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Journal of Extracellular Biology logoLink to Journal of Extracellular Biology
. 2024 Feb 23;3(2):e141. doi: 10.1002/jex2.141

RAB31 drives extracellular vesicle fusion and cancer‐associated fibroblast formation leading to oxaliplatin resistance in colorectal cancer

Yu‐Chan Chang 1, Yi‐Fang Yang 2, Chien‐Hsiu Li 3, Ming‐Hsien Chan 1, Meng‐Lun Lu 4, Ming‐Huang Chen 4,5,6, Chi‐Long Chen 7,8,✉, Michael Hsiao 3,✉
PMCID: PMC11080812  PMID: 38939899

Abstract

Epithelial‐mesenchymal transition (EMT) is associated with tumorigenesis and drug resistance. The Rab superfamily of small G‐proteins plays a role in regulating cell cytoskeleton and vesicle transport. However, it is not yet clear how the Rab family contributes to cancer progression by participating in EMT. By analysing various in silico datasets, we identified a statistically significant increase in RAB31 expression in the oxaliplatin‐resistant group compared to that in the parental or other chemotherapy drug groups. Our findings highlight RAB31's powerful effect on colorectal cancer cell lines when compared with other family members. In a study that analysed multiple online meta‐databases, RAB31 RNA levels were continually detected in colorectal tissue arrays. Additionally, RAB31 protein levels were correlated with various clinical parameters in clinical databases and were associated with negative prognoses for patients. RAB31 expression levels in all three probes were calculated using a computer algorithm and were found to be positively correlated with EMT scores. The expression of the epithelial‐type marker CDH1 was suppressed in RAB31 overexpression models, whereas the expression of the mesenchymal‐type markers SNAI1 and SNAI2 increased. Notably, RAB31‐induced EMT and drug resistance are dependent on extracellular vesicle (EV) secretion. Interactome analysis confirmed that RAB31/AGR2 axis‐mediated exocytosis was responsible for maintaining colorectal cell resistance to oxaliplatin. Our study concluded that RAB31 alters the sensitivity of oxaliplatin, a supplementary chemotherapy approach, and is an independent prognostic factor that can be used in the treatment of colorectal cancer.

Keywords: AGR2, colon cancer, epithelial‐mesenchymal transition, oxaliplatin resistance, RAB31

1. INTRODUCTION

Colorectal cancer is highly diagnosed and prevalent, with a significant number of cases (Siegel et al., 2022). On average, approximately 30% of patients with colon cancer are diagnosed with synchronous or metachronous metastases (Engstrand et al., 2018). For patients with metastatic colon cancer, commonly prescribed adjuvant chemotherapy drugs include irinotecan and oxaliplatin (Abrams et al., 2014). However, the development of chemoresistance leads to tumour recurrence and decreased survival rates. Therefore, understanding the causes of resistance and the complete mechanism will help patients to consider alternative treatment options. Drug resistance is often the leading cause of treatment failure in patients with relapsing cancer. In this case, the ineffectiveness of the drug can result from both its activity and the cell's ability to transport it outside the cell (Wilson et al., 2006). Research has indicated that long‐term exposure of colorectal cancer cells to oxaliplatin induces epithelial‐to‐mesenchymal transition (EMT) processes, such as the reduction of E‐cadherin and the increase in Snail or vimentin, which enables the cells to resist efficacy (Yang et al., 2006). In colorectal cancer, EMT is the primary mechanism that promotes early invasion and metastasis (Todosi et al., 2012). Multiple clinical studies have consistently demonstrated that a lack of E‐cadherin is associated with a poorer prognosis and malignancy in colorectal cancers (Ye et al., 2015). Recently, it was demonstrated that tumour cells alter the basis of EMT and reprogram the tumour microenvironment (Spano & Zollo, 2012). One of the significant mechanisms resulting in oxaliplatin resistance in colorectal cancer is extracellular vesicle (EV) secretion (Han et al., 2020; Liu et al., 2019). Therefore, it is critical to identify the specific molecules that can trigger EMT and influence oxaliplatin resistance, thereby inhibiting early metastasis.

The Rab family of small GTPases is a member of the Ras superfamily. In the human body, Rab GTPase regulates vesicle trafficking and recycling by converting between the guanosine diphosphate (GDP) and guanosine triphophate (GTP) forms (Homma et al., 2021). Each member of the Rab family performs unique functions, and has distinct distributions and expressions. Some members exhibit coordinated functionality, whereas others are redundant (Hutter, 2007; Martínez‐Morales et al., 2022). Studies indicate that aberrant Rab expression during tumorigenesis is a significant, independent prognostic/diagnostic factor (Jin et al., 2021). Scientists have suggested that Rabs regulate oncogenic pathways or act as co‐activators with several transcription factors (Erami et al., 2017; Stenmark, 2009). Recent discoveries regarding Rabs and their protein‐interacting partners have confirmed their importance in cancer and other diseases (Chang et al., 2023). In colorectal cancer, Rab3C expression is associated with tumour metastasis via the STAT3/IL‐6 axis (Chang et al., 2017). RAB31 has also been reported to contribute to endosomal trafficking and the endosomal sorting complex required for the transport (ESCRT)‐independent EV pathway (Jalagadugula et al., 2022; Wei et al., 2021), a more detailed mechanism has not been investigated.

This study focused on the expression of the RAB31 gene in colorectal cells, utilising a series of clinical correlation selection procedures. Although RAB31 plays a crucial role in vesicle‐ and granule‐targeting, its involvement in the EMT pathway and drug resistance has been observed. It is noteworthy that this observation has only been made for RAB31, and none of the other Rabs have demonstrated this association. We identified new pathways and phenotypes that differed from previously reported canonical pathways. Additionally, we uncovered a unique function of RAB31 in colorectal cancer.

