Recent Advances In Cancer Immunotherapy Research Articles

Recent Advances in Cancer Immunotherapy: Clinical Implications and Future Directions

Cancer immunotherapy has transformed cancer treatment by harnessing the immune system to recognize and eliminate cancer cells. Recent years have witnessed significant advancements in this field, including the development of immune checkpoint inhibitors, chimeric antigen receptor (CAR) T-cell therapy, cancer vaccines, and adoptive cell therapy. These approaches have shown promising results in clinical trials, leading to improved outcomes for cancer patients. This paper provides an in-depth overview of recent advances in cancer immunotherapy, their clinical implications, challenges, and future directions.

The immunosuppressive landscape in tumor microenvironment.

Recent advances in cancer immunotherapy, especially immune checkpoint inhibitors (ICIs), have revolutionized the clinical outcome of many cancer patients. Despite the fact that impressive progress has been made in recent decades, the response rate remains unsatisfactory, and many patients do not benefit from ICIs. Herein, we summarized advanced studies and the latest insights on immune inhibitory factors in the tumor microenvironment. Our in-depth discussion and updated landscape of tumor immunosuppressive microenvironment may provide new strategies for reversing tumor immune evasion, enhancing the efficacy of ICIs therapy, and ultimately achieving a better clinical outcome.

Pancreatic cancer-associated fibroblasts modulate macrophage differentiation via sialic acid-Siglec interactions

Despite recent advances in cancer immunotherapy, pancreatic ductal adenocarcinoma (PDAC) remains unresponsive due to an immunosuppressive tumor microenvironment, which is characterized by the abundance of cancer-associated fibroblasts (CAFs). Once identified, CAF-mediated immune inhibitory mechanisms could be exploited for cancer immunotherapy. Siglec receptors are increasingly recognized as immune checkpoints, and their ligands, sialic acids, are known to be overexpressed by cancer cells. Here, we unveil a previously unrecognized role of sialic acid-containing glycans on PDAC CAFs as crucial modulators of myeloid cells. Using multiplex immunohistochemistry and transcriptomics, we show that PDAC stroma is enriched in sialic acid-containing glycans compared to tumor cells and normal fibroblasts, and characterized by ST3GAL4 expression. We demonstrate that sialic acids on CAF cell lines serve as ligands for Siglec-7, -9, -10 and -15, distinct from the ligands on tumor cells, and that these receptors are found on myeloid cells in the stroma of PDAC biopsies. Furthermore, we show that CAFs drive the differentiation of monocytes to immunosuppressive tumor-associated macrophages in vitro, and that CAF sialylation plays a dominant role in this process compared to tumor cell sialylation. Collectively, our findings unravel sialic acids as a mechanism of CAF-mediated immunomodulation, which may provide targets for immunotherapy in PDAC.

Recent Advances in Cancer Immunotherapy with a Focus on FDA-Approved Vaccines and Neoantigen-Based Vaccines.

Cancer immunotherapies refer to the concept of retraining the immune system to target malignant cells. Multiple immunotherapeutic options exist including immune modulating antibodies, immune stimulating cytokines, chimeric antigen receptor T cell therapy, and vaccines. Overall, this field has advanced rapidly as knowledge of the tumor microenvironment, immunological pathways, and biotechnology expands. Specifically, advancements in neoantigen identification, characterization, and formulation into a vaccine show promise. This review is focused on previously United States Food and Drug Administration-approved cancer therapeutic vaccines and neoantigen-based vaccine developments along with the associated relevant clinical trials.

Long noncoding RNA MIAT regulates TP53 ubiquitination and expedites prostate adenocarcinoma progression by recruiting TBL1X.

