Myeloid-derived suppressor cells: key immunosuppressive regulators and therapeutic targets in hematological malignancies

Current and future immunotherapeutic approaches in pancreatic cancer treatment

Pancreatic cancer is a major cause of cancer-related death, but despondently, the outlook and prognosis for this resistant type of tumor have remained grim for a long time. Currently, it is extremely challenging to prevent or detect it early enough for effective treatment because patients rarely exhibit symptoms and there are no reliable indicators for detection. Most patients have advanced or spreading cancer that is difficult to treat, and treatments like chemotherapy and radiotherapy can only slightly prolong their life by a few months. Immunotherapy has revolutionized the treatment of pancreatic cancer, yet its effectiveness is limited by the tumor's immunosuppressive and hard-to-reach microenvironment. First, this article explains the immunosuppressive microenvironment of pancreatic cancer and highlights a wide range of immunotherapy options, including therapies involving oncolytic viruses, modified T cells (T-cell receptor [TCR]-engineered and chimeric antigen receptor [CAR] T-cell therapy), CAR natural killer cell therapy, cytokine-induced killer cells, immune checkpoint inhibitors, immunomodulators, cancer vaccines, and strategies targeting myeloid cells in the context of contemporary knowledge and future trends. Lastly, it discusses the main challenges ahead of pancreatic cancer immunotherapy.

Targeting the innate immune system in pediatric and adult AML

While the introduction of T cell-based immunotherapies has improved outcomes in many cancer types, the development of immunotherapies for both adult and pediatric AML has been relatively slow and limited. In addition to the need to identify suitable target antigens, a better understanding of the immunosuppressive tumor microenvironment is necessary for the design of novel immunotherapy approaches. To date, most immune characterization studies in AML have focused on T cells, while innate immune lineages such as monocytes, granulocytes and natural killer (NK) cells, received less attention. In solid cancers, studies have shown that innate immune cells, such as macrophages, myeloid-derived suppressor cells and neutrophils are highly plastic and may differentiate into immunosuppressive cells depending on signals received in their microenvironment, while NK cells appear to be functionally impaired. Hence, an in-depth characterization of the innate immune compartment in the TME is urgently needed to guide the development of immunotherapeutic interventions for AML. In this review, we summarize the current knowledge on the innate immune compartment in AML, and we discuss how targeting its components may enhance T cell-based- and other immunotherapeutic approaches.

Identification of cell differentiation trajectory-related gene signature to reveal the prognostic significance and immune landscape in prostate cancer based on multiomics analysis

Background

In the context of prostate cancer (PCa), the occurrence of biochemical recurrence (BCR) stands out as a pivotal factor significantly impacting prognosis, potentially leading to metastasis and mortality. However, the early detection of BCR poses a substantial challenge for PCa patients. There is an urgent need to pinpoint hub genes that can serve as predictive indicators for BCR in PCa patients.

Methods

Our primary goal was to identify cell differentiation trajectory-related gene signature in PCa patients by pseudo-time trajectory analysis. We further explored the functional enrichment of overlapped marker genes and probed clinically relevant modules and BCR-related genes using Weighted Gene Co-expression Network Analysis (WGCNA) in PCa patients. Key genes predicting recurrence-free survival were meticulously identified through univariate and multivariate Cox regression analyses. Subsequently, these genes were utilized to construct a prognostic gene signature, the expression, predictive efficacy, putative functions, and immunological landscape of which were thoroughly validated. Additionally, we employed immunohistochemistry (IHC) and a western blotting assay to quantify the expression of PYCR1 in clinical samples.

Results

Our single-cell RNA (scRNA) sequencing analysis unveiled three subgroups characterized by distinct differentiation trajectories, and the marker genes associated with these groups were extracted from PCa patients. These marker genes successfully classified the PCa sample into two molecular subtypes, demonstrating a robust correlation with clinical characteristics and recurrence-free survival. Through WGCNA and Lasso analysis, we identified four hub genes (KLK3, CD38, FASN, and PYCR1) to construct a risk profile of prognostic genes linked to BCR. Notably, the high-risk patient group exhibited elevated levels of B cell naive, Macrophage M0, and Macrophage M2 infiltration, while the low-risk group displayed higher levels of T cells CD4 memory activated and monocyte infiltration. Furthermore, IHC and western blotting assays confirmed the heightened expression of PYCR1 in PCa tissues.

