Design Of Combination Therapies Research Articles

Ultra-high-throughput screening of antimicrobial combination therapies using a two-stage transparent machine learning model.

Here, we present M2D2, a two-stage machine learning (ML) pipeline that identifies promising antimicrobial drug combinations, which are crucial for combating drug resistance. M2D2 addresses key challenges in drug combination discovery by predicting drug synergies using computationally generated drug-protein interaction data, thereby circumventing the need for expensive omics data. The model improves the accuracy of drug target identification using high-throughput experimental and computational methods via feedback between ML stages. M2D2's transparent framework provides mechanistic insights into drug interactions and was benchmarked against chemogenomics, transcriptomics, and metabolomics datasets. We experimentally validated M2D2 using high-throughput screening of 946 combinations of Food and Drug Administration (FDA)- approved drugs and antibiotics against Escherichia coli . We discovered synergy between a cerebrovascular drug and a widely used penicillin antibiotic and validated predicted mechanisms of action using genome-wide CRISPR inhibition screens. M2D2 offers a transparent ML tool for rapidly designing combination therapies and guides repurposing efforts while providing mechanistic insights.

Evaluating [225Ac]Ac-FAPI-46 for the treatment of soft-tissue sarcoma in mice

PurposeFibroblast Activation Protein (FAP) is an emerging theranostic target that is highly expressed on cancer-associated fibroblasts and on certain tumor cells including sarcoma. We investigated the anti-tumor efficacy of [225Ac]Ac-FAPI-46 as monotherapy or in combination with immune checkpoint blockade (ICB) in immunocompetent murine models of sarcoma sensitive or resistant to ICB.Methods[68Ga]Ga- and [225Ac]Ac-FAPI-46 were tested in subcutaneous FAP+ FSA fibrosarcoma bearing C3H/Sed/Kam mice. The efficacy of up to three cycles of 60 kBq [225Ac]Ac-FAPI-46 was evaluated as monotherapy and in combination with an anti-PD-1 antibody. Efficacy of [225Ac]Ac-FAPI-46 and/or ICB was further compared in FAP-overexpressing FSA (FSA-F) tumors that were sensitive to ICB or rendered ICB-resistant by tumor-induction in the presence of Abatacept.Results[225Ac]Ac-FAPI-46 was well tolerated up to 3 × 60 kBq but had minimal effect on FSA tumor growth. The combination of three cycles [225Ac]Ac-FAPI-46 and ICB resulted in growth delay in 55% of mice (6/11) and partial tumor regression in 18% (2/11) of mice. In FSA-F tumors with FAP overexpression, both [225Ac]Ac-FAPI-46 and ICB were effective without additional benefits from the combination. In locally immunosuppressed and ICB resistant FAP-F tumors, however, [225Ac]Ac-FAPI-46 restored responsiveness to ICB, resulting in significant tumor regression and tumor-free survival of 56% of mice in the combination group up to 60 days post treatment.Conclusion[225Ac]Ac-FAPI-46 efficacy is correlated with tumoral FAP expression levels and can restore responsiveness to PD-1 ICB. These data illustrate that careful patient selection based on target expression and rationally designed combination therapies are critically important to maximize the therapeutic impact of FAP-targeting radioligands.

Second-generation checkpoint inhibitors and Treg depletion synergize with a mouse cancer vaccine in accordance with tumor microenvironment characterization

BackgroundDespite advances in checkpoint inhibitor (CPI) therapy for cancer treatment, many cancers remain resistant. Tumors deemed “cold” based on lack of T cell infiltration show reduced potential for CPI therapy....

Abstract ED10-02: Identifying Collateral Vulnerabilities in the AKT pathway for Therapeutic Benefit

