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Article

Ras-Related Mutants Identified in Young-Onset Colorectal Cancer Display Divergent Phenotypes and Retain Their Pro-Angiogenic Effects

by
Andrei Phillip L. David
1,†,
Mariko Isabelle P. Galvez
1,‡,§,
Sidney Allen A. Chua
1,§,
Dominique Mickai G. Leaño
1,§,
Dennis L. Sacdalan
1,2 and
Reynaldo L. Garcia
1,*
1
Disease Molecular Biology and Epigenetics Laboratory, National Institute of Molecular Biology and Biotechnology, University of the Philippines Diliman, Quezon City 1101, Philippines
2
Division of Medical Oncology, Department of Medicine, University of the Philippines Manila, Manila 1000, Philippines
*
Author to whom correspondence should be addressed.
†
Current address: International Max Planck Research School for Molecular Biology, University of Göttingen, 37077 Göttingen, Germany.
‡
Current address: College of Medicine, University of the Philippines Manila, Manila 1000, Philippines.
§
These authors contributed equally to this work.
Cells 2026, 15(4), 349; https://doi.org/10.3390/cells15040349
Submission received: 26 November 2025 / Revised: 5 February 2026 / Accepted: 6 February 2026 / Published: 14 February 2026
(This article belongs to the Section Cell Signaling)
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Abstract

The Ras-related (RRAS) gene is a member of the Ras superfamily and remains largely uncharacterized compared to KRAS, NRAS, and HRAS. Its role in tumorigenesis remains poorly documented, as evidenced by its lack of canonical mutations in any cancer type. This study investigated the effects of the novel RRAS R78W and E63D mutants—identified in Filipino young-onset colorectal cancer (YO-CRC) patients—on cancer hallmarks. In silico analysis was performed to predict the effect of the mutations on RRAS structure. F-actin staining of transfected NIH3T3 cells displayed massive cytoskeletal remodeling and formation of migratory and invasive structures. RRAS R78W enhanced migration when compared to wild-type RRAS in NIH3T3 and HCT116 cells, whereas neither mutant affected invasive capacity. Both mutants did not abolish the pro-angiogenic ability of wild-type RRAS in endothelial tube formation assays. RRAS E63D conferred resistance to apoptosis in both cell lines. Both mutants had no effect on cellular proliferation in either cell line. Overexpression of both mutants did not increase Akt and Erk1/2 phosphorylation. In silico analysis further suggests that the mutations confer increased GEF-binding ability versus wild-type. Results of the study highlight the need to characterize Ras isoform- and mutation-specific phenotypic effects, which may have repercussions in CRC management.

Graphical Abstract

1. Introduction

Colorectal cancer (CRC) is one of the most common types of cancer, ranking third in terms of incidence and second in terms of mortality worldwide [1]. An increase in the number of young-onset CRC (YO-CRC) cases has been observed in the last decade amidst a decline in the number of CRC cases globally [2,3]. YO-CRC accounts for 14% of the total number of CRC cases in the Philippines, which is markedly higher than the global average of 9.7% [4,5]. The surge in YO-CRC cases can be partly attributed to the increasingly westernized lifestyle of individuals, and reports suggest that YO-CRC presents a distinct molecular, histological, and anatomical landscape when compared to late-onset CRC (LO-CRC) [6,7].
The classical Ras superfamily of proteins is implicated in the onset and progression of CRC by activating downstream pathways such as MAPK and PI3K/Akt pathways. Ras proteins are small GTPases that function as molecular switches through cycling between active GTP-bound and inactive GDP-bound states [8]. Due to the ability of Ras to activate a myriad of cellular processes, mutations in the classical Ras isoforms are implicated in various types of cancer. KRAS mutations are found in around 88% of pancreatic cancer and 50% of colorectal cancer cases, whereas mutations in NRAS are linked to the onset and progression of leukemia and skin cutaneous melanoma [9]. Alternatively, the presence of activating mutations in lesser-known members of the Ras superfamily can potentially induce oncogenesis comparable to that of the classical Ras isoforms.
RRAS is a member of the R-Ras subfamily that codes for the RRAS protein [10]. RRAS, together with RRAS2 and MRAS, was first identified through a low-stringency hybridization experiment aimed at characterizing novel Ras-related genes [11]. The human RRAS protein shares 48% amino acid sequence identity with classical Ras proteins [12]. Human and mouse R-Ras proteins are highly similar, with 95% amino acid sequence identity [13].
Like the classical Ras proteins, R-Ras contains a G-domain consisting of GTP-binding and effector-binding regions. This cycle is tightly regulated by guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs) [14]. Several GEFs stimulate GTP/GDP exchange in R-Ras. These include RasGRF, C3G, and CalDAG-GEFs, all of which bind to the switch II domain of R-Ras [15,16]. In contrast, RalGDS—a GEF linked to cell survival and tumor progression—directly interacts with R-Ras through the switch I domain [17]. GTP hydrolysis of R-Ras is enhanced by specific GAPs such as p120GAP, GAP1m, and GAP1IP4BP [13,18].
Aside from its core GTPase activity, R-Ras has unique structural features that influence its function. Its unique 26 N-terminal amino acid sequence regulates actin organization, lamellipodia formation, and cell migration through interaction with Rac [14]. The C-terminal hypervariable region (HVR) contains unique sequence motifs that allow R-Ras to interact with RhoA, forming focal adhesions and stress fibers [19]. Both Rac and Rho signaling allow for the dynamic turnover of actin to promote the formation of transient migratory structures in the cell. During migration, Rac inactivates Rho to promote ruffling and lamellipodial formation, leading to the rapid accumulation of actin filaments at the leading edge of the cell and actin disassembly at the rear end [20].
RRAS performs some biological functions distinct from the classical Ras isoforms. While KRAS primarily drives proliferation through the MAPK pathway, RRAS promotes cell survival, spreading, migration, and cytoskeletal remodeling via Rac/Rho signaling. RRAS activates PI3K signaling to promote cell survival in COS-7 kidney fibroblast and BA/F3 murine pro-B cell lines [21,22]. In breast epithelial cells, RRAS was shown to localize at the leading edge of migrating cells to promote Rho activation and Rac inactivation [23]. RRAS promotes migration in melanoma cells by binding to Filamin A [24]. An E63G mutation in RRAS was shown to promote cell survival and RalGDS binding in NIH3T3 cells [17]. Meanwhile, functional studies in R-Ras knockout mice have revealed its role in vascular integrity, immune cell trafficking, and endothelial–pericyte function [25,26,27].
RRAS plays an ambiguous role in cancer. In specific contexts such as cervical and gastric cancers, RRAS is involved in tumor progression by promoting migration and invasion [28,29]. Moreover, RRAS was shown to promote migration and invasion in vitro using HCT116 and SW480 colorectal cancer cell lines [30]. However, in MCF7 breast cancer cell lines, RRAS functions as a tumor suppressor [31]. This functional ambiguity might stem from cell-type-specific expression of downstream effectors, with the precise mechanisms of each remaining largely unknown.
The unclear role of RRAS in cancer is further obscured by the lack of data on clinically relevant mutations. Unlike the classical Ras isoforms, RRAS lacks a canonical hotspot mutation. Prior functional studies have relied on generating Rras mutations such as T61S, E63G, and Y66C with Q87L cooperative mutations, which are solely based on Hras effector domain mutations [17]. Previous studies reported that the rare RRAS G39dup and V55M germline mutations identified in Noonan syndrome enhance GEF-binding ability and MAPK signaling, whereas patients with non-syndromic juvenile myelomonocytic leukemia harboring the rare somatic mutations G39dup and Q87L have cooperative NRAS mutations that led to rapid disease progression [32]. Thus, there is a need to identify and characterize novel RRAS mutations from actual CRC patient cohorts to further understand its function in various cellular contexts, and how mutations in this isoform contribute to CRC pathology.
The advent of next-generation sequencing (NGS) allowed the identification and characterization of novel, non-hotspot mutations in the Ras superfamily that may play a role in CRC development and novel modes of resistance to therapy. Prospective, targeted NGS of YO-CRC tumors from Filipino patients revealed two novel mutations in RRAS: RRAS R78W (c. 232C>T) and RRAS E63D (c.189G>T) [4].
R78 is found near the switch II domain of RRAS, and a mutation from a positively charged arginine to the hydrophobic tryptophan might confer an unwanted effect on the protein. Position 63 can be found in the switch I domain, a highly conserved region of the protein. The switch I and II domains are highly exposed regions of Ras, allowing them to serve as docking sites for various effector and receptor molecules, including GEFs [33]. Hence, mutations on or near the switch domains might improve or disrupt the binding between RRAS and GEFs.
Here, we examined the effect of the novel RRAS mutations on various cancer hallmarks with respect to the wild-type RRAS and canonical KRAS G12D and NRAS Q61K mutations. The results of the study can provide insights into the role of RRAS in colorectal cancer and its biology in general. If further supported with mechanistic and in vivo studies, the mutations can serve as biomarkers for responsiveness to therapy.

