEPIA showed that 8 genes (ACSL3, AIFM2, HILPDA, HSD17B7, LPCAT1, LSS, PLIN3, and RAB10) were up-regulated, and 5 genes (CIDEB, G0S2, HSD17B13, PLIN1, and PLIN2) were down-regulated in bulk LIHC tissues (n = 369) compared with the adjacent normal tissues (n = 50) (Fig. 1A). Furthermore, we applied q-PCR to validate the expression of these genes in hepatoma tissue of HCC patients collected by our group. The result indicated that the expression patterns of selected 13 lipid droplets localized genes were consistent with the data from GEPIA (Fig. 1B). We further analyzed the protein expression of the 13 selected lipid droplets localized genes on the Human Protein Atlas database. The representative immunohistochemistry pictures and the IHC scores were shown in Fig. 2. The IHC information of G0S2 and PLIN2 were not found in this database. Altogether, these data revealed that 13 proteins among the selected cohort of LDs localized proteins have transcriptional change in HCC, indicating that the selected proteins may have function in the progression of HCC, and may correlated with the prognosis of HCC patients.
Relationship between transcriptional levels of lipid droplets localized genes and the clinicopathological parameters in HCC patients
According to UALCAN database, we analyzed the relationship between mRNA expression of selected lipid droplets localized genes and the clinicopathological parameters of HCC patients, including the tumor grade and individual cancer stage. The mRNA expression levels of selected lipid droplets genes were significantly correlated with the tumor grade of HCC patients. The highest mRNA levels of ACSL3, AIFM2, HSD17B7, LPCAT1, LSS, PLIN3, and RAB10 were found in grade 3 tumors, while the lowest mRNA levels of CIDEB, G0S2, HSD17B13, PLIN1 and PLIN2 were found in grade 4 tumors (Fig. 3A). Similarly, the mRNA levels of selected localized genes were also related to individual cancer stage. ACSL3, AIFM2, HSD17B7, LPCAT1, LSS, PLIN3 and RAB10 were up-regulated with the progression of cancer stage of HCC patients, while CIDEB, G0S2, HSD17B13, PLIN1 and PLIN2 were down-regulated (Fig. 3B). Regretfully, we have not found the information of HILPDA in this database. In summary, these results indicated that the mRNA levels of selected lipid droplets localized genes were significantly associated with the clinicopathological parameters in HCC patients.
The prognostic value of lipid droplets genes for OS in LIHC patients
GEPIA database was used to analyzed the relationship between the expression of each selected lipid droplets gene and patients OS in LIHC. The results revealed that high expression of ACSL3, AIFM2, HILPDA, LPCAT1, PLIN3 and RAB10, and low expression of CIDEB, HSD17B13, and PLIN1 were significantly associated with poor OS of patients with LIHC. While the expression of G0S2, HSD17B7, LSS and PLIN2 was not related to the OS of LIHC patients (Fig. 4).
A comprehensive investigation was conducted to explore the correlation between selected genes and the prognosis of HCC patients. The progression-free interval (PFI), disease-specific survival (DSS), and relapse-free survival (RFS) were analyzed for the identified proteins in HCC patients. Our findings suggest that the transcription of HILPDA, HSD17B13, LPCAT1, PLIN3, and RAB10 may be associated with the progression-free survival of HCC patients (Figure S2A). Similarly, DSS analysis showed that the transcription of HILPDA, HSD17B13, LPCAT1, and RAB10 may be associated with the disease-free survival of HCC patients (Figure S3A). Additionally, the transcription of CIDEB, HSD17B13, LPCAT1, and RAB10 may be associated with the relapse-free survival of HCC patients, as demonstrated by RFS analysis (Figure S4A). For determined the prognostic value of selected genes in HCC patients, we used the whole TCGA dataset of LIHC (374 HCC patients) for time-dependent ROC analysis, and found that the AUC scores of ACSL3, HILPDA, LPCAT1, PLIN3 and RAB10 are higher than 0.6, which revealed a well diagnostic performance of the six genes with HCC Figure S5A). These results revealed that the transcriptional levels of selected LD-localized proteins have prognostic value in HCC patients.