Abstract The PI 3-kinase (PI3K) and AKT signaling pathway plays a critical role in regulating all aspects of normal cellular physiology, and is also frequently deregulated in human pathophysiologies, most evidently in cancer and diabetes. Three AKT isoforms exist in humans encoded by distinct genes (AKT1, AKT2, AKT3), and although originally thought to function redundantly, many studies have shown that AKT isoforms have non-overlapping and unique roles in both normal physiology and disease. Similarly, genetic lesions in the PIK3CA and AKT oncogenes have been described, and many of the genes that contribute to PI3K/AKT pathway activation and also signal termination have been found to be altered in human cancers. Numerous drugs that inhibit PI3K as well AKT have been developed for therapeutic use in patients, and many of these are being evaluated in late-stage clinical trials. During the seminar, I will review the major mechanisms that contribute to AKT hyperactivation in cancer. Genetic lesions in the PI3K/AKT pathway in human cancers will also be discussed, as well as efforts to target this pathway therapeutically, including our recent efforts aimed at developing new AKT degrader compounds. I will further present new studies using CRISPR-based genome wide synthetic lethal screens to identify genes that synergize with PI3K and AKT pathway inhibition to induce a cytotoxic response in TNBC addicted to pathway hyperactivation. I will present studies on genes and mechanisms that represent collateral vulnerabilities to pathway inhibition and our efforts at designing combination therapy strategies for cancer patients with genetic aberrations in the PI3K and AKT pathway. Citation Format: A. Toker. Identifying Collateral Vulnerabilities in the AKT pathway for Therapeutic Benefit [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr ED10-02.

Designing combination therapies for cancer treatment: application of a mathematical framework combining CAR T-cell immunotherapy and targeted radionuclide therapy.

Cancer combination treatments involving immunotherapies with targeted radiation therapy are at the forefront of treating cancers. However, dosing and scheduling of these therapies pose a challenge. Mathematical models provide a unique way of optimizing these therapies. Using a preclinical model of multiple myeloma as an example, we demonstrate the capability of a mathematical model to combine these therapies to achieve maximum response, defined as delay in tumor growth. Data from mice studies with targeted radionuclide therapy (TRT) and chimeric antigen receptor (CAR)-T cell monotherapies and combinations with different intervals between them was used to calibrate mathematical model parameters. The dependence of progression-free survival (PFS), overall survival (OS), and the time to minimum tumor burden on dosing and scheduling was evaluated. Different dosing and scheduling schemes were evaluated to maximize the PFS and optimize timings of TRT and CAR-T cell therapies. Therapy intervals that were too close or too far apart are shown to be detrimental to the therapeutic efficacy, as TRT too close to CAR-T cell therapy results in radiation related CAR-T cell killing while the therapies being too far apart result in tumor regrowth, negatively impacting tumor control and survival. We show that splitting a dose of TRT or CAR-T cells when administered in combination is advantageous only if the first therapy delivered can produce a significant benefit as a monotherapy. Mathematical models are crucial tools for optimizing the delivery of cancer combination therapy regimens with application along the lines of achieving cure, maximizing survival or minimizing toxicity.

Abstract 1925: Wild-type RAS signaling is an essential therapeutic target in RAS-mutated cancers

Abstract Single-agent targeting of RAS-mutated cancers using RAF/MEK/ERK or PI3K/AKT pathway inhibitors is ineffective; blocking one pathway relieves negative feedback control of RTK signaling and hyperactivates parallel effector pathways. While combined MEK and PI3K inhibition is effective in preclinical models, toxicity of this combination prevents its clinical use. Alternative strategies for treating RAS-mutated cancers are essential. Therapeutics directly targeting mutated RAS proteins have the potential to spare normal cellular function thereby lessening overall toxicity. Unfortunately, direct RAS inhibition as a monotherapy does not fully block RAS effector signaling. RAS proteins show differential activation of RAF and PI3K pathways: KRAS potently activates RAF but poorly activates PI3K, whereas HRAS effectively activates PI3K but poorly activates RAF. Further, mutant RAS inhibition relieves negative feedback controls leading to rapid hyperactivation of RTK−WT RAS signaling. A more comprehensive understanding of the interplay between mutant RAS and RTK−WT RAS signaling is essential to developing rational therapeutic approaches to treat RAS-mutated cancers. We found that WT RAS enhanced mutant RAS-driven transformation by activating RAS effectors poorly engaged by mutated RAS. Further, inhibition of RAS effectors activated poorly by mutant RAS synergized with and limited resistance to mutant HRAS and KRAS inhibitors. The mutant HRAS inhibitor tipifarnib blocked PI3K signaling and synergized with MEK inhibitors in HRAS-mutated cancer cell lines; covalent KRASG12C inhibitors blocked MEK signaling and synergized with PI3K inhibitors in KRASG12C- mutated cell lines. Synergy between inhibitors of mutant RAS and RAS effectors was dependent on intact RTK/WT RAS signaling and was lost in both RASless or SOSless MEFs. Dual knock-out of WT RAS isoforms in KRAS- and HRAS-mutated cancer cell lines reduced PI3K signaling in KRAS-mutant cell lines and MAPK signaling in HRAS-mutant cell lines and reduced proliferation, confirming our findings in MEF cells. Overall, our data highlight the critical role of WT RAS isoforms in supporting mutant RAS signaling and should be considered when designing combination therapies in RAS-mutated cancers. Citation Format: Nancy E. Sealover, Bridget Finniff, Jacob Hughes, Hyun Lee, Robert L. Kortum. Wild-type RAS signaling is an essential therapeutic target in RAS-mutated cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1925.

