Nutlin-3a: A Potential Therapeutic Opportunity for TP53 Wild-Type Ovarian Carcinomas

The potential for senotherapy as a novel approach to extend life quality in veterinary medicine

Cellular senescence, a condition where cells undergo arrest and can assume an inflammatory phenotype, has been associated with initiation and perpetuation of inflammation driving multiple disease processes in rodent models and humans. Senescent cells secrete inflammatory cytokines, proteins, and matrix metalloproteinases, termed the senescence associated secretory phenotype (SASP), which accelerates the aging processes. In preclinical models, drug interventions termed "senotherapeutics" selectively clear senescent cells and represent a promising strategy to prevent or treat multiple age-related conditions in humans and veterinary species. In this review, we summarize the current available literature describing in vitro evidence for senotheraputic activity, preclinical models of disease, ongoing human clinical trials, and potential clinical applications in veterinary medicine. These promising data to date provide further justification for future studies identifying the most active senotherapeutic combinations, dosages, and routes of administration for use in veterinary medicine.

An overview of the functions of p53 and drugs acting either on wild- or mutant-type p53

TP53, also known as the "guardian of the genome," is an important tumor suppressor gene. It is encoded by the human genome and is associated with the development of diverse cancers. The p53 protein, encoded by TP53, functions in the cell to monitor DNA damage and prompts the cell to respond appropriately. When DNA is damaged, p53 halts the cell cycle, allowing cells to enter the repair state. If the repair is ineffective, p53 induces cell death via apoptosis. This prevents DNA damage transmission during cell division and reduces cancer risk. However, the p53 gene mutation compromises its function. This leads to the inability of cells to respond properly to DNA damage, which may result in cancer development. Mutations in p53 are widespread in diverse cancers, especially highly prevalent cancers, including breast, colon, and lung cancers. Despite the association between p53 mutations and cancer, researchers have discovered drugs and treatments that may reactivate mutated p53 function. Therefore, p53 remains an important area of research in cancer treatment and holds promise as a new direction for cancer therapy. In summary, TP53 is a vital tumor suppressor gene responsible for monitoring DNA damage and prompting cells to respond appropriately. This article summarizes drugs related to p53 and diverse strategies for discovering drugs that act on either wide or mutant p53. Herein, p53 is categorized into two types: wild and mutant type. Drugs are also classified according to diverse treatment strategies, enabling readers to differentiate between the two types of p53 and aiding in selecting the appropriate research direction. Additionally, this review offers a valuable reference for drug design.

Novel Molecular Subtyping Scheme Based on In Silico Analysis of Cuproptosis Regulator Gene Patterns Optimizes Survival Prediction and Treatment of Hepatocellular Carcinoma

BACKGROUND

The liver plays an important role in maintaining copper homeostasis. Copper ion accumulation was elevated in HCC tissue samples. Copper homeostasis is implicated in cancer cell proliferation and angiogenesis. The potential of copper homeostasis as a new theranostic biomarker for molecular imaging and the targeted therapy of HCC has been demonstrated. Recent studies have reported a novel copper-dependent nonapoptotic form of cell death called cuproptosis, strikingly different from other known forms of cell death. The correlation between cuproptosis and hepatocellular carcinoma (HCC) is not fully understood.

MATERIALS AND METHODS

The transcriptomic data of patients with HCC were retrieved from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and were used as a discovery cohort to construct the prognosis model. The gene expression data of patients with HCC retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases were used as the validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to construct the prognosis model. A principal component analysis (PCA) was used to evaluate the overall characteristics of cuproptosis regulator genes and obtain the PC1 and PC2 scores. Unsupervised clustering was performed using the ConsensusClusterPlus R package to identify the molecular subtypes of HCC. Cox regression analysis was performed to identify cuproptosis regulator genes that could predict the prognosis of patients with HCC. The receiver operating characteristics curve and Kaplan-Meier survival analysis were used to understand the role of hub genes in predicting the diagnosis and prognosis of patients, as well as the prognosis risk model. A weighted gene co-expression network analysis (WGCNA) was used for screening the cuproptosis subtype-related hub genes. The functional enrichment analysis was performed using Metascape. The 'glmnet' R package was used to perform the LASSO regression analysis, and the randomForest algorithm was performed using the 'randomForest' R package. The 'pRRophetic' R package was used to estimate the anticancer drug sensitivity based on the data retrieved from the Genomics of Drug Sensitivity in Cancer database. The nomogram was constructed using the 'rms' R package. Pearson's correlation analysis was used to analyze the correlations.

RESULTS

We constructed a six-gene signature prognosis model and a nomogram to predict the prognosis of patients with HCC. The Kaplan-Meier survival analysis revealed that patients with a high-risk score, which was predicted by the six-gene signature model, had poor prognoses (log-rank test p < 0.001; HR = 1.83). The patients with HCC were grouped into three distinct cuproptosis subtypes (Cu-clusters A, B, and C) based on the expression pattern of cuproptosis regulator genes. The patients in Cu-cluster B had poor prognosis (log-rank test p < 0.001), high genomic instability, and were not sensitive to conventional chemotherapeutic treatment compared to the patients in the other subtypes. Cancer cells in Cu-cluster B exhibited a higher degree of the senescence-associated secretory phenotype (SASP), a marker of cellular senescence. Three representative genes, CDCA8, MCM6, and NCAPG2, were identified in patients in Cu-cluster B using WGCNA and the "randomForest" algorithm. A nomogram was constructed to screen patients in the Cu-cluster B subtype based on three genes: CDCA8, MCM6, and NCAPG2.

