AKT1 Functional Polymorphism (rs2494750) Influences Clinical Outcomes in Patients With Advanced Lung Cancer Treated With EGFR Inhibitors

Abstract

Background

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are the standard first-line treatment for patients with advanced lung cancer harboring activating EGFR mutations. This study aimed to investigate the association between genetic polymorphisms in the EGFR signaling pathway and clinical outcomes in patients receiving EGFR-TKI therapy.

Methods

We enrolled 266 patients with advanced lung cancer treated with EGFR-TKIs and examined 30 putative functional polymorphisms across 11 genes involved in the EGFR signaling pathway. Associations between these polymorphisms and clinical outcomes were assessed.

Results

Among the polymorphisms analyzed, AKT1 rs2494750G>C was significantly associated with improved chemotherapy response (codominant model: odds ratio, 1.78; 95% confidence interval [CI], 1.05–2.99; P = 0.031) and prolonged progression-free survival (recessive model: hazard ratio, 0.62; 95% CI, 0.39–0.97; P = 0.037). In the luciferase reporter assays, the rs2494750C allele exhibited significantly lower promoter activity than the rs2494750G allele in H522 and A549 lung cancer cell lines (P = 0.033 and P < 0.001, respectively). AKT1 expression levels were also significantly reduced in individuals with the CC genotype compared to those with GG or GC genotypes (P = 0.034).

Conclusion

The AKT1 rs2494750G>C polymorphism reduces promoter activity and gene expression of AKT1, potentially contributing to improved clinical outcomes in patients with advanced lung cancer treated with EGFR-TKIs.

Graphical Abstract

INTRODUCTION

Lung cancer remains the leading cause of cancer-related mortality worldwide.1 The identification of driver mutations in cancer-related genes (EGFR mutation, ALK and ROS1 rearrangements, BRAF V600E, KRAS G12C mutations) and consequently, the emergence of targeted therapies for each mutation, has significantly transformed the therapeutic landscape of lung cancer.2,3 The development of targeted therapies for these genetic alterations, including epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) and ALK inhibitors, has led to marked improvements in survival outcomes and reduced adverse reactions compared to conventional cytotoxic chemotherapy. Among the various actionable driver mutations, EGFR mutations are the most common, and mutation prevalence varies by racial background, occurring in approximately 40–60% of Asian patients, compared to 10–15% in Western populations.2

EGFR-TKIs have become the standard first-line treatment for patients with advanced non-small cell lung cancer (NSCLC) harboring activating EGFR mutations.4 First-generation EGFR-TKIs (e.g., gefitinib and erlotinib) significantly improved response rates and progression-free survival (PFS) compared to platinum-based chemotherapy.5,6 Second-generation agents (e.g., afatinib and dacomitinib) further extended PFS in comparison to their first-generation counterparts.7,8 More recently, third-generation EGFR-TKIs (e.g., osimertinib and lazertinib) are being developed and are now adopted in clinical practice.9,10 Nevertheless, resistance to EGFR-TKIs remains an inevitable challenge in most cases. Mechanisms of resistance may be EGFR-dependent, such as the T790M mutation or EGFR amplification, or EGFR-independent, involving alterations in HER-2, MET, FGFR, or even histological transformation to small cell lung cancer.11 Additionally, patients with exon 19 deletions tend to have a more favorable outcomes with EGFR-TKI therapy compared to those with exon 21 L858R mutations.4,12 Despite these observations, significant variability in treatment response and outcome persists even among patients with the same EGFR mutation, underscoring the need for additional predictive biomarkers.

Single nucleotide polymorphisms (SNPs), the most common form of genetic variation, represent a single base change in the genome. Certain functional SNPs can influence cancer susceptibility, treatment response, or prognosis.13,14,15 Based on this rationale, we hypothesized that SNPs in genes involved in the EGFR signaling pathway may influence the clinical efficacy of EGFR-TKIs in patients with NSCLC harboring EGFR mutations, thereby impacting treatment response or PFS. Therefore, we aimed to identify putative functional SNPs in EGFR signaling pathway–related genes and investigate their potential association with clinical outcomes in this patient population.

