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Prevalence and spectrum of AKT1, PIK3CA, PTEN and TP53 somatic mutations in Chinese breast cancer patients

  • Guoli Li,

    Roles Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

    Affiliation School of Life Sciences, Central South University, Changsha, Hunan, China

  • Xinwu Guo,

    Roles Data curation, Formal analysis, Software, Writing – review & editing

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Ming Chen,

    Roles Data curation, Formal analysis, Software

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Lili Tang,

    Roles Resources

    Affiliation Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China

  • Hui Jiang,

    Roles Data curation

    Affiliation School of Life Sciences, Central South University, Changsha, Hunan, China

  • Julia X. Day,

    Roles Data curation

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Yueliang Xie,

    Roles Data curation

    Affiliation School of Life Sciences, Central South University, Changsha, Hunan, China

  • Limin Peng,

    Roles Formal analysis, Software

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Xunxun Xu,

    Roles Data curation

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Jinliang Li,

    Roles Formal analysis, Software

    Affiliation Sanway Gene Technology Inc., Changsha, Hunan, China

  • Shouman Wang,

    Roles Resources

    Affiliation Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China

  • Zhi Xiao,

    Roles Resources

    Affiliation Department of Breast Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, China

  • Lizhong Dai,

    Roles Conceptualization, Data curation, Supervision

    Affiliations Sanway Gene Technology Inc., Changsha, Hunan, China, Research Center for Technologies in Nucleic Acid-Based Diagnostics, Changsha, Hunan, China, Research Center for Technologies in Nucleic Acid-Based Diagnostics and Therapeutics, Changsha, Hunan, China

  • Jun Wang

    Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Visualization, Writing – review & editing

    junwang@csu.edu.cn

    Affiliations School of Life Sciences, Central South University, Changsha, Hunan, China, Sanway Gene Technology Inc., Changsha, Hunan, China

Prevalence and spectrum of AKT1, PIK3CA, PTEN and TP53 somatic mutations in Chinese breast cancer patients

  • Guoli Li, 
  • Xinwu Guo, 
  • Ming Chen, 
  • Lili Tang, 
  • Hui Jiang, 
  • Julia X. Day, 
  • Yueliang Xie, 
  • Limin Peng, 
  • Xunxun Xu, 
  • Jinliang Li
PLOS
x

Abstract

Breast cancer, one of the most frequently occurring cancers worldwide, is the leading cause of cancer-related death among women. AKT1, PIK3CA, PTEN and TP53 mutations were common observed in breast cancer representing potential clinical biomarkers for cancer classification and treatment. A comprehensive knowledge of AKT1, PIK3CA, PTEN and TP53 mutations in breast cancer was still insufficient in Chinese population. In this study, the complete coding regions and exon-intron boundaries of AKT1, PIK3CA, PTEN and TP53 genes were sequenced in paired breast tumor and normal tissues from 313 Chinese breast cancer patients using microfluidic PCR-based target enrichment and next-generation sequencing technology. Total 120 somatic mutations were identified in 190 of the 313 patients (60.7%), with the mutation frequency of AKT1 as 3.2%, PIK3CA as 36.4%, PTEN as 4.8%, and TP53 as 33.9%. Among these mutations, 1 in PIK3CA (p.I69N), 3 in PTEN (p.K62X, c.635-12_636delTTAACCATGCAGAT and p.N340IfsTer4) and 5 in TP53 (p.Q136AfsTer5, p.K139_P142del, p.Y234dup, p.V274LfsTer31 and p.N310TfsTer35) were novel. Notably, PIK3CA somatic mutations were significantly associated with ER-positive or PR-positive tumors. TP53 somatic mutations were significantly associated with ER-negative, PR-negative, HER2-positive, BRCA1 mutation, Ki67 high expression and basal-like tumors. Our findings provided a comprehensive mutation profiling of AKT1, PIK3CA, PTEN and TP53 genes in Chinese breast cancer patients, which have potential implications in clinical management.