2. MATERIAL AND METHODS

2.1. Cell lines and stable clones

Eight human colon cancer cell lines, three of which (CX‐1, DLD‐1 and H3347) were maintained in RPMI‐1640 medium and two cell lines (HCT116 and HT‐29) were maintained in McCoy's 5A modified medium (Sigma, St. Louis, MO, USA). The medium was supplemented with 10% fetal bovine serum (GIBCO, Grand Island, NY, USA), penicillin (100 units/mL) and streptomycin (100 μg/mL). Cells were incubated in a humidified atmosphere of 95% air, 5% CO2 at 37°C. SW48, SW480 and SW620 cells were cultured in Leibovitz L‐15 medium (Sigma, St. Louis, MO, USA) and incubated in a CO2‐free incubator. The L‐15 medium formula is designed for free gas exchange with the atmosphere. When using this medium for culture, the mixture of CO2 and air is harmful to cells, so these cells were cultured in a CO2‐free incubator. Human Colonic Fibroblasts were purchased from ScienceCell company (Cat#2880) and maintained in Fibroblast Medium (FM, Cat #2301, ScienCell, Carlsbad, CA, USA)

2.2. Gene construction and lentivirus production

The lentiviral envelope and packing plasmids (pMDG and p△8.91) were purchased from the National RNAi Core Facility (Academia Sinica, Taiwan). The pDONR223_RAB31 lentiviral construct and empty vector were purchased from Addgene (Watertown, MA, USA) and swapped in a lentiviral backbone‐based system. Lentiviruses were co‐transfected into 293 T cells with pMDG (p = 8.91) and the plasmid construct using the calcium phosphate transfection method. After 48 h of incubation, the lentiviruses were collected and used to infect cells with polybrene (2 μg/mL). For two weeks, cells with altered RAB31 expression were selected using blasticidin (2 μg/mL). Finally, a plasmid carrying a vector control sequence was used to create control cells.

2.3. Cell viability measurements

Cell viability was determined using the TACS tetrazolium salt 3‐(4,5‐dimethylthiazol‐2‐yl)−2, 5‐diphenyltetrazolium bromide (MTT) cell proliferation assay kit (Trevigen, Gaithersburg, MD, USA), according to the manufacturer's instructions. The MTT assay was used to determine cell viability in cell proliferation and cytotoxicity assays. The cells were seeded at a concentration of 2000 cells/100 μL of culture medium per well in 96‐well microplates. At 24 h post‐seeding, the cells were treated with the dimethyl sulfoxide (DMSO) solvent control or different doses of oxaliplatin/GW4869 for 24, 48 or 72 h. Subsequently, the cells were incubated in a medium containing MTT for 4 h, lysed with DMSO, and optical density at 570 nm was measured using a microplate reader (Spectral Max250; Molecular Devices, Sunnyvale, CA, USA).

2.4. Electron microscopy and multivesicular body (MVB) quantification

The cells were washed in phospate buffered saline (PBS) and fixed for 1 h in 2.5% glutaraldehyde in 0.1 M phosphate buffer at room temperature. Then, the cells were slowly and gently scraped and pelleted in Eppendorf tubes. We washed the pellets in phosphate buffer and incubated them with 1% OsO4 for 90 min at 4°C. The samples were then dehydrated, embedded in Spurr, and sectioned using a Leica ultramicrotome (Leica Microsystems) (Edgar, 2016; Villarroya‐Beltri et al., 2016). Ultrathin sections (50–70 nm) were stained with 2% uranyl acetate for 10 min, followed by a lead staining solution for 5 min, and observed using a transmission electron microscope (Hitachi TEM system). ImageJ software was used for calibration, quantification and analysis of the images. We identified MVBs and counted them by morphology, with only discrete ILVs. Lysosomes showed a multilayer morphology. We analysed at least 20 MVBs per experiment, using separate cells. We analysed the data from duplicate or triplicate experiments and used two to four grids for each condition. The minimum number of cells scored under each condition was 20. We generated box scatter plots using Prism GraphPad software and performed statistical tests in Microsoft Excel (calibration: 2.0; magnification: ×2.0 K–×6.0 K; lens mode: Zoom‐1; acc. voltage: 75.0 kV; emission: 5.8 μA. Data are presented as mean ± standard deviation; *** p‐value < 0.0001.

2.5. Nanoparticle tracking analysis

We used a nanoparticle tracking analysis (NTA) system to analyse the particle size distribution of the EV sample. The system was equipped with a 488 nm laser and a high‐sensitivity scientific CMOS camera, and was used with a NanoSight NS300 system (Malvern Technologies, Malvern, UK). According to the manufacturer's specifications, we diluted the sample at 1:100 in particle‐free PBS to an acceptable recommended concentration to reduce the number of particles in the field of view to below 100/frame. We recorded the reading videos in a single capture for 60 s at 30 frames per second (fps), with the camera level set to 15 and manual temperature monitoring. Then, we used NTA 3.1.54 software to divide the particle size distribution into 10 nm wide intervals, which was used for all the video reproductions to determine the concentration measurement value. To understand the variability in the estimated value within the entire interval width, the software organized the statistical data obtained from each frame.

2.6. Western blot analysis

The cells were lysed in RIPA buffer for 30 min and then centrifuged at 13,000 rpm for 15 min at 4°C. Protein concentrations were measured using Bicinchoninic acid assay (BCA assay) protein assay reagent (Thermo Fisher Scientific, Waltham, MA, USA). Total proteins (30 μg) were separated by SDS Poly‐acrylamide‐gel‐eletrophoresis (SDS‐PAGE) on 10% polyacrylamide gels and transferred to (lyvinylidene fluoride a PVDF) membranes. The membranes were hybridised with primary antibodies overnight after blocking for 30 min in 5% non‐fat milk. The samples were incubated with secondary antibodies for 1 h, and the proteins were visualised using enhanced chemiluminescence reagents (ECL) (Perkin Elmer, Waltham, MA, USA). Quantitative data were obtained using ImageJ software.