METHODS

Study population

This retrospective study included patients diagnosed with stage III or IV NSCLC who were not candidates for curative surgical resection and received first-line therapy with EGFR-TKIs at Kyungpook National University Hospital (KNUH) between April 2010 and April 2017. Patients with stage IV disease who experienced recurrence after curative surgery and subsequently received EGFR-TKIs as first-line chemotherapy were also included. A total of 266 patients who provided informed consent and biological samples were enrolled. Among them, 148 had EGFR exon 19 deletions, 111 had the exon 21 L858R mutation, and 7 had uncommon EGFR mutations. All patients were Korean and had adenocarcinoma histology. The EGFR-TKIs used during the study period were gefitinib, erlotinib, and afatinib; second-generation dacomitinib and the third-generation osimertinib and lazertinib had not yet been approved in Korea for first-line use as of April 2017.

Genomic DNA was extracted from whole blood samples obtained prior to treatment. Samples were provided by the National Biobank of Korea-KNUH, supported by the Ministry of Health, Welfare and Family Affairs.

Polymorphism selection and genotyping

A total of 614,701 polymorphisms in 16 genes related to the EGFR signaling pathway were retrieved from the NCBI database (https://www.ncbi,nlm,nih,gov/SNP): EGFR, ERBB2, ERBB3, ERBB4, KRAS, NRAS, BRAF, PTEN, PIK3CA, LKB1, AKT1, mTOR, NF1, RASA1, TSC1, and TSC2. From these, 843 putative functional polymorphisms were selected using the SNP functional prediction model (https://snpinfo.niehs,nih.gov/). SNPs with a minor allele frequency of < 0.1 in HapMap Japanese population in Tokyo (n = 761) and those in strong linkage disequilibrium (LD) (r² > 0.8) (n = 46) were excluded using the TagSNP utility for LD tag SNP selection. This filtering resulted in 36 candidate SNPs. Genotyping was performed using the Sequenom MassARRAY iPLEX assay (Sequenom, San Diego, CA, USA) according to the manufacturer’s instructions. One SNP failed genotyping and five SNPs were excluded due to deviation from Hardy-Weinberg equilibrium (P < 0.05) or low call rates (< 95%). Ultimately, 30 SNPs in 11 EGFR signaling pathway–related genes were analyzed for associations with clinical outcomes in the 266 enrolled patients.

Promoter-luciferase constructs and luciferase assay

To evaluate whether the rs2494750G>C variant affects promoter activity of the AKT serine/threonine kinase 1 (AKT1) gene, we performed a luciferase assay. AKT1 promoter fragments encompassing the rs2494750 site and pGL3-basic plasmid were synthesized by polymerase chain reaction (PCR) using the following primers: AKT1 forward, 5′-cttggcattcGGAGACAGCCAGTGCAAAATAAG-3′; AKT1 reverse, 5′-aacagtaccgCAGAGGAGGAGCGGTGTCTAG-3′, pGL3-basic forward: 5′-tcctcctctgCGGTACTGTTGGTAAAGCCAC-3′ and pGL3-basic reverse, 5′-ggctgtctccGAATGCCAAGCTTACTTAGATC-3′ (overlapping sequences are indicated in lowercase). The PCR products were assembled into the pGL3-basic-AKT1 construct containing the rs2494750 G or C allele using the NEBuilder™ HiFi DNA Assembly Master Mix Kit, according to the manufacturer's instructions (New England Biolabs, Frankfurt, Germany). All constructs were verified by DNA sequencing. Human NSCLC cell lines H522 and A549 were transfected the constructs and pRL-SV40 vector (Promega, Madison, WI, USA) using Effectene transfection reagent (Qiagen, Hilden, Germany). The cells were collected 48 hours post-transfection, and luciferase activity was measured using the Dual-Luciferase® Reporter Assay System (Promega), with results normalized based on the activity of Renilla luciferase. Results are presented as the mean ± standard deviation from three independent experiments.

RNA preparation and quantitative reverse transcription-PCR

To assess ATK1 expression in tumor versus normal lung tissue, we analyzed mRNA levels in paired tumor and adjacent non-tumorous lung tissue samples from 109 patients with NSCLC who underwent surgery for stage I-IIIA disease. ATK1 mRNA expression was examined by quantitative reverse transcription-PCR (qRT-PCR). Total RNA was extracted using Trizol (Invitrogen, Carlsbad, CA, USA). Real-time PCR was performed using a LightCycler 480 (Roche Applied Science, Mannheim, Germany) and QuantiFast SYBR Green PCR Master Mix (Qiagen). The primers for AKT1 and β-actin genes were: AKT1 forward, 5′-CCACCTGACCAAGATGACAG-3′; AKT1 reverse, 5′-TCTCCATCCCTCCAAGCTATC-3′; β-actin forward, 5′-TTGTTACAGGAAGTCCCTTGCC-3′; β-actin reverse, 5′- ATGCTATCACCTCCCCTGTGT-3′. Each sample was analyzed in duplicate. Relative AKT1 mRNA expression levels were normalized to β-actin and calculated using the 2^−ΔΔCt method.

Statistical analysis

Patients were categorized as responders (complete or partial response), or non-responders (stable or progressive disease) based on their clinical response to EGFR-TKI therapy. PFS was estimated using the Kaplan-Meier method, and survival differences were assessed using the log-rank test. Multivariable Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for age, sex, smoking status, disease stage, and Eastern Cooperative Oncology Group performance status. Comparison was conducted in dominant, recessive, and codominant models. A P value < 0.05 was considered statistically significant. All analyses were conducted using the Statistical Analysis System for Windows, version 9.1 (SAS Institute, Cary, NC, USA). Box plots were generated using the ggplot2 package in R program.

Ethics statement

The study protocol was approved by the Institutional Review Board (IRB) of Kyungpook National University Hospital (IRB approval No. KNUMCBIO_14-1009), and written informed consent was obtained from all participants.

RESULTS

Clinical characteristics of the study population

The overall response rate to EGFR-TKIs was 83.8%, and the median PFS was 16.6 months (Table 1). Patients harboring EGFR exon 19 deletions tended to have a better response to therapy than those with the exon 21 L8585R mutation (P = 0.063; Table 1). Similarly, patients treated with second-generation EGFR-TKIs had a trend toward longer PFS compared to those treated with first-generation agents (P = 0.067; Table 1).

Table 1. Univariate analysis for chemotherapy response and progression-free survival by clinical variables.

