Blood eosinophilic relative count is prognostic for breast cancer and associated with the presence of tumor at diagnosis and at time of relapse

Granulocytes and mast cells in AllergoOncology-Bridging allergy to cancer: An EAACI position paper

Derived from the myeloid lineage, granulocytes, including basophils, eosinophils, and neutrophils, along with mast cells, play important, often disparate, roles across the allergic disease spectrum. While these cells and their mediators are commonly associated with allergic inflammation, they also exhibit several functions either promoting or restricting tumor growth. In this Position Paper we discuss common granulocyte and mast cell features relating to immunomodulatory functions in allergy and in cancer. We highlight key mechanisms which may inform cancer treatment and propose pertinent areas for future research. We suggest areas where understanding the communication between granulocytes, mast cells, and the tumor microenvironment, will be crucial for identifying immune mechanisms that may be harnessed to counteract tumor development. For example, a comprehensive understanding of allergic and immune factors driving distinct neutrophil states and those mechanisms that link mast cells with immunotherapy resistance, might enable targeted manipulation of specific subpopulations, leading to precision immunotherapy in cancer. We recommend specific areas of investigation in AllergoOncology and knowledge exchange across disease contexts to uncover pertinent reciprocal functions in allergy and cancer and allow therapeutic manipulation of these powerful cell populations. These will help address the unmet needs in stratifying and managing patients with allergic diseases and cancer.

The causal relationships of granulocytes and melanoma skin cancer: A univariable and multivariable Mendelian randomization study

BACKGROUND

Increasing evidence has revealed that granulocyte has a critical role in tumorigenesis and progression. In this study, Mendelian randomization (MR) analysis was utilized for estimating the causal association between neutrophil percentage and melanoma skin cancer, eosinophil percentage and melanoma skin cancer, basophil percentage and melanoma skin cancer, respectively.

METHODS

The Genome-Wide Association Study (GWAS) ids for melanoma skin cancer, neutrophil percentage, eosinophil percentage and basophil percentage were derived from Integrative Epidemiology Unit (IEU) Open GWAS database. The univariable MR (UVMR) analysis was conducted to estimate the risk using MR-Egger, weighted median, inverse variance weighted (IVW). In addition, sensitivity analysis was conducted to assess the reliability of UVMR results. Finally, the multivariable MR (MVMR) analysis was performed to investigate causality between neutrophil percentage and eosinophil percentage in the presence of both and melanoma skin cancer.

RESULTS

The UVMR indicated that neutrophil percentage and eosinophil percentage were significantly and causally related to melanoma skin cancer, with neutrophil percentage [p = 0.025, odds ratio (OR) = 1.002] as a risk factor and eosinophil percentage (p = 7.04E-06, OR = 0.997) as a protective factor. Moreover, MVMR analysis indicated eosinophil percentage remained the protective factor (p = 0.003, OR = 0.998), while the causality of neutrophil percentage and melanoma skin cancer became insignificant (p > 0.05).

CONCLUSION

The causal relationships of neutrophil percentage and melanoma skin cancer, eosinophil percentage and melanoma skin cancer were shown by this study, which provided a reference for subsequent research and treatment related to melanoma skin cancer.

Exploration of SERPINA family functions and prognostic value in breast cancer based on transcriptome and in vitro analysis

Breast cancer poses a significant risk to women worldwide, yet specific role of SERPINA gene family in breast cancer remains unclarified. Data were collected from online databases. SERPINA family gene expression was presented, and prognosis value was evaluated. Multi-omics methods were employed to explore the SERPINA-related biological processes, followed by comprehensive analyses of their roles in breast cancer. Single-cell data were analyzed to characterize the SERPINA family gene expression in different cell clusters. We selected SERPINA5 as the target gene. Via pan-cancer analysis, SERPINA5 was also investigated in various cancers. The experimental validation was conducted in MDA-MB-231 cell line eventually. SERPINA family showed differential expression in breast cancer, which were mainly expressed in myeloid cells, epithelial cells, and dendritic cells. SERPINA5 expression was upregulated in breast cancer, which was associated with a better prognosis. Immune infiltration illustrated the positive correlativity between SERPINA5 intensity and eosinophilic recruitment. Pan-cancer analysis indicated the function of SERPINA5 as a potential biomarker in other cancers. Finally, experimental validation demonstrated that SERPINA5 contributes to lower invasion and metastatic potential of breast cancer cells. With bioinformatics analysis, the significant role SERPINA family genes functioned in breast cancer was comprehensively explored, with SERPINA5 emerging as a key gene in suppressing breast cancer progression.