Introduction

Breast cancer is the most common cancer types and the leading cause of cancer mortality in females in the world [1]. It was estimated that approximately 278,800 new breast cancer cases with 64,600 deaths occurred in China in 2013 [2]. It is well known that cancer progression is driven by mutations in cancer genome [3]. Somatic mutations in AKT1, PIK3CA PTEN and TP53 genes were found at high frequency in breast cancer, with PIK3CA as 26.4%, TP53 as 24.7%, PTEN as 3.8% and AKT1 as 2.8% in the Catalogue of Somatic Mutations in Cancer (COSMIC) database [4]. Recent large genomic landscape studies have showed that TP53 and PIK3CA were the two most frequently mutated driver genes in primary breast cancer and the mutation spectrum of these four genes displayed subgroup specificity with great clinical significance in cancer classification and treatment [5, 6]. However, the spectrum of these four gene mutations in breast cancer is still largely unknown in Chinese population. Thus a comprehensive understanding of the prevalence and clinical characteristics of AKT1, PIK3CA, PTEN and TP53 gene mutations in Chinese breast cancer patients is urgently needed.

With the advance of next-generation sequencing (NGS) technologies, mutation analysis has become effective and feasible for routine clinical application in breast cancer [7]. In this study, paired tumor and normal tissues from a cohort of 313 Chinese breast cancer patients were screened for ATK1, PIK3CA, PTEN and TP53 mutations using microfluidic PCR-based target enrichment and NGS technology. Furthermore, clinicopathological characteristics of breast cancer associated with the mutations of these four genes were analyzed in parallel.

Material and methods

Patients and tissue samples

Fresh tumor and paired adjacent normal tissues (located at least 2 cm away from the site of tumor tissue) from 313 primary breast cancer patients were collected at Xiangya Hospital, Central South University from year 2013 to 2015. The clinicopathological characteristics of the 313 patients were summarized in Table 1. All breast specimens were reviewed by experienced pathologists. The breast cancer molecular subtypes were characterized based on the guideline of St Gallen International Expert Consensus (2013) [8]. All of the 313 patients have been tested for BRCA1 and BRCA2 mutations by NGS and validated using Sanger sequencing in our previous study [9]. All the patients in this study were females of Chinese Han population without selection for family history or onset age. We declared that the experiments performed in this study comply with the current laws of the People's Republic of China. This study was approved by the Ethics Committee of Central South University, Changsha, China, and all participants had given written informed consent.

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Table 1. Clinicopathological characteristics of 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.t001

Library preparation and NGS

Genomic DNA of all samples were extracted using the TIANamp Genomic DNA Kit (TianGen Biotech, Beijing, China), and quantified using a Nanodrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). Totally, 60 pairs of primers were designed to amplify the complete coding regions and exon–intron boundaries of target genes, and the primer sequences were displayed in S1 Table. The primers were designed using the on-line design tool, Primer3 (http://bioinfo.ut.ee/primer3/), by following the User Guide of Access ArrayTM System for Illumina Sequencing Systems (Fluidigm, South San Franciso, CA, USA). All primers were validated by single-plex PCR with assessment of PCR products for expected size on agarose gel. The high-throughput target enrichment was performed on the Fluidigm Access Array (Fluidigm, South San Franciso, CA, USA) according to established workflows [911]. Then the target gene libraries were sequenced on an Illumina MiSeq sequencer (SanDiego, CA, USA) using MiSeq Reagent Kit v2 (500 cycles).

