Molecular characterization of an intact p53 pathway subtype in high-grade serous ovarian cancer

P53 Gene as a Promising Biomarker and Potential Target for the Early Diagnosis of Reproductive Cancers

One of the crucial aspects of cancer research is diagnosis with specificity and accuracy. Early cancer detection mostly helps make appropriate decisions regarding treatment and metastasis. The well-studied transcription factor tumor suppressor protein p53 is essential for maintaining genetic integrity. p53 is a key tumor suppressor that recognizes the carcinogenic biological pathways and eradicates them by apoptosis. A wide range of carcinomas, especially gynecological such as ovarian, cervical, and endometrial cancers, frequently undergo TP53 gene mutations. This study evaluates the potential of the p53 gene as a biological marker for the diagnosis of reproductive system neoplasms. Immunohistochemistry of p53 is rapid, easy to accomplish, cost-effective, and preferred by pathologists as a surrogate for the analysis of TP53 mutation. Thus, this review lays a groundwork for future efforts to develop techniques using p53 for the early diagnosis of cancer.

The Challenges and Prospects of p53-Based Therapies in Ovarian Cancer

It has been well established that mutations in the tumor suppressor gene, p53, occur readily in a vast majority of cancer tumors, including ovarian cancer. Typically diagnosed in stages three or four, ovarian cancer is the fifth leading cause of death in women, despite accounting for only 2.5% of all female malignancies. The overall 5-year survival rate for ovarian cancer is around 47%; however, this drops to an abysmal 29% for the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC). HGSOC has upwards of 96% of cases expressing mutations in p53. Therefore, wild-type (WT) p53 and p53-based therapies have been explored as treatment options via a plethora of drug delivery vehicles including nanoparticles, viruses, polymers, and liposomes. However, previous p53 therapeutics have faced many challenges, which have resulted in their limited translational success to date. This review highlights a selection of these historical p53-targeted therapeutics for ovarian cancer, why they failed, and what the future could hold for a new generation of this class of therapies.

A Network Pharmacology Study to Uncover the Mechanism of FDY003 for Ovarian Cancer Treatment

Ovarian cancer (OC) is one of the deadliest gynecological tumors responsible for 0.21 million deaths per year worldwide. Despite the increasing interest in the use of herbal drugs for cancer treatment, their pharmacological effects in OC treatment are not understood from a systems perspective. Using network pharmacology, we determined the anti-OC potential of FDY003 from a comprehensive systems view. We observed that FDY003 suppressed the viability of human OC cells and further chemosensitized them to cytotoxic chemotherapy. Through network pharmacological and pharmacokinetic approaches, we identified 16 active ingredients in FDY003 and their 108 targets associated with OC mechanisms. Functional enrichment investigation revealed that the targets may coordinate diverse cellular behaviors of OC cells, including their growth, proliferation, survival, death, and cell cycle regulation. Furthermore, the FDY003 targets are important constituents of diverse signaling pathways implicated in OC mechanisms (eg, phosphoinositide 3-kinase [PI3K]-Akt, mitogen-activated protein kinase [MAPK], focal adhesion, hypoxia-inducible factor [HIF]-1, estrogen, tumor necrosis factor [TNF], erythroblastic leukemia viral oncogene homolog [ErbB], Janus kinase [JAK]-signal transducer and activator of transcription [STAT], and p53 signaling). In summary, our data present a comprehensive understanding of the anti-OC effects and mechanisms of action of FDY003.

The misuse of distributional assumptions in functional class scoring gene-set and pathway analysis

Gene-set analysis (GSA) is a standard procedure for exploring potential biological functions of a group of genes. The development of its methodology has been an active research topic in recent decades. Many GSA methods, when newly proposed, rely on simulation studies to evaluate their performance with an implicit assumption that the multivariate expression values are normally distributed. This assumption is commonly adopted in GSAs, particularly those in the group of functional class scoring (FCS) methods. The validity of the normality assumption, however, has been disputed in several studies, yet no systematic analysis has been carried out to assess the effect of this distributional assumption. Our goal in this study is not to propose a new GSA method but to first examine if the multi-dimensional gene expression data in gene sets follow a multivariate normal (MVN) distribution. Six statistical methods in three categories of MVN tests were considered and applied to a total of 24 RNA data sets. These RNA values were collected from cancer patients as well as normal subjects, and the values were derived from microarray experiments, RNA sequencing, and single-cell RNA sequencing. Our first finding suggests that the MVN assumption is not always satisfied. This assumption does not hold true in many applications tested here. In the second part of this research, we evaluated the influence of non-normality on the statistical power of current FCS methods, both parametric and nonparametric ones. Specifically, the scenario of mixture distributions representing more than one population for the RNA values was considered. This second investigation demonstrates that the non-normality distribution of the RNA values causes a loss in the statistical power of these GSA tests, especially when subtypes exist. Among the FCS GSA tools examined here and among the scenarios studied in this research, the N-statistics outperform the others. Based on the results from these two investigations, we conclude that the assumption of MVN should be used with caution when evaluating new GSA tools, since this assumption cannot be guaranteed and violation may lead to spurious results, loss of power, and incorrect comparison between methods. If a newly proposed GSA tool is to be evaluated, we recommend the incorporation of a wide range of multivariate non-normal distributions or sampling from large databases if available.

