Oncomorphic TP53 Mutations in Gynecologic Cancers Lose the Normal Protein:Protein Interactions with the microRNA Microprocessing Complex

TP53 Sequencing and p53 Immunohistochemistry Predict Outcomes When Bevacizumab Is Added to Frontline Chemotherapy in Endometrial Cancer: An NRG Oncology/Gynecologic Oncology Group Study

PURPOSE

The status of p53 in a tumor can be inferred by next-generation sequencing (NGS) or by immunohistochemistry (IHC). We examined the association between p53 IHC and sequence and whether p53 IHC alone, or integrated with TP53 NGS, predicts the outcome.

METHODS

From GOG-86P, a randomized phase II study of chemotherapy combined with either bevacizumab or temsirolimus in advanced endometrial cancer, 213 cases had p53 protein expression data measured by IHC and TP53 NGS data. An analysis was designed to integrate p53 expression by IHC with the presence or absence of a TP53 mutation. These variables were further correlated with progression-free survival (PFS) and overall survival (OS) in the chemotherapy plus bevacizumab arms versus the chemotherapy plus temsirolimus arm.

RESULTS

In the analysis of p53 IHC, the most striking treatment effect favoring bevacizumab was in cases where p53 was overexpressed (PFS hazard ratio [HR]: 0.46, 95% CI, 0.26 to 0.88; OS HR: 0.31, 95% CI, 0.16 to 0.62). On integrated analysis, patients with TP53 missense mutations and p53 protein overexpression had a similar treatment effect on PFS (HR: 0.41, 95% CI, 0.22 to 0.83) and OS (HR: 0.28, 95% CI, 0.14 to 0.59) favoring bevacizumab plus chemotherapy relative to temsirolimus plus chemotherapy. Concordance between TP53 NGS and p53 IHC was 88%. Concordance was 92% when cases with TP53 mutations and POLE mutations or mismatch repair deficiency were removed.

CONCLUSION

IHC for p53 alone or when integrated with sequencing for TP53 identifies a specific, high-risk tumor genotype/phenotype for which bevacizumab is particularly beneficial in improving outcomes when combined with chemotherapy.

The Synthetic Curcumin Analog HO-3867 Rescues Suppression of PLAC1 Expression in Ovarian Cancer Cells

Elevated expression of placenta-specific protein 1 (PLAC1) is associated with the increased proliferation and invasiveness of a variety of human cancers, including ovarian cancer. Recent studies have shown that the tumor suppressor p53 directly suppresses PLAC1 transcription. However, mutations in p53 lead to the loss of PLAC1 transcriptional suppression. Small molecules that structurally convert mutant p53 proteins to wild-type conformations are emerging. Our objective was to determine whether the restoration of the wild-type function of mutated p53 could rescue PLAC1 transcriptional suppression in tumors harboring certain TP53 mutations. Ovarian cancer cells OVCAR3 and ES-2, both harboring TP53 missense mutations, were treated with the p53 reactivator HO-3867. Treatment with HO-3867 successfully rescued PLAC1 transcriptional suppression. In addition, cell proliferation was inhibited and cell death through apoptosis was increased in both cell lines. We conclude that the use of HO-3867 as an adjuvant to conventional therapeutics in ovarian cancers harboring TP53 missense mutations could improve patient outcomes. Validation of this conclusion must, however, come from an appropriately designed clinical trial.

Molecular Characterization of Non-responders to Chemotherapy in Serous Ovarian Cancer

Nearly one-third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial treatment with platinum-based therapy. Genomic and clinical characterization of these patients may lead to potential alternative therapies. Here, the objective is to classify non-responders into subsets using clinical and molecular features. Using patients from The Cancer Genome Atlas (TCGA) dataset with platinum-resistant or platinum-refractory HGSC, we performed a genome-wide unsupervised cluster analysis that integrated clinical data, gene copy number variations, gene somatic mutations, and DNA promoter methylation. Pathway enrichment analysis was performed for each cluster to identify the targetable processes. Following the unsupervised cluster analysis, three distinct clusters of non-responders emerged. Cluster 1 had overrepresentation of the stage IV disease and suboptimal debulking, under-expression of miRNAs and mRNAs, hypomethylated DNA, “loss of function” TP53 mutations, and the overexpression of genes in the PDGFR pathway. Cluster 2 had low miRNA expression, generalized hypermethylation, MUC17 mutations, and significant activation of the HIF-1 signaling pathway. Cluster 3 had more optimally cytoreduced stage III patients, overexpression of miRNAs, mixed methylation patterns, and “gain of function” TP53 mutations. However, the survival for all clusters was similar. Integration of genomic and clinical data from patients that do not respond to chemotherapy has identified different subgroups or clusters. Pathway analysis further identified the potential alternative therapeutic targets for each cluster.

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.