Sequencing data analysis and variant annotation

The raw sequencing data were base-called and demultiplexed using MiSeq Reporter v.1.8.1 (Illumina, SanDiego, CA, USA) with default parameters and FASTQ files were generated for downstream data analysis. The adapter sequences and low quality reads were trimmed away from the raw reads using Trimmomatic v.0.32 [12]. Cleaned reads were aligned to the UCSC human reference genome hg19 using the Burrows-Wheeler Alignment tool (BWA) v.0.7.10 [13]. After alignment, the SAMtools (v.1.1) [14] software was applied to convert the alignment files to a sorted, indexed binary alignment map (BAM) format. Base recalibration and realignment around indels was done with the GATK v3.1.1 [15]. Germline genotypes were called by the GATK UnifiedGenotyper (with paired tumor and adjacent normal tissues sample), and somatic mutations were called by MuTect (v.1.1.4) [16] under the High-Confidence mode with default parameter settings. Both tumor and matched normal tissue samples from the same patient were sequenced together in a NGS run. The variants present only in tumor tissue samples were thus classified as somatic mutations. And variants present in both tumor and paired normal tissue samples were classified as germline mutations. We defined the final list of somatic mutations with the following filters: number of reads with the altered base in the tumor ≥10; frequency of the reads with the altered base in the tumor ≥ 5% except for variants that are also reported in COSMIC database; minor allele frequency <0.1% in each of the following publicly available databases: 1000 Genomes (http://www.1000genomes.org/) and Exome Aggregation Consortium (http://exac.broadinstitute.org/). Variants were annotated using ANNOVAR (February, 2016) with the annotate_variation.pl script [17]. This tool mapped variants to RefSeq genes, known variations from dbSNP 138 and annotated the predicted functional consequences of missense variants using two silico tools (SIFT [18] and PolyPhen-2 [19]). Additional clinical variant annotations were obtained from NCBI ClinVar (http://www.ncbi.nlm.nih.gov/clinvar), and COSMIC database (http://cancer.sanger.ac.uk/cosmic). The reference sequences for numbering were based on the NCBI GenBank Database for AKT1 (NM_005163.2 and NP_005154.2), PIK3CA (NM_006218.2 and NP_006209.2), PTEN (NM_000314.4 and NP_000305.3) and TP53 (NM_000546.5 and NP_000537.3). Novel mutations were defined as variants that have neither been previously recorded in dbSNP (http://www.ncbi.nlm.nih.gov/SNP), ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/), 1000 Genomes (http://www.1000genomes.org/), Exome Aggregation Consortium (http://exac.broadinstitute.org/) or COSMIC (http://cancer.sanger.ac.uk/cosmic), nor reported in literatures. In this study, all variants were classified according to the American College of Medical Genetics and Genomics recommendations [20]. Variants resulted in non-functional or truncating-proteins were classified as pathogenic mutations (including stop-gain mutations, frameshift mutations and splice site mutations). In addition, we also considered variants as pathogenic mutations if they were annotated as “pathogenic” in NCBI ClinVar. The annotation and classification of the protein domains of these 4 genes was based on the NCBI’s Conserved Domain Database (CDD) [21].

Statistical analysis

Continuous data were summarized using mean and standard deviation. The difference of age among patients with different gene mutation status was determined by the Wilcoxon Rank Sum test. And χ2 test was used to compare categorical variables between groups across clinicopathological characteristics. Alternatively, Fisher’s exact test was used when χ2 test was violated. The obtained P values were considered statistically significant if the P value is < 0.05. The Holm’s procedure was used to adjust P values for multiple testing [22]. All the computations were performed using the R software (version 3.1.0, http://www.cran.r-project.org).

Results

Detection of mutations by NGS

Microfluidic PCR-based target enrichment and NGS were performed to sequence the entire coding regions and exon-intron boundaries of AKT1, PIK3CA, PTEN and TP53 genes in the cohort of 313 Chinese breast cancer patients. Total 120 somatic mutations were detected in 190 patients (190/313, 60.7%) (Table 2 and S2 Table). The somatic mutation frequency of AKT1, PIK3CA, PTEN and TP53 in this cohort was 3.2% (10/313), 36.4% (114/313), 4.8% (15/313) and 33.9% (106/313), respectively. Similarly, the somatic mutation frequency of these genes reported by TCGA [23] was 2.4%, 35.5%, 3.2% and 35.3%, respectively (Table 2). Notably, one synonymous variant (p.T125T in TP53) was included in this study, because it can lead to alternative splicing as previously reported [24]. In addition, 6 germline mutations were also found (1 in PIK3CA, 2 in PTEN and 3 in TP53) in 6 of the 313 patients (S3 Table). Among these 126 mutations, 53 were considered as pathogenic (42.9%), including 52 somatic mutations and 2 germline mutations (Table 3). All the somatic mutations detected in this study were confirmed in two different NGS runs. In addition, all germline mutations and the somatic mutations with allele fraction ≧20% in tumor tissues were confirmed using Sanger sequencing (S1 and S2 Figs).

