Therapeutic Targeting of Cancer-Associated Fibroblasts in the Non-Small Cell Lung Cancer Tumor Microenvironment

IL-17A-induced cancer-associated fibroblasts releases CXCL12 to promote lung adenocarcinoma progression via Wnt/β-Catenin signaling pathway

BACKGROUND

Cancer-associated fibroblasts (CAFs) and their secretion, C-X-C motif chemokine ligand 12 (CXCL12), play an important role in the development of lung adenocarcinoma (LUAD). Interleukin 17A (IL-17A) is also crucial in regulating tumor progression. Herein, we explored the specific relationships between these two factors and their mechanisms in the progression of LUAD.

METHODS

Immunohistochemistry was utilized to assess the differential expression levels of IL-17A and CXCL12 in tumor versus normal tissues of LUAD patients, followed by gene correlation analysis. Cell counting kit-8 (CCK8), wound-healing and transwell assays were performed to investigate the effect of IL-17A on the function of LUAD cells. qPCR, immunofluorescence, immunohistochemistry and western blot analyses were conducted to elucidate the potential mechanism by which IL-17A facilitates the development of LUAD via CXCL12. Male BALB-C nude mice were used to explore the role of IL-17A in subcutaneous LUAD mouse models.

RESULTS

Elevated expression levels of IL-17A and CXCL12 were observed in LUAD tissues, exhibiting a positive correlation. Further studies revealed that IL-17A could stimulate CAFs to enhance the release of CXCL12, thereby facilitating the growth, proliferation, and metastasis of LUAD. The binding of CXCL12 to its specific receptor influences the activation of the Wnt/β-Catenin pathway, which in turn affects the progression of LUAD. In vivo experiments have demonstrated that IL-17A enhances the growth of LUAD tumors by facilitating the secretion of CXCL12. Conversely, inhibiting CXCL12 has been demonstrated to impede tumor growth.

CONCLUSIONS

We discovered that IL-17A promotes the release of CAFs-derived CXCL12, which in turn facilitates the development of LUAD via the Wnt/β-Catenin signaling pathway.

Biophysical perspectives to understanding cancer-associated fibroblasts

The understanding of cancer has evolved significantly, with the tumor microenvironment (TME) now recognized as a critical factor influencing the onset and progression of the disease. This broader perspective challenges the traditional view that cancer is primarily caused by mutations, instead emphasizing the dynamic interaction between different cell types and physicochemical factors within the TME. Among these factors, cancer-associated fibroblasts (CAFs) command attention for their profound influence on tumor behavior and patient prognoses. Despite their recognized importance, the biophysical and mechanical interactions of CAFs within the TME remain elusive. This review examines the distinctive physical characteristics of CAFs, their morphological attributes, and mechanical interactions within the TME. We discuss the impact of mechanotransduction on CAF function and highlight how these cells communicate mechanically with neighboring cancer cells, thereby shaping the path of tumor development and progression. By concentrating on the biomechanical regulation of CAFs, this review aims to deepen our understanding of their role in the TME and to illuminate new biomechanical-based therapeutic strategies.

AI-guided histopathology predicts brain metastasis in lung cancer patients

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Vascularized tissue on mesh-assisted platform (VT-MAP): a novel approach for diverse organoid size culture and tailored cancer drug response analysis

This study presents the vascularized tissue on mesh-assisted platform (VT-MAP), a novel microfluidic in vitro model that uses an open microfluidic principle for cultivating vascularized organoids. Addressing the gap in 3D high-throughput platforms for drug response analysis, the VT-MAP can host tumor clusters of various sizes, allowing for precise, size-dependent drug interaction assessments. Key features include capability for forming versatile co-culture conditions (EC, fibroblasts and colon cancer organoids) that enhance tumor organoid viability and a perfusable vessel network that ensures efficient drug delivery and maintenance of organoid health. The VT-MAP enables the culture and analysis of organoids across a diverse size spectrum, from tens of microns to several millimeters. The VT-MAP addresses the inconsistencies in traditional organoid testing related to organoid size, which significantly impacts drug response and viability. Its ability to handle various organoid sizes leads to results that more accurately reflect patient-derived xenograft (PDX) models and differ markedly from traditional in vitro well plate-based methods. We introduce a novel image analysis algorithm that allows for quantitative analysis of organoid size-dependent drug responses, marking a significant step forward in replicating PDX models. The PDX sample from a positive responder exhibited a significant reduction in cell viability across all organoid sizes when exposed to chemotherapeutic agents (5-FU, oxaliplatin, and irinotecan), as expected for cytotoxic drugs. In sharp contrast, PDX samples of a negative responder showed little to no change in viability in smaller clusters and only a slight reduction in larger clusters. This differential response, accurately replicated in the VT-MAP, underscores its ability to generate data that align with PDX models and in vivo findings. Its capacity to handle various organoid sizes leads to results that more accurately reflect PDX models and differ markedly from traditional in vitro methods. The platform's distinct advantage lies in demonstrating how organoid size can critically influence drug response, revealing insights into cancer biology previously unattainable with conventional techniques.

Comprehensive Analysis of Lung Adenocarcinoma and Brain Metastasis through Integrated Single-Cell Transcriptomics

Lung adenocarcinoma (LUAD) is a highly prevalent and lethal form of lung cancer, comprising approximately half of all cases. It is often diagnosed at advanced stages with brain metastasis (BM), resulting in high mortality rates. Current BM management involves complex interventions and conventional therapies that offer limited survival benefits with neurotoxic side effects. The tumor microenvironment (TME) is a complex system where cancer cells interact with various elements, significantly influencing tumor behavior. Immunotherapies, particularly immune checkpoint inhibitors, target the TME for cancer treatment. Despite their effectiveness, it is crucial to understand metastatic lung cancer and the specific characteristics of the TME, including cell-cell communication mechanisms, to refine treatments. Herein, we investigated the tumor microenvironment of brain metastasis from lung adenocarcinoma (LUAD-BM) and primary tumors across various stages (I, II, III, and IV) using single-cell RNA sequencing (scRNA-seq) from publicly available datasets. Our analysis included exploring the immune and non-immune cell composition and the expression profiles and functions of cell type-specific genes, and investigating the interactions between different cells within the TME. Our results showed that T cells constitute the majority of immune cells present in primary tumors, whereas microglia represent the most dominant immune cell type in BM. Interestingly, microglia exhibit a significant increase in the COX pathway. Moreover, we have shown that microglia primarily interact with oligodendrocytes and endothelial cells. One significant interaction was identified between DLL4 and NOTCH4, which demonstrated a relevant association between endothelial cells and microglia and between microglia and oligodendrocytes. Finally, we observed that several genes within the HLA complex are suppressed in BM tissue. Our study reveals the complex molecular and cellular dynamics of BM-LUAD, providing a path for improved patient outcomes with personalized treatments and immunotherapies.

Boosting immune responses in lung tumor immune microenvironment: A comprehensive review of strategies and adjuvants

The immune system has a substantial impact on the growth and expansion of lung malignancies. Immune cells are encompassed by a stroma comprising an extracellular matrix (ECM) and different cells like stromal cells, which are known as the tumