Mertk: An emerging target in cancer biology and immuno-oncology

Knocking down of Xkr8 enhances chemotherapy efficacy through modulating tumor immune microenvironment

Scramblase Xk-related protein 8 (Xkr8) regulates the externalization of phosphatidylserine (PS) during apoptosis and holds a pivotal role in fostering tumor immunosuppression. Targeting Xkr8 in conjunction with chemotherapy demonstrated a novel avenue for amplifying antitumor immune response and overcoming chemo-immune resistance. Here we further evaluated this strategy by using a clinically relevant orthotopic model and elucidated the mechanism through in-depth single-cell RNA sequencing (scRNA-seq). We found that Xkr8 knockdown exhibited the potential to lead to immunogenic cell death (ICD) by impeding the normal clearance of apoptotic cells. Co-delivery of Xkr8 small interference RNA (siRNA) and a prodrug conjugate of 5-fluorouracil (5-Fu) and oxoplatin (FuOXP) showed remarkable therapeutic efficacy in an orthotopic pancreatic tumor model with increased infiltration of proliferative NK cells and activated macrophages in the tumor microenvironment (TME). Single-cell trajectory analysis further unveiled that tumor infiltrating CD8+ T cells are differentiated favorably to cytotoxic over exhausted phenotype after combination treatment. Our study sheds new light on the impact of Xkr8 knockdown on TME and solidifies the rationale of combining Xkr8 knockdown with chemotherapy to treat various types of cancers.

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

Establishment of a novel efferocytosis potential index predicts prognosis and immunotherapy response in cancers

The biological function and prognostic value of efferocytosis in cancer remains unclear. In this study, we systematically analysed the expression profiles and genetic variations of 50 efferocytosis-related regulator genes in 33 cancer types. Using data from The Cancer Genome Atlas, we established an efferocytosis potential index (EPI) model to represent the efferocytosis level in each cancer type. The relationship between the EPI and prognosis, immune-related molecules, specific pathways, and drug sensitivity was determined. We found that efferocytosis regulator genes were abnormally expressed in cancer tissue, perhaps owing to copy number variations, gene alterations, and DNA methylation. For the most part, the EPI was higher in tumour vs. normal tissues. In most of the 33 cancer types, it positively correlated with cell death- and immune-related pathway enrichment, the tumour microenvironment, immune infiltration, and drug sensitivity. For specific cancers, a high EPI may be a prognostic risk factor and, in patients treated receiving immune checkpoint therapy, a predictor of poor prognosis. Our study reveals the biological functions of efferocytosis-related regulator genes in distinct cancers and highlights the potential of efferocytosis intervention in cancer therapy.

MerTK Drives Proliferation and Metastatic Potential in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by the absence of the estrogen receptor, progesterone receptor, and receptor tyrosine kinase HER2 expression. Due to the limited number of FDA-approved targeted therapies for TNBC, there is an ongoing need to understand the molecular underpinnings of TNBC for the development of novel combinatorial treatment strategies. This study evaluated the role of the MerTK receptor tyrosine kinase on proliferation and invasion/metastatic potential in TNBC. Immunohistochemical analysis demonstrated MerTK expression in 58% of patient-derived TNBC xenografts. The stable overexpression of MerTK in human TNBC cell lines induced an increase in proliferation rates, robust in vivo tumor growth, heightened migration/invasion potential, and enhanced lung metastases. NanoString nCounter analysis of MerTK-overexpressing SUM102 cells (SUM102-MerTK) revealed upregulation of several signaling pathways, which ultimately drive cell cycle progression, reduce apoptosis, and enhance cell survival. Proteomic profiling indicated increased endoglin (ENG) production in SUM102-MerTK clones, suggesting that MerTK creates a conducive environment for increased proliferative and metastatic activity via elevated ENG expression. To determine ENG's role in increasing proliferation and/or metastatic potential, we knocked out ENG in a SUM102-MerTK clone with CRISPR technology. Although this ENG knockout clone exhibited similar in vivo growth to the parental SUM102-MerTK clone, lung metastasis numbers were significantly decreased ~4-fold, indicating that MerTK enhances invasion and metastasis through ENG. Our data suggest that MerTK regulates a unique proliferative signature in TNBC, promoting robust tumor growth and increased metastatic potential through ENG upregulation. Targeting MerTK and ENG simultaneously may provide a novel therapeutic approach for TNBC patients.