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Table 2. Frequencies of somatic mutations in this study compared with TCGA data.

https://doi.org/10.1371/journal.pone.0203495.t002

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Table 3. Pathogenic mutations of AKT1, PIK3CA, PTEN and TP53 genes in the 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.t003

Frequency and spectrum of AKT1, PIK3CA, PTEN and TP53 mutations

In AKT1 gene, total 2 somatic mutations were detected in 10 of 313 patients (3.2%), both of which were missense mutations located in exon 3 within pleckstrin homology (PH) domain of the AKT1 protein. The mutation p.E17K, which occurred in 9 patients (9/10, 90%), and dominated the mutation spectrum of AKT1 (Fig 1A and S2 Table). No germline mutation was found in AKT1.

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Fig 1.

Mutational spectrum of AKT1 (a), PTEN (b), PIK3CA according to molecular subtypes (c-f) and TP53 according to molecular subtypes (g-j). Non-silent somatic mutations mapped to the protein sequence of each genes are shown. Cyan dot indicates missense mutation; Red dot indicates nonsense mutation; Black dot indicates splice site mutation; Green dot indicates frameshift mutation; Brown dot indicates in-frame mutation. The number of dots indicates the number of cases. Protein domains are shown as colored bars: PH, pleckstrin homology domain; HM, hydrophobic motif domain; C2, conserved domain 2; PI3K_p85B, p85 binding domain; PI3K_rbd, Ras-binding domain; PI3Ka, accessory domain; PI3K/PI4K, phosphatidylinositol 3-kinase and phosphatidylinositol 4-kinase domain.

https://doi.org/10.1371/journal.pone.0203495.g001

In PIK3CA gene, total 17 somatic mutations were detected in 114 of the 313 patients (36.4%), which located across 7 different exons (exon 2, 5, 8, 9, 10, 14 and 21) (S2 Table). Notably, 9 patients harbored two mutations of PIK3CA. Exon 10 and 21 were the two hotspot regions within PI3Ka and PI3Kc domain, mutations of which presented in 34 (34/114, 29.8%) and 70 (70/114, 61.4%) of cases, respectively (Fig 1C–1F and S2 Table). Among them, 26 patients had p.E545K mutation and 7 patients had p.E542K mutation in PI3Ka domain (Table 4). Total 52 patients had p.H1047R mutation in PI3Kc domain, and 15 patients had a different p.H1047L mutation at the same spot (Table 4). One novel somatic mutation p.I69N was found in the PI3K_p85B domain (S2 Table). In addition, one germline mutation (p.K733R) was detected in PIK3CA. By in silico analysis, it was predicted to be deleterious by SIFT and benign by PolyPhen-2 (S3 Table).

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Table 4. Recurrent somatic mutations with the percentage >1% in the 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.t004

In PTEN gene, total 17 somatic mutations, which located across 7 different exons (exon 1, 2, 3, 5, 6, 7 and 8), were identified in 15 of the 313 patients (4.8%), and no recurrent mutations were found (S2 Table). Of these 17 mutations, 8 located in the phosphatase domain and 9 located in the conserved domain 2 (C2) (Fig 1B), including 8 nonsense mutations, 5 missense mutations, 3 frameshift indels and 1 splice site mutation. Notably, two patients harbored two mutations in PTEN (Patient 124 harboring p.Q17X and p.C211X, Patient 258 harboring p.Y27N and p.G165R) (S2 Table). Three novel somatic mutations (p.K62X, p.N340IfsTer4 and c.635-12_636delTTAACCATGCAGAT) were detected in PTEN, all of which may lead to a truncated or non-functional PTEN protein. In addition, two germline mutations were found in PTEN (S3 Table). The mutation p.C136R was recorded in NCBI ClinVar database as pathogenic. Another germline mutation p.Q110E was novel and predicted to be tolerated by SIFT and benign by PolyPhen-2.

In TP53 gene, total 84 somatic mutations were identified in 106 of the 313 patients (33.9%), with 5 patients harboring two mutations. All the somatic coding mutations of TP53 located in exon 4, 5, 6, 7, 8, 9 and 11, and additional 3 splicing variants located in intron 4 and 9 (Fig 1G–1J and S2 Table). A large proportion of somatic mutations found in TP53 clustered in the region from exon 4 to exon 8 within the DNA-binding domain, mutations of which presented in 97 cases (97/106, 91.5%). The somatic mutation of TP53 included 62 missense mutations, 10 indels (5 inframe and 5 frameshift), 9 nonsense mutations and 3 splicing variants. Notably, 5 novel somatic mutations (p.Q136AfsTer5, p.K139_P142del, p.Y234dup, p.V274LfsTer31 and p.N310TfsTer35) were detected in TP53. All of these were frameshift mutations which may lead to deleterious effect on TP53 protein function. Additionally, 3 germline mutations were detected in TP53 (S4 Table). The two missense mutations, p.G244S and p.P295L, were recorded in NCBI ClinVar as likely pathogenic and uncertain significance, respectively. The remaining one splicing variant c.559+1G>A was classified as pathogenic mutations.

