Research ArticleExperimental Studies
Open Access

Development of Acquired Resistance in Alpelisib-treated Gastric Cancer Cells With PIK3CA Mutations and Overcoming Strategies

MINSU KANG, KUI-JIN KIM, JI HEA SUNG, MILANG NAM, SUNG-HYUN HWANG, WOOCHAN PARK, JEONGMIN SEO, EUN HEE JUNG, KOUNG JIN SUH, JI-WON KIM, SE HYUN KIM, JIN WON KIM, YU JUNG KIM, JEE HYUN KIM and KEUN-WOOK LEE
Anticancer Research May 2025, 45 (5) 1877-1896; DOI: https://doi.org/10.21873/anticanres.17567

Abstract

Background/Aim: Alpelisib has shown promise in preclinical studies for treating PIK3CA-mutant gastric cancer (GC), and its combination with chemotherapy has progressed to clinical trials. However, acquired resistance to alpelisib remains a significant challenge. This study aimed to elucidate the mechanisms underlying acquired alpelisib resistance and propose potential therapeutic strategies to overcome it.

Materials and Methods: Acquired alpelisib-resistant GC cell lines were developed by prolonged drug exposure. Mechanistic studies included whole-exome sequencing, western blotting, immunoprecipitation, Cdc42 and Rac1 activity assays, caspase-3/7 assays, colony formation assays, and sphere formation assays to investigate resistance pathways and therapeutic interventions.

Results: Two GC cell lines with acquired resistance to alpelisib, SNU601-R and AGS-R, were successfully developed from SNU601 and AGS. Both acquired alpelisib-resistant cell lines exhibited PTEN functional loss, leading to activation of SRC, STAT1, AKT, and PRAS40 signaling pathways. Combination treatments with pan-PI3K inhibitors or AKT inhibitors successfully overcame resistance. Among these, the combination of capivasertib, an AKT inhibitor, with SN38 demonstrated superior cytotoxic effects. Furthermore, the combination of capivasertib and SN38 significantly reduced the colony forming ability and sphere formation compared to each treatment alone in SNU601-R and AGS-R cells.

Conclusion: In alpelisib-treated GC cells with PIK3CA mutations, PTEN functional loss and changes in the associated signaling pathway were identified as important mechanisms of acquired alpelisib resistance. The combination of capivasertib and SN38 effectively overcomes acquired resistance to alpelisib in PIK3CA-mutant GC, providing a preclinical rationale for future clinical trials targeting acquired alpelisib-resistant GC with PIK3CA mutations.

Keywords:

Introduction

Gastric cancer (GC) remains a global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related mortality worldwide (1). Despite advances in systemic chemotherapy, the median overall survival for metastatic or recurrent GC remains 12-18 months, highlighting the need for more effective treatments. Current treatment regimens primarily include fluoropyrimidines, platinum agents, taxanes, and irinotecan (2-4), with immune checkpoint inhibitors like nivolumab and pembrolizumab offering additional options in select cases. However, apart from trastuzumab (5), T-DXd (6), zolbetuximab (7, 8), and ramucirumab (9), the landscape of targeted therapies remains limited, underscoring the pressing need for novel strategies.

The PIK3CA gene encodes the p110α catalytic subunit of phosphatidylinositol 3-kinase (PI3K), a critical regulator in the PI3K/AKT/mTOR signaling pathway (10, 11). This pathway governs essential cellular processes, including survival, proliferation, apoptosis, and metastasis (11). PI3K comprises a regulatory subunit (p85) and a catalytic subunit (p110), with p110α encoded by PIK3CA being a frequent oncogenic driver. PIK3CA mutations, which are associated with resistance to HER2-targeted therapies in breast cancer (12, 13), underscore their importance as therapeutic targets. In GC, PIK3CA mutations represent the third most common genetic alteration, occurring in 32% of hypermutated tumors and 9-13% of non-hypermutated tumors (14).

Given its oncogenic role, PIK3CA has become a potential focus for targeted therapies. Alpelisib, a PIK3CA-specific inhibitor, has demonstrated significant efficacy in suppressing PIK3CA-mutant tumor growth and is approved for breast cancer treatment following the SOLAR-1 trial (15). In contrast to breast cancer, research on PIK3CA mutations in GC remains limited. Our group has actively addressed this gap, demonstrating that PIK3CA mutations drive tumor aggressiveness and activate downstream AKT signaling in GC (16). Building on these findings, we conducted preclinical studies revealing that alpelisib synergistically enhances antitumor effects when combined with paclitaxel in PIK3CA-mutant GC models, supporting its potential for clinical application (17). These efforts served as an impetus for starting a new Phase IB/II trial evaluating alpelisib with paclitaxel in patients with PIK3CA-altered metastatic or recurrent GC (ClinicalTrials.gov ID: NCT04526470).

However, acquired resistance to targeted therapies, including alpelisib, remains a critical clinical challenge, limiting the durability of therapeutic responses. This study aimed to elucidate the mechanisms of acquired resistance to alpelisib in PIK3CA-mutant GC cells and explore potential strategies to overcome it.