CONCLUSION

Publicly available databases and various bioinformatics tools were used to study the heterogeneity of cuproptosis in patients with HCC. Three HCC subtypes were identified, with differences in the survival outcomes, genomic instability, senescence environment, and response to anticancer drugs. Further, three cuproptosis-related genes were identified, which could be used to design personalized therapeutic strategies for HCC.

CopA3 peptide inhibits MDM2-p53 complex stability in colorectal cancers and activates p53 mediated cell death machinery

The diverse expression patterns of the tumor suppressor p53 in cancer cells reflect the regulatory efficiency of multiple cellular pathways. By contrast, many human tumors are reported to develop in the presence of wild-type p53. Recently, several oncogene inhibitors have been used clinically to suppress tumor development by functionally reactivating other oncoproteins. On the other hand, p53 reactivation therapies have not been well established, as few of the p53-MDM2 complex inhibitors such as Nutlin-3 induces mutation in p53 gene upon prolonged usage. Therefore, in this study CopA3, a 9-mer dimeric D-type peptide with anticancer activity against the human colorectal cancer cells, was used to explore the efficacy of p53 reactivation in-vitro and in-vivo. The anticancer activity of CopA3 was more selective towards the wild-type p53 expressing cells than the p53 deficient or mutant colorectal cancer cells. In response to this, this study investigated the signaling pathway in vitro and validated its anti-tumor activity in-vivo. The protein-peptide interaction and molecular docking efficiently provided insight into the specific binding affinity of CopA3 to the p53-binding pocket of the MDM2 protein, which efficiently blocked the p53 and MDM2 interaction. CopA3 plays a crucial role in the binding with MDM2 and enhanced the nuclear translocation of the p53 protein, which sequentially activated the downstream targets to trigger the autophagic mediated cell death machinery through the JNK/Beclin-1 mediated pathway. Collectively, CopA3 affected the MDM2-p53 interaction, which suppressed tumor development. This study may provide a novel inhibitor candidate for the MDM2-p53 complex, which could ultimately suppress the growth of colorectal cancer cells without being cytotoxic to the healthy neighboring cells present around the tumor microenvironment.

Enzalutamide-induced signatures revealed by epigenetic plasticity using single-cell multi-omics sequencing in prostate cancer

Prostate cancer is morphologically and molecularly heterogeneous, which poses obstacles for early diagnosis and treatment. Advancements in understanding the heterogeneity of prostate cancer will help navigate through these challenges and ultimately benefit patients. In this study, we integrated single-cell sequencing for transposase-accessible chromatin and whole transcriptome in prostate cancer cell lines, aiming to decode the epigenetic plasticity upon enzalutamide (ENZ) treatment. By comparing the cell populations representing early-treatment response or resistance to the initial tumor cells, we identified seven signature gene sets; they present consistent trends of chromatin closing co-occurred with down-regulated genes during early response and chromatin opening with up-regulated genes upon maintaining drug resistance. In the molecular signatures, we found genes ZNF337, MAPK15, and ESRRG are favorable in progression-free prognosis during early response, while genes CCDC150, CCDC18, and POC1A marked poor prognosis underpinning the pre-existing drug resistance in The Cancer Genome Atlas prostate adenocarcinoma cohort. Ultimately, drug-target analyses nominated combinatory drug candidates to either enhance early-treatment response or potentially overcome ENZ resistance. Together, our integrative, single-cell multi-omics approach in pre-clinical models is effective in identifying informative signatures from complex molecular events, illustrating diverse drug responses in prostate cancer, and invoking novel combinatory drug strategies to inform clinical decision making.

A random forest-based metabolic risk model to assess the prognosis and metabolism-related drug targets in ovarian cancer

As one of the most common gynecologic malignant tumors, ovarian cancer is usually diagnosed at an advanced and incurable stage because of its early asymptomatic onset. Increasing research into tumor biology has demonstrated that abnormal cellular metabolism precedes tumorigenesis, therefore it has become an area of active research in academia. Cellular metabolism is of great significance in cancer diagnostic and prognostic studies. In this study, we integrated The Cancer Genome Atlas dataset with multiple Gene Expression Omnibus ovarian cancer datasets, identified 17 metabolic pathways with prognostic values using the random forest algorithm, constructed a metabolic risk scoring model based on metabolic pathway enrichment scores, and classified patients with ovarian cancer into two subtypes. Then, we systematically investigated the differences between different subtypes in terms of prognosis, differential gene expression, immune signature enrichment, Hallmark signature enrichment, and somatic mutations. As well, we successfully predicted differences in sensitivity to immunotherapy and chemotherapy drugs in patients with different metabolic risk subtypes. Moreover, we identified 5 drug targets associated with high metabolic risk and low metabolic risk ovarian cancer phenotypes through the weighted correlation network analysis and investigated their roles in the genesis of ovarian cancer. Finally, we developed an XGBoost classifier for predicting metabolic risk types in patients with ovarian cancer, producing a good predictive effect. In light of the above study, the research findings will provide valuable information for prognostic prediction and personalized medical treatment of patients with ovarian cancer.