Cost-effective prognostic evaluation of breast cancer: using a STAR nomogram model based on routine blood tests

Background

Breast cancer (BC) is the most common and prominent deadly disease among women. Predicting BC survival mainly relies on TNM staging, molecular profiling and imaging, hampered by subjectivity and expenses. This study aimed to establish an economical and reliable model using the most common preoperative routine blood tests (RT) data for survival and surveillance strategy management.

Methods

We examined 2863 BC patients, dividing them into training and validation cohorts (7:3). We collected demographic features, pathomics characteristics and preoperative 24-item RT data. BC risk factors were identified through Cox regression, and a predictive nomogram was established. Its performance was assessed using C-index, area under curves (AUC), calibration curve and decision curve analysis. Kaplan-Meier curves stratified patients into different risk groups. We further compared the STAR model (utilizing HE and RT methodologies) with alternative nomograms grounded in molecular profiling (employing second-generation short-read sequencing methodologies) and imaging (utilizing PET-CT methodologies).

Results

The STAR nomogram, incorporating subtype, TNM stage, age and preoperative RT data (LYM, LYM%, EOSO%, RDW-SD, P-LCR), achieved a C-index of 0.828 in the training cohort and impressive AUCs (0.847, 0.823 and 0.780) for 3-, 5- and 7-year OS rates, outperforming other nomograms. The validation cohort showed similar impressive results. The nomogram calculates a patient's total score by assigning values to each risk factor, higher scores indicating a poor prognosis. STAR promises potential cost savings by enabling less intensive surveillance in around 90% of BC patients. Compared to nomograms based on molecular profiling and imaging, STAR presents a more cost-effective, with potential savings of approximately $700-800 per breast cancer patient.

Conclusion

Combining appropriate RT parameters, STAR nomogram could help in the detection of patient anemia, coagulation function, inflammation and immune status. Practical implementation of the STAR nomogram in a clinical setting is feasible, and its potential clinical impact lies in its ability to provide an early, economical and reliable tool for survival prediction and surveillance strategy management. However, our model still has limitations and requires external data validation. In subsequent studies, we plan to mitigate the potential impact on model robustness by further updating and adjusting the data and model.

Eosinophil dynamics during chemo-radiotherapy correlate to clinical outcome in stage Ⅱ-Ⅳa nasopharyngeal carcinoma patients: Results from a large cohort study

BACKGROUND AND PURPOSE

We investigated the dynamics of eosinophil depletion during definitive concurrent chemo-radiotherapy (CCRT) and their association with the prognosis of stage Ⅱ-Ⅳa nasopharyngeal carcinoma (NPC) patients.

MATERIALS AND METHODS

Fuzzy C-means algorithm (FCMA) assessed longitudinal trends in circulating eosinophil counts (CECs) of 1225 patients throughout the period of radical radiotherapy. The prognostic impact on patients' survival was evaluated with Kaplan-Meier analysis and Cox proportional risk model was used to determine the hazard ratio for adverse prognostic effects in grades of eosinophil depletion. The interactive effect of pre-treatment CECs and CCRT on outcomes was evaluated using HRs within the framework of Cox regression models.

RESULTS

Three grades of eosinophil depletion, as defined by the interaction between dynamic types of CECs in the period of treatment and the value of CECs at the termination of treatment, significantly stratified the poor prognosis in terms of progression-free survival (PFS), overall survival (OS), and distant metastasis-free survival (DMFS) [1.57-fold (P = 0.001), 1.69-fold (P = 0.007), and 1.51-fold (P = 0.019) for G1, 2.4-fold (P < 0.001), 2.76-fold (P < 0.001), and 2.31-fold (P < 0.001) for G2, as compared with G0]. Furthermore, high levels of pre-treatment CECs acted as the strongest protective factor against severe depletion grade (G0 vs. G2, HR = 0.20, P = 0.005; G1 vs. G2, HR = 0.14, P < 0.001). However, compared with radiotherapy alone, the benefit from CCRT was attenuated in patients with high pre-treatment CECs.