Variables		No. of cases	Response to chemotherapy				Progression-free survival
			Responders (CR+PR)	Non-responders (SD+PD)	OR (95% CI)	P	MST, mon	95% CI	Log-rank P	HR (95% CI)	P
Overall		266	223 (83.8)	43 (16.2)			16.6	15.4–18.5
Age, yr
	< 65	121	101 (83.5)	20 (16.5)	1.00		15.4	12.4–8.2		1.00
	≥ 65	145	122 (84.1)	23 (15.9)	1.05 (0.55–2.02)	0.883	18.2	15.9–21.6	0.145	0.81 (0.61–1.08)	0.146
Gender
	Male	93	78 (83.9)	15 (16.1)	1.00		15.4	11.6–18.3		1.00
	Female	173	145 (83.8)	28 (16.2)	0.99 (0.50–1.98)	0.991	17.4	16.0–19.6	0.099	0.78 (0.57–1.05)	0.100
Smoking status
	Never	179	148 (82.7)	31 (17.3)	1.00		17.4	15.9–19.4		1.00
	Ever	87	75 (86.2)	12 (13.8)	1.31 (0.63–2.69)	0.464	15.4	11.6–18.3	0.484	1.16 (0.82–1.52)	0.484
Clinical stage
	Ⅲ	19	14 (73.7)	5 (26.3)	1.00		23.6	7.59–N.D.		1.00
	Ⅳ	247	209 (84.6)	38 (15.4)	1.96 (0.67–5.77)	0.219	16.4	15.1–18.3	0.096	1.71 (0.90–3.24)	0.100
PS ECOG
	0–1	86	74 (86.1)	12 (13.9)	1.00		19.4	16.6–23.6		1.00
	2	180	149 (82.8)	31 (17.2)	0.78 (0.38–1.61)	0.499	15.5	12.5–17.4	0.011	1.49 (1.09–2.03)	0.011
Weight loss
	No	166	136 (81.9)	30 (73.7)	1.00		16.4	13.0–18.5		1.00
	Yes	19	14 (18.1)	5 (26.3)	0.62 (0.21–1.85)	0.388	15.4	6.9–29.4	0.837	1.06 (0.62–1.80)	0.837
EGFR mutation
	Exon 19 deletion	148	129 (87.2)	19 (12.8)	1.00		17.4	15.5–19.4		1.00
	Exon 21 L858R	111	87 (78.4)	24 (21.6)	0.53 (0.28–1.03)	0.063	15.2	10.6–18.5		1.21 (0.91–1.62)	0.193
	Othersa	7	7 (100.0)	0 (0.0)	–	0.984	32.1	8.6–32.1	0.286	0.65 (0.21–2.05)	0.463
EGFR-TKI
	1st generation	166	135 (81.3)	31 (18.7)	1.00		15.9	12.4–17.4		1.00
	2nd generation	100	88 (88.0)	12 (12.0)	1.68 (0.82–3.45)	0.155	18.5	15.6–24.1	0.065	0.75 (0.56–1.02)	0.067

CR = complete response, PR = partial response, SD = stable disease, PD = progressive disease, OR = odds ratio, MST = median survival time, CI = confidence interval, HR = hazard ratio, PS = performance status, ECOG = Eastern Cooperative Oncology Group, N.D. = not determined.

^aUncommon EGFR mutations; two G719A, three G719X and two S768I.

Association between polymorphisms and clinical outcomes

Among the 30 SNPs analyzed, only AKT1 rs2494750G>C was significantly associated with both treatment response and PFS. The remaining 29 SNPs showed weak associations with either response or PFS, or no association at all (Supplementary Table 1). The rs2494750G>C polymorphism was significantly associated with improved treatment response under a codominant model (GG vs. GC vs. CC = 76.4% vs. 89.4% vs. 86.8%; odds ratio [OR] = 1.78; 95% CI: 1.05–2.99; P = 0.031; Table 2). Patients with the rs2494750 CC genotype had significantly longer PFS compared to those with the rs2494750 GG or GC genotypes under a recessive model (CC vs. GG+GC = 20.4 months vs. 16.0 months; HR, 0.62; 95% CI, 0.39–0.97; P = 0.037; Table 2 and Fig. 1). In subgroup analyses, the association between ATK1 rs2494750G>C and both treatment response and PFS was significant only in patients treated with first-generation EGFR-TKIs (Supplementary Table 2). No significant difference in AKT1 rs2494750 genotype distribution was observed between patients with or without the T790M mutation (Supplementary Table 3).

Table 2. Genotypes of rs2494750 and their associations with clinical outcomes.

