Unveiling the genetic landscape: high frequency of pik3ca mutation in luminal a and b breast cancer within the Indonesian population

Unveiling the genetic landscape: high frequency of pik3ca mutation in luminal a and b breast cancer within the Indonesian population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Unveiling the genetic landscape: high frequency of pik3ca mutation in luminal a and b breast cancer within the Indonesian population Yan Wisnu Prajoko, Didik Setyo Heriyanto, Nur Dina Amalina, Bayu Tirta Dirja, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4000099/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Breast cancer (BC) is a global health concern with significant mortality rates, necessitating a deep understanding of its molecular landscape. Objective: This study focuses on the prevalence of phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations in Luminal A and B BC within the Indonesian population. Luminal A and B BC, characterized by estrogen receptor (ER) and/or progesterone receptor (PR) positivity, face challenges in endocrine therapy due to acquired resistance, often mediated by PI3K/Akt/mTOR pathway activation. Methods: The study, conducted from 2019 to 2022, collected samples from diverse Indonesian regions, representing various islands. Histopathological analysis and immunohistochemistry classified samples into molecular subtypes. Results: Genetic analysis using PIK3CA mutation detection kits revealed a mutation frequency of 36.2%, with Luminal A BC exhibiting the highest mutation rate (46.1%). Notably, Luminal B HER-2 (positive) BC demonstrated a lower mutation frequency (19%). Statistical analyses highlighted correlations between PIK3CA mutations and molecular subtypes (p=0.01), with Luminal A and Luminal B HER-2 (negative) BC showing higher mutation frequencies. No significant associations were observed with age, tumor location, or histopathology diagnosis. Luminal A BC demonstrated a higher prevalence of PIK3CA mutations in patients over 50 years old (68.1%). Comparisons with existing literature and inconsistencies in PIK3CA mutation prevalence across different BC subtypes underline the need for population-specific research. Conclusion : The study emphasizes the importance of assessing PIK3CA mutations in BC management, offering insights for personalized therapies and potential advancements in understanding this complex disease within the Indonesian context. PIK3CA mutation breast cancer Indonesia population INTRODUCTION Breast cancer (BC) is a public health problem that has a high mortality rate for women around the world [ 1 , 2 ]. It is the second most common cause of cancer death after lung cancer in women, with more than one million new cases diagnosed each year [ 3 , 4 ] Molecular biomarkers and their correlation with pathological parameters are essential for diagnosis, prognosis, predictive utility, management, and prevention of BC [ 5 ]. In addition to the adverse impacts caused by industrial-induced pollutants or mental-related endocrine changes, BC is known as a complex and heterogeneous disease, triggered by genomic variation [ 4 , 6 ]. Statistically, 5–10% of breast cancers are caused primarily by genetic factors caused by the accumulation of acquired somatic changes [ 7 , 8 ]. Invasive BC is primarily categorized into four molecular subtypes using immunohistology analysis, based on the expression status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) [ 9 – 11 ]. Luminal A BC, which is positive for either or both ER and PR and negative for HER2, accounts for 50–60% of BC cases and generally has a favorable prognosis [ 12 , 13 ]. Luminal B BC, positive for ER and/or PR and HER2, constitutes about 30% of BC cases [ 11 ]. Luminal B BC is characterized by high levels of ki67, a marker of cell proliferation, and typically has a poor prognosis [ 14 ]. HER2 Enriched BC, which is ER and PR negative but HER2 positive, represents around 15–20% of BC cases [ 15 ]. This subtype is associated with a poor prognosis but can be effectively treated with HER2-targeted therapies [ 16 – 18 ]. Triple-negative BC (TNBC), which is negative for ER, PR, and HER2, accounts for 10–20% of BC cases. TNBC is associated with a poor prognosis due to its aggressive nature and lack of targeted therapies [ 19 , 20 ]. Treatment regimens for luminal A and B breast cancer (HR + BC) typically integrate various modalities, including chemotherapy, surgery, radiotherapy, and adjuvant therapies such as endocrine therapy [ 8 , 21 ]. Endocrine therapy has emerged over recent decades as a safe and efficacious personalized approach for HR + BC patients. Established endocrine therapies encompass Selective Estrogen Receptor Modulators (SERMs) like tamoxifen, Selective Estrogen Receptor Degraders (SERDs) such as Fulvestrant, and Aromatase Inhibitors (AIs) including exemestane and letrozole [ 22 ]. However, a primary challenge associated with endocrine therapy is the development of acquired or intrinsic resistance [ 23 ]. SERDs and AIs can induce resistance through various mechanisms, including the upregulation of signaling pathways such as phosphatidylinositol 3-kinase (PI3K), mammalian target of rapamycin (mTOR), and extracellular signal-regulated kinase (Ras-ERK) [ 24 , 25 ]. These pathways offer alternative routes for HR + BC to evade treatment and sustain cancer cell proliferation and survival [ 26 ]. In response to these challenges, researchers are actively developing novel therapeutics to circumvent estrogen-independent cell survival, targeting key mechanisms of resistance, notably the PI3K/Akt/mTOR pathway [ 27 ]. These emerging therapies, currently undergoing clinical trials, hold promise in overcoming endocrine therapy resistance. Leading examples include pan-PI3K inhibitors (e.g., Buparlisib, Pictilisib) and isoform-specific PI3K inhibitors (e.g., Alpelisib, Taselisib) [ 28 ]. The PI3Ks represent a family of lipid kinases classified into three classes based on their structures and substrate specificities. Among the primary examples is the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) gene [ 27 , 28 ]. Somatic alterations in the PIK3CA gene stand out as one of the most prevalent genetic triggers in breast cancer, with a frequency estimated at approximately 30–40% [ 29 ]. Positioned on chromosome 3q26.32, the PIK3CA gene encodes the alpha isoform (p110α), the principal isoform of the catalytic subunit within the class 1A phosphatidylinositol 3-kinase (PI3K), a lipid phosphokinase [ 30 ]. Functionally, the PI3K family mediates signals crucial for various cellular activities, encompassing proliferation, metabolism, migration, translation, apoptosis evasion, and angiogenesis. Predominantly, mutations in breast cancer localize to three hot spots (HS): E542K and E545K on exon 9, encoding the helical domain (HD), and H1047R on exon 20, encoding the kinase domain (KD) [ 31 ]. Previous research has indicated that endocrine-resistant PIK3CA-mutant cases may potentially benefit from treatment with PI3K inhibitors, underscoring the significance of elucidating the prevalence of PIK3CA mutations among populations to inform potential future avenues in hormone receptor-positive breast cancer treatment [ 32 ]. Research underscores the significance of analyzing PIK3CA gene mutations due to their association with the onset and progression of breast cancers (BCs). These mutations are detected in 20–40% of BC patients [ 29 , 30 , 32 ]. Studies suggest that the presence of PIK3CA mutations can negatively impact disease-free survival (DFS) and pathological complete response (pCR) to targeted therapy and chemotherapy in patients with HER2-enriched and triple-negative breast cancer (TNBC) [ 33 ]. This suggests the potential benefit of assessing PIK3CA mutations in all molecular subtypes of BC, including non-hormonal subtypes. However, there is a noticeable lack of data on this subject, particularly in the Indonesian population. Recently, numerous studies have examined BC PIK3CA mutations in various countries and regions, revealing inconsistencies in the results regarding the clinical pathological characteristics of PIK3CA mutation [ 28 – 30 , 33 ]. Small sample sizes, different detection methods, and varying inclusion criteria are likely contributing factors to these inconsistent outcomes. The aim of this study is to determine the prevalence of PIK3CA mutations among the Indonesian population and to identify potential correlations between these mutations and established clinicopathological profiles of breast cancer patients. This research carries considerable importance in the context of breast cancer management in Indonesia, as there is presently a dearth of national data regarding the prevalence of PIK3CA mutations and associated clinicopathological information among breast cancer patients in the country. It is envisaged that this investigation will serve as a catalyst for further exploration of PIK3CA in Indonesian breast cancer patients, thereby potentially facilitating substantial progress in comprehending and addressing this disease. MATERIALS AND METHODS Ethics approval Ethical approval for this study was granted by the Medical and Health Research Ethics Committee (MHREC) under Ethical Approval Number No.32/EC/KEPK/FK-UNDIP/II/2023. Study design This study employed a cross-sectional approach to analyze samples obtained from the archive of Cito Clinical Laboratory, Indonesia, spanning the period from 2019 to 2022. The samples were collected from various islands across the Indonesian archipelago, including Java, Kalimantan, Sumatera, Mataram, and Papua. Histopathological examination and grading of Breast Cancer (BC) samples were conducted, as necessary. Subsequently, the samples underwent immunohistochemistry (IHC) analysis to determine their molecular subtypes. Finally, genetic analysis was performed on each viable sample to identify the presence of any PIK3CA mutations. Breast Cancer Sample Paraffin blocks obtained from patients histopathologically diagnosed with primary breast cancer, including Invasive Breast Carcinoma of No Special Type (NST), Invasive Lobular Carcinoma, Invasive Papillary Carcinoma, and Mucinous Carcinoma of the breast, were included in this study. Samples were collected from multiple centers situated in various provinces across the diverse islands of Indonesia. Histological evaluation was conducted by two pathologists, and exclusion criteria comprised FFPE samples of inadequate quality and incomplete medical records data. Patient data regarding clinico-pathological characteristics, including sociodemographic factors (age), tumor pathology (location/site, histopathology, histologic grade), and clinical parameters, were acquired. Immunohistochemistry