Phosphatidylinositol 3-kinase Catalytic Alpha Research Articles

Computational pathology to improve biomarker testing in breast cancer: how close are we?

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided.

Using an Improved Residual Network to Identify PIK3CA Mutation Status in Breast Cancer on Ultrasound Image.

BackgroundThe detection of phosphatidylinositol-3 kinase catalytic alpha (PIK3CA) gene mutations in breast cancer is a key step to design personalizing an optimal treatment strategy. Traditional genetic testing methods are invasive and time-consuming. It is urgent to find a non-invasive method to estimate the PIK3CA mutation status. Ultrasound (US), one of the most common methods for breast cancer screening, has the advantages of being non-invasive, fast imaging, and inexpensive. In this study, we propose to develop a deep convolutional neural network (DCNN) to identify PIK3CA mutations in breast cancer based on US images.Materials and MethodsWe retrospectively collected 312 patients with pathologically confirmed breast cancer who underwent genetic testing. All US images (n=800) of breast cancer patients were collected and divided into the training set (n=600) and test set (n=200). A DCNN-Improved Residual Network (ImResNet) was designed to identify the PIK3CA mutations. We also compared the ImResNet model with the original ResNet50 model, classical machine learning models, and other deep learning models.ResultsThe proposed ImResNet model has the ability to identify PIK3CA mutations in breast cancer based on US images. Notably, our ImResNet model outperforms the original ResNet50, DenseNet201, Xception, MobileNetv2, and two machine learning models (SVM and KNN), with an average area under the curve (AUC) of 0.775. Moreover, the overall accuracy, average precision, recall rate, and F1-score of the ImResNet model achieved 74.50%, 74.17%, 73.35%, and 73.76%, respectively. All of these measures were significantly higher than other models.ConclusionThe ImResNet model gives an encouraging performance in predicting PIK3CA mutations based on breast US images, providing a new method for noninvasive gene prediction. In addition, this model could provide the basis for clinical adjustments and precision treatment.

A Signature of Three Apoptosis-Related Genes Predicts Overall Survival in Breast Cancer.

BackgroundThe commonest malignancy in women is known as breast cancer (BC). Numerous studies demonstrated that apoptosis appears to be critical to the management and clinical outcome of BC patients. The purpose of this study is to explore the potential connection between apoptosis and BC and establish the apoptosis-associated gene signature in BC.MethodsThe data of BC patient transcripts and related clinical information comes from the Cancer Genome Atlas Database (TCGA), and the genes related to apoptosis come from the Molecular Characterization Database (MSigDB). We identified the abnormally expressed apoptosis-related genes in BC samples. The optimal apoptosis-related genes screened by Cox regression analysis were designed to construct a prognostic model for predicting BC patients. Using the Nom Chart to Predict 1-Year, 3-Year, and 5-Year overall survival for BC patients. The gene signature-related functional pathways were explored by gene set enrichment analysis (GSEA).ResultsThree genes [alpha subunit of the interleukin 3 receptor (IL3RA), apoptosis-inducing factor mitochondrial-associated 1 (AIFM1), and phosphatidylinositol-3 kinase catalytic alpha (PIK3CA)] correlated with apoptosis were shown to be strongly linked to the overall survival of BC. Survival analysis shows that the risk score is directly proportional to the poor prognosis of BC patients. Risk assessment based on three genetic characteristics (age, pathological stage N, and pathological stage M) can independently predict the prognosis of patients with BC. The Nom chart is most suitable for assessing the long-term survival rate of BC patients. The results of GSEA demonstrated that numerous cell cycle-related pathways were abundant in the high-risk group.ConclusionWe constructed an apoptosis-associated gene signature in BC, which had a potential clinical application prospect for BC patients.

MFOLFOXIRI with or without bevacizumab for conversion therapy of RAS/BRAF/PIK3CA mutant unresectable colorectal liver metastases: the FORBES non-randomized phase II trial.