Conclusion

This study leveraged the differentiation trajectory and genetic variability of the microenvironment to uncover crucial prognostic genes associated with BCR in PCa patients. These findings present novel perspectives for tailoring treatment strategies for PCa patients on an individualized basis.

Immunogenic cell death related mRNAs associated signature to predict immunotherapeutic response in osteosarcoma

Background

Immunogenic cell death (ICD) is related to cancer prognosis, which has a synergic effect in combination with chemotherapy or immunotherapy. Yet, the relationship between ICD and osteosarcoma remained unclear.

Materials and methods

Three osteosarcoma datasets including therapeutically applicable research to generate effective treatments (TARGET), GSE126209 and GSE21257 datasets were included. A protein-protein interaction network was constructed based on ICD-related genes. We performed unsupervised consensus clustering to classify molecular subtypes (clusters). Survival analysis, Estimation of stromal and immune cells in malignant tumour tissues using expression data (ESTIMATE), Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and differential analysis were employed to characterize the molecular differences between different clusters. Univariate Cox regression analysis was conducted to confirm prognostic genes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to demonstrate the aberrant expression of ICD-correlated signature genes in osteosarcoma. A series of cellular experiments, including cell counting kit-8 (CCK-8), transwell, and flow cytometry, were used to demonstrate the regulatory role of key genes in the ICD model on the malignant phenotype of osteosarcoma.

Results

Three clusters (cluster1, 2, 3) were constructed and they showed distinct overall survival and immune infiltration. ICD-related genes were highly expressed in cluster1. Moreover, Cluster1 had the best prognosis, high immune score and high expression of human leukocyte antigen (HLA)-related genes. TLR4, LY96, IFNGR1, CD4, and CASP1 were identified as prognostic genes for establishing an ICD-related risk signature. According to the risk signature, two risk groups (high and low risks) showing differential prognosis and response to immunotherapy. The low risks group had a better prognosis but was not sensitive to immunotherapy. Molecular assays verified that prognostic genes were abnormally under-expressed in osteosarcoma. Cellular assays demonstrated that LY96, the most significantly down-regulated gene in osteosarcoma, inhibited the migration, invasion, and proliferation phenotypes of osteosarcoma cells and prolonged the cell cycle. Analysis of oxidative stress related pathway enrichment in tumor microenvironment was conducted by single-sample gene set enrichment analysis (ssGSEA).

Conclusions

This study demonstrated the prognostic significance of ICD-correlated genes in osteosarcoma patients. The five-gene risk signature facilitate prognostic evaluation and prediction of osteosarcoma patients' response to immunotherapy. The risk signature also offered a possibility for the exploit of novel ICD-related treatment.

Navigating the Immune Maze: Pioneering Strategies for Unshackling Cancer Immunotherapy Resistance

Cancer immunotherapy has ushered in a transformative era in oncology, offering unprecedented promise and opportunities. Despite its remarkable breakthroughs, the field continues to grapple with the persistent challenge of treatment resistance. This resistance not only undermines the widespread efficacy of these pioneering treatments, but also underscores the pressing need for further research. Our exploration into the intricate realm of cancer immunotherapy resistance reveals various mechanisms at play, from primary and secondary resistance to the significant impact of genetic and epigenetic factors, as well as the crucial role of the tumor microenvironment (TME). Furthermore, we stress the importance of devising innovative strategies to counteract this resistance, such as employing combination therapies, tailoring immune checkpoints, and implementing real-time monitoring. By championing these state-of-the-art methods, we anticipate a paradigm that blends personalized healthcare with improved treatment options and is firmly committed to patient welfare. Through a comprehensive and multifaceted approach, we strive to tackle the challenges of resistance, aspiring to elevate cancer immunotherapy as a beacon of hope for patients around the world.