Staining This study comprised 207 cases of diverse breast cancer (BC) types. Immunohistochemistry (IHC) was employed to examine the samples, utilizing anti-estrogen receptor (ER), anti-progesterone receptor (PR), anti-human epidermal growth factor receptor 2 (HER2), and anti-Ki67 antibodies from Ventana™. Staining procedures were conducted utilizing the Ventana BenchMark XT and Discovery XT™ Tissue Diagnostic and IHC autostainer. All protocols strictly adhered to the manufacturer’s instructions and protocols to ensure the attainment of consistent and reliable results. DNA extraction Paraffin blocks from various breast cancer subtypes were cut into 10 pieces with 5μm thickness. Ten pieces in one slide continued with DNA extraction. Genomic DNA was extracted using the GeneAll® Exgene™ FFPE Tissue DNA according to the manufacturer's protocol. DNA samples were then quantified using a NanoDrop™ spectrophotometer (Thermo Scientific, Waltham, MA, USA). Samples of sufficient concentration and quality were adjusted to a concentration of 20 ng/µL for PCR applications. Detection of PIK3CA Mutation The samples were further analyzed for PIK3CA mutation at both Cito Clinical Laboratory and the Department of Anatomical Pathology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada. Specimens originating from islands other than Java were meticulously transported to Yogyakarta, ensuring strict adherence to established standards. The detection of PIK3CA mutation biomarkers was conducted using the BioColomelt-Dx™ in vitro diagnostics kit, developed by Biofarma Ltd, Indonesia. This molecular diagnostic kit utilizes Polymerase Chain Reaction (PCR) and High-Resolution Melting (HRM) techniques. Subsequently, the findings were validated using the Qiagen therascreen® PIK3CA RGQ PCR kit. The Qiagen Therascreen® kit is a Real-Time (RT) qualitative PCR test designed for the detection of 11 gene mutations in the PIK3CA gene, including PIK3CA Exon 9 and 20, utilizing FFPE DNA samples. Statistical Analysis The statistical analysis was conducted using Excel and IBM SPSS version 27. The correlation between variables was calculated using Fisher's exact test with a significance level of α= 0.05. RESULTS Clinicopathologic characteristics of the breast cancer samples The characteristics of the samples are summarized in Table 1. A total of 104 (50.2%) samples were obtained from the right breast, while 103 (49.8%) samples were obtained from the left breast. The mean age of the patients was 56 years old. Histopathological types included 4 (1.9%) samples of grade I Invasive Breast Carcinoma of No Special Type (IBC-NST), 81 (39.1%) samples of grade II IBC-NST, 84 (40.6%) samples of grade III IBC-NST, 34 (16.4%) samples of Invasive Lobular Carcinoma, 1 (0.5%) sample of Invasive Papillary Carcinoma, and 3 (1.4%) samples of Mucinous Carcinoma. Molecular Subtypes, as determined by Immunohistochemistry Evaluation, comprised 102 (49.3%) samples of Luminal A, 37 (17.9%) samples of Luminal B HER-2 (negative), 21 (10.1%) samples of Luminal B HER-2 (positive), 20 (9.7%) samples of HER-2 Enriched, and 27 (13%) samples of triple-negative breast cancer (TNBC). Table 1. Clinicopathology characteristics of the study samples Characteristic N (%) Age ≤ 50 years old 75 (36.2%) > 50 years old 132 (63.8%) Location Right Breast 104 (50.2%) Left Breast 103 (49.8%) Histopathology Diagnosis Invasive Breast Carcinoma of NST, Grade I 4 (1.9%) Invasive Breast Carcinoma of NST, Grade II 81 (39.1%) Invasive Breast Carcinoma of NST, Grade III 84 (40.6%) Invasive Lobular Carcinoma of the Breast 34 (16.4%) Invasive Papillary Carcinoma of the Breast 1 (0.5%) Mucinous Carcinoma of the Breast 3 (1.4%) Molecular Subtypes (IHC Evaluation) Luminal A 102 (49.3%) Luminal B HER-2 (negative) 37 (17.9%) Luminal B HER-2 (positive) 21 (10.1%) HER-2 Enriched 20 (9.7%) TNBC 27 (13%) Abbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer. PIK3CA Mutation Status in Breast Cancer Samples A total of 75 (36.2%) samples showed positive PIK3CA mutation (Table 2). Table 2. Frequency of the PIK3CA mutations in breast cancer samples Characteristic N (%) PIK3CA mutation status Positive (Mutated) Negative (Wild type) 75 (36.2%) 132 (63.8%) Table 3 illustrates the correlation between clinicopathological features and the PIK3CA mutation status. Notably, a substantial proportion of samples from patients aged over 50 years (34.1%) exhibited PIK3CA mutation; however, no significant association between mutation status and patient age was observed (p > 0.05). Similarly, no discernible correlation was found between mutation status and tumor location, whether in the right or left breast (p > 0.05). Regarding Invasive Breast Carcinoma (IBC) grades, mutations were more prevalent in higher grades (Grade I: 25%; Grade II: 35.8%; Grade III: 42.9%). Nonetheless, no definitive association between histopathology diagnosis and PIK3CA mutation status was established. These findings suggest that mutation status does not significantly correlate with age, tumor location, or histopathology diagnosis in breast cancer cases; rather, these variables appear to be independent based on the dataset analyzed. However, a noteworthy discovery in this study was the significant association between PIK3CA mutation status and molecular subtypes as determined by immunohistochemistry evaluation (p=0.01; p<0.05). Specifically, PIK3CA mutations were more prevalent in Luminal A breast cancer samples (mutation rate: 46.1%) and Luminal B HER-2 (negative) breast cancer samples (mutation rate: 40.5%), compared to Luminal B HER-2 (positive), HER-2 enriched, and triple-negative breast cancer (TNBC) subtypes (mutation frequencies: 19%, 20%, 18.5%, respectively), which exhibited lower mutation frequencies than the overall mutation frequency of 36.2% (refer to Table 2). Table 3. Association between the Clinicopathology Characteristics and PIK3CA mutation status in breast cancer samples Characteristic PIK3CA Mutation Status p-value Negative (Wildtype), N (%) Positive (Mutated), N (%) Age 0.453 ≤ 50 years old 45 (60%) 30 (40%) > 50 years old 87 (65.9%) 45 (34.1%) Location 0.472 Right Breast 69 (66.3%) 35 (33.7%) Left Breast 63 (61.2%) 40 (38.8%) Histopathology Diagnosis 0.169 Invasive Breast Carcinoma of NST, Grade I 3 (75%) 1 (25%) Invasive Breast Carcinoma of NST, Grade II 52 (64.2%) 29 (35.8%) Invasive Breast Carcinoma of NST, Grade III 48 (57.1%) 36 (42.9%) Invasive Lobular Carcinoma of the Breast 26 (76.5%) 8 (23.5%) Invasive Papillary Carcinoma of the Breast 0 (0%) 1 (100%) Mucinous Carcinoma of the Breast 3 (100%) 0 (0%) Molecular Subtypes (IHC Evaluation) 0.01* Luminal A 55 (53.9%) 47 (46.1%) Luminal B HER-2 (negative) 22 (59.5%) 15 (40.5%) Luminal B HER-2 (positive) 17 (81%) 4 (19%) HER-2 Enriched 16 (80%) 4 (20%) TNBC 22 (81.5%) 5 (18.5%) *Fisher's exact test p<0.05. Abbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer. Table 4 showed that findings of the study indicate a strong correlation between histopathology diagnosis and molecular subtypes of breast cancer (p=0.007; p<0.01). Notably, Luminal A BC is most commonly observed in IBC of NST compared to all other molecular subtypes. On the other hand, Luminal B HER-2 (positive), HER-2 Enriched, Luminal B HER-2 (negative) BC, and TNBC are frequently observed in IBC of NST, with proportions of 90.5%, 75%, 67.6%, and 66.7% respectively. Table 4. Association between Clinicopathology Characteristics in breast cancer samples (IHC vs Histopathology Diagnosis) Characteristic Histopathology Diagnosis p-value Invasive Breast Carcinoma of NST Invasive Lobular Carcinoma of the Breast Invasive Papillary Carcinoma of the Breast Mucinous Carcinoma of the Breast Molecular Subtypes (IHC) 0.007* Luminal A 92 (90.2%) 8 (7.8%) 0 (0%) 2 (2%) Luminal B HER-2 (negative) 25 (67.6%) 10 (27%) 1 (2.7%) 1 (2.7%) Luminal B HER-2 (positive) 19 (90.5%) 2 (9.5%) 0 (0%) 0 (0%) HER-2 Enriched 15 (75%) 5 (25%) 0 (0%) 0 (0%) TNBC 18 (66.7%) 9 (33.3%) 0 (0.0%) 0 (0.0%) *Fisher's exact test p<0.05. Abbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer. Table 5 showed that there is no significant association between PIK3CA mutation status and different luminal molecular subtypes (p>0.05). However, we found that the Luminal B HER-2 (positive) subtype has a lower mutation frequency of 19% compared to the 46.1% and 40.5% of Luminal A and Luminal B HER-2 (negative) BC respectively. Within the Luminal Mutated PIK3CA tumors, only 4 of 66 samples (6%) are Luminal B HER-2 (positive). Table 5. Association between the Luminal Hormonal Receptor Positive Molecular Subtypes and PIK3CA mutation status in breast cancer samples Characteristic PIK3CA Mutation Status p-value Negative (Wildtype), N (%) Positive (Mutated), N (%) Molecular Subtypes (IHC Evaluation) 0.07 Luminal A 55 (51.6%) 47 (46.1%) Luminal B HER-2 (negative) 22 (61.1%) 15 (40.5.%) Luminal B HER-2 (positive) 17 (81%) 4 (19%) *Fisher's exact test p<0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2. Table 6 showed that there is no significant association between PIK3CA mutation status with the TNBC and HER-2 enriched molecular subtypes. Similarly, both HER-2 enriched and TNBC showed lower mutation frequency compared to overall PIK3CA mutation frequency. Table 6. Association between the TNBC and HER-2 Molecular Subtypes and PIK3CA mutation status in breast cancer samples Characteristic PIK3CA Mutation Status p-value Negative (Wildtype), N (%) Positive (Mutated), N (%) Molecular Subtypes (IHC Evaluation) 1.000 HER-2 Enriched 16 (80.0%) 4 (20.0%) TNBC 22 (81.5%) 5 (18.5%) *Fisher's exact test p<0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer. Upon a more comprehensive analysis as presented in Table 7, it was observed that there is no statistically significant association between age groups and molecular subtypes in PIK3CA positive (mutated) samples. Nevertheless, it is evident that there is a higher prevalence (68.1%) of older (>50 years old) patients in Luminal A with PIK3CA positive (mutated) samples. When comparing between molecular subtypes in those who are >50 years old , it is also evident that Luminal A is the most prevalent molecular subtype (71%). Table 7. Association between each molecular subtypes and age in PIK3CA positive (mutated) breast cancer samples Characteristic Age p-value ≤ 50 years old > 50 years old Molecular Subtypes (IHC Evaluation) in PIK3CA Positive (Mutated) Samples 0.298 Luminal A 15 (31.9%) 32 (68.1%) Luminal B HER-2 (negative) 8 (53.3%) 7 (46.7%) Luminal B HER-2 (positive) 3 (75%) 1 (25%) HER-2 Enriched 2 (50%) 2 (50%) TNBC 2 (40%) 3 (60%) *Fisher's exact test p<0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer. DISCUSSION The phosphatidylinositol-3-kinase (PI3K) pathway plays a pivotal role in the proliferation and