Abstract 4560: Assessing cancer drug combination efficacy across 900+ PRISM cell lines in a multiplexed screening assay

Abstract Combination therapies are crucial in cancer care, yet identifying which combination will benefit a specific patient is challenging. The vast array of clinical, investigational, and tool anticancer agents and diverse cancer contexts makes investigating many drug combinations over a large number of cell lines infeasible. Here, we describe a multiplexed screening approach using the PRISM assay, where drug combinations are screened on >900 DNA-barcoded cancer cell lines. We analyze cell viability data in drug combinations and single agents using established metrics to describe the combined effects such as additivity, synergy, and antagonism. Quantifying and classifying combined effects will help prioritize specific combinations for follow-up investigations and provide biological and mechanistic insights, thus enabling rationally designed combination therapies. We illustrate our methodology through data from three drug combinations that exemplify synergy and antagonism. In the first combination, temozolomide+O6-benzylguanine (alkylating agent + MGMT inhibitor), we found that cell lines expressing MGMT were sensitized to temozolomide in the presence of O6-benzylguanine, thus illustrating synergy. In the second combination, we screened two anti-apoptosis compounds A-1331852+AZD5991 (BCL-xL + MCL1 inhibitor) and found that BCL-xL and MCL1 inhibition were also synergistic. In the third combination, ML210+ferrostatin-1 (GPX4 inhibitor inducing ferroptosis + ferroptosis inhibitor), we found that ferrostatin-1 antagonized the effects of ML210. Our analysis also reveals the importance of appropriate dose selection and analytical metrics for reliably measuring combined effects. In conclusion, the PRISM platform's multiplexed cell line screening is a robust method for characterizing rationally designed drug combinations, offering a systematic approach to enhance the precision of combination therapy development in cancer care. Citation Format: Ashish Bino George, Shiker Nair, Mustafa Kocak, Ellen Nguyen, Alvin Kalathungal, Anthony Fazio, Cole Ponsi, Aydin Golabi, Melissa A. Ronan, Matthew G. Rees, Jennifer A. Roth. Assessing cancer drug combination efficacy across 900+ PRISM cell lines in a multiplexed screening assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4560.

Abstract A096: Blockade of LAIR1-collagen interaction enhances the therapeutic activity of BiTE-secreting T cells in ovarian cancer

Abstract Introduction: The tumor microenvironment (TME), abundant with collagen produced by cancer associated fibroblasts (CAFs), plays a critical role in evading the immune system and limiting the efficacy of cell therapies. High levels of collagen and CAF expression correlate with malignant potential, decreased T cell accumulation, and overall unfavorable clinical outcomes in ovarian cancer (OC). Finding ways to address this immunosuppressive TME is therefore critical to improving therapeutic options. We recently reported on the therapeutic potential of adoptively transferred T cells engineered to secrete a folate receptor alpha (FRα)-targeted bispecific T cell engager (FR-B T cells) to target a tumor antigen commonly overexpressed in OC. Transcriptional profiling following ACT revealed that effector-like FR-B T cells (FR-BE T cells) upregulated genes associated with extracellular matrix interaction, suggesting interaction with the tumor stroma may limit antitumor immunity by FR-B T cells. Our goal was to improve the effectiveness of FR-B T cells by inhibiting LAIR-1, a widely present immune checkpoint receptor that sends T cell inhibitory signals after binding to collagen-like domains, leading to T cell exhaustion. We hypothesized that interrupting the LAIR1-collagen pathway using a LAIR1 decoy (NC410, supplied by NextCure Inc.) could amplify the FR-BE T cell effector function, thereby improving the response. Methods: We utilized in vitro co-culture assays to understand the phenotype and mechanistic changes occurring at the level of the T cell/tumor interface when exposed to collagen, as well as effects of LAIR 1 pathway blockade with the addition of NC410. In vivo murine models were used to determine disease progression and overall survival (OS) following treatment with bispecific T cell engager-armed T cells ± LAIR1 blockade. Results: Phenotypic analysis of FR-B T cells revealed elevated LAIR-1 expression on FR-BE T cells. FRα+ OC lysis by FR-BE T cells was diminished in the presence of collagen, suggesting LAIR-1 signaling can suppress tumor attack. In vitro, the addition of NC410 enhanced the activity of FR-BE T cells when exposed to collagen, improving both FRα+ target cell lysis and partially restoring the production of IFN-γ by FR-BE T cells. In vivo, the combination of NC410 with FR-BE T cells led to improved tumor control compared to FR-BE T cell therapy alone. Conclusions: Our results highlight understanding the interactions between infiltrating immune cells and the immunosuppressive TME to better design combination therapies that improve duration and magnitude of immune attack on tumors. By blocking T cell/stromal interactions, FR-B T cell therapy can be further enhanced, creating a promising opportunity to improve the impact of adoptive cell therapy in OC. Citation Format: Sarah Werner, Nicole Gaulin, Jessie Chiello, Theja Giridharan, Anm Nazmul Khan, Sora Suzuki, Suzanne Hess, Sol Langermann, Emese Zsiros, Brahm H. Segal, A.J. Robert McGray. Blockade of LAIR1-collagen interaction enhances the therapeutic activity of BiTE-secreting T cells in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A096.

Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients.

Members of the transient receptor potential (TRP) protein family shape oncogenic development, but the specific relevance of TRP-related genes in hepatocellular carcinoma (HCC) has yet to be defined. To investigate the role of TRP genes in HCC, their association with HCC development and treatment was examined. HCC patient gene expression and clinical data were downloaded from The Cancer Genome Atlas database, and univariate and least absolute shrinkage and selection operator Cox regression models were employed to explore the TRP-related risk spectrum. Based on these analyses, clinically relevant TRP family genes were selected, and the association between the key TRP canonical type 1 (TRPC1) gene and HCC patient prognosis was evaluated. In total, 28 TRP family genes were screened for clinical relevance, with multivariate analyses ultimately revealing three of these genes (TRPC1, TRP cation channel subfamily M member 2, and TRP cation channel subfamily M member 6) to be significantly associated with HCC patient prognosis (P < 0.05). These genes were utilized to establish a TRP-related risk model. Patients were separated into low- and high-risk groups based on the expression of these genes, and high-risk patients exhibited a significantly poorer prognosis (P = 0.001). Functional analyses highlighted pronounced differences in the immune status of patients in these two groups and associated enriched immune pathways. TRPC1 was identified as a candidate gene in this family worthy of further study, with HCC patients expressing higher TRPC1 levels exhibiting poorer survival outcomes. Consistently, quantitative, immunohistochemistry, and western blot analyses revealed increased TRPC1 expression in HCC. These three TRP genes help determine HCC patient prognosis, providing insight into tumor immune status and immunological composition. These findings will help design combination therapies including immunotherapeutic and anti-TRP agents.

Drug-drug salts of Naftopidil with non-steroidal anti-inflammatory drugs for potential multi-drug therapy

Drug-drug cocrystals (DDCs) are a subclass of pharmaceutical cocrystals in which both the components of a cocrystal are active drugs. DDCs are the recent advancement based on the crystal engineering approach to overcome the problems associated with conventional combination therapy. They also allow the modulation of the physicochemical properties of parent drugs. Four new drug-drug salts of Naftopidil (NFPD), a BCS class IV anti-cancer drug, were prepared by liquid-assisted grinding and solvent evaporation technique, with Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) such as Aspirin (ASP), Tolfenamic acid (TFA), Mefenamic acid (MFA) and Niflumic acid (NIFA) as coformers. The solids obtained were characterized by Single Crystal X-Ray diffraction (SCXRD), Powder X-ray Diffraction (PXRD), Thermo Gravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). Furthermore, the solubility of NFPD in the solids was determined by the shake flask method. SCXRD analysis showed that O–H···N hydrogen bond interactions found in the pure NFPD crystal structure are replaced by the N+–H···O- and O–H···O hydrogen bond interactions in the drug-drug solids. Additionally, the transfer of a proton from the carboxylic group of NSAIDs to piperazine nitrogen of NFPD is observed in all the drug-drug crystal structures, which suggests the nature of the solids as salts. NFPD-ASP salt exhibited improved solubility (33.2 µg/ml), which is eight-fold higher than the pure NFPD solubility (4.3 µg/ml). NFPD-MFA (0.6 µg/ml), NFPD-TFA (0.17 µg/ml), and NFPD-NIFA (1.35 µg/ml) showed reduced solubility than the pure NFPD. We anticipate that the current research will provide an alternate strategy to overcome the solubility issue of NFPD and provide potential candidates for designing combination therapy to treat complications in Benign Prostatic Hypertrophy (BPH), which involves pain and inflammation.