MerTK-dependent efferocytosis by monocytic-MDSCs mediates resolution of post-lung transplant injury

Rationale

Patients with end stage lung diseases require lung transplantation (LTx) that can be impeded by ischemia-reperfusion injury (IRI) leading to subsequent chronic lung allograft dysfunction (CLAD) and inadequate outcomes.

Objectives

We examined the undefined role of MerTK (receptor Mer tyrosine kinase) on monocytic myeloid-derived suppressor cells (M-MDSCs) in efferocytosis (phagocytosis of apoptotic cells) to facilitate resolution of lung IRI.

Methods

Single-cell RNA sequencing of lung tissue and BAL from post-LTx patients was analyzed. Murine lung hilar ligation and allogeneic orthotopic LTx models of IRI were used with Balb/c (WT), cebpb -/- (MDSC-deficient), Mertk -/- or MerTK-CR (cleavage resistant) mice. Lung function, IRI (inflammatory cytokine and myeloperoxidase expression, immunohistology for neutrophil infiltration), and flow cytometry of lung tissue for efferocytosis of apoptotic neutrophils were assessed in mice.

Measurements and Main Results

A significant downregulation in MerTK-related efferocytosis genes in M-MDSC populations of CLAD patients compared to healthy subjects was observed. In the murine IRI model, significant increase in M-MDSCs, MerTK expression and efferocytosis was observed in WT mice during resolution phase that was absent in cebpb -/- Land Mertk -/- mice. Adoptive transfer of M-MDSCs in cebpb -/- mice significantly attenuated lung dysfunction, and inflammation leading to resolution of IRI. Additionally, in a preclinical murine orthotopic LTx model, increases in M-MDSCs were associated with resolution of lung IRI in the transplant recipients. In vitro studies demonstrated the ability of M-MDSCs to efferocytose apoptotic neutrophils in a MerTK-dependent manner.

Conclusions

Our results suggest that MerTK-dependent efferocytosis by M-MDSCs can significantly contribute to the resolution of post-LTx IRI.

Tumor-associated macrophages: an effective player of the tumor microenvironment

Cancer progression is primarily caused by interactions between transformed cells and the components of the tumor microenvironment (TME). TAMs (tumor-associated macrophages) make up the majority of the invading immune components, which are further categorized as anti-tumor M1 and pro-tumor M2 subtypes. While M1 is known to have anti-cancer properties, M2 is recognized to extend a protective role to the tumor. As a result, the tumor manipulates the TME in such a way that it induces macrophage infiltration and M1 to M2 switching bias to secure its survival. This M2-TAM bias in the TME promotes cancer cell proliferation, neoangiogenesis, lymphangiogenesis, epithelial-to-mesenchymal transition, matrix remodeling for metastatic support, and TME manipulation to an immunosuppressive state. TAMs additionally promote the emergence of cancer stem cells (CSCs), which are known for their ability to originate, metastasize, and relapse into tumors. CSCs also help M2-TAM by revealing immune escape and survival strategies during the initiation and relapse phases. This review describes the reasons for immunotherapy failure and, thereby, devises better strategies to impair the tumor-TAM crosstalk. This study will shed light on the understudied TAM-mediated tumor progression and address the much-needed holistic approach to anti-cancer therapy, which encompasses targeting cancer cells, CSCs, and TAMs all at the same time.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing Reveals That TAM2-Driven Genes Affect Immunotherapeutic Response and Prognosis in Pancreatic Cancer

Tumor-associated macrophages M2 (TAM2), which are highly prevalent infiltrating immune cells in the stroma of pancreatic cancer (PC), have been found to induce an immunosuppressive tumor microenvironment, thus enhancing tumor initiation and progression. However, the immune therapy response and prognostic significance of regulatory genes associated with TAM2 in PC are currently unknown. Based on TCGA transcriptomic data and single-cell sequencing data from the GEO database, we identified TAM2-driven genes using the WGCNA algorithm. Molecular subtypes based on TAM2-driven genes were clustered using the ConsensusClusterPlus algorithm. The study constructed a prognostic model based on TAM2-driven genes through Lasso-COX regression analysis. A total of 178 samples obtained by accessing TCGA were accurately categorized into two molecular subtypes, including the high-TAM2 infiltration (HMI) cluster and the low-TAM2 infiltration (LMI) cluster. The HMI cluster exhibits a poor prognosis, a malignant tumor phenotype, immune-suppressive immune cell infiltration, resistance to immunotherapy, and a high number of genetic mutations, while the LMI cluster is the opposite. The prognostic model composed of six hub genes from TAM2-driven genes exhibits a high degree of accuracy in predicting the prognosis of patients with PC and serves as an independent risk factor. The induction of TAM2 was employed as a means of verifying these six gene expressions, revealing the significant up-regulation of BCAT1, BST2, and MERTK in TAM2 cells. In summary, the immunophenotype and prognostic model based on TAM2-driven genes offers a foundation for the clinical management of PC. The core TAM2-driven genes, including BCAT1, BST2, and MERTK, are involved in regulating tumor progression and TAM2 polarization, which are potential targets for PC therapy.