Identification of Novel Somatic TP53 Mutations in Patients with High-Grade Serous Ovarian Cancer (HGSOC) Using Next-Generation Sequencing (NGS)

Somatic mutations in TP53 are a hallmark of high-grade serous ovarian cancer (HGSOC), although their prognostic and predictive value as markers is not well defined. Next-generation sequencing (NGS) can identify novel mutations with high sensitivity, that may be repurposed as potential druggable anti-cancer targets and aid in therapeutic decisions. Here, a commercial NGS cancer panel comprising 26 genes, including TP53, was used to identify new genetic markers of platinum resistance and patient prognosis in a retrospective set of patients diagnosed with epithelial ovarian cancer. Six novel TP53 somatic mutations in untreated tumors from six distinct patients diagnosed with HGSOC were identified: TP53 c.728_739delTGGGCGGCATGA (p.Met243_Met247del, in-frame insertion or deletion (INDEL); TP53 c.795_809delGGGACGGAACAGCTT (p.Gly266_Phe270del, in-frame INDEL); TP53 c.826_827GC>AT (p.Ala276Ile, missense); TP53 c.1022insT (p.Arg342Profs*5, frameshift INDEL); TP53 c.1180delT (p.Ter394Aspfs*28, frameshift INDEL); and TP53 c.573insT (p.Gln192Serfs*17, frameshift INDEL). Novel TP53 variants were validated by classical sequencing methods and their impact on protein expression in tumors explored by immunohistochemistry. Further insights into the potential functional effect of the mutations were obtained by different in silico approaches, bioinformatics tools, and structural modeling. This discovery of previously unreported TP53 somatic mutations provides an opportunity to translate NGS technology into personalized medicine and identify new potential targets for therapeutic applications.

microRNAs are differentially regulated between MDM2-positive and negative malignant pleural mesothelioma

Background

Malignant pleural mesothelioma (MPM) is a highly aggressive tumour first-line treated with a combination of cisplatin and pemetrexed. MDM2 and P14/ARF (CDKN2A) are upstream regulators of TP53 and may contribute to its inactivation. In the present study, we now aimed to define the impact of miRNA expression on this mechanism.

Material and Methods

24 formalin-fixed paraffin-embedded (FFPE) tumour specimens were used for miRNA expression analysis of the 800 most important miRNAs using the nCounter technique (NanoString). Significantly deregulated miRNAs were identified before a KEGG-pathway analysis was performed.

Results

17 miRNAs regulating TP53, 18 miRNAs regulating MDM2, and 11 miRNAs directly regulating CDKN2A are significantly downregulated in MDM2-expressing mesotheliomas. TP53 is downregulated in MDM2-negative tumours through miRNAs with a miSVR prediction score of 11.67, RB1 with a prediction score of 8.02, MDM2 with a prediction score of 4.50 and CDKN2A with a prediction score of 1.27.

Conclusion

MDM2 expression seems to impact miRNA expression levels in MPM. Especially, miRNAs involved in TP53-signaling are strongly decreased in MDM2-positive mesotheliomas. A better understanding of its tumour biology may open the chance for new therapeutic approaches and thereby augment patients' outcome.

Genome-wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer

Cancer typically develops due to genetic abnormalities, but a single gene abnormality cannot completely account for the onset of cancer. The Cancer Genome Atlas (CGA) project was conducted for the cross-sectional genome-wide analysis of numerous genetic abnormalities in various types of cancer. This approach has facilitated the identification of novel AT-rich interaction domain 1A gene mutations in ovarian clear cell carcinoma, frequent tumor protein 53 (TP53) gene mutations in high-grade ovarian serous carcinoma, and Kirsten rat sarcoma and B-rapidly accelerated fibrosarcoma proto-oncogene, serine/threonine kinase gene mutations in low-grade ovarian serous carcinoma. Genome-wide analysis of endometrial cancers has led to the establishment of four subgroups: Polymerase ultramutated, microsatellite instability hypermutated, genome copy-number low and genome copy-number high. These results may facilitate the improvement of the prediction of patient prognosis and therapeutic sensitivity in various types of gynecologic cancer. The enhanced use of currently available therapeutic agents and the development of novel drugs may be facilitated by the novel classification of ovarian cancer based on TP53 mutations, the efficacy of poly (ADP-ribose) polymerase inhibitors for tumors with breast cancer 1/2 mutations and the effect of phosphoinositide-3-kinase (PI3K)/mammalian target of rapamycin inhibitors for tumors with mutations in the PI3K/protein kinase B signaling pathway. Important results have been revealed by genome-wide analyses; however, the pathogenic underlying mechanisms of gynecologic cancer will require further studies and multilateral evaluation using epigenetic, transcriptomic and proteomic analyses, in addition to genomic analysis.

Confronting the Care Delivery Challenges Arising from Precision Medicine

Understanding the biology of cancer at the cellular and molecular levels, and the application of such knowledge to the patient, has opened new opportunities and uncovered new obstacles to quality cancer care delivery. Benefits include our ability to now understand that many, if not most, cancers are not one-size-fits-all. Cancers are a variety of diseases for which intervention may be very different. This approach is beginning to bear fruit in gynecologic cancers where we are investigating therapeutic optimization at a more focused level, that while not yet precision care, is perhaps much improved. Obstacles to quality care for patients come from many directions. These include incomplete understanding of the role of the mutant proteins in the cancers, the narrow spectrum of agents, broader mutational profiles in solid tumors, and sometimes overzealous application of the findings of genetic testing. This has been further compromised by the unbridled use of social media by all stakeholders in cancer care often without scientific qualification, where anecdote sometimes masquerades as a fact. The only current remedy is to wave the flag of caution, encourage all patients who undergo genetic testing, either germline or somatic, to do so with the oversight of genetic counselors and physician scientists knowledgeable in the pathways involved. This aspiration is accomplished with well-designed clinical trials that inform next steps in this complex and ever evolving process.