Correia, Cristina

Abstract Background: The kinases ataxia-telangiectasia-mutated-and-Rad3-related (ATR), checkpoint kinase 1 (CHK1) and WEE1 participate in the response to replication stress. Inhibitors of ATR, WEE1 and CHK1 are being tested for antineoplastic activity as monotherapies and in combination with chemotherapy. Although these agents impair cell cycle checkpoints, fork stabilization, origin firing and homologous recombination (HR), little is known about the apoptotic pathways that are engaged and the critical mediators activating cell death mechanisms. The present study utilizes high grade serous ovarian cancer (HGSOC) cell lines and patient derived xenografts (PDXs) to identify the primary mechanism of cell death in ovarian cancer and assess changes involved in the resistance setting after treatment with these inhibitors. Methods: A panel of HGSOC cell lines was examined for responses to ceralasertib (ATRi), prexasertib (CHK1i) or adavosertib (WEE1i) using colony forming assays, immunoblotting and assays for apoptosis. Mechanisms involved in acquired resistance and downstream changes in cell fate were evaluated by generating prexasertib-resistant HGSOC cell lines. Subsequent NGS analysis was performed in the sensitive and resistant pairs. Results: Irrespective of the homologous recombination (HR) status, ovarian cell lines and PDXs underwent cell death during prolonged exposure at clinically achievable concentrations. Treatment of ovarian cancer cell lines with ATRi, CHK1i or WEE1i activated the replication checkpoint, consistent with previously published reports. The subsequent apoptotic response involved PMAIP1 and BCL2L11 upregulation rather than the TNFa-induced death receptor-mediated apoptosis we recently described in acute leukemia (Cancer Res. PMID: 33414171). Additionally, ovarian lines selected for CHK1i resistance failed to die in response to either ATRi or WEE1i. Conclusions: Prexasertib, ceralasertib, and adavosertib exhibit monotherapy activity in both HR deficient and proficient HGSOC cell lines and PDX models. Unlike AML, death receptor mediated apoptosis was not observed; instead, the primary mechanism of cell killing in HGSOC lines involves activation of the mitochondrial apoptotic pathway. Cross-resistance of these DNA damage repair modulators is likely multifactorial and mainly involves diminished replication stress response. Citation Format: Annapoorna Venkatachalam, Kevin L. Peterson, Cristina Correia, Karen S. Flatten, Xianon Hou, Paula A. Schneider, Emily Balczewski, Cordelia McGehee, Rachel M. Hurley, Xue W. Meng, Chance Sine, Rameen Shah, Nicole Vincelettte, Husheng Ding, Hu Li, Saravut (John) Weroha, Scott H. Kaufmann. CHK1 inhibitor prexasertib induces NOXA-dependent apoptosis in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1832.

Abstract Background: Large scale genetic perturbations screens have been instrumental for many key discoveries. In the last decade sequence specific genetic perturbations created RNAi and CRISPR (PMID: 25446316). Recently, specific genome targeting approaches using single guide RNAs (sgRNAs) for the CRISPR-Cas9 system have been repurposed to induce sequence-specific repression or activation of gene expression at a genome-wide scale. Different perturbation approaches have different effects and encompass a trade-off between specificity and duration in establishing a measurable perturbation which can result in different biological readouts. However, bench-side strategies are time consuming and expensive. The method described here aims to build a systems-based computational platform to assess pharmacological and biological perturbations at genome-wide network level.Methods: Our network tool NetDecoder (Nucleic Acids Res. 2016; 44(10):e100) that models genome-wide information flow will be used to build context specific protein-protein interaction networks. These networks will be subsequently subjected to in silico perturbations and their impacts on network properties will be assessed. AVANA and Demeter datasets will be used during method validation procedures. Results: Using publicly available expression datasets we generated context specific Breast Cancer networks and individually manipulated nodes and edges of context-specific networks associated with pharmacological FDA approved targets. Our perturbation networks captured cellular rewiring by engulfing new gene players, alterations of the network size and its connectivity. Conclusions: Our in-silico genome wide perturbation platform provides a flexible approach to fine-tune single and tandem manipulations, allowing for inexpensively monitoring a range of pharmacological interventions using large omics data. Citation Format: Cristina Correia, Choong Yong Ung, Cheng Zhang, Scott H. Kaufmann, Hu Li. A genome wide pharmacological perturbation platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1226.

Abstract Current understandings of individual disease etiology and therapeutics are limited despite great need. To fill the gap, we propose a novel computational pipeline which collects potent disease gene cooperative pathways to envision individualized disease etiology and therapies. Our algorithm constructs individualized disease modules de novo which enable us to elucidate the importance of mutated genes in specific patients and to understand the synthetic penetrance of these genes across patients. We reveal that importance of notorious cancer drivers TP53 and PIK3CA fluctuate widely across breast cancers and peak in tumors with distinct numbers of mutations, and that rarely mutated genes such as XPO1 and PLEKHA1 have high disease module importance in specific individuals. Furthermore, individualized module disruption enables us to devise customized singular and combinatorial target therapies which were highly varied across patients demonstrating the need for precision therapeutics pipelines. As the first analysis of de novo individualized disease modules, we illustrate the power of individualized disease modules for precision medicine by providing deep novel insights on the activity of diseased genes in individuals. Citation Format: Taylor Weiskittel, Cristina Correia, Choong Ung, Cheng Zhang, Hu Li. De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 490.

Abstract Cytotoxic CD8+ T cells (CTL) are a crucial component of the immune system notable for their ability to eliminate rapidly proliferating malignant cells. However, the T-cell intrinsic factors required for human CTLs to accomplish highly efficient antitumor cytotoxicity are not well defined. By evaluating human CD8+ T cells from responders versus nonresponders to treatment with immune checkpoint inhibitors, we sought to identify key factors associated with effective CTL function. Single-cell RNA-sequencing analysis of peripheral CD8+ T cells from patients treated with anti–PD-1 therapy showed that cells from nonresponders exhibited decreased expression of the cytolytic granule-associated molecule natural killer cell granule protein-7 (NKG7). Functional assays revealed that reduced NKG7 expression altered cytolytic granule number, trafficking, and calcium release, resulting in decreased CD8+ T-cell–mediated killing of tumor cells. Transfection of T cells with NKG7 mRNA was sufficient to improve the tumor-cell killing ability of human T cells isolated from nonresponders and increase their response to anti–PD-1 or anti–PD-L1 therapy in vitro. NKG7 mRNA therapy also improved the antitumor activity of murine tumor antigen–specific CD8+ T cells in an in vivo model of adoptive cell therapy. Finally, we showed that the transcription factor ETS1 played a role in regulating NKG7 expression. Together, our results identify NKG7 as a necessary component for the cytotoxic function of CD8+ T cells and establish NKG7 as a T-cell–intrinsic therapeutic target for enhancing cancer immunotherapy. See related article by Li et al., p. 154.

Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has revolutionized biomedical imaging analysis, drug discovery, and systems biology, is an ideal strategy to fill these gaps in single-cell studies. Machine learning additionally has proven to be remarkably synergistic with single-cell data because it remedies unique challenges while capitalizing on the positive aspects of single-cell data. In this review, we describe how systems-biology algorithms have layered machine learning with biological components to provide systems level analyses of single-cell omics data, thus elucidating complex biological mechanisms. Accordingly, we highlight the trifecta of single-cell, systems-biology, and machine-learning approaches and illustrate how this trifecta can significantly contribute to five key areas of scientific research: cell trajectory and identity, individualized medicine, pharmacology, spatial omics, and multi-omics. Given its success to date, the systems-biology, single-cell omics, and machine-learning trifecta has proven to be a potent combination that will further advance biomedical research.

Abstract Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated, leading to homologous recombination (HR) deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived ovarian cancer xenograft PH039, which lacks HR gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by cyclical niraparib treatment in vivo. PH039 acquired PARPi resistance by the third treatment cycle and grew through subsequent treatment with either niraparib or rucaparib. Transcriptional profiling throughout the course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of ovarian cancer samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated an association between loss of RAD51C methylation prior to on-study biopsy and limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide a model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

Oncolytic viruses (OVs) are a class of immunotherapeutic agents with promising preclinical results for the treatment of glioblastoma (GBM) but have shown limited success in recent clinical trials. Advanced bioengineering principles from disciplines such as synthetic and systems biology are needed to overcome the current challenges faced in developing effective OV-based immunotherapies for GBMs, including off-target effects and poor clinical responses. Synthetic biology is an emerging field that focuses on the development of synthetic DNA constructs that encode networks of genes and proteins (synthetic genetic circuits) to perform novel functions, whereas systems biology is an analytical framework that enables the study of complex interactions between host pathways and these synthetic genetic circuits. In this review, the authors summarize synthetic and systems biology concepts for developing programmable, logic-based OVs to treat GBMs. Programmable OVs can increase selectivity for tumor cells and enhance the local immunological response using synthetic genetic circuits. The authors discuss key principles for developing programmable OV-based immunotherapies, including how to 1) select an appropriate chassis, a vector that carries a synthetic genetic circuit, and 2) design a synthetic genetic circuit that can be programmed to sense key signals in the GBM microenvironment and trigger release of a therapeutic payload. To illustrate these principles, some original laboratory data are included, highlighting the need for systems biology studies, as well as some preliminary network analyses in preparation for synthetic biology applications. Examples from the literature of state-of-the-art synthetic genetic circuits that can be packaged into leading candidate OV chassis are also surveyed and discussed.

