PIK3CA somatic mutations in breast cancer: Mechanistic insights from Langevin dynamics simulations

Biological evaluations and computational studies of newly synthesized thymol-based Schiff bases as anticancer, antimicrobial and antioxidant agents

Three new thymol-based molecules were synthesized and evaluated as anticancer, antimicrobial and antioxidant agents. Liver, colon, lung and prostate cancer cell lines were utilized in cytotoxicity tests. The results demonstrated that synthesized molecules had a cytotoxic effect against the screened cell lines. One of the molecules (4a) was found to have a higher efficacy towards the colon cancer cell line (DLD-1) with an IC50 value of 12.39 µM and the other (4c) towards the prostate cancer cell line (PC3) with an IC50 value of 7.67 µM than the positive control drug cisplatin. To assess the antimicrobial activity of molecules (4a-c), Gram-positive bacteria, Gram-negative bacteria and yeast were subjected to agar disc diffusion and broth microdilution assays. The investigation of antioxidant potential was conducted using the DPPH radical scavenging activity assay. While all compounds displayed strong cytotoxic and antioxidant properties, they exhibited only moderate antimicrobial activity. Molecular docking studies were performed on epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor 2 (VEGFR-2), focal adhesion kinase (FAK), B-Raf and phosphoinositide 3-kinase (PI3K). The binding energies and interactions obtained from the docking results of compounds (4a-c) supported the experimental results. Drug similarity rates and pharmacokinetic properties were analyzed with the absorption, distribution, metabolism and excretion (ADME) method. Geometric parameters such as chemical potential (µ), electrophilicity index (ω) and chemical softness (σ) of compounds (4a-c) were calculated using the 6-31*G basis set B3LYP method.Communicated by Ramaswamy H. Sarma.

PIK3CA mutations in breast cancer: A Tunisian series

BACKGROUND

The aim of this study was to analyze PIK3CA mutations in exons 9 and 20 in breast cancers (BCs) and their association with clinicopathological characteristics.

METHODS

Mutational analysis of PIK3CA exon 9 and 20 was performed by Sanger sequencing in 54 primary BCs of Tunisian women. The associations of PIK3CA mutations with clinicopathological characteristics were analyzed.

RESULTS

Fifteen exon 9 and exon 20 PIK3CA variants were identified in 33/54 cases (61%). PIK3CA mutations including pathogenic (class 5/Tier I) or likely pathogenic (class 4/Tier II) occurred in 24/54 cases (44%): 17/24 cases (71%) in exon 9, 5/24 cases (21%) in exon 20 and 2/24 cases (8%) in both exons. Of these 24 cases, 18 (75%) carried at least one of the three hot spot mutations: E545K (in 8 cases), H1047R (in 4 cases), E542K (in 3 cases), E545K/E542K (in one case), E545K/H1047R (in one case) and P539R/H1047R (in one case). Pathogenic PIK3CA mutations were associated with negative lymph node status (p = 0.027). Age distribution, histological SBR tumor grading, estrogen and progesterone receptors, human epidermal growth factor receptor 2, and molecular classification were not correlated with PIK3CA mutations (p > 0.05).

CONCLUSION

The frequency of somatic PIK3CA mutations in BCs of Tunisian women is slightly higher than that of BCs of Caucasian women and more observed in exon 9 than in exon 20. PIK3CA mutated status is associated with negative lymph node status. These data need to be confirmed in larger series.

Therapeutic targeting of ARID1A and PI3K/AKT pathway alterations in cholangiocarcinoma

BACKGROUND

Genetic alterations in ARID1A were detected at a high frequency in cholangiocarcinoma (CCA). Growing evidence indicates that the loss of ARID1A expression leads to activation of the PI3K/AKT pathway and increasing sensitivity of ARID1A-deficient cells for treatment with the PI3K/AKT inhibitor. Therefore, we investigated the association between genetic alterations of ARID1A and the PI3K/AKT pathway and evaluated the effect of AKT inhibition on ARID1A-deficient CCA cells.

METHODS

Alterations of ARID1A, PI3K/AKT pathway-related genes, clinicopathological data and overall survival of 795 CCA patients were retrieved from cBio Cancer Genomics Portal (cBioPortal) databases. The association between genetic alterations and clinical data were analyzed. The effect of the AKT inhibitor (MK-2206) on ARID1A-deficient CCA cell lines and stable ARID1A-knockdown cell lines was investigated. Cell viability, apoptosis, and expression of AKT signaling were analyzed using an MTT assay, flow cytometry, and Western blots, respectively.