Recombinant Human p53 Adenovirus Injection (rAd-p53) Combined with Chemotherapy for 4 Cases of High-grade Serous Ovarian Cancer

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC) is one of the most common ovarian epithelial carcinomas. It is highly invasive, easily recurs after systemic treatment, and has a poor prognosis. Despite many new chemotherapeutic drugs and trials of combinations of different regimens that have been used in treatment attempts, there has been no meaningful progress in the treatment of HGSOC. With the development of gene sequencing technology, gene therapy has become a new direction for tumors treatment. It is reported that the P53 has a very high mutation rate in HGSOC, which provides a theoretical basis for the application of gene therapy in HGSOC patients. Recombinant human p53 adenovirus injection (rAd-p53) is the world's first approved oncology gene therapy drug.

CASE REPORT

In this article, we retrospectively analyzed 4 cases of HGSOC patients treated with rAdp53. Three of them were recurrent ovarian cancer, and one was the initial treatment. The treatment method was to apply recombinant human p53 adenovirus injection (rAd-p53) to the lesions for local injection, 72 hours later, the lesions were injected with bleomycin or fluorouracil, and systemic intravenous chemotherapy was performed simultaneously. After rAd-p53 treatment, one of the three relapsed ovarian cancers achieved complete remission(CR), one achieved partial remission (PR), and one was stable disease (SD); the treatment-naive patient was operated after rAd-p53 combined with neoadjuvant chemotherapy and achieved pathological CR. Under the action of various mechanisms of P53, the subsequent tumor treatment showed the characteristics of slow tumor progression, no ascites, and local recurrence. As of the end of follow-up, the OS of 4 patients was 71-120 months.

CONCLUSION

Through the remarkable efficacy of these 4 cases, we can see that the application of rAdp53 combined with chemotherapy can effectively control tumor lesions, prolong the survival time of patients, improve the quality of life of patients, which provide valuable experiences for rAd-p53 treatment in ovarian cancer, promote the further development and progress of gene therapy in this field.

Comprehensive Gene Mutation Profiling of Circulating Tumor DNA in Ovarian Cancer: Its Pathological and Prognostic Impact

Simple Summary

Recent advances in cancer genomic medicine enabled gene-profiling of individual tumors using tumor tissue DNA. However, surgical tumor biopsy is invasive and sometimes difficult to perform in advanced/recurrent cancers. Liquid biopsy using circulating tumor DNA (ctDNA), which can analyze in real time and repeatedly, has attracted attention as a non-invasive technique, although it has been rarely used in ovarian cancer. The aim of the present study was to demonstrate the comprehensive gene mutation profiles of ctDNA in ovarian cancer patients with different histological subtypes and its association with clinicopathological and prognostic outcomes. Of 51 patients, 48 showed one or more non-synonymous somatic mutations, including TP53, APC, KRAS, EGFR, MET, and PIK3CA. Patients with higher ctDNA concentration or with any pathogenic mutations showed worse progression-free survival (PFS). These results suggest that ctDNA-based gene profiling may serve as a prognostic indicator and might help in establishing personalized therapeutic strategies for ovarian cancer.