Western blot analysis was performed using the following primary antibodies: anti‐RAB31 (1:1000) (Cat # 15485‐1‐AP, Proteintech, Rosemont, IL, USA), anti‐pEGFR tyr 1173 (1:1000) (Cat # ab32578, Abcam), anti‐EGFR (1:1000) (Cat # ab32198, Abcam), anti‐pErk thr 202 (1:1000) (Cat # ab201015, Abcam), anti‐Erk (1:1000) (Cat # ab32537, Abcam), anti‐pAkt ser 473 (1:1000) (cat. no: 4060, Cell Signaling Technology), anti‐Akt (1:2000) (cat. no: 4691, Cell Signaling Technology), anti‐Slug (1:1000) (cat. no: 9585, Cell Signaling Technology), anti‐E‐cadherin (1:1000) (cat. no.610182, BD Biosciences), anti‐TSG101 (1:1000) (Cat # ab125011, Abcam), anti‐VPS24 (1:1000) (Cat # 15472‐1‐AP, Proteintech), anti‐VPS28 (1:1000) (Cat # 15478‐1‐AP, Proteintech), anti‐CD9 (1:5000) (Cat # sc‐6327, Sdanta Cruz), anti‐CHMP4B (1:1000) (Cat # 42466, Cell Signaling Technology), anti‐FLOT1 (1:2000) (Cat # ab41927, Abcam), anti‐FLOT2 (1:2000) (Cat # 3244, Cell Signaling Technology), anti‐CD63 (1:1000) (Cat # ab231975, Abcam), anti‐TBC1D2B (1:1000) (Cat # ab185102, Abcam) anti‐calnexin (1:1000) (Cat # ab92573, Abcam), anti‐vimentin (1:1000) (Cat # ab92547, Abcam), and anti‐α‐tubulin (1:104) (Sigma‐Aldrich, St. Louis, MO, USA).

2.7. EV isolation and extraction

According to traditional ultra‐high‐speed centrifugation, the exosomal fraction from the filtered fluid of the cell culture medium was isolated. Briefly, cancer cells and debris were removed from the conditioned medium by centrifugation at 500×g for 10 min and 2000×g for 30 min. The supernatant was then filtered through a 0.22‐μm filter and ultra‐high‐speed centrifuged at 100,000×g for 90 min (Beckman 70Ti rotor). Finally, the isolated EV pellets were resuspended and washed three times with PBS through Amicon‐0.5 mL centrifugal filters (100 kDa, Millipore, Billerica, MA, USA) for concentration and further analysis. These procedures have also been described in previous studies (Chang et al., 2020).

2.8. Exosome membrane labelling

Researchers commonly use fluorescent dyes to label the cellular membrane during exosome labelling because the lipid bilayers in exosomes are a good target. Here, we chose the ExoParkler Exosome Membrane Labeling Lit‐Red (Dojindo, Kumamoto, Japan), which enabled us to use the application to experiment using multiple labels. After collecting 109−1010 exosomes suspended in 100 μL PBS, we added 2 μL Mem Dye stock solution and mixed it with the exosomes. We transferred the staining exosomes to a filtration tube and centrifuged them at 3000×g for 5 mins about three times. We added 50 μL of PBS to recover the labelled exosomes.

2.9. Immunoprecipitation and immunoblotting analyses

Whole‐cell lysates (2 mg) from cultured cells were incubated overnight in IP buffer with 25 μL of protein A/G magnetic beads and the corresponding antibodies against RAB31 (Cat # 15485‐1‐AP, Proteintech, Rosemont, IL, USA) or AGR2 (Cat # GTX00601, GeneTex, Hsinchu, Taiwan) in a 1.5 mL microcentrifuge tube with a final volume of 1000 μL. Proteins interacting with the antibodies were purified according to the manufacturer's protocol.

2.10. Migration/Invasion assay

For migration/invasion assays, we coated 8 μm‐pore‐size polycarbonate filters (GE Healthcare Life Sciences, Chalfont St. Giles, UK) with 1 mg/mL human fibronectin (Sigma, St. Louis, MO, USA). Alternatively, if the other side is coated with Matrigel, it is used for invasion experiments. We added medium containing 10% FBS to the lower compartment, and cells suspended in serum‐free medium were added to the upper compartment of the Boyden chamber. After optimal timing (12–16 h), the migrating cells were stained with Giemsa solution and counted under a light microscope (400×, eight random fields of each well) for further quantification. We performed three independent experiments, each with four replicates. Count the number of Giemsa‐stained cells in each field of view and take the percentage, with the control group as the baseline. The detailed process and classification are introduced in our previous study (Chang et al., 2019).

2.11. Luciferase reporter assay

CRC cancer cells were transfected with 0.5 μg of reporter containing E‐cadherin sequence inserted upstream of the firefly luciferase gene in the pGL3 enhancer plasmid vector. As an internal standard, all plasmids were co‐transfected with pRL‐TK, which contains the Renilla luciferase gene. Cells were collected 48 h after transfection, and cell lysates were prepared according to Promega's instruction manual.  The luciferase signals were measured by using a plate reader and One‐Glo luciferase reagent (#E6120, Promega, Madison, WI, USA).

2.12. Synergy calculation

We formulated all dosing groups in a dose‐dependent manner from 1 nM to 100 μM to calculate the cell viability percentages. These values were uploaded to the SynergyFinder website for statistical analysis (https://synergyfinder.fimm.fi/). We present the synergy scores and degrees of inhibition for the two compounds based on available algorithms (synergy score (δ‐score) < 10: antagonistic; −10−10: additive; > 10: synergistic).

2.13. Statistical analysis

The non‐parametric Mann‐Whitney U‐test was used to analyse the statistical significance of the results from three independent experiments. Statistical analyses were performed using SPSS (Statistical Package for the Social Sciences) 17.0 software (version 17.0; SPSS, Chicago, IL, USA). For all analyses, a p‐value of < 0.05 was considered significant.

3. RESULTS

3.1. RAB31 expression confers resistance to oxaliplatin and serves as an independent prognostic marker

To discern chemoresistance events among therapeutic treatments for colorectal cancer and identify potentially involved genes, we analysed the GEO dataset (GSE42387), which includes commonly used drugs such as oxaliplatin and irinotecan for advanced and metastatic colorectal cancers. After normalisation and selection of an appropriate cutoff (1.5‐fold change), we used a Venn diagram to identify genes affected by oxaliplatin and irinotecan in the two colorectal cancer files (Figure 1a). The findings revealed significant alterations in several probes in the oxaliplatin‐resistant group when compared to the irinotecan‐resistant and parental groups. Among HT‐29 and LoVo cells, 342 (in red) and 531 (in blue) genes were identified. After merging and selecting common features, we isolated 18 candidates for further experimentation. Among these probes, RAB31 ranked high and multiple groups of probes showed similar trends (Figure 1b). Previous research has shown that RAB31 is involved in oxaliplatin resistance and is associated with a high risk of colorectal cancer (Zheng et al., 2015). Forest plots are revealing that RAB31 expression is associated with a high risk ratio in colorectal cancer cohorts, similar to other significant prognostic variables. We found RAB31 to be the only statistically significant candidate among the Rab family in this dataset. To verify that RAB31 expression is not specific to HT‐29 and LoVo cells, we analysed multiple GEO datasets (GSE30011 and GSE10405). These findings indicate that several colorectal cancer cell lines induced RAB31 expression following exposure to oxaliplatin (Figure 1d). Compared to the other candidates, RAB31 exhibited a more prominent trend in multiple cell models (Figure S1). Additionally, a meta‐cohort analysis of clinical data showed a significant elevation of RAB31 expression in colorectal carcinomas (p = 9.78e‐05) (Figure 1e). Therefore, upregulation of RAB31 expression in colorectal cancer could be linked to oxaliplatin resistance. From a clinical perspective, it is worth noting that RAB31 has prognostic value in relation to both the overall survival rate and disease‐free survival rate (Figure S2A,B). Interestingly, independent cohorts using chemotherapy demonstrated a significant effect on the outcomes of patients receiving chemotherapy (Figure S2C).