Materials and Methods

Cell lines. SNU601 cell line, which has a PIK3CA mutation (E542K), was obtained from the Korean Cell Line Bank (Seoul, Republic of Korea) and cultured in RPMI-1640 (LM011-51, Welgene, Daegu, Republic of Korea) supplemented with 10% fetal bovine serum (FBS) from Gibco (26140079, Thermo Fisher Scientific, Waltham, MA, USA), 4 mM L-glutamine (LM007-01, Welgene), and 1% penicillin/streptomycin (LS202-2, Welgene). AGS cell line, which also has PIK3CA mutations (E545A and E453K), was obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA) and grown in RPMI-1640 supplemented with 10% FBS, 4 mM L-glutamine, and 1% penicillin/streptomycin. Cultures were maintained in a 5% CO2 incubator at 37°C.

Antibodies and reagents. Antibodies against p-AKT S473 (#4058), p-AKT T308 (#9275), AKT (#9275), Cdc42 (#2462), γ-H2AX (#2577), p-PRAS40 T246 (#2997), PRAS40 (#2691), p-S6BP S240/4 (#5364), S6BP (#2217), p-SRC Y419 (#2101), SRC (#2108), p-STAT1 S727 (#9177), STAT1 (#9172), Rac1 (#2465), and vinculin (#13901) were purchased from Cell Signaling Technology (Danvers, MA, USA). HRP-conjugated anti-rabbit (#111-035-003) and anti-mouse (#115-035-003) secondary antibodies were obtained from Jackson ImmunoResearch (West Grove, PA, USA). Phosphate buffered saline (PBS) was purchased from Welgene. Doxycycline was purchased from Sigma (St Louis, MO, USA). SN38, TGX-221, pictilisib, PI-103, MK-2206, ipatasertib, and capivasertib, were purchased from Selleckchem (Houston, TX, USA).

Authentication of cell lines by DNA fingerprinting. The authentication of each cell line [SNU601 parental (SNU601-P), SNU601 with acquired resistance to alpelisib (SNU601-R), AGS parental (AGS-P), and AGS with acquired resistance to alpelisib (AGS-R)] was performed using the AmpFLSTR Identifiler PCR Amplification Kit (Applied Biosystems, catalog 4322288; Foster, CA, USA) by Macrogen (Feb. 18, 2021). The 3530xL DNA Analyzer (Applied Biosystems) and the GeneMapper v5.0 software (Applied Biosystems) were used for DNA fingerprinting analysis.

Cell viability assay. The evaluation of cell viability was conducted using the CellTiter-Glo luminescent cell viability assay (Promega, Madison, WI, USA), following the manufacturer’s instructions. Initially (day 0), cells were seeded onto 384-well plates at a density of 1,000 cells per well. On day 3, the plates were left to incubate at room temperature for 1 h, following which 20 μl of the CellTiter-Glo reagent was introduced into each well. The mixture was then subjected to agitation using an orbital shaker for 10 min. Luminescence levels were determined using a Synergy H1 hybrid multi-mode reader (Bio-Tek, Winooski, VT, USA).

Whole exome sequencing of cell lines. DNA was extracted from parental and acquired alpelisib-resistant cell lines. Library preparation and exome capture were conducted using Agilent SureSelectXT Human All Exon V6 (Santa Clara, CA, USA). Whole exome sequencing (WES) was performed with a paired-end, 100-bp using Illumina NovaSeq 6000 (San Diego, CA, USA). The depth of coverage of tumors and normal control samples were at least 300× and 200×, respectively. WES data were analyzed using the Genomon2 pipeline (Institute of Medical Science, University of Tokyo, Tokyo, Japan; https://github.com/Genomon-Project/, last accessed on Dec 2, 2024) as previously described (18). In brief, sequencing reads from adapter-trimmed .fastq files were aligned to the human reference genome GRCh37 (hg19) using Burrows-Wheeler Aligner version 0.7.12, with default settings. Single nucleotide variants and small indels were called by eliminating polymorphisms and sequencing errors and filtered by pre-specified criteria (18). Then, the merged list of target variants was manually called in each .bam file using bam-readcount version 0.8.0 (https://github.com/genome/bam-readcount, last accessed on Dec 2, 2024) with Phred score and mapping quality of more than 30 and 60, respectively.

Phosphorylation array analysis of JAK/STAT and AKT signaling pathways. Human JAK/STAT Pathway Phosphorylation Array C1 (AAH-JAKSTAT-1-4) and AKT Pathway Phosphorylation Array C1 (AAH-AKT-1-4) were obtained from RayBiotech (Norcross, GA, USA). The phosphorylation arrays were conducted according to the manufacturer’s instructions.

Western blotting. Following PBS washing, cells underwent treatment with radioimmunoprecipitation assay (RIPA) buffer, then were detached from the culture dish using a cell scraper and collected into 1.5 ml tubes. Cell lysates were obtained via centrifugation at 12,000×g for 30 min at 4°C. Protein concentration in the resulting supernatant was determined using the Bradford assay (BioLegend, San Diego, CA, USA). Subsequently, proteins (ranging from 10 to 40 μg) were separated using SDS polyacrylamide gel electrophoresis and transferred onto polyvinylidene difluoride membranes (Bio-Rad, Hercules, CA, USA). Membranes were blocked with a 5% skim milk buffer, followed by overnight incubation with primary antibodies. Afterward, membranes were exposed to secondary antibodies conjugated with horseradish peroxidase (dilution of 1:4,000) for 1 h. Immunoreactivity was visualized using an enhanced chemiluminescence assay (Biosesang, Seongnam, Republic of Korea), with imaging performed using a ChemiDoc Touch imager (Bio-Rad). Western blot analyses were performed in at least three biological replicates.