RESULTS

The analysis of a total of 795 CCA samples revealed that ARID1A alterations significantly co-occurred with mutations of EPHA2 (p < 0.001), PIK3CA (p = 0.047), and LAMA1 (p = 0.024). Among the EPHA2 mutant CCA tumors, 82% of EPHA2 mutant tumors co-occurred with ARID1A truncating mutations. CCA tumors with ARID1A and EPHA2 mutations correlated with better survival compared to tumors with ARID1A mutations alone. We detected that 30% of patients with PIK3CA driver missense mutations harbored ARID1A-truncated mutations and 60% of LAMA1-mutated CCA co-occurred with truncating mutations of ARID1A. Interestingly, ARID1A-deficient CCA cell lines and ARID1A-knockdown CCA cells led to increased sensitivity to treatment with MK-2206 compared to the control. Treatment with MK-2206 induced apoptosis in ARID1A-knockdown KKU-213A and HUCCT1 cell lines and decreased the expression of pAKT^S473 and mTOR.

CONCLUSION

These findings suggest a dependency of ARID1A-deficient CCA tumors with the activation of the PI3K/AKT-pathway, and that they may be more vulnerable to selective AKT pathway inhibitors which can be used therapeutically.

The Spectrum, Tendency and Predictive Value of PIK3CA Mutation in Chinese Colorectal Cancer Patients

Background

PIK3CA is a high-frequency mutation gene in colorectal cancer, while its prognostic value remains unclear. This study evaluated the mutation tendency, spectrum, prognosis power and predictive power in cetuximab treatment of PIK3CA in Chinese CRC cohort.

Methods

The PIK3CA exon 9 and 20 status of 5763 CRC patients was detected with Sanger sequencing and a high-resolution melting test. Clinicopathological characteristics of 5733 patients were analyzed. Kaplan-Meier method and nomogram were used to evaluate the overall survival curve and disease recurrence, respectively.

Results

Fifty-eight types of mutations in 13.4% (771/5733) of the patients were detected. From 2014 to 2018, the mutation rate of PIK3CA increased from 11.0% to 13.5%. At stage IV, exon 20 mutated patients suffered shorter overall survival time than wild-type patients (multivariate COX regression analysis, HR = 2.72, 95% CIs = 1.47-5.09; p-value = 0.012). At stage III, PIK3CA mutated patients were more likely to relapse (multivariate Logistic regression analysis, exon 9: OR = 2.54, 95% CI = 1.34-4.73, p = 0.003; exon 20: OR = 3.89, 95% CI = 1.66-9.10, p = 0.002). The concordance index of the nomogram for predicting the recurrence risk of stage III patients was 0.685. After cetuximab treatment, the median PFS of PIK3CA exon 9 wild-type patients (n = 9) and mutant patients (n = 5) did not reach a significant difference (3.6 months vs. 2.3 months, Log-rank test, p-value = 0.513).

Conclusions

We found that PIK3CA mutation was an adverse predictive marker for the overall survival of stage IV patients and recurrence of stage III patients, respectively. Further more, we suggested that PIK3CA exon 9 mutations are not negative predictors of cetuximab treatment in KRAS, NRAS, and BRAF wild-type mCRC patients.

Molecular characterisation in tongue squamous cell carcinoma reveals key variants potentially linked to clinical outcomes

BACKGROUND

Oral tongue squamous cell carcinoma (OTSCC) is a highly aggressive malignancy characterized by frequent recurrence, poor survival with relatively few therapeutic options due to the late diagnosis in many cases.

OBJECTIVES

Understanding the molecular pathways underlying OTSCC tumourigenesis and the discovery of diagnostic and/or prognostic biomarkers.

METHODS

We performed high-throughput mutational analysis of 44 OTSCC formalin-fixed paraffin-embedded (FFPE) cases using the Cancer Hotspots Panel (CHP) v2 on the Ion Torrent™platform. We determined the frequency of human papilloma virus (HPV) using PCR and Epstein bar virus (EBV) positivity using immunohistochemistry. As a control for EBV infection we screened matched non-tumourous tissues.

RESULTS

Sequencing analysis identified missense, nonsense and frameshift mutations in TP53 (66%), PIK3CA (27%), CDKN2A (25%), EGFR (18%), and PTEN (14%). Interestingly, no significant associations were found between damaging mutations and clinicopathological data. A total of 10/44 of the OTSCC samples (23%) tested was positive for HPV18 DNA. OTSCC patients with positive HPV infection had worse overall survival compared to HPV-negative cases as determined by Kaplan-Meier survival (p= 0.023). Furthermore, EBNA1 expression showed a strong tumour-enriched expression pattern in 20 out of 21 samples (95%) in the epithelial compartments of the tissues analysed.