STEM-24. WDR5 REPRESENTS A THERAPEUTICALLY EXPLOITABLE TARGET FOR CANCER STEM CELLS IN GLIOBLASTOMA

Abstract Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors that are driven by populations of cancer stem cells (CSCs). In this study, we perform an epigenetic-focused functional genomics screen in GBM organoids and identify WDR5 as an essential epigenetic regulator in the SOX2-enriched, therapy resistant cancer stem cell niche. Despite their importance for tumor growth, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy resistant niche. Our niche-specific screens identified WDR5, an H3K4 histone methyltransferase responsible for activating specific gene expression, as indispensable for GBM CSC growth and survival. In GBM CSC models, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, required for stem cell maintenance and including the POU5F1(OCT4)::SOX2 motif. We incorporated a SOX2/OCT4 motif driven GFP reporter system into our CSC cell models and found that WDR5 inhibitor treatment resulted in dose-dependent silencing of stem cell reporter activity. Further, WDR5 inhibitor treatment altered the stem cell state, disrupting CSC in vitro growth and self-renewal as well as in vivo tumor growth. Our results unveiled the role of WDR5 in maintaining the CSC state in GBM and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers. This conceptual and experimental framework can be applied to many cancers, and can unmask unique microenvironmental biology and rationally designed combination therapies.

Characterizing evolutionary dynamics reveals strategies to exhaust the spectrum of subclonal resistance in EGFR-mutant lung cancer.

The emergence of resistance to targeted therapies restrains their efficacy. The development of rational-ly guided drug combinations could overcome this currently insurmountable clinical challenge. However, our limited understanding of the trajectories that drive the outgrowth of resistant clones in cancer cell populations precludes design of drug combinations to forestall resistance. Here, we propose an iterative treatment strategy coupled with genomic profiling and genome-wide CRISPR activation screening to systematically extract and define pre-existing resistant subpopulations in an EGFR-driven lung cancer cell line. Integrating these modalities identifies several resistance mechanisms, including activation of YAP/TAZ signaling by WWTR1 amplification, and estimated the associated cellular fitness for mathematical population modeling. These observations led to the development of a combina-tion therapy that eradicated resistant clones in large cancer cell line populations by exhausting the spectrum of genomic resistance mechanisms. However, a small fraction of cancer cells was able to enter a reversible non-proliferative state of drug tolerance. This sub-population exhibited mesenchy-mal properties, NRF2 target gene expression and sensitivity to ferroptotic cell death. Exploiting this induced collateral sensitivity by GPX4 inhibition clears drug tolerant populations and led to tumor cell eradication. Overall, this experimental in vitro data and theoretical modeling demonstrate why targeted mono- and dual therapies will likely fail in sufficiently large cancer cell populations to limit long-term efficacy. Our approach is not tied to a particular driver mechanism and can be used to systematically assess and ideally exhaust the resistance landscape for different cancer types to rationally design com-bination therapies.

361 WDR5 represents a therapeutically exploitable target for cancer stem cells in glioblastoma

OBJECTIVES/GOALS: Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors that are driven by populations of cancer stem cells (CSCs). In this study, we perform an epigenetic-focused functional genomics screen in GBM organoids and identify WDR5 as an essential epigenetic regulator in the SOX2-enriched, therapy resistant cancer stem cell niche. METHODS/STUDY POPULATION: Despite their importance for tumor growth, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy resistant niche. Our niche-specific screens identified WDR5, an H3K4 histone methyltransferase responsible for activating specific gene expression, as indispensable for GBM CSC growth and survival. RESULTS/ANTICIPATED RESULTS: In GBM CSC models, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, required for stem cell maintenance and including the POU5F1(OCT4)::SOX2 motif. We incorporated a SOX2/OCT4 motif driven GFP reporter system into our CSC cell models and found that WDR5 inhibitor treatment resulted in dose-dependent silencing of stem cell reporter activity. Further, WDR5 inhibitor treatment altered the stem cell state, disrupting CSC in vitro growth and self-renewal as well as in vivo tumor growth. DISCUSSION/SIGNIFICANCE: Our results unveiled the role of WDR5 in maintaining the CSC state in GBM and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers. This conceptual and experimental framework can be applied to many cancers, and can unmask unique microenvironmental biology and rationally designed combination therapies.

