Tumor immune microenvironment and response to neoadjuvant chemotherapy in hormone receptor/HER2+ early stage breast cancer

Establishing a model composed of immune-related gene-modules to predict tumor immunotherapy response

At present, tumor immunotherapy has been widely applied to treat various cancers. However, the accuracy of predicting treatment efficacy has not yet achieved a significant breakthrough. This study aimed to construct a prediction model based on the modified WGCNA algorithm to precisely judge the anti-tumor immune response. First, we used a murine colon cancer model to screen corresponding DEGs according to different groups. GSEA was used to analyze the potential mechanisms of the immune-related DEGs (irDEGs) in each group. Subsequently, the intersection of the irDEGs in every group was acquired, and 7 gene-modules were mapped. Finally, 4 gene-modules including cogenes, antiPD-1 immu-genes, chemo immu-genes and comb immu-genes, were selected for subsequent study. Furthermore, a clinical dataset of gastric cancer patients receiving immunotherapy was enrolled, and the irDEGs were identified. A total of 34 vital irDEGs were obtained from the intersections of the vital irDEGs and the four gene-modules. Next, the vital irDEGs were analyzed by the modified WGCNA algorithm, and the correlation coefficients between the 4 gene-modules and the response status to immunotherapy were calculated. Thus, a prediction model based on correlation coefficients was built, and the corresponding model scores were acquired. The AUC calculated according to the model score was 0.727, which was non-inferior to that of the ESTIMATE score and the TIDE score. Meanwhile, the AUC calculated according to the classification of the model scores was 0.705, which was non-inferior to that of the ESTIMATE classification and the TIDE classification. The prediction accuracy of the model was validated in clinical datasets of other cancers.

A review concerning the breast cancer-related tumour microenvironment

Breast cancer (BC) is currently the most common malignant tumour in women and one of the leading causes of their death around the world. New and increasingly personalised diagnostic and therapeutic tools have been introduced over the last few decades, along with significant advances regarding the study and knowledge related to BC. The tumour microenvironment (TME) refers to the tumour cell-associated cellular and molecular environment which can influence conditions affecting tumour development and progression. The TME is composed of immune cells, stromal cells, extracellular matrix (ECM) and signalling molecules secreted by these different cell types. Ever deeper understanding of TME composition changes during tumour development and progression will enable new and more innovative therapeutic strategies to become developed for targeting tumours during specific stages of its evolution. This review summarises the role of BC-related TME components and their influence on tumour progression and the development of resistance to therapy. In addition, an account on the modifications in BC-related TME components associated with therapy is given, and the completed or ongoing clinical trials related to this topic are presented.

Factors affecting heterogeneity in breast cancer microenvironment: A narrative mini review

Breast cancer (BC) heterogeneity is a key trait of BC tumors with crucial implications on tumorigenesis, diagnosis, and therapeutic modalities. It is influenced by tumor intrinsic features and by the tumor microenvironment (TME) composition of different intra-tumoral regions, which in turn affect cancer progression within patients. In this mini review, we will highlight the mechanisms that generate cancer heterogeneity in BC and how they affect the responses to cancer therapies.

Immune characteristics and clinical significance of peripheral blood lymphocytes in breast cancer

BACKGROUND

In the context of breast cancer (BC), the correlation between lymphocytes and clinical outcomes, along with treatment response, has garnered attention. Despite this, few investigations have delved into the interplay among distinct peripheral blood lymphocyte (PBL) types, immune attributes, and their clinical implications within the BC landscape.

METHODS

The primary objective of this study was to scrutinize the baseline status of PBL subsets in patients with primary BC, track their dynamic changes throughout treatment, and ascertain their interrelation with prognosis. Flow cytometry was employed to analyse PBLs from a cohort of 74 BC patients.

RESULTS

Our analysis revealed that baseline levels of Treg and PD-L1 + T cells were lower in BC patients compared to the reference values. Notably, a disparity in baseline PD-L1 + T cell levels surfaced between patients who underwent adjuvant therapy and those subjected to neoadjuvant therapy (NAT). Furthermore, a meticulous evaluation of PBL subsets before and after treatment underscored discernible alterations in 324 + T cells and CD19 + CD32 + B cells over the course of therapy. Strikingly, heightened CD4 + T cell levels at baseline were linked to enhanced event-free survival (EFS) (p = 0.02) and a robust response to chemotherapy.

CONCLUSIONS

These results indicate that PBLs may serve as a significant marker to assess the immune status of BC patients, and therapy has the potential to modify patient immune profiles. In addition, peripheral blood CD4 + T cell levels may serve as promising biomarkers for diagnosis and prognosis in future studies of BC.

Prognostic Implications of the Residual Tumor Microenvironment after Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Patients without Pathological Complete Response

With a high risk of relapse and death, and a poor or absent response to therapeutics, the triple-negative breast cancer (TNBC) subtype is particularly challenging, especially in patients who cannot achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Although the tumor microenvironment (TME) is known to influence disease progression and the effectiveness of therapeutics, its predictive and prognostic potential remains uncertain. This work aimed to define the residual TME profile after NAC of a retrospective cohort with 96 TNBC patients by immunohistochemical staining (cell markers) and chromogenic in situ hybridization (genetic markers). Kaplan-Meier curves were used to estimate the influence of the selected TME markers on five-year overall survival (OS) and relapse-free survival (RFS) probabilities. The risks of each variable being associated with relapse and death were determined through univariate and multivariate Cox analyses. We describe a unique tumor-infiltrating immune profile with high levels of lymphocytes (CD4, FOXP3) and dendritic cells (CD21, CD1a and CD83) that are valuable prognostic factors in post-NAC TNBC patients. Our study also demonstrates the value of considering not only cellular but also genetic TME markers such as MUC-1 and CXCL13 in routine clinical diagnosis to refine prognosis modelling.

Immune Response in Colorectal Carcinoma: A Review of Its Significance as a Predictive and Prognostic Biomarker

Colorectal carcinoma is a leading cause of cancer-related death worldwide. There is significant prognostic heterogeneity in stage II and III tumours, necessitating the development of new biomarkers to better identify patients at risk of disease progression. Recently, the tumour immune environment, particularly the type and quantity of T lymphocytes, has been shown to be a useful biomarker in predicting prognosis for patients with colorectal carcinoma. In this review, the significance of the immune response in colorectal carcinoma, including its influence on prognosis and response to therapy, will be detailed.