FIGURE 1.

FIGURE 1

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RAB31 as a predictor of oxaliplatin resistance to in colorectal cancer. (a) Venn diagram showing significant changes in targets between oxaliplatin resistance or SN‐38 (Irinotecan)‐resistance HT‐29 and LoVo cells compared to the parental group, respectively. All raw data analyses are from GSE42387. (b) Boxplot showing the expression levels between the three events in (a). (c) The forest plot that predicts prognosis markers in the colorectal cancer cohort and their corresponding risk ratios, p‐values, and probe IDs. (d) The levels of expression for RAB31 were analysed in both treated and oxaliplatin‐resistant colorectal cancer cell lines in various datasets (GSE30011 and GSE10405). (e) RAB31 expression levels were evaluated in a colorectal cancer meta‐cohort, obtained from the TNMplot website (Bartha & Győrffy, 2021). The significance of the difference was determined using a non‐parametric Mann‐Whitney U test.

3.2. RAB31 exhibits heterogeneity and exocytotic properties in colorectal cancer

To examine the expression and characteristics of RAB31 in colorectal models, we obtained endogenous expression levels of RAB31 mRNA from the COAD panel on TCGA website (Figure 2a). Additionally, we measured the expression of RAB31 in our cellular model (Figure 2b), providing evidence of consistent trends and differential baselines for RAB31 across each cell line (Figure 2b). Based on these expression profiles, we selected CX‐1 and HT‐29 as overexpressing cells. Both quantitative polymerase chain reaction (qPCR) and western blot assays verified the overexpression of varying concentrations of RAB31 cDNA in CX‐1 and HT‐29 cells (Figure 2c,d).

FIGURE 2.

FIGURE 2

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High expression and secretion of RAB31 is observed in malignant cells. (a) Boxplot showing the expression levels of RAB31 mRNA in colorectal cancer cells detected by next‐generation sequencing from the Cancer Cell Line Encyclopedia (CCLE) dataset. (b) qPCR analysis was performed on RAB31 expression in the collected colorectal cancer cell panel collected. (c) qPCR results showing the overexpression vector or gradient expression of RAB31 in CX‐1 and HT‐29 cells, respectively. (d) Western blots detected RAB31 expression with vector or gradient RAB31 expression in CX‐1 and HT‐29 cells, respectively. (e) qPCR results of RAB31 expression in total lysates or EV isolates performed in CX‐1 and HT‐29 RAB31 overexpressing cells, respectively. (f) Western blots that detect RAB31 expression and EV‐related molecules in total lysates or isolation of EV from HT‐29 cells. (g) qPCR detection of RAB31 expression levels in total lysates or EVs from HT‐29 overexpressing cells treated with or without GW4869. EV, extracellular vesicle; qPCR, quantitative polymerase chain reaction. ***p  <  0.001 compared to vehicle group by Student's t‐test.

Rab proteins play crucial roles in various biological functions such as vesicle trafficking and exocytosis (Hendrix & Hume, 2011; Jin et al., 2021). RAB31 is an exocytotic RAB protein known for its effect on the extent and efficiency of exocytosis when overexpressed. Some literature has suggested that RAB31 is incorporated into exosomes and leaves cells (Wei et al., 2021). We tried to isolate extracellular vesicle (EV) and compare them with total lysate. EVs were isolated and analysed for the presence of positive markers (TSG101) or negative markers (calnexin). Upon overexpression of RAB31, EVs showed the presence of RAB31 protein at higher levels than total lysate, as shown by qPCR and immunoblotting (Figure 2e,f). Instead, the exocytosis inhibitor GW4869 was used to interfere with this process. Our findings indicated that GW4869 partially inhibited the expression of RAB31 (Figure 2g). In addition, some mRNA, microRNA and natural antisense RNA including HMBS, B2M, RPL13A, miR‐21 and miR‐192 in CRC cell line exosomes have been detected and compared in previously published literature (Chiba et al., 2012). We incorporated these molecules and observed that these entities were downregulated following GW4869 intervention (Figure S3). Therefore, RAB31 expression controls the degree of exocytosis in CRC cell lines of colorectal cancer.

3.3. RAB31‐induced exocytosis confers oxaliplatin resistance to colorectal cancer cells

To confirm the potential connection between RAB31 expression and oxaliplatin resistance, we modelled oxaliplatin IC50 values in colorectal cancer cell lines using the Genomics of Drug Sensitivity in Cancer (GDSC) website (Figure 3a). We selected several colorectal cancer cell lines, including SW1116, LS‐123, and HT‐29, for further experimentation. Of these, SW1116 and LS‐123 were observed as drug‐resistant cells, whereas HT‐29 cells were deemed sensitive. Combined with previous qPCR results (Figure 2b), cells expressing low levels of RAB31, such as HT‐29, exhibited lower IC50 values, while those expressing high levels of RAB31, such as SW1116, displayed increased resistance to oxaliplatin treatment. Our experimental findings demonstrate a trend similar to that of the GDSC profiles (Figure 3b). In our RAB31 knockdown cell model, we significantly reduced the IC50 of oxaliplatin (Figure 3c).

FIGURE 3.