Baicalein Induces G2/M Cell Cycle Arrest Associated with ROS Generation and CHK2 Activation in Highly Invasive Human Ovarian Cancer Cells

Ovarian cancer is a lethal gynecological cancer because drug resistance often results in treatment failure. The CHK2, a tumor suppressor, is considered to be an important molecular target in ovarian cancer due to its role in DNA repair. Dysfunctional CHK2 impairs DNA damage-induced checkpoints, reduces apoptosis, and confers resistance to chemotherapeutic drugs and radiation therapy in ovarian cancer cells. This provides a basis for finding new effective agents targeting CHK2 upregulation or activation to treat or prevent the progression of advanced ovarian cancer. Here, the results show that baicalein (5,6,7-trihydroxyflavone) treatment inhibits the growth of highly invasive ovarian cancer cells, and that baicalein-induced growth inhibition is mediated by the cell cycle arrest in the G₂/M phase. Baicalein-induced G₂/M phase arrest is associated with an increased reactive oxygen species (ROS) production, DNA damage, and CHK2 upregulation and activation. Thus, baicalein modulates the expression of DNA damage response proteins and G₂/M phase regulatory molecules. Blockade of CHK2 activation by CHK2 inhibitors protects cells from baicalein-mediated G₂/M cell cycle arrest. All the results suggest that baicalein has another novel growth inhibitory effect on highly invasive ovarian cancer cells, which is partly related to G₂/M cell cycle arrest through the ROS-mediated DNA breakage damage and CHK2 activation. Collectively, our findings provide a molecular basis for the potential of baicalein as an adjuvant therapeutic agent in the treatment of metastatic ovarian cancer.

DNA Damage Response Alterations in Ovarian Cancer: From Molecular Mechanisms to Therapeutic Opportunities

The DNA damage response (DDR), a set of signaling pathways for DNA damage detection and repair, maintains genomic stability when cells are exposed to endogenous or exogenous DNA-damaging agents. Alterations in these pathways are strongly associated with cancer development, including ovarian cancer (OC), the most lethal gynecologic malignancy. In OC, failures in the DDR have been related not only to the onset but also to progression and chemoresistance. It is known that approximately half of the most frequent subtype, high-grade serous carcinoma (HGSC), exhibit defects in DNA double-strand break (DSB) repair by homologous recombination (HR), and current evidence indicates that probably all HGSCs harbor a defect in at least one DDR pathway. These defects are not restricted to HGSCs; mutations in ARID1A, which are present in 30% of endometrioid OCs and 50% of clear cell (CC) carcinomas, have also been found to confer deficiencies in DNA repair. Moreover, DDR alterations have been described in a variable percentage of the different OC subtypes. Here, we overview the main DNA repair pathways involved in the maintenance of genome stability and their deregulation in OC. We also recapitulate the preclinical and clinical data supporting the potential of targeting the DDR to fight the disease.

Targeting p53-MDM2 interaction by small-molecule inhibitors: learning from MDM2 inhibitors in clinical trials

p53, encoded by the tumor suppressor gene TP53, is one of the most important tumor suppressor factors in vivo and can be negatively regulated by MDM2 through p53–MDM2 negative feedback loop. Abnormal p53 can be observed in almost all tumors, mainly including p53 mutation and functional inactivation. Blocking MDM2 to restore p53 function is a hotspot in the development of anticancer candidates. Till now, nine MDM2 inhibitors with different structural types have entered clinical trials. However, no MDM2 inhibitor has been approved for clinical application. This review focused on the discovery, structural modification, preclinical and clinical research of the above compounds from the perspective of medicinal chemistry. Based on this, the possible defects in MDM2 inhibitors in clinical development were analyzed to suggest that the multitarget strategy or targeted degradation strategy based on MDM2 has the potential to reduce the dose-dependent hematological toxicity of MDM2 inhibitors and improve their anti-tumor activity, providing certain guidance for the development of agents targeting the p53–MDM2 interaction.

SEMCM: A Self-Expressive Matrix Completion Model for Anti-cancer Drug Sensitivity Prediction

Background:

Genomic data sets generated by several recent large scale high-throughput screening efforts pose a thorny computational challenge for anticancer drug sensitivity prediction.

Objective:

We aimed to design an algorithm model that would predict missing elements in incomplete matrices and could be applicable to drug response prediction programs.

Method:

We developed a novel self-expressive matrix completion model to improve the predictive performance of drug response prediction problems. The model is based on the idea of subspace clustering and as a convex problem, it can be solved by alternating direction method of multipliers. The original incomplete matrix can be filled through model training and parameters updated iteratively.

Results:

We applied SEMCM to Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets to predict unknown response values. A large number of experiments have proved that the algorithm has good prediction results and stability, which are better than several existing advanced drug sensitivity prediction and matrix completion algorithms. Without modeling mutation information, SEMCM could correctly predict cell line-drug associations for mutated cell lines and wild cell lines. SEMCM can also be used for drug repositioning. The newly predicted drug responses of GDSC dataset suggest that BL-41 was highly sensitive to Bortezomib. Moreover, the sensitivity of A172 and NCI-H1437 to Paclitaxel was roughly the same.

Conclusion:

We report an efficient anticancer drug sensitivity prediction algorithm which is open-source and can predict the unknown responses of cancer cell lines to drugs. Experimental results prove that our method can not only improve the prediction accuracy but also can be applied to drug repositioning.

Distinct transcriptional programs stratify ovarian cancer cell lines into the five major histological subtypes

BACKGROUND

Epithelial ovarian cancer (OC) is a heterogenous disease consisting of five major histologically distinct subtypes: high-grade serous (HGSOC), low-grade serous (LGSOC), endometrioid (ENOC), clear cell (CCOC) and mucinous (MOC). Although HGSOC is the most prevalent subtype, representing 70-80% of cases, a 2013 landmark study by Domcke et al. found that the most frequently used OC cell lines are not molecularly representative of this subtype. This raises the question, if not HGSOC, from which subtype do these cell lines derive? Indeed, non-HGSOC subtypes often respond poorly to chemotherapy; therefore, representative models are imperative for developing new targeted therapeutics.