NAFLD may contribute to the transcriptional different of PLIN3 in HCC patients
Considering the tight correlation of LDs accumulation and NAFLD, we hypothesized that the transcriptional change of the selected LDs localized proteins may attributed to the dysfunction of lipid metabolism in liver. Thus, we constructed mice model with LDs accumulation in the liver, and investigated the transcriptional change of selected LDs localized proteins. First, we constructed mice model with LDs accumulation in the liver by CDAA diet. H&E and Oil red staining confirmed the establishment of NASH model (Fig. 5A). Transcriptome analysis revealed the expression of ACSL3, AIFM2, CIDEB, HILPDA, LPCAT1, LSS, PLIN1, PLIN2, PLIN3 and RAB10 in the liver of control and CDAA treated mouse, and it was almost similar to the pattern in liver normal and tumor tissues we examined in online database and patients (Fig. 5B). Next, we took PLIN3 as an example to explore its expression in NAFL related HCC tissues. The mRNA and protein levels of PLIN3 in liver tissues, including normal tissue, NAFL, HCC without or with NAFL, were examined by qRT-PCR (Fig. 5C), immunohistochemistry (Fig. 5D), and western blot (Fig. 5E), which indicated that LDs accumulation in the liver could promote the transcription and protein expression of PLIN3. Moreover, compared with HCC tissues without NAFLD, the mRNA and protein levels of PLIN3 in HCC tissues with NAFLD were significantly increased. These results demonstrated that the hepatic steatosis partially contributed to the aberrant transcription of LDs localized proteins, which may be crucial for the higher mortality of HCC patients with hepatic steatosis.
PLIN3 regulates the invasion and chemosensitivity of hepatoma cells
To further validate the function of PLIN3 in hepatoma cells, we first constructed PLIN3 knockdown cell lines, including HepG2 and LM3, by shRNA lentivirus, and the knockdown efficiency was confirmed by qRT-PCR (Fig. 6A). CCK-8 assay showed that PLIN3 had no effects on the proliferation of hepatoma cells (Fig. 6B). Besides, transwell assay revealed that the knockdown of PLIN3 remarkably impeded the migration and invasion of Hepatoma cells (Fig. 6C). Moreover, we explored if PLIN3 participated in the chemosensitivity of Hepatoma cells. The results showed that the knockdown of PLIN3 could enhance the cytotoxicity of sorafenib, doxorubicin and cisplatin in Hepatoma cells (Fig. 6D). Finally, we performed western blot to detect the apoptosis induced by these chemotherapeutic agents, and found that the cytotoxicity enhancement of PLIN3 knockdown in hepatoma cells may attributed to the increased apoptosis levels (Fig. 6E). These results demonstrated that PLIN3 strengthen the survival of hepatoma cells, and may contribute to HCC progression.
Discussion
As highly dynamic organelles, LDs are actively participated in lipid storage and have an important role in lipid homeostasis, but their additional biological activities are rarely characterized. Recently, LDs have been considered as new hallmarks of cancer cells, their accumulation has been reported occurring in various cancer types and participating in mediating many aspects of cancer cells, including proliferation, invasion, metastasis, as well as chemotherapy resistance [12]. Furthermore, the increasing contents of LDs could offer energy source for proliferative cancer cells to satisfy their metabolic needs, and the storage of excessive FAs and cholesterol in LDs could also help them preventing lipotoxicity and ER stress. In addition, the increasing number of LDs is also a characteristic of hepatic steatosis, which could increase the risk for steatohepatitis, liver cirrhosis, and even hepatocellular carcinoma (HCC) [26]. Thus, investigating the regulation of LDs dynamic is a potential strategy of HCC treatment. While directly manipulating the LDs dynamic is difficult, targeting to the LDs localized proteins, which are the main regulators of LDs metabolism, is a more prospective way to investigate the LDs dynamic in HCC.
The main function and dynamic of LDs are carried out by LDs localized proteins. Although the LDs proteome analysis in mammalian cells has revealed that approximately 150 proteins associated with LDs, our literature research found that few of these proteins has been verified to localize on the surface of LDs by immunofluorescence, which is the most direct way to demonstrate the association between LDs and LDs localized proteins. The verified proteins localized on LDs are crucial for the origination, transportation, and fusion of LDs, and involved in multiple biological processes, such as lipid metabolism and signaling, redox metabolism, autophagy, gene transcription, ubiquitination, membrane trafficking and immunity [17, 27]. As core members of lipid metabolism and storage, LDs localized proteins also play an important role in liver steatosis, but there are few studies focusing on their specific function and mechanisms in the occurrence and development of HCC.