2. Materials and Methods

2.1. Generation of Mutant RRAS Constructs

The canonical KRAS G12D and NRAS Q61K, as well as the wild-type RRAS constructs used in the study, are available in the laboratory and were previously cloned into the pTargeT™ mammalian expression vector (Promega Corporation, Madison, WI, USA). Wild-type RRAS was used as the template for generating the RRAS mutant constructs. Splicing-by-overlap-extension PCR-based site-directed mutagenesis was done to introduce the c.232C>T and c.189G>T mutations into the wild-type template to generate the RRAS R78W and E63D mutants, respectively. Wild-type forward and reverse external primers, and internal reverse and forward mutagenic primers were designed to amplify RRAS in two halves in two separate first-round PCR reactions. Aliquots of the two amplicons were used as templates in a second-round PCR to generate the mutant constructs using the external forward and reverse primers. The PCR primers used are listed in Table 1. Full-length RRAS R78W and E63D fragments were cloned into the pTargeT™ vector (Promega Corporation) via TA cloning.
Fragments were amplified in a polymerase chain reaction mixture containing 1X PCR buffer (Titanium® Taq PCR Buffer; Clontech Laboratories, Inc., Mountainview, CA, USA), 0.125 μM each of deoxynucleoside triphosphate (Promega Corporation), 0.5 μM each of appropriate forward and reverse primers, 0.1 U/μL Taq DNA polymerase (Clontech Laboratories, Inc.), and 1 ng/μL DNA template. The reaction mix was subjected to 25 cycles of denaturation at 94 °C for 30 s, annealing at 61 °C for 30 s, and extension at 72 °C for 30 s. A final extension step at 72 °C for 10 min was done to allow the complete generation of partially copied DNA fragments and addition of 3′ A-overhangs.
Orientation and sequence identity of the constructs were confirmed by Sanger sequencing. After verification, transfection-grade mutant RRAS plasmids were prepared using a QIAGEN® Plasmid Midi Kit (QIAGEN, Hilden, Germany) following the manufacturer’s protocol.
Expression of the wild-type and mutant RRAS proteins was verified by Western blot analysis (Figure S1) following the protocol described in Section 2.8 below.

2.2. Culture and Transfection of Cell Lines

NIH3T3 Mus musculus fibroblast (ATCC® CRL-1658™; American Type Culture Collection, Manassas, VA, USA) and HCT116 human colon cancer cells (ATCC® CCL-247™, ATCC) were maintained and used in subsequent functional assays. The NIH3T3 cell line is the most preferred cell line for studying Ras oncogenes due to its ability to express oncogenic phenotypes even in the absence of cooperative mutations [34]. For assays requiring an epithelial phenotype, the HCT116 cell line—which is wild-type for the RRAS gene—was used. Transfected oncogenes can still modulate their oncogenic phenotype despite harboring a KRAS G13D mutation [35]. HUVEC was used for the endothelial tube formation assay as described in a previous study [36].
NIH3T3 cells were grown in Dulbecco’s Modified Eagle Medium (DMEM; Gibco; Thermo Fisher Scientific, Inc., Waltham, MA, USA) supplemented with 10% newborn calf serum (NBCS; Gibco; Thermo Fisher Scientific, Inc.) and 3.7 g/L sodium bicarbonate. HCT116 cells were cultured in Roswell Park Memorial Institute 1640 medium (RPMI-1640; Gibco; Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (FBS; Gibco; Thermo Fisher Scientific, Inc.) and 2.0 g/L sodium bicarbonate. Human umbilical vein endothelial cell (HUVEC; ATCC® CRL-1730™, ATCC) was propagated in Ham’s F-12K medium supplemented with 10% FBS, 50 μg/mL endothelial cell growth supplement, and 100 μg/mL heparin. The cell lines were incubated in a humidified atmosphere containing 5% CO2 at 37 °C.
For cancer hallmark assays, around 60,000 NIH3T3 cells or 150,000 HCT116 cells were seeded in a 12-well plate and transfected with appropriate pTargeT™ constructs using Lipofectamine™ 2000 Transfection Reagent (Thermo Fisher Scientific, Inc.). A mixture of 1 μg construct and Lipofectamine™ 2000 Transfection Reagent (Thermo Fisher Scientific, Inc.) was prepared in Opti-MEM™ reduced serum medium (Thermo Fisher Scientific, Inc.) and added to each well. To assess transfection efficiency, a parallel transfection using a mammalian expression vector with green fluorescent protein reporter called pmR-ZsGreen1 (Clontech Laboratories, Inc.) was performed. At least 70% transfection efficiency was routinely observed before proceeding with downstream assays.

2.3. F-Actin Staining

At 24 h post-transfection, around 2500 NIH3T3 cells/well were reseeded in a 96-well clear-bottom black plate and incubated for 36 h. Cells were fixed with cold 4% paraformaldehyde in 1X phosphate-buffered saline (PBS) for 5 min. Cells were washed with ice-cold PBS thrice for 5 min each, after which permeabilization of cells was done by adding 0.1% Triton X-100 in 1X PBS for 5 min. Blocking was then performed by incubating the samples with 1% bovine serum albumin in 1X PBS for 1 h. F-actin filaments were stained using Alexa Fluor™ 488 Phalloidin (Thermo Fisher Scientific, Inc.) for 30 min. Cells were washed thrice with 1X PBS for 5 min, followed by the addition of the nuclear counterstain Hoechst 33342 (Thermo Fisher Scientific, Inc.) for 5 min. Fluorescent images were obtained using the IN Cell Analyzer 6000 (GE Healthcare Life Sciences, Marlborough, MA, USA) at 40× magnification to visualize stained F-actin structures and nuclei. Nuclear area and cytoplasmic shrinkage were quantified from DAPI- and phalloidin-stained fluorescent micrographs, respectively, using Fiji version 2.10.0 [37].

2.4. Scratch Wound Assay

Transfected NIH3T3 or HCT116 cells were grown to confluence in a 96-well plate. A straight-line scratch was made on the confluent monolayer using a sterile white pipette tip. Debris was removed by washing the monolayer with 1X PBS. Cells were stained using 2 μg/mL calcein AM (Thermo Fisher Scientific, Inc.) diluted in DMEM with 0.5% NBCS for NIH3T3 cells and RPMI with 4% FBS for HCT116 cells. An image of the artificial wound was immediately captured using the IN Cell Analyzer 6000 (GE Healthcare Life Sciences). Calcein AM was replenished after 16 h, and another fluorescent micrograph was obtained at the same field of view. The wound area at different time points was analyzed using Fiji version 2.10.0 [37], and the change in wound closure was obtained relative to the initial wound area.