METHODS

Non-negative matrix factorisation (NMF) was applied to transcriptomic data from 44 OC cell lines in the Cancer Cell Line Encyclopedia, assessing the quality of clustering into 2-10 groups. Epithelial OC subtypes were assigned to cell lines optimally clustered into five transcriptionally distinct classes, confirmed by integration with subtype-specific mutations. A transcriptional subtype classifier was then developed by trialling three machine learning algorithms using subtype-specific metagenes defined by NMF. The ability of classifiers to predict subtype was tested using RNA sequencing of a living biobank of patient-derived OC models.

RESULTS

Application of NMF optimally clustered the 44 cell lines into five transcriptionally distinct groups. Close inspection of orthogonal datasets revealed this five-cluster delineation corresponds to the five major OC subtypes. This NMF-based classification validates the Domcke et al. analysis, in identifying lines most representative of HGSOC, and additionally identifies models representing the four other subtypes. However, NMF of the cell lines into two clusters did not align with the dualistic model of OC and suggests this classification is an oversimplification. Subtype designation of patient-derived models by a random forest transcriptional classifier aligned with prior diagnosis in 76% of unambiguous cases. In cases where there was disagreement, this often indicated potential alternative diagnosis, supported by a review of histological, molecular and clinical features.

CONCLUSIONS

This robust classification informs the selection of the most appropriate models for all five histotypes. Following further refinement on larger training cohorts, the transcriptional classification may represent a useful tool to support the classification of new model systems of OC subtypes.

PDK2 leads to cisplatin resistance through suppression of mitochondrial function in ovarian clear cell carcinoma

Ovarian clear cell carcinoma (CCC) exhibits an association with endometriosis, resistance to oxidative stress, and poor prognosis owing to its resistance to conventional platinum‐based chemotherapy. A greater understanding of the molecular characteristics and pathogenesis of ovarian cancer subtypes may facilitate the development of targeted therapeutic strategies, although the mechanism of drug resistance in ovarian CCC has yet to be determined. In this study, we assessed exome sequencing data to identify new therapeutic targets of mitochondrial function in ovarian CCC because of the central role of mitochondria in redox homeostasis. Copy number analyses revealed that chromosome 17q21‐24 (chr.17q21‐24) amplification was associated with recurrence in ovarian CCC. Cell viability assays identified an association between cisplatin resistance and chr.17q21‐24 amplification, and mitochondrion‐related genes were enriched in patients with chr.17q21‐24 amplification. Patients with high expression of pyruvate dehydrogenase kinase 2 (PDK2) had a worse prognosis than those with low PDK2 expression. Furthermore, inhibition of PDK2 synergistically enhanced cisplatin sensitivity by activating the electron transport chain and by increasing the production of mitochondrial reactive oxygen species. Mouse xenograft models showed that inhibition of PDK2 with cisplatin inhibited tumor growth. This evidence suggests that targeting mitochondrial metabolism and redox homeostasis is an attractive therapeutic strategy for improving drug sensitivity in ovarian CCC.

Target Genetic Abnormalities for the Treatment of Colon Cancer and Its Progression to Metastasis

Colorectal carcinogenesis involves various processes from the accumulation of genetic alterations to genetic and epigenetic modulations and chromosomal abnormalities. It also involves mutations in oncogenes and tumour suppressor genes. Genomic instability plays a vital role in CRC. Advances in modern biological techniques and molecular level studies have identified various genes involved in colorectal cancer (CRC). KRAS, BRAF, PI3K, and p53 genes play a significant role in different phases of CRC. Alteration of these genes leads to development or progression and metastasis colon cancer. This review focuses on the role of KRAS, BRAF, PI3KCA, and TP53 genes in carcinogenesis and their significance in various stages of CRC. It also provides insights on specific modulators acting on these genes. Further, this review discusses the mechanism of the pathways involving these genes in carcinogenesis and current molecules and treatment options under various stages of clinical evaluation.

Gain-of-function p53 protein transferred via small extracellular vesicles promotes conversion of fibroblasts to a cancer-associated phenotype

Tumor and stromal interactions consist of reciprocal signaling through cytokines, growth factors, direct cell-cell interactions, and extracellular vesicles (EVs). Small EVs (≤200 nm) have been considered critical messengers of cellular communication during tumor development. Here, we demonstrate that gain-of-function (GOF) p53 protein can be packaged into small EVs and transferred to fibroblasts. GOF p53 protein is selectively bound by heat shock protein 90 (HSP90), a chaperone protein, and packaged into small EVs. Inhibition of HSP90 activity blocks packaging of GOF, but not wild-type, p53 in small EVs. GOF p53-containing small EVs result in their conversion to cancer-associated fibroblasts. In vivo studies reveal that GOF p53-containing small EVs can enhance tumor growth and promote fibroblast transformation into a cancer-associated phenotype. These findings provide a better understanding of the complex interactions between cancer and stromal cells and may have therapeutic implications.

Ma et al. report that gain-of-function (GOF) p53 protein can be packaged into small EVs and transferred to stromal fibroblasts. The packaging of GOF p53 into small EVs is regulated by HSP90. Small EVs with GOF p53 activate Nrf2-mediated pathways in fibroblasts and induce their conversion to a cancer-associated phenotype.

P53/miR-154 Pathway Regulates the Epithelial-Mesenchymal Transition in Glioblastoma Multiforme Cells by Targeting TCF12

PURPOSE

Glioblastoma multiforme (GBM) is an aggressive brain tumor with a rather short survival time. Mutation of p53 has been observed and reported to play critical roles in the progression of GBM. However, the pathological mechanisms are still unclear. This study was designed to identify the role of miR-154 in mediating the biological functions of p53 in glioblastoma multiforme.