Targeted degradation of MERTK and other TAM receptor paralogs by heterobifunctional targeted protein degraders

TAM receptors (TYRO3, AXL, and MERTK) comprise a family of homologous receptor tyrosine kinases (RTK) that are expressed across a range of liquid and solid tumors where they contribute to both oncogenic signaling to promote tumor proliferation and survival, as well as expressed on myeloid and immune cells where they function to suppress host anti-tumor immunity. In recent years, several strategies have been employed to inhibit TAM kinases, most notably small molecule tyrosine kinase inhibitors and inhibitory neutralizing monoclonal antibodies (mAbs) that block receptor dimerization. Targeted protein degraders (TPD) use the ubiquitin proteasome pathway to redirect E3 ubiquitin ligase activity and target specific proteins for degradation. Here we employ first-in-class TPDs specific for MERTK/TAMs that consist of a cereblon E3 ligase binder linked to a tyrosine kinase inhibitor targeting MERTK and/or AXL and TYRO3. A series of MERTK TPDs were designed and investigated for their capacity to selectively degrade MERTK chimeric receptors, reduce surface expression on primary efferocytic bone marrow-derived macrophages, and impact on functional reduction in efferocytosis (clearance of apoptotic cells). We demonstrate proof-of-concept and establish that TPDs can be tailored to either selectivity degrades MERTK or concurrently degrade multiple TAMs and modulate receptor expression in vitro and in vivo. This work demonstrates the utility of proteome editing, enabled by tool degraders developed here towards dissecting the therapeutically relevant pathway biology in preclinical models, and the ability for TPDs to degrade transmembrane proteins. These data also provide proof of concept that TPDs may serve as a viable therapeutic strategy for targeting MERTK and other TAMs and that this technology could be expanded to other therapeutically relevant transmembrane proteins.

Efferocytosis signatures as prognostic markers for revealing immune landscape and predicting immunotherapy response in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with late diagnosis; therefore, the identification of new early biomarkers could help reduce mortality. Efferocytosis, a process in which one cell engulfs another cell, including macrophages, dendritic cells, NK cells, etc., plays a complex role in tumorigenesis, sometimes promoting and sometimes inhibiting tumor development. However, the role of efferocytosis-related genes (ERGs) in HCC progression has been poorly studied, and their regulatory effects in HCC immunotherapy and drug targeting have not been reported. Methods: We downloaded efferocytosis-related genes from the Genecards database and screened for ERGs that showed significant expression changes between HCC and normal tissues and were associated with HCC prognosis. Machine learning algorithms were used to study prognostic gene features. CIBERSORT and pRRophetic R packages were used to evaluate the immune environment of HCC subtypes and predict treatment response. CCK-8 experiments conducted on HCC cells were used to assess the reliability of drug sensitivity prediction. Results: We constructed a prognostic prediction model composed of six genes, and the ROC curve showed good predictive accuracy of the risk model. In addition, two ERG-related subgroups in HCC showed significant differences in tumor immune landscape, immune response, and prognostic stratification. The CCK-8 experiment conducted on HCC cells confirmed the reliability of drug sensitivity prediction. Conclusion: Our study emphasizes the importance of efferocytosis in HCC progression. The risk model based on efferocytosis-related genes developed in our study provides a novel precision medicine approach for HCC patients, allowing clinicians to customize treatment plans based on unique patient characteristics. The results of our investigation carry noteworthy implications for the development of individualized treatment approaches involving immunotherapy and chemotherapy, thereby potentially facilitating the realization of personalized and more efficacious therapeutic interventions for HCC.