2.5. Invasion Assay

Transwell invasion assay was performed using HTS Transwell®-96 well permeable support (8.0 μm Polyester membrane, Corning Life Sciences, Tewksbury, MA, USA). At 24 h post-transfection, NIH3T3 (5 × 103 cells/well) and HCT116 (1 × 104 cells/well) cells were resuspended in serum-free media and seeded into the upper chamber of the transwell inserts pre-coated with collagen. For migration controls, cells were seeded in uncoated transwell inserts. The lower chamber was filled with 250 µL of complete medium to serve as a chemoattractant. Following a 48 h incubation, cells were stained with calcein AM (Thermo Fisher Scientific, Inc.) for 10–15 min. Unmigrated and non-invaded cells remaining on the upper surface of the membrane were gently removed by swabbing and washing with 1x PBS. Cells that migrated or invaded the underside of the membrane were imaged using the IN Cell Analyzer 6000 (GE Healthcare Life Sciences) at 4× magnification and quantified using IN Carta® Image Analysis Software (version 1.17.0412545 (Molecular Devices, San Jose, CA, USA). Invasion was calculated by normalizing the number of invading cells to the corresponding migration controls.

2.6. Endothelial Tube Formation Assay

HCT116 cells were grown in low-serum conditions 24 h post-transfection. At 48 h post-transfection, the conditioned media harboring pro-angiogenic factors from transfected HCT116 cells were harvested and filtered. HUVEC was resuspended in a 1:1 mixture containing the conditioned media and HUVEC maintenance media, which was subsequently seeded in a 96-well plate coated with Geltrex™ LDEV-Free Reduced Growth Factor Basement Membrane Matrix (Thermo Fisher Scientific, Inc.). HUVEC was incubated for 4 h at 37 °C in the mixture containing 5% CO2 to facilitate the formation of capillary-like vessels. At 4 h post-seeding, HUVEC was stained using 6.4 μg/mL calcein AM (Thermo Fisher Scientific, Inc.) and incubated for 30 min. Fluorescent micrographs were obtained using the IN Cell Analyzer 6000 (GE Healthcare Life Sciences) at 4× magnification. Tube formation analysis was done using the Angiogenesis Analyzer ImageJ plugin with Fiji version 2.10.0 [37,38,39].

2.7. Apoptosis Assay

NIH3T3 or HCT116 cells were seeded and transfected in a 96-well clear plate. At 24 h post-transfection, apoptosis was induced in NIH3T3 cells by reducing the serum concentration to 0.1% NBCS. For HCT116 cells, 10 mM sodium butyrate was added to the maintenance media to induce apoptosis. At 20 h post-induction, Caspase-Glo® 3/7 Assay reagent (Promega Corporation) was added to each well, and the plate was incubated for 2 h with shaking at 40 rpm. A 100 μL aliquot of lysate per well was transferred to an opaque white plate, and luminescence readings were obtained using a CLARIOstar® microplate reader (BMG Labtech, Ortenberg, Germany). Caspase-3/7 activity is reported as normalized relative luminescence unit (RLU) to uninduced setups.

2.8. Cell Proliferation Assay

Transfected NIH3T3 or HCT116 cells were reseeded into two 96-well plates at 24 h post-transfection. An aliquot of 10 μL CellTiter 96® AQueous One Solution Cell Proliferation Assay reagent was added to each of the wells after reseeding, at 48 h post-transfection for NIH3T3 cells, and 72 h post-transfection for HCT116 cells. The plate was incubated until color formation. Absorbance values at 570 nm were obtained using a CLARIOstar® microplate reader (BMG Labtech).

2.9. Western Blot Analysis

At 48 h post-transfection, total protein was harvested from NIH3T3 or HCT116 cells using radioimmunoprecipitation assay (RIPA) buffer (Thermo Fisher Scientific, Inc.) with 1X Halt™ Protease Inhibitor Cocktail (Thermo Fisher Scientific, Inc.). Lysates were cleared using centrifugation at 10,000× g for 20 min at 4 °C. Protein concentration was quantified using bicinchoninic acid (BCA) assay (Thermo Fisher Scientific, Inc.) following the manufacturer’s protocol. A total of 20 μg protein was loaded in 12% polyacrylamide gel and run at 100 V for 2 h. Transfer of protein from the polyacrylamide gel to the PVDF membrane was performed at 20 V for 16 h at room temperature. The membrane was rinsed with distilled deionized water and was blocked with 5% milk in tris-buffered saline with 0.1% Tween 20 (TBST) for 1 h.
Membrane was probed overnight using the following primary antibodies: 1:1000 rabbit anti-RRAS antibody (Thermo Fisher Scientific, Inc.; Cat. No. PA5-28270), 1:1000 rabbit anti-E-cadherin (24E10) monoclonal antibody (Cell Signaling Technology, Danvers, MA, USA; Cat. No. 3195), 1:1000 rabbit anti-p-Akt (Cell Signaling Technology; Cat. No. 4060S), 1:1000 rabbit anti-p-Erk (Cell Signaling Technology; Cat. No. 9101), 1:1000 mouse anti-Akt (Cell Signaling Technology; Cat. No. 9272), 1:1000 anti-Erk (Cell Signaling Technology; Cat. No. 137F5), and 1:4000 rabbit anti-GAPDH (Cell Signaling Technology; Cat. No. 2118). An appropriate secondary antibody was then used: goat anti-rabbit IgG (H + L), HRP-conjugated (Thermo Fisher Scientific, Inc.; Cat. No. 31460) or goat anti-mouse IgG (H + L), HRP-conjugated (Thermo Fisher Scientific, Inc.; Cat. No. 31430). Chemiluminescent detection was done using Clarity Western ECL Substrate (Bio-Rad, San Francisco, CA, USA; Cat. No. 1705061). ChemiDoc Image Touch System (Bio-Rad) was used to obtain images of the bands, and densitometric analysis was carried out using Image Lab 6.1 Software (Bio-Rad).

2.10. Bioinformatics Analysis

The 3D structures of RRAS R78W and E63D mutants were generated using SWISS-MODEL [40,41] and AlphaFold 3 [42]. Additionally, the 3D structure of RRAS WT was generated using AlphaFold 3. PyMOL 2.5.5 was used to visualize the mutant models superimposed with the wild-type RRAS structure (PDB: 2FN4) [43,44]. The predicted modeling template (PTM) score and predicted aligned error (PAE) plots were used to evaluate the AlphaFold 3 predicted structures. The PAE plots were visualized using ChimeraX version 1.8 [45]. Root-mean-square deviation (RMSD) values were subsequently calculated. For GTP docking simulations, PyMOL 2.5.5 and AutoDock Tools 4.2 were used [43,44,46]. Receptors were first prepared by removing water molecules and adding polar hydrogens and Kollman charges. The GTP ligand was then docked on the modified protein using AutoDock Vina [47]. The binding interaction of RRAS proteins with a guanine nucleotide exchange factor (GEF) was predicted using AlphaFold 3 [42]. The interface PTM (iPTM) score and PAE plots were used to evaluate the predictions. Additionally, the interaction prediction score from aligned errors (iPSAE) [48] was calculated to supplement the iPTM score. Further analysis of the binding interface was done using PDBePISA [49].