Despite recent advances in cancer immunotherapy, their efficacy for treating patients with prostate adenocarcinoma (PRAD) is low due to complex immune evasion mechanisms. However, the function of long non-coding RNA (lncRNAs) in immune evasion has not been fully clarified. This study aimed to expound the role of myocardial infarction-associated transcript (MIAT), a lncRNA significantly upregulated in three PRAD-associated datasets, in immune evasion and try to reveal the potential mechanism. MIAT was highly expressed in PRAD tissues and predicted poor prognosis, and suppression of MIAT inhibited the malignant biological behavior of PRAD cells. Moreover, the depletion of MIAT promoted the immune response of CD8+ T cells and hampered the immune evasion of PRAD cells. In addition, MIAT downregulated TP53 protein expression by recruiting transducin beta-like protein 1X (TBL1X) for ubiquitination modification. Silencing of TP53 or overexpression of TBL1X was enough to abate the tumor suppressive effects of MIAT knockdown in vitro and in vivo. Our results provide evidence for a novel regulation mechanism of CD8+ T cells in PRAD and MIAT may serve as a potential therapeutic target in PRAD.

Light-responsive nanomedicine for cancer immunotherapy.

Immunotherapy emerged as a paradigm shift in cancer treatments, which can effectively inhibit cancer progression by activating the immune system. Remarkable clinical outcomes have been achieved through recent advances in cancer immunotherapy, including checkpoint blockades, adoptive cellular therapy, cancer vaccine, and tumor microenvironment modulation. However, extending the application of immunotherapy in cancer patients has been limited by the low response rate and side effects such as autoimmune toxicities. With great progress being made in nanotechnology, nanomedicine has been exploited to overcome biological barriers for drug delivery. Given the spatiotemporal control, light-responsive nanomedicine is of great interest in designing precise modality for cancer immunotherapy. Herein, we summarized current research utilizing light-responsive nanoplatforms to enhance checkpoint blockade immunotherapy, facilitate targeted delivery of cancer vaccines, activate immune cell functions, and modulate tumor microenvironment. The clinical translation potential of those designs is highlighted and challenges for the next breakthrough in cancer immunotherapy are discussed.

Dynamics and specificities of T cells in cancer immunotherapy.

Recent advances in cancer immunotherapy - ranging from immune-checkpoint blockade therapy to adoptive cellular therapy and vaccines - have revolutionized cancer treatment paradigms, yet the variability in clinical responses to these agents has motivated intense interest in understanding how the T cell landscape evolves with respect to response to immune intervention. Over the past decade, the advent of multidimensional single-cell technologies has provided the unprecedented ability to dissect the constellation of cell states of lymphocytes within a tumour microenvironment. In particular, the rapidly expanding capacity to definitively link intratumoural phenotypes with the antigen specificity of T cells provided by T cell receptors (TCRs) has now made it possible to focus on investigating the properties of T cells with tumour-specific reactivity. Moreover, the assessment of TCR clonality has enabled a molecular approach to track the trajectories, clonal dynamics and phenotypic changes of antitumour T cells over the course of immunotherapeutic intervention. Here, we review the current knowledge on the cellular states and antigen specificities of antitumour T cells and examine how fine characterization of T cell dynamics in patients has provided meaningful insights into the mechanisms underlying effective cancer immunotherapy. We highlight those T cell subsets associated with productive T cell responses and discuss how diverse immunotherapies might leverage the pre-existing tumour-reactive T cell pool or instruct de novo generation of antitumour specificities. Future studies aimed at elucidating the factors associated with the elicitation of productive antitumour T cell immunity are anticipated to instruct the design of more efficacious treatment strategies.

Abstract 1714: CRACD/KIAA1211 loss drives cell plasticity and immune evasion of small cell lung cancer

Abstract Small cell lung carcinoma (SCLC) is a lethal neuroendocrine type of lung cancer with limited therapeutic options. Despite recent advances in cancer immunotherapy, its efficacy is limited to a small subset of SCLC patient tumors. The molecular origin of the refractoriness to immunotherapy remains elusive. CRACD (Capping protein inhibiting regulator of actin dynamics; KIAA1211/CRAD) gene is frequently mutated and transcriptionally downregulated in SCLC. Cracd knockout (KO) causes the transformation of preneoplastic neuroendocrine cells and significantly accelerates SCLC development in a mouse model initiated by the loss of Rb1, Trp53, and Rbl2 in the lung epithelium. Cracd KO induces tumor cell plasticity generating deregulated cell lineage trajectories of SCLC tumors. Strikingly, Cracd KO SCLC tumors display the complete loss of CD8+ T cells due to epigenetic suppression of the MHC-I pathway. Furthermore, single-cell transcriptomic analyses of SCLC patient samples classified SCLC by concurrent features: CRACD inactivation and tumor antigen presentation impairment. This study suggests CRACD as a tumor suppressor of SCLC that regulates proliferation and immune recognition of cells, providing novel insight into the mechanism of SCLC evading immune surveillance. Citation Format: Shengzhe Zhang, Kee-Bum Kim, Yuanjian Huang, Dong-Wook Kim, Bongjun Kim, Kyung-Pil Ko, Gengyi Zou, Jie Zhang, Sohee Jun, Nicole A. Kirk, Ye Eun Hwang, Young Ho Ban, Joseph M. Chan, Charles M. Rudin, Kwon-Sik Park, Jae-Il Park. CRACD/KIAA1211 loss drives cell plasticity and immune evasion of small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1714.

