FOXP3+ T cells in uterine sarcomas are associated with favorable prognosis, low extracellular matrix expression and reduced YAP activation

What is the relevance of FoxP3 in the tumor microenvironment and cancer outcomes?

INTRODUCTION

Forkhead box P3 (FoxP3) transcription factor plays critical roles in controlling immune responses and cancer progression in different cancers. FoxP3 expression within the tumor microenvironment (TME) may influence clinical outcomes negatively or positively, and it could play dual roles in cancer, either by promoting or inhibiting tumor development and progression. Some studies reported that high levels of FoxP3 could be associated with tumor progression and worse prognosis, while others reported contradictory results.

AREAS COVERED

In this special report, we present a brief account on the role and function of FoxP3 in the TME, and its contribution to the clinical outcomes of cancer patients. Importantly, we give insights on the potential factors that could contribute to different clinical outcomes in cancer patients.

EXPERT OPINION

Different studies showed that FoxP3 expression can be associated with bad prognoses in cancer patients. However, FoxP3 could have opposing roles by enhancing cancer progression or regression. Location and expression of FoxP3 in T cells or tumor cells can have different impacts on cancer prognoses. Different factors should be considered to establish FoxP3 as a more robust prognostic biomarker and a potential therapeutic target for enhancing anti-tumor immunity and improving clinical outcomes of cancer patients.

MMP14 expression and collagen remodelling support uterine leiomyosarcoma aggressiveness

Fibrillar collagen deposition, stiffness and downstream signalling support the development of leiomyomas (LMs), common benign mesenchymal tumours of the uterus, and are associated with aggressiveness in multiple carcinomas. Compared with epithelial carcinomas, however, the impact of fibrillar collagens on malignant mesenchymal tumours, including uterine leiomyosarcoma (uLMS), remains elusive. In this study, we analyse the network morphology and density of fibrillar collagens combined with the gene expression within uLMS, LM and normal myometrium (MM). We find that, in contrast to LM, uLMS tumours present low collagen density and increased expression of collagen-remodelling genes, features associated with tumour aggressiveness. Using collagen-based 3D matrices, we show that matrix metalloproteinase-14 (MMP14), a central protein with collagen-remodelling functions that is particularly overexpressed in uLMS, supports uLMS cell proliferation. In addition, we find that, unlike MM and LM cells, uLMS proliferation and migration are less sensitive to changes in collagen substrate stiffness. We demonstrate that uLMS cell growth in low-stiffness substrates is sustained by an enhanced basal yes-associated protein 1 (YAP) activity. Altogether, our results indicate that uLMS cells acquire increased collagen remodelling capabilities and are adapted to grow and migrate in low collagen and soft microenvironments. These results further suggest that matrix remodelling and YAP are potential therapeutic targets for this deadly disease.

Constructing a Prognostic Model of Uterine Corpus Endometrial Carcinoma and Predicting Drug-Sensitivity Responses Using Programmed Cell Death-Related Pathways

Background: Uterine Corpus Endometrial Carcinoma (UCEC) is the most common type of cancer that develops in the uterus, specifically originating from the endometrium, the inner lining of the uterus. Programmed cell death (PCD) is a highly regulated process that eliminates damaged, aged, or unwanted cells in the body. Dysregulation of PCD pathways can contribute to the formation and progression of various cancers, including UCEC. Methods: Fourteen PCD pathways (autophagy-dependent cell death, alkaliptosis, apoptosis, cuproptosis, entotic cell death, ferroptosis, immunogenic cell death, lysosome-dependent cell death, MPT-driven necrosis, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were involved in building a prognostic signature. The model was trained and tested using data from the TCGA-UCEC and validated with the GSE119041 dataset. Results: A 12-gene PCD signature (DRAM1, ELAPOR1, MAPT, TRIM58, UCHL1, CDKN2A, CYFIP2, AKT2, LINC00618, TTPA, TRIM46, and NOS2) was established and validated in an independent dataset. UCEC patients with a high PCD score (PCDS) exhibited worse prognosis. Furthermore, PCDS was found to be associated with immune related cells and key tumor microenvironment components through multiple methods. It was observed that UCEC patients with a high PCD score may not benefit from immunotherapy, but some chemo drugs like Bortezomib may be useful. Conclusion: In conclusion, a novel PCD model was established by comprehensively analyzing diverse cell death patterns. This model accurately predicts the clinical prognosis and drug sensitivity of UCEC. The findings suggest that the PCD signature can serve as a valuable tool in assessing prognosis and guiding treatment decisions for UCEC patients.