2.11. Statistical Analysis

One-way analysis of variance (ANOVA) was used to compare more than two independent groups, and Tukey’s Honestly Significant Differences (HSD) method was used as a post hoc test for pairwise comparisons. A p < 0.05 was used to define statistical significance. Data are reported as mean ± S.D.

3. Results

3.1. Wild-Type and Mutant RRAS Overexpression Promote Extensive Cytoskeletal Remodeling in NIH3T3 Cells

To investigate the effects of wild-type and mutant RRAS overexpression on the overall cytoskeletal organization of NIH3T3 cells, phalloidin staining and high-content imaging were performed. NIH3T3 cells transfected with the empty vector control were polygonal, with a round nucleus, and with prominent parallel stress fibers traversing the entire length of the cell (Figure 1A). Cells transfected with the canonical KRAS G12D and NRAS Q61K mutants as positive controls revealed gross morphological changes when compared to the empty vector setup. Most cells overexpressing either KRAS G12D (Figure 1B) or NRAS Q61K (Figure 1C) displayed shrunken cytoplasm and stretched nuclei—although others retained the polygonal morphology found in untransformed NIH3T3 cells. Locomotory organelles such as lamellipodia and filopodia were evident in KRAS G12D-transfected cells but were less prominent in cells transfected with NRAS Q61K. Perinuclear actin rims were observable in KRAS G12D-transfected cells, but are less evident in cells overexpressing NRAS Q61K. Formation of tunneling nanotubes (TNTs)—thin intercellular bridges that allow the passage of cargoes such as organelles, RNA, protein, and lipids [50,51,52,53,54]—was seen in cells transfected with either positive control. Overexpression of KRAS G12D or NRAS Q61K resulted in the formation of a few peripheral dorsal ruffles, some of which collapsed into circular dorsal ruffles, further causing cytoskeletal disorganization [55,56]. Invadopodia, actin protrusions that promote extracellular matrix (ECM) degradation, were prominent in KRAS G12D-transfected cells [57]. A few multinucleated cells were observed in cells overexpressing KRAS G12D.
Cells transfected with wild-type RRAS induced extensive cytoskeletal remodeling when compared to empty vector control (Figure 1D). They showed a preponderance of highly migratory fan-shaped cells with a migrating front laden with knob-like lamellipodia and hair-like filopodia, as well as a nucleus located opposite the migrating front [58]. Cells with shrunken cytoplasm were also prominent, and a few cells developed a multilobulated nucleus. Stretching of nuclei and multinucleation were more frequent when compared to cells transfected with NRAS Q61K and the empty vector control. Transient structures such as invadopodia, perinuclear actin rim, and circular dorsal ruffles were observable.
Both RRAS R78W (Figure 1E) and RRAS E63D-transfected cells (Figure 1F) displayed massive cytoskeletal remodeling when compared to the empty vector control. Fan-shaped cells were prominent in both setups, like those observed in cells transfected with wild-type RRAS. Stretched nuclei, as well as locomotory organelles such as lamellipodia and filopodia, were evident, similar to the wild-type setup. Cells overexpressing either RRAS mutant displayed various transient migratory and invasive structures that soften the cytoskeleton, including peripheral dorsal ruffles, circular dorsal ruffles, perinuclear actin rim, and invadopodia. Most RRAS R78W-transfected cells revealed crisscrossing of actin filaments, which indicates early-stage actin filament disassembly.
To assess the effect of RRAS mutations on the overall cellular morphology, the nuclear-to-cytoplasmic ratio, nuclear circularity, and nuclear area were quantified using Fiji version 2.10.0 (Figure S3). Results showed a significant increase in nuclear-to-cytoplasmic ratio in cells overexpressing RRAS E63D versus wild-type RRAS. Furthermore, RRAS R78W overexpression showed a significant decrease in nuclear circularity in the cells when compared to wild-type RRAS, indicating nuclear deformation and loss of roundedness. Meanwhile, RRAS mutants did not show an effect on the nuclear area when compared to wild-type RRAS. These results, together with the structures observed in the fluorescence micrographs, suggest that the RRAS mutants promote disruptions in the cytoskeleton and gross morphology of the cell.

3.2. RRAS R78W Promotes Migration in NIH3T3 and HCT116 Cells

Scratch wound assay was employed to assess the effect of the RRAS mutants on cellular migration (Figure 2A,B). For comparison, empty vector, KRAS G12D, and NRAS Q61K were included as controls. Under low serum conditions (0.5% NBCS for NIH3T3 and 4% FBS for HCT116 cells), NIH3T3 and HCT116 cells transfected with RRAS R78W showed a significant increase in the rate of wound closure when compared to the empty vector and wild-type RRAS controls, suggesting that RRAS R78W promotes migration in both cell lines (Figure 2C,D). Results further suggest that RRAS E63D does not affect cellular migration in both cell lines. Overexpression of KRAS G12D, but not NRAS Q61K, resulted in an increased rate of wound closure in both cell lines.

3.3. RRAS Mutants Do Not Affect Invasion in NIH3T3 and HCT116 Cells

To assess the effect of the novel RRAS mutants on cellular invasion, transwell invasion assays were done for transfected NIH3T3 (Figure 3A) and HCT116 (Figure 3B) cells. For comparison, empty vector, KRAS G12D, and NRAS Q61K setups were included as controls. Invasive capacity was assessed by counting cells that invaded the underside of the membrane and was normalized against the migration controls. As shown in Figure 3, KRAS G12D significantly increased invasion in both cell lines relative to the empty vector control. In contrast, overexpression of wild-type RRAS and the RRAS mutants E63D and R78W did not result in a detectable increase in invasive capacity in either NIH3T3 or HCT116 cells.

3.4. RRAS Promotes HUVEC Tube Formation In Vitro

To determine the effect of the RRAS mutations on angiogenesis, endothelial tube formation assays were performed (Figure 4A). Conditioned media from transfected HCT116 cells secreting pro-angiogenic factors were harvested and used for culturing HUVEC. Features of tube formation, such as junction, extremity, segment, and mesh, were identified and analyzed using the Angiogenesis Analyzer ImageJ plugin with Fiji version 2.10.0 [37,38,39]. To quantitatively determine the extent of tube formation in each setup, parameters such as total mesh area, number of extremities, number of isolated segments, mesh index, and mean mesh size were computed (Figure 4B–F).
Media from wild-type RRAS-transfected HCT116 cells increased total mesh area (Figure 4B) and decreased the number of isolated segments (Figure 4C) when compared to the empty vector control setup. This suggests that wild-type RRAS overexpression favors the formation of highly developed HUVEC mesh in contrast to the creation of remote segments. Cells transfected with the RRAS R78W and E63D mutants retained the total mesh area and number of isolated segments when compared to the wild-type RRAS setup. KRAS G12D-transfected cells showed an increase in total mesh area when compared to the empty vector control, although not statistically significant. On the other hand, cells transfected with NRAS Q61K have similar total mesh area and number of isolated segments as with the empty vector control setup.
The canonical mutant KRAS and NRAS controls did not affect the number of extremities (Figure 4D), mesh index (Figure 4E), and mean mesh size (Figure 4F). The RRAS mutants showed no significant difference in the number of extremities compared to both wild-type RRAS and empty vector control setups. RRAS E63D showed a significant difference in mean mesh size when compared to the empty vector control setup, but not with wild-type RRAS. Overall, results suggest that wild-type RRAS promotes angiogenesis, and the novel mutations did not abolish its pro-angiogenic effect.