Abstract

Liquid biopsies from circulating tumor DNA (ctDNA) have been employed recently as a non-invasive diagnostic tool for detecting cancer-specific gene mutations. Here, we show the comprehensive gene mutation profiles of ctDNA in 51 patients with different histological subtypes of stage I–IV ovarian cancer, and their association with clinical outcomes. The ctDNA extracted from pre-treatment patients’ plasma were analyzed using Cancer Personalized Profiling by Deep Sequencing targeting 197 genes. Of 51 patients, 48 (94%) showed one or more non-synonymous somatic mutations, including TP53 (37.3%), APC (17.6%), KRAS (15.7%), EGFR (13.7%), MET (11.8%), PIK3CA (11.8%), NPAP1 (11.8%), and ALK (9.8%). The most frequently mutated genes were as follows: TP53 in high-grade serous carcinoma (66.7%), APC in clear cell carcinoma (30.8%), PIK3CA in endometrioid carcinoma (40%), and KRAS in mucinous carcinoma (66.7%). Higher cell-free (cf)DNA concentration significantly correlated with worse progression-free survival (PFS) in all patients as well as stage III–IV patients (p = 0.01 and 0.005, respectively). Further, patients with any pathogenic mutations showed significantly worse PFS (p = 0.048). Blood tumor mutational burden detected from ctDNA did not significantly correlate with the histological subtypes or survival. Collectively, clinico-genomic profiles of individual ovarian cancer patients could be identified using ctDNA and may serve as a useful prognostic indicator. These findings suggest that ctDNA-based gene profiling might help in establishing personalized therapeutic strategies.

Identification of novel mutations of ovarian cancer-related genes from RNA-sequencing data for Japanese epithelial ovarian cancer patients

Ovarian cancer has the highest mortality rate among gynecological cancers. Gene mutations are involved in the carcinogenesis, metastasis, and therapeutic response in ovarian cancer. However, the variety and proportion of gene mutation is not fully analyzed in Japanese ovarian cancer patients, especially, in those with recurrent tumors. In the present study, RNA-sequencing was performed for 32 clinical ovarian specimens obtained from 24 Japanese patients (24 primary cancer specimens and 8 recurrent specimens paired with corresponding primary cancer specimens). Mutations in 24 primary specimens were analyzed by comparing the sequence data mapped on RefSeq genes with those in the public online databases BRCA Exchange, COSMIC, ClinVar, and cBioportal. Mutations were observed in TP53 in 16 specimens (67%), BRCA1 in 9 (38%), BRCA2 in 13 (54%), ARID1A in 3 (13%), PIK3CA in 2 (8%), KRAS in 1 (4%), PTEN in 1 (4%), and CTNNB1 in 1 (4%), excluding synonymous mutations. Among those identified muations, 13 of 14 mutations in TP53, 10 of 11 mutations of BRCA1, 10 of 23 mutation positions of BRCA2, none of 7 mutations of ARID1A, 1 mutation of PIK3CA, and 1 mutation of CTNNB1 were consistent with those reported in the public online databases; however, the other mutations identified were novel. Comparison between matched-paired specimens of primary and recurrent tumors revealed the changes of mutational status in expressed RNAs. RNA-sequencing-based mutation analysis will be useful to reveal ethnic differences of gene mutations in ovarian cancer and to understand the contribution of gene mutations to recurrence.

Clinical relevance of TP53 hotspot mutations in high-grade serous ovarian cancers

Background

Mutation of TP53 is the most frequent genetic alteration in high-grade serous ovarian cancer (HGSOC). The impact of hotspot mutations of TP53 and protein levels on patient outcomes in HGSOC has not been fully elucidated.

Methods

The study population (n = 791) comprised of HGSOC samples with TP53 mutation from TCGA and other publicly available data. Univariate and multivariate cox proportional hazards regression analyses were used to select variables that were correlated with patient survival.

Results

We assessed the effects of TP53 mutations based on type and individual hotspot mutations on patient outcomes in HGSOC. Only hotspot mutations were associated with outcomes. Three hotspot mutations: G266, Y163C, and R282, in aggregate were associated with a worsened overall and recurrence-free survival compared with other hotspot mutations (p < 0.0001 and p = 0.001), other non-hotspot missense mutations (p < 0.0001 and p = 0.008), truncated mutations (p < 0.0001 and p = 0.001), and all other mutations (p < 0.0001 and p = 0.001). Specific hotspot mutations were associated with different protein expression patterns consistent with different functions.

Conclusions

This study provides evidence that individual TP53 hotspot mutations have different impact on HGSOC patient outcomes and potentially TP53 function. Thus the status of particular TP53 aberrations could influence response to therapy and selection of therapeutic agents.