In current study, we first summarized the LDs localized proteins verified by immunofluorescence through literature research. Then, by transcriptional analysis, we found that 13 LDs localized proteins are differentially expressed in HCC, and have prognostic value for HCC patients. Among them, ACSL3, AIFM2, HILPDA, HSD17B7, LPCAT1, LSS, PLIN3 and RAB10 were upregulated and CIDEB, G0S2, HSD17B13, PLIN1 and PLIN2 were downregulated in HCC tissues compared to normal tissues based on GEPIA database. To verify these results, we examined their expression in tissue samples we collected and got the similar consequences. Next, we confirmed their protein expression by using the Human Protein Atlas database, and the results showed that the majority of protein levels corresponded to mRNA transcripts other than HSD17B7, but there were no immunohistochemistry results of G0S2 and PLIN2 identified in this database. Besides, the analysis of prognostic value further revealed the important roles of these factors in HCC.
Among the LDs localized factors we analyzed, there are three perilipins (PLINs), namely PLIN1, PLIN2 and PLIN3. PLINs are one of the most abundant LDs localized proteins, and comprise five members, including PLIN1, PLIN2, PLIN3, PLIN4 and PLIN5, which have been numbered in the order of their discovery [28]. PLIN2 and PLIN3 are ubiquitously expressed, while PLIN1, PLIN4 and PLIN5 have more limited tissue expression. PLINs can be used as a barrier for LDs decomposition, therefore help stabilizing triglycerides in LDs and promote their biosynthesis, thus promoting the growth of LDs. In addition, PLINs can also directly control how and when the cells and tissues to store, mobilize and use lipids, and they are the important regulators of lipid metabolism. Therefore, PLINs could play an important role in obesity, diabetes, liver disease and cancer caused by abnormal lipid metabolism.
In the liver, PLIN2 and PIN3 are two main functional LDs localized proteins, their expression levels on the LDs surface are dynamic in response to cellular metabolic needs, which can regulate the accessibility of enzymes involved in the lipid synthesis or lipolysis. PLIN2 would be degraded if displaced from the LDs, therefore it is a nonexchangeable protein [29]. However, PLIN3 is a highly exchangeable protein involved in various processes, such as lipid storage, lipid mobilization, and LDs biogenesis [30, 31]. In addition, PLIN3 is stable in the cytosol in quiescent stage and can be recruited to nascent LDs immediately when lipid storage is stimulated, and its knockdown could result in the inhibition of growth and maturation of LDs in cells even if stimulated by oleic acid [30]. In our informatics analysis based on public databases, PLIN3 was highly expressed in HCC tumor tissues, and positively correlated with the tumor grade and stage of HCC patients, while the expression pattern of PLIN2 was completely opposite. As for their prognostic values, the HCC patients with high expression of PLIN3 possessed poor prognosis, while the expression of PLIN2 was not related to the prognosis of HCC patients. It was indicated that PLIN3 was more positively correlated with the development of HCC. Thus, we took PLIN3 as a targeting protein to reveal the function of LDs localized proteins in the malignant progression of hepatoma cells.
The majority of current researches focused PLIN3 on its role in liver steatosis [32, 33], only a few studies paid attention to its function in cancers [34,35,36], and there has not a single study connecting PLIN3 with HCC so far. In our study, we confirmed that the protein levels of PLIN3 in HCC tissues is certainly associated with hepatic steatosis, and found that PLIN3 has the highest expression in HCC tissues accompanying with NAFLD. Knockdown of PLIN3 in hepatoma cells affected their migration and invasion, and it further had an influence on the cytotoxicity and apoptosis of sorafenib and doxorubicin on hepatoma cells, indicating that PLIN3 could affect the chemosensitivity of hepatoma cells. The mechanism of PLIN3 in sorafenib and doxorubicin induced the apoptosis of hepatoma cells may be attributed to autophagy. LDs have been recognized as the site for autophagosome biogenesis [37], and chaperone-mediated autophagy (CMA) is required to degrade PLIN3 before the selective sequestration of LDs by the autophagosome, which means that before autophagosome biogenesis associated and initiated by ATGs, PLIN3 would have to be removed from LDs surface [38], but the specific function of this mechanism on HCC development need to be further investigated. In our CDAA induced mouse NASH model, we found that the liver steatosis contributed to the expression changes of LDs localized proteins including PLIN3. Combine with the function of PLIN3 identified in hepatoma cells, we speculated that PLIN3 might be an important factor in the progression of NAFLD to HCC. However, this needs further intensive investigation and the exploration of the specific role of PLIN3 in the NAFLD-HCC pathogenesis would help to identify new targets for the diagnosis and prognosis of respective pathologies.
