Author Correction: Multiplexed inhibition of immunosuppressive genes with Cas13d for combinatorial cancer immunotherapy
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Targeting of TAMs: can we be more clever than cancer cells?
With increasing incidence and geography, cancer is one of the leading causes of death, reduced quality of life and disability worldwide. Principal progress in the development of new anticancer therapies, in improving the efficiency of immunotherapeutic tools, and in the personification of conventional therapies needs to consider cancer-specific and patient-specific programming of innate immunity. Intratumoral TAMs and their precursors, resident macrophages and monocytes, are principal regulators of tumor progression and therapy resistance. Our review summarizes the accumulated evidence for the subpopulations of TAMs and their increasing number of biomarkers, indicating their predictive value for the clinical parameters of carcinogenesis and therapy resistance, with a focus on solid cancers of non-infectious etiology. We present the state-of-the-art knowledge about the tumor-supporting functions of TAMs at all stages of tumor progression and highlight biomarkers, recently identified by single-cell and spatial analytical methods, that discriminate between tumor-promoting and tumor-inhibiting TAMs, where both subtypes express a combination of prototype M1 and M2 genes. Our review focuses on novel mechanisms involved in the crosstalk among epigenetic, signaling, transcriptional and metabolic pathways in TAMs. Particular attention has been given to the recently identified link between cancer cell metabolism and the epigenetic programming of TAMs by histone lactylation, which can be responsible for the unlimited protumoral programming of TAMs. Finally, we explain how TAMs interfere with currently used anticancer therapeutics and summarize the most advanced data from clinical trials, which we divide into four categories: inhibition of TAM survival and differentiation, inhibition of monocyte/TAM recruitment into tumors, functional reprogramming of TAMs, and genetic enhancement of macrophages.
Enhancer reprogramming: critical roles in cancer and promising therapeutic strategies
Transcriptional dysregulation is a hallmark of cancer initiation and progression, driven by genetic and epigenetic alterations. Enhancer reprogramming has emerged as a pivotal driver of carcinogenesis, with cancer cells often relying on aberrant transcriptional programs. The advent of high-throughput sequencing technologies has provided critical insights into enhancer reprogramming events and their role in malignancy. While targeting enhancers presents a promising therapeutic strategy, significant challenges remain. These include the off-target effects of enhancer-targeting technologies, the complexity and redundancy of enhancer networks, and the dynamic nature of enhancer reprogramming, which may contribute to therapeutic resistance. This review comprehensively encapsulates the structural attributes of enhancers, delineates the mechanisms underlying their dysregulation in malignant transformation, and evaluates the therapeutic opportunities and limitations associated with targeting enhancers in cancer.
Immunogenicity of cell death and cancer immunotherapy with immune checkpoint inhibitors
While immunotherapy with immune checkpoint inhibitors (ICIs) has revolutionized the clinical management of various malignancies, a large fraction of patients are refractory to ICIs employed as standalone therapeutics, necessitating the development of combinatorial treatment strategies. Immunogenic cell death (ICD) inducers have attracted considerable interest as combinatorial partners for ICIs, at least in part owing to their ability to initiate a tumor-targeting adaptive immune response. However, compared with either approach alone, combinatorial regimens involving ICD inducers and ICIs have not always shown superior clinical activity. Here, we discuss accumulating evidence on the therapeutic interactions between ICD inducers and immunotherapy with ICIs in oncological settings, identify key factors that may explain discrepancies between preclinical and clinical findings, and propose strategies that address existing challenges to increase the efficacy of these combinations in patients with cancer.
The guided fire from within: intratumoral administration of mRNA-based vaccines to mobilize memory immunity and direct immune responses against pathogen to target solid tumors
We investigated a novel cancer immunotherapy strategy that effectively suppresses tumor growth in multiple solid tumor models and significantly extends the lifespan of tumor-bearing mice by introducing pathogen antigens into tumors via mRNA-lipid nanoparticles. The pre-existing immunity against the pathogen antigen can significantly enhance the efficacy of this approach. In mice previously immunized with BNT162b2, an mRNA-based COVID-19 vaccine encoding the spike protein of the SARS-CoV-2 virus, intratumoral injections of the same vaccine efficiently tagged the tumor cells with mRNA-expressed spike protein. This action rapidly mobilized the pre-existing memory immunity against SARS-CoV-2 to kill the cancer cells displaying the spike protein, while concurrently reprogramming the tumor microenvironment (TME) by attracting immune cells. The partial elimination of tumor cells in a normalized TME further triggered extensive tumor antigen-specific T cell responses through antigen spreading, eventually resulting in potent and systemic tumor-targeting immune responses. Moreover, combining BNT162b2 treatment with anti-PD-L1 therapy yielded a more substantial therapeutic impact, even in “cold tumor” types that are typically less responsive to treatment. Given that the majority of the global population has acquired memory immunity against various pathogens through infection or vaccination, we believe that, in addition to utilizing the widely held immune memory against SARS-CoV-2 via COVID-19 vaccine, mRNA vaccines against other pathogens, such as Hepatitis B Virus (HBV), Common Human Coronaviruses (HCoVs), and the influenza virus, could be rapidly transitioned into clinical use and holds great promise in treating different types of cancer. The extensive selection of pathogen antigens expands therapeutic opportunities and may also overcome potential drug resistance.
Identifying perturbations that boost T-cell infiltration into tumours via counterfactual learning of their spatial proteomic profiles
Cancer progression can be slowed down or halted via the activation of either endogenous or engineered T cells and their infiltration of the tumour microenvironment. Here we describe a deep-learning model that uses large-scale spatial proteomic profiles of tumours to generate minimal tumour perturbations that boost T-cell infiltration. The model integrates a counterfactual optimization strategy for the generation of the perturbations with the prediction of T-cell infiltration as a self-supervised machine learning problem. We applied the model to 368 samples of metastatic melanoma and colorectal cancer assayed using 40-plex imaging mass cytometry, and discovered cohort-dependent combinatorial perturbations (CXCL9, CXCL10, CCL22 and CCL18 for melanoma, and CXCR4, PD-1, PD-L1 and CYR61 for colorectal cancer) that support T-cell infiltration across patient cohorts, as confirmed via in vitro experiments. Leveraging counterfactual-based predictions of spatial omics data may aid the design of cancer therapeutics.
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