Tumor and immune remodeling following radiotherapy in human renal cell carcinoma

Basic and applied research progress of TRAIL in hematologic malignancies

Hematological malignancies encompass a diverse range of blood-related cancers characterized by abnormal blood cell production. These cancers, classified by the World Health Organization based on lineage, cell origin, and progression, provide a more comprehensive framework for understanding cancer biology. This classification has significantly advanced cancer research, particularly in genetic analyses for diagnosis and treatment. Despite recent clinical improvements, challenges, such as relapse, resistance, and high mortality, remain unresolved. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), a protein that induces apoptosis in cancer cells without affecting normal cells, has emerged as a promising therapeutic target. However, its clinical efficacy is limited by factors, such as tumor heterogeneity and resistance to TRAIL signaling. This review examines the mechanisms of TRAIL in hematological malignancies, factors contributing to resistance, and the current state of preclinical and clinical research, highlighting potential strategies to enhance TRAIL-based therapies in blood cancers.

Leveraging radiotherapy to improve immunotherapy outcomes: rationale, progress and research priorities

The most successful immunotherapies for solid malignancies to date, immune checkpoint inhibitors, target the essential role of T cells in antitumor immunity. However, T-cell dysfunction presents a major hindrance to treatment efficacy, warranting research into combined treatment strategies for improving outcomes. The use of radiotherapy for this purpose has garnered much interest. Preclinical study has established that radiotherapy activates various immune mechanisms to improve T-cell activation, localisation and function within tumors, which improves response to immune checkpoint inhibitors. However, so far, these strategies have not been successfully translated into the clinic. Here, we briefly reflect on the development of immune checkpoint inhibitors and the mechanistic insights revealed by an evolving understanding of T-cell dysfunction in cancer, before providing an overview of the immunomodulatory effects of radiotherapy in the context of the T-cell-mediated antitumor immune response. We discuss the mixed results of clinical trials, comment on various factors that may preclude immuno-radiotherapy responses in the clinic, and highlight priorities for preclinical and clinical study. Finally, we discuss the role of emerging combinations of radiotherapy and immunotherapy to potentially provide additional treatment options and improve outcomes for patients.

Pre-immunotherapy alters stereotactic ablative radiotherapy-induced systemic T cell responses in early-stage NSCLC

BACKGROUND

Stereotactic ablative radiotherapy (SABR) is thought to activate T cell responses in patients with cancer, leading to its combination with immunotherapy and chemotherapy for treatment of non-small-cell lung cancer (NSCLC). Here, we aimed to provide a high-resolution transcriptomic profiling of the systemic T cell response following SABR, with or without preceding immunotherapy/chemotherapy.

METHODS

We conducted single-cell RNA and T cell receptor (TCR) sequencing of T cells from peripheral blood of seven patients with early-stage NSCLC taken pre- and post-SABR without or with prior immunotherapy and chemotherapy (icSABR). Other flow cytometry, single-cell RNA-seq data and bulk RNA-seq data were used to validate the results.

RESULTS

We uncovered distinct T cell response patterns induced by these treatments: while terminal effector CD8+ T cells showed increased cytotoxic and inhibitory scores, and upregulated immune-activated pathways post-SABR, the reverse responses occurred post-icSABR. Furthermore, the proportion of large T cell clones increased and single clone decreased post-SABR, while the opposite was seen post-icSABR. Of note, both SABR and icSABR largely changed TCR clonotypes, which were mainly large clones post-SABR but single clone post-icSABR, and predominantly from terminal effector CD8+ T cells and T helper cells, respectively.

CONCLUSIONS

These findings reveal a complex interplay between SABR and immunotherapy, with potentially valuable implications for treatment strategies involving SABR and immunotherapy to induce systemic T cell responses for tumor eradication in patients with NSCLC.

Dynamic single-cell sequencing unveils the tumor microenvironment evolution of gastric cancer abdominal wall metastases during radiotherapy

Although the combination of immunotherapy and radiotherapy (RT) for the treatment of malignant tumors has shown rapid development, the insight of how RT remodels the tumor microenvironment to prime antitumor immunity involves a complex interplay of cell types and signaling pathways, much of which remains to be elucidated. Four tumor samples were collected from the same abdominal wall metastasis site of the patient with gastric cancer at baseline and during fractionated RT for single-cell RNA and T-cell receptor sequencing. The Seurat analysis pipeline and immune receptor analysis were used to characterize the gastric cancer metastasis ecosystem and investigated its dynamic changes of cell proportion, cell functional profiles and cell-to-cell communication during RT. Immunohistochemical and immunofluorescent staining and bulk RNA sequencing were applied to validate the key results. We found tumor cells upregulated immune checkpoint genes in response to RT. The infiltration and clonal expansion of T lymphocytes declined within tumors undergoing irradiation. Moreover, RT led to the accumulation of proinflammatory macrophages and natural killer T cells with enhanced cytotoxic gene expression signature. In addition, subclusters of dendritic cells and endothelial cells showed decrease in the expression of antigen present features in post-RT samples. More ECM component secreted by myofibroblasts during RT. These findings indicate that RT induced the dynamics of the immune response that should be taken into consideration when designing and clinically implementing innovative multimodal cancer treatment regimens of different RT and immunotherapy approaches.

Evaluation of the clinical significance of lymphocyte subsets and myeloid suppressor cells in patients with renal carcinoma

PURPOSE

The purpose of this study was to analyze the expression patterns of immune cells in renal cancer patients, including myeloid-derived suppressor cells (MDSCs), regulatory T cells (Tregs), CD3 + /CD4 + T cells, CD3 + / CD8 + T cells, and CD3- CD16 + CD56 + cells. In addition, this study will explore the correlation between these immune markers and the progression of renal cell carcinoma and evaluate their potential application in predicting the therapeutic effect of renal cell carcinoma.