METHODS

In the current study, the expression of miR-154 in GBM tissue samples and cell lines with wt-p53 or mutant p53 was evaluated. The functions of miR-154 in tumor migration, invasion and epithelial-mesenchymal transition were analyzed in vitro. A luciferase reporter assay was used to identify the target of miR-154.

RESULTS

We found that expression of miR-154 was much lower in patient tissues with mutant p53. Further study revealed that p53 was a transcription factor of miR-154 and that the R273H mutation led to its inactivation. In addition, overexpression of miR-154 remarkably suppressed cell migration, invasion and EMT in vitro and tumor growth in vivo. Moreover, TCF12 was proven to be a direct target of miR-154, and the tumor suppressive effect of miR-154 was reversed by TCF12.

CONCLUSION

Overall, miR-154, which was regulated by wt-p53, inhibited migration, invasion and EMT of GBM cells by targeting TCF12, indicating that miR-154 may act as a biomarker and that the p53/miR-154/TCF12 pathway could be a potential therapeutic target for GBM.

Two-step multi-omics modelling of drug sensitivity in cancer cell lines to identify driving mechanisms

Drug sensitivity prediction models for human cancer cell lines constitute important tools in identifying potential computational biomarkers for responsiveness in a pre-clinical setting. Integrating information derived from a range of heterogeneous data is crucial, but remains non-trivial, as differences in data structures may hinder fitting algorithms from assigning adequate weights to complementary information that is contained in distinct omics data. In order to counteract this effect that tends to lead to just one data type dominating supposedly multi-omics models, we developed a novel tool that enables users to train single-omics models separately in a first step and to integrate them into a multi-omics model in a second step. Extensive ablation studies are performed in order to facilitate an in-depth evaluation of the respective contributions of singular data types and of combinations thereof, effectively identifying redundancies and interdependencies between them. Moreover, the integration of the single-omics models is realized by a range of distinct classification algorithms, thus allowing for a performance comparison. Sets of molecular events and tissue types found to be related to significant shifts in drug sensitivity are returned to facilitate a comprehensive and straightforward analysis of potential computational biomarkers for drug responsiveness. Our two-step approach yields sets of actual multi-omics pan-cancer classification models that are highly predictive for a majority of drugs in the GDSC data base. In the context of targeted drugs with particular modes of action, its predictive performances compare favourably to those of classification models that incorporate multi-omics data in a simple one-step approach. Additionally, case studies demonstrate that it succeeds both in correctly identifying known key biomarkers for sensitivity towards specific drug compounds as well as in providing sets of potential candidates for additional computational biomarkers.

The Role of GDF15 in Regulating the Canonical Pathways of the Tumor Microenvironment in Wild-Type p53 Ovarian Tumor and Its Response to Chemotherapy

Simple Summary

Patients with wild-type p53 ovarian cancer appear to have a poorer survival rate than those with mutant p53 due to resistance to chemotherapy. The mechanism underlying this observation is not clearly understood. The aim of this study was to identify potential biomarkers regulated by p53 that conferred resistance using in vitro and in vivo studies. Growth differentiation factor 15 (GDF15) expression was demonstrated to be controlled by p53 in both ovarian cancer cell lines and orthotopic mouse models. The histological and RNAseq studies of the GDF15-knocked down, A2780 cell line-induced tumor revealed that the ratio and canonical pathways of stromal/tumor were modified by secretory GDF15.

Abstract

Background: The standard treatment of ovarian cancer is surgery followed by a chemotherapeutic combination consisting of a platinum agent, such as cisplatin and a taxane-like paclitaxel. We previously observed that patients with ovarian cancer wild-type for p53 had a poorer survival rate than did those with p53 mutations. Thus, a better understanding of the molecular changes of epithelial ovarian cancer cells with wild-type p53 in response to treatment with cisplatin could reveal novel mechanisms of chemoresistance. Methods: Gene expression profiling was performed on an ovarian cancer cell line A2780 with wild-type p53 treated with cisplatin. A gene encoding a secretory protein growth differentiation factor 15 (GDF15) was identified to be highly induced by cisplatin treatment in vitro. This was further validated in a panel of wild-type and mutant p53 ovarian cancer cell lines, as well as in mouse orthotopic models. The mouse tumor tissues were further analyzed by histology and RNA-seq. Results: GDF15 was identified as one of the highly induced genes by cisplatin or carboplatin in ovarian cancer cell lines with wild-type p53. The wild-type p53-induced expression of GDF15 and GDF15-confered chemotherapy resistance was further demonstrated in vitro and in vivo. This study also discovered that GDF15-knockdown (GDF15-KD) tumors had less stromal component and had different repertoires of activated and inhibited canonical pathways in the stromal cell and cancer cell components from that of the control tumors after cisplatin treatment. Conclusions: GDF15 expression from the wild-type p53 cancer cells can modulate the canonical pathways in the tumor microenvironment in response to cisplatin, which is a possible mechanism of chemoresistance.

Model-based optimization of combination protocols for irradiation-insensitive cancers

Alternations in the p53 regulatory network may render cancer cells resistant to the radiation-induced apoptosis. In this theoretical study we search for the best protocols combining targeted therapy with radiation to treat cancers with wild-type p53, but having downregulated expression of PTEN or overexpression of Wip1 resulting in resistance to radiation monotherapy. Instead of using the maximum tolerated dose paradigm, we exploit stochastic computational model of the p53 regulatory network to calculate apoptotic fractions for both normal and cancer cells. We consider combination protocols, with irradiations repeated every 12, 18, 24, or 36 h to find that timing between Mdm2 inhibitor delivery and irradiation significantly influences the apoptotic cell fractions. We assume that uptake of the inhibitor is higher by cancer than by normal cells and that cancer cells receive higher irradiation doses from intersecting beams. These two assumptions were found necessary for the existence of protocols inducing massive apoptosis in cancer cells without killing large fraction of normal cells neighboring tumor. The best found protocols have irradiations repeated every 24 or 36 h with two inhibitor doses per irradiation cycle, and allow to induce apoptosis in more than 95% of cancer cells, killing less than 10% of normal cells.

