Significance of TP53 Mutational Status-Associated Signature in the Progression and Prognosis of Endometrial Carcinoma

Background:TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status-associated signature in EC. In this study, we aim to conduct a TP53 mutation associated prognostic genes signature for EC.Methods: Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation associated prognostic genes signature. The overall survival rate between the high-risk and low-risk groups was compared by Kaplan-Meier (K-M) method. Results: We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status-associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high- and low-risk groups. Kaplan–Meier (K-M) analysis indicated that the patients in the high-risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status-associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens.Conclusion: In summary, our research constructed a powerful TP53 mutational status-associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.

TP53 Mutational Status-Based Genomic Signature for Prognosis and Predicting Therapeutic Response in Pancreatic Cancer

TP53 mutation is a critical driver mutation that affects the carcinogenesis and prognosis of patients with pancreatic cancer (PC). Currently, there is no driver mutation-derived signature based on TP53 mutational status for prognosis and predicting therapeutic response in PC. In the present study, we characterized the TP53 mutational phenotypes in multiple patient cohorts and developed a prognostic TP53-associated signature based on differentially expressed genes between PC samples with mutated TP53 and wild-type TP53. Comprehensive investigations were carried out in prognostic stratification, genetic variation, immune cell infiltration, and efficacy prediction of chemotherapy and targeted therapy. We found that TP53 mutation commonly occurred as a survival-related driver mutation in PC. In total, 1,154 differentially expressed genes were found between two distinct TP53 mutational phenotypes. A five-gene TP53-associated signature was constructed in The Cancer Genome Atlas (TCGA) cohort by least absolute shrinkage and selection operator (LASSO)–Cox analysis and proven to be a robust prognostic predictor, which performed well in three independent Gene Expression Omnibus (GEO) validating cohorts. Remarkably, patients in the low-risk group were characterized with decreased tumor mutation burden and activity of immunity, with favorable prognosis. Higher fractions of macrophages M0 and impaired CD8 + T cells were observed in patients in the high-risk group, suggesting immunosuppression with poor survival. Patients in the high-risk group also demonstrated enhanced response to specific chemotherapeutic agents, including gemcitabine and paclitaxel. Several targeted inhibitors, like histamine receptor inhibitor, were screened out as promising drugs for PC treatment. Collectively, the TP53-associated signature is a novel prognostic biomarker and predictive indicator of PC. The signature could contribute to optimizing prognostic stratification and guide effective PC treatments.

Inhibitor of DNA-binding family regulates the prognosis of ovarian cancer

Aim: The mechanistic role of inhibitor of DNA binding or differentiation (ID) family in ovarian cancer (OC) has remained unclear. Materials & methods: We used the Oncomine, GEPIA, Kaplan–Meier Plotter, cBioPortal, SurvExpress, PROGgene V2, TIMER, and FunRich to evaluate the prognostic value of IDs in patients with OC. Results: the mRNA transcripts of all IDs were markedly downregulated in OC compared with normal tissue. The prognostic value of IDs was also explored within the subtypes, pathological stages, clinical stages and TP53 mutational status. The group with low-risk IDs showed relatively good overall survival (OS) compared with the high-risk group. Conclusion: ID1/3/4 may be exploited as promising prognostic biomarkers and therapeutic targets in OC patients.

Contribution of Idasanutlin Exposure to Safety, Pharmacodynamics and Clinical Response of Patients with Acute Myeloid Leukemia Treated with Idasanutlin + Cytarabine in Phase I and III Studies