Cdc42 and Rac1 activity assay. The activity of Cdc42 and Rac1 was assessed using a pull-down assay with GTPase-coated beads, performed according to the manufacturer’s instructions with the Rac1/Cdc42 activity assay kit (#17-441, Sigma). Cdc42 and Rac1 activity was assessed employing the Rac1/Cdc42 Activation Assay Kit (#17-441, Sigma) following the manufacturer’s instructions. Cells were cultured on serum-free media for 20 h, followed by lysing through scraping in Mg2+ lysis buffer consisting of 25 mM Hepes (pH 7.5), 150 mM NaCl, 1% Igepal CA-630, 10 mM MgCl2, 1 mM EDTA, and 2% glycerol. After a brief centrifuge pulse, the supernatant was collected. For every 400 μl of cell extract, 10 μg of Cdc42/Rac1 assay reagent (PAK-1 PBD, agarose beads) was added and incubated for 1 h at 4°C with gentle rotating. Subsequently, beads were centrifuged (5 s, 13,000 rpm, 4°C), washed three times with wash buffer, and then resuspended in 4X SDS buffer, followed by boiling for 5 min at 95°C before western blotting. Total and activated Cdc42 and Rac1 were subjected to analysis through western blotting, as previously described, using anti-Cdc42 or anti-Rac1 antibodies, respectively.

Plasmid, virus production, and transduction. The pMDLg/pRRE (Addgene plasmid #12251), pRSV/REV (Addgene plasmid #12253), pMD2.G (Addgene plasmid #12259) were gifts from Professors Didier Trono (19). Additionally, the TLCV2 (Addgene plasmid #87360) was a gift from Professor Adam Karpf (20). On the day before transfection, 2.5×106 293T cells were seeded onto 100 mm culture plates. Transfection was performed using polyethylenimine following the manufacturer’s guidelines. Specifically, the transfection mixture comprised 2 μg of TLCV2, 7.5 μg of pMDLg/pRRE, 7.5 μg of pRSV/REV, and 5 μg of pMD2.G. The DNA: PEI complex (in a 1:4 ratio) was added to the cells, and the volume was adjusted to 10 mL using Opti-MEM (Thermo Fisher Scientific) before overnight incubation. After 48 h of transfection, the viral supernatants were harvested and filtered using a 0.22 μm pore-size filter. The viral supernatants were then stored at −70°C until further use. For SNU601-R and AGS-R cells infected with the viral supernatants, puromycin was gradually introduced over several weeks to facilitate the selection of stable cells. Doxycycline (10 μg/ml) was used to induce Cas9-based conditional knockout in stable cells, with treatment times varying by experiment.

Combination index analysis. Cells were seeded onto 384-well plates at a density of 1,000 cells per well. Then, treatments with individual agents and their combinations commenced and continued for 3 days. These treatments were based on a ten-point titration curve centered around the half-maximal inhibitory concentration (IC50) values of the single agents. Cell viability was assessed using a CellTiter-Glo luminescent cell viability assay according to the manufacturer’s instructions. Subsequently, combination index (CI) scores were computed utilizing a methodology previously outlined by Chou (21) and facilitated by the CalcuSyn software (Biosoft). The CalcuSyn software implements the Chou-Talalay CI method, which is founded on the median-effect equation, rooted in the mass-action law. By inputting resultant proliferation data and data from single drug treatments into CalcuSyn, CI values were obtained for each combination point, providing a quantitative assessment of synergy (CI <1), additivity (CI=1), and antagonism (CI >1).

Caspase-3/7 assay. Cells were seeded onto 96-well plates at a density of 3×103 cells per well. Following this, the cells underwent treatment with either the vehicle alone, SN38 alone (5 nM), or SN38 in combination with TGX-221 (1 μM), pictilisib (1 μM), PI-103 (1 μM), MK2206 (1 μM), ipatasertib (1 μM), and capivasertib (1 μM) for 48 h. Caspase-3/7 activity was assessed using a luminometric Caspase-Glo® 3/7 Assay kit (Promega, Madison, WI, USA) according to the manufacturer’s instructions. The caspase reagent was added to the wells, and the plate was mixed using an orbital shaker before incubating at room temperature for 30 min. Luminescence was then measured using a Synergy H1 hybrid multi-mode reader (Bio-Tek, Winooski, VT, USA). The caspase-3/7 activity values presented were normalized relative to the untreated vehicle control value.

Colony forming assay. Cells were initially seeded onto 6-well plates and allowed to grow for 4 days. Following this incubation period, the cells underwent the specified treatments for 14 days, during which the culture media was regularly changed. After the 14-day culture period, the colonies were processed through several steps. Firstly, they were washed with PBS and subsequently stained with Coomassie Brilliant Blue for 30 min at room temperature. Following staining, the colonies were rinsed with water and allowed to air dry. Following this, the colonies were imaged using a ChemiDoc Touch imager (Bio-Rad), and their measurements were obtained using the ImageJ software (National Institutes of Health, Bethesda, MD, USA).

Sphere forming assay. Cells were seeded at a density of 5×102 cells per well in 24-well plates coated with poly-HEMA and Matrigel. The growth medium consisted of RPMI supplemented with 20 ng/ml EGF (PeproTech, Cranbury, NJ, USA), 20 ng/ml bFGF (PeproTech), 50 ng/ml IGF (PeproTech), and 1x B27 (Invitrogen, Waltham, MA, USA). Cells were incubated at 37°C in a humidified atmosphere containing 5% CO2 for up to 7 days. Sphere areas were measured and compared between groups.