Abstract Although inhibitors of the kinases CHK1, ATR, and WEE1 are undergoing clinical testing, it remains unclear how these three classes of agents kill susceptible cells and whether they utilize the same cytotoxic mechanism. Here we observed that CHK1 inhibition induces apoptosis in a subset of acute leukemia cell lines in vitro, including TP53-null acute myeloid leukemia (AML) and BCR/ABL–positive acute lymphoid leukemia (ALL), and inhibits leukemic colony formation in clinical AML samples ex vivo. In further studies, downregulation or inhibition of CHK1 triggered signaling in sensitive human acute leukemia cell lines that involved CDK2 activation followed by AP1-dependent TNF transactivation, TNFα production, and engagement of a TNFR1- and BID-dependent apoptotic pathway. AML lines that were intrinsically resistant to CHK1 inhibition exhibited high CHK1 expression and were sensitized by CHK1 downregulation. Signaling through this same CDK2–AP1–TNF cytotoxic pathway was also initiated by ATR or WEE1 inhibitors in vitro and during CHK1 inhibitor treatment of AML xenografts in vivo. Collectively, these observations not only identify new contributors to the antileukemic cell action of CHK1, ATR, and WEE1 inhibitors, but also delineate a previously undescribed pathway leading from aberrant CDK2 activation to death ligand–induced killing that can potentially be exploited for acute leukemia treatment. Significance: This study demonstrates that replication checkpoint inhibitors can kill AML cells through a pathway involving AP1-mediated TNF gene activation and subsequent TP53-independent, TNFα-induced apoptosis, which can potentially be exploited clinically.

Abstract Purpose: To determine if the degree of estrogen suppression with aromatase inhibitors (AI: anastrozole, exemestane, letrozole) is associated with efficacy in early-stage breast cancer, and to examine for differences in the mechanism of action between the three AIs. Experimental Design: Matched case–control studies [247 matched sets from MA.27 (anastrozole vs. exemestane) and PreFace (letrozole) trials] were undertaken to assess whether estrone (E1) or estradiol (E2) concentrations after 6 months of adjuvant therapy were associated with risk of an early breast cancer event (EBCE). Preclinical laboratory studies included luciferase activity, cell proliferation, radio-labeled ligand estrogen receptor binding, surface plasmon resonance ligand receptor binding, and nuclear magnetic resonance assays. Results: Women with E1 ≥1.3 pg/mL and E2 ≥0.5 pg/mL after 6 months of AI treatment had a 2.2-fold increase in risk (P = 0.0005) of an EBCE, and in the anastrozole subgroup, the increase in risk of an EBCE was 3.0-fold (P = 0.001). Preclinical laboratory studies examined mechanisms of action in addition to aromatase inhibition and showed that only anastrozole could directly bind to estrogen receptor α (ERα), activate estrogen response element-dependent transcription, and stimulate growth of an aromatase-deficient CYP19A1−/− T47D breast cancer cell line. Conclusions: This matched case–control clinical study revealed that levels of estrone and estradiol above identified thresholds after 6 months of adjuvant anastrozole treatment were associated with increased risk of an EBCE. Preclinical laboratory studies revealed that anastrozole, but not exemestane or letrozole, is a ligand for ERα. These findings represent potential steps towards individualized anastrozole therapy.

Abstract BRCA1 plays a key role in homologous recombination (HR) DNA repair. Accordingly, changes that downregulate BRCA1, including BRCA1 mutations and reduced BRCA1 transcription, due to promoter hypermethylation or loss of the BRCA1 transcriptional regulator CDK12, disrupt HR in multiple cancers. In addition, BRCA1 has also been implicated in the regulation of metabolism. Here, we show that reducing BRCA1 expression, either by CDK12 or BRCA1 depletion, led to metabolic reprogramming of ovarian cancer cells, causing decreased mitochondrial respiration and reduced ATP levels. BRCA1 depletion drove this reprogramming by upregulating nicotinamide N-methyltransferase (NNMT). Notably, the metabolic alterations caused by BRCA1 depletion and NNMT upregulation sensitized ovarian cancer cells to agents that inhibit mitochondrial metabolism (VLX600 and tigecycline) and to agents that inhibit glucose import (WZB117). These observations suggest that inhibition of energy metabolism may be a potential strategy to selectively target BRCA1-deficient high-grade serous ovarian cancer, which is characterized by frequent BRCA1 loss and NNMT overexpression. Significance: Loss of BRCA1 reprograms metabolism, creating a therapeutically targetable vulnerability in ovarian cancer.