3.5. RRAS E63D Confers Resistance to Apoptosis in NIH3T3 and HCT116 Cells

To determine the effect of the RRAS mutations on cell survival, caspase-3/7 activity was measured using the luminescence-based Caspase-3/7 Glo® Assay System. Induction of apoptosis was achieved by serum reduction (0.1% NBCS) in NIH3T3 cells and the addition of 10 mM sodium butyrate in HCT116 cells. RRAS E63D showed a significant decrease in caspase-3/7 activity in NIH3T3 (Figure 5A) and HCT116 (Figure 5B) cell lines when compared to wild-type RRAS, suggesting that the mutation promotes resistance to apoptosis in both cells. The novel RRAS mutant R78W showed no significant increase in resistance to apoptosis versus wild-type RRAS. NRAS Q61K, but not KRAS G12D and the wild-type RRAS, promoted cell survival in both cell lines in comparison with the empty vector control.

3.6. Wild-Type and Mutant RRAS Do Not Promote Proliferation in NIH3T3 and HCT116 Cells

To assess the effect of the RRAS mutants on cell proliferation, CellTiter 96® AQueous One Solution MTS Cell Proliferation Assay was performed. Upon growing the transfected cells in low serum conditions (2.5% NBCS for NIH3T3 and 4% in HCT116 cells), the novel RRAS mutants R78W and E63D did not promote proliferation when compared to wild-type RRAS in NIH3T3 (Figure 6A) and HCT116 (Figure 6B) cell lines, as indicated by comparable fold change in absorbance readouts. Both NRAS Q61K and wild-type RRAS did not affect proliferation in both cell lines in comparison with the empty vector control. Only the canonical KRAS G12D control shows a significant increase in proliferation in both cell lines when compared to the empty vector control.

3.7. RRAS Overexpression Does Not Promote Akt and Erk Phosphorylation

Ras promotes the phosphorylation of downstream effectors such as Erk and Akt to activate MAPK and PI3K/Akt pathways, respectively [59,60]. To determine the pathways responsible for inducing phenotypic changes in the transfected cells, the phosphorylation states of Akt (Figure 7A) and Erk1/2 (Figure 7B) were examined through Western blot analysis. Transfected NIH3T3 cells used for the Akt phosphorylation assay were treated with 2 ng/mL EGF for 5 min to stimulate the activation of the PI3K/Akt pathway.
Densitometric analysis shows that transfection of wild-type and mutant RRAS resulted in similar Akt phosphorylation levels when compared to the empty vector control, suggesting that the wild-type and mutant RRAS overexpression did not affect Akt phosphorylation (Figure 7C). Similarly, p-Erk1/2 levels were comparable across NIH3T3 cells transfected with empty vector, wild-type, and mutant RRAS constructs (Figure 7D). On the other hand, both the canonical KRAS G12D and NRAS Q61K promoted increased Akt and Erk1/2 phosphorylation when compared to the empty vector control, suggesting that the canonical controls confer oncogenic phenotypes through the activation of MAPK and PI3K/Akt pathways.

3.8. In Silico Analysis Reveals Oncogenic Impact of RRAS R78W and E63D Mutants

To predict the possible effect of RRAS R78W and E63D mutations on the structure and function of the protein, in silico analysis was performed. Visualization and calculation of RMSD values of the superimposed wild-type and mutant RRAS models generated by SWISS-MODEL were performed using PyMOL 2.5.5 to determine the effect of the mutations on the overall structure of the protein. RMSD values were computed to be 0.074 Å for RRAS R78W and 0.069 Å for RRAS E63D mutations (Figure 8A). The small RMSD values suggest that the novel RRAS R78W and E63D mutants do not have an overall significant effect on the global structure of RRAS.
Protein–ligand docking simulations of RRAS mutants and GTP ligand were done using AutoDock Vina to predict the effect of the mutations on GTP binding. First, the interacting residues of RRAS with GTP were compared between the wild-type and mutant RRAS structures. Results revealed similar interacting residues between GTP and RRAS models, with comparable lengths of hydrogen bond ranging from 2.8 Å to 3.3 Å across all setups (Figure 8C). Second, the GTP-binding affinity values of wild-type and mutant RRAS models were obtained (Figure 8D). Docking simulations revealed a binding affinity score of −10.8 kcal/mol for wild-type RRAS. The binding affinity values of −10.7 kcal/mol and −10.6 kcal/mol were obtained for RRAS R78W and E63D mutants, respectively. The results imply that the differences in binding energy between the wild-type and mutant RRAS models are negligible. Taken together, the results suggest that the mutations do not affect the GTP function of RRAS.
To predict whether the mutations affect GEF-binding affinity, protein-protein docking between RRAS and a known RRAS-interacting GEF, GRF1, was performed using AlphaFold 3. First, to evaluate the accuracy of the 3D structure prediction of AlphaFold 3 with RRAS, the RRAS wild-type structure was predicted and compared with the RRAS crystal structure, 2FN4. The 3D structures of the two RRAS mutants were similarly generated and compared to 2FN4. The RMSD values computed for each structure relative to 2FN4 are 0.397 Å for wild-type, 0.428 Å for the R78W mutation, and 0.441 Å for the E63D mutation. The PTM score for each structure was calculated as 0.91 for wild-type, 0.9 for the R78W mutation, and 0.91 for the E63D mutation (Figure 8B). The PAE plots for each structure also show an overall high confidence in the predicted structures (Figure S7A). The low RMSD values and high confidence (>0.8 PTM) suggest both high accuracy in RRAS structure prediction and disruptions in the overall RRAS structure in relation to the solved RRAS structure.
Second, to predict the three-dimensional structure of the RRAS-GRF1 complex, both RRAS and GRF1 were folded using AlphaFold 3 to take advantage of its built-in interaction prediction capability. To assess the quality of protein–protein interaction prediction, iPTM and IPSAE scores were obtained. The iPTM and IPSAE scores obtained for all three models are above 0.8, indicating that there is high confidence in the structures predicted using AlphaFold3. (Figure 8E). Additionally, the PAE plots show an overall high confidence in the predicted protein interaction complexes (Figure S7B). Together, these suggest that the R78W and E63D mutations retain the GEF-binding ability of RRAS. Further analysis of the binding interface was done using PDBePISA (Table S1). Comparisons between the binding interface between R78W and E63D to GRF1 vs. wild-type to GRF1 reveal differences in interface area and binding energy. E63D had a larger binding interface area than wild-type (1757 Å2 vs. 1719.1 Å2), while R78W had a smaller binding interface area (1686.4 Å2). Analysis of the binding energy of the protein complexes shows that E63D had a lower binding energy than wild-type (−13 kcal/mol vs. −12.4 kcal/mol), while R78W had an identical binding energy to wild-type RRAS (−12.4 kcal/mol). Additionally, the calculated dissociation energy of both E63D and R78W was higher than wild-type (15.9 kcal/mol and 12 kcal/mol, respectively, vs. 8.9 kcal/mol). The binding interface analysis suggests that both RRAS mutations may confer increased interaction with GRF1 vs. wild-type RRAS.
Overall, in silico analysis suggests that the novel RRAS R78W and E63D mutants retain the global structure and GTP-binding ability of RRAS. However, protein-protein docking simulations suggest that the RRAS R78W and E63D mutants had higher affinities for GRF1 in comparison with the wild type.