Protein-protein interaction modulators: advances, successes and remaining challenges

Modulating disease-relevant protein-protein interactions (PPIs) using small-molecule inhibitors is a quite indispensable diagnostic and therapeutic strategy in averting pathophysiological cues and disease progression. Over the years, targeting intracellular PPIs as drug design targets has been a challenging task owing to their highly dynamic and expansive interfacial areas (flat, featureless and relatively large). However, advances in PPI-focused drug discovery technology have been reported and a few drugs are already on the market, with some potential drug-like candidates already in clinical trials. In this article, we review the advances, successes and remaining challenges in the application of small molecules as valuable PPI modulators in disease diagnosis and therapeutics.

The Roles of p53 in Mitochondrial Dynamics and Cancer Metabolism: The Pendulum between Survival and Death in Breast Cancer?

Cancer research has been heavily geared towards genomic events in the development and progression of cancer. In contrast, metabolic regulation, such as aberrant metabolism in cancer, is poorly understood. Alteration in cellular metabolism was once regarded simply as a consequence of cancer rather than as playing a primary role in cancer promotion and maintenance. Resurgence of cancer metabolism research has identified critical metabolic reprogramming events within biosynthetic and bioenergetic pathways needed to fulfill the requirements of cancer cell growth and maintenance. The tumor suppressor protein p53 is emerging as a key regulator of metabolic processes and metabolic reprogramming in cancer cells&mdash;balancing the pendulum between cell death and survival. This review provides an overview of the classical and emerging non-classical tumor suppressor roles of p53 in regulating mitochondrial dynamics: mitochondrial engagement in cell death processes in the prevention of cancer. On the other hand, we discuss p53 as a key metabolic switch in cellular function and survival. The focus is then on the conceivable roles of p53 in breast cancer metabolism. Understanding the metabolic functions of p53 within breast cancer metabolism will, in due course, reveal critical metabolic hotspots that cancers advantageously re-engineer for sustenance. Illustration of these events will pave the way for finding novel therapeutics that target cancer metabolism and serve to overcome the breast cancer burden.

Ubiquitination and deubiquitination emerge as players in idiopathic pulmonary fibrosis pathogenesis and treatment

Idiopathic pulmonary fibrosis (IPF) is a fatal fibrotic lung disease that is associated with aberrant activation of TGF-β, myofibroblast differentiation, and abnormal extracellular matrix (ECM) production. Proper regulation of protein stability is important for maintenance of intracellular protein homeostasis and signaling. Ubiquitin E3 ligases mediate protein ubiquitination, and deubiquitinating enzymes (DUBs) reverse the process. The role of ubiquitin E3 ligases and DUBs in the pathogenesis of IPF is relatively unexplored. In this review, we provide an overview of how ubiquitin E3 ligases and DUBs modulate pulmonary fibrosis through regulation of both TGF-β-dependent and -independent pathways. We also summarize currently available small-molecule inhibitors of ubiquitin E3 ligases and DUBs as potential therapeutic strategies for the treatment of IPF.

USP15-dependent lysosomal pathway controls p53-R175H turnover in ovarian cancer cells

Gain-of-function p53 mutants such as p53-R175H form stable aggregates that accumulate in cells and play important roles in cancer progression. Selective degradation of gain-of-function p53 mutants has emerged as a highly attractive therapeutic strategy to target cancer cells harboring specific p53 mutations. We identified a small molecule called MCB-613 to cause rapid ubiquitination, nuclear export, and degradation of p53-R175H through a lysosome-mediated pathway, leading to catastrophic cancer cell death. In contrast to its effect on the p53-R175H mutant, MCB-613 causes slight stabilization of p53-WT and has weaker effects on other p53 gain-of-function mutants. Using state-of-the-art genetic and chemical approaches, we identified the deubiquitinase USP15 as the mediator of MCB-613's effect on p53-R175H, and established USP15 as a selective upstream regulator of p53-R175H in ovarian cancer cells. These results confirm that distinct pathways regulate the turnover of p53-WT and the different p53 mutants and open new opportunities to selectively target them.

MDM2 is a potential therapeutic target and prognostic factor for ovarian clear cell carcinomas with wild type TP53

MDM2, a ubiquitin ligase, suppresses wild type TP53 via proteasome-mediated degradation. We evaluated the prognostic and therapeutic value of MDM2 in ovarian clear cell carcinoma. MDM2 expression in ovarian cancer tissues was analyzed by microarray and real-time PCR, and its relationship with prognosis was evaluated by Kaplan-Meier method and log-rank test. The anti-tumor activities of MDM2 siRNA and the MDM2 inhibitor RG7112 were assessed by cell viability assay, western blotting, and flow cytometry. The anti-tumor effects of RG7112 in vivo were examined in a mouse xenograft model. MDM2 expression was significantly higher in clear cell carcinoma than in ovarian high-grade serous carcinoma (P = 0.0092) and normal tissues (P = 0.035). High MDM2 expression determined by microarray was significantly associated with poor progression-free survival and poor overall survival (P = 0.0002, and P = 0.0008, respectively). Notably, RG7112 significantly suppressed cell viability in clear cell carcinoma cell lines with wild type TP53. RG7112 also strongly induced apoptosis, increased TP53 phosphorylation, and stimulated expression of the proapoptotic protein PUMA. Similarly, siRNA knockdown of MDM2 induced apoptosis. Finally, RG7112 significantly reduced the tumor volume of xenografted RMG-I clear cell carcinoma cells (P = 0.033), and the density of microvessels (P = 0.011). Our results highlight the prognostic value of MDM2 expression in clear cell carcinoma. Thus, MDM2 inhibitors such as RG7112 may constitute a class of potential therapeutics.