Background: Myelosuppression, and especially severe and prolonged neutropenia, can make patients (pts) with acute myeloid leukemia (AML) susceptible to fatal infections. Idasanutlin (idasa), a MDM2 antagonist promoting p53 tumor suppressor activity, showed tolerable safety and preliminary clinical activity alone and in combination with cytarabine (C) in pts with AML in a Phase I/Ib study (NCT01773408; NP28679). In the Phase III MIRROS study (NCT02545283; WO29519) comparing idasa + cytarabine (idasa-C) to placebo-C in pts with relapsed or refractory (r/r) AML, idasa-C did not improve overall survival (OS) in TP53-wild type pts (Konopleva, EHA 2020). The proportion of pts with composite complete remission (CR) at end of induction (EoI) was higher with idasa-C vs placebo-C; however, response at EoI did not translate into OS benefit. Longer and more pronounced neutropenia was observed with idasa-C. Here we investigated the contribution of idasa exposure variability to those findings, in particular, the relationship between exposure and toxicity and efficacy in pts with AML. Methods: MIRROS and NP28679 have been previously described (Montesinos, Future Oncol, 2020; Martinelli, EHA 2016). Plasma idasa concentrations were collected during induction and consolidation in 407 pts with AML (MIRROS: 285 with r/r AML; NP28679: 122 with AML), and a population pharmacokinetic (PK) analysis was completed. For each pt, predicted average concentrations values (Cav) were computed, as the ratio of cumulative area under the curve over the duration of the induction treatment period (5 days). Tertiles of Cav (low, medium, high) were used to reflect variability in exposure among pts. Logistic regression models assessed correlations between the probability of occurrence of adverse events (serious AEs [SAEs], febrile neutropenia), the probability of being responders at EoI and idasa exposure. These PK/pharmacodynamic (PD) analyses were restricted to pts treated with the idasa spray-dried powder formulation. In addition, the relationships between concentrations of the p53 target macrophage inhibitory cytokine 1 (MIC-1) and idasa exposure was characterized using an indirect PK/PD model developed in 245 pts with solid tumors (NCT01462175; NP27872), AML (NP28679) or polycythemia vera (NCT03287245; NP39761). Results: Idasa exposure was highly variable with lower exposure mainly associated with higher body weight and male sex. In addition, pts with vomiting during treatment had reduced exposure. However, a large part of the interpatient variability remains mostly unexplained. The exposure-response analysis, conducted in 316 pts with AML, showed a higher risk of SAEs with higher idasa exposure (Cav) during induction (p=0.03). There was also an association between idasa exposure and occurrence of febrile neutropenia (p=0.022; Figure 1). However, due to exposure variability, reducing the dose from 300 mg twice daily to 300 mg daily would result in a similar risk of febrile neutropenia at the median exposures (approximately 40%). No association between idasa exposure and complete remission rates at EoI was observed (N=295, p=0.622; Figure 2). Dose-exposure related increases in MIC-1 were observed at all idasa doses investigated, starting at the 100 mg total daily dose. Pts with AML in the lower tertile of exposure (Cav: 2503-5797 ng/mL) showed lower maximum MIC-1 release from baseline, contrary to pts from the highest tertile (7981-14651 ng/mL). MIC-1 release is present regardless of TP53 mutational status, suggesting a systemic rather than tumor derived induction. No difference was seen between responders and non-responders at EoI. Conclusions: Combined clinical pharmacology data in pts with AML receiving idasa revealed 1) Variability in idasa exposure does not correlate with clinical outcomes in pts treated with idasa-C. 2) p53 engagement (i.e., MIC-1 biomarker release) is seen at all dose levels investigated; however, MIC-1 release does not correlate with clinical response at EoI or TP53 mutational status. 3) The risk of SAEs is higher in pts with greater idasa exposure. 4) Data do not support lowering the dose of idasa to mitigate the risk of febrile neutropenia while sustaining clinical efficacy at idasa-C doses investigated. Disclosures Jamois: Roche: Current Employment, Current equity holder in publicly-traded company, Other: Roche: Support of parent study and funding of editorial support. Anders:Roche: Current Employment, Other: Support of parent study and funding of editorial support. Beckermann:Roche: Current Employment, Current equity holder in publicly-traded company, Other: Support of parent study and funding of editorial support; Novartis: Current equity holder in publicly-traded company. Genevray:Roche: Current Employment, Other: Support of parent study and funding of editorial support. Mundt:Swissmedic (starting September 2020): Current Employment; Roche: Current equity holder in publicly-traded company, Other: Support of parent study and funding of editorial support. Petry:Roche: Current Employment, Current equity holder in publicly-traded company, Other: Support of parent study and funding of editorial support. Yang:Certara: Current Employment; Roche: Other: Support of parent study and funding of editorial support. Kassir:Certara: Current Employment; Roche: Other: Support of parent study and funding of editorial support. Schmitt:F. Hoffmann-La Roche Ltd: Current Employment, Current equity holder in publicly-traded company.

