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. Author manuscript; available in PMC: 2012 Jan 1.
Published in final edited form as: Lung Cancer. 2010 May 5;71(1):82–88. doi: 10.1016/j.lungcan.2010.04.008

PI3K/PTEN/AKT/mTOR Pathway Genetic Variation Predicts Toxicity and Distant Progression in Lung Cancer Patients Receiving Platinum-based Chemotherapy

Xia Pu 1,*, Michelle AT Hildebrandt 1,*, Charles Lu 2, Jie Lin 1, David J Stewart 2, Yuanqing Ye 1, Jian Gu 1, Margaret R Spitz 1, Xifeng Wu 1
PMCID: PMC2952281  NIHMSID: NIHMS204291  PMID: 20447721

Summary

Non-small cell lung cancer (NSCLC) is still the leading cause of cancer-related deaths. The effect of the PI3K/PTEN/AKT/mTOR signaling pathway on cancer treatment, including NSCLC, has been well documented. In this study, we analyzed associations between genetic variations within this pathway and clinical outcomes following platinum-based chemotherapy in 168 patients with stage IIIB (wet) or stage IV NSCLC. Sixteen tagging SNPs in five core genes (PIK3CA, PTEN, AKT1, AKT2, and FRAP1) of this pathway and identified SNPs associated with development of toxicity and disease progression. We observed significantly increased toxicity for patients with PIK3CA:rs2699887 (OR: 3.86, 95% CI: 1.08 – 13.82). In contrast, a SNP in PTEN was associated with significantly reduced risk for chemotherapeutic toxicity (OR: 0.44, 95% CI: 0.20 - 0.95). We identified three SNPs in AKT1 resulting in significantly decreased risks of distant progression in patients carrying at least one variant allele with HRs of 0.66 (95% CI: 0.45 - 0.97), 0.52 (95% CI: 0.35 - 0.77), and 0.62 (95% CI: 0.42 - 0.91) for rs3803304, rs2498804, and rs1130214, respectively. Furthermore, these same variants conferred nearly two-fold increased progression-free survival times. The current study provides evidence that genetic variations within the PI3K/PTEN/AKT/mTOR signaling pathway are associated with variation in clinical outcomes of NSCLC patients. With further validation, our findings may provide additional biomarkers for customized treatment of platinum-based chemotherapy for NSCLC.

Keywords: lung cancer, chemotherapy, platinum-agents, AKT, clinical outcomes

Introduction

Lung cancer is the leading cause of cancer mortality in the United States with over 160,000 deaths estimated in 2009 [1]. Approximately 80% of lung cancer cases are non-small cell lung cancer (NSCLC) and of these, a majority present with advanced stage [2]. The prognosis for these patients is poor with few options for treatment – including chemotherapy and radiation [3]. Because of this, there is a need for better, and more individualized treatment options for advanced NSCLC.

Platinum-based chemotherapeutic agents, such as cisplatin and carboplatin, are used to treat various types of cancers including lung cancer. Unfortunately, although platinum-based combination chemotherapy has enhanced overall survival and quality of life for lung cancer patients, the 1-year survival rate is still only 29% [4]. The major hurdles in the use of platinum agents are the development of chemoresistance and severe side effects [5, 6]. The most common side effects include ototoxicity, neuropathy, nephrotoxicity, and myelosuppression. These effects are thought to be caused by increased production of reactive oxygen species and apoptosis in sensitive tissues. Several factors are known to influence a patient's response to therapy, including age, ethnicity, stage of disease, performance status, and co-morbidities. However, a patient's genetic background may also play an important role in modulating response to therapy. Therefore, one strategy to enhance the effectiveness of platinum-based treatment of NSCLC while avoiding adverse events is to gain a better understanding of the influence of genetic variations on the clinical outcome of patients.