viability of malignant cells and is frequently dysregulated in various types of cancer, including breast cancer (BC). This deregulation can occur through several mechanisms, such as mutations or amplifications in PI3K itself, the inactivation of the tumor suppressor PTEN, or the activation of upstream oncogenes and tyrosine kinase growth factor receptors [34]. PIK3CA mutations have been extensively studied in newly diagnosed BC, often linked to favorable characteristics like positive ER expression, smaller tumor size, and low histological grade [35]. Two recent studies also found that PIK3CA mutations were associated with older age and lower tumor grade at diagnosis [36].However, these mutations show variable prevalence and implications across different studies and populations. For example, a study in Yogyakarta, Indonesia found that Luminal A subtype is frequently observed in Grade I tumors, whereas Grade III tumors are more commonly associated with the Luminal B, HER2 enriched, and Triple-Negative Breast Cancer (TNBC) [37, 38]. These findings exhibit a divergent pattern compared to our study, potentially attributable to variances in sample populations across different provinces and regions within Indonesia [38]. Recent studies from different populations have also presented conflicting results regarding the relationship between PIK3CA mutations and tumor grading, adding the layer of complexity [39]. PIK3CA wild-type tumors had lower tumor grade, higher ER expression, and lower AR expression compared to mutant tumors, contradictory with recent findings that there was no significant correlation between histological Scarff-Bloom-Richardson (SBR) tumor grading and PIK3CA mutation status [40]. On the other hand, our study is in accordance with the study by Cizkova that showed that PIK3CA mutations are predominantly found in higher-grade tumors, particularly SBR grade II [41]. Due to the inconclusive findings, additional investigation is warranted, encompassing a greater sample size and a more comprehensive representation of the entirety of the Indonesian center. Our findings indicate a decreasing prevalence of PIK3CA mutation across different molecular subtypes, with the highest frequency observed in Luminal A subtype, followed by Luminal B HER-2 (negative), HER-2 enriched, Luminal B HER-2+, and TNBC subtypes. The results are partially consistent with the research conducted by Wu et al. (2019). Nonetheless, the study failed to further categorize Luminal B into Luminal B HER-2 negative or Luminal B HER-2+ [42]. Therapeutically, the presence of PIK3CA mutations has been linked to reduced rates of achieving pathological complete response (pCR) in neoadjuvant chemotherapy, indicating potential chemoresistance [43, 44]. Moreover, these mutations have been associated with resistance to anti-HER2 treatment in HER2 enriched patients and endocrine treatment in ER+ patients [28, 31]. Previous study reported that ER-positive, HER2-negative, PIK3CA mutant breast cancers, despite apparent PI3K/AKT pathway activation, downstream mTOR1 signaling was not greatly elevated at the transcriptional and biological levels. One of their hypotheses for underlying the mechanism is that PIK3CA mutations are associated with weak pathway activation, and that other PI3K pathway alterations produce stronger pathway activation. The study suggests that, in ER+/HER2− BC with PIK3CA mutations, pathway activation surprisingly does not result in greatly elevated downstream signaling and their functional output differs substantially compared with that of PTEN loss [24, 44]. The mechanism underlying these observations could be mediated by unknown genes. Potential candidates are PP2A and/or PML, both known negative regulators of AKT1 and mTOR, and both present in the larger gene signature list [44]. This mechanism appears to be specific to TNBC cells and is not observed in other BC subtypes where PML and prometastatic HIF1A target genes are underexpressed. As a consequence, PML promotes cell migration, invasion, and metastasis in TNBC cell and mouse models [10, 33, 45, 46]. A study revealed that loss of specific PP2A regulatory subunits is functionally important in breast tumorigenesis, and support strategies to enhance PP2A activity as a therapeutic approach in breast cancer [33]. Approximately 30-40% of breast cancer cases that are positive for HER2 enriched exhibit a mutation in the PIK3CA gene. In a study, the presence of PIK3CA mutation in circulating tumor DNA (ctDNA) was observed in all patients who tested negative for the mutation in the tissue. Suggesting the prevalence of PIK3CA mutation in HER2 enriched breast cancer may be inaccurately assessed through the examination of stored tissue samples, such as in our study. As a result, the implementation of liquid biopsy as a valuable method to more effectively capture temporal heterogeneity is proposed in another study [33]. This approach has the potential to increase the number of patients who may derive therapeutic benefits from targeted treatments, since such mutations have been associated with trastuzumab resistance in HER2+ patients [18, 47]. The presence of PIK3CA gene mutations has been observed in approximately 9% of TNBC, including cases that recur as metastatic tumors after initial hormone receptor-positive (HR+) breast cancer. In such cases, the PIK3CA mutation has been found to persist. TNBC can be classified into six subtypes according to gene expression, as proposed by Lehman. Among these subtypes, the luminal androgen receptor (LAR) and mesenchymal stem-like (MSL) subtypes exhibit a greater prevalence of PIK3CA mutations [41]. The role of PIK3CA mutations and alterations in the PI3K/AKT pathway is of significant importance in breast cancer biology. However, their significance is more comprehensively understood in HR+/HER2- breast cancer in comparison to TNBC and HER2 enriched breast cancer, which necessitate additional research endeavors [33]. The overall survival (OS) of patients with PIK3CA-mutated metastatic triple-negative breast cancer (mTNBC) was found to be higher compared to patients with PIK3CA wild-type (WT) mTNBC. The presence of PIK3CA mutations in early TNBC patients has been linked to the expression of the androgen receptor and apocrine subtype [41, 48]. Additionally, these mutations have shown an inverse correlation with immune system activation and PTEN alterations [41]. The alteration of the PI3K/AKT/PTEN pathway has been found in 25% – 40% patients with mTNBC. This finding provides support for research in the PIK3/AKT/PTEN pathway and its inhibitors [36]. In the clinical setting of TNBC and HER2 enriched subtypes, it is important to highlight their aggressive features. These types of breast cancers demonstrate wild-type (WT) status in relation to PIK3CA mutations. The presence of other complex pathways that have substantial roles in the development of breast cancer across different molecular subtypes may explain this phenomenon. In order to advance future research, it is crucial to conduct further investigation into the PIK3/AKT/PTEN and mTOR pathways, as they are closely associated with PIK3CA. Moreover, it is imperative to conduct protein expression level analysis in order to obtain a comprehensive comprehension of the involvement of these pathways in triple-negative breast cancer (TNBC) and HER2-enriched subtypes. Previous studies have demonstrated that the growth and viability of AR + TNBC cell line models can be significantly diminished through the administration of PI3K inhibitors in conjunction with an AR antagonist. Hence, these findings provide a strong justification for the pre-selection of patients with triple-negative breast cancer (TNBC) using a biomarker, namely androgen receptor (AR) expression, in order to investigate the potential application of AR antagonists in conjunction with PI3K/mTOR inhibitors [41]. Regrettably, our study solely focused on the fundamental molecular subtypes of triple-negative breast cancer (TNBC) and did not encompass the additional six subtypes proposed by Lehman. Hence, it is imperative for future investigations to incorporate these supplementary subtypes, particularly in the context of triple-negative breast cancer (TNBC). Declarations ACKNOWLEDGMENT We extend our sincere gratitude to all those who contributed to the completion of this manuscript. FUNDING This research was supported by grants from the Ministry of Education, Culture, Research, and Technology, Indonesia under national collaborative research scheme 2023. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. CONTRIBUTIONS YWP and DSH conceptualized and designed the study, analyzed the data, and conceptualized and wrote the manuscript; NDA, VL, and ANG conducted the experiments, analyzed the data, and drafted the manuscript; BTD and SS analyzed the data and designed the part of the study; YWP provided of study materials and data analysis; DSH provided study material data interpretation; YWP and NDA conceptualized the study and provide the manuscript. The final version of the manuscript was approved by all authors. CORESSPONDING AUTHOR Correspondence to Yan Wisnu Prajoko ETHICS DECLARTIONS ETHICS APPROVAL AND CONSNET TO PARTICIPATE The study was conducted in 2023 to 2024 with written informed consent. Ethical approval was obtained from the Medical and Health Research Ethics Committee (MHREC) under Ethical Approval Number No.32/EC/KEPK/FK-UNDIP/II/2023. All methods were performed in accordance with the relevant guidelines and regulations. CONSENT FOR PUBLICATION Not applicable. CONFLICT OF INTEREST The authors have no conflicts of interest to declare. DATA AVAILABILITY The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Shumway DA, Sabolch A, Jagsi R. Breast Cancer. Med Radiol 2020; 1–43. Giaquinto AN, Sung H, Miller KD, et al. Breast Cancer Statistics, 2022. CA Cancer J Clin 2022; 72: 524–541. Azamjah N, Soltan-Zadeh Y, Zayeri F. Global trend of breast cancer mortality rate: A 25-year study. 