In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes.

The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. Immunotherapies have revolutionized the treatment of blood cancer. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. Particularly, more than 30 years of immunological synapse (IS) research data demonstrate that T cell efficacy is not only controlled by the specificity and avidity of the tumor antigen and T cell interaction, but also it depends on a collective process, involving multiple adhesion and regulatory molecules, as well as tumor microenvironment, spatially and temporally organized at the IS formed by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells. The optimal function of cytotoxic lymphocytes (including CTL and NK) depends on IS quality. Recognizing the inadequacy of conventional tools and the importance of IS in immune cell functions, we investigate a new strategy for assessing CAR-T efficacy by quantifying CAR IS quality using the glass-support planar lipid bilayer system combined with ML-based data analysis. Previous studies in our group show that CAR-T IS quality correlates with antitumor activities in vitro and in vivo. However, current manually quantified IS quality data analysis is time-consuming and labor-intensive with low accuracy, reproducibility, and repeatability. In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. The network output is flexible and produces bounding boxes, instance segmentation, contour outlines (borders), intensities of the borders, and segmentations without borders. Based on requirements, one or a combination of this information is used in statistical analysis. The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. The results suggest that CAR cell IS quality can be used as a potential composite biomarker and correlates with antitumor activities in patients, which is sufficiently discriminative to further test the CAR IS quality as a clinical biomarker to predict response to CAR immunotherapy in cancer. For translational research, the method developed here can also provide guidelines for designing and optimizing numerous CAR constructs for potential clinical development. Trial Registration: ClinicalTrials.gov NCT00881920.

Detours to Replication: Functions of Specialized DNA Polymerases during Oncogene-induced Replication Stress.

Incomplete and low-fidelity genome duplication contribute to genomic instability and cancer development. Difficult-to-Replicate Sequences, or DiToRS, are natural impediments in the genome that require specialized DNA polymerases and repair pathways to complete and maintain faithful DNA synthesis. DiToRS include non B-DNA secondary structures formed by repetitive sequences, for example within chromosomal fragile sites and telomeres, which inhibit DNA replication under endogenous stress conditions. Oncogene activation alters DNA replication dynamics and creates oncogenic replication stress, resulting in persistent activation of the DNA damage and replication stress responses, cell cycle arrest, and cell death. The response to oncogenic replication stress is highly complex and must be tightly regulated to prevent mutations and tumorigenesis. In this review, we summarize types of known DiToRS and the experimental evidence supporting replication inhibition, with a focus on the specialized DNA polymerases utilized to cope with these obstacles. In addition, we discuss different causes of oncogenic replication stress and its impact on DiToRS stability. We highlight recent findings regarding the regulation of DNA polymerases during oncogenic replication stress and the implications for cancer development.

Standardized protocol for the evaluation of chimeric antigen receptor (CAR)-modified cell immunological synapse quality using the glass-supported planar lipid bilayer.

Chimeric antigen receptor (CAR)-modified cell therapy is an effective therapy that harnesses the power of the human immune system by re-engineering immune cells that specifically kill tumor cells with tumor antigen specificity. Key to the effective elimination of tumor cells is the establishment of the immunological synapse (IS) between CAR-modified immune cells and their susceptible tumors. For functional activity, CAR-modified cells must form an effective IS to kill tumor cells specifically. The formation of the CAR-specific IS requires the coordination of many cellular processes including reorganization of the cytoskeletal structure, polarization of lytic granules, accumulation of tumor antigen, and phosphorylation of key signaling molecules within the IS. Visualization and assessment of the CAR IS quality can reveal much about the molecular mechanisms that underlie the efficacy of various CAR-modified immune cells. This chapter provides a standardized method of assessing the IS quality by quantifying the tumor antigen (defining the CAR IS formation), cytoskeleton (key component of CAR IS structure), and various molecules of interest involved in the IS formation (key molecular mechanism signatures of CAR IS function) using immunofluorescence on the glass-supported planar lipid bilayer, with a focus on tumor antigen only in this study. We provide specific insights and helpful tips for reagent and sample preparation, assay design, and machine learning (ML)-based data analysis. The protocol described in this chapter will provide a valuable tool to visualize and assess the IS quality of various CAR-modified immune cells.

Overexpression of oncogenic H-Ras in hTERT-immortalized and SV40-transformed human cells targets replicative and specialized DNA polymerases for depletion.