Platinum-containing agents are cytotoxic through the creation of platinum-DNA crosslinks and the induction of cell cycle arrest and ultimately apoptosis if not properly repaired [7]. Several pathways are involved in this process, including the PI3K/PTEN/AKT/mTOR pathway that is responsible for balancing cell survival and apoptosis [8, 9]. This pathway is activated in various cancer types and plays a role in the development of chemoresistance to platinum-based chemotherapy [10-14]. This pathway is complex; however, the core components include PI3K (phosphoinositide-3-kinase), PTEN (phosphatase and tensin homolog), AKT (v-akt murine thymoma viral oncogene homolog) and mTOR (mammalian target of rapamycin). Genetic variations in the genes encoding these important molecules may modulate signaling through this pathway and result in variation in the development of toxicity or clinical outcomes following platinum-based therapy.

Genetic variations within the PI3K/PTEN/AKT/mTOR have recently been reported to modulate clinical outcomes in esophageal cancer [15]. Because of the variation in response to platinum-based chemotherapy in NSCLC patients, there is a need for efficient biomarkers to predict who will benefit from the chemotherapy while avoiding the development of unnecessary adverse events. In the current study, we set out to determine the association between genetic variations in AKT1, AKT2, PIK3CA (catalytic subunit of PI3K), PTEN, and FRAP1 (encoding for mTOR) with development of toxicity and disease progression in NSCLC patients treated with platinum-compounds.

Materials and Methods

Patient Population

All of the patients were selected from an ongoing epidemiology lung cancer study. The patients included in this analysis were enrolled from 1995 to 2004 and were newly diagnosed, histological confirmed NSCLC cases treated with primary platinum-based (carboplatin or cisplatin) combination chemotherapy at the University of Texas M. D. Anderson Cancer Center. We further restricted the analysis to non-Hispanic Caucasian patients with stage IIIB (wet) or IV NSCLC. All the subjects signed a consent form and the study was approved by the Institutional Review Board of The University of Texas M. D. Anderson Cancer Center. Peripheral blood specimens for genetic analysis were collected from each patient at the time of diagnosis prior to chemotherapy or radiotherapy treatment.

Epidemiological and Clinical Data Collection

Epidemiological data was collected using a structured questionnaire including demographic characteristics, family history of cancer, smoking history, and alcohol consumption. We defined an individual who had never smoked or had smoked no more than 100 cigarettes in his or her lifetime as never smoker; an individual who had quit smoking at least one year before diagnosis was defined as former smoker; a person who currently smoking or had quit smoking less than one year prior to diagnosis was defined as current & recent quitter. Clinical and follow-up information were abstracted from medical records. Performance status was determined based on the ECOG scale prior to treatment [16]. Complete blood counts were performed prior to each treatment based on M. D. Anderson's practice guidelines. Toxicities included in this study were neutropenia, neutropenic fever, anemia, thromobocytopenia, leukocytopenia, and nephrotoxicity that occurred during any of the primary chemotherapy treatment cycles [17]. Time to progression was measured from date of first treatment to date of progression of disease, last follow-up or death. Local progression was limited to primary tumor site and regional lymph nodes while distant progression was defined as a metastasis located outside of the thoracic cavity or in the other lung.

SNP Selection and Genotyping

Genomic DNA was extracted from peripheral blood lymphocytes using the Human Whole Blood Genomic DNA Extraction Kit (Qiagen, Valencia, CA). We selected tagging SNPs from 5-kb flanking and within the gene regions of five genes: AKT1, AKT2, PIK3CA, PTEN and FRAP1 (mTOR). Sixteen tagging SNPs were identified by the tagger algorithm with a cut-off value of r2 = 0.8 and a MAF (minor allele frequency) = 0.1-0.35, based on the allele frequencies from CEPH samples that were genotyped by the International HapMap Project. For each SNP, genotyping was performed using the TaqMan Pre-Designed SNP Genotyping Assays (Applied Biosystems, Foster City, CA) following manufacturer's instructions. End-point fluorescence was read by ABI Prism 7900HT Sequence Detection System with genotype calls being made with SDS software (SDS 2.1, Applied Biosystems, Foster City, CA).

Statistical Analysis

For toxicity risk, unconditional multivariate logistic regression analysis was performed to estimate adjusted odds ratios (ORs) along with the corresponding 95% confident intervals (95% CIs) for each SNP. The Cox proportional hazard model was used to assess the effect of individual SNPs on progression (local and distant)-free survival. Hazard ratios (HRs) and 95% CIs were estimated by fitting the Cox model while adjusting for age, gender, clinical stage, performance status, and smoking status. Kaplan-Meier curves and log-rank tests were used to assess progression-free survival time. All statistical analyses were performed using STATA software (version 10, STATA Corporation, College Station, TX) with P < 0.05 being considered statistically significant. The Benjamini-Hochberg method was used to correct for multiple comparisons based on an false discovery rate (FDR) of 10% [18].

Results

Patient Characteristics

Our patient population consisted of 168 non-Hispanic Caucasian patients with advanced stage NSCLC who received primary platinum-based chemotherapy (Table 1). A majority were treated with carboplatin-based treatment (88.7%) compared to cisplatin-based (11.3%) with an average number of treatment cycles of 4.5. Seventeen (10.1%) presented with stage IIIB (wet) and 151 (89.9%) with stage IV disease. The mean age was 58.1 years (SD: 11.08, range: 28-81 years). There were 94 men (56%) and 74 women (44%). There were 48 (28.6%) never smokers, 58 (34.5%) former smokers, and 62 (36.9%) current smokers or recent quitters. The median time enrolled in the study was 10.94 months with an overall median survival time of 10.92 months.

Table 1. Patient Characteristics.

Characteristic # of Patients %
Total 168
Age
Mean 58.1
SD 11.08
Range 28-81
Sex
Male 94 56
Female 74 44
Clinical Stage
Stage IIIB (wet) 17 10.1
Stage IV 151 89.9
Smoking Status
Never 48 28.6
Former 58 34.5
Current & Recent Quitter 62 36.9
Performance Status
0 38 22.6
1 109 64.9
2-4 21 12.5
Treatment Regimen
Carboplatin-based 149 88.7
Cisplatin-based 19 11.3
Local Progression
No 102 60.7
Yes 66 39.3
Distant Progression
No 51 30.4
Yes 117 69.6+
Toxicity
No 100 59.5
Yes 68 40.5
Histology
Adenocarcinoma 102 60.7
Non-small cell carcinoma 23 13.7
Squamous cell cacinoma 24 14.3
Other NSCLC 19 11.3

Associations between SNPs and Risk of Toxicity

We analyzed the 16 SNPs for associations with toxicity due to platinum-based chemotherapy. Two SNPs were found to be significantly associated with toxicity (Table 2). PTEN:rs2299939 showed a negative association with patients carrying at least one variant allele having a 56% reduced risk of developing a severe side effect (OR: 0.44, 95% CI: 0.20 - 0.95, P = 0.036). In contrast, patients who were homozygous for the PIK3CA:rs2699887 variant exhibited a significantly increased risk of toxicity (OR: 3.86, 95% CI: 1.08 - 13.82, P = 0.038). Both of these associations remained significant after correct for multiple comparisons at an FDR of 10%. No other SNPs were significantly associated with toxicity risk. Because cisplatin and carboplatin-based treatment regimens differ slightly in toxicity profiles, we stratified our analysis by platinum agent. The results in the carboplatin treatment group were similar to the full population (data not shown). Due to small sample size, we were not able to perform stratified analysis in the cisplatin group.

Table 2. PI3K/PTEN/AKT/mTOR pathway genotypes and toxicity.

SNP and Genotype Toxicity

Yes No OR* 95% CI P value
AKT1:rs3803304 62 93
 CC 26 49 1.00
 CG 30 37 1.43 0.71 to 2.86 0.317
 GG 6 7 1.67 0.50 to 5.60 0.408
 CG + GG 1.46 0.75 to 2.84 0.261

AKT1:rs2494738 65 99
 AA 53 81 1.00
 AG 11 18
 GG 1 0
 AG+GG 1.04 0.45 to 2.42 0.921

AKT1:rs2498804 66 97
 GG 21 41 1.00
 GT 37 46 1.45 0.71 to 2.95 0.305
 TT 8 10 1.65 0.55 to 4.96 0.373
 GT + TT 1.48 0.75 to 2.94 0.257

AKT1:rs1130214 66 97
 GG 30 54 1.00
 GT 29 38 1.38 0.69 to 2.77 0.364
 TT 7 5 2.92 0.80 to 10.67 0.105
 GT + TT 1.55 0.79 to 3.01 0.200