CONCLUSIONS

Taken together, this study highlights that the two most common events in OTSCC are TP53 mutations and EBV positivity. Helping to understand the contribution of TP53 mutations and EBV infection events could serve as useful biomarkers for OTSCC.

Prevalence of Phosphatidylinositol-3-Kinase (PI3K) Pathway Alterations and Co-alteration of Other Molecular Markers in Breast Cancer

Background: PI3K/AKT signaling pathway is activated in breast cancer and associated with cell survival. We explored the prevalence of PI3K pathway alterations and co-expression with other markers in breast cancer subtypes. Methods: Samples of non-matched primary and metastatic breast cancer submitted to a CLIA-certified genomics laboratory were molecularly profiled to identify pathogenic or presumed pathogenic mutations in the PIK3CA-AKT1-PTEN pathway using next generation sequencing. Cases with loss of PTEN by IHC were also included. The frequency of co-alterations was examined, including DNA damage response pathways and markers of response to immuno-oncology agents. Results: Of 4,895 tumors profiled, 3,558 (72.7%) had at least one alteration in the PIK3CA-AKT1-PTEN pathway: 1,472 (30.1%) harbored a PIK3CA mutation, 174 (3.6%) an AKT1 mutation, 2,682 (54.8%) had PTEN alterations (PTEN mutation in 7.0% and/or PTEN loss by IHC in 51.4% of cases), 81 (1.7%) harbored a PIK3R1 mutation, and 4 (0.08%) a PIK3R2 mutation. Most of the cohort consisted of metastatic sites (n = 2974, 60.8%), with PIK3CA mutation frequency increased in metastatic (32.1%) compared to primary sites (26.9%), p < 0.001. Other PIK3CA mutations were identified in 388 (7.9%) specimens, classified as "off-label," as they were not included in the FDA-approved companion test for PIK3CA mutations. Notable co-alterations included increased PD-L1 expression and high tumor mutational burden in PIK3CA-AKT1-PTEN mutated cohorts. Novel concurrent mutations were identified including CDH1 mutations. Conclusions: Findings from this cohort support further exploration of the clinical benefit of PI3K inhibitors for "off-label" PIK3CA mutations and combination strategies with potential clinical benefit for patients with breast cancer.

Helical and kinase domain mutations of PIK3CA, and their association with hormone receptor expression in breast cancer

Breast cancer is one of the major causes of female morbidity and mortality, accounting for ~25% of the total cancer cases in women. Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic α subunit (PIK3CA) mutations serve a major role in downstream signaling of receptor tyrosine kinases. The present study aimed to elucidate the frequency of exon 9 and 20 mutations of PIK3CA and their role in disease progression. A total of 118 tumor samples from confirmed breast cancer patients were collected from the histopathology laboratory at King Fahd Hospital of the University (Al-Khobar, Saudi Arabia). Sanger sequencing was performed on extracted DNA to identify the mutations on exons 9 and 20 of PIK3CA. The results were further validated by competitive allele-specific TaqMan polymerase chain reaction. Three mutations, namely E542K and E545K within exon 9, and H1047R within exon 20, were observed in 25 patients (21.2%). Among these, 18 patients carried the H1047R mutation of the kinase domain, while the remaining 7 patients carried mutations in the helical domain. PIK3CA mutations were associated with the estrogen receptor-positive/progesterone receptor-positive (ER⁺/PR⁺) group of tumors in contrast to the ER⁻/PR⁻ group (P=0.021). Furthermore, it was observed that the PIK3CA mutation was associated with a poor disease prognosis. Taken together, the current study emphasized the potential of PIK3CA mutations as an important biomarker for breast cancer classification and the possible use of PIK3CA inhibitor as targeted therapy for breast cancer.

Investigating the Inhibitory Effect of Wortmannin in the Hotspot Mutation at Codon 1047 of PIK3CA Kinase Domain: A Molecular Docking and Molecular Dynamics Approach

Oncogenic mutations in phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) are the most frequently reported in association with various forms of cancer. Several studies have reported the significance of hotspot mutations in a catalytic subunit of PIK3CA in association with breast cancer. Mutations are frequently observed in the highly conserved region of the kinase domain (797-1068 amino acids) of PIK3CA are activating or gain-of-function mutations. Mutation in codon 1047 occurs in the C-terminal region of the kinase domain with histidine (H) replaced by arginine (R), lysine (L), and tyrosine (Y). Pathogenicity and protein stability predictors PhD-SNP, Align GVGD, HANSA, iStable, and MUpro classified H1047R as highly deleterious when compared to H1047L and H1047Y. To explore the inhibitory activity of Wortmannin toward PIK3CA, the three-dimensional structure of the mutant protein was determined using homology modeling followed by molecular docking and molecular dynamics analysis. Docking studies were performed for the three mutants and native with Wortmannin to measure the differences in their binding pattern. Comparative docking study revealed that H1047R-Wortmannin complex has a higher number of hydrogen bonds as well as the best binding affinity next to the native protein. Furthermore, 100 ns molecular dynamics simulation was initiated with the docked complexes to understand the various changes induced by the mutation. Though Wortmannin was found to nullify the effect of H1047R over the protein, further studies are required for designing a better compound. As SNPs are major genetic variations observed in disease condition, personalized medicine would provide enhanced drug therapy.

Rapid detection of genetic mutations in individual breast cancer patients by next-generation DNA sequencing

Breast cancer is the most common malignancy in women and the leading cause of cancer deaths in women worldwide. Breast cancers are heterogenous and exist in many different subtypes (luminal A, luminal B, triple negative, and human epidermal growth factor receptor 2 (HER2) overexpressing), and each subtype displays distinct characteristics, responses to treatment, and patient outcomes. In addition to varying immunohistochemical properties, each subtype contains a distinct gene mutation profile which has yet to be fully defined. Patient treatment is currently guided by hormone receptor status and HER2 expression, but accumulating evidence suggests that genetic mutations also influence drug responses and patient survival. Thus, identifying the unique gene mutation pattern in each breast cancer subtype will further improve personalized treatment and outcomes for breast cancer patients. In this study, we used the Ion Personal Genome Machine (PGM) and Ion Torrent AmpliSeq Cancer Panel to sequence 737 mutational hotspot regions from 45 cancer-related genes to identify genetic mutations in 80 breast cancer samples of various subtypes from Chinese patients. Analysis revealed frequent missense and combination mutations in PIK3CA and TP53, infrequent mutations in PTEN, and uncommon combination mutations in luminal-type cancers in other genes including BRAF, GNAS, IDH1, and KRAS. This study demonstrates the feasibility of using Ion Torrent sequencing technology to reliably detect gene mutations in a clinical setting in order to guide personalized drug treatments or combination therapies to ultimately target individual, breast cancer-specific mutations.

Investigating the structure and dynamics of the PIK3CA wild-type and H1047R oncogenic mutant

The PIK3CA gene is one of the most frequently mutated oncogenes in human cancers. It encodes p110α, the catalytic subunit of phosphatidylinositol 3-kinase alpha (PI3Kα), which activates signaling cascades leading to cell proliferation, survival, and cell growth. The most frequent mutation in PIK3CA is H1047R, which results in enzymatic overactivation. Understanding how the H1047R mutation causes the enhanced activity of the protein in atomic detail is central to developing mutant-specific therapeutics for cancer. To this end, Surface Plasmon Resonance (SPR) experiments and Molecular Dynamics (MD) simulations were carried out for both wild-type (WT) and H1047R mutant proteins. An expanded positive charge distribution on the membrane binding regions of the mutant with respect to the WT protein is observed through MD simulations, which justifies the increased ability of the mutated protein variant to bind to membranes rich in anionic lipids in our SPR experiments. Our results further support an auto-inhibitory role of the C-terminal tail in the WT protein, which is abolished in the mutant protein due to loss of crucial intermolecular interactions. Moreover, Functional Mode Analysis reveals that the H1047R mutation alters the twisting motion of the N-lobe of the kinase domain with respect to the C-lobe and shifts the position of the conserved P-loop residues in the vicinity of the active site. These findings demonstrate the dynamical and structural differences of the two proteins in atomic detail and propose a mechanism of overactivation for the mutant protein. The results may be further utilized for the design of mutant-specific PI3Kα inhibitors that exploit the altered mutant conformation.

The PI3Kα protein is involved in cellular processes such as cell growth, division, and formation of new blood vessels (angiogenesis) that aid cancer cell survival. In certain types of cancer cells, PI3Kα is found to be altered compared to healthy cells. These PI3Kα alterations, called mutations, are found in 27% of breast cancer patients, 24% of endometrial cancer patients, and 15% of colon cancer patients. PI3Kα mutations cause the protein to become overactivated and may contribute to tumor growth. The most common PI3Kα amino acid mutation is a histidine changed to an arginine: H1047R. Understanding how the H1047R mutation overactivates PI3Kα is central to developing therapeutics for cancer patients who bear PI3Kα mutations. To this end, we performed simulations and experiments of the mutated and physiological proteins to explain why the mutant protein becomes overactivated. Our results indicate structural and dynamical differences between the mutant and physiological proteins that may affect the PI3Kα function. Based on these differences, we propose a mechanism that highlights the series of events that lead to the mutant H1047R PI3Kα overactivation. This study provides insights into developing mutant-specific PI3Kα inhibitors that exploit the altered conformation of the mutant with respect to the physiological protein.