4. Discussion

The classical Ras family of proteins, composed of KRAS, NRAS, and HRAS share ~80% amino acid sequence homology, yet they perform distinct but overlapping biochemical functions [61]. The differences in the allosteric lobe sequences account for the slower GTP hydrolysis activity of KRAS and NRAS when compared to HRAS [62]. Moreover, the differences in the post-translational modification due to their distinct C-terminal sequences influence plasma membrane trafficking and turnover, which can affect downstream signaling [63]. Whether these subtle changes in structure contribute to the functional differences in the classical Ras isoforms—and eventually to cancer-type specificity of isoforms—remains largely unexplored.
Due to the crucial role of Ras in normal cellular processes, the classical Ras isoforms have been implicated in many types of cancer. Around 25% of tumors harbor gain-of-function mutations in Ras, although the frequency of mutations varies across cancer types [9]. In CRC, missense mutations in KRAS are found in 40% of CRC tumors, whereas 3–5% of the tumors harbor activating NRAS mutations [64]. HRAS mutations are less commonly observed in CRC [64]. Activating mutations in KRAS and NRAS correlate with non-responsiveness to EGFR-targeted therapy against CRC [65].
KRAS, the most well-characterized Ras isoform, was thought to be undruggable due to decades-long failure in finding therapeutics that target Ras mutants. Recently, KRAS G12C-targeting drugs have been commercialized and released in the market [66,67], whereas the development of drugs that target KRAS G12D is underway [68]. While pre-clinical data and clinical trials indicate a positive response in targeting specific KRAS mutations, patients become resistant to therapy over time due to NRAS and HRAS-mediated activation of MAPK and PI3K/Akt pathways as a compensatory mechanism in reduced KRAS stimulation [69]. This further highlights the need to characterize the lesser-known Ras isoforms and determine their implication in the onset and development of diseases such as CRC.
A less-characterized member of the Ras superfamily is the Ras-related protein or RRAS, which shares 55% amino acid sequence homology with the classical Ras isoforms [31] (Figure S8). While RRAS and the classical Ras isoforms share consensus sequences in the G domain, RRAS has unique N- and C-terminal sequences that function in processes such as actin organization and cell migration [13,14,31]. Due to similarities and differences in the structure among the Ras isoforms, it is conceivable that the wild-type and mutant RRAS may promote distinct and overlapping oncogenic phenotypes when compared to the canonical KRAS and NRAS mutants. This study examined the phenotypic effects on cancer hallmarks of the novel RRAS R78W and E63D mutants, alongside the canonical KRAS G12D and NRAS Q61K mutants, when compared to wild-type RRAS.
The effect of the novel RRAS mutations on metastatic potential was investigated by assessing their functional impact on cytoskeletal arrangement, migration, invasion, and angiogenesis. Migration, invasion, and metastasis are processes exploited by cancer cells to promote tumor spread, all of which involve dynamic cytoskeletal reorganization. Transfection of wild-type and mutant RRAS, as well as the canonical KRAS G12D and NRAS Q61K mutants, induced changes in the F-actin structure of NIH3T3 cells.
Overexpression of wild-type and mutant RRAS resulted in a mixture of shrunken and fan-shaped NIH3T3 cells. Shrinking of cytoplasm and stretching of nuclei promote a more migratory phenotype by allowing cells to penetrate tissues and organs smaller than the nuclear diameter [70]. Migrating, fan-shaped fibroblasts tend to harbor large lamellipodia with few stress fibers to aid in the extension of the leading front [71,72]. Aside from surveying the intercellular environment, filopodia also initiate the formation of large lamellipodia to promote migration [73,74]. Formation of transient migratory and invasive structures, such as peripheral dorsal ruffles, circular dorsal ruffles, and perinuclear actin rim, was also prominent in cells overexpressing wild-type and mutant RRAS. Peripheral dorsal ruffles collapse inwards to form circular dorsal ruffles, disrupting and softening the cytoskeleton in the process to promote migration [55,56]. Perinuclear actin rim aids in nuclear deformation and genome protection during migration [75].
Furthermore, transient structures associated with migration and invasion in cancer cells, such as invadopodia, tunneling nanotubes, multilobulated nuclei, and multinucleated cells, were also found in RRAS-overexpressing cells. Invadopodia are specialized actin-rich protrusions that recruit proteases to degrade the ECM [57]. Invadopodia are often found in dense ECM or cell-rich regions and are correlated with the invasive capacity of tumor cells [76]. TNTs allow rapid intercellular transmission of cargoes to promote invasion and metastasis, including mRNAs, regulatory non-coding RNAs, proteins, lipids, and even entire organelles such as mitochondria [50,51,52,53,54]. In the context of therapeutics, intercellular communication through TNTs allows drug redistribution in cancer systems, implicating TNT formation as a mechanism for chemotherapy resistance [77]. Additionally, multilobulation and multinucleation occur in cancer cells due to failure in mitosis and cytokinesis, respectively [78]. The canonical control KRAS G12D mutation promoted massive cytoskeletal remodeling similar to that observed in wild-type and mutant RRAS. In contrast, NRAS Q61K induced cytoskeletal changes in NIH3T3 cells to a lesser extent when compared to KRAS G12D.
Although wild-type RRAS and both RRAS mutants promoted cytoskeletal reorganization in cells, only RRAS R78W overexpression resulted in increased migration of NIH3T3 and HCT116 cells, similar to the canonical KRAS G12D control. In contrast, neither RRAS mutant increased the invasive capacity of either cell line. This observation is not totally unexpected. While early stages of migration involve cytoskeletal rearrangement and pseudopodial formation, cells need to undertake further steps to migrate, among which include translocation of the nucleus and cell body via acto-myosin contractile forces and disassembly of cell–substrate adhesive structures at the trailing edge [79]. Thus, it is possible that wild-type RRAS and RRAS E63D, similar to that already reported for NRAS Q61K, only affect the initial stages but not the later stages of migration [80]. Moreover, unlike migration, cellular invasion needs additional proteolytic degradation and remodeling of the surrounding ECM in order to invade other surrounding tissues, which was not enhanced by either RRAS mutant. Nonetheless, the results are consistent with those reported in the literature involving the role of RRAS in membrane protrusion, lamellipodial formation, and cell migration in melanoma, breast, and cervical cells [24,29,81].
Angiogenesis allows cancer cells to obtain nutrients from the tumor microenvironment [82]. Additionally, the vasculature formed during angiogenesis can be utilized by cancer cells to intravasate and access the bloodstream or lymphatics [83]. Results of this study revealed that wild-type and mutant RRAS, but not the canonical KRAS G12D and NRAS Q61K controls, can induce tube formation in HUVEC in vitro. Conditioned media from cells overexpressing wild-type RRAS enhanced HUVEC tube formation compared to the empty-vector control, as exhibited by increased total mesh area and reduced number of isolated segments. Further, the RRAS R78W and E63D mutations did not abolish the ability of RRAS to induce tube formation in HUVEC.
Overall, the results described in this study suggest that overexpression of wild-type RRAS—akin to physiological upregulation in cells—may aid in instigating a metastatic program by inducing changes in the cytoskeletal structure of cancer cells and promoting the formation of tumor vasculature. The novel RRAS R78W and E63D mutants promoted extensive changes in the F-actin organization of cells, and RRAS R78W increased cellular migration. Findings of the study further highlight the need to study the lesser-known RRAS protein, as this isoform and its other uncharacterized mutations could promote tumor development and metastasis comparable to that induced by the classical Ras isoform mutations.
Results of the study further support the idea that tumor formation and development are induced in a mutation-, isoform-, and tissue-specific manner. RRAS E63D promoted increased resistance to apoptosis in both NIH3T3 and HCT116 cells when compared to wild-type RRAS, whereas overexpression of wild-type RRAS did not promote cell survival when compared to empty vector control in both cell lines. Neither the wild-type nor mutant RRAS overexpression resulted in enhanced proliferation in NIH3T3 and HCT116 cells. Only KRAS G12D overexpression resulted in increased proliferation versus empty vector in NIH3T3 and HCT116 cells, as previously reported for these canonical mutant controls [80,84,85,86]. Thus, the coexistence of different mutations in distinct Ras isoforms has vast repercussions in the prognosis and management of CRC.
Mutations in the classical Ras isoforms confer oncogenic effects to cells through the MAPK and PI3K/Akt pathways [87,88]. Previous reports documented that RRAS activates MAPK and/or PI3K pathways in a context-dependent manner [32,89,90]. However, results of this study showed that overexpression of the wild-type and mutant RRAS did not affect Akt and Erk1/2 phosphorylation levels in the wild-type background of NIH3T3 cells. Other studies have proposed alternative pathways activated by RRAS, such as Rac and Rho, to promote membrane ruffling and cell migration [14,23,91]. This connection is noteworthy due to the implication of Rho protein activation in KRAS inhibitor resistance [92,93]. The effects of the two novel RRAS mutants on these pathways can be explored in future work.
In silico analysis has provided insights into how the point mutations may affect RRAS structure and function. The low RMSD values obtained upon superimposition of RRAS mutants with the wild type suggest that the mutants retain their global structure and function. Further, protein–ligand docking simulations showed a negligible effect on the GTP-binding function of RRAS mutants.
Protein–protein interaction simulations between RRAS and GRF1, a GEF, suggest that the novel R78W and E63D mutations can enhance RRAS-GEF binding affinity. If validated with mechanistic studies such as protein–protein interaction assays, the increased RRAS-GEF binding can explain how the novel mutants confer oncogenic phenotypes.
Limited studies have identified and characterized RRAS mutations in cancer, largely due to the absence of a canonical mutation. The study contributes to the limited body of knowledge on RRAS by investigating two novel RRAS mutations—R78W and E63D—identified in Filipino young-onset colorectal cancer patients. While KRAS and NRAS are well-established drivers of CRC, the role of RRAS in tumor progression remains understudied despite its known involvement in cell migration.
Functional characterization of novel mutations may contribute to a more targeted approach to treating CRC. Different CRC tumors possess distinct molecular profiles, and by elucidating the functional consequences of a mutation, a clinician becomes guided as to the specific vulnerabilities that may be targeted. Additionally, RRAS mutations could serve as additional biomarkers for responsiveness or non-responsiveness to therapy once these mutations have been fully characterized and validated with clinical correlates.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells15040349/s1. Table S1: Binding interface analysis of the AlphaFold 3-predicted RRAS-GRF1 complexes using PDBePISA; Figure S1: Western blot detection of RRAS and GAPDH in NIH3T3 and HCT116 cells; Figure S2: Enlarged images of phalloidin-stained NIH3T3 cells; Figure S3: Cell dimensions calculated from actin staining; Figure S4: Apoptosis induction data for the Caspase-Glo® 3/7 Assay; Figure S5: Western blot analysis of Akt phosphorylation in NIH3T3 cells; Figure S6: Western blot analysis of Erk phosphorylation in NIH3T3 cells; Figure S7: Confidence scores and predicted aligned error (PAE) plots of AlphaFold 3 predicted structures; Figure S8: Multiple Sequence Alignment of the various Ras isoforms.