FIGURE 3

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RAB31 secretion and expression are the main factors involved in the resistance of colon cancer cells to oxaliplatin. (a) The IC50 values for oxaliplatin were determined in various colon cancer cell lines. Drug resistance was indicated as red, while drug sensitivity was indicated as green. (b) The alamarBlue assay is used to measure the cell viability of various colon cancer cell lines treated with oxaliplatin(0.01–100μM), including HT‐29, HCT‐116, and SW620 cells. (c) The alamarBlue assay was used to measure the cell viability of SW1116 cells with or without RAB31 knockdown clones and treated with oxaliplatin. Two independent knockdown clones, shRAB31‐1 and shRAB31‐2. (d) The alamarBlue assay was used to measure the cell viability of HT‐29 cells under various treatments with conditioned medium (CM) and oxaliplatin. (e) The alamarBlue assay was used to measure the cell viability of the HT‐29 RAB31 overexpression cell model combined with GW4869 in response to oxaliplatin treatment. (f) An evaluation of the synergistic effect of GW4869 and oxaliplatin on HT‐29 RAB31 expression levels was plotted. **p < 0.01, ***p  <  0.001 compared to vehicle group by Student's t‐test.

To confirm the association of these events with the exocytotic properties of RAB31, we analysed the conditioned medium from the RAB31 overexpression model, which demonstrated heightened resistance to oxaliplatin in colorectal cancer (see Figure 3d). Conversely, introducing the exocytosis inhibitor GW4869 into the RAB31 overexpression model considerably enhanced the response to oxaliplatin (Figure 3e). More importantly, oxaliplatin and GW4869 exhibited synergistic effects in a colorectal cancer model with RAB31 overexpression (Figure 3f and Figure S4). Taken together, these findings suggest that RAB31 expression enhances exocytosis, giving rise to drug resistance.

3.4. EMT and RAB31 form a regulatory loop that promotes exocytosis and metastasis

During the process of epithelial‐to‐mesenchymal transition (EMT), changes in tissue morphology occur, while mesenchymal‐type cells facilitate drug resistance and exocytosis, which can ultimately lead to tumour metastasis. These factors are widely acknowledged in literature (Islam et al., 2022; Park et al., 2022). In this study, we aimed to examine the association between RAB31 expression and both mesenchymal and epithelial markers in CRC patients with colorectal cancer. The study found a positive correlation between the RAB31 gene's expression in colorectal cancer and the mesenchymal markers CDH2 (R = 0.84), SNAI2 (R = 0.9), TWIST1 (R = 0.85), and SNAI1 (R = 0.61) (Figure S5A). In addition, gene expression was negatively correlated with EMT‐related microRNA miR‐203a‐3p (R = −0.350) in the clinical population (Quiñones‐Díaz et al., 2020) (Figure S5B) and displayed an inverse correlation with the epithelial‐type markers CDH1 (R = −0.095) and TJP3 (R = −0.31) (Figure S5C). Not only do we detect expression of EMT molecules, but we also calculate the previously defined “EMT Score” algorithm by scientists (Salt et al., 2014). We studied the transcriptome profiles of 34 CRC cell lines (GSE36133), extracted EMT markers and RAB31 expression and observed a positive correlation between EMT score and RAB31 expression (Figure S6 and Table S1).

To verify whether the association between RAB31 and the EMT score in the clinical data above could be demonstrated in the colorectal cancer cell expression profile, we assessed the expression levels of RAB31 and EMT‐enabling genes, which had been evaluated for their corresponding EMT score (Matsuda et al., 2016), in the colorectal cancer cells (Figure 4a). Additionally, we evaluated the increased migratory and invasive potential of colorectal cancer cells following the overexpression of RAB31 (Figure 4b). Additionally, the luciferase reporter gene assay demonstrated the restoration of E‐cadherin promoter activity in the RAB31 knockdown model, and vice versa (Figure 4c). Upon RAB31 overexpression, the integration of multiple target genes (CDH1, TJP1, SNAI2, SNAI1, VIM, TWIST1 and miR‐18a) was verified through qPCR, with a trend of EMT observed (Figure 4d). Slug and vimentin expression was upregulated by RAB31 overexpression (Figure 4e), whereas they were downregulated by RAB31 knockdown (Figure 4f). Adding the exocytosis inhibitor GW4869 to the overexpression model also suppressed EMT (Figure 4g and Figure S7). Based on these findings, we can conclude that there is a relationship between RAB31 expression, exocytosis, and EMT.

FIGURE 4.

FIGURE 4

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Interaction between RAB31 and EMT‐related molecules in colorectal cancer cell lines. (a) Western blots expressing RAB31, E‐cadherin, Snail, Slug and Vimentin in a panel of colorectal cancer cells. (b) Migration/invasion ability (%) in HT‐29 cells with or without RAB31 overexpression plasmids. (c) Luciferase reporter activity of the E‐cadherin molecule in models of RAB31 overexpression and RAB31 knockdown colorectal cancer, respectively. (d) qPCR analysis was performed for the expression of EMT‐related markers (CDH1, TJP1, SNAI2, SNAI1, VIM, TWIST1 and miR‐18a) in the RAB31 expression model. (e) Western blots showing the RAB31, Slug, and Vimentin in HT‐29 cells with or without RAB31 overexpression plasmids. (f) Western blots showing the RAB31, Slug, Vimentin and E‐cadherin in SW620 cells with or without shRAB31 clones. (g) Migration/invasion ability in models of overexpression of HT‐29 RAB31 with or without GW4869 treatment. EMT, epithelial‐mesenchymal transition; qPCR, quantitative polymerase chain reaction,*p < 0.05, **p < 0.01, ***p  <  0.001 compared to vehicle group by Student's t‐test.

3.5. RAB31 is involved in ESCRT‐independent pathways and facilitates the fusion and release of AGR2

To explain the role of RAB31 in EV secretion and EMT, we posited that RAB31 and its interaction partners regulate membrane fusion and exocytosis. We first used EM (electron microscope) imaging to observe cell morphology and vesicle formation. In the RAB31 overexpression model, we found that there were more vesicles such as MVBs, ILVs and lysosomes (Figure 5a) and NTA proved that the RAB31 overexpression group could produce more vesicles (Figure S8). We also observed a significant increase in the fluorescent signal of EV‐specific membrane protein markers isolated from the RAB31 overexpression model compared to the vector group (Figure 5b). Previous findings suggest that RAB31 cuts through an ESCRT‐independent exocytosis pathway (Narumi et al., 2015; Tomoshige et al., 2018; Wodziak et al., 2016). Therefore, we analysed several ESCRT‐dependent and independent molecules to identify this signature. The RAB31 overexpression models exhibited significantly elevated ESCRT‐independent markers such as FLOT1/2, CD63 and TBC1D2B compared to controls (Figure 5c). We opted for VPS24 and FLOT1 shRNA to interfere with the exocytosis process. FLOT1 knockdown can bring about more significant changes in particle intensity/size (Figure 5d), EV‐related miRNA expression (Figure 5e), EMT marker expression (Figure 5f) and cell migration ability (Figure 5g). The evidence supports the findings that RAB31 depends on the ESCRT‐independent model to promote cancer cell exocytosis.