AKT2:rs892119 65 97
 AA 40 72 1.00
 AG 24 23 2.06 1.00 to 4.27 0.051
 GG 1 2 1.00 0.08 to 12.26 1.000
 AG + GG 1.97 0.97 to 4.02 0.061

AKT2:rs8100018 63 95
 CC 39 46 1.00
 CG 20 39 0.54 0.26 to 1.12 0.096
 GG 4 10 0.42 0.12 to 1.52 0.186
 CG + GG 0.51 0.26 to 1.02 0.056

FRAP1:rs11121704 66 97
 CC 32 56 1.00
 CT 28 36 1.31 0.65 to 2.62 0.448
 TT 6 5 2.79 0.73 to 10.61 0.133
 CT + TT 1.47 0.76 to 2.84 0.253

FRAP1:rs2295080 66 98
 GG 27 49 1.00
 GT 32 42 1.40 0.71 to 2.76 0.333
 TT 7 7 2.18 0.66 to 7.20 0.202
 GT + TT 1.50 0.78 to 2.88 0.224

PIK3CA:rs7651265 66 98
 AA 58 76 1.00
 AG 8 21
 GG 0 1
 AG + GG 0.43 0.17 to 1.06 0.065

PIK3CA:rs7640662 65 99
 CC 45 74 1.00
 CG 17 24 1.05 0.49 to 2.25 0.909
 GG 3 1 4.52 0.44 to 46.59 0.205
 CG + GG 1.19 0.57 to 2.48 0.649

PIK3CA:rs7621329 65 99
 CC 47 63 1.00
 CT 18 30
 TT 0 6
 CT+TT 0.63 0.31 to 1.28 0.202

PIK3CA:rs6443624 66 99
 AA 42 55 1.00
 AC 24 36
 CC 0 8
 AC + CC 0.71 0.37 to 1.37 0.310

PIK3CA:r52699887 65 98
 AA 34 56 1.00
 AG 21 38 0.93 0.46 to 1.89 0.845
 GG 10 4 3.86 1.08 to 13.82 0.038
 AG + GG 1.21 0.62 to 2.34 0.576

PTEN:rs2299939 64 93
 AA 51 58 1.00
 AC 13 29
 CC 0 6
 AC + CC 0.44 0.20 to 0.95 0.036

PTEN:rs12569998 66 99
 GG 46 75 1.00
 GT 19 23 1.40 0.66 to 2.97 0.386
 TT 1 1 4.48 0.20 to 100.80 0.346
 GT + TT 1.45 0.69 to 3.06 0.323

PTEN:rs12357281 66 99
 CC 61 86 1.00
 CG 5 12
 GG 0 1
 CG + GG 0.54 0.17 to 1.66 0.281
*

adjusted for age, gender, clinical stage, performance status, and smoking status

Associations between SNPs and Progression Risk and Progression-free Survival

We next analyzed the association between SNPs and distant progression. None of the variants were associated with local progression (Table 3), but three of the 16 SNPs were associated with distant progression risk. These SNPs (rs3803304, rs2498804, rs1130214) all tagged genetic variation in AKT1. Patients carrying at least one variant allele exhibited similarly reduced risks with HRs of 0.66 (95% CI: 0.45 - 0.97, P = 0.035), 0.52 (95% CI: 0.35 - 0.77, P = 0.001) and 0.62 (95% CI: 0.42 - 0.91, P = 0.016), respectively. Although only AKT1:rs2498804 remained at an FDR of 10%, as shown in Figure 1, all three of these variants conferred a nearly two-fold prolonged progression-free time, from 4.84 to 7.30 months for rs3803304 (P = 0.022), 4.11 to 8.29 months for rs2498804 (P = 0.0005), and 5.3 to 8.42 months for rs1130214 (P = 0.028). Table 4 shows the linkage disequilibrium (LD) between the four AKT1 SNPs included in this analysis. Of the three identified as significantly associated with risk, only rs3803304 and rs2498804 exhibited modest LD (r2=0.75), with rs1130214 not sharing any LD with these two SNPs (r2=0.00 and 0.16, respectively). Similar to the toxicity analysis, the results in the carboplatin treatment group were comparable to the full population (data not shown).