TP53 mutations in high grade serous ovarian cancer and impact on clinical outcomes: a comparison of next generation sequencing and bioinformatics analyses

Objective

Mutations in TP53 are found in the majority of high grade serous ovarian cancers, leading to gain of function or loss of function of its protein product, p53, involved in oncogenesis. There have been conflicting reports as to the impact of the type of these on prognosis. We aim to further elucidate this relationship in our cohort of patients.

Methods

229 patients with high grade serous ovarian cancer underwent tumor profiling through an institutional molecular screening program with targeted next generation sequencing. TP53 mutations were classified using methods previously described in the literature. Immunohistochemistry on formalin-fixed paraffin embedded tissue was used to assess for TP53 mutation. Using divisive hierarchal clustering, we generated patient clusters with similar clinicopathologic characteristics to investigate differences in outcomes.

Results

Six different classification schemes of TP53 mutations were studied. These did not show an association with first platinum-free interval or overall survival. Next generation sequencing reliably predicted mutation in 80% of cases, similar to the proportion detected by immunohistochemistry. Divisive hierarchical clustering generated four main clusters, with cluster 3 having a significantly worse prognosis (p<0.0001; log-rank test). This cluster had a higher concentration of gain of function mutations and these patients were less likely to have undergone optimal debulking surgery.

Conclusions

Different classifications of TP53 mutations did not show an impact on outcomes in this study. Immunohistochemistry was a good predictor for TP53 mutation. Cluster analysis showed that a subgroup of patients with gain of function mutations (cluster 3) had a worse prognosis.

Exome and copy number variation analyses of Mayer-Rokitansky-Küster- Hauser syndrome

Mayer–Rokitansky–Küster–Hauser (MRKH) syndrome is characterized by congenital absence of the vagina and uterus. We conducted genome-wide SNP analyses and exome sequencing to detect the causes of MRKH syndrome. We identified de novo variants of MYCBP2, NAV3, and PTPN3 in three families and a variant of MYCBP2 in a sporadic case. Here, we demonstrated the partial genetic makeup of Japanese MRKH syndrome.

Gene microarray analysis of lncRNA and mRNA expression profiles in patients with high‑grade ovarian serous cancer

High-grade ovarian serous cancer is known for its high rates of invasion and metastasis, and resultant high mortality rate. Therefore, research concerning biomarkers and underlying molecular mechanisms of high-grade ovarian serous cancer progression and prognosis are urgently required. Long non-coding RNAs (lncRNAs) have been the subject of an increasing number of studies, and certain lncRNAs have been demonstrated to serve an important function in the development and progression of various cancers, including HOX transcript antisense RNA, competing endogenous lncRNA 2 for microRNA let-7b, urothelial cancer associated 1, and H19, imprinted maternally expressed transcript (non-protein coding). However, few studies have investigated the differential expression of lncRNAs in high-grade ovarian serous cancer. In the present study, differences in lncRNA and mRNA expression profiles between high-grade ovarian serous cancer tissue samples and healthy fallopian tube tissue samples were investigated using microarray analysis, and the differential expression of lncRNAs and mRNAs was confirmed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Then, five abnormally expressed lncRNAs were selected, and the associations between these lncRNAs and ovarian cancer clinicopathological parameters were examined using RT-qPCR. The expression profiles of certain lncRNAs and mRNAs were confirmed to be altered between high-grade ovarian serous cancer tissues and healthy fallopian tube tissues. Furthermore, the expression levels of selected lncRNAs were associated with International Federation of Gynecology and Obstetrics stage and lymph node metastasis. These lncRNAs and mRNAs may therefore be involved in the pathogenesis of high-grade ovarian serous cancer. The results of the present study provide an experimental foundation for further exploration of the value of these lncRNAs and mRNAs in the early diagnosis and treatment of high-grade ovarian serous cancer.

Does a p53 "Wild-type" Immunophenotype Exclude a Diagnosis of Endometrial Serous Carcinoma?