Multiple-gene and recurrent mutations in AKT1, PIK3CA, PTEN and TP53

Among the 190 somatic mutation carriers, 137 (137/190, 72.1%) harbored mutation in single gene (Table 2 and S3 Table). Total 51 patients (51/190, 26.8%) harbored co-mutation in two genes and 2 patients (2/190, 1.1%) harbored co-mutation in three genes. These included 2 patients (2/313, 0.6%) with co-mutations in AKT1-PIK3CA, 2 patients (2/313, 0.6%) with co-mutations in AKT1-TP53, 4 patients (4/313, 1.3%) with co-mutations in PIK3CA-PTEN, 40 patients (40/313, 12.8%) with co-mutations in PIK3CA-TP53, 3 patients (3/313, 1.0%) with co-mutations in PTEN-TP53 and 2 patients (2/313, 0.6%) with co-mutations in PIK3CA-PTEN-TP53. No concurred mutation was observed in AKT1-PTEN and AKT1-PIK3CA-TP53 genes (Table 2 and S2 Table).

Total 25 recurrent somatic mutations were found in this study (S2 Table). Among them, 10 mutations each recurred in >1% cases of this cohort of 313 patients (Table 4), including 1 mutation in AKT1 (p.E17K), 5 mutations in PIK3CA (p.N345K, p.E542K, p.E545K, p.H1047R and p.H1047L) and 4 mutations in TP53 (p.A159V, p.R175H, p.R213X and p.R248W). Overall, 125 of the 313 (39.9%) patients harbored at least one of these 10 mutations accounting for 55.7% of all mutations found in AKT1, PIK3CA and TP53. We did not observe any recurrent mutation in PTEN gene in this study. All of the PTEN mutations only presented in one patient each.

Association of somatic mutations with clinicopathological characteristics

We analyzed correlations between somatic mutation status of the 4 genes and patient clinicopathological characteristics (Table 5). Comparing mutation carriers and non-carriers, PIK3CA mutation carriers were significantly more likely to be ER-positive (P = 0.041), PR-positive (P = 0.004) and invasive ductal carcinoma (IDC) (P = 0.002). TP53 mutation carriers had a significant higher proportion of patients to be ER-negative (P<0.001), PR-negative (P<0.001), HER2-positive (P = 0.002), IHC p53 mutation positive (P = 0.018) and with high Ki67 expression (P<0.001) than non-carriers. No significant difference of clinicopathological characteristics was identified between mutation carriers and non-carriers of AKT1 or PTEN (Table 4).

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Table 5. Clinicopathological characteristics and associations with somatic mutation status in 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.t005

Furthermore, we assessed whether these somatic mutations were associated with deleterious germline BRCA1/2 mutations. All of the 313 patients have been tested for BRCA1/2 mutations by NGS in our previous study [9]. As shown in Table 5, almost all of the AKT1, PIK3CA and PTEN somatic mutation carriers did not harbor BRCA1/2 mutation, except that one PIK3CA somatic mutation carrier had a BRCA1 mutation. Five TP53 somatic mutation carriers co-harbored BRCA1 mutation and one TP53 somatic mutation carrier co-harbored BRCA2 mutation. Notably, all of the five BRCA1 mutation positive patients harbored TP53 somatic mutations (P = 0.001).