Table 3. PI3K/PTEN/AK17mTOR pathway genotypes and disease progression.

SNP and Genotype Local Progression Distant Progression

Yes No HR* 95% CI P value Yes No HR* 95% CI P value
AKT1:rs3803304 58 97 112 43
 CC 28 47 1.00 57 18 1.00
 CG 22 45 0.80 0.45 to 1.42 0.448 44 23 0.61 0.41 to 0.92 0.017
 GG 8 5 1.59 0.71 to 3.54 0.261 11 2 0.97 0.50 to 1.86 0.921
 CG + GG 0.93 0.55 to 1.57 0.790 0.66 045 to 0.97 0.035

AKT1:rs2494738 65 99 117 47
 AA 52 82 1.00 96 38 1.00
 AG 12 17 0.94 0.49 to 1.79 0.847 20 9
 GG 1 0 1 0
 AG+GG 0.99 0.53 to 1.86 0.985 0.80 0.49 to 1.29 0.357

AKT1:rs2498804 64 99 116 47
 GG 24 38 1.00 49 13 1.00
 GT 30 53 0.80 0.46 to 1.40 0.432 52 31 0.47 0.31 to 0.72 < 0.001
 TT 10 8 1.26 0.60 to 2.68 0.540 15 3 0.76 0.42 to 1.37 0.357
 GT + TT 0.89 0.53 to 1.50 0.661 0.52 0.35 to 0.77 0.001

AKT1:rs1130214 64 99 116 47
 GG 35 49 1.00 63 21 1.00
 GT 24 43 0.74 0.43 to 1.27 0.275 45 22 0.60 0.40 to 0.90 0.013
 TT 5 7 0.91 0.35 to 2.36 0.840 8 4 0.77 0.36 to 1.63 0.492
 GT+TT 0.76 0.45 to 1.28 0.305 0.62 0.42 to 0.91 0.016

AKT2:rs892119 65 97 114 48
 AA 46 66 1.00 80 32 1.00
 AG 18 29 0.93 0.53 to 1.63 0.788 32 15 0.83 0.54 to 1.25 0.370
 GG 1 2 0.97 0.13 to 7.26 0.973 2 1 0.68 0.16 to 2.84 0.595
 AG + GG 0.93 0.53 to 1.61 0.790 0.82 0.54 to 1.23 0.328

AKT2:rs8100018 60 98 110 48
 CC 30 55 1.00 57 28 1.00
 CG 24 35 1.17 0.67 to 2.02 0.588 43 16 1.31 0.86 to 1.93 0.208
 GG 6 8 1.09 0.43 to 2.76 0.856 10 4 1.30 0.66 to 2.56 0.456
 CG + GG 1.15 0.68 to 1.93 0.599 1.30 0.88 to 1.92 0.181

FRAP1:rs11121704 65 98 115 48
 CC 34 54 1.00 64 24 1.00
 CT 26 38 1.14 0.67 to 1.94 0.622 43 21 0.73 0.49 to 1.10 0.130
 TT 5 6 1.34 0.51 to 3.57 0.553 8 3 0.81 0.38 to 1.74 0.593
 CT + TT 1.17 0.71 to 1.94 0.528 0.75 0.51 to 1.09 0.129

FRAP1:rs2295080 63 101 117 47
 GG 26 50 1.00 55 21 1.00
 GT 30 44 1.21 0.71 to 2.06 0.486 51 23 0.77 0.52 to 1.13 0.186
 TT 7 7 1.70 0.72 to 4.03 0.224 11 3 0.91 0.47 to 1.77 0.784
 GT + TT 1.28 0.77 to 2.12 0.343 0.79 0.55 to1.14 0.215

PIK3CA:rs7651265 65 99 116 48
 AA 53 81 1.00 94 40 1.00
 AG 11 18 0.96 0.50 to 1.85 0.901 21 8 0.98 0.60 to 1.58 0.919
 GG 1 0 1 0
 AG + GG 1.04 0.55 to 1.96 0.902 1.02 0.64 to 1.64 0.921