TP53 in Myelodysplastic Syndromes: Recent Biological and Clinical Findings

TP53 dysregulation plays a pivotal role in the molecular pathogenesis of myelodysplastic syndromes (MDS), identifying a subgroup of patients with peculiar features. In this review we report the recent biological and clinical findings of TP53-mutated MDS, focusing on the molecular pathways activation and on its impact on the cellular physiology. In MDS, TP53 mutational status is deeply associated with del(5q) syndrome and its dysregulation impacts on cell cycle, DNA repair and apoptosis inducing chromosomal instability and the clonal evolution of disease. TP53 defects influence adversely the MDS clinical outcome and the treatment response rate, thus new therapeutic approaches are being developed for these patients. TP53 allelic state characterization and the mutational burden evaluation can therefore predict prognosis and identify the subgroup of patients eligible for targeted therapy. For these reasons, in the era of precision medicine, the MDS diagnostic workup cannot do without the complete assessment of TP53 mutational profile.

Radiomic profiles via machine learning to predict response, overall survival, and KRAS status in metastatic colorectal tumors treated with FOLFOX/bevacizumab/hydroxychloroquine.

e15125 Background: Autophagy is a resistance mechanism to chemotherapy that is inhibited by hydroxychloroquine (HCQ). We have reported a phase II trial of FOLFOX/bevacizumab/HCQ in 28 evaluable patients with untreated metastatic colorectal cancer (mCRC). Overall response rate was 68%, with 11% complete response (CR) and 57% partial response (PR), while stable disease (SD) was seen in 30%. We hypothesize that analysis of CT imaging features via machine learning (ML) will enhance subtle yet important radiographic characteristics, and reveal imaging signatures determinant of outcome and mutational status. Methods: Baseline CT images were collected and 1265 quantitative imaging (QI) features extracted across all the metastatic sites – liver, lung, and lymph nodes – including descriptors of size, morphology, texture, and intensity. Cross-validated sequential feature selection coupled with support vector machine (SVM) was used to determine the most discriminative QI features for our integrative predictor of response and mutational status, and support vector regression (SVR) was used to derive imaging predictors of overall survival. The model predictions were compared with actual clinical results, including response, survival, and genomic aberrations. Results: Various QI features, primarily descriptive of texture and tumor volume, were determined as most important by the ML predictor. Using this signature, our predictor classified “Responder (PR+CR) vs Non-responder (SD)” with an accuracy of 85% [sensitivity(se) = 0.84, specificity(sp) = 0.71, AUC = 0.85]. The QI features were also able to detect KRAS and TP53 mutational status with an accuracy of 88% [se = 0.92, sp = 0.85, AUC = 0.87] and 86% [se = 0.80, sp = 0.90, AUC = 0.84], respectively. The SVM model predicted overall survival greater than the median (32 mo) with an accuracy of 86% [se = 0.93, sp = 0.79, AUC = 0.87]. The Pearson correlation coefficient between the SVR score and overall survival was estimated to be 0.73 (p < 0.0001). Conclusions: Radiomic analysis of baseline CT imaging features analyzed by ML yielded an imaging signature predictive of response, survival, and KRAS and TP53 mutational status. If validated in a larger clinical data set, machine learning may offer a predictive biomarker to aid clinical decision making for mCRC patients.

TP53 mutations in circulating tumor DNA in men with metastastic castration-resistant prostate cancer mCRPC.

249 Background: Genes involved in mCRPC, including the tumor suppressor gene TP53, can be monitored with ctDNA but implications are unclear. Methods: Between 8/6/15 to 9/19/18, patients with mCRPC with available ctDNA genomic data using Guardant360 (Guardant360, Redwood City, CA) were included. Relationships between various lines of therapy and TP53 mutational status were analyzed. Patients positive for TP53 mutants were categorized using mutant allelic fraction of > 0%, ≥0.5%, ≥1% and ≥5%. Results: This study included 215 patients with mCRPC, median age 70 (41-90), and 80% Caucasians who had ctDNA after one line treatment for CRPC that included abiraterone (55%), enzalutamide (22%), and sipuleucel T (21%). Frequent co-alterations with TP53 mutants after 1 line of CRPC therapy included AR (14%), NF1 (5%), EGFR (4%), and PIK3CA (4%). See Table for relationships between lines of therapy and mutant TP53 allelic fraction. Conclusions: In this cohort of men with mCRPC, a higher mutational burden of TP53 in ctDNA was frequent and particularly associated with multiple lines of therapy. [Table: see text]