Gene/ID No.		No. of cases (%)a	Response to chemotherapy				Progression-free survival
			Respondersb	Non-respondersb	OR (95% CI)c	P c	MST (95% CI)	Log-Rank P	HR (95% CI)d	P d
AKT1 rs2494750
	GG	110 (42.1)	84 (76.4)	26 (23.6)	1.00		14.5 (12.2–18.6)		1.00
	GC	113 (43.3)	101 (89.4)	12 (10.6)	2.61 (1.22–5.55)	0.013	16.4 (15.1–18.5)		1.01 (0.74–1.38)	0.952
	CC	38 (14.6)	33 (86.8)	5 (13.2)	2.15 (0.75–6.18)	0.156	20.4 (18.2–30.1)		0.62 (0.39–1.00)	0.052
Dominant					1.57 (1.12–2.22)	0.009	18.2 (16.0–18.7)	0.440	0.95 (0.82–1.10)	0.454
Recessive					1.41 (0.51–3.89)	0.510	16.0 (13.3–18.0)	0.047	0.62 (0.39–0.97)	0.037
Codominant					1.78 (1.05–2.99)	0.031		0.139	0.84 (0.69–1.04)	0.109

Values are presented as number (%).

OR = odds ratio, CI = confidence interval, MST = median survival time (months), HR = hazard ratio.

^aColumn percentage.

^bRow percentage.

^cOR, 95% CI, and their corresponding P values were calculated by multivariate regression analysis, adjusted for age, gender, smoking status, stage, Eastern Cooperative Oncology Group performance status.

^dHR, 95% CI and their corresponding P values were calculated using multivariate Cox proportional hazard models, adjusted for age, gender, smoking status, stage, Eastern Cooperative Oncology Group performance status.

Fig. 1. Kaplan-Meier curves for progression-free survival stratified by AKT1 rs2494750 genotype under a recessive model. A P value was calculated using the multivariate Cox proportional model.

Functional effect of rs2494750 on AKT1 promoter activity

The rs2494750G>C SNP is located in the 5′ untranslated region UTR of AKT1 and may influence promoter activity. To test this, we performed a luciferase reporter assay to investigate the effect of this polymorphism on AKT1 promoter activity. The rs2494750 C allele showed significantly reduced promoter activity compared to the G allele in H522 and A549 lung cancer cell lines (P = 0.033 and P < 0.001, respectively; Fig. 2). Additionally, AKT1 mRNA expression was significantly higher in tumor samples compared to paired non-malignant lung tissues from 109 patients with NSCLC (P = 0.001; Fig. 3A). When stratified by genotype, AKT1 expression was significantly lower in patients with the CC genotype compared to those with the GG or GC genotypes (P = 0.034; Fig. 3B).

Fig. 2. Luciferase assay showing the effect of the rs2494750 G and C alleles on AKT1 promoter activity in H522 and A549 lung cancer cell lines.

Fig. 3. AKT1 mRNA expression. (A) Comparison of AKT1 mRNA expression between 109 paired tumor and adjacent non-malignant lung tissues. (B) AKT1 mRNA expression stratified by rs2494750 genotypes.

DISCUSSION

This study investigated the association between polymorphisms in EGFR pathway–related genes and clinical outcomes in advanced NSCLC patients treated with EGFR-TKIs as first-line therapy. Among the 30 analyzed SNPs, AKT1 rs2494750G>C was significantly associated with better chemotherapy response and prolonged PFS. Functional assays further demonstrated that this SNP modulates AKT1 expression.

Protein kinases are key regulators of cellular processes such as signaling, metabolism, proliferation, survival, and migration. The phosphoinositide 3-kinase (PI3K)-AKT signaling pathway is one of the most frequently activated pathways in human cancers.16,17 AKT, also known as protein kinase B, is a serine/threonine kinase with three isoforms (AKT1, AKT2, and AKT3).18 Hyperactivation of AKT has been observed across multiple cancer types,19,20,21,22 as is associated with tumor progression, metastasis, and treatment resistance.23,24,25 Therefore, the development of targeted therapies against AKT has been a major focus of precision oncology.26,27,28 In lung cancer, particularly in EGFR-mutant subtypes, AKT activation is frequently observed,29,30 and has been linked to resistance against EGFR-TKIs.30,31