DXP Synthase Function in a Bacterial Metabolic Adaptation and Implications for Antibacterial Strategies.

Pathogenic bacteria possess a remarkable ability to adapt to fluctuating host environments and cause infection. Disturbing bacterial central metabolism through inhibition of 1-deoxy-d-xylulose 5-phosphate synthase (DXPS) has the potential to hinder bacterial adaptation, representing a new antibacterial strategy. DXPS functions at a critical metabolic branchpoint to produce the metabolite DXP, a precursor to pyridoxal-5-phosphate (PLP), thiamin diphosphate (ThDP) and isoprenoids presumed essential for metabolic adaptation in nutrient-limited host environments. However, specific roles of DXPS in bacterial adaptations that rely on vitamins or isoprenoids have not been studied. Here we investigate DXPS function in an adaptation of uropathogenic E. coli (UPEC) to d-serine (d-Ser), a bacteriostatic host metabolite that is present at high concentrations in the urinary tract. UPEC adapt to d-Ser by producing a PLP-dependent deaminase, DsdA, that converts d-Ser to pyruvate, pointing to a role for DXPS-dependent PLP synthesis in this adaptation. Using a DXPS-selective probe, butyl acetylphosphonate (BAP), and leveraging the toxic effects of d-Ser, we reveal a link between DXPS activity and d-Ser catabolism. We find that UPEC are sensitized to d-Ser and produce sustained higher levels of DsdA to catabolize d-Ser in the presence of BAP. In addition, BAP activity in the presence of d-Ser is suppressed by β-alanine, the product of aspartate decarboxylase PanD targeted by d-Ser. This BAP-dependent sensitivity to d-Ser marks a metabolic vulnerability that can be exploited to design combination therapies. As a starting point, we show that combining inhibitors of DXPS and CoA biosynthesis displays synergy against UPEC grown in urine where there is increased dependence on the TCA cycle and gluconeogenesis from amino acids. Thus, this study provides the first evidence for a DXPS-dependent metabolic adaptation in a bacterial pathogen and demonstrates how this might be leveraged for development of antibacterial strategies against clinically relevant pathogens.

APE1 promotes non-homologous end joining by initiating DNA double-strand break formation and decreasing ubiquitination of artemis following oxidative genotoxic stress

BackgroundApurinic/apyrimidinic endonuclease 1 (APE1) imparts radio-resistance by repairing isolated lesions via the base excision repair (BER) pathway, but whether and how it is involved in the formation and/or repair of DSBs remains mostly unknown.MethodsImmunoblotting, fluorescent immunostaining, and the Comet assay were used to investigate the effect of APE1 on temporal DSB formation. Chromatin extraction, 53BP1 foci and co-immunoprecipitation, and rescue assays were used to evaluate non-homologous end joining (NHEJ) repair and APE1 effects. Colony formation, micronuclei measurements, flow cytometry, and xenograft models were used to examine the effect of APE1 expression on survival and synergistic lethality. Immunohistochemistry was used to detect APE1 and Artemis expression in cervical tumor tissues.ResultsAPE1 is upregulated in cervical tumor tissue compared to paired peri-tumor, and elevated APE1 expression is associated with radio-resistance. APE1 mediates resistance to oxidative genotoxic stress by activating NHEJ repair. APE1, via its endonuclease activity, initiates clustered lesion conversion to DSBs (within 1 h), promoting the activation of the DNA-dependent protein kinase catalytic subunit (DNA-PKcs), a key kinase in the DNA damage response (DDR) and NHEJ pathway. APE1 then participates in NHEJ repair directly by interacting with DNA- PKcs. Additionally, APE1 promotes NHEJ activity by decreasing the ubiquitination and degradation of Artemis, a nuclease with a critical role in the NHEJ pathway. Overall, APE1 deficiency leads to DSB accumulation at a late phase following oxidative stress (after 24 h), which also triggers activation of Ataxia-telangiectasia mutated (ATM), another key kinase of the DDR. Inhibition of ATM activity significantly promotes synergistic lethality with oxidative stress in APE1-deficient cells and tumors.ConclusionAPE1 promotes NHEJ repair by temporally regulating DBS formation and repair following oxidative stress. This knowledge provides new insights into the design of combinatorial therapies and indicates the timing of administration and maintenance of DDR inhibitors for overcoming radio-resistance.