Somatic mutations distribution across different molecular subtypes

The distribution of the somatic mutations of the 4 genes varied in different breast cancer molecular subtypes (Fig 2). PIK3CA mutations occurred at high frequency in luminal A (40.7%) and luminal B (38.3%) tumors, while relatively low in basal-like (32.5%) and HER2-enriched (18.9%) tumors (Fig 2). In contrast, TP53 mutations were more common in basal-like (62.5%) and HER2-enriched (54.1%) tumors than in luminal A (11.6%) and luminal B (37.5%) tumors (Fig 2). AKT1 mutations only occurred in luminal A (5.8%), luminal B (3.1%) and HER2-enriched (2.7%) tumors. PTEN mutations only occurred in luminal A (5.8%), luminal B (5.5%) and basal-like (7.5%) tumors. The associations between somatic mutation of the 4 genes and breast cancer molecular subtypes were analyzed (Table 5). The TP53 mutations showed significant association with breast cancer subtypes (P<0.001) and had higher proportion of patients with basal-like (23.6% vs. 7.3%) and HER2-enriched (18.9% vs. 8.2%) tumors, comparing with non-TP53 mutations.

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Fig 2. The distribution of somatic mutations in different breast cancer subtypes of the 313 breast cancer patients.

a. The graphical summary of somatic mutations of the 4 genes in molecular subtypes. All of the 190 tumor samples with 4 gene somatic mutations are grouped into 5 groups: luminal A (n = 46), luminal B (n = 81), basal-like (n = 29), HER2-enriched (n = 22) and unknown (n = 11). The stripe panel shows every specific case harboring the 4 gene mutation with different mutation types. One stripe indicates one patient. Green stripe indicates missense mutation; Blue stripe indicates frameshift mutation; Red stripe indicates nonsense mutation; Black stripe indicates split site mutation; Dark Gray stripe indicates silent mutation; Cyan stripe indicates inframe indel mutation; Yellow star indicates mutation recorded in COSMIC database. b. The somatic mutation frequency of AKT1, PTEN, PIK3CA and TP53 in different breast cancer subtypes. The frequency of somatic mutations for individual gene is shown in the bar chart in various groups according to molecular subtypes of breast cancer. These groups include All (N = 313), luminal A (N = 86), luminal B (N = 128), basal-like (N = 40), HER2-enriched (N = 37) and unknown (N = 22).

https://doi.org/10.1371/journal.pone.0203495.g002

Discussion

In this study, by integrating microfluidic PCR-based target enrichment and NGS technologies, we sequenced the entire coding regions and exon-intron boundaries of TP53 and three PI3K pathway genes (AKT1, PIK3CA, PTEN) in paired tumor and normal tissue samples from 313 Chinese breast cancer patients. Our results showed that somatic mutations of these genes occurred at high frequency among Chinese breast cancer patients. Previously, several studies have conducted mutational analysis including AKT1, PIK3CA, PTEN and/or TP53 genes in breast cancer worldwide [6, 2542]. However, few studies have focused on the comprehensive study of AKT1, PIK3CA, PTEN and TP53 mutations altogether in Chinese breast cancer patients. Most of these studies focused on either selected hotspot sites or selected exons of these four genes [3743]. As shown in S4 Table, due to the differences of detection methods and studied regions, the reported mutation frequency of these four genes varied a lot among different studies and different populations. The mutation frequencies of AKT1, PIK3CA, PTEN, and TP53 in Chinese population were reported to range 0–4.4%, 7.5–38.8%, 0–4.8% and 10.0–33.9% respectively (S4 Table). In other populations, these frequencies were reported to range 1.4–6.0%, 7.1–45.0%, 1.0–5% and 27.2–38.8% respectively (S4 Table). In all studies, PIK3CA and TP53 were consistently the top two frequently mutated genes, which confirmed their important role in breast carcinogenesis.

In addition to high frequency of PIK3CA and TP53 single-gene somatic mutation, TP53-PIK3CA co-mutations were detected as high as 12.8% in our cohort, compared that as 8.7% in a TCGA cohort [23] (Table 2). This co-occurrence pattern was also discovered by prior studies with frequency as 5.3% in 120 breast cancer patients [28] and as 5.9% in 1766 breast cancer patients [44]. Previous in vivo study has confirmed that TP53 and PIK3CA mutations show cooperation in mammary tumor formation in mice [45]. It have been reported that TP53-PIK3CA co-mutation carriers had worst disease-free survival comparing with non-mutation carriers, PIK3CA-mutation-only or TP53-mutation-only carriers [46]. Since a high frequency of TP53-PIK3CA co-mutations was detected in our cohort, this mutation pattern need to be evaluated closely in clinical settings for Chinese breast cancer patient in the future.