METHODS

In this study, 80 renal cancer patients who received treatment in our hospital from October 2022 to December 2023 were selected as the research object and 50 healthy people who underwent a physical examination at the same time were selected as the control group. All participants had a 3 ml venous blood sample taken in the morning on an empty stomach. All patients with renal cell carcinoma have been confirmed by histopathological diagnosis. Clinicopathological data including age, gender, BMI, clinical stage, tumor size and pathological type were collected.MDSC, Treg, CD3 + /CD4 + T cells, CD3 + /CD8 + T cells, the ratio of CD3 + /CD4 + T cells/CD3 + /CD8 + T cell and the expression level of CD3-CD16 + CD56 + cells were detected by flow cytometry.

RESULTS

Through the detection of flow cytometry, we observed that there was no significant difference in gender, age, BMI and other baseline characteristics between renal cancer patients and healthy controls, and the P value was greater than 0.05. However, in the analysis of peripheral blood immune cell subsets, including CD3 + /CD4 + , CD3 + /CD8 + , CD3 + /CD4 + /CD3 + /CD8 + ratio, NK cells, regulatory T cells (T-reg), polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) and mononuclear myeloid-derived suppressor cells (M-MDSC) were significantly different between renal cell carcinoma group and normal control group (P < 0.05). Specifically, the expression levels of CD3 + /CD4 + and CD3 + /CD8 + cells in renal cancer patients were lower than those in normal subjects, while the expression levels of T-reg, PMN-MDSC and M-MDSC were relatively high. (2) In the flow cytometry analysis, the expression level of immune cell subsets in the peripheral blood of renal cancer patients was detected.The results showed that there was no significant correlation between the expression of CD3 + /CD4 + , CD3 + /CD8 + , CD3 + /CD4 + /CD3 + /CD8 + ratio, NK cells, T-reg cells, PMN-MDSC and M-MDSC and the sex, age, BMI and pathological type of the patients. These differences were not statistically significant (P > 0.05).At the same time, CD3 + /CD8 + T cells, the ratio of CD3 + /CD4 + /CD3 + /CD8 + and the expression level of NK cells were not significantly correlated with tumor size and clinical stage (P > 0.05). However, the expression levels of CD3 + /CD4 + cells, M-MDSC, PMN-MDSC, and T-reg cells were statistically significantly different with tumor size and clinical stage (P < 0.05).There was a significant difference between these indexes and lymph node metastasis (P < 0.05). (3) The results of Logistic regression analysis showed that the low expression of CD3 + /CD4 + lymphocytes and the high expression of T-reg, PMN-MDSC and M-MDSC in peripheral blood may be related to the clinical stage of renal cell carcinoma.

CONCLUSION

(1) Compared with healthy individuals, patients with renal cell carcinoma showed a significant decrease in CD3 + /CD4 + T cells, CD3 + /CD8 + T cells and CD3-CD16 + CD56 + cells, while the CD4 + /CD8 + ratio increased. In addition, the number of PMN-MDSC, M-MDSC and T-reg cells was significantly increased compared with the normal population, indicating that the immune system function of patients was impaired. (2) The expression levels of CD3 + /CD4 + , PMN-MDSC, M-MDSC and T-reg were different in tumor size and clinical stage. Specifically, the expression levels of PMN-MDSC, M-MDSC, and T-reg increased correspondingly with the increase in tumor diameter and the progression of the clinical stage.

Metabolic heterogeneity in clear cell renal cell carcinoma revealed by single-cell RNA sequencing and spatial transcriptomics

BACKGROUND

Clear cell renal cell carcinoma is a prototypical tumor characterized by metabolic reprogramming, which extends beyond tumor cells to encompass diverse cell types within the tumor microenvironment. Nonetheless, current research on metabolic reprogramming in renal cell carcinoma mostly focuses on either tumor cells alone or conducts analyses of all cells within the tumor microenvironment as a mixture, thereby failing to precisely identify metabolic changes in different cell types within the tumor microenvironment.

METHODS

Gathering 9 major single-cell RNA sequencing databases of clear cell renal cell carcinoma, encompassing 195 samples. Spatial transcriptomics data were selected to conduct metabolic activity analysis with spatial localization. Developing scMet program to convert RNA-seq data into scRNA-seq data for downstream analysis.

RESULTS

Diverse cellular entities within the tumor microenvironment exhibit distinct infiltration preferences across varying histological grades and tissue origins. Higher-grade tumors manifest pronounced immunosuppressive traits. The identification of tumor cells in the RNA splicing state reveals an association between the enrichment of this particular cellular population and an unfavorable prognostic outcome. The energy metabolism of CD8+ T cells is pivotal not only for their cytotoxic effector functions but also as a marker of impending cellular exhaustion. Sphingolipid metabolism evinces a correlation with diverse macrophage-specific traits, particularly M2 polarization. The tumor epicenter is characterized by heightened metabolic activity, prominently marked by elevated tricarboxylic acid cycle and glycolysis while the pericapsular milieu showcases a conspicuous enrichment of attributes associated with vasculogenesis, inflammatory responses, and epithelial-mesenchymal transition. The scMet facilitates the transformation of RNA sequencing datasets sourced from TCGA into scRNA sequencing data, maintaining a substantial degree of correlation.

CONCLUSIONS

The tumor microenvironment of clear cell renal cell carcinoma demonstrates significant metabolic heterogeneity across various cell types and spatial dimensions. scMet exhibits a notable capability to transform RNA sequencing data into scRNA sequencing data with a high degree of correlation.