CONCLUSIONS

CECs reduction after treatment in patients with NPC may be helpful in the clinical setting to aid in assessing the prognosis for standard treatment of NPC.

Type 1 and type 2 cytokine-mediated immune orchestration in the tumour microenvironment and their therapeutic potential

Cancer remains the second leading cause of death worldwide despite modern breakthroughs in medicine, and novel treatments are urgently needed. The revolutionary success of immune checkpoint inhibitors in the past decade serves as proof of concept that the immune system can be effectively harnessed to treat cancer. Cytokines are small signalling proteins with critical roles in orchestrating the immune response and have become an attractive target for immunotherapy. Type 1 immune cytokines, including interferon γ (IFNγ), interleukin-12 (IL-12), and tumour necrosis factor α (TNFα), have been shown to have largely tumour suppressive roles in part through orchestrating anti-tumour immune responses mediated by natural killer (NK) cells, CD8⁺ T cells and T helper 1 (Th1) cells. Conversely, type 2 immunity involving group 2 innate lymphoid cells (ILC2s) and Th2 cells are involved in tissue regeneration and wound repair and are traditionally thought to have pro-tumoural effects. However, it is found that the classical type 2 immune cytokines IL-4, IL-5, IL-9, and IL-13 may have conflicting roles in cancer. Similarly, type 2 immunity-related cytokines IL-25 and IL-33 with recently characterised roles in cancer may either promote or suppress tumorigenesis in a context-dependent manner. Furthermore, type 1 cytokines IFNγ and TNFα have also been found to have pro-tumoural effects under certain circumstances, further complicating the overall picture. Therefore, the dichotomy of type 1 and type 2 cytokines inhibiting and promoting tumours respectively is not concrete, and attempts of utilising these for cancer immunotherapy must take into account all available evidence. This review provides an overview summarising the current understanding of type 1 and type 2 cytokines in tumour immunity and discusses the prospects of harnessing these for immunotherapy in light of previous and ongoing clinical trials.

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.

Eosinophilia in cancer and its regulation by sex hormones

Gender differences in the functionality of the immune system have been attributed, in part, to direct and indirect effects of sex steroids, especially estrogens, on immune cell repertoire and activity. Notable are studies that have defined roles for estrogens in the regulation of the biology of dendritic cells (DCs), macrophages, T cells and natural killer (NK) cells. Although estrogens can modulate eosinophil function, the mechanisms by which this occurs and how it contributes to the pathobiology of different diseases remains underexplored. Furthermore, although the importance of eosinophils in infection is well established, it remains unclear as to how these innate immune cells, which are present in different tumors, impact the biology of cancer cells and/or response to therapeutics. The observation that eosinophilia influences the efficacy of immune checkpoint blockers (ICBs) is significant considering the role of estrogens as regulators of eosinophil function and recent studies suggesting that response to ICBs is impacted by gender. Thus, in this review, we consider what is known about the roles of estrogen(s) in regulating tissue eosinophilia/eosinophil function and how this influences the pathobiology of breast cancer (in particular). This information provides the context for a discussion of how estrogens/the estrogen receptor (ER) signaling axis can be targeted in eosinophils and how this would be expected to influence the activity of standard-of-care interventions and contemporary immunotherapy regimens in cancer(s).

Excess of blood eosinophils prior to therapy correlates with worse prognosis in mesothelioma

Background

Only a fraction of patients with malignant pleural mesothelioma (MPM) will respond to chemo- or immunotherapy. For the majority, the condition will irremediably relapse after 13 to 18 months. In this study, we hypothesized that patients' outcome could be correlated to their immune cell profile. Focus was given to peripheral blood eosinophils that, paradoxically, can both promote or inhibit tumor growth depending on the cancer type.

Methods

The characteristics of 242 patients with histologically proven MPM were retrospectively collected in three centers. Characteristics included overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and disease control rate (DCR). The mean absolute eosinophil counts (AEC) were determined by averaging AEC data sets of the last month preceding the administration of chemo- or immunotherapy.

Results

An optimal cutoff of 220 eosinophils/µL of blood segregated the cohort into two groups with significantly different median OS after chemotherapy (14 and 29 months above and below the threshold, p = 0.0001). The corresponding two-year OS rates were 28% and 55% in the AEC ≥ 220/µL and AEC < 220/µL groups, respectively. Based on shorter median PFS (8 vs 17 months, p < 0.0001) and reduced DCR (55.9% vs 35.2% at 6 months), the response to standard chemotherapy was significantly affected in the AEC ≥ 220/µL subset. Similar conclusions were also drawn from data sets of patients receiving immune checkpoint-based immunotherapy.

