An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers

The effect of exercise and disease status on mobilization of anti-tumorigenic and pro-tumorigenic immune cells in women with breast cancer

Background

Mobilization of certain immune cells may improve the ability of the immune system to combat tumor cells, but the effect of acute exercise on mobilizing immune cells has been sparsely investigated in cancer patients. Therefore, we examined how acute exercise influences circulating immune cells in breast cancer patients.

Methods

Nineteen newly diagnosed breast cancer patients aged 36-68 performed 30 minutes of moderate-intensity exercise with a cycle ergometer. Blood samples were collected at various time points: at rest, at 15 (E15) and 30 minutes (E30) after onset of the exercise, and at 30 and 60 minutes post-exercise. We analyzed several immune cell subsets using flow cytometry.

Results

Acute exercise increased the number of total leukocytes, neutrophils, lymphocytes, monocytes, basophils, total T-cells, CD4+ T-cells, T helper (Th) 2-cells, Th 17-cells, CD8+ T-cells, CD4-CD8- T-cells, CD56+ natural killer (NK) cells, and CD14-CD16+ monocytes. Many of the changes were transient. Proportions of NK-cells and CD8+ T-cells increased, while the proportion of myeloid derived suppressor cells (MDSCs) reduced, and proportion of regulatory T-cells remained unchanged by exercise. Several associations were detected between cell mobilizations and disease state. For instance, tumor size correlated negatively with NK cell mobilization at E15, and progesterone receptor positivity correlated negatively with CD8+ T-cell mobilization.

Conclusion

The findings show that the proportions of CD8+ T-cells and NK cells increased and the proportion of MDSCs proportion decreased in breast cancer patients after 30-minute exercise, suggesting a change in the profile of circulating immune cells towards more cytotoxic/anti-tumorigenic. The mobilization of some immune cells also appears to be related to the disease state.

The effects of postoperative targeted immunotherapy on peripheral blood cytokines and immune cell profile in lung cancer patients

Objective

Cytokines and cell subsets are important components of the tumor microenvironment. Previous research has revealed that there are differences in cytokines and cell subsets in the peripheral blood of lung cancer (LCA) patients before and after eradication. The purpose of this study is to explore the monitoring value of cytokines and cellular subpopulations as biomarkers in post-immunotherapy monitoring of patients with LCA after surgery.

Methods

We conducted a case-control study using double-antibody sandwich magnetic microsphere flow cytometry with immunofluorescence technology and fluorescent monoclonal antibody multiparameter flow cytometry to detect differences in peripheral blood cytokines and cell subsets between LCA patients after immunotherapy and healthy controls.

Results

Our research results show that there are differences in the levels of IL-4, IL-6, IL-10, IL-17, IFN-γ, TNF-α in the peripheral blood of LCA patients (n=70) after immunotherapy compared to the healthy controls (n=55) (P<0.05), and there are differences in 10 cell subgroups including DP T Cells, AT cells, and NLR in the peripheral blood compared to the healthy controls (n=35) (P<0.05). Further analysis revealed significant differences in the detection data of IL-6, IL-10, IFN-γ, CD56dim NK cells, Total B cells, Total NE cells, CD15+M cells, and NLR between LCA deceased patients (n=25) and LCA surviving patients (n=27) during the same period (P<0.05). The continuous monitoring of cytokines and cell subsets is far more valuable than a single-time test, as abnormal fluctuations in the data of cytokines and cell subsets are often associated with poor prognosis. In addition, IL-6 and NLR showed the strongest discriminative ability between postoperative immunotherapy-treated LCA patients and healthy controls, with AUC values of 0.840 and 0.822, respectively. There was a significant association between IFN-γ and distant metastasis in LCA (P<0.05), as well as between CD56dim NK cells and lymph node infiltration (P<0.05).

Conclusion

This research results support peripheral blood cytokines and cell subsets as biomarkers for monitoring the postoperative immune status and predicting the prognosis of LCA patients after immunotherapy. The continuous monitoring of cytokines and cell subsets is far more valuable than a single-time detection.

Single-cell transcriptome analysis of macrophage subpopulations contributing to chemotherapy resistance in ovarian cancer

BACKGROUND

Ovarian cancer, a fatal gynecological malignancy, is primarily managed through surgery and chemotherapy. However, a significant challenge arises as patients frequently experience relapse due to chemotherapy resistance. This study delves into the complex functions and underlying mechanisms of macrophages in chemotherapy resistance in ovarian cancer.

METHOD

The single-cell transcriptome sequencing data of ovarian cancer with or without chemotherapy were analyzed. Then, corresponding cell types were identified, and macrophages were extracted from all cells. Following the standardized single-cell analysis using the Seurat package, 15 distinct macrophage clusters were found and differentially expressed genes among them were analyzed. Moreover, their association with chemotherapy resistance was explored through cell proportions and gene expression.

RESULT

In the single-cell transcriptomic analysis of ovarian cancer tissues before and after chemotherapy, the cellular proportion of CXCL5+ macrophages, THBS1+ macrophages, and MMP9+ macrophages were significantly increased following chemotherapy. Further investigation revealed that these macrophage subpopulations upregulated the expression of multiple pro-tumorigenic angiogenic or invasive factors, in addition to CXCL5, THBS1, and MMP9, including CTSL, CXCL1, and CCL18. Finally, pathway enrichment analysis revealed the significant activation of signaling pathways, such as NOD-like receptor, MAPK, and TNF in these macrophage subpopulations, which provides direction for studying the mechanism of these subpopulations.

CONCLUSION

CXCL5+, THBS1+, and MMP9+ macrophage subpopulations exhibit an increased cellular prevalence post-chemotherapy and pro-tumorigenic molecular expression profiles, suggesting a close association with chemoresistance in ovarian cancer. These findings contribute to our understanding of the roles and mechanisms of macrophages in ovarian cancer chemoresistance, providing a theoretical basis and direction for the development of therapies targeting macrophages in overcoming ovarian cancer chemoresistance.

Spatial insights into immunotherapy response in non-small cell lung cancer (NSCLC) by multiplexed tissue imaging

The spatial localisation of immune cells within tumours are key to understand the intercellular communications that can dictate clinical outcomes. Here, we demonstrate an analysis pipeline for highly multiplexed CODEX data to phenotype and profile spatial features and interactions in NSCLC patients that subsequently received PD1 axis immunotherapy. We found that regulatory T cells (Tregs) are enriched in non-responding patients and this was consistent with their localization within stromal and peripheral tumour-margins. Proximity-based interactions between Tregs and both monocytes (p = 0.009) and CD8+ T cells (p = 0.009) were more frequently found in non-responding patients, while macrophages were more frequently located in proximity to HLADR+ tumour cells (p = 0.01) within responding patients. Cellular neighbourhoods analysis indicated that both macrophages (p = 0.003) and effector CD4+ T cells (p = 0.01) in mixed tumour neighbourhoods, as well as CD8+ T cells (p = 0.03) in HLADR+ tumour neighbourhoods were associated with favorable clinical response. Evaluation of the inferred regulatory functions between immune cells relative to the tumour suggested that macrophages exhibit an immunosuppressive phenotype against both CD4+ and CD8+ T cells, and that this association scores more highly in ICI refractory patients. These spatial patterns are associated with overall survival in addition to ICI response and may thus indicate features for the functional understanding of the tumour microenvironment.

Prognostic value of a modified‑immune scoring system in patients with pathological T4 colorectal cancer

Tumor-infiltrating immune cells, such as lymphocytes and macrophages, have been associated with tumor aggressiveness, prognosis and treatment response in colorectal cancer (CRC). An immune scoring system, Immunoscore (IS), based on tumor-infiltrating T cells in stage I-III CRC, was used to predict prognosis. An alternative immune scoring signature of immune activation (SIA) reflects the balance between anti- and pro-tumoral immune components. The present study aimed to evaluate the prognostic value of modified IS (mIS) and modified SIA (mSIA) in locally advanced pathological T4 (pT4) CRC, including stage IV CRC. Immunohistochemical staining for immune cell markers, such as CD3 (pan-T cell marker), CD8 (anti-tumoral cytotoxic T cell marker) and CD163 (tumor-supportive macrophage marker), in specimens from patients with radically resected pT4 CRC at stages II-IV was performed. mIS levels in the T4 CRC cohort were not associated with prognosis. However, low mSIA levels were associated with low survival. Furthermore, low mSIA was an independent predictor of recurrence in patients with radically resected pT4 CRC. In patients with CRC who did not receive postoperative adjuvant chemotherapy, low mSIA was a major poor prognostic factor; however, this was not observed in patients receiving adjuvant chemotherapy. Evaluation of the tumor-infiltrating immune cell population could serve as a valuable marker of recurrence and poor prognosis in patients with locally advanced CRC. mSIA assessment after radical CRC resection may be promising for identifying high-risk patients with pT4 CRC who require aggressive adjuvant chemotherapy.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Comprehensive Analysis Reveals Prognostic and Therapeutic Immunity-Related Biomarkers for Pediatric Metastatic Osteosarcoma