Emerging Therapeutic Targets and Drug Resistance Mechanisms in Immunotherapy of Hematological Malignancies

CAR-T cell therapy has revolutionized the treatment of hematological malignancies with high remission rates in the case of ALL and NHL. This therapy has some limitations such as long manufacturing periods, persistent restricted cell sources and high costs. Moreover, combination regimens increase the risk of immune-related adverse events, so the identification new therapeutic targets is important to minimize the risk of toxicities and to guide more effective approaches. Cancer cells employ several mechanisms to evade immunosurveillance, which causes resistance to immunotherapy; therefore, a very important therapeutic approach is to focus on the development of rational combinations of targeted therapies with non-overlapping toxicities. Recent progress in the development of new inhibitory clusters of differentiation (CDs), signaling pathway molecules, checkpoint inhibitors, and immunosuppressive cell subsets and factors in the tumor microenvironment (TME) has significantly improved anticancer responses. Novel strategies regarding combination immunotherapies with CAR-T cells are the most promising approach to cure cancer.

Unraveling the enigma of tumor-associated macrophages: challenges, innovations, and the path to therapeutic breakthroughs

Tumor-associated macrophages (TAMs) are integral to the tumor microenvironment (TME), influencing cancer progression significantly. Attracted by cancer cell signals, TAMs exhibit unparalleled adaptability, aligning with the dynamic tumor milieu. Their roles span from promoting tumor growth and angiogenesis to modulating metastasis. While substantial research has explored the fundamentals of TAMs, comprehending their adaptive behavior, and leveraging it for novel treatments remains challenging. This review delves into TAM polarization, metabolic shifts, and the complex orchestration of cytokines and chemokines determining their functions. We highlight the complexities of TAM-targeted research focusing on their adaptability and potential variability in therapeutic outcomes. Moreover, we discuss the synergy of integrating TAM-focused strategies with established cancer treatments, such as chemotherapy, and immunotherapy. Emphasis is laid on pioneering methods like TAM reprogramming for cancer immunotherapy and the adoption of single-cell technologies for precision intervention. This synthesis seeks to shed light on TAMs' multifaceted roles in cancer, pinpointing prospective pathways for transformative research and enhancing therapeutic modalities in oncology.

Nano-engineering nanomedicines with customized functions for tumor treatment applications

Nano-engineering with unique "custom function" capability has shown great potential in solving technical difficulties of nanomaterials in tumor treatment. Through tuning the size and surface properties controllablly, nanoparticles can be endoewd with tailored structure, and then the characteristic functions to improve the therapeutic effect of nanomedicines. Based on nano-engineering, many have been carried out to advance nano-engineering nanomedicine. In this review, the main research related to cancer therapy attached to the development of nanoengineering nanomedicines has been presented as follows. Firstly, therapeutic agents that target to tumor area can exert the therapeutic effect effectively. Secondly, drug resistance of tumor cells can be overcome to enhance the efficacy. Thirdly, remodeling the immunosuppressive microenvironment makes the therapeutic agents work with the autoimmune system to eliminate the primary tumor and then prevent tumor recurrence and metastasis. Finally, the development prospects of nano-engineering nanomedicine are also outlined.

Myeloid-derived suppressor cells (MDSCs): what do we currently know about the effect they have against anti-PD-1/PD-L1 therapies?

Recent advances in cancer treatment such as PD-1/PD-L1 checkpoint inhibitors have prompted multiple research studies to determine all of the factors that influence response or failure to these new treatments. One of those identified factors is myeloid-derived suppressor cells (MDSCs). These cells were identified and described for the first time in 2007 in laboratory mice and cancer patients. Previous studies showed that a greater number of MDSCs was directly related to a greater tumour volume. There are two clearly identified subpopulations: Mononuclear-type myeloid-derived suppressor cells (M-MDSCs) and polymorphonuclear (PMN-MDSCs). These cell population subtypes play a very important role, depending on the type of cancer, since they have the particularity of expressing PD-L1, which interacts with PD-1, inhibiting the expansion of cytotoxic T lymphocytes, promoting resistance to these treatments.