FIGURE 5.

FIGURE 5

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RAB31 plays a role in the exocytosis pathway, which operates independently from ESCRT. (a) Representative images of RAB31‐expression model in HT‐29 cells examined by transmission electron microscopy (TEM). Blue arrows indicate exocytosis; yellow and red arrows indicate ILVs and MVBs, respectively. Scale bar: 1 μm and 0.5 μm, respectively. (b) Representative images of exosomes between vector and RAB31‐overexpression models in HT‐29 cells examined by confocal microscopy. Analysis represents exosomal membranes. Blue: DAPI. Green: exosome membrane. Scale bar: 25 μm. (c) Western blots showing the ESCRT‐dependent molecules (TSG101, VPS24, VPS28, CD9 and CHMP4B) and ESCRT‐independent molecules (EGFR, FLOT1/2, CD63 and TBC1D2B) in EVs isolated from RAB31 overexpression models. HSP70 was used as an internal control. (d) EV concentration (particles/ml) and intensity (a.u.) of the HT‐29 RAB31 overexpressing cells with or without VPS24 and FLOT shRNA treatment were examined by nanoparticle tracking analysis (NTA). (e) qPCR analysis of miR‐21 and miR‐192 expression in EVs isolated from RAB31 overexpression models with or without VPS24 and FLOT shRNA treatment. (f) Western blots showing RAB31, Slug, Vimentin and E‐cadherin in HT‐29 RAB31 overexpressing cells with or without VPS24 and FLOT shRNA treatment. Tubulin was used as an internal control. (g) Migration ability of HT‐29 RAB31 overexpressing cells with or without VPS24 and FLOT shRNA treatment. ESCRT, endosomal sorting complex required for the transport; EV, extracellular vesicle; ILVs, intraluminal vesicles; MVBs, multivesicular bodies. **p < 0.01, ***p  <  0.001 compared to the vehicle group by Student's t‐test.

We investigated whether EVs associate with fusion components or interaction partners other than RAB31‐EGFR. We analysed the RAB31 interactome, concentrating on eight membrane candidates: ABCC2, EGFR, TCTN2/TCTN3, CD55, FLOT1, AGR2, STX7 and NCSTN (Figure 6a). Among these candidates, we observed a notable increase in AGR2 expression in both intracellular and isolated EVs. Further analysis revealed a direct interaction between AGR2 and RAB31 using a two‐way immunoprecipitation assay (Figure 6c). Additionally, an increase in AGR2 was observed in the model utilising EGF to catalyse EGFR‐regulated exocytosis (Figure 6d). Notably, the phosphorylation status of EGFR and EGF stimulation had no significant impact on AGR2 function (Hong et al., 2021). To demonstrate the impact of AGR2 inhibition, we observed that RAB31‐induced EMT was inhibited upon the downregulation of AGR2 (Figure 6e). Additionally, we detected heightened arginase activity, indicative of highly activated AGR2 function, with a significant increase upon RAB31 overexpression. This activity was fully compromised by the use of the dominant‐negative S19N mutant form (Yeo et al., 2015) (Figure 6f). Using the same cell model, the multiplex model conspicuously observed fusion at the membrane area, while the control or dominant negative models did not exhibit identical results (Figure 6g). Our model manipulations show that overexpression of RAB31 increases exocytosis in cancer cells and that RAB31 also leaves the cell upon fusion with the EV membrane.

FIGURE 6.

FIGURE 6

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RAB31 fuses AGR2 into vesicles that target Epidermal Growth Factor Receptor (EGFR)‐directed ESCRT‐independent vesicles. (a) Venn diagram indicates RAB31 interaction partners and only molecules in the membrane location. (b) Western blots detect RAB31/AGR2 expression and EV‐related molecules (CD9, CD63, TSG101) in EV isolated from HT‐29 cells with or without RAB31 overexpression. (c) Immunoprecipitation analysis of the protein interaction affinity between RAB31 and AGR2 in HT‐29 RAB31 overexpression models. (d) Western blots detected AGR2, phosphor/total‐EGFR and phosphor/total‐Erk expression in HT‐29 cells with or without EGF (5–25 ng/ml) treatment. Actin was used as an internal control. (e) Western blots detected AGR2, Slug, Vimentin and E‐cadherin expression in HT‐29 RAB31 cells with or without siAGR2 transfected. Actin was used as an internal control. (f) Arginase activity was detected between vector, RAB31 wild‐type and RAB31 S19N expression models. (g) Immunofluorescence signals of RAB31, AGR2 and DAPI among vector, RAB31 wild‐type and RAB31 S19N expression models were detected by confocal microscopy. The degree of colocalisation of RAB31/AGR2 in membrane regions was quantified by Metamorph software. ESCRT, endosomal sorting complex required for the transport; EV, extracellular vesicle. ***p  <  0.001 compared to vehicle group by Student's t‐test.

3.6. RAB31 is found to impact cancer‐associated fibroblast (CAF) development and presentation by means of AGR2 discharge

In addition to facilitating malignant progression and metastasis in tumours, exocytosis releases factors that induce reprogramming of the tumour microenvironment and alter immune infiltration. To investigate this, we used a bioinformatics algorithm to examine the expression of RAB31 and various immune responses. Our findings revealed a positive correlation between RAB31 and CAFs in colon cancer (Figure 7a). Additionally, scatter plots were analysed using four distinct statistical models that revealed reliable patterns between RAB31 expression levels and infiltration levels (Figure 7b). Notably, CAF events were a significant independent prognostic factor in colorectal cancer (Figure 7c).

FIGURE 7.