Author Contributions

Conceptualization, D.L.S. and R.L.G.; methodology, A.P.L.D., S.A.A.C., D.M.G.L. and R.L.G.; validation, A.P.L.D., S.A.A.C. and D.M.G.L.; formal analysis, A.P.L.D., M.I.P.G., S.A.A.C. and D.M.G.L.; investigation, A.P.L.D., M.I.P.G., S.A.A.C. and D.M.G.L.; resources, D.L.S. and R.L.G.; data curation, A.P.L.D. and M.I.P.G.; writing—original draft preparation, A.P.L.D. and R.L.G.; writing—review and editing, A.P.L.D., S.A.A.C., D.M.G.L., D.L.S. and R.L.G.; visualization, A.P.L.D., M.I.P.G., S.A.A.C. and D.M.G.L.; supervision, D.L.S. and R.L.G.; project administration, D.L.S. and R.L.G.; funding acquisition, D.L.S. and R.L.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the University of the Philippines System (OVPAA-EIDR Code 06-008) and the Philippine Council for Health Research and Development (grant code FP150025), as well as by in-house funds from the National Institute of Molecular Biology and Biotechnology, University of the Philippines Diliman.

Institutional Review Board Statement

This study did not involve human participants or animals and only used cell lines and gene constructs. The next-generation sequencing study referred to in the article, from which the sequences of the mutant oncogenes were obtained, was approved by the University of the Philippines Manila Research Ethics Board with the study protocol codes UPMREB 2016-042-01 (approval date: 16 February 2016) and UPMREB 2016-001-01 (approval date: 19 March 2018).