A graph theoretic approach to utilizing protein structure to identify non-random somatic mutations

Background

It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of "driver" mutations that are primarily responsible for tumorigenesis. Further, due to recent pharmacological successes in treating these driver mutations and their resulting tumors, a variety of approaches have been developed to identify potential driver mutations using methods such as machine learning and mutational clustering. We propose a novel methodology that increases our power to identify mutational clusters by taking into account protein tertiary structure via a graph theoretical approach.

Results

We have designed and implemented GraphPAC (Graph Protein Amino acid Clustering) to identify mutational clustering while considering protein spatial structure. Using GraphPAC, we are able to detect novel clusters in proteins that are known to exhibit mutation clustering as well as identify clusters in proteins without evidence of prior clustering based on current methods. Specifically, by utilizing the spatial information available in the Protein Data Bank (PDB) along with the mutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC), GraphPAC identifies new mutational clusters in well known oncogenes such as EGFR and KRAS. Further, by utilizing graph theory to account for the tertiary structure, GraphPAC discovers clusters in DPP4, NRP1 and other proteins not identified by existing methods. The R package is available at: http://bioconductor.org/packages/release/bioc/html/GraphPAC.html.

Conclusion

GraphPAC provides an alternative to iPAC and an extension to current methodology when identifying potential activating driver mutations by utilizing a graph theoretic approach when considering protein tertiary structure.

Utilizing protein structure to identify non-random somatic mutations

Background

Human cancer is caused by the accumulation of somatic mutations in tumor suppressors and oncogenes within the genome. In the case of oncogenes, recent theory suggests that there are only a few key “driver” mutations responsible for tumorigenesis. As there have been significant pharmacological successes in developing drugs that treat cancers that carry these driver mutations, several methods that rely on mutational clustering have been developed to identify them. However, these methods consider proteins as a single strand without taking their spatial structures into account. We propose an extension to current methodology that incorporates protein tertiary structure in order to increase our power when identifying mutation clustering.

Results

We have developed iPAC (identification of Protein Amino acid Clustering), an algorithm that identifies non-random somatic mutations in proteins while taking into account the three dimensional protein structure. By using the tertiary information, we are able to detect both novel clusters in proteins that are known to exhibit mutation clustering as well as identify clusters in proteins without evidence of clustering based on existing methods. For example, by combining the data in the Protein Data Bank (PDB) and the Catalogue of Somatic Mutations in Cancer, our algorithm identifies new mutational clusters in well known cancer proteins such as KRAS and PI3KC α. Further, by utilizing the tertiary structure, our algorithm also identifies clusters in EGFR, EIF2AK2, and other proteins that are not identified by current methodology. The R package is available at: http://www.bioconductor.org/packages/2.12/bioc/html/iPAC.html.

Conclusion

Our algorithm extends the current methodology to identify oncogenic activating driver mutations by utilizing tertiary protein structure when identifying nonrandom somatic residue mutation clusters.

Bi-directional SIFT predicts a subset of activating mutations

Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant) algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT) is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

Somatic mutations in PI3Kalpha: structural basis for enzyme activation and drug design

The PI3K pathway is a communication hub coordinating critical cell functions including cell survival, cell growth, proliferation, motility and metabolism. Because PI3Kalpha harbors recurrent somatic mutations resulting in gains of function in human cancers, it has emerged as an important drug target for many types of solid tumors. Various PI3K isoforms are also being evaluated as potential therapeutic targets for inflammation, heart disease, and hematological malignancies. Structural biology is providing insights into the flexibility of the PI3Ks, and providing basis for understanding the effects of mutations, drug resistance and specificity.

Form and flexibility in phosphoinositide 3-kinases

PI3Ks (phosphoinositide 3-kinases) have important roles in a variety of cellular activities, including survival, proliferation, growth, shape, migration and intracellular sorting. Consistent with their function in cell survival and growth, the gene for the class Iα PI3K catalytic subunit is a common site of gain-of-function mutations in cancers. Ongoing structural studies of these enzymes and the complexes they make with their regulatory subunits have helped to clarify the mechanistic basis of this role in tumour development. The broad spectrum of biological activities associated with various isotypes of class I PI3Ks has led to an intense search for isotype-specific inhibitors as tools in mammalian cell biology and for therapeutic application. Structural studies of the class I PI3Ks suggest that flexibility may be a component of the catalytic cycle of the enzymes.