Statistical analysis. The data were analyzed utilizing IBM SPSS Statistics for Windows version 28.0 (IBM Corp., Armonk, NY, USA). The significant differences between the mean values were assessed using Duncan’s multiple range test. Statistical significance was set at p<0.05. Dunnett’s test was performed to validate the reproducibility of the results. Statistical significance was denoted as *p<0.05, **p<0.01, and ***p<0.001. Additionally, a student’s t-test was utilized to compare two independent groups, where significance levels were denoted as follows: *p<0.05; **p<0.01; or ***p<0.001.

Results

Acquired resistance to alpelisib was developed in PIK3CA-mutant GC cell lines through prolonged treatment. To assess the genetic variation that may arise from extended treatment with alpelisib, PIK3CA-mutant GC cells (SNU601-P and AGS-P) were treated with increasing doses for 12 months. DNA fingerprinting verified that the acquired alpelisib-resistant cell lines were derived from the parental cells. After being exposed to alpelisib continuously for 12 months, the cells acquired resistance to alpelisib and were designated as SNU601-R and AGS-R, corresponding to their parental cells, SNU601-P and AGS-P, respectively. By analyzing the half-maximal inhibitory concentration (IC50) values, it was found that the SNU601-R and AGS-R cells were less sensitive to alpelisib with IC50 values of 19.35 μM and 14.67 μM, respectively, than their parental control cells [SNU601-P (0.84 μM) and AGS-P (0.93 μM), respectively] (Figure 1). This indicates an increase in resistance of approximately 23-fold and 16-fold, respectively. Thus, SNU601-P, -R, and AGS-P, -R cells were used in this study to analyze the mechanism of acquired alpelisib resistance, further.

Figure 1.
Figure 1.

Evaluation of alpelisib cytotoxicity in parental and acquired alpelisib-resistant SNU601 and AGS cells. (A) SNU601 parent and acquired alpelisib-resistant cells and (B) AGS parent and acquired alpelisib-resistant cells were seeded in 384-well plates and treated with alpelisib at the indicated concentrations (n=4). After 3 days of incubation, the antiproliferative effect was assessed using the CellTiter-Glo® luminescent cell viability assay.

Loss of PTEN function causes acquired alpelisib resistance. We analyzed WES data to assess the genomic differences between parental and acquired alpelisib-resistant cell lines. Mutations and copy number variations identified in acquired alpelisib-resistant cell lines compared to the parental cell lines were comprehensively analyzed. From these data, two key patterns were identified as potential drivers of acquired alpelisib resistance: (1) mutations in tumor suppressor genes accompanied by copy number loss or the complete loss of both homologous alleles containing the tumor suppressor gene; and (2) gain-of-function mutations or amplifications in oncogenes. Interestingly, PTEN alterations were observed in both SNU601-R and AGS-R cell lines (Table I and Figure 2). In SNU601-R, a copy number loss was accompanied by a p.R74fs frameshift deletion. In AGS-R, both homologous alleles containing the PTEN locus were completely lost. Notably, both SNU601 and AGS parental cell lines originally harbored wild-type PTEN (22). These findings suggest that the loss of PTEN function is a critical mechanism driving acquired alpelisib resistance.

View this table:
Table I.

PTEN alterations identified in alpelisib-resistant cell lines compared to the parental cell lines.

Figure 2.
Figure 2.

Identification of PTEN loss through whole exome sequencing in SNU601-R and AGS-R cells. (A) In SNU601-R cells, PTEN loss was characterized by a copy number loss accompanied by a p.R74fs frameshift deletion. (B) In AGS-R cells, both homologous alleles containing the PTEN locus were completely lost.

Loss of PTEN leads to activation of SRC, STAT1, AKT, and PRAS40 phosphorylation in acquired alpelisib-resistant SNU601 and AGS cells. To determine the differences in the JAK/STAT and AKT signaling pathways between acquired alpelisib-resistant and parental cells, we used a human JAK/STAT and AKT pathway phosphorylation array. Phosphorylation protein array analysis showed that p-SRC Y419 expression increased by 1.37-fold (p<0.05) in SNU601-R cells and 2.88-fold (p<0.05) in AGS-R cells compared to their respective parental cells (Figure 3A). The levels of p-STAT1 S727 increased by 1.31-fold (p<0.05) in SNU601-R cells and by 1.92-fold (p<0.05) in AGS-R cells (Figure 3A). Comparably, p-AKT S473 levels were 1.27-fold (p <0.05) higher in SNU601-R cells and 1.32-fold (p<0.05) higher in AGS-R cells than their parental cells (Figure 3B). Similar to p-AKT S473, p-PRAS40 T246 increased 2.28-fold (p <0.05) in SNU601-R cells and 1.15-fold (p<0.05) in AGS-R cells compared to parental cells.

Figure 3.
Figure 3.
Figure 3.

Protein expression of JAK/STAT and AKT signaling pathways in acquired alpelisib-resistant cells. (A) JAK/STAT phosphorylation array analysis was performed in SNU601-P and -R cells, as well as AGS-P and -R cells (n=2). (B) AKT phosphorylation array analysis was conducted in SNU601-P and -R cells, as well as AGS-P and -R cells (n=2). (C) For Western blot analysis, cells were seeded at a density of 1×106 cells per 60 mm plate. The following day, the medium was replaced with serum-free media, and the cells were incubated for 24 h. After incubation, the cells were harvested, quantified, and analyzed for protein expression using western blot. Indicated antibodies were used to detect the respective proteins, with vinculin serving as the loading control.