An aberrant p53 immunophenotype may be identified in several histotypes of endometrial carcinoma, and is accordingly recognized to lack diagnostic specificity in and of itself. However, based on the high frequency with which p53 aberrations have historically been identified in endometrial serous carcinoma, a mutation-type immunophenotype is considered to be highly sensitive for the histotype. Using an illustrative case study and a review of the literature, we explore a relatively routine diagnostic question: whether the negative predictive value of a wild-type p53 immunophenotype for serous carcinoma is absolute, that is, whether a p53-wild type immunophenotype is absolutely incompatible with a diagnosis of serous carcinoma. The case is an advanced stage endometrial carcinoma that was reproducibly classified by pathologists from 3 institutions as serous carcinoma based on its morphologic features. By immunohistochemistry, the tumor was p53-wild type (DO-7 clone), diffusely positive for p16 (block positivity), and showed retained expression of PTEN, MSH2, MSH6, MLH1, and PMS2. Next generation sequencing showed that there indeed was an underlying mutation in TP53 (D393fs*78, R213*). The tumor was microsatellite stable, had a low mutational burden (4 mutations per MB), and displayed no mutations in the exonuclease domain of DNA polymerase epsilon (POLE) gene. Other genomic alterations included RB1 mutation (R46fs*19), amplifications in MYST3 and CRKL, and ARID1A deletion (splice site 5125-94_5138del108). A review of the recent literature identified 5 studies in which a total of 259 cases of serous carcinoma were whole-exome sequenced. The average TP53 mutational rate in endometrial serous carcinoma was only 75% (range, 60 to 88). A total of 12 (33%) of 36 immunohistochemical studies reported a p53-aberrant rate of <80% in endometrial serous carcinoma. We discuss in detail several potential explanations that may underlie the scenario of serous carcinoma-like morphology combined with p53-wild-type immunophenotype, including analytic limitations, a nonserous histotype displaying morphologic mimicry of serous carcinoma, and true biological phenomena (including the possibility of a TP53-independent pathway of endometrial serous carcinogenesis). Ultimately, our central thematic question is provisionally answered in the negative. At present, the available data would not support a categorical conclusion that a p53 alteration is a necessary and obligate component in the genesis and/or diagnosis of endometrial serous carcinoma. On the basis of their collective experience, the authors proffer some recommendations on the use of p53 immunohistochemistry in the histotyping of endometrial carcinomas.

Mutant p53 stimulates cell invasion through an interaction with Rad21 in human ovarian cancer cells

Missense mutations of TP53 are extremely common, and mutant p53 accumulation and gain-of-function play crucial roles in human ovarian cancer. Here, we investigated the role of mutant p53 in cell migration and invasion as well as its underlying molecular mechanisms in human ovarian cancer cells. Overexpression of mutant p53 significantly increased migration and invasion in p53-null SKOV3 cells. In contrast, knockdown of mutant p53 significantly compromised mutant p53-induced cell migration and invasion. Microarray analysis revealed that several migration/invasion-related genes, including S1PR1 (Sphingosine-1-phosphate receptor 1) and THBS1 (Thrombospodin 1), were significantly upregulated in SKOV3 cells that overexpressed mutant p53-R248 (SKOV3^R248). We found that Rad21 is involved in the transcriptional regulation of the migration/invasion-related genes induced by mutant p53-R248. Knockdown of Rad21 significantly attenuated the mutant p53-R248-induced invasion and the expressions of S1PR1 and THBS1. Moreover, co-immunoprecipitation and chromatin immunoprecipitation assays revealed that mutant p53 interacts with Rad21 and binds to the Rad21-binding elements in the S1PR1 and THBS1 genes. Finally, downregulation of S1PR1 significantly attenuated the invasion driven by mutant p53-R248. These novel findings reveal that mutant p53-R248 maintains gain-of-function activity to stimulate cell invasion and induces the related gene expressions through an interaction with Rad21 in human ovarian cancer cells.

TP53 mutations in epithelial ovarian cancer

Genomic sequencing analyses of a variety of human cancers have revealed that massive mutations of cancer-relevant genes are the major alterations in cancerous cells, and their mutation frequencies or rates are highly associated with the development, progression, metastasis, and drug resistance of cancers as well as their clinical outcomes and prognosis. One predominant genetic alternation in human epithelial ovarian cancer (EOC) is the mutation of TP53 that encodes the tumor suppressor p53 protein. This essay will review the most recent progress in understanding the role of TP53 mutations in development, progression, and metastasis of EOC, and discuss the potential of TP53 mutations as diagnostic and prognostic biomarkers as well as therapeutic targets for EOC.

Identification of novel exonic mobile element insertions in epithelial ovarian cancers

Mobile elements comprise about half of the human genome. Three active mobile element families (L1, Alu, and SVA) possibly cause diseases such as cancer. We conducted mobile element insertion (MEI) profiling of 44 epithelial ovarian cancers using exome-sequencing data. We identified a total of 106 MEIs using the Mobster program, 8 of which were novel exonic MEIs.