Targeting Transcription Factors ATF5, CEBPB and CEBPD with Cell-Penetrating Peptides to Treat Brain and Other Cancers.

Developing novel therapeutics often follows three steps: target identification, design of strategies to suppress target activity and drug development to implement the strategies. In this review, we recount the evidence identifying the basic leucine zipper transcription factors ATF5, CEBPB, and CEBPD as targets for brain and other malignancies. We describe strategies that exploit the structures of the three factors to create inhibitory dominant-negative (DN) mutant forms that selectively suppress growth and survival of cancer cells. We then discuss and compare four peptides (CP-DN-ATF5, Dpep, Bpep and ST101) in which DN sequences are joined with cell-penetrating domains to create drugs that pass through tissue barriers and into cells. The peptide drugs show both efficacy and safety in suppressing growth and in the survival of brain and other cancers in vivo, and ST101 is currently in clinical trials for solid tumors, including GBM. We further consider known mechanisms by which the peptides act and how these have been exploited in rationally designed combination therapies. We additionally discuss lacunae in our knowledge about the peptides that merit further research. Finally, we suggest both short- and long-term directions for creating new generations of drugs targeting ATF5, CEBPB, CEBPD, and other transcription factors for treating brain and other malignancies.

Combinatorial regimens of chemotherapeutic agents: A new perspective on raising the heat of the tumor immune microenvironment.

Harnessing the broad immunostimulatory capabilities of chemotherapy in combination with immune checkpoint inhibitors has improved immunotherapy outcomes in patients with cancer. Certain chemotherapeutic agents can extensively modify the tumor microenvironment (TME), resulting in the reprogramming of local immune responses. Although chemotherapeutic agents with an enhanced generation of potent anti-tumor immune responses have been tested in preclinical animal models and clinical trials, this strategy has not yet shown substantial therapeutic efficacy in selected difficult-to-treat cancer types. In addition, the efficacy of chemotherapeutic agent-based monotherapy in eliciting a long-term anti-tumor immune response is restricted by the immunosuppressive TME. To enhance the immunomodulatory effect of chemotherapy, researchers have made many attempts, mainly focusing on improving the targeted distribution of chemotherapeutic agents and designing combination therapies. Here, we focused on the mechanisms of the anti-tumor immune response to chemotherapeutic agents and enumerated the attempts to advance the use of chemo-immunotherapy. Furthermore, we have listed the important considerations in designing combinations of these drugs to maximize efficacy and improve treatment response rates in patients with cancer.

Abstract LB119: Precision combination therapies based on recurrent oncogenic co-alterations

Abstract Cancer cells depend on multiple driver alterations whose oncogenic effects can be suppressed by drug combinations. Discovering effective combination therapies and selecting patients to maximize therapeutic benefit are challenging due to the complexity of the molecular landscape of drug responses. Here, we provide a comprehensive resource of precision combination therapies tailored to oncogenic co-alterations that are recurrent across patient cohorts. To generate the resource, we developed REcurrent Features Leveraged for Combination Therapy (REFLECT), which integrates machine learning and cancer informatics algorithms. Based on multi-omic data, the method maps recurrent co-alteration signatures in patient cohorts to combination therapies. The resource matches &amp;gt; 2,000 drug combinations to co-alteration signatures across 201 cohorts stratified from 10,392 patients and 33 cancer types. We validated the REFLECT pipeline using data from patient-derived xenografts (PDX), in vitro drug screens, and combination therapy clinical trials. These validations demonstrate that REFLECT selects combination therapies with significantly improved efficacy, drug synergy, and survival outcomes. In patient cohorts with immunotherapy response markers, HER2 activation, and DNA repair aberrations, we have identified therapeutically actionable and recurrent co-alteration signatures. REFLECT provides a resource and framework to design combination therapies tailored to tumor cohorts in data-driven clinical trials and pre-clinical studies. Citation Format: Anil Korkut, Xubin Li, Elizabeth Kong, Gonghong Yan, Zeynep Dereli, Behnaz Bozorgui, Parisa Imanirad, Jacob Elnaggar, Augustin Luna, David Menter, Patrick Pilié, Timothy Yap, Scott Kopetz, Chris Sander. Precision combination therapies based on recurrent oncogenic co-alterations [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 LB119.