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Characteristics and outcomes according to molecular subtypes of breast cancer as classified by a panel of four biomarkers using immunohistochemistry. Breast 2012; 21: 50–57. Zong Y, Zhu L, Wu J, et al. Progesterone receptor status and Ki-67 index may predict early relapse in luminal B/HER2 negative breast cancer patients: A retrospective study. PLoS One ; 9. Epub ahead of print 29 August 2014. DOI: 10.1371/journal.pone.0095629. Godoy-Ortiz A, Sanchez-Muñoz A, Parrado MRC, et al. Deciphering her2 breast cancer disease: Biological and clinical implications. Front Oncol ; 9. Epub ahead of print 2019. DOI: 10.3389/fonc.2019.01124. Camilleri-Broët S, Hardy-Bessard AC, Le Tourneau A, et al. HER-2 overexpression is an independent marker of poor prognosis of advanced primary ovarian carcinoma: A multicenter study of the GINECO group. Annals of Oncology 2004; 15: 104–112. Meiyanto E, Husnaa U, Kastian RF, et al. The target differences of anti-tumorigenesis potential of curcumin and its analogues against HER-2 positive and triple-negative breast cancer cells. Adv Pharm Bull 2021; 11: 188–196. Tjipta A, Hermansyah D, Suzery M, et al. Application of Bioinformatics Analysis to Identify Important Pathways and Hub Genes in Breast Cancer Affected by HER-2. International Journal of Cell and Biomedical Science 2022; 1: 18–27. Amalina ND, Wahyuni S, Harjito. Cytotoxic effects of the synthesized Citrus aurantium peels extract nanoparticles against MDA-MB-231 breast cancer cells. J Phys Conf Ser 2021; 1918: 032006. Mursiti S, Amalina ND, Marianti A. Inhibition of breast cancer cell development using Citrus maxima extract through increasing levels of Reactive Oxygen Species (ROS). J Phys Conf Ser 2021; 1918: 052005. Chakraborty S, Rahman T. The difficulties in cancer treatment. Ecancermedicalscience 2012; 6: ed16. Burguin A, Diorio C, Durocher F. Breast cancer treatments: Updates and new challenges. J Pers Med ; 11. Epub ahead of print 1 August 2021. DOI: 10.3390/jpm11080808. Fan W, Chang J, Fu P. Endocrine therapy resistance in breast cancer: Current status, possible mechanisms and overcoming strategies. Future Medicinal Chemistry 2015; 7: 1511–1519. Yip PY. Phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin (PI3K-Akt-mTOR) signaling pathway in non-small cell lung cancer. Translational Lung Cancer Research 2015; 4: 165–176. Lloyd MR, Wander SA, Hamilton E, et al. Next-generation selective estrogen receptor degraders and other novel endocrine therapies for management of metastatic hormone receptor-positive breast cancer: current and emerging role. Therapeutic Advances in Medical Oncology ; 14. Epub ahead of print 2022. DOI: 10.1177/17588359221113694. Alfakeeh A, Brezden-Masley C. Overcoming endocrine resistance in hormone receptor–positive breast cancer. Current Oncology 2018; 25: S18–S27. Fuso P, Muratore M, D’angelo T, et al. PI3K Inhibitors in Advanced Breast Cancer: The Past, The Present, New Challenges and Future Perspectives. Cancers ; 14. Epub ahead of print 1 May 2022. DOI: 10.3390/cancers14092161. Bertucci A, Bertucci F, Gonçalves A. Phosphoinositide 3-Kinase (PI3K) Inhibitors and Breast Cancer: An Overview of Current Achievements. Cancers ; 15. Epub ahead of print 1 March 2023. DOI: 10.3390/cancers15051416. Martínez-Saéz O, Chic N, Pascual T, et al. Frequency and spectrum of PIK3CA somatic mutations in breast cancer. Breast Cancer Research ; 22. Epub ahead of print 13 May 2020. DOI: 10.1186/s13058-020-01284-9. Vatte C, Al Amri AM, Cyrus C, et al. Helical and kinase domain mutations of PIK3CA, and their association with hormone receptor expression in breast cancer. Oncol Lett 2019; 18: 2427–2433. Verret B, Cortes J, Bachelot T, et al. Efficacy of PI3K inhibitors in advanced breast cancer. Annals of oncology : official journal of the European Society for Medical Oncology 2019; 30: x12–x20. Rekaya M Ben, Sassi F, Saied E, et al. PIK3CA mutations in breast cancer: A Tunisian series. PLoS One ; 18. Epub ahead of print 1 May 2023. DOI: 10.1371/journal.pone.0285413. Hu H, Zhu J, Zhong Y, et al. PIK3CA mutation confers resistance to chemotherapy in triple-negative breast cancer by inhibiting apoptosis and activating the PI3K/AKT/mTOR signaling pathway. Ann Transl Med 2021; 9: 410–410. De Mattos-Arruda L. PIK3CA mutation inhibition in hormone receptor-positive breast cancer: Time has come. ESMO Open ; 5. Epub ahead of print 17 August 2020. DOI: 10.1136/esmoopen-2020-000890. Kalinsky K, Jacks LM, Heguy A, et al. PIK3CA mutation associates with improved outcome in breast cancer. Clinical Cancer Research 2009; 15: 5049–5059. Mosele F, Stefanovska B, Lusque A, et al. Outcome and molecular landscape of patients with PIK3CA-mutated metastatic breast cancer. Annals of Oncology 2020; 31: 377–386. Sutnick AI, Gunawan S. Cancer in Indonesia. JAMA: The Journal of the American Medical Association 2020; 247: 3087–3088. The Global Cancer Observatory. Cancer Incident in Indonesia. International Agency for Research on Cancer 2020; 858: 1–2. Ishida N, Baba M, Hatanaka Y, et al. PIK3CA mutation, reduced AKT serine 473 phosphorylation, and increased ERα serine 167 phosphorylation are positive prognostic indicators in postmenopausal estrogen receptor-positive early breast cancer , www.oncotarget.com (2018). Tharin Z, Richard C, Derangère V, et al. PIK3CA and PIK3R1 tumor mutational landscape in a pan-cancer patient cohort and its association with pathway activation and treatment efficacy. Sci Rep ; 13. Epub ahead of print 1 December 2023. DOI: 10.1038/s41598-023-31593-w. Lehmann BD, Bauer JA, Schafer JM, et al. PIK3CA mutations in androgen receptor-positive triple negative breast cancer confer sensitivity to the combination of PI3K and androgen receptor inhibitors. Breast Cancer Research ; 16. Epub ahead of print 8 August 2014. DOI: 10.1186/s13058-014-0406-x. Keegan NM, Furney SJ, Walshe JM, et al. Phase ib trial of copanlisib, a phosphoinositide-3 kinase (Pi3k) inhibitor, with trastuzumab in advanced pre-treated her2-positive breast cancer “panther”. Cancers (Basel) 2021; 13: 1–13. Ponente M, Campanini L, Cuttano R, et al. PML promotes metastasis of triple-negative breast cancer through transcriptional regulation of HIF1A target genes. JCI Insight ; 2. Epub ahead of print 23 February 2017. DOI: 10.1172/JCI.INSIGHT.87380. Loi S, Haibe-Kains B, Majjaj S, et al. PIK3CA mutations associated with gene signature of low mTORC1 signaling and better outcomes in estrogen receptor-positive breast cancer. Proc Natl Acad Sci U S A 2010; 107: 10208–10213. Jabeen H, Saleemi S, Razzaq H, et al. Investigating the scavenging of reactive oxygen species by antioxidants via theoretical and experimental methods. J Photochem Photobiol B 2018; 180: 268–275. Makker A, Goel MM, Das V, et al. PI3K-Akt-mTOR and MAPK signaling pathways in polycystic ovarian syndrome, uterine leiomyomas and endometriosis: An update. Gynecological Endocrinology 2012; 28: 175–181. Shetty PK, Thamake SI, Biswas S, et al. Reciprocal Regulation of Annexin A2 and EGFR with Her-2 in Her-2 Negative and Herceptin-Resistant Breast Cancer. PLoS One ; 7. Epub ahead of print 2012. DOI: 10.1371/journal.pone.0044299. Schwartzberg LS, Vidal GA. Targeting PIK3CA Alterations in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor-2–Negative Advanced Breast Cancer: New Therapeutic Approaches and Practical Considerations. Clinical Breast Cancer 2020; 20: e439–e449. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4000099","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":309036808,"identity":"2b51f668-d879-4908-9a37-63ca7cc6fc34","order_by":0,"name":"Yan Wisnu Prajoko","email":"","orcid":"","institution":"Diponegoro University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"Wisnu","lastName":"Prajoko","suffix":""},{"id":309036809,"identity":"246d4f18-6f16-473b-8133-63281fab375e","order_by":1,"name":"Didik Setyo Heriyanto","email":"","orcid":"","institution":"Gadjah Mada University","correspondingAuthor":false,"prefix":"","firstName":"Didik","middleName":"Setyo","lastName":"Heriyanto","suffix":""},{"id":309036810,"identity":"ed5a97dd-1a81-42ec-a890-d6e139e547ea","order_by":2,"name":"Nur Dina Amalina","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYHACxgMJQKINiB//MbCRAwkdeEBAD0wLswFPRZoxTAS/FpBVDQwMbBI8Zw4nNoCE8Gnhn3b4wYGHO+xk+6SbH0hItjGnzw87/BBoi52cbgN2LRK30wwOJJ5JNm6TOWZgYNjGlrsRJJLAkGxsdgCHNbcTgFramBPbJBIMEhLbeHI3zk4AaTmQuA2HFvnb6R+AWuqBWoCMg0DScDaQgU+Lwe0ckC2HgVpyDBsbzhgkyEvn4LfF8HZOAVDLcWOglmJmhooEww3SQJEEA9x+kbudvvHhz7Zq2fkz0rf/ZjD4Ly8/O33zhw8VdnI4vY/pVLBKA2KVg4B8AymqR8EoGAWjYCQAAFnEavBMU1d6AAAAAElFTkSuQmCC","orcid":"","institution":"State University of Semarang","correspondingAuthor":true,"prefix":"","firstName":"Nur","middleName":"Dina","lastName":"Amalina","suffix":""},{"id":309036811,"identity":"2dfd5c2d-8ab2-4b18-bbcd-5f1b1c883e8d","order_by":3,"name":"Bayu Tirta Dirja","email":"","orcid":"","institution":"University of Mataram","correspondingAuthor":false,"prefix":"","firstName":"Bayu","middleName":"Tirta","lastName":"Dirja","suffix":""},{"id":309036812,"identity":"fdf48987-6112-49a7-aa34-b9d162fc841f","order_by":4,"name":"Susanto Susanto","email":"","orcid":"","institution":"Diponegoro University","correspondingAuthor":false,"prefix":"","firstName":"Susanto","middleName":"","lastName":"Susanto","suffix":""},{"id":309036813,"identity":"b8ff2e84-e37a-4cd6-ba32-56c47498196f","order_by":5,"name":"Vincent Lau","email":"","orcid":"","institution":"Gadjah Mada University","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Lau","suffix":""},{"id":309036814,"identity":"b3ff9076-44df-440d-91c8-394ec1f4c29e","order_by":6,"name":"Andrew Nobiantoro Gunawan","email":"","orcid":"","institution":"Gadjah Mada University","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"Nobiantoro","lastName":"Gunawan","suffix":""}],"badges":[],"createdAt":"2024-02-29 14:18:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4000099/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4000099/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59015748,"identity":"e9fe1fa0-953f-43ba-8204-153ca013d300","added_by":"auto","created_at":"2024-06-25 10:26:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":588748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4000099/v1/4ccdef62-12a1-4301-a164-005a593dbdee.