We used western blot analysis to confirm the repeatability of the exome sequencing findings on PTEN depletion and protein array results in acquired alpelisib-resistant cell lines. PTEN, which was highly expressed in parental SNU601 and AGS cells, was found to be barely detectable in SNU601-R and AGS-R cells (Figure 3C). The expression levels of p-SRC Y419, p-STAT1 S727, p-AKT S473, and p-PRAS40 T246 were clearly higher in the acquired alpelisib-resistant cells compared to the parental cells, thus validating the reproducibility of the phosphorylation protein array results.

AKT activation is mediated by the p110β-Cdc42 feedback mechanism in acquired alpelisib-resistant cells. To investigate whether PTEN loss mediated by acquired alpelisib resistance affects AKT and PRAS40 phosphorylation through PI3K p110α or PI3K p110β signaling, we generated conditional knockout SNU601-R and AGS-R cells for p110α and p110β. Treatment of both cell lines with 10 μg/ml doxycycline for 48 h revealed that p-PRAS40 T246 expression levels slightly decreased following the conditional knockout of sgp110α and sgp110β in SNU601-R, while a substantial reduction was observed in AGS-R cells. However, p-S6BP S240/4 expression was further reduced in sgp110β compared to sgp110α in both cell lines (Figure 4A). These data may indicate that in SNU601 and AGS cells, PI3K p110β feedback resulting from PTEN loss can activate AKT signaling when acquired alpelisib resistance develops.

Figure 4.
Figure 4.
Figure 4.

AKT activation driven by PI3K p110β and Cdc42 activity in acquired alpelisib-resistant cells. (A) PIK3CA and PIK3CB conditional knockout cell lines were treated with 10 μg/ml doxycycline for 48 h. Western blot analysis was performed in SNU601-R and AGS-R cells using specific antibodies to detect the expression of indicated proteins. (B) Cdc42/Rac1 GTPase activity was observed in SNU601-P and -R cells, as well as AGS-P and -R cells. (C) Cdc42 conditional knockout SNU601-R cells were treated with 10 μg/ml doxycycline for 72 and 96 h. Western blot analysis was conducted using specific antibodies to assess the expression of indicated proteins.

PI3K p110β activation can occur through the replacement of GDP with GTP in the GTPase Ras binding domain (23). Using a pulldown assay, we examined Cdc42/Rac1 GTP activity in both acquired alpelisib-resistant and parental cell lines to investigate how PTEN loss due to alpelisib resistance leads to AKT activation. Our analysis revealed that acquired alpelisib-resistant cells exhibited a substantial increase in the GTP-bound form of Cdc42/Rac1 in SNU601-R and AGS-R cells compared to their respective parental cells (Figure 4B).

Next, we performed Cdc42 conditional knockout experiments in SNU601-R cells to investigate the potential effects of Cdc42 knockout on the regulation of downstream AKT signaling. Cdc42 expression decreased in SNU601-R cells stably expressing gRNA after treatment with 1 μg/mL of doxycycline for 0, 72, and 96 h (Figure 4C). Additionally, the expression of AKT substrate p-PRAS40 T246 and the downstream target gene p-S6BP S240/244 decreased in a time-dependent manner. These findings suggest that the link between p110β and GTP-bound Cdc42 is preserved in the acquired alpelisib-resistant state of GC cells, resulting in AKT activation.

Inhibition of SRC and STAT1 did not suppress the proliferation of acquired alpelisib-resistant GC cells. Next, we investigated whether inhibiting proteins activated by acquired alpelisib resistance would inhibit the proliferation of acquired alpelisib-resistant GC cells. We evaluated STAT1 and SRC by treating SNU601-P, -R, and AGS-P, -R cells with the STAT1 inhibitor fludarabine and the SRC inhibitors bosutinib, dasatinib, and saracatinib. In SNU601 cells, SNU601-R exhibited cross-resistance to alpelisib and fludarabine, whereas in AGS cells, there was no differential response to fludarabine between the parental and acquired alpelisib-resistant cells (Figure 5A). Following treatment with SRC inhibitors, SNU601-R showed cross-resistance to bosutinib, and AGS-R exhibited cross-resistance to dasatinib and saracatinib. The IC50 values of STAT1 or SRC inhibitors in acquired alpelisib-resistant cells were not lower than those in the parental cells (Figure 5B). Therefore, it was confirmed that blocking SRC and STAT1 in acquired alpelisib-resistant cells is not an effective strategy.

Figure 5.
Figure 5.
Figure 5.

Evaluation of overcoming acquired alpelisib resistance using STAT1, SRC, PI3K, or AKT Inhibitors in acquired alpelisib-resistant GC cells. (A) Cells were seeded in 384-well plates and treated with fludarabine at the indicated concentrations (n=4). (B) Cells were seeded in 384-well plates and treated with bosutinib, dasatinib, and saracatinib (n=4). (C) Cells were seeded in 384-well plates and treated with AZD8186, TGX-221, duvelisib, pictilisib, PI-103, MK-2206, ipatasertib, and capivasertib (n=4). For (A), (B), and (C), after 3 days of incubation, the antiproliferative effect was measured using the CellTiter-Glo® luminescent cell viability assay. (D) For Western blot analysis, cells were seeded at a density of 1×106 cells per 60 mm plate. The following day, the medium was replaced with serum-free media, and the cells were incubated for 24 h. After incubation, the cells were treated with the respective inhibitors for 24 h, then harvested, quantified, and analyzed for protein expression. Indicated antibodies were used to detect the respective proteins, with Vinculin serving as the loading control.