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed in this study are available from the corresponding author upon reasonable request. Next-generation sequencing data, from which the novel RRAS mutants reported in this study were identified, are available via BioProject accession number PRJNA1156316.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Figure 1. F-actin cytoskeletal organization of cells transfected with wild-type and mutant RRAS compared to empty vector, KRAS G12D, and NRAS Q61K controls. Transfected NIH3T3 cells were stained to visualize F-actin (green) and nucleus (blue). Representative micrographs showing cytoskeletal changes in NIH3T3 cells transfected with (A) empty vector, (B) KRAS G12D, (C) NRAS Q61K, (D) wild-type RRAS, (E) RRAS R78W, and (F) RRAS E63D mutants. (G) Legend displaying symbols used to highlight structural features observed in cells. Enlarged images of cytoskeletal features are shown in Figure S2.
Figure 1. F-actin cytoskeletal organization of cells transfected with wild-type and mutant RRAS compared to empty vector, KRAS G12D, and NRAS Q61K controls. Transfected NIH3T3 cells were stained to visualize F-actin (green) and nucleus (blue). Representative micrographs showing cytoskeletal changes in NIH3T3 cells transfected with (A) empty vector, (B) KRAS G12D, (C) NRAS Q61K, (D) wild-type RRAS, (E) RRAS R78W, and (F) RRAS E63D mutants. (G) Legend displaying symbols used to highlight structural features observed in cells. Enlarged images of cytoskeletal features are shown in Figure S2.
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Figure 2. Scratch wound assay of cells overexpressing RRAS mutants and controls. Representative images of (A) NIH3T3 and (B) HCT116 cells visualized with calcein AM at 0 h and 16 h post-scratch. Representative data (mean ± s.d.) from three independent trials, each done in triplicate, were obtained upon calculating the rate of wound closure in (C) NIH3T3 and (D) HCT116 cells. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
Figure 2. Scratch wound assay of cells overexpressing RRAS mutants and controls. Representative images of (A) NIH3T3 and (B) HCT116 cells visualized with calcein AM at 0 h and 16 h post-scratch. Representative data (mean ± s.d.) from three independent trials, each done in triplicate, were obtained upon calculating the rate of wound closure in (C) NIH3T3 and (D) HCT116 cells. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
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Figure 3. Transwell invasion assay of cells transfected with RRAS mutants and controls in (A) NIH3T3 and (B) HCT116 cell lines. Data presented (mean ± s.d.) are representative of three independent trials, each done in triplicate. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05, ** p < 0.01, and ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
Figure 3. Transwell invasion assay of cells transfected with RRAS mutants and controls in (A) NIH3T3 and (B) HCT116 cell lines. Data presented (mean ± s.d.) are representative of three independent trials, each done in triplicate. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05, ** p < 0.01, and ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
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Figure 4. Endothelial tube formation assay using conditioned media from HCT116 cells overexpressing RRAS mutants and appropriate controls. (A) Representative micrographs of HUVEC (green) obtained through high-content imaging using a montage of z-stacks at 4× magnification. Scale bar = 300 μm. Representative data (mean ± s.d.) of (B) total mesh area, (C) number of isolated segments, (D) number of extremities, (E) mesh index, and (F) mean mesh size across three independent trials, each done in quadruplicate, are shown. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
Figure 4. Endothelial tube formation assay using conditioned media from HCT116 cells overexpressing RRAS mutants and appropriate controls. (A) Representative micrographs of HUVEC (green) obtained through high-content imaging using a montage of z-stacks at 4× magnification. Scale bar = 300 μm. Representative data (mean ± s.d.) of (B) total mesh area, (C) number of isolated segments, (D) number of extremities, (E) mesh index, and (F) mean mesh size across three independent trials, each done in quadruplicate, are shown. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
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Figure 5. Effect of RRAS mutants on cell survival versus controls. Caspase-3/7 activity in (A) NIH3T3 and (B) HCT116 cells transfected with RRAS constructs and controls. Data presented (mean ± s.d.) are representative of three independent trials, each done in triplicate. Representative data for relative luminescence readings (RLU) of uninduced and induced setups are shown in Figure S4. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. RLU: relative luminescence units; PTT: pTarget™ empty vector; WT: wild type.
Figure 5. Effect of RRAS mutants on cell survival versus controls. Caspase-3/7 activity in (A) NIH3T3 and (B) HCT116 cells transfected with RRAS constructs and controls. Data presented (mean ± s.d.) are representative of three independent trials, each done in triplicate. Representative data for relative luminescence readings (RLU) of uninduced and induced setups are shown in Figure S4. Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc test. * p < 0.05; ns = not significant. RLU: relative luminescence units; PTT: pTarget™ empty vector; WT: wild type.
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Figure 6. Effect of RRAS mutants on cellular proliferation. (A) Representative trial (mean ± s.d.; n = 3, each done in triplicate) for NIH3T3 cells. Colorimetric readout was obtained at 24 h and 48 h post-transfection. (B) Representative bar graph (mean ± s.d.) for HCT116 cells showing fold change upon obtaining readouts at 24 h and 72 h post-transfection (n = 3, each trial done in triplicate). Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc analysis. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
Figure 6. Effect of RRAS mutants on cellular proliferation. (A) Representative trial (mean ± s.d.; n = 3, each done in triplicate) for NIH3T3 cells. Colorimetric readout was obtained at 24 h and 48 h post-transfection. (B) Representative bar graph (mean ± s.d.) for HCT116 cells showing fold change upon obtaining readouts at 24 h and 72 h post-transfection (n = 3, each trial done in triplicate). Statistical analysis was performed using one-way ANOVA and Tukey’s HSD post hoc analysis. * p < 0.05; ns = not significant. PTT: pTarget™ empty vector; WT: wild type.
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Figure 7. Western blot analysis of Akt and Erk phosphorylation in NIH3T3 cells. Detection of (A) p-Akt/Akt and (B) p-Erk/Erk transfected with RRAS mutants or controls. Representative graphs obtained from densitometric analysis of (C) p-Akt and (D) p-Erk1/2 expression. Data presented are representative of three independent trials. Uncropped blots are shown in Figures S5 and S6. PTT: pTarget™ empty vector; WT: wild type.
Figure 7. Western blot analysis of Akt and Erk phosphorylation in NIH3T3 cells. Detection of (A) p-Akt/Akt and (B) p-Erk/Erk transfected with RRAS mutants or controls. Representative graphs obtained from densitometric analysis of (C) p-Akt and (D) p-Erk1/2 expression. Data presented are representative of three independent trials. Uncropped blots are shown in Figures S5 and S6. PTT: pTarget™ empty vector; WT: wild type.
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Figure 8. In silico analysis predicting the oncogenic impact of the novel RRAS mutants. (A) Mutant models generated using SWISS-MODEL were superimposed on the wild-type RRAS crystal, 2FN4. RRAS WT: green; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue. (B) RRAS models generated using AlphaFold 3 were superimposed on the wild-type RRAS crystal, 2FN4. RRAS WT (2FN4): green; RRAS WT (AlphaFold 3): yellow; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue. (C) Interaction plot of RRAS and GTP. H-bonds: green dotted lines. (D) Surface view of RRAS-docked GTP ligand with binding affinity scores. GTP: black; H-bonds: yellow dotted lines. (E) AlphaFold 3 prediction of the RRAS-GRF1 complex with iPTM and iPSAE scores. RRAS WT: yellow; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue; GRF1: orange.
Figure 8. In silico analysis predicting the oncogenic impact of the novel RRAS mutants. (A) Mutant models generated using SWISS-MODEL were superimposed on the wild-type RRAS crystal, 2FN4. RRAS WT: green; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue. (B) RRAS models generated using AlphaFold 3 were superimposed on the wild-type RRAS crystal, 2FN4. RRAS WT (2FN4): green; RRAS WT (AlphaFold 3): yellow; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue. (C) Interaction plot of RRAS and GTP. H-bonds: green dotted lines. (D) Surface view of RRAS-docked GTP ligand with binding affinity scores. GTP: black; H-bonds: yellow dotted lines. (E) AlphaFold 3 prediction of the RRAS-GRF1 complex with iPTM and iPSAE scores. RRAS WT: yellow; R78W protein: cyan; R78W site: red; E63D protein: magenta; E63D site: blue; GRF1: orange.
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Table 1. Primer sequences used to generate the mutant RRAS constructs. (*) denotes where missense substitutions were incorporated.
Table 1. Primer sequences used to generate the mutant RRAS constructs. (*) denotes where missense substitutions were incorporated.
DesignationSequence (5′–3′)
RRAS-WT-FATGAGCAGCGGGGCGGCG
RRAS-WT-RCTACAGGAGGACGCAGGGGC
RRAS-R78W-FGCCT*GGCTGGACATCCTGGACACCGC
RRAS-R78W-RCAGGATGTCCAGCCA*GGCTGGGA
RRAS-E63D-FCTGACTACGACCCCACTATTGAT*GACTCCT
RRAS-E63D-RTCGTGTAGGAGTCA*TCAATAGTGGGGTCGT
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David, A.P.L.; Galvez, M.I.P.; Chua, S.A.A.; Leaño, D.M.G.; Sacdalan, D.L.; Garcia, R.L. Ras-Related Mutants Identified in Young-Onset Colorectal Cancer Display Divergent Phenotypes and Retain Their Pro-Angiogenic Effects. Cells 2026, 15, 349. https://doi.org/10.3390/cells15040349

AMA Style

David APL, Galvez MIP, Chua SAA, Leaño DMG, Sacdalan DL, Garcia RL. Ras-Related Mutants Identified in Young-Onset Colorectal Cancer Display Divergent Phenotypes and Retain Their Pro-Angiogenic Effects. Cells. 2026; 15(4):349. https://doi.org/10.3390/cells15040349

Chicago/Turabian Style

David, Andrei Phillip L., Mariko Isabelle P. Galvez, Sidney Allen A. Chua, Dominique Mickai G. Leaño, Dennis L. Sacdalan, and Reynaldo L. Garcia. 2026. "Ras-Related Mutants Identified in Young-Onset Colorectal Cancer Display Divergent Phenotypes and Retain Their Pro-Angiogenic Effects" Cells 15, no. 4: 349. https://doi.org/10.3390/cells15040349

APA Style

David, A. P. L., Galvez, M. I. P., Chua, S. A. A., Leaño, D. M. G., Sacdalan, D. L., & Garcia, R. L. (2026). Ras-Related Mutants Identified in Young-Onset Colorectal Cancer Display Divergent Phenotypes and Retain Their Pro-Angiogenic Effects. Cells, 15(4), 349. https://doi.org/10.3390/cells15040349

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