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUnveiling the genetic landscape: high frequency of pik3ca mutation in luminal a and b breast cancer within the Indonesian population\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer (BC) is a public health problem that has a high mortality rate for women around the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is the second most common cause of cancer death after lung cancer in women, with more than one million new cases diagnosed each year [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Molecular biomarkers and their correlation with pathological parameters are essential for diagnosis, prognosis, predictive utility, management, and prevention of BC [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition to the adverse impacts caused by industrial-induced pollutants or mental-related endocrine changes, BC is known as a complex and heterogeneous disease, triggered by genomic variation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Statistically, 5\u0026ndash;10% of breast cancers are caused primarily by genetic factors caused by the accumulation of acquired somatic changes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInvasive BC is primarily categorized into four molecular subtypes using immunohistology analysis, based on the expression status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Luminal A BC, which is positive for either or both ER and PR and negative for HER2, accounts for 50\u0026ndash;60% of BC cases and generally has a favorable prognosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Luminal B BC, positive for ER and/or PR and HER2, constitutes about 30% of BC cases [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Luminal B BC is characterized by high levels of ki67, a marker of cell proliferation, and typically has a poor prognosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. HER2 Enriched BC, which is ER and PR negative but HER2 positive, represents around 15\u0026ndash;20% of BC cases [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This subtype is associated with a poor prognosis but can be effectively treated with HER2-targeted therapies [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Triple-negative BC (TNBC), which is negative for ER, PR, and HER2, accounts for 10\u0026ndash;20% of BC cases. TNBC is associated with a poor prognosis due to its aggressive nature and lack of targeted therapies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTreatment regimens for luminal A and B breast cancer (HR\u0026thinsp;+\u0026thinsp;BC) typically integrate various modalities, including chemotherapy, surgery, radiotherapy, and adjuvant therapies such as endocrine therapy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Endocrine therapy has emerged over recent decades as a safe and efficacious personalized approach for HR\u0026thinsp;+\u0026thinsp;BC patients. Established endocrine therapies encompass Selective Estrogen Receptor Modulators (SERMs) like tamoxifen, Selective Estrogen Receptor Degraders (SERDs) such as Fulvestrant, and Aromatase Inhibitors (AIs) including exemestane and letrozole [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, a primary challenge associated with endocrine therapy is the development of acquired or intrinsic resistance [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. SERDs and AIs can induce resistance through various mechanisms, including the upregulation of signaling pathways such as phosphatidylinositol 3-kinase (PI3K), mammalian target of rapamycin (mTOR), and extracellular signal-regulated kinase (Ras-ERK) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These pathways offer alternative routes for HR\u0026thinsp;+\u0026thinsp;BC to evade treatment and sustain cancer cell proliferation and survival [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In response to these challenges, researchers are actively developing novel therapeutics to circumvent estrogen-independent cell survival, targeting key mechanisms of resistance, notably the PI3K/Akt/mTOR pathway [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These emerging therapies, currently undergoing clinical trials, hold promise in overcoming endocrine therapy resistance. Leading examples include pan-PI3K inhibitors (e.g., Buparlisib, Pictilisib) and isoform-specific PI3K inhibitors (e.g., Alpelisib, Taselisib) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe PI3Ks represent a family of lipid kinases classified into three classes based on their structures and substrate specificities. Among the primary examples is the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) gene [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Somatic alterations in the PIK3CA gene stand out as one of the most prevalent genetic triggers in breast cancer, with a frequency estimated at approximately 30\u0026ndash;40% [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Positioned on chromosome 3q26.32, the PIK3CA gene encodes the alpha isoform (p110α), the principal isoform of the catalytic subunit within the class 1A phosphatidylinositol 3-kinase (PI3K), a lipid phosphokinase [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Functionally, the PI3K family mediates signals crucial for various cellular activities, encompassing proliferation, metabolism, migration, translation, apoptosis evasion, and angiogenesis. Predominantly, mutations in breast cancer localize to three hot spots (HS): E542K and E545K on exon 9, encoding the helical domain (HD), and H1047R on exon 20, encoding the kinase domain (KD) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Previous research has indicated that endocrine-resistant PIK3CA-mutant cases may potentially benefit from treatment with PI3K inhibitors, underscoring the significance of elucidating the prevalence of PIK3CA mutations among populations to inform potential future avenues in hormone receptor-positive breast cancer treatment [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch underscores the significance of analyzing PIK3CA gene mutations due to their association with the onset and progression of breast cancers (BCs). These mutations are detected in 20\u0026ndash;40% of BC patients [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Studies suggest that the presence of PIK3CA mutations can negatively impact disease-free survival (DFS) and pathological complete response (pCR) to targeted therapy and chemotherapy in patients with HER2-enriched and triple-negative breast cancer (TNBC) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This suggests the potential benefit of assessing PIK3CA mutations in all molecular subtypes of BC, including non-hormonal subtypes. However, there is a noticeable lack of data on this subject, particularly in the Indonesian population. Recently, numerous studies have examined BC PIK3CA mutations in various countries and regions, revealing inconsistencies in the results regarding the clinical pathological characteristics of PIK3CA mutation [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Small sample sizes, different detection methods, and varying inclusion criteria are likely contributing factors to these inconsistent outcomes.\u003c/p\u003e \u003cp\u003eThe aim of this study is to determine the prevalence of PIK3CA mutations among the Indonesian population and to identify potential correlations between these mutations and established clinicopathological profiles of breast cancer patients. This research carries considerable importance in the context of breast cancer management in Indonesia, as there is presently a dearth of national data regarding the prevalence of PIK3CA mutations and associated clinicopathological information among breast cancer patients in the country. It is envisaged that this investigation will serve as a catalyst for further exploration of PIK3CA in Indonesian breast cancer patients, thereby potentially facilitating substantial progress in comprehending and addressing this disease.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eEthical approval for this study was granted by the Medical and Health Research Ethics Committee (MHREC) under Ethical Approval Number No.32/EC/KEPK/FK-UNDIP/II/2023.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study employed a cross-sectional approach to analyze samples obtained from the archive of Cito Clinical Laboratory, Indonesia, spanning the period from 2019 to 2022. The samples were collected from various islands across the Indonesian archipelago, including Java, Kalimantan, Sumatera, Mataram, and Papua. Histopathological examination and grading of Breast Cancer (BC) samples were conducted, as necessary. Subsequently, the samples underwent immunohistochemistry (IHC) analysis to determine their molecular subtypes. Finally, genetic analysis was performed on each viable sample to identify the presence of any PIK3CA mutations.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eBreast Cancer Sample\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eParaffin blocks obtained from patients histopathologically diagnosed with primary breast cancer, including Invasive Breast Carcinoma of No Special Type (NST), Invasive Lobular Carcinoma, Invasive Papillary Carcinoma, and Mucinous Carcinoma of the breast, were included in this study. Samples were collected from multiple centers situated in various provinces across the diverse islands of Indonesia. Histological evaluation was conducted by two pathologists, and exclusion criteria comprised FFPE samples of inadequate quality and incomplete medical records data. Patient data regarding clinico-pathological characteristics, including sociodemographic factors (age), tumor pathology (location/site, histopathology, histologic grade), and clinical parameters, were acquired.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eImmunohistochemistry Staining\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis study comprised 207 cases of diverse breast cancer (BC) types. Immunohistochemistry (IHC) was employed to examine the samples, utilizing anti-estrogen receptor (ER), anti-progesterone receptor (PR), anti-human epidermal growth factor receptor 2 (HER2), and anti-Ki67 antibodies from Ventana\u0026trade;. Staining procedures were conducted utilizing the Ventana BenchMark XT and Discovery XT\u0026trade; Tissue Diagnostic and IHC autostainer. All protocols strictly adhered to the manufacturer\u0026rsquo;s instructions and protocols to ensure the attainment of consistent and reliable results.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDNA extraction\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eParaffin blocks from\u0026nbsp;various\u0026nbsp;breast cancer subtypes were cut into\u0026nbsp;10\u0026nbsp;pieces with 5\u0026mu;m thickness.\u0026nbsp;Ten\u0026nbsp;pieces in one slide continued with DNA extraction. Genomic DNA was extracted using the\u0026nbsp;GeneAll\u0026reg; Exgene\u0026trade; FFPE Tissue DNA\u0026nbsp;according to the manufacturer\u0026apos;s protocol. DNA samples were then quantified using a NanoDrop\u0026trade; spectrophotometer (Thermo Scientific, Waltham, MA, USA). Samples of sufficient concentration and quality were adjusted to a concentration of 20 ng/\u0026micro;L for PCR applications.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDetection of PIK3CA Mutation\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe samples were further analyzed for PIK3CA mutation at both Cito Clinical Laboratory and the Department of Anatomical Pathology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada. Specimens originating from islands other than Java were meticulously transported to Yogyakarta, ensuring strict adherence to established standards. The detection of PIK3CA mutation biomarkers was conducted using the BioColomelt-Dx\u0026trade; in vitro diagnostics kit, developed by Biofarma Ltd, Indonesia. This molecular diagnostic kit utilizes Polymerase Chain Reaction (PCR) and High-Resolution Melting (HRM) techniques. Subsequently, the findings were validated using the Qiagen therascreen\u0026reg; PIK3CA RGQ PCR kit. The Qiagen Therascreen\u0026reg; kit is a Real-Time (RT) qualitative PCR test designed for the detection of 11 gene mutations in the PIK3CA gene, including PIK3CA Exon 9 and 20, utilizing FFPE DNA samples.