Screening of PI3K or AKT inhibitors was conducted to examine whether they could overcome acquired alpelisib-resistance in SNU601-R and AGS-R cells. To investigate another strategy of inhibiting the PI3K and AKT signaling pathways, we treated SNU601-R and AGS-R cells with PI3K and AKT inhibitors. This allowed us to find drugs that particularly inhibited proliferation in acquired alpelisib-resistant cells. The efficiency of these inhibitors was assessed by determining their IC50 values in acquired alpelisib-resistant cell lines. PI-103, p110α/β/δ/γ inhibitor, displayed IC50 values of 11.20 μM for SNU601-R cells and 3.38 μM for AGS-R cells (Figure 5C). Pictilisib, p110α/β/δ/γ inhibitor, demonstrated IC50 values of 7.42 μM for SNU601-R cells and 7.91 μM for AGS-R cells (Table II). For SNU601-R cells, AZD8186, p110β/δ inhibitor, showed an IC50 value of 11.36 μM, while for AGS-R cells, the IC50 value was 8.74 μM. TGX-221, p110β inhibitor, had IC50 values of 70.29 μM in SNU601-R cells and 61.75 μM in AGS-R cells. Duvelisib, p110δ/γ inhibitor, had IC50 values of 36.05 μM in SNU601-R cells and 11.19 μM in AGS-R cells.

View this table:
Table II.

Evaluation of the half-maximal dose of PI3K or AKT inhibitors in acquired alpelisib-resistant GC cells.

Ipatasertib, pan-AKT inhibitor, considerably increased the sensitivity of SNU601-R cells, exhibiting IC50 values of 1.62 μM in SNU601-R cells and 0.37 μM in AGS-R cells. MK-2206, allosteric AKT inhibitor, had comparable IC50 values in SNU601-R cells and AGS-R cells, measuring 1.34 μM and 0.88 μM, respectively. Capivasertib, pan-AKT inhibitor, exhibited strong inhibitory effects, with IC50 values of 0.44 μM in SNU601-R cells and 0.09 μM in AGS-R cells. These findings highlight the varying degrees of sensitivity and resistance to various inhibitors between the two cell lines. Notably, the results imply that AKT inhibitors, such as capivasertib, ipatasertib, and MK-2206, have a more pronounced antiproliferative impact on SNU601-R and AGS-R cells compared to inhibitors that target the PI3K isoform.

We next assessed the inhibitory effects of AKT and PI3K inhibitors on the expression of AKT signaling at a consistent dose of 1 μM using Western blot analysis. Among the PI3K inhibitors, pictilisib efficiently inhibited p-S6RP S240/4 in SNU601-R cells, whereas PI-103 inhibited p-S6RP S240/4 in AGS-R cells (Figure 5D). Interestingly, in both cell lines, AKT inhibitors demonstrated significant inhibitory effects on AKT signaling pathway. MK-2206 exhibited robust inhibition of p-AKT S473 and p-AKT T308. Ipatasertib and capivasertib effectively inhibited AKT activity in preclinical models, leading to dephosphorylation of AKT substrates and downstream pathway proteins (24, 25). Consistent with these findings, we observed that both inhibitors notably reduced the phosphorylation of the AKT downstream target p-S6BP S240/4.

SN38 combined with capivasertib demonstrated notable cytotoxic activity in SNU601-R and AGS-R cells. Next, we evaluated whether combining PI3K or AKT inhibitors with SN38, the active metabolite of irinotecan, would provide an advantage in treating acquired alpelisib-resistant GC cells compared to using SN38 alone. Irinotecan is widely used as a third-line chemotherapy in metastatic or recurrent GC, so it was selected as a drug to be combined with capivasertib in this study. Western blot analysis revealed that pictilisib in SNU601-R cells and PI103 in AGS-R cells inhibited the AKT signaling pathway (Figure 6A), consistent with the results shown in Figure 5D. Among the AKT inhibitors, MK-2206 specifically inhibited p-AKT S473, while ipatasertib and capivasertib notably suppressed p-PRAS40 T246 and p-S6BP S240/4. In contrast, SN38 treatment alone did not significantly affect the AKT signaling pathway. When comparing SN38 treatment alone with SN38 combined with PI3K or AKT inhibitors, the combination treatment increased γ-H2AX levels in SNU601-R cells. In AGS-R cells, the combination of SN38 and AKT inhibitors markedly enhanced the expression of γ-H2AX compared to SN38 combined with TGX-221, pictilisib, or PI-103.

Figure 6.
Figure 6.
Figure 6.

Assessment of the combined effects of SN38 with PI3K or AKT inhibitors in acquired alpelisib-resistant GC Cells. (A) For Western blot, 1×106 cells were seeded per 60 mm plate, incubated in serum-free media for 24 h, treated with inhibitors for another 24 h, and analyzed for protein expression using specific antibodies. Vinculin was used as the loading control. (B) For caspase-3/7 activity, 3×103 cells were seeded per 96-well plate, treated with inhibitors for 48 h, and assessed using the Caspase-Glo® 3/7 Assay kit according to the manufacturer’s instructions (n=3). (C) SNU601-R and AGS-R cells were treated with increasing concentrations of SN38 and PI3K or AKT inhibitors at a constant ratio (n=4). Combination index (CI) values were calculated using CalcuSyn software based on the Chou-Talalay method.