PIK3CA:rs7640662 65 99 116 48
 CC 46 73 1.00 83 36 1.00
 CG 16 25 1.1 0.60 to 2.02 0.753 31 10 1.06 0.69 to 1.64 0.791
 GG 3 1 2.29 0.67 to 7.81 0.186 2 2 0.48 0.11 to 2.01 0.312
 CG + GG 1.20 0.68 to 2.12 0.538 0.99 0.65 to 1.52 0.974

PIK3CA:rs7621329 65 99 117 47
 CC 44 66 1.00 79 31 1.00
 CT 17 31 0.71 0.40 to 1.26 0.238 34 14 0.76 0.51 to 1.15 0.197
 TT 4 2 1.95 0.68 to 5.61 0.213 4 2 0.77 0.27 to 2.21 0.629
 CT + TT 0.82 0.48 to 1.39 0.460 0.76 0.51 to 1.14 0.183

PIK3CA:rs6443624 65 100 117 48
 AA 38 59 1.00 69 28 1.00
 AC 22 38 0.81 0.47 to 1.39 0.439 44 16 0.88 0.59 to 1.30 0.516
 CC 5 3 1.66 0.63 to 4.39 0.307 4 4 0.58 0.20 to 1.65 0.307
 AC + CC 0.91 0.55 to 1.51 0.705 0.84 0.58 to 1.22 0.360

PIK3CA:rs2699887 65 98 115 48
 AA 34 56 1.00 67 23 1.00
 AG 25 34 1.28 0.76 to 2.18 0.353 37 22 0.77 0.51 to 1.17 0.225
 GG 6 8 1.17 0.47 to 2.89 0.733 11 3 0.92 0.47 to 1.80 0.800
 AG + GG 1.26 0.77 to 2.08 0.362 0.80 0.54 to 1.18 0.258

PTEN:rs2299939 61 96 110 47
 AA 45 64 1.00 77 32 1.00
 AC 15 27 0.78 0.42 to 1.43 0.416 31 11 0.94 0.61 to 1.44 0.770
 CC 1 5 1.54 0.20 to 11.82 0.681 2 4 1.16 0.28 to 4.80 0.839
 AC + CC 0.80 0.44 to 1.45 0.466 0.95 0.62 to 1.45 0.806

PTEN:rs12569998 65 100 117 48
 GG 48 73 1.00 83 38 1.00
 GT 15 27 1.10 0.60 to 2.02 0.761 32 10 1.34 0.86 to 2.07 0.195
 TT 2 0 2 0
 GT + TT 1.23 0.69 to 2.19 0.492 1.40 0.91 to 2.14 0.127

PTEN:rs12357281 65 100 117 48
 CC 56 91 1.00 105 42 1.00
 CG 8 9 0.94 0.42 to 2.07 0.876 11 6 0.98 0.51 to 1.88 0.945
 GG 1 0 1 0 1.10 0.14 to 8.41 0.929
 CG + GG 1.08 0.51 to 2.29 0.848 0.99 0.53 to 1.84 0.969
*

adjusted for age, gender, clinical stage, performance status, and smoking status

Fig 1.

Fig 1

Kaplan-Meier curves of distant progression-free survival times in lung cancer patients by AKT1 SNPs A) rs3803304, B) rs2498804, and C) rs1130214. The numbers in parentheses are the numbers of patients with progression over the total number of patients by genotype. MST = median time to progression in months.

Table 4. Linkage disequilibrium (r2) between AKT1 SNPs.

AKT1:rs3803304 AKT1:rs2498804 AKT1:rs1130214
AKT1:rs2498804 0.75
AKT1:rs1130214 0.00 0.16
AKT1: rs2494738 0.11 0.12 0.00

Discussion

Lung cancer has remained the leading cause for cancer-related mortality in the United States [1]. A growing body of evidence suggests that lung tumors activate certain cellular signaling pathways to become invasive and resistant to platinum-based chemotherapy [19]. The deregulation of the PI3K/PTEN/AKT/mTOR pathway in human cancers has been extensively studied over the past few years [20-23]. Furthermore, this pathway has been reported to be associated with response to platinum-based chemotherapy treatment in lung cancer cell lines [13, 24]. In this study, we determined whether common variations in genes in this pathway (PIK3CA, PTEN, AKT1, AKT2, and FRAP1) were able to modulate the development of toxicity and clinical outcomes of NSCLC patients receiving platinum-based chemotherapy.