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe statistical analysis was conducted using Excel and IBM SPSS version 27. The correlation between variables was calculated using Fisher\u0026apos;s exact test with a significance level of \u0026alpha;= 0.05.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003e\u003cstrong\u003eClinicopathologic characteristics of the breast cancer samples\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe characteristics of the samples are summarized in Table 1. A total of 104 (50.2%) samples were obtained from the right breast, while 103 (49.8%) samples were obtained from the left breast. The mean age of the patients was 56 years old. Histopathological types included 4 (1.9%) samples of grade I Invasive Breast Carcinoma of No Special Type (IBC-NST), 81 (39.1%) samples of grade II IBC-NST, 84 (40.6%) samples of grade III IBC-NST, 34 (16.4%) samples of Invasive Lobular Carcinoma, 1 (0.5%) sample of Invasive Papillary Carcinoma, and 3 (1.4%) samples of Mucinous Carcinoma. Molecular Subtypes, as determined by Immunohistochemistry Evaluation, comprised 102 (49.3%) samples of Luminal A, 37 (17.9%) samples of Luminal B HER-2 (negative), 21 (10.1%) samples of Luminal B HER-2 (positive), 20 (9.7%) samples of HER-2 Enriched, and 27 (13%) samples of triple-negative breast cancer (TNBC).\u003c/p\u003e\n\u003cp\u003eTable 1. Clinicopathology characteristics of the study samples \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\" rowspan=\"2\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"28\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003e\u0026le; 50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e75 \u0026nbsp;(36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003e\u0026gt; 50 years old\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e132 \u0026nbsp;(63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eRight Breast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e104 (50.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eLeft Breast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e103 (49.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eHistopathology Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e4 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e81 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e84 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eInvasive Lobular Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e34 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eInvasive Papillary Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e1 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eMucinous Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e3 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC Evaluation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e102 (49.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eLuminal B HER-2 (negative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e37 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eLuminal B HER-2 (positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e21 (10.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eHER-2 Enriched\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e20 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003eTNBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e27 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003ePIK3CA Mutation Status in Breast Cancer Samples\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA total of 75 (36.2%) samples showed positive PIK3CA mutation (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Frequency of the PIK3CA mutations in breast cancer samples \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\" rowspan=\"2\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"28\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003ePIK3CA mutation status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.58532695374801%\"\u003e\n \u003cp\u003ePositive (Mutated)\u003c/p\u003e\n \u003cp\u003eNegative (Wild type)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.414673046251995%\"\u003e\n \u003cp\u003e75 (36.2%)\u003c/p\u003e\n \u003cp\u003e132 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 illustrates the correlation between clinicopathological features and the PIK3CA mutation status. Notably, a substantial proportion of samples from patients aged over 50 years (34.1%) exhibited PIK3CA mutation; however, no significant association between mutation status and patient age was observed (p \u0026gt; 0.05). Similarly, no discernible correlation was found between mutation status and tumor location, whether in the right or left breast (p \u0026gt; 0.05). Regarding Invasive Breast Carcinoma (IBC) grades, mutations were more prevalent in higher grades (Grade I: 25%; Grade II: 35.8%; Grade III: 42.9%). Nonetheless, no definitive association between histopathology diagnosis and PIK3CA mutation status was established. These findings suggest that mutation status does not significantly correlate with age, tumor location, or histopathology diagnosis in breast cancer cases; rather, these variables appear to be independent based on the dataset analyzed. However, a noteworthy discovery in this study was the significant association between PIK3CA mutation status and molecular subtypes as determined by immunohistochemistry evaluation (p=0.01; p\u0026lt;0.05). Specifically, PIK3CA mutations were more prevalent in Luminal A breast cancer samples (mutation rate: 46.1%) and Luminal B HER-2 (negative) breast cancer samples (mutation rate: 40.5%), compared to Luminal B HER-2 (positive), HER-2 enriched, and triple-negative breast cancer (TNBC) subtypes (mutation frequencies: 19%, 20%, 18.5%, respectively), which exhibited lower mutation frequencies than the overall mutation frequency of 36.2% (refer to Table 2).\u003c/p\u003e\n\u003cp\u003eTable 3. Association between the Clinicopathology Characteristics and PIK3CA mutation status in breast cancer samples\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"628\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\" rowspan=\"3\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.94267515923567%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePIK3CA Mutation Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.8448275862069%\"\u003e\n \u003cp\u003eNegative (Wildtype), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52.1551724137931%\"\u003e\n \u003cp\u003ePositive (Mutated), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003e\u0026le; 50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e45 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e30 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003e\u0026gt; 50 years old\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e87 (65.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e45 (34.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eRight Breast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e69 (66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e35 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eLeft Breast\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e\u0026nbsp;63 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e40 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eHistopathology Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e3 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e1 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e52 (64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e29 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST, Grade III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e48 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e36 (42.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eInvasive Lobular Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e26 (76.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e8 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eInvasive Papillary Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eMucinous Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e3 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC Evaluation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e0.01*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e55 (53.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e47 (46.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eLuminal B HER-2 (negative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e22 (59.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e15 (40.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eLuminal B HER-2 (positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e17 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e4 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eHER-2 Enriched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e16 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e4 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.968152866242036%\"\u003e\n \u003cp\u003eTNBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.67515923566879%\"\u003e\n \u003cp\u003e22 (81.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.26751592356688%\"\u003e\n \u003cp\u003e5 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.089171974522294%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Fisher\u0026apos;s exact test p\u0026lt;0.05. Abbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer.\u003c/p\u003e\n\u003cp\u003eTable 4 showed that findings of the study indicate a strong correlation between histopathology diagnosis and molecular subtypes of breast cancer (p=0.007; p\u0026lt;0.01). Notably, Luminal A BC is most commonly observed in IBC of NST compared to all other molecular subtypes. On the other hand, Luminal B HER-2 (positive), HER-2 Enriched, Luminal B HER-2 (negative) BC, and TNBC are frequently observed in IBC of NST, with proportions of 90.5%, 75%, 67.6%, and 66.7% respectively.