Cancer hotspot mutations carry valuable information for diagnosis, prognosis and treatment [47]. In this cohort, total 10 mutations were found to be recurrently mutated in >1% patients accounting for 55.7% somatic mutations in AKT1, PIK3CA and TP53 (Table 4). Of these 10 mutations, AKT1 p.E17K, three PIK3CA mutations within the PI3Ka (E542K and E545K) and PI3Kc (H1047R) domains and two TP53 mutations (p.R175H and p.R248W) within the DNA binding domain were well established hotspots in breast cancer [48, 49]. Additional 3 mutations (p.N345K and p.H1047L in PIK3CA, p.R213X in TP53) were also reported as hotspots by a recent study on a large number of tumors by a novel statistical algorithm [50]. The p.H1047L mutation occurred at the same location as p.H1047R, which were also detected by a study on Chinese breast cancer patients [42]. The mutation TP53 p.A159V was also detected by another study on breast cancer with the frequency as 0.9% (5/560) [5]. These hotspot mutations may be important candidate target for clinical applications in cancer treatment and screening.

Previous studies suggested that somatic mutation was one of the mechanisms leading to PTEN loss [51, 52]. In this study, the frequency of somatic mutations of PTEN was reported as 4.8%, while loss of PTEN in protein expression was reported as high as 48% in breast cancer [53]. The reason was that other mechanisms such as promoter methylation, loss of heterozygosity, transcriptional or post-transcriptional regulation can also lead to PTEN loss. In this study, 11 out of the 17 somatic mutations found in PTEN were stopgain SNVs or frameshift indels which can cause truncated PTEN protein. And the other 6 PTEN somatic mutations were predicted to be deleterious or probably damaging (S2 Table). Taken together, all PTEN somatic mutations may lead to deleterious effect on protein function, which suggested that PTEN alteration play a critical role in breast tumorgenesis.

AKT1 is a downstream mediator of phosphatidylinositol 3-kinase. In line with previous studies [39, 54] on Chinese breast cancer patients, we detected only one hotspot mutation (p.E17K) in the pleckstrin homology domain. Recently, it has been demonstrated that mutation AKT1 p.E17K is a therapeutic target which is sensitive to AKT inhibitors in breast cancer patients [55]. Thus 9 out of the 10 (90%) AKT1 somatic mutation carriers with p.E17K mutations in this study (S2 Table) may be good candidates for AKT inhibitors treatment.

In conclusion, our results showed that somatic mutations in AKT1, PIK3CA, PTEN and TP53 genes were common events in Chinese breast cancer patients and had distinct spectrum across different breast cancer subtypes. Total 60.7% of the patients harbored at least 1 somatic mutation. PIK3CA somatic mutations were significantly associated with ER-positive or PR-positive tumors. TP53 somatic mutations were significantly associated with ER-negative, PR-negative, HER2-positive, BRCA1 mutation, Ki67 high expression and basal-like tumors. These findings provided a comprehensive mutational characterization of AKT1, PIK3CA, PTEN and TP53 genes in Chinese breast cancer patients with valuable implications for clinical management and optimal design of clinical trials in the future.

Supporting information

S1 Fig. Verification of somatic mutations in tumor tissues by Sanger sequencing.

https://doi.org/10.1371/journal.pone.0203495.s001

(PDF)

S2 Fig. Verification of germline mutations in tumor/normal tissues by Sanger sequencing.

https://doi.org/10.1371/journal.pone.0203495.s002

(PDF)

S1 Table. The primer sequences of the AKT1, PIK3CA, PTEN and TP53 genes.

https://doi.org/10.1371/journal.pone.0203495.s003

(XLSX)

S2 Table. Somatic mutations of AKT1, PIK3CA, PTEN and TP53 genes in the 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.s004

(XLSX)

S3 Table. Germline variants of PIK3CA, PTEN and TP53 genes in the 313 breast cancer patients.

https://doi.org/10.1371/journal.pone.0203495.s005

(XLSX)

S4 Table. Worldwide distribution pattern of AKT1, PIK3CA, PTEN and TP53 mutations in primary breast cancer.

https://doi.org/10.1371/journal.pone.0203495.s006

(XLSX)

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