To further investigate the effects of PI3K and AKT inhibitors in combination with SN38, we evaluated the caspase-3/7 activity in SNU601-R and AGS-R cells. In SNU601-R cells, SN38 treatment alone significantly increased caspase-3/7 activity, and combining SN38 with capivasertib further enhanced this activity compared to SN38 alone. In AGS-R cells, SN38 combined with pictilisib, PI-103, MK-2206, ipatasertib, or capivasertib exhibited higher caspase-3/7 activity than SN38 alone, with the combination of SN38 and capivasertib showing the highest caspase-3/7 activity.

In addition, we evaluated the synergistic effects of SN38 combined with PI3K or AKT inhibitors in SNU601-R and AGS-R cells. The CI values for TGX-221, pictilisib, PI-103, MK-2206, ipatasertib, and capivasertib in SNU601-R cells were 0.320, 0.134, 0.245, 0.286, 0.384, and 0.295, respectively (Figure 6C). In AGS-R cells, the CI values were 0.939 for TGX-221, 0.716 for pictilisib, 0.877 for PI-103, 0.736 for MK-2206, 0.405 for ipatasertib, and 0.333 for capivasertib.

To evaluate the effect of prolonged treatment with SN38 and capivasertib, we performed a colony-forming assay and observed that the combination treatment significantly inhibited colony formation in SNU601-R and AGS-R cells compared to SN38 or capivasertib alone (Figure 7A). Additionally, we assessed the sphere-forming ability of SNU601-R and AGS-R cells by treating them with SN38 alone, capivasertib alone, or the combination. Both SN38 and capivasertib alone significantly reduced sphere formation in these cells (Figure 7B), while the combination treatment demonstrated a more pronounced inhibitory effect on sphere formation than either treatment alone.

Figure 7.
Figure 7.
Figure 7.

Assessment of the impact of prolonged combination treatment with SN38 and capivasertib on colony forming and sphere forming ability in acquired alpelisib-resistant cell lines. (A) Colony-forming ability was assessed in acquired alpelisib-resistant cells treated with SN38 (0, 0.5, and 1 nM) alone, capivasertib (0, 0.5, and 1 μM) alone, or their combination (n=3). (B) Sphere-forming ability was evaluated in acquired alpelisib-resistant cells treated with SN38 (0 and 0.5 nM) alone, capivasertib (0 and 0.5 μM) alone, or their combination (n=3).

These findings indicate that the addition of PI3K or AKT inhibitors to SN38 treatment can enhance therapeutic efficacy in GC cells with acquired resistance to alpelisib. Notably, among the PI3K and AKT inhibitors, capivasertib exhibited the most pronounced synergistic effects with SN38, showing superior cytotoxic activity in both SNU601-R and AGS-R cells.

Discussion

Our group has previously demonstrated the efficacy of combining alpelisib with paclitaxel in GC cell lines and mouse models harboring PIK3CA mutations (17). This preclinical research established a basis for a clinical trial targeting patients with PIK3CA-altered metastatic or recurrent GC (ClinicalTrials.gov ID: NCT04526470), in which alpelisib is combined with paclitaxel as a second-line palliative chemotherapy. However, although the combination of alpelisib with paclitaxel is being tried in PIK3CA-mutated GC patients, it is expected that acquired resistance to this regimen will eventually develop. Based on these circumstances, the present study addresses the significant challenge of overcoming acquired resistance to alpelisib in PIK3CA-mutated GC. By generating acquired alpelisib-resistant cell lines (SNU601-R and AGS-R), we identified PTEN functional loss as a common resistance mechanism. This deficiency activated downstream signaling pathways, including SRC, STAT1, and AKT. Importantly, we demonstrated that the combination of an AKT inhibitor and SN38 effectively mitigated this resistance.

Through WES and subsequent functional analyses, we confirmed that PTEN loss was a pivotal driver of acquired alpelisib resistance in both SNU601-R and AGS-R cell lines. In SNU601-R cells, PTEN loss was linked to a copy number deletion and frameshift mutation (p.R74fs), whereas AGS-R cells exhibited complete homozygous deletion of the PTEN locus. This loss of PTEN led to the activation of the PI3K/AKT signaling pathway, as evidenced by increased phosphorylation of AKT and its downstream effector PRAS40. Elevated levels of p-SRC and p-STAT1 were also observed, suggesting potential alternative pathways contributing to acquired alpelisib resistance. PTEN-deficient cells often exhibit SRC activation, suggesting PTEN acts upstream of SRC as a key regulator (26). Activated SRC induces the phosphorylation of STATs, which promotes dimerization and transcriptional activation (27). However, in this study, treatment with SRC or STAT1 inhibitors failed to produce cytotoxic effects in GC cells with acquired resistance to alpelisib, suggesting their limited role as main resistance drivers.

PTEN acts as a tumor suppressor by dephosphorylating PIP3, thereby antagonizing the PI3K/AKT pathway (28). PTEN deficiency has been associated with resistance to therapies such as tamoxifen, trastuzumab, and alpelisib in breast cancer (29-31), anti-PD-1 therapy in non-small cell lung cancer (32), trastuzumab in GC (33), MDM2 inhibitor CGM097 in colorectal cancer (34), sunitinib in renal cell carcinoma (35), and selumetinib in acute myeloid leukemia (36). These associations underscore PTEN’s critical role as a biomarker for predicting drug resistance across various cancers. To overcome resistance to PIK3CA inhibitors and PTEN loss in cancer, pan-PI3K and PI3K-selective inhibitors have been used (37-39). However, little is known about the mechanisms underlying acquired resistance to alpelisib in PIK3CA-mutated GC, and there is currently no successful clinical treatment strategy in this situation.