Pre-clinical efficacy and synergistic potential of the MDM2-p53 antagonists, Nutlin-3 and RG7388, as single agents and in combined treatment with cisplatin in ovarian cancer

Ovarian cancer is the fifth leading cause of cancer-related female deaths. Due to serious side effects, relapse and resistance to standard chemotherapy, better and more targeted approaches are required. Mutation of the TP53 gene accounts for 50% of all human cancers. In the remaining malignancies, non-genotoxic activation of wild-type p53 by small molecule inhibition of the MDM2-p53 binding interaction is a promising therapeutic strategy. Proof of concept was established with the cis-imidazoline Nutlin-3, leading to the development of RG7388 and other compounds currently in early phase clinical trials. This preclinical study evaluated the effect of Nutlin-3 and RG7388 as single agents and in combination with cisplatin in a panel of ovarian cancer cell lines. Median-drug-effect analysis showed Nutlin-3 or RG7388 combination with cisplatin was additive to, or synergistic in a p53-dependent manner, resulting in increased p53 activation, cell cycle arrest and apoptosis, associated with increased p21^WAF1 protein and/or caspase-3/7 activity compared to cisplatin alone. Although MDM2 inhibition activated the expression of p53-dependent DNA repair genes, the growth inhibitory and pro-apoptotic effects of p53 dominated the response. These data indicate that combination treatment with MDM2 inhibitors and cisplatin has synergistic potential for the treatment of ovarian cancer, dependent on cell genotype.

Targeting RNA-Polymerase I in Both Chemosensitive and Chemoresistant Populations in Epithelial Ovarian Cancer

Purpose: A hallmark of neoplasia is increased ribosome biogenesis, and targeting this process with RNA polymerase I (Pol I) inhibitors has shown some efficacy. We examined the contribution and potential targeting of ribosomal machinery in chemotherapy-resistant and -sensitive models of ovarian cancer.Experimental Design: Pol I machinery expression was examined, and subsequently targeted with the Pol I inhibitor CX-5461, in ovarian cancer cell lines, an immortalized surface epithelial line, and patient-derived xenograft (PDX) models with and without chemotherapy. Effects on viability, Pol I occupancy of rDNA, ribosomal content, and chemosensitivity were examined.Results: In PDX models, ribosomal machinery components were increased in chemotherapy-treated tumors compared with controls. Thirteen cell lines were sensitive to CX-5461, with IC₅₀s 25 nmol/L-2 μmol/L. Interestingly, two chemoresistant lines were 10.5- and 5.5-fold more sensitive than parental lines. CX-5461 induced DNA damage checkpoint activation and G₂-M arrest with increased γH2AX staining. Chemoresistant cells had 2- to 4-fold increased rDNA Pol I occupancy and increased rRNA synthesis, despite having slower proliferation rates, whereas ribosome abundance and translational efficiency were not impaired. In five PDX models treated with CX-5461, one showed a complete response, one a 55% reduction in tumor volume, and one maintained stable disease for 45 days.Conclusions: Pol I inhibition with CX-5461 shows high activity in ovarian cancer cell lines and PDX models, with an enhanced effect on chemoresistant cells. Effects occur independent of proliferation rates or dormancy. This represents a novel therapeutic approach that may have preferential activity in chemoresistant populations. Clin Cancer Res; 23(21); 6529-40. ©2017 AACR.

Exome Sequencing Identifies Potentially Druggable Mutations in Nasopharyngeal Carcinoma

In this study, we first performed whole exome sequencing of DNA from 10 untreated and clinically annotated fresh frozen nasopharyngeal carcinoma (NPC) biopsies and matched bloods to identify somatically mutated genes that may be amenable to targeted therapeutic strategies. We identified a total of 323 mutations which were either non-synonymous (n = 238) or synonymous (n = 85). Furthermore, our analysis revealed genes in key cancer pathways (DNA repair, cell cycle regulation, apoptosis, immune response, lipid signaling) were mutated, of which those in the lipid-signaling pathway were the most enriched. We next extended our analysis on a prioritized sub-set of 37 mutated genes plus top 5 mutated cancer genes listed in COSMIC using a custom designed HaloPlex target enrichment panel with an additional 88 NPC samples. Our analysis identified 160 additional non-synonymous mutations in 37/42 genes in 66/88 samples. Of these, 99/160 mutations within potentially druggable pathways were further selected for validation. Sanger sequencing revealed that 77/99 variants were true positives, giving an accuracy of 78%. Taken together, our study indicated that ~72% (n = 71/98) of NPC samples harbored mutations in one of the four cancer pathways (EGFR-PI3K-Akt-mTOR, NOTCH, NF-κB, DNA repair) which may be potentially useful as predictive biomarkers of response to matched targeted therapies.