BackgroundThe aim of this non-randomized single-center phase II trial was to prospectively assess the clinical efficacy of triplet chemotherapy with modified 5-fluorouracil, folinic acid, oxaliplatin, and irinotecan (mFOLFOXIRI) plus bevacizumab as conversion therapy for initially unresectable rat sarcoma viral oncogene homolog (RAS)/v-raf murine sarcoma viral oncogene homolog B1 (BRAF)/phosphatidylinositol-3 kinase catalytic alpha (PIK3CA) mutant colorectal liver-limited metastases (CRLMs).MethodsPatients with RAS/BRAF/PIK3CA mutant initially unresectable CRLMs were recruited at a ratio of 2:1 to receive mFOLFOXIRI plus bevacizumab (experimental group) or mFOLFOXIRI alone (control group). The rate of patients attaining no evidence of disease (NED) was the primary endpoint. The secondary endpoints included objective response rate (ORR), depth of tumor response (DpR), secondary resection rate, progression-free survival (PFS), overall survival (OS), and safety.ResultsThe rate of NED achieved was 40.7% and 30.8%, respectively, in the experimental (n=54) and control groups (n=26); the adjusted odds ratio was 4.519 [95% confidence interval (CI): 1.247–16.375, P=0.022]. The ORR was 77.4% in the experimental group and 60.0% in the control group (P=0.112). The median DpR was significantly greater in the experimental group (45.6% vs. 34.9%, P=0.041). The median PFS was 12.6 months in the experimental group and 9.1 months in the control group [adjusted hazard ratio (HR): 0.584, 95% CI: 0.304–1.121, P=0.106]. Median OS was prolonged in the experimental group compared with the control group (42.6 vs. 35.3 months, adjusted HR: 0.443, 95% CI: 0.195–1.006, P=0.052). Thirty patients (55.6%) in the experimental group and 16 (61.5%) in the control group experienced grade 3/4 adverse events.ConclusionsWe observed that the combination of mFOLFOXIRI and bevacizumab increased the rate of clinical NED and showed a trend toward improved survival compared with mFOLFOXIRI alone. This could represent a conversion therapy option for fit patients with initially unresectable RAS/BRAF/PIK3CA mutant CRLMs.

Somatic mosaicism of the PIK3CA gene identified in a Hungarian girl with macrodactyly and syndactyly

Isolated macrodactyly (OMIM 155500) belongs to a heterogeneous group of overgrowth syndromes. It is a congenital anomaly resulting in enlargement of all tissues localized to the terminal portions of a limb and caused by somatic mutations in the phosphatidylinositol 3-kinase catalytic alpha (PIK3CA, OMIM 171834) gene. Here we report a Hungarian girl with macrodactyly and syndactyly. Genetic screening at hotspots in the PIK3CA gene identified a mosaic mutation (c.1624G > A, p.Glu542Lys) in the affected tissue, but not in the peripheral blood. To date, this somatic mutation has been reported in eight patients affected by different forms of segmental overgrowth syndromes. Detailed analysis of the Hungarian child and previously reported cases suggests high phenotypic diversity associated with the p.Glu542Lys somatic mutation. The identification of the mutation provides a novel therapeutic modality for the affected patients: those who carry somatic mutations in the PIK3CA gene are potential recipients of a novel “repurposing” approach of rapamycin treatment.

Absence of hotspot mutations in exons 9 and 20 of the PIK3CA gene in human oral squamous cell carcinoma in the Greek population

Phosphatidylinositol-3 kinases (PI3K) are a group of heterodimeric lipid kinases that regulate many cellular processes. Recent studies have reported high frequencies of somatic hotspot mutations in the phosphatidylinositol-3 kinase catalytic alpha (PIK3CA) gene, which encodes for one of these kinases, in several human solid tumors, including oral squamous cell carcinoma (OSCC). The aim of this study was to determine the frequency of hotspot mutations in exons 9 and 20 of the PIK3CA gene in OSCC in the Greek population. Eighty-six formalin-fixed and paraffin-embedded primary tumor specimens were analyzed by direct genomic DNA sequencing. Chi-square was used for statistical analysis. No hotspot mutations were detected in any of the samples. Two intronic polymorphisms IVS8 and IVS9 were detected, mainly in patients with cancer of the buccal mucosa and lower gingival and alveolus respectively. PIK3CA hotspot mutations are unlikely to play a major role in the pathogenesis of OSCC in the Greek population.

Expression analysis of genes at 3q26-q27 involved in frequent amplification in squamous cell lung carcinoma

Gene amplifications are known to occur frequently in lung cancer. Recently, we identified gene amplifications at 3q26 in squamous cell lung carcinoma (SCC) using reverse chromosome painting. Here, our aim was to analyse the expression of genes which map within the amplified chromosomal region. The genes which were selected for their known function and their potential involvement in tumour development included the genes for ribosomal protein L22 ( RPL22), butyrylcholinesterase ( BCHE), glucose transporter 2 ( SLC2A2), transferrin receptor ( TFRC), thrombopoietin ( THPO) and the phosphatidylinositol-3 kinase catalytic alpha polypeptide ( PIK3CA). While five genes were expressed in the majority of the 17 samples of SCC, the gene for the glucose transporter 2 ( SLC2A2) was expressed in only three cases, excluding SLC2A2 as the target gene of the amplification unit. For a subset of tumours, we determined the amplification status of the six genes. The TFRC, PIK3CA, BCHE, THPO and SLC2A2 genes were amplified in several cases, whereas the RPL22 gene was amplified in only one case. The combined amplification and expression data of this and our previous studies indicate that the amplified region at 3q26 contains several genes that are transcribed in SCC, providing the possibility that several amplified and functionally important genes at 3q26 may be involved in the pathogenesis of SCC.