Although platinum-based agents are successful in treating several types of cancer, treatment is often associated with adverse side effects, including myleosuppression, ototoxicity, nephrotoxicity, and peripheral neurotoxicity due to increased apoptosis in cells with platinum-related DNA damage [5, 6]. Cisplatin and carboplatin are the most commonly used platinum-containing chemotherapeutic agents in NSCLC. Cisplatin-based therapy has been found to provide a better survival benefit for NSCLC patients, but it is associated with more severe toxicity compared to carboplatin-based therapy. However, treatment with either of these agents is hindered by development of severe toxicities and chemoresistance [25].

Since the PI3K/PTEN/AKT/mTOR pathway is involved in the balance between cell survival and death, genetic variation in the core components of this pathway may shift this balance, resulting in altered toxicity risk. In the current study, a genetic variation (rs2299939) in the negative regulator of this pathway, PTEN, was associated with a 54% decreased risk of toxicity. PTEN protein expression is often lost in NSCLC, but this loss is rarely due to inactivating mutations, loss of heterozygosity, or hypermethlyation of the gene [26-30]. Our results suggest that genetic variations in PTEN may modulate PTEN activity. Specifically, since rs2299939 is associated with a decrease in toxicity, we speculate that this SNP, or another functional SNP that is tagged by this variant, may decrease the expression of PTEN and hence the inhibitory effect of PTEN on signaling through this pathway. Further investigation will be needed to understand the effect of this SNP on PTEN function. In contrast, patients carrying at least one variant rs2699887 allele in PIK3CA, the catalytic domain for PI3K, had a nearly 4-fold increased risk of toxicity. PIK3CA is a known oncogene and is responsible for initiating signaling through this pathway activating cell survival signals [31]. Decreased PI3K activity would result increased apoptosis in sensitive, non-cancer cells causing an increase in toxic side-effects. Therefore, the genetic variation tagged by the PIK3CA:rs2699887 SNP would likely cause an decrease in PI3K signaling. The contrasting results of PTEN and PIK3CA genetic variation have biological plausibility based on their function in regulating signaling through this pathway.

The serine-threonine kinase AKT is a central node in cell signaling that regulates several processes, including cell survival, proliferation, and protein synthesis [8]. AKT activation is a common molecular alteration during carcinogenesis, and it has been reported that AKT is constitutively activated in NSCLC resulting in cell survival by blocking induction of apoptosis [32]. In addition, forced expression of AKT1 was found to be sufficient to regulate cisplatin resistance in cultured lung cancer cells [13]. We found that three AKT1 tagging SNPs decreased risk for distant disease progression. These three SNPs do not share a high degree of linkage disequilibrium, suggesting the presence of at least two independent causal variants. The directionality of the effect indicates that the functional variants all diminish AKT1 activity causing decreased signaling through this pathway, and thus a reduction in cell survival signals. However, since the variants genotyped in this study were tagging SNPs, we are unable to identify the causative SNP and mechanism responsible. Future studies are clearly warranted in this regard.

Platinum-based chemotherapy is still the core treatment for NSCLC patients. Although knowledge and chemotherapeutic methods for treating NSCLC keep evolving, the survival rate has not improved notably with chemotherapy. New biologic insight and biomarkers are desired to find new approaches for treating patients with advanced disease. In the current study, although based on a small sample size, the homogenous nature of the treatment regimens the patients received allowed us to identify genetic variations within the PI3K/PTEN/AKT/mTOR signaling pathway that are associated with variation in development of toxicity and clinical outcomes for NSCLC patients. With validation, our findings may provide additional biomarkers for individualized treatment in order to enhance the efficiency and reduce toxicity during chemotherapy with platinum-based agents for NSCLC.

Acknowledgments

This research was supported in part, by National Cancer Institute (NCI) grants R01 CA111646 P50 CA070907, and R01 CA055769. MATH is supported by an NCI Cancer Prevention Research Fellowship training grant R25T CA57730. The study sponsors have no involvement in any aspects of the preparation of this manuscript.

Footnotes

Conflict of Interest: The authors declare no conflicts of interest.

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