Our findings underscore the therapeutic potential of targeting the PI3K/AKT pathway in PTEN-deficient GC. This concept was previously proposed, as AKT activation is linked to chemoresistance in GC, and targeting the PI3K/AKT pathway may improve therapy (40). Among the inhibitors tested, capivasertib, an AKT inhibitor, exhibited the highest cytotoxicity in alpelisib-resistant cell lines. To further enhance clinical relevance, we explored combinations involving SN38, the active metabolite of irinotecan (a topoisomerase I inhibitor) which is commonly employed in third-line GC therapy. As we are currently conducting a clinical trial with the combination of alpelisib and paclitaxel as a second-line palliative chemotherapy in patients with PIK3CA-altered GC, irinotecan was selected as the cytotoxic anticancer agent to be used in combination with other anticancer drugs in this preclinical study. The combination of capivasertib and SN38 showed remarkable synergy, significantly reducing cell viability and enhancing caspase-3/7 activity in both SNU601-R and AGS-R cells. Extended treatment also inhibited colony formation and 3D spheroid proliferation, further validating its efficacy.

While pan-PI3K and AKT inhibitors demonstrated cytotoxicity in acquired alpelisib-resistant cell lines, their intolerable toxicity in clinical settings limits their practical use. Capivasertib is an AKT inhibitor already in clinical use for metastatic breast cancer. As a third-line therapy for alpelisib-resistant metastatic or recurrent GC, our research prioritizes the combination of capivasertib and irinotecan, which exhibited robust antiproliferative effects in preclinical models.

A limitation of this study was the limited number of cell lines and the lack of in vivo models. We attempted several times to conduct animal experiments using the SNU601-R and AGS-R cell lines, but these cell lines did not grow when subcutaneously transplanted into mice, making it impossible to conduct animal experiments. Nonetheless, the consistent observation of PTEN loss across two distinct GC cell lines strengthens the validity of our findings. By linking PTEN deficiency to acquired alpelisib resistance-mediated by the p110β-Cdc42 feedback mechanism and subsequent AKT activation—we provide a mechanistic foundation for future research. This insight highlights the role of PTEN loss in driving oncogenic signaling pathways and therapeutic resistance.

Conclusion

This study advances our understanding of the mechanisms underlying acquired alpelisib resistance in PIK3CA-mutant GC and provides compelling evidence for combining capivasertib with chemotherapy as a strategy to overcome this challenge. Further investigations using patient-derived xenografts and clinical samples may be necessary to confirm these findings’ clinical applicability.

Acknowledgements

This research was funded by the Seoul National University Bundang Hospital Research Fund (No. 14-2019-006) and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MIST) (No. RS-2023-00240907). The funders played no role in the study design, data collection and analysis, decision to publish, and preparation of the manuscript. We would like to thank Novartis Pharma AG for providing alpelisib for this pre-clinical research. We extend our gratitude to Prof. Didier Trono for providing pMDLg/pRRE, pRSV/REV, and pMD2.G, and to Prof. Adam Karpf for providing TLCV2.

Footnotes

  • Authors’ Contributions

    Minsu Kang: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Validation; Visualization; Roles/Writing – original draft; Writing – review & editing. Kui-Jin Kim: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Validation; Visualization; Roles/Writing – original draft; Writing – review & editing. Ji Hea Sung: Data curation; Formal analysis; Methodology; Visualization. Milang Nam: Data curation; Formal analysis; Methodology; Visualization. Sung-Hyun Hwang: Data curation; Formal analysis; Methodology; Visualization. Woochan Park: Data curation; Project administration; Resources; Writing – review & editing. Jeongmin Seo: Data curation; Project administration; Resources; Writing – review & editing. Eun Hee Jung: Data curation; Project administration; Resources; Writing – review & editing. Koung Jin Suh: Data curation; Project administration; Resources; Writing – review & editing. Ji-Won Kim: Data curation; Project administration; Resources; Writing – review & editing. Se Hyun Kim: Data curation; Project administration; Resources; Writing – review & editing. Jin Won Kim: Data curation; Project administration; Resources; Writing – review & editing. Yu Jung Kim: Data curation; Project administration; Resources; Writing – review & editing. Jee Hyun Kim: Data curation; Project administration; Resources; Writing – review & editing. Keun-Wook Lee: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; Roles/Writing – original draft; Writing – review & editing.

  • Conflicts of Interest

    The Authors declare no conflicts of interest.

  • Received February 6, 2025.
  • Revision received March 14, 2025.
  • Accepted April 2, 2025.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

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Development of Acquired Resistance in Alpelisib-treated Gastric Cancer Cells With PIK3CA Mutations and Overcoming Strategies
MINSU KANG, KUI-JIN KIM, JI HEA SUNG, MILANG NAM, SUNG-HYUN HWANG, WOOCHAN PARK, JEONGMIN SEO, EUN HEE JUNG, KOUNG JIN SUH, JI-WON KIM, SE HYUN KIM, JIN WON KIM, YU JUNG KIM, JEE HYUN KIM, KEUN-WOOK LEE
Anticancer Research May 2025, 45 (5) 1877-1896; DOI: 10.21873/anticanres.17567
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