Optimization of CD200 checkpoint immunotherapy for treating glioblastoma.

Glioblastoma Multiforme (GBM) is a lethal brain cancer with a median survival between 10-14 months. The standard of care for GBM is a combination of resection, followed by chemotherapy, and radiotherapy. Recent advances in cancer immunotherapy have significantly improved the survival of patients in selected solid tumors. However, in the case of GBM, current immunotherapy has failed, potentially, due to obstacles including immunosuppressive molecules in the tumor microenvironment. CD200 is an immunosuppressive protein that is overexpressed on tumors suppressing the immune system. The University of Minnesota developed a novel CD200 checkpoint immunotherapy, currently in Phase I clinical trial (NCT04642937), targeting the activation receptors on immune cells with a peptide ligand to overcome its immunosuppressive effect on recurrent GBM. While the treatment shows promising results in patient outcomes, the CD200 mechanism in the dendritic cells is still unclear. In this study, we postulate a detailed pathway and develop an Ordinary Differential Equation model, based on the law of mass action, to describe its behavior. Using Global Sensitivity analysis techniques, we explore the parameter space and identify potential targets on the pathway to optimize the CD200 checkpoint therapy and improve its clinical impact.

Unconventional Effector Cells in Cancer Therapy: A Narrative Review

Cancer immunotherapy has revolutionized the field of oncology by harnessing the power of the immune system to target and eliminate cancer cells. Traditional immunotherapeutic approaches have primarily focused on activating and enhancing the activity of conventional immune cells, such as T cells and natural killer (NK) cells. However, recent advances in cancer immunotherapy have explored the use of unconventional effector cells, which possess unique characteristics and capabilities that make them attractive candidates for targeting cancer. This review aims to provide an overview about unconventional effector cells in cancer therapy, highlighting their potential advantages, challenges, and future prospects.

Immune System Influence on Hematopoietic Stem Cells and Leukemia Development.

Hematopoietic stem cells (HSCs) are the source for all blood cells, including immune cells, and they interact dynamically with the immune system. This chapter will explore the nature of stem cells, particularly HSCs, in the context of their immune microenvironment. The dynamic interactions between stem cells and the immune system can have profound implications for current and future therapies, particularly regarding a potential "immune-privileged" HSC microenvironment. Immune/stem cell interactions change during times of stress and injury. Recent advances in cancer immunotherapy have overturned the long-standing belief that, being derived from the self, cancer cells should be immunotolerant. Instead, an immunosurveillance system recognizes and eliminates emergent pre-cancerous cells. Only in the context of a failing immunosurveillance system does cancer fully develop. Combined with the knowledge that stem cells or their unique properties can be critically important for cancer initiation, persistence, and resistance to therapy, understanding the unique immune properties of stem cells will be critical for the development of future cancer therapies. Accordingly, the therapeutic implications for leukemic stem cells (LSCs) inheriting an immune-privileged state from HSCs will be discussed. Through their dynamic interactions with a diverse immune system, stem cells serve as the light and dark root of cancer prevention vs. development.

Current landscape and future directions of bispecific antibodies in cancer immunotherapy.