FIGURE 7

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RAB31 regulates CAF formation and metastatic capacity through secretion of AGR2. (a) The correlation between RAB31 expression levels and cancer‐associated fibroblast events was investigated by several statistical algorithms. The predictions and calculations are from the TIMER website. (b) The scatter plot between RAB31 expression levels and cancer‐associated fibroblast events was investigated by several statistical algorithms (EPIC, MCPCOUNTER, XCELL and TIDE). The predictions and calculations are from the TIMER website. (c) Kaplan‐Meier analysis of the percentage of CAF with concomitant low or high levels determined algorithmically by the TIMER website at the endpoint of overall survival probability in patients with colon adenocarcinoma. (d) qPCR analysis of ACTA2, CTGF, CXCL1 and IL‐6 expression in CAF cells after adding HT‐29 vector or RAB31 overexpression conditioned medium. (e) Migration ability of SW620 and HT‐29 cells combined with control or CAF‐conditioned medium, respectively. (f) qPCR analysis of ACTA2, CTGF and IL‐6 expression in CAF cells after adding HT‐29 RAB31 with wild‐type, mutant, and wild‐type combined shAGR2, respectively. (g) Schematic representation of fusion vesicles and mechanisms of resistance to oxaliplatin resistance in the dynamic progression of colon cancer. CAF, cancer‐associated fibroblasts; qPCR, quantitative polymerase chain reaction. ***p  <  0.001 compared to vehicle group by Student's t‐test.

We developed a culture system comprising colorectal cancer cell lines and fibroblasts using several established canonical CAF biomarkers. After adding condition medium in the RAB31 overexpression group, CAF markers were upregulated compared with the control group (Figure 7d). Furthermore, the conditioned medium (CM) of the treated cells (CAF‐CM) significantly enhanced the migration capacity of the colorectal cancer cell lines (Figure 7e). Likewise, we recruited dominant negative RAB31 (S19N) and shAGR2. CAF labelling previously elevated by addition of conditioned medium in which RAB31 was overexpressed was reversed (Figure 7f). Based on this evidence, we demonstrated that the fusion of RAB31 with EGFR/AGR2 during exocytosis and EMT is a hastened process that induces oxaliplatin resistance and CAF development (Figure 7g). This finding warrants further attention in the treatment and research of colorectal cancer.

4. DISCUSSION

Irinotecan and oxaliplatin are currently the most prevalent drugs used to treat advanced colorectal cancer because of their ability to damage DNA replication, hindering the growth of cancerous cells. Objective statistics indicate that approximately 30%–40% of patients experience relapse and drug resistance, calling for a need to seek an efficient target to enhance drug resistance and thus benefit colon cancer patients (Duineveld et al., 2016). This is primarily due to drug resistance, as prescribed therapeutic drugs cannot inhibit the progression of cancer cells. In this study, we propose a primary role for RAB31 in the profiling of oxaliplatin and irinotecan in drug‐resistant cell lines. Clinical analysis of TCGA indicated a significantly different recurrence‐free survival outcome (p = 0.047) when RAB31 was increased in colorectal cancer. RAB31 expression was consistently induced in colorectal cancer cells exposed to an oxaliplatin environment, as observed in various genetic profiles. During this period, RAB31 continued to show an upward trend until the cells developed drug resistance. Studies have shown that upregulation of RAB31 is associated with oxaliplatin resistance in colorectal cancer(Zheng et al., 2015).

RAB31 has been implicated in numerous malignancies in previous studies (Li et al., 2019). It is the most researched marker for breast cancer (Chua & Tang, 2015). The expression of RAB31 is linked to poor prognosis, particularly among those with the ER+ subtype (Jin et al., 2012; Kotzsch et al., 2008;2017). Additionally, it has been demonstrated that MCU1 regulates RAB31, and when overexpressed, RAB31 promotes increased proliferation and sphere formation in breast cancer cells (Young et al., 2010). The effects of RAB31 on cell growth and death have been reported in gastric cancer and glioblastoma (Chen et al., 2018; Pan et al., 2016). RAB31 regulates miR‐30c‐2‐3p, which controls GLI1 and subsequently influences the growth and death of gastric cancer cells. RAB31 may also be regulated by RAI14 (Chen et al., 2018). A recent study showed that overexpression of RAB31 leads to reduced efficacy of bortezomib and increased anti‐apoptotic activity (Yoon et al., 2019), suggesting that RAB31 promotes drug resistance in various cancers. Researchers have discovered that Rab proteins are associated with multidrug resistance in various types of cancers. This indicates that the overexpression of Rab proteins can affect cancer cell resistance to drugs (Engstrand et al., 2018; Gopal Krishnan et al., 2020; Han et al., 2020). Notably, this study is the first to describe the potential role of RAB31 in oxaliplatin resistance. EMT is a cellular mechanism that responds to environmental changes such as drug stimulation. The role of RAB31 in regulating tumour growth through the mTOR/p70S6K/Cyclin D1 pathway has been demonstrated in colorectal cancer (Yang et al., 2020). However, the link between colorectal cancer and EMT has not yet been investigated. Both microarray and clinical studies have demonstrated that RAB31 is significantly associated with mesenchymal markers and inversely associated with epithelial markers in colorectal cancer. We need to continue to explore whether RAB31 affects EMT and E‐cadherin directly or through indirect regulatory mechanisms. Our next step will be to extract the miRNAs or mRNAs involved in EVs to demonstrate that they play important roles in E‐cadherin expression and EMT. In addition to the targets detected in this study, we will also establish RNA‐seq and ChIP‐seq for demonstration in further experiments. RAB31 expression has been confirmed in many colorectal cancer cell lines, which is consistent with clinical data that may indicate variations in morphology during the EMT process. The expression of RAB31 has been demonstrated to affect cell growth and motility in various cancer types such as esophageal squamous cell carcinoma, osteosarcoma and cervical cancer (Huang et al., 2022; Liu et al., 2018; Wu et al., 2020). Establishing a RAB31‐based model confirmed a correlation between the expression of E‐cadherin and mesenchymal‐related molecules (SNAI2, VIM and TWIST1) at the RNA and protein levels in colorectal cancer cells and RAB31 biological function. Evidence suggests that EMT mediated by RAB31 contributes to oxaliplatin resistance in colorectal cancer. Furthermore, the level of RAB31 in cells was found to be correlated with the IC50 of oxaliplatin, as established by the relationship between cells and IC50. Knocking down RAB31 increased cell sensitivity to oxaliplatin. The findings of this study support the hypothesis that RAB31 modifies the morphology and drug responses of colorectal cancer cells.