Evaluation of in vitro and in vivo efficacy of pharmacological lysine‐specific demethylase 1 (LSD1) inhibitors in glioblastoma stem cell (GSC) models

Epigenetically directed cancer therapeutics, such as targeting the histone demethylase LSD1, are an emerging approach to the treatment of glioblastoma (GBM), with dozens of candidates in preclinical development. To date, knockdown (KD) of LSD1 exerts effects on proliferation, but an evaluation and comparison of pharmacological LSD1 inhibitors in GBM is lacking. Therefore, the present study evaluated the effect of LSD1 KD compared with pharmacological inhibition and studied four LSD1 inhibitors in patient derived GSCs in vitroand in vivo for therapeutic efficacy and genes associated with resistance.Changes in gene expression were observed upon KD of LSD1 and compared with pharmacological inhibition of LSD1 in GBM cells. Four LSD1 inhibitors were assessed in a panel of nine GSC lines for their effects on cell viability and colony formation. The radioresistant GSC line, GSC 20, was used to establish an orthotopic xenograft model to evaluate the in vivo activity of LSD1 inhibition. In parallel, we identified five genes associated with resistance to LSD1 inhibition using RNA‐seq comparing non‐transformed and isogenic resistant GBM lines. Lastly, we probed for the presence of this gene set in our in vitro and in vivo GSC experiments with LSD1 inhibitors and in GBM patient exome data.In GBM cell lines, we identified an upregulation of genes associated with cell death, regulation of cell proliferation, and regulation of intracellular signaling upon both LSD1 KD and LSD1 inhibition using tranylcypromine treatment. Additional, more selective, pharmacological inhibitors of LSD1 (GSK‐LSD1, RN‐1 and SP‐2577) in vitro had differential responses in the GSCs that were more varied, and responses were dependent on the specific LSD1 inhibitor and GSC line. Importantly, the response to LSD1 inhibition in vitro was not dependent on the GSC radiosensitivity or molecular subtype indicating unique determinants of sensitivity. When assessing in vivoefficacy, the GSC tumor‐bearing mice treated with GSK‐LSD1 had a strong reduction in tumor burden that occurred seven weeks into treatment. However, tumor regrowth occurred and overall survival was not significantly better in LSD1 inhibitor treated mice. To understand mechanisms associated with tumor regrowth, we mined our existing data on selectivity and sensitivity to LSD1 blockade and identified five genes potentially associated with resistance to LSD1 inhibition, including HKDC1, RAB3IL1, RAB39B, FTH1, and FAM213A. These genes were found to be upregulated in treatment resistant GSCs and in the brain tissue of GSK‐LSD1 treated mice after they succumbed to tumor burden. Finally, the resistant‐associated genes were present in exome sequencing data from GBM patients where they showed an inverse relationship with LSD1 expression.Future studies will focus on designing combination therapies with LSD1 inhibitors that will enhance their effects and overcome resistance associated with treatment by targeting pathways associated with the genes we have uncovered.

Bipartite network models to design combination therapies in acute myeloid leukaemia

Combination therapy is preferred over single-targeted monotherapies for cancer treatment due to its efficiency and safety. However, identifying effective drug combinations costs time and resources. We propose a method for identifying potential drug combinations by bipartite network modelling of patient-related drug response data, specifically the Beat AML dataset. The median of cell viability is used as a drug potency measurement to reconstruct a weighted bipartite network, model drug-biological sample interactions, and find the clusters of nodes inside two projected networks. Then, the clustering results are leveraged to discover effective multi-targeted drug combinations, which are also supported by more evidence using GDSC and ALMANAC databases. The potency and synergy levels of selective drug combinations are corroborated against monotherapy in three cell lines for acute myeloid leukaemia in vitro. In this study, we introduce a nominal data mining approach to improving acute myeloid leukaemia treatment through combinatorial therapy.