Recent advances in cancer immunotherapy using monoclonal antibodies have dramatically revolutionized the therapeutic strategy against advanced malignancies, inspiring the exploration of various types of therapeutic antibodies. Bispecific antibodies (BsAbs) are recombinant molecules containing two different antigens or epitopes identifying binding domains. Bispecific antibody-based tumor immunotherapy has gained broad potential in preclinical and clinical investigations in a variety of tumor types following regulatory approval of newly developed technologies involving bispecific and multispecific antibodies. Meanwhile, a series of challenges such as antibody immunogenicity, tumor heterogeneity, low response rate, treatment resistance, and systemic adverse effects hinder the application of BsAbs. In this review, we provide insights into the various architecture of BsAbs, focus on BsAbs' alternative different mechanisms of action and clinical progression, and discuss relevant approaches to overcome existing challenges in BsAbs clinical application.

Optogenetic-controlled immunotherapeutic designer cells for post-surgical cancer immunotherapy

Surgical resection is the main treatment option for most solid tumors, yet cancer recurrence after surgical resection remains a significant challenge in cancer therapy. Recent advances in cancer immunotherapy are enabling radical cures for many tumor patients, but these technologies remain challenging to apply because of side effects related to uncontrollable immune system activation. Here, we develop far-red light-controlled immunomodulatory engineered cells (FLICs) that we load into a hydrogel scaffold, enabling the precise optogenetic control of cytokines release (IFN-β, TNF-α, and IL-12) upon illumination. Experiments with a B16F10 melanoma resection mouse model show that FLICs-loaded hydrogel implants placed at the surgical wound site achieve sustainable release of immunomodulatory cytokines, leading to prevention of tumor recurrence and increased animal survival. Moreover, the FLICs-loaded hydrogel implants elicit long-term immunological memory that prevents against tumor recurrence. Our findings illustrate that this optogenetic perioperative immunotherapy with FLICs-loaded hydrogel implants offers a safe treatment option for solid tumors based on activating host innate and adaptive immune systems to inhibit tumor recurrence after surgery. Beyond extending the optogenetics toolbox for immunotherapy, we envision that our optogenetic-controlled living cell factory platform could be deployed for other biomedical contexts requiring precision induction of bio-therapeutic dosage.

Flow cytometry-based immunophenotyping of myeloid-derived suppressor cells in human breast cancer patient blood samples

Multi-color flow cytometry is the standard approach for immunophenotyping clinical samples. With the recent advances in cancer immunotherapy, myeloid-derived suppressor cells (MDSC), immature myeloid-lineage cells in cancer patient blood and the tumor microenvironment, are highlighted as an important immune cell population that correlates with prognosis and therapeutic efficacy. In contrast to their clear functions and existence, immunophenotyping of MDSC is not consistent among investigators due to surface antigens overlapping with many normal hematopoietic lineage cell populations. We performed a clinical study and analyzed more than 1000 breast cancer patients blood samples to quantitate MDSC during breast cancer progression. In this methodology manuscript, we described detailed procedures for study design, sample logistics and handling, staining and flow cytometric analysis. This protocol used a 7-color fluorochrome-conjugated antibody panel to analyze polymorphonuclear (PMN)- and monocytic (M)-MDSC subsets simultaneously. The interim analysis results of this study showed that both PMN and M-MDSC populations are increased in patients with bone metastasis compared with patients with visceral organ metastasis. In conclusion, this work provides a versatile, comprehensive, and practical protocol to measure MDSC in patient blood samples.

Novel antigens for targeted radioimmunotherapy in hepatocellular carcinoma.

Liver cancer is the sixth common cancer and forth cause of cancer-related death worldwide. Based on usually advanced stages of hepatocellular carcinoma (HCC) at the time of diagnosis, therapeutic options are limited and, in many cases, not effective, and typically result in the tumor recurrence with a poor prognosis. Radioimmunotherapy (RIT) offers a selective internal radiation therapy approach using beta or alpha emitting radionuclides conjugated with tumor-specific monoclonal antibodies (mAbs), or specific selective peptides. When compared to chemotherapy or radiotherapy, radiolabeled mAbs against cancer-associated antigens could provide a high therapeutic and exclusive radiation dose for cancerous cells while decreasing the exposure-induced side effects to healthy tissues. The recent advances in cancer immunotherapy, such as blockade of immune-checkpoint inhibitors (ICIs), has changed the landscape of cancer therapy, and the efficacy of different classes of immunotherapy has been tested in many clinical trials. Taking into account the use of ICIs in the liver tumor microenvironment, combined therapies with different approaches may enhance the outcome in the future clinical studies. With the development of novel immunotherapy treatment options in the recent years, there has been a great deal of information about combining the diverse treatment modalities to boost the effectiveness of immunomodulatory drugs. In this opinion review, we will discuss the recent advancements in RIT. The current status of immunotherapy and internal radiotherapy will be updated, and we will propose novel approaches for the combination of both techniques. Potential target antigens for radioimmunotherapy in Hepatocellular carcinoma (HCC). HCC radioimmunotherapy target antigens are the most specific and commonly accessible antigens on the surface of HCC cells. CTLA-4 ligand and receptor, TAMs, PD-1/PD-L, TIM-3, specific IEXs/TEXs, ROBO1, and cluster of differentiation antigens CD105, CD147 could all be used in HCC radioimmunotherapy. Abbreviations: TAMs, tumor-associated macrophages; CTLA-4, cytotoxic T-lymphocyte associated antigen-4; PD-1, Programmed cell death protein 1; PD-L, programmed death-ligand1; TIM-3, T-cell immunoglobulin (Ig) and mucin-domain containing protein-3; IEXs, immune cell-derived exosomes; TEXs, tumor-derived exosomes.

Recent advances in cancer immunotherapy: Modulation of tumor microenvironment by Toll-like receptor ligands.

Immunotherapy is considered a promising approach for cancer treatment. An important strategy for cancer immunotherapy is the use of cancer vaccines, which have been widely used for cancer treatment. Despite the great potential of cancer vaccines for cancer treatment, their therapeutic effects in clinical settings have been limited. The main reason behind the lack of significant therapeutic outcomes for cancer vaccines is believed to be the immunosuppressive tumor microenvironment (TME). The TME counteracts the therapeutic effects of immunotherapy and provides a favorable environment for tumor growth and progression. Therefore, overcoming the immunosuppressive TME can potentially augment the therapeutic effects of cancer immunotherapy in general and therapeutic cancer vaccines in particular. Among the strategies developed for overcoming immunosuppression in TME, the use of toll-like receptor (TLR) agonists has been suggested as a promising approach to reverse immunosuppression. In this paper, we will review the application of the four most widely studied TLR agonists including agonists of TLR3, 4, 7, and 9 in cancer immunotherapy.

Machine learning and bioinformatics analysis revealed classification and potential treatment strategy in stage 3\u20134 NSCLC patients

BackgroundPrecision medicine has increased the accuracy of cancer diagnosis and treatment, especially in the era of cancer immunotherapy. Despite recent advances in cancer immunotherapy, the overall survival rate of advanced NSCLC patients remains low. A better classification in advanced NSCLC is important for developing more effective treatments.MethodThe calculation of abundances of tumor-infiltrating immune cells (TIICs) was conducted using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT), xCell (xCELL), Tumor IMmune Estimation Resource (TIMER), Estimate the Proportion of Immune and Cancer cells (EPIC), and Microenvironment Cell Populations-counter (MCP-counter). K-means clustering was used to classify patients, and four machine learning methods (SVM, Randomforest, Adaboost, Xgboost) were used to build the classifiers. Multi-omics datasets (including transcriptomics, DNA methylation, copy number alterations, miRNA profile) and ICI immunotherapy treatment cohorts were obtained from various databases. The drug sensitivity data were derived from PRISM and CTRP databases.ResultsIn this study, patients with stage 3–4 NSCLC were divided into three clusters according to the abundance of TIICs, and we established classifiers to distinguish these clusters based on different machine learning algorithms (including SVM, RF, Xgboost, and Adaboost). Patients in cluster-2 were found to have a survival advantage and might have a favorable response to immunotherapy. We then constructed an immune-related Poor Prognosis Signature which could successfully predict the advanced NSCLC patient survival, and through epigenetic analysis, we found 3 key molecules (HSPA8, CREB1, RAP1A) which might serve as potential therapeutic targets in cluster-1. In the end, after screening of drug sensitivity data derived from CTRP and PRISM databases, we identified several compounds which might serve as medication for different clusters.ConclusionsOur study has not only depicted the landscape of different clusters of stage 3–4 NSCLC but presented a treatment strategy for patients with advanced NSCLC.

T-cell dysfunction in the glioblastoma microenvironment is mediated by myeloid cells releasing interleukin-10

Despite recent advances in cancer immunotherapy, certain tumor types, such as Glioblastomas, are highly resistant due to their tumor microenvironment disabling the anti-tumor immune response. Here we show, by applying an in-silico multidimensional model integrating spatially resolved and single-cell gene expression data of 45,615 immune cells from 12 tumor samples, that a subset of Interleukin-10-releasing HMOX1+ myeloid cells, spatially localizing to mesenchymal-like tumor regions, drive T-cell exhaustion and thus contribute to the immunosuppressive tumor microenvironment. These findings are validated using a human ex-vivo neocortical glioblastoma model inoculated with patient derived peripheral T-cells to simulate the immune compartment. This model recapitulates the dysfunctional transformation of tumor infiltrating T-cells. Inhibition of the JAK/STAT pathway rescues T-cell functionality both in our model and in-vivo, providing further evidence of IL-10 release being an important driving force of tumor immune escape. Our results thus show that integrative modelling of single cell and spatial transcriptomics data is a valuable tool to interrogate the tumor immune microenvironment and might contribute to the development of successful immunotherapies.

Algorithmic asymptotic analysis: Extending the arsenal of cancer immunology modeling

The recent advances in cancer immunotherapy boosted the development of tumor-immune system models, with the aim to indicate more efficient treatments. Physical understanding is however difficult to be acquired, due to the complexity and the multi-scale dynamics of these models. In this work, the dynamics of a fundamental model formulating the interactions of tumor cells with natural killer cells, CD8+ T cells and circulating lymphocytes is examined. It is first shown that the long-term evolution of the system towards high-tumor or tumor-free equilibria is determined by the dynamics of an initial explosive stage of tumor progression. Focusing on this stage, the algorithmic Computational Singular Perturbation methodology is employed to identify the underlying mechanisms confining the system’s evolution and the governing slow dynamics along them. These insights are preserved along different tumor-immune system and patient-dependent realizations. On top of these identifications, a novel reduced model is algorithmically constructed, which accurately predicts the dynamics of the system during the explosive stage and includes half of the parameters of the detailed model. The present analysis demonstrates the potential of algorithmic asymptotic analysis for acquiring physical understanding and for simplifying the complexity of cancer immunology models. Along with the current techniques on the field, this analysis can provide guidelines for more effective treatment development.

Going with the Flow: Modeling the Tumor Microenvironment Using Microfluidic Technology.

Simple SummaryThe clinical success of cancer immunotherapy targeting immune checkpoints (e.g., PD-1, CTLA-4) has ushered in a new era of cancer therapeutics aimed at promoting antitumor immunity in hopes of offering durable clinical responses for patients with advanced, metastatic cancer. This success has also reinvigorated interest in developing tumor model systems that recapitulate key features of antitumor immune responses to complement existing in vivo tumor models. Patient-derived tumor models have emerged in recent years to facilitate study of tumor–immune dynamics. Microfluidic technology has enabled development of microphysiologic systems (MPSs) for the evaluation of the tumor microenvironment, which have shown early promise in studying tumor–immune dynamics. Further development of microfluidic-based “tumor-on-a-chip” MPSs to study tumor–immune interactions may overcome several key challenges currently facing tumor immunology.Recent advances in cancer immunotherapy have led a paradigm shift in the treatment of multiple malignancies with renewed focus on the host immune system and tumor–immune dynamics. However, intrinsic and acquired resistance to immunotherapy limits patient benefits and wider application. Investigations into the mechanisms of response and resistance to immunotherapy have demonstrated key tumor-intrinsic and tumor-extrinsic factors. Studying complex interactions with multiple cell types is necessary to understand the mechanisms of response and resistance to cancer therapies. The lack of model systems that faithfully recapitulate key features of the tumor microenvironment (TME) remains a challenge for cancer researchers. Here, we review recent advances in TME models focusing on the use of microfluidic technology to study and model the TME, including the application of microfluidic technologies to study tumor–immune dynamics and response to cancer therapeutics. We also discuss the limitations of current systems and suggest future directions to utilize this technology to its highest potential.