Annexin/S100A Protein Family Regulation through p14ARF-p53 Activation: A Role in Cell Survival and Predicting Treatment Outcomes in Breast Cancer

The annexin family and S100A associated proteins are important regulators of diverse calcium-dependent cellular processes including cell division, growth regulation and apoptosis. Dysfunction of individual annexin and S100A proteins is associated with cancer progression, metastasis and cancer drug resistance. This manuscript describes the novel finding of differential regulation of the annexin and S100A family of proteins by activation of p53 in breast cancer cells. Additionally, the observed differential regulation is found to be beneficial to the survival of breast cancer cells and to influence treatment efficacy. We have used unbiased, quantitative proteomics to determine the proteomic changes occurring post p14ARF-p53 activation in estrogen receptor (ER) breast cancer cells. In this report we identified differential regulation of the annexin/S100A family, through unique peptide recognition at the N-terminal regions, demonstrating p14ARF-p53 is a central orchestrator of the annexin/S100A family of calcium regulators in favor of pro-survival functions in the breast cancer cell. This regulation was found to be cell-type specific. Retrospective human breast cancer studies have demonstrated that tumors with functional wild type p53 (p53wt) respond poorly to some chemotherapy agents compared to tumors with a non-functional p53. Given that modulation of calcium signaling has been demonstrated to change sensitivity of chemotherapeutic agents to apoptotic signals, in principle, we explored the paradigm of how p53 modulation of calcium regulators in ER+ breast cancer patients impacts and influences therapeutic outcomes.

Specific TP53 Mutants Overrepresented in Ovarian Cancer Impact CNV, TP53 Activity, Responses to Nutlin-3a, and Cell Survival

Evolutionary Action analyses of The Cancer Gene Atlas data sets show that many specific p53 missense and gain-of-function mutations are selectively overrepresented and functional in high-grade serous ovarian cancer (HGSC). As homozygous alleles, p53 mutants are differentially associated with specific loss of heterozygosity (R273; chromosome 17); copy number variation (R175H; chromosome 9); and up-stream, cancer-related regulatory pathways. The expression of immune-related cytokines was selectively related to p53 status, showing for the first time that specific p53 mutants impact, and are related to, the immune subtype of ovarian cancer. Although the majority (31%) of HGSCs exhibit loss of heterozygosity, a significant number (24%) maintain a wild-type (WT) allele and represent another HGSC subtype that is not well defined. Using human and mouse cell lines, we show that specific p53 mutants differentially alter endogenous WT p53 activity; target gene expression; and responses to nutlin-3a, a small molecular that activates WT p53 leading to apoptosis, providing "proof of principle" that ovarian cancer cells expressing WT and mutant alleles represent a distinct ovarian cancer subtype. We also show that siRNA knock down of endogenous p53 in cells expressing homozygous mutant alleles causes apoptosis, whereas cells expressing WT p53 (or are heterozygous for WT and mutant p53 alleles) are highly resistant. Therefore, despite different gene regulatory pathways associated with specific p53 mutants, silencing mutant p53 might be a suitable, powerful, global strategy for blocking ovarian cancer growth in those tumors that rely on mutant p53 functions for survival. Knowing p53 mutational status in HGSC should permit new strategies tailored to control this disease.

Mutant p53 Promotes Epithelial Ovarian Cancer by Regulating Tumor Differentiation, Metastasis, and Responsiveness to Steroid Hormones

Mutations in the tumor protein p53 (TP53) are the most frequently occurring genetic events in high-grade ovarian cancers, especially the prevalence of the Trp53(R172H)-mutant allele. In this study, we investigated the impact of the Trp53(R172H)-mutant allele on epithelial ovarian cancer (EOC) in vivo We used the Pten/Kras(G12D)-mutant mouse strain that develops serous EOC with 100% penetrance to introduce the mutant Trp53(R172H) allele (homolog for human Trp53(R172H)). We demonstrate that the Trp53(R172H) mutation promoted EOC but had differential effects on disease features and progression depending on the presence or absence of the wild-type (WT) TP53 allele. Heterozygous WT/Trp53(R172H) alleles facilitated invasion into the ovarian stroma, accelerated intraperitoneal metastasis, and reduced TP53 transactivation activity but retained responsiveness to nutlin-3a, an activator of WT TP53. Moreover, high levels of estrogen receptor α in these tumors enhanced the growth of both primary and metastatic tumors in response to estradiol. Ovarian tumors homozygous for Trp53(R172H) mutation were undifferentiated and highly metastatic, exhibited minimal TP53 transactivation activity, and expressed genes with potential regulatory functions in EOC development. Notably, heterozygous WT/Trp53(R172H) mice also presented mucinous cystadenocarcinomas at 12 weeks of age, recapitulating human mucinous ovarian tumors, which also exhibit heterozygous TP53 mutations (∼50%-60%) and KRAS mutations. Therefore, we present the first mouse model of mucinous tumor formation from ovarian cells and supporting evidence that mutant TP53 is a key regulator of EOC progression, differentiation, and responsiveness to steroid hormones. Cancer Res; 76(8); 2206-18. ©2016 AACR.

A Decision Tree Based Classifier to Analyze Human Ovarian Cancer cDNA Microarray Datasets

Ovarian cancer is the deadliest gynaecological disease because of the high mortality rate and there is no any symptom in cancer early stage. It was often the terminal cancer period when patients were diagnosed with ovarian cancer and thus delays a good opportunity of treatment. The current common method for detecting ovarian cancer is blood testing for analyzing the tumor marker CA-125 of serum. However, specificity and sensitivity of CA-125 are insufficient for early detection. Therefore, it has become an urgent issue to look for an efficient method which precisely detects the tumor markers for ovarian cancer. This study aims to find the target genes of ovarian cancer by different algorithms of information science. Feature selection and decision tree were applied to analyze 9600 ovarian cancer-related genes. After screening the target genes, candidate genes will be analyzed by Ingenuity Pathway Analysis (IPA) software to create a genetic pathway model and to understand the interactive relationship in the different pathological stages of ovarian cancer. Finally, this research found 9 oncogenes associated with ovarian cancer and some genes had not been discovered in previous studies. This system will assist medical staffs in diagnosis and treatment at cancer early stage and improve the patient's survival.