NAFLD is characterized by augmented accumulation of LDs, and the alteration in LDs metabolism has been proposed as a new hallmark of cancer [39]. Therefore, the changes in the expression of LDs localized proteins may be the accelerators in the progression of NAFLD to HCC. Moreover, the expression changes of these proteins may connect the hepatic steatosis with the malignance advancement of HCC. Thus, elucidating the mechanisms underlying this process is important for the development of new treatments and new therapeutic targets. Targeting to the LDs localized proteins could be the potential ways for the precision medicine of HCC patients with NAFLD.
Data Availability
The original datasets of RNA sequence generated and analyzed during the current study have been uploaded on the GEO database (GSE223446), and can be downloaded from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse223446.
References
McGlynn KA, Petrick JL, El-Serag HB. Epidemiology of Hepatocellular Carcinoma. Hepatology. 2021;73(1):4–13.
Golabi P, Fazel S, Otgonsuren M, Sayiner M, Locklear C, Younossi Z. Mortality assessment of patients with hepatocellular carcinoma according to underlying disease and treatment modalities. Medicine. 2017;96(9):e5904.
Yip T, Lee H, Chan W, Wong G, Wong V. Asian perspective on NAFLD-associated HCC. J Hepatol. 2022;76(3):726–34.
Ertle J, Dechêne A, Sowa J, Penndorf V, Herzer K, Kaiser G, Schlaak J, Gerken G, Syn W, Canbay A. Non-alcoholic fatty liver disease progresses to hepatocellular carcinoma in the absence of apparent cirrhosis. Int J Cancer. 2011;128(10):2436–43.
Cholankeril G, Patel R, Khurana S, Satapathy S. Hepatocellular carcinoma in non-alcoholic steatohepatitis: current knowledge and implications for management. World J Hepatol. 2017;9(11):533–43.
Kanwal F, Kramer J, Mapakshi S, Natarajan Y, Chayanupatkul M, Richardson P, Li L, Desiderio R, Thrift A, Asch S, et al. Risk of Hepatocellular Cancer in patients with non-alcoholic fatty liver disease. Gastroenterology. 2018;155(6):1828–1837e1822.
Younossi Z, Otgonsuren M, Henry L, Venkatesan C, Mishra A, Erario M, Hunt S. Association of nonalcoholic fatty liver disease (NAFLD) with hepatocellular carcinoma (HCC) in the United States from 2004 to 2009. Hepatology (Baltimore MD). 2015;62(6):1723–30.
Bechmann LP, Hannivoort RA, Gerken G, Hotamisligil GS, Trauner M, Canbay A. The interaction of hepatic lipid and glucose metabolism in liver diseases. J Hepatol. 2012;56(4):952–64.
Hu B, Lin JZ, Yang XB, Sang XT. Aberrant lipid metabolism in hepatocellular carcinoma cells as well as immune microenvironment: a review. Cell Prolif. 2020;53(3):e12772.
Seebacher F, Zeigerer A, Kory N, Krahmer N. Hepatic lipid droplet homeostasis and fatty liver disease. Semin Cell Dev Biol. 2020;108:72–81.
Chen K, Ma J, Jia X, Ai W, Ma Z, Pan Q. Advancing the understanding of NAFLD to hepatocellular carcinoma development: from experimental models to humans. Biochim et Biophys acta Reviews cancer. 2019;1871(1):117–25.
Li Z, Liu H, Luo X. Lipid droplet and its implication in cancer progression. Am J cancer Res. 2020;10(12):4112–22.
Corbet C, Bastien E, Santiago de Jesus J, Dierge E, Martherus R, Vander Linden C, Doix B, Degavre C, Guilbaud C, Petit L, et al. TGFβ2-induced formation of lipid droplets supports acidosis-driven EMT and the metastatic spreading of cancer cells. Nat Commun. 2020;11(1):454.