Moreover, genetic variants in AKT are associated with susceptibility to various cancer types.32,33,34 Dysregulation in the PI3K-AKT signaling pathway can affect cancer proliferation, invasion, metastasis, and drug resistance.35 Alterations in the PI3K-AKT signaling may influence apoptosis, angiogenesis, which may have an impact on cancer prognosis.36 Our study found that the AKT1 rs2494750G>C polymorphism, located in the 5′ UTR of the gene, was significantly associated with improved chemotherapy response and PFS. Sequence alignment predicts this region to be a transcription factor binding site, and may influence AKT1 transcription and translation. Functional studies confirmed that the rs2494750 C allele exhibited significantly reduced level of AKT1 activation compared to the G allele in H522 and A549 lung cancer cell lines (Fig. 2). Furthermore, AKT1 expression was significantly lower in tumor samples with the CC genotype compared to GG or GC genotypes (Fig. 3B). Higher AKT1 expression in tumor tissue compared to the normal tissue suggests that AKT1 plays a role in the development of cancer, while reduced AKT1 levels in established tumors may be associated with improved prognosis. Accordingly, the AKT1 rs2494750 G to C substitution may modulate AKT1 expression, potentially affecting tumor metabolism, proliferation, or apoptosis, and thereby influencing the prognosis of lung cancer patients. These results are supported by findings reported by Lee et al.37 that inhibiting siRNA-mediated AKT1 inhibition in NSCLC cells reduced cancer cell growth and migration and enhanced apoptosis in response to cisplatin treatment. Similarly, FitzGerald et al.38 found that AKT1 rs2494750G>C polymorphism was associated with improved prostate cancer–specific survival.

In our study, AKT1 rs2494750G>C was significantly associated with improved chemotherapy response and prolonged PFS, but not with overall survival (Supplementary Table 4). This discrepancy may be attributed to the variability in overall survival among patients treated with EGFR-TKIs, which can depend on resistance mechanisms, particularly the emergence of the T790M mutation, and the use of third-generation EGFR-TKIs or subsequent lines of therapy. Subgroup analysis revealed a significant association between AKT1 rs2494750G>C and both response to chemotherapy and PFS in patients with first-generation EGFR-TKIs, but not in those treated with second-generation agents (Supplementary Table 2). This may be due to the limited sample size in the second-generation EGFR-TKI group (n = 100) compared to the first-generation group (n = 166), reducing statistical power. Moreover, the potential role of AKT1 rs2494750G>C in patients treated with third-generation EGFR-TKIs (e.g., osimertinib and lazertinib) remains unclear, as these drugs were not included in this study due to their unavailability as first-line treatments during the study period. Further research is warranted to assess the prognostic and predictive value of AKT1 rs2494750G>C in patients receiving third-generation EGFR-TKIs.

Additionally, although this study focused on EGFR-TKI therapy, AKT1 rs2494750G>C may also influence the efficacy of other treatment modalities such as conventional chemotherapy or immunotherapy, or may serve as an independent prognostic biomarker for lung cancer. To establish this, further investigations in cohorts receiving non-EGFR-TKI therapies as first-line treatment are needed.

In summary, our study identified AKT1 rs2494750G>C as a potential predictive biomarker for improved response and PFS in patients with NSCLC treated with EGFR-TKIs as first-line therapy. Functional analyses demonstrated that this polymorphism may impact AKT1 promoter activity and gene expression, potentially influencing clinical outcomes.

SUPPLEMENTARY MATERIALS

Supplementary Table 1

List of analyzed single nucleotide polymorphisms

Supplementary Table 2

Genotypes of rs2494750 and their associations with clinical outcomes by EGFR-TKI generation

Supplementary Table 3

Genotypes of rs2494750 according to T790M mutation status

Supplementary Table 4

Overall survival according to rs2949750 genotype