\u003c/p\u003e\n\u003cp\u003eTable 4. Association between Clinicopathology Characteristics in breast cancer samples (IHC vs Histopathology Diagnosis)\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"625\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" rowspan=\"3\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.88%\" colspan=\"4\" rowspan=\"2\"\u003e\n \u003cp\u003eHistopathology Diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.604966139954854%\"\u003e\n \u003cp\u003eInvasive Breast Carcinoma of NST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.733634311512414%\"\u003e\n \u003cp\u003eInvasive Lobular Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.959367945823928%\"\u003e\n \u003cp\u003eInvasive Papillary Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.702031602708804%\"\u003e\n \u003cp\u003eMucinous Carcinoma of the Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e0.007*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e92 (90.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e8 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e2 (2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"29\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eLuminal B HER-2 (negative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e25 (67.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e10 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e1 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e1 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"29\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eLuminal B HER-2 (positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e19 (90.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e2 (9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"29\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eHER-2 Enriched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e15 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e5 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003eTNBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.44%\"\u003e\n \u003cp\u003e18 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.24%\"\u003e\n \u003cp\u003e9 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.4%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.12%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Fisher\u0026apos;s exact test p\u0026lt;0.05. Abbreviations: NST = No Special Type, IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer.\u003c/p\u003e\n\u003cp\u003eTable 5 showed that there is no significant association between PIK3CA mutation status and different luminal molecular subtypes (p\u0026gt;0.05). However, we found that the Luminal B HER-2 (positive) subtype has a lower mutation frequency of 19% compared to the 46.1% and 40.5% of Luminal A and Luminal B HER-2 (negative) BC respectively. Within the Luminal Mutated PIK3CA tumors, only 4 of 66 samples (6%) are Luminal B HER-2 (positive).\u003c/p\u003e\n\u003cp\u003eTable 5. Association between the Luminal Hormonal Receptor Positive Molecular Subtypes and PIK3CA mutation status in breast cancer samples\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\" rowspan=\"3\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.00159489633174%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003ePIK3CA Mutation Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eNegative (Wildtype), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003ePositive (Mutated), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC Evaluation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e55 (51.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e47 (46.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal B HER-2 (negative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e22 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e15 (40.5.%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal B HER-2 (positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e17 (81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e4 (19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Fisher\u0026apos;s exact test p\u0026lt;0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2.\u003c/p\u003e\n\u003cp\u003eTable 6 showed that there is no significant association between PIK3CA mutation status with the TNBC and HER-2 enriched molecular subtypes. Similarly, both HER-2 enriched and TNBC showed lower mutation frequency compared to overall PIK3CA mutation frequency.\u003c/p\u003e\n\u003cp\u003eTable 6. Association between the TNBC and HER-2 Molecular Subtypes and PIK3CA mutation status in breast cancer samples\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\" rowspan=\"3\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.00159489633174%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003ePIK3CA Mutation Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003eNegative (Wildtype), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003ePositive (Mutated), \u0026nbsp;N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"17\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC Evaluation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eHER-2 Enriched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e16 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e4 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eTNBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e22 (81.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e5 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Fisher\u0026apos;s exact test p\u0026lt;0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer.\u003c/p\u003e\n\u003cp\u003eUpon a more comprehensive analysis as presented in Table 7, it was observed that there is no statistically significant association between age groups and molecular subtypes in PIK3CA positive (mutated) samples. Nevertheless, it is evident that there is a higher prevalence (68.1%) of older (\u0026gt;50 years old) patients in Luminal A with PIK3CA positive (mutated) samples. \u0026nbsp;When comparing between molecular subtypes in those who are \u0026gt;50 years old , it is also evident that Luminal A is the most prevalent molecular subtype (71%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 7. Association between each molecular subtypes and age in PIK3CA positive (mutated) breast cancer samples\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"627\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\" rowspan=\"3\"\u003e\n \u003cp\u003eCharacteristic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.00159489633174%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" height=\"55\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026le; 50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u0026gt; 50 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eMolecular Subtypes (IHC Evaluation) in PIK3CA Positive (Mutated) Samples\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e15 (31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e32 (68.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal B HER-2 (negative)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e8 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e7 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eLuminal B HER-2 (positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e3 (75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e1 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eHER-2 Enriched\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e2 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e2 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.49760765550239%\"\u003e\n \u003cp\u003eTNBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e2 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.50079744816587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\" height=\"30\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Fisher\u0026apos;s exact test p\u0026lt;0.05. Abbreviations: IHC = Immunohistochemistry, HER-2 = Human Epidermal Growth Factor-2, TNBC = Triple Negative Breast Cancer.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe phosphatidylinositol-3-kinase (PI3K) pathway plays a pivotal role in the proliferation and viability of malignant cells and is frequently dysregulated in various types of cancer, including breast cancer (BC). This deregulation can occur through several mechanisms, such as mutations or amplifications in PI3K itself, the inactivation of the tumor suppressor PTEN, or the activation of upstream oncogenes and tyrosine kinase growth factor receptors [34].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePIK3CA mutations have been extensively studied in newly diagnosed BC, often linked to favorable characteristics like positive ER expression, smaller tumor size, and low histological grade [35]. Two recent studies also found that PIK3CA mutations were associated with older age and lower tumor grade at diagnosis [36].However, these mutations show variable prevalence and implications across different studies and populations. For example, a study in Yogyakarta, Indonesia found that Luminal A subtype is frequently observed in Grade I tumors, whereas Grade III tumors are more commonly associated with the Luminal B, HER2 enriched, and Triple-Negative Breast Cancer (TNBC) [37, 38]. These findings exhibit a divergent pattern compared to our study, potentially attributable to variances in sample populations across different provinces and regions within Indonesia [38]. Recent studies from different populations have also presented conflicting results regarding the relationship between PIK3CA mutations and tumor grading, adding the layer of complexity [39]. PIK3CA wild-type tumors had lower tumor grade, higher ER expression, and lower AR expression compared to mutant tumors, contradictory with recent findings that there was no significant correlation between histological Scarff-Bloom-Richardson (SBR) tumor grading and PIK3CA mutation status [40]. On the other hand, our study is in accordance with the study by Cizkova that showed that PIK3CA mutations are predominantly found in higher-grade tumors, particularly SBR grade II [41]. Due to the inconclusive findings, additional investigation is warranted, encompassing a greater sample size and a more comprehensive representation of the entirety of the Indonesian center.\u003c/p\u003e\n\u003cp\u003eOur findings indicate a decreasing prevalence of PIK3CA mutation across different molecular subtypes, with the highest frequency observed in Luminal A subtype, followed by Luminal B HER-2 (negative), HER-2 enriched, Luminal B HER-2+, and TNBC subtypes. The results are partially consistent with the research conducted by Wu et al. (2019). Nonetheless, the study failed to further categorize Luminal B into Luminal B HER-2 negative or Luminal B HER-2+ [42].\u003c/p\u003e\n\u003cp\u003eTherapeutically, the presence of PIK3CA mutations has been linked to reduced rates of achieving pathological complete response (pCR) in neoadjuvant chemotherapy, indicating potential chemoresistance [43, 44]. Moreover, these mutations have been associated with resistance to anti-HER2 treatment in HER2 enriched patients and endocrine treatment in ER+ patients [28, 31].