Background and Objectives: Osteosarcoma, the most prevalent malignant bone tumor in children and adolescents, presents a complex pathogenesis characterized by various genetic and epigenetic alterations. This study aims to identify key differentially expressed genes (DEGs) in pediatric osteosarcoma, with a focus on those influencing metastasis and patient survival. Materials and Methods: We utilized the GSE33382 dataset from the GEO database for a comprehensive bioinformatic analysis. This included a protein-protein interaction (PPI) network analysis, Cox regression, and Kaplan-Meier survival analysis to identify central DEGs associated with osteosarcoma metastasis and patient survival. Results: Our analysis identified 88 DEGs related to osteosarcoma metastasis. Among them, three survival-related central DEGs-C1QA, CD74, and HLA-DMA-were significantly linked to patient outcomes. Further correlation analysis established a strong relationship between these genes, tumor mutation burden (TMB), immune checkpoint gene expression, and overall survival. Notably, C1QA and CD74 exhibited higher expression in non-metastatic osteosarcoma cases, suggesting a potential role in disease progression. Conclusions: The identified DEGs, particularly C1QA, CD74, and HLA-DMA, may serve as critical biomarkers for pediatric osteosarcoma prognosis and potential targets for immunotherapy. These findings provide a deeper understanding of the molecular landscape of osteosarcoma and open new avenues for therapeutic intervention.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

The role and participation of immune cells in the endometrial tumor microenvironment

The tumor microenvironment is surrounded by blood vessels and consists of malignant, non-malignant, and immune cells, as well as signalling molecules, which primarily affect the therapeutic response and curative effects of drugs in clinical studies. Tumor-infiltrating immune cells participate in tumor progression, impact anticancer therapy, and eventually lead to the development of immune tolerance. Immunotherapy is evolving as a promising therapeutic intervention to stimulate and activate the immune system to suppress cancer cell growth. Endometrial cancer (EC) is an immunogenic disease, and in recent years, immunotherapy has shown benefit in the treatment of recurrent and advanced EC. This review discusses the key molecular pathways associated with the intra-tumoral immune response and the involvement of circulatory signalling molecules. Specific immunologic signatures in EC which offer targets for immunomodulating agents, are also discussed. We have summarized the available literature in support of using immunotherapy in EC. Lastly, we have also discussed ongoing clinical trials that may offer additional promising immunotherapy options in the future. The manuscript also explored innovative approaches for screening and identifying effective drugs, and to reduce the financial burdens for the development of personalized treatment strategies. Collectively, we aim to provide a comprehensive review of the role of immune cells and the tumor microenvironment in the development, progression, and treatment of EC.

A paradigm shift in the prevention and diagnosis of oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a widespread disease with only 50%-60% 5-year survival. Individuals with potentially malignant precursor lesions are at high risk.

METHODS

Survival could be increased by effective, affordable, and simple screening methods, along with a shift from incisional tissue biopsies to non-invasive brush biopsies for cytology diagnosis, which are easy to perform in primary care. Along with the explainable, fast, and objective artificial intelligence characterisation of cells through deep learning, an easy-to-use, rapid, and cost-effective methodology for finding high-risk lesions is achievable. The collection of cytology samples offers the further opportunity of explorative genomic analysis.

RESULTS

Our prospective multicentre study of patients with leukoplakia yields a vast number of oral keratinocytes. In addition to cytopathological analysis, whole-slide imaging and the training of deep neural networks, samples are analysed according to a single-cell RNA sequencing protocol, enabling mapping of the entire keratinocyte transcriptome. Mapping the changes in the genetic profile, based on mRNA expression, facilitates the identification of biomarkers that predict cancer transformation.

CONCLUSION

This position paper highlights non-invasive methods for identifying patients with oral mucosal lesions at risk of malignant transformation. Reliable non-invasive methods for screening at-risk individuals bring the early diagnosis of OSCC within reach. The use of biomarkers to decide on a targeted therapy is most likely to improve the outcome. With the large-scale collection of samples following patients over time, combined with genomic analysis and modern machine-learning-based approaches for finding patterns in data, this path holds great promise.