Cotte A, Aires V, Fredon M, Limagne E, Derangère V, Thibaudin M, Humblin E, Scagliarini A, de Barros J, Hillon P, et al. Lysophosphatidylcholine acyltransferase 2-mediated lipid droplet production supports colorectal cancer chemoresistance. Nat Commun. 2018;9(1):322.
Berndt N, Eckstein J, Heucke N, Gajowski R, Stockmann M, Meierhofer D, Holzhütter H. Characterization of lipid and lipid droplet metabolism in Human HCC. Cells 2019, 8(5).
Yang L, Ding Y, Chen Y, Zhang S, Huo C, Wang Y, Yu J, Zhang P, Na H, Zhang H, et al. The proteomics of lipid droplets: structure, dynamics, and functions of the organelle conserved from bacteria to humans. J Lipid Res. 2012;53(7):1245–53.
Bersuker K, Peterson C, To M, Sahl S, Savikhin V, Grossman E, Nomura D, Olzmann J. A proximity labeling strategy provides insights into the Composition and Dynamics of lipid droplet proteomes. Dev Cell. 2018;44(1):97–112e117.
Petan T. Lipid Droplets in Cancer. Reviews of physiology, biochemistry and pharmacology 2020.
Cruz A, Barreto E, Fazolini N, Viola J, Bozza P. Lipid droplets: platforms with multiple functions in cancer hallmarks. Cell Death Dis. 2020;11(2):105.
Ndiaye H, Liu J, Hall A, Minogue S, Morgan M, Waugh M. Immunohistochemical staining reveals differential expression of ACSL3 and ACSL4 in hepatocellular carcinoma and hepatic gastrointestinal metastases. Biosci Rep 2020, 40(4).
Chen J, Zhuo J, Yang F, Liu Z, Zhou L, Xie H, Xu X, Zheng S. 17-beta-hydroxysteroid dehydrogenase 13 inhibits the progression and recurrence of hepatocellular carcinoma. Hepatobiliary & pancreatic diseases international: HBPD INT. 2018;17(3):220–6.
Zhang Y, Pan Q, Yu Y, Zhong X. microRNA-519d induces autophagy and apoptosis of human hepatocellular carcinoma cells through activation of the AMPK Signaling Pathway via Rab10. Cancer Manage Res. 2020;12:2589–602.
Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017;45:W98–W102.
Chandrashekar D, Bashel B, Balasubramanya S, Creighton C, Ponce-Rodriguez I, Chakravarthi B, Varambally S. UALCAN: a portal for facilitating Tumor Subgroup Gene expression and survival analyses. Neoplasia (New York NY). 2017;19(8):649–58.
Liu X, Zhang Y, Wang Z, Liu L, Zhang G, Li J, Ren Z, Dong Z, Yu Z. PRRC2A promotes Hepatocellular Carcinoma Progression and Associates with Immune Infiltration. J hepatocellular carcinoma. 2021;8:1495–511.
Musso G, Cassader M, Gambino R. Non-alcoholic steatohepatitis: emerging molecular targets and therapeutic strategies. Nat Rev Drug Discovery. 2016;15(4):249–74.
Bersuker K, Olzmann J. Establishing the lipid droplet proteome: mechanisms of lipid droplet protein targeting and degradation. Biochim et Biophys acta Mol cell biology lipids. 2017;1862:1166–77.
Kimmel A, Brasaemle D, McAndrews-Hill M, Sztalryd C, Londos C. Adoption of PERILIPIN as a unifying nomenclature for the mammalian PAT-family of intracellular lipid storage droplet proteins. J Lipid Res. 2010;51(3):468–71.
Masuda Y, Itabe H, Odaki M, Hama K, Fujimoto Y, Mori M, Sasabe N, Aoki J, Arai H, Takano T. ADRP/adipophilin is degraded through the proteasome-dependent pathway during regression of lipid-storing cells. J Lipid Res. 2006;47(1):87–98.
Bulankina A, Deggerich A, Wenzel D, Mutenda K, Wittmann J, Rudolph M, Burger K, Höning S. TIP47 functions in the biogenesis of lipid droplets. J Cell Biol. 2009;185(4):641–55.