Recently, the tumour microenvironment has been suggested as a means to promote tumour cells to evade suppression by both drug therapy and the immune system (Wei et al., 2021; Zheng et al., 2020). In this context, EVs secretion plays a critical role and may serve as a promising therapeutic target for colorectal cancer. (Li et al., 2019; Pan et al., 2016). Studies have shown that EVs serve as a means of communication between tumour cells and surrounding cells (Zhang et al., 2022). Rab proteins have been implicated in membrane‐related physiological functions such as exocytosis (Banworth & Li, 2018; Hendrix et al., 2010). In our study, we showed that RAB31 overexpression led to an increase in RNA and protein levels, suggesting an increase in exocytosis efficacy. Upon inhibiting extracellular vesicle (EV) function, we observed a reversal of RAB31‐mediated epithelial‐mesenchymal transition processes and a consequent change in cellular resistance to oxaliplatin drugs. Moreover, it is noteworthy that evidence supporting the use of EV inhibitors indicates that they synergistically enhance cell sensitivity to oxaliplatin drugs. This finding supports the idea that RAB31 plays a crucial role in altering EMT phenotypes and drug resistance. Whether EMT or oxaliplatin, there is growing evidence that EVs and their cargo, including long non‐coding RNAs, miRNAs and some DNA fragments, may be released and involved. In this study, we roughly detected several targets already mentioned, such as EMT‐related target, miR21 and miR‐192 (Figure S3), as well as oxaliplatin resistance‐related molecules, such as CPT1A and miR‐1915‐3p (Figure S9) (Lin et al., 2021; Xiao et al., 2021). We are using NGS technology to further reveal differentially expressed genes (DEGs) through EV isolation and try to find more candidate genes.

Rab protein‐mediated membrane transport is required for interactions with diverse proteins (D'Adamo et al., 2014). Through interactome analysis, several new partners of RAB31 have been identified in colorectal cancer. In previous studies, AGR2's distribution exhibited was positively correlated with EGFR, potentially enabling stimulation of EGFR signalling. Additionally, RAB31 may have the ability to guide EGFR towards multivesicular endosomes (Narumi et al., 2015; Tomoshige et al., 2018; Wodziak et al., 2016). However, we discovered that AGR2 directly interacts with RAB31 and contributes to EMT and exocytosis in colorectal cancer, which are unrelated to EGFR signalling. Furthermore, AGR2 has been linked to unfavorable prognosis in colorectal cancer, and activation of the Wnt/β‐catenin axis can prompt AGR2 to promote stem cell activity (Dahal Lamichane et al., 2019). The study results suggest that AGR2 affects not only the RAB31 interaction, but also EMT and exocytosis in colorectal cancer. Despite overexpression of RAB31 activating EGFR signalling, AGR2 protein levels remained unaffected by inhibition of EGFR signalling, and Rab‐31‐mediated resistance to oxaliplatin persisted.

Previous studies have shown that cancer‐associated fibroblasts mediate the extracellular form of RAB31, thereby driving the progression of colorectal cancer. More research is required to determine the function of RAB31 in the tumour microenvironment (Yang et al., 2020). To fill this knowledge gap, our study proposes that EVs could be one mechanism by which RAB31 influences drug resistance in colorectal cancer. In summary, our findings contribute to the understanding of RAB31 in the tumour microenvironment. The use of RAB31 represents a promising target for investigating drug resistance in colorectal cancer and may offer an alternative therapy.

AUTHOR CONTRIBUTIONS

Conception and design: Yu‐Chan Chang, Ming‐Huang Chen, Chi‐Long Chen and Michael Hsiao. Development of methodology: Yu‐Chan Chang, Chien‐Hsiu Li, Ming‐Hsien Chanand and Yi‐Fang Yang. Acquisition of data (provided animals, acquired and managed patients, and provided facilities): Yu‐Chan Chang, Chien‐Hsiu Li, Ming‐Hsien Chan, Yi‐Fang Yang and Meng‐Lun Lu. Data analysis and interpretation (e.g., statistical analysis, biostatistics, computational analysis): Yu‐Chan Chang, Chien‐Hsiu Li, Ming‐Hsien Chanand and Yi‐Fang Yang. Writing, review, and/or revision of the manuscript: Yu‐Chan Chang, Chien‐Hsiu Li, Ming‐Hsien Chan, Yi‐Fang Yang, Ming‐Huang Chen, Chi‐Long Chen and Michael Hsiao. Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Ming‐Huang Chen and Chi‐Long Chen. Study supervision: Michael Hsiao.

CONFLICT OF INTEREST STATEMENT

The authors disclosed no conflicts.

CRC tissues were recovered from the Department of Pathology, Taipei Municipal Wan Fang Hospital (Taipei, Taiwan), with approval from the Institutional Review Board (TMU‐IRB 99049).

Supporting information

Supporting Information

JEX2-3-e141-s001.docx (2.7MB, docx)

Supporting Information

JEX2-3-e141-s002.xlsx (11.2KB, xlsx)

ACKNOWLEDGEMENTS

We would like to thank the GRC Instrument Core Facilities for their support with the Affymetrix microarray, IVIS spectrum, Aperio digital pathology analyses, and AS‐EM core facility. This study was supported by the Ministry of Science and Technology [MOST 111‐2320‐B‐038‐061] and [NSTC 112‐2320‐B‐038‐048] to C. L. Chen.

Chang, Y.‐C. , Yang, Y.‐F. , Li, C.‐H. , Chan, M.‐H. , Lu, M.‐L. , Chen, M.‐H. , Chen, C.‐L. , & Hsiao, M. (2024). RAB31 drives extracellular vesicle fusion and cancer‐associated fibroblast formation leading to oxaliplatin resistance in colorectal cancer. Journal of Extracellular Biology, 3, e141. 10.1002/jex2.141

Contributor Information

Chi‐Long Chen, Email: chencl@tmu.edu.tw.

Michael Hsiao, Email: mhsiao@gate.sinica.edu.tw.

DATA AVAILABILITY STATEMENT

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information

JEX2-3-e141-s001.docx (2.7MB, docx)

Supporting Information

JEX2-3-e141-s002.xlsx (11.2KB, xlsx)

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

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