DNA polymerases play essential functions in replication fork progression and genome maintenance. DNA lesions and drug-induced replication stress result in up-regulation and re-localization of specialized DNA polymerases η and κ. Although oncogene activation significantly alters DNA replication dynamics, causing replication stress and genome instability, little is known about DNA polymerase expression and regulation in response to oncogene activation. Here, we investigated the consequences of mutant H-RAS G12V overexpression on the regulation of DNA polymerases in h-TERT immortalized and SV40-transformed human cells. Focusing on DNA polymerases associated with the replication fork, we demonstrate that DNA polymerases are depleted in a temporal manner in response to H-RAS G12V overexpression. The polymerases targeted for depletion, as cells display markers of senescence, include the Pol α catalytic subunit (POLA1), Pol δ catalytic and p68 subunits (POLD1 and POLD3), Pol η, and Pol κ. Both transcriptional and post-transcriptional mechanisms mediate this response. Pol η (POLH) depletion is sufficient to induce a senescence-like growth arrest in human foreskin fibroblast BJ5a cells, and is associated with decreased Pol α expression. Using an SV-40 transformed cell model, we observed cell cycle checkpoint signaling differences in cells with H-RasG12V-induced polymerase depletion, as compared to Pol η-deficient cells. Our findings contribute to our understanding of cellular events following oncogene activation and cellular transformation.

DNA Polymerase Eta Prevents Tumor Cell-Cycle Arrest and Cell Death during Recovery from Replication Stress.

: Neoplastic transformation and genome instability are enhanced by replication stress, conditions that slow or stall DNA replication forks. Consequently, cancer cells require multiple enzymes and checkpoint signaling pathways to mitigate replication stress for their viability and proliferation. Targeting proteins that enhance cancer cell survival during replication stress is a recent approach in clinical strategies, especially when targets produce synthetic lethality. DNA polymerase eta (Pol η) has many key functions in genome stability, particularly for translesion synthesis. Here we demonstrate that endogenous Pol η displays significant protein induction and forms intense foci throughout the nucleus in response to replication stress induced by drugs that do not directly form DNA adducts. During replication stress, Pol η-deficient cells displayed hyperactivation of the ATR replication checkpoint and arrested late in the cell cycle. During recovery from replication stress, Pol η-deficient cells continue to display aberrant phenotypes, including delayed cell-cycle progression, apoptosis, and cell survival. Depletion or inhibition of ATR was synthetically lethal with Pol η deficiency, particularly when tumor cells were treated with replication stress-inducing drugs. Together our data expand knowledge of the cellular environments that increase endogenous Pol η expression beyond DNA damaging agents and demonstrate that Pol η regulation is central to the replication stress response. Because Pol η is aberrantly expressed in several tumor types, our results are critical for developing more effective chemotherapy approaches and identify coinhibition of Pol η and ATR as a potential therapeutic strategy. SIGNIFICANCE: This study demonstrates that replication stress upregulates Pol η (POLH) in tumor cells and reveals a role for Pol η in tumor cell recovery following replication stress.

Tumor suppressive microRNA-137 negatively regulates Musashi-1 and colorectal cancer progression.

Stem cell marker, Musashi-1 (MSI1) is over-expressed in many cancer types; however the molecular mechanisms involved in MSI1 over-expression are not well understood. We investigated the microRNA (miRNA) regulation of MSI1 and the implications this regulation plays in colorectal cancer. MicroRNA miR-137 was identified as a MSI1-targeting microRNA by immunoblotting and luciferase reporter assays. MSI1 protein was found to be highly expressed in 79% of primary rectal tumors (n=146), while miR-137 expression was decreased in 84% of the rectal tumor tissues (n=68) compared to paired normal mucosal samples. In addition to reduced MSI1 protein, exogenous expression of miR-137 inhibited cell growth, colony formation, and tumorsphere growth of colon cancer cells. Finally, in vivo studies demonstrated that induction of miR-137 can decrease growth of human colon cancer xenografts. Our results demonstrate that miR-137 acts as a tumor-suppressive miRNA in colorectal cancers and negatively regulates oncogenic MSI1.

Identification and validation of novel small molecule disruptors of HuR-mRNA interaction.

HuR, an RNA binding protein, binds to adenine- and uridine-rich elements (ARE) in the 3'-untranslated region (UTR) of target mRNAs, regulating their stability and translation. HuR is highly abundant in many types of cancer, and it promotes tumorigenesis by interacting with cancer-associated mRNAs, which encode proteins that are implicated in different tumor processes including cell proliferation, cell survival, angiogenesis, invasion, and metastasis. Drugs that disrupt the stabilizing effect of HuR upon mRNA targets could have dramatic effects on inhibiting cancer growth and persistence. In order to identify small molecules that directly disrupt the HuR-ARE interaction, we established a fluorescence polarization (FP) assay optimized for high throughput screening (HTS) using HuR protein and an ARE oligo from Musashi RNA-binding protein 1 (Msi1) mRNA, a HuR target. Following the performance of an HTS of ∼6000 compounds, we discovered a cluster of potential disruptors, which were then validated by AlphaLISA (Amplified Luminescent Proximity Homogeneous Assay), surface plasmon resonance (SPR), ribonucleoprotein immunoprecipitation (RNP IP) assay, and luciferase reporter functional studies. These compounds disrupted HuR-ARE interactions at the nanomolar level and blocked HuR function by competitive binding to HuR. These results support future studies toward chemical probes for a HuR function study and possibly a novel therapy for HuR-overexpressing cancers.