\u003c/p\u003e\n\u003cp\u003ePrevious study reported that ER-positive, HER2-negative, PIK3CA mutant breast cancers, despite apparent PI3K/AKT pathway activation, downstream mTOR1 signaling was not greatly elevated at the transcriptional and biological levels. One of their hypotheses for underlying the mechanism is that PIK3CA mutations are associated with weak pathway activation, and that other PI3K pathway alterations produce stronger pathway activation. The study suggests that, in ER+/HER2\u0026minus; BC with PIK3CA mutations, pathway activation surprisingly does not result in greatly elevated downstream signaling and their functional output differs substantially compared with that of PTEN loss\u0026nbsp;[24, 44].\u003c/p\u003e\n\u003cp\u003eThe mechanism underlying these observations could be mediated by unknown genes. Potential candidates are PP2A and/or PML, both known negative regulators of AKT1 and mTOR, and both present in the larger gene signature list [44]. This mechanism appears to be specific to TNBC cells and is not observed in other BC subtypes where PML and prometastatic HIF1A target genes are underexpressed. As a consequence, PML promotes cell migration, invasion, and metastasis in TNBC cell and mouse models [10, 33, 45, 46]. A study revealed that loss of specific PP2A regulatory subunits is functionally important in breast tumorigenesis, and support strategies to enhance PP2A activity as a therapeutic approach in breast cancer [33].\u003c/p\u003e\n\u003cp\u003eApproximately 30-40% of breast cancer cases that are positive for HER2 enriched exhibit a mutation in the PIK3CA gene. In a study, the presence of PIK3CA mutation in circulating tumor DNA (ctDNA) was observed in all patients who tested negative for the mutation in the tissue. Suggesting the prevalence of PIK3CA mutation in HER2 enriched breast cancer may be inaccurately assessed through the examination of stored tissue samples, such as in our study. As a result, the implementation of liquid biopsy as a valuable method to more effectively capture temporal heterogeneity is proposed in another study\u0026nbsp;[33]. This approach has the potential to increase the number of patients who may derive therapeutic benefits from targeted treatments, since such mutations have been associated with trastuzumab resistance in HER2+ patients\u0026nbsp;[18, 47].\u003c/p\u003e\n\u003cp\u003eThe presence of PIK3CA gene mutations has been observed in approximately 9% of TNBC, including cases that recur as metastatic tumors after initial hormone receptor-positive (HR+) breast cancer. In such cases, the PIK3CA mutation has been found to persist. TNBC can be classified into six subtypes according to gene expression, as proposed by Lehman. Among these subtypes, the luminal androgen receptor (LAR) and mesenchymal stem-like (MSL) subtypes exhibit a greater prevalence of PIK3CA mutations\u0026nbsp;[41]. The role of PIK3CA mutations and alterations in the PI3K/AKT pathway is of significant importance in breast cancer biology. However, their significance is more comprehensively understood in HR+/HER2- breast cancer in comparison to TNBC and HER2 enriched breast cancer, which necessitate additional research endeavors\u0026nbsp;[33].\u003c/p\u003e\n\u003cp\u003eThe overall survival (OS) of patients with PIK3CA-mutated metastatic triple-negative breast cancer (mTNBC) was found to be higher compared to patients with PIK3CA wild-type (WT) mTNBC. The presence of PIK3CA mutations in early TNBC patients has been linked to the expression of the androgen receptor and apocrine subtype\u0026nbsp;[41, 48]. Additionally, these mutations have shown an inverse correlation with immune system activation and PTEN alterations\u0026nbsp;[41]. The alteration of the PI3K/AKT/PTEN pathway has been found in 25% \u0026ndash; 40% patients with mTNBC. This finding provides support for research in the PIK3/AKT/PTEN pathway and its inhibitors\u0026nbsp;[36].\u003c/p\u003e\n\u003cp\u003eIn the clinical setting of TNBC and HER2 enriched subtypes, it is important to highlight their aggressive features. These types of breast cancers demonstrate wild-type (WT) status in relation to PIK3CA mutations. The presence of other complex pathways that have substantial roles in the development of breast cancer across different molecular subtypes may explain this phenomenon. In order to advance future research, it is crucial to conduct further investigation into the PIK3/AKT/PTEN and mTOR pathways, as they are closely associated with PIK3CA. Moreover, it is imperative to conduct protein expression level analysis in order to obtain a comprehensive comprehension of the involvement of these pathways in triple-negative breast cancer (TNBC) and HER2-enriched subtypes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrevious studies have demonstrated that the growth and viability of AR\u0026thinsp;+\u0026thinsp;TNBC cell line models can be significantly diminished through the administration of PI3K inhibitors in conjunction with an AR antagonist. Hence, these findings provide a strong justification for the pre-selection of patients with triple-negative breast cancer (TNBC) using a biomarker, namely androgen receptor (AR) expression, in order to investigate the potential application of AR antagonists in conjunction with PI3K/mTOR inhibitors [41]. Regrettably, our study solely focused on the fundamental molecular subtypes of triple-negative breast cancer (TNBC) and did not encompass the additional six subtypes proposed by Lehman. Hence, it is imperative for future investigations to incorporate these supplementary subtypes, particularly in the context of triple-negative breast cancer (TNBC).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our sincere gratitude to all those who contributed to the completion of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by grants from the Ministry of Education, Culture, Research, and Technology, Indonesia under national collaborative research scheme 2023. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYWP and DSH conceptualized and designed the study, analyzed the data, and conceptualized and wrote the manuscript; NDA, VL, and ANG conducted the experiments, analyzed the data, and drafted the manuscript; BTD and SS analyzed the data and designed the part of the study; YWP provided of study materials and data analysis; DSH provided study material data interpretation; YWP and NDA conceptualized the study and provide the manuscript. The final version of the manuscript was approved by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCORESSPONDING AUTHOR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Yan Wisnu Prajoko\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS DECLARTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS APPROVAL AND CONSNET TO PARTICIPATE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in 2023 to 2024 with written informed consent. Ethical approval was obtained from the Medical and Health Research Ethics Committee (MHREC) under Ethical Approval Number No.32/EC/KEPK/FK-UNDIP/II/2023. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONSENT FOR PUBLICATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShumway DA, Sabolch A, Jagsi R. Breast Cancer. \u003cem\u003eMed Radiol\u003c/em\u003e 2020; 1\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eGiaquinto AN, Sung H, Miller KD, et al. 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Epub ahead of print 2012. DOI: 10.1371/journal.pone.0044299.\u003c/li\u003e\n\u003cli\u003eSchwartzberg LS, Vidal GA. Targeting PIK3CA Alterations in Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor-2\u0026ndash;Negative Advanced Breast Cancer: New Therapeutic Approaches and Practical Considerations. \u003cem\u003eClinical Breast Cancer\u003c/em\u003e 2020; 20: e439\u0026ndash;e449.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PIK3CA mutation, breast cancer, Indonesia population","lastPublishedDoi":"10.21203/rs.3.rs-4000099/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4000099/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Breast cancer (BC) is a global health concern with significant mortality rates, necessitating a deep understanding of its molecular landscape. Objective: This study focuses on the prevalence of phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations in Luminal A and B BC within the Indonesian population. Luminal A and B BC, characterized by estrogen receptor (ER) and/or progesterone receptor (PR) positivity, face challenges in endocrine therapy due to acquired resistance, often mediated by PI3K/Akt/mTOR pathway activation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The study, conducted from 2019 to 2022, collected samples from diverse Indonesian regions, representing various islands. Histopathological analysis and immunohistochemistry classified samples into molecular subtypes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Genetic analysis using PIK3CA mutation detection kits revealed a mutation frequency of 36.2%, with Luminal A BC exhibiting the highest mutation rate (46.1%). Notably, Luminal B HER-2 (positive) BC demonstrated a lower mutation frequency (19%). Statistical analyses highlighted correlations between PIK3CA mutations and molecular subtypes (p=0.01), with Luminal A and Luminal B HER-2 (negative) BC showing higher mutation frequencies. No significant associations were observed with age, tumor location, or histopathology diagnosis. Luminal A BC demonstrated a higher prevalence of PIK3CA mutations in patients over 50 years old (68.1%). Comparisons with existing literature and inconsistencies in PIK3CA mutation prevalence across different BC subtypes underline the need for population-specific research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The study emphasizes the importance of assessing PIK3CA mutations in BC management, offering insights for personalized therapies and potential advancements in understanding this complex disease within the Indonesian context.\u003c/p\u003e","manuscriptTitle":"Unveiling the genetic landscape: high frequency of pik3ca mutation in luminal a and b breast cancer within the Indonesian population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 17:33:17","doi":"10.21203/rs.3.rs-4000099/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d37dff61-1d12-47d5-a1ae-ec334463f26d","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-25T10:17:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-03 17:33:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4000099","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4000099","identity":"rs-4000099","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}