Matrix stiffness affects tumor-associated macrophage functional polarization and its potential in tumor therapy

The extracellular matrix (ECM) plays critical roles in cytoskeletal support, biomechanical transduction and biochemical signal transformation. Tumor-associated macrophage (TAM) function is regulated by matrix stiffness in solid tumors and is often associated with poor prognosis. ECM stiffness-induced mechanical cues can activate cell membrane mechanoreceptors and corresponding mechanotransducers in the cytoplasm, modulating the phenotype of TAMs. Currently, tuning TAM polarization through matrix stiffness-induced mechanical stimulation has received increasing attention, whereas its effect on TAM fate has rarely been summarized. A better understanding of the relationship between matrix stiffness and macrophage function will contribute to the development of new strategies for cancer therapy. In this review, we first introduced the overall relationship between macrophage polarization and matrix stiffness, analyzed the changes in mechanoreceptors and mechanotransducers mediated by matrix stiffness on macrophage function and tumor progression, and finally summarized the effects of targeting ECM stiffness on tumor prognosis to provide insight into this new field.

Molecular characterization of ferroptosis in soft tissue sarcoma constructs a prognostic and immunotherapeutic signature through experimental and bioinformatics analyses

Ferroptosis regulators have been found to affect tumor progression. However, studies focusing on ferroptosis and soft tissue sarcoma (STS) are rare. Somatic mutation, copy number variation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, consensus clustering, differentially expressed genes analysis (DEGs), principal component analysis (PCA) and gene set enrichment analysis (GSEA) were used to identify and explore different ferroptosis modifications in STS. A nomogram was constructed to predict the prognosis of STS. Moreover, three immunotherapy datasets were used to assess the Fescore. Western blotting, siRNA transfection, EdU assay and reactive oxygen species (ROS) measurement were performed. 16 prognostic ferroptosis regulators were screened and significant differences were observed in somatic mutation, copy number variation (CNV) and RT-qPCR among these ferroptosis regulators. 2 different ferroptosis modification patterns were found (Fe cluster A and B). Fe cluster A with higher Fescore was correlated with p53 pathway and had better prognosis of STS (p = 0.002) while Fe cluster B with lower Fescore was correlated with angiogenesis and MYC pathway and showed a poorer outcome. Besides, the nomogram effectively predicted the outcome of STS and the Fescore could also well predict the prognosis of other 16 tumors and immunotherapy response. Downregulation of LOX also inhibited growth and increased ROS production in sarcoma cells. The molecular characterization of ferroptosis regulators in STS was explored and an Fescore was constructed. The Fescore quantified ferroptosis modification in STS patients and effectively predicted the prognosis of a variety of tumors, providing novel insights for precision medicine.

The extracellular matrix - immune microenvironment crosstalk in cancer therapy: Challenges and opportunities

Targeting the tumour immune microenvironment (TIME) by cancer immunotherapy has led to improved patient outcomes. However, response to these treatments is heterogeneous and cancer-type dependant. The therapeutic activity of classical cancer therapies such as chemotherapy, radiotherapy, and surgical oncology is modulated by alterations of the TIME. A major regulator of immune cell function and resistance to both immune and classical therapies is the extracellular matrix (ECM). Concurrently, cancer therapies reshape the TIME as well as the ECM, causing both pro- and anti-tumour responses. Accordingly, the TIME-ECM crosstalk presents attractive opportunities to improve therapy outcomes. Here, we review the molecular crosstalk between the TIME and the ECM in cancer and its implications in cancer progression and clinical intervention. Additionally, we discuss examples and future directions of ECM and TIME co-targeting in combination with oncological therapies including surgery, chemotherapy, and radiotherapy.

A prognostic model and immune regulation analysis of uterine corpus endometrial carcinoma based on cellular senescence

Background

This study aimed to explore the clinical significance of cellular senescence in uterine corpus endometrial carcinoma (UCEC).

Methods

Cluster analysis was performed on GEO data and TCGA data based on cellular senescence related genes, and then performed subtype analysis on differentially expressed genes between subtypes. The prognostic model was constructed using Lasso regression. Survival analysis, microenvironment analysis, immune analysis, mutation analysis, and drug susceptibility analysis were performed to evaluate the practical relevance. Ultimately, a clinical nomogram was constructed and cellular senescence-related genes expression was investigated by qRT-PCR.

Results

We ultimately identified two subtypes. The prognostic model divides patients into high-risk and low-risk groups. There were notable discrepancies in prognosis, tumor microenvironment, immunity, and mutation between the two subtypes and groups. There was a notable connection between drug-sensitive and risk scores. The nomogram has good calibration with AUC values between 0.75-0.8. In addition, cellular senescence-related genes expression was investigated qRT-PCR.

Conclusion

Our model and nomogram may effectively forecast patient prognosis and serve as a reference for patient management.