Conclusion

In conclusion, baseline AEC ≥ 220/µL preceding therapy is associated with worse outcome and quicker relapse in MPM.

Eosinophils and melanoma: Implications for immunotherapy

New therapies such as immune checkpoint blockers (ICB) have offered extended survival to patients affected by advanced melanoma. However, ICBs have demonstrated debilitating side effects on the joints, liver, lungs, skin, and gut. Several biomarkers have been identified for their role in predicting which patients better tolerate ICBs. Still, these biomarkers are limited by immunologic and genetic heterogeneity and the complexity of translation into clinical practice. Recent observational studies have suggested eosinophil counts, and serum levels of eosinophil cationic protein are significantly associated with prolonged survival in advanced-stage melanoma. It is likely that eosinophils thereby modulate treatment response through mechanisms yet to be explored. Here, we review the functionality of eosinophils, their oncogenic role in melanoma and discuss how these mechanisms may influence patient response to ICBs and their implications in clinical practice.

Overexpression of SKA3 correlates with poor prognosis in female early breast cancer

BACKGROUND

Spindle and kinetochore associated complex subunit 3 (SKA3) plays an important role in tumorigenesis and the progression of various tumors. But the relationship between SKA3 and early breast cancer remains unclear. The study aimed to explore the prognostic significance of SKA3 in breast cancer.

METHODS

In the study, SKA3 expression was initially assessed using the Oncomine database and The Cancer Genome Atlas database (TCGA). Then, we presented validation results for RT-qPCR (quantitative reverse transcription PCR) and ELISA (enzyme-linked immunosorbent assay). The relationship between clinical characteristics and SKA3 expression was assessed by Chi-square test and Fisher's exact test. Kaplan-Meier method and Cox regression analysis were conducted to evaluate the prognostic value of SKA3. Gene set enrichment analysis (GSEA) was performed to screen biological pathways using the TCGA dataset. Besides, single sample gene set enrichment analysis (ssGSEA) was utilized to identify immune infiltration cells about SKA3.

RESULTS

SKA3 mRNA was expressed at high levels in breast cancer tissues compared with normal tissues. Chi-square test and Fisher's exact test showed SKA3 expression was related to age, tumor (T) classification, node (N) classification, tumor-node-metastasis (TNM) stage, estrogen receptor (ER), progesterone receptor (PR), molecular subtype, and race. RT-qPCR results showed that SKA3 expression was overexpressed in ER, PR status, and molecular subtype in Chinese people. Kaplan-Meier curves implicated that high SKA3 expression was related to a poor prognosis in female early breast cancer patients. Cox regression models showed that high SKA3 expression could be used as an independent risk factor for female early breast cancer. Four signaling pathways were enriched in the high SKA3 expression group, including mTORC1 signaling pathway, MYC targets v1, mitotic spindle, estrogen response early. Besides, the SKA3 expression level was associate with infiltrating levels of activated CD4 T cells and eosinophils in breast cancer.

CONCLUSION

High SKA3 expression correlates with poor prognosis and immune infiltrates in breast cancer. SKA3 may become a biomarker for the prognosis of breast cancer.

Peripheral blood eosinophil count is associated with response to chemoimmunotherapy in metastatic triple-negative breast cancer

Introduction: There is evidence for an association between peripheral blood eosinophil count (PBEC) and response to cancer immunotherapy; however, such data is limited in metastatic triple-negative breast cancer (mTNBC). Patients & methods: This report presents patients (n = 14) who received a combination of durvalumab and paclitaxel for mTNBC (NCT02628132). Results: There was a statistically significant correlation (p = 0.028) between an increase in PBEC (>300/mm³) during treatment and response to the combination therapy. Survival analysis showed a statistically significant association between progression-free survival and increased PBEC, after therapy (p = 0.005). A similar trend existed for overall survival, although it did not reach statistical significance (p = 0.167). Conclusion: This is the first study to report on eosinophilia in mTNBC treated with chemoimmunotherapy and supports a role for eosinophils in immunotherapy for mTNBC.

The Role of Innate Immune Cells in Tumor Invasion and Metastasis

Metastasis is considered one of the hallmarks of cancer and enhanced tumor invasion and metastasis is significantly associated with cancer mortality. Metastasis occurs via a series of integrated processes involving tumor cells and the tumor microenvironment. The innate immune components of the microenvironment have been shown to engage with tumor cells and not only regulate their proliferation and survival, but also modulate the surrounding environment to enable cancer progression. In the era of immune therapies, it is critical to understand how different innate immune cell populations are involved in this process. This review summarizes recent literature describing the roles of innate immune cells during the tumor metastatic cascade.

Metastasis-Entrained Eosinophils Enhance Lymphocyte-Mediated Antitumor Immunity

The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein-coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ-activated eosinophils facilitated CD4⁺ and CD8⁺ T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics. SIGNIFICANCE: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.

The Microenvironment's Role in Mycosis Fungoides and Sézary Syndrome: From Progression to Therapeutic Implications

BACKGROUND

Mycosis fungoides (MF) and Sezary Syndrome (SS) are the most common cutaneous T-cell lymphomas. It has been hypothesized that the interaction between the immune system, cutaneous cells, and neoplastic elements may play a role in MF/SS pathogenesis and progression.

METHODS

This paper aims to revise in a narrative way our current knowledge of the microenvironment's role in MF/SS.

RESULTS AND CONCLUSIONS

Literature data support a possible implication of microenvironment cells in MF/SS pathogenesis and progression, opening up new therapeutic avenues.

Overexpression of MAL2 Correlates with Immune Infiltration and Poor Prognosis in Breast Cancer

Background

Myelin and lymphocyte, T cell differentiation protein 2 (MAL2) is highly expressed in various cancers and associated with the development and prognosis of cancer. However, the relationship between MAL2 and breast cancer requires further investigation. This study aimed to explore the prognostic significance of MAL2 in breast cancer.

Methods

MAL2 expression was initially assessed using the Oncomine database and The Cancer Genome Atlas (TCGA) database and verified by quantitative real-time polymerase chain reaction (RT-qPCR). The chi-square test or Fisher's exact test was used to explore the association between clinical characteristics and MAL2 expression. The prognostic value of MAL2 in breast cancer was assessed by the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify the biological pathways correlated with MAL2 expression in breast cancer. Besides, a single-sample GSEA (ssGSEA) was used to assess the relationship between the level of immune infiltration and MAL2 in breast cancer.

Results

Both bioinformatics and RT-qPCR results showed that MAL2 was expressed at high levels in breast cancer tissues compared with the adjacent tissues. The chi-square test or Fisher's exact test indicated that MAL2 expression was related to stage, M classification, and vital status. Kaplan–Meier curves implicated that high MAL2 expression was significantly associated with the poor prognosis. Cox regression models showed that high MAL2 expression could be an independent risk factor for breast cancer. GSEA showed that 14 signaling pathways were enriched in the high-MAL2-expression group. Besides, the MAL2 expression level negatively correlated with infiltrating levels of eosinophils and plasmacytoid dendritic cells in breast cancer.

Conclusion

Overexpression of MAL2 correlates with poor prognosis and lower immune infiltrating levels of eosinophils and plasmacytoid dendritic cells in breast cancer and may become a biomarker for breast cancer prognosis.

Immunity and Breast Cancer: Focus on Eosinophils

The role of eosinophils, a cell type involved in the immune response to parasitic infections and allergies, has been investigated in different cancer types, in both tumor tissue and at the circulating level. Most studies showed a role mainly in conjunction with immunotherapy in melanomas and lung tumors, while few data are available in breast cancer. In this review, we summarize literature data on breast cancer, showing a prognostic role of circulating eosinophil counts as well as of the presence of tumor tissue infiltration by eosinophils. In particular, some studies showed an association between a higher circulating eosinophil count and a good prognosis, as well as an association with response to neoadjuvant chemotherapy in hormone receptor-negative/HER2-positive and in triple negative breast cancer. Several mechanistic studies have also been conducted in in vivo models, but the exact mechanism by which eosinophils act in the presence of breast cancer is still unknown. Further studies on this subject are desirable, in order to understand their role at the cellular level, identify related biomarkers and/or possibly search for new therapeutic targets.

