A risk scoring system based on tumor microenvironment cells to predict prognosis and immune activity in triple-negative breast cancer

Subclassification of B-acute lymphoblastic leukemia according to age, immunophenotype and microenvironment, predicts MRD risk in Mexican children from vulnerable regions

Introduction

The decisive key to disease-free survival in B-cell precursor acute lymphoblastic leukemia in children, is the combination of diagnostic timeliness and treatment efficacy, guided by accurate patient risk stratification. Implementation of standardized and high-precision diagnostic/prognostic systems is particularly important in the most marginalized geographic areas in Mexico, where high numbers of the pediatric population resides and the highest relapse and early death rates due to acute leukemias are recorded even in those cases diagnosed as standard risk.

Methods

By using a multidimensional and integrated analysis of the immunophenotype of leukemic cells, the immunological context and the tumor microenvironment, this study aim to capture the snapshot of acute leukemia at disease debut of a cohort of Mexican children from vulnerable regions in Puebla, Oaxaca and Tlaxcala and its potential use in risk stratification.

Results and discussion

Our findings highlight the existence of a distinct profile of ProB-ALL in children older than 10 years, which is associated with a six-fold increase in the risk of developing measurable residual disease (MRD). Along with the absence of CD34+ seminal cells for normal hematopoiesis, this ProB-ALL subtype exhibited several characteristics related to poor prognosis, including the high expression level of myeloid lineage markers such as MPO and CD33, as well as upregulation of CD19, CD34, CD24, CD20 and nuTdT. In contrast, it showed a trend towards decreased expression of CD9, CD81, CD123, CD13, CD15 and CD21. Of note, the mesenchymal stromal cell compartment constituting their leukemic niche in the bone marrow, displayed characteristics of potential suppressive microenvironment, such as the expression of Gal9 and IDO1, and the absence of the chemokine CXCL11. Accordingly, adaptive immunity components were poorly represented. Taken together, our results suggest, for the first time, that a biologically distinct subtype of ProB-ALL emerges in vulnerable adolescents, with a high risk of developing MRD. Rigorous research on potential enhancing factors, environmental or lifestyle, is crucial for its detection and prevention. The use of the reported profile for early risk stratification is suggested.

GPR81-mediated reprogramming of glucose metabolism contributes to the immune landscape in breast cancer

BACKGROUND

Local tumor microenvironment (TME) plays a crucial role in immunotherapy for breast cancer (BC). Whereas, the molecular mechanism responsible for the crosstalk between BC cells and surrounding immune cells remains unclear. The present study aimed to determine the interplay between GPR81-mediated glucometabolic reprogramming of BC and the immune landscape in TME.

MATERIALS AND METHODS

Immunohistochemistry (IHC) assay was first performed to evaluate the association between GPR81 and the immune landscape. Then, several stable BC cell lines with down-regulated GPR81 expression were established to directly identify the role of GPR81 in glucometabolic reprogramming, and western blotting assay was used to detect the underlying molecular mechanism. Finally, a transwell co-culture system confirmed the crosstalk between glucometabolic regulation mediated by GPR81 in BC and induced immune attenuation.

RESULTS

IHC analysis demonstrated that the representation of infiltrating CD8⁺ T cells and FOXP3⁺ T cells were dramatically higher in BC with a triple negative (TN) subtype in comparison with that with a non-TN subtype (P < 0.001). Additionally, the ratio of infiltrating CD8⁺ to FOXP3⁺ T cells was significantly negatively associated with GPR81 expression in BC with a TN subtype (P < 0.001). Furthermore, GPR81 was found to be substantially correlated with the glycolytic capability (P < 0.001) of BC cells depending on a Hippo-YAP signaling pathway (P < 0.001). In the transwell co-culture system, GPR81-mediated reprogramming of glucose metabolism in BC significantly contributed to a decreased proportion of CD8⁺ T (P < 0.001) and an increased percentage of FOXP3⁺ T (P < 0.001) in the co-cultured lymphocytes.

CONCLUSION

Glucometabolic reprogramming through a GPR81-mediated Hippo-YAP signaling pathway was responsible for the distinct immune landscape in BC. GPR81 was a potential biomarker to stratify patients before immunotherapy to improve BC's clinical prospect.

Systematic evaluation of tumor microenvironment and construction of a machine learning model to predict prognosis and immunotherapy efficacy in triple-negative breast cancer based on data mining and sequencing validation

Background: The role of the tumor microenvironment (TME) in predicting prognosis and therapeutic efficacy has been demonstrated. Nonetheless, no systematic studies have focused on TME patterns or their function in the effectiveness of immunotherapy in triple-negative breast cancer.

Methods: We comprehensively estimated the TME infiltration patterns of 491 TNBC patients from four independent cohorts, and three cohorts that received immunotherapy were used for validation. The TME subtypes were comprehensively evaluated based on immune cell infiltration levels in TNBC, and the TRG score was identified and systematically correlated with representative tumor characteristics. We sequenced 80 TNBC samples as an external validation cohort to make our conclusions more convincing.

Results: Two TME subtypes were identified and were highly correlated with immune cell infiltration levels and immune-related pathways. More representative TME-related gene (TRG) scores calculated by machine learning could reflect the fundamental characteristics of TME subtypes and predict the efficacy of immunotherapy and the prognosis of TNBC patients. A low TRG score, characterized by activation of immunity and ferroptosis, indicated an activated TME phenotype and better prognosis. A low TRG score showed a better response to immunotherapy in TNBC by TIDE (Tumor Immune Dysfunction and Exclusion) analysis and sensitivity to multiple drugs in GDSC (Genomics of Drug Sensitivity in Cancer) analysis and a significant therapeutic advantage in patients in the three immunotherapy cohorts.

Conclusion: TME subtypes played an essential role in assessing the diversity and complexity of the TME in TNBC. The TRG score could be used to evaluate the TME of an individual tumor to enhance our understanding of the TME and guide more effective immunotherapy strategies.

Perspectives for 3D-Bioprinting in Modeling of Tumor Immune Evasion

In a living organism, cancer cells function in a specific microenvironment, where they exchange numerous physical and biochemical cues with other cells and the surrounding extracellular matrix (ECM). Immune evasion is a clinically relevant phenomenon, in which cancer cells are able to direct this interchange of signals against the immune effector cells and to generate an immunosuppressive environment favoring their own survival. A proper understanding of this phenomenon is substantial for generating more successful anticancer therapies. However, classical cell culture systems are unable to sufficiently recapture the dynamic nature and complexity of the tumor microenvironment (TME) to be of satisfactory use for comprehensive studies on mechanisms of tumor immune evasion. In turn, 3D-bioprinting is a rapidly evolving manufacture technique, in which it is possible to generate finely detailed structures comprised of multiple cell types and biomaterials serving as ECM-analogues. In this review, we focus on currently used 3D-bioprinting techniques, their applications in the TME research, and potential uses of 3D-bioprinting in modeling of tumor immune evasion and response to immunotherapies.