Skinner J, Shew T, Schwartz D, Tzekov A, Lepus C, Abumrad N, Wolins N. Diacylglycerol enrichment of endoplasmic reticulum or lipid droplets recruits perilipin 3/TIP47 during lipid storage and mobilization. J Biol Chem. 2009;284(45):30941–8.
Carr R, Patel R, Rao V, Dhir R, Graham M, Crooke R, Ahima R. Reduction of TIP47 improves hepatic steatosis and glucose homeostasis in mice. Am J Physiol Regul Integr Comp Physiol. 2012;302(8):R996–1003.
Ferguson D, Zhang J, Davis M, Helsley R, Vedin L, Lee R, Crooke R, Graham M, Allende D, Parini P, et al. The lipid droplet-associated protein perilipin 3 facilitates hepatitis C virus-driven hepatic steatosis. J Lipid Res. 2017;58(2):420–32.
Wang K, Ruan H, Song Z, Cao Q, Bao L, Liu D, Xu T, Xiao H, Wang C, Cheng G, et al. PLIN3 is up-regulated and correlates with poor prognosis in clear cell renal cell carcinoma. Urol Oncol. 2018;36(7):343e319–49.
Szigeti A, Minik O, Hocsak E, Pozsgai E, Boronkai A, Farkas R, Balint A, Bodis J, Sumegi B, Bellyei S. Preliminary study of TIP47 as a possible new biomarker of cervical dysplasia and invasive carcinoma. Anticancer Res. 2009;29(2):717–24.
Zhou L, Song Z, Hu J, Liu L, Hou Y, Zhang X, Yang X, Chen K. ACSS3 represses prostate cancer progression through downregulating lipid droplet-associated protein PLIN3. Theranostics. 2021;11(2):841–60.
Dupont N, Chauhan S, Arko-Mensah J, Castillo E, Masedunskas A, Weigert R, Robenek H, Proikas-Cezanne T, Deretic V. Neutral lipid stores and lipase PNPLA5 contribute to autophagosome biogenesis. Curr biology: CB. 2014;24(6):609–20.
Kaushik S, Cuervo A. Degradation of lipid droplet-associated proteins by chaperone-mediated autophagy facilitates lipolysis. Nat Cell Biol. 2015;17(6):759–70.
Corn K, Windham M, Rafat M. Lipids in the tumor microenvironment: from cancer progression to treatment. Prog Lipid Res. 2020;80:101055.
Acknowledgements
Not applicable.
Funding
This work was supported by National Natural Science Foundation of China (81901613), the Joint Construction Project of Medical Science and Technology Research Plan of Henan Province (LHGJ20190023), Natural Science Foundation of Henan Province-Young Scientists Fund(232300420258), Natural Science Foundation of Guangdong Province (2020A1515011299), China Postdoctoral Science Foundation Grant (2019M653189), the Fundamental Research Funds for the Central Universities (20ykpy28).
Author information
Authors and Affiliations
Contributions
YZZ and KPL carried out experiments and write the manuscript. YZZ and XL involved in experimental execution and data analysis, QHL and BYZ performed the ROC-analysis and involved in the revision of manuscript, LWL and ZHD participated in the writing of the manuscript. YZZ, ZHD and KPL designed the study and reviewed the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Ethics approval and consent to participate
For the usage of liver tissue of human, all experimental procedures complied with the experimental management regulations of the State Council of the People’s Republic of China, and strictly follow China’s GCP, the “Declaration of Helsinki” and relevant Chinese laws and regulations. The usage of the clinical samples and methods in this study was carried out in accordance with the approved guidelines by the Third Affiliated Hospital of Sun Yat-Sen University, and written informed consent to participate in the study was obtained from all subjects. Informed consent forms were signed by all study participants. The protocol was approved by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University. For the mice experiment, all experimental methods were conducted in accordance with the Animal Care and Use Regulations of China. All methods were reported in accordance with ARRIVE guidelines.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Zhang, Y., Liang, X., Lian, Q. et al. Transcriptional analysis of the expression and prognostic value of lipid droplet-localized proteins in hepatocellular carcinoma. BMC Cancer 23, 677 (2023). https://doi.org/10.1186/s12885-023-10987-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s12885-023-10987-z