Epigenetic Regulation of Immunotherapy Response in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is defined by the absence of estrogen receptor and progesterone receptor and human epidermal growth factor receptor 2 (HER2) overexpression. This malignancy, representing 15-20% of breast cancers, is a clinical challenge due to the lack of targeted treatments, higher intrinsic aggressiveness, and worse outcomes than other breast cancer subtypes. Immune checkpoint inhibitors have shown promising efficacy for early-stage and advanced TNBC, but this seems limited to a subgroup of patients. Understanding the underlying mechanisms that determine immunotherapy efficiency is essential to identifying which TNBC patients will respond to immunotherapy-based treatments and help to develop new therapeutic strategies. Emerging evidence supports that epigenetic alterations, including aberrant chromatin architecture conformation and the modulation of gene regulatory elements, are critical mechanisms for immune escape. These alterations are particularly interesting since they can be reverted through the inhibition of epigenetic regulators. For that reason, several recent studies suggest that the combination of epigenetic drugs and immunotherapeutic agents can boost anticancer immune responses. In this review, we focused on the contribution of epigenetics to the crosstalk between immune and cancer cells, its relevance on immunotherapy response in TNBC, and the potential benefits of combined treatments.

Peripheral blood eosinophilia may be a prognostic biomarker in non-small cell lung cancer patients treated with immunotherapy

Background

Eosinophils have been traditionally associated with the initiation and propagation of inflammatory responses, particularly in allergic diseases and helminth infections. More recently, an association between eosinophils and cancer has been the focus of several studies, but controversial results have emerged. This study aims to evaluate the prognostic role of peripheral blood eosinophilia in non-small cell lung cancer (NSCLC) patients receiving immunotherapy (IO). We also evaluated the impact of peripheral eosinophilia on the occurrence of immune-related adverse effects (irAEs).

Methods

Advanced NSCLC patients under IO were included in a retrospective single-center study. Peripheral blood eosinophilia was defined by a count greater than 500/µL. Patients were analyzed for eosinophil counts, overall survival (OS), progression-free survival (PFS), overall response rate (ORR) and disease control rate (DCR).

Results

A total of 121 NSCLC patients receiving IO were included. Thirty-three (27.3%) patients presented peripheral blood eosinophilia during treatment. Patients with peripheral eosinophilia presented more frequently non-progression as best overall response to IO (83.3% vs. 58.1%, P=0.014), higher median OS (26.6 vs. 9.5 months, P=0.022) and higher median PFS (13.8 vs. 4.6 months, P=0.013). IrAEs were more common in patients with peripheral eosinophilia (66.7% vs. 36.4%, P=0.003).

Conclusions

This study suggests that peripheral blood eosinophilia may predict better outcomes in NSCLC patients receiving IO, despite being associated with an increased risk of irAEs. According to our findings eosinophils may be involved in immune response against tumor. Routine eosinophils count assessment may be an additional prognostic tool in NSCLC patients receiving IO.

The Crosstalk Between Tumor Cells and the Immune Microenvironment in Breast Cancer: Implications for Immunotherapy

Breast cancer progression is a complex process controlled by genetic and epigenetic factors that coordinate the crosstalk between tumor cells and the components of tumor microenvironment (TME). Among those, the immune cells play a dual role during cancer onset and progression, as they can protect from tumor progression by killing immunogenic neoplastic cells, but in the meanwhile can also shape tumor immunogenicity, contributing to tumor escape. The complex interplay between cancer and the immune TME influences the outcome of immunotherapy and of many other anti-cancer therapies. Herein, we present an updated view of the pro- and anti-tumor activities of the main immune cell populations present in breast TME, such as T and NK cells, myeloid cells, innate lymphoid cells, mast cells and eosinophils, and of the underlying cytokine-, cell–cell contact- and microvesicle-based mechanisms. Moreover, current and novel therapeutic options that can revert the immunosuppressive activity of breast TME will be discussed. To this end, clinical trials assessing the efficacy of CAR-T and CAR-NK cells, cancer vaccination, immunogenic cell death-inducing chemotherapy, DNA methyl transferase and histone deacetylase inhibitors, cytokines or their inhibitors and other immunotherapies in breast cancer patients will be reviewed. The knowledge of the complex interplay that elapses between tumor and immune cells, and of the experimental therapies targeting it, would help to develop new combination treatments able to overcome tumor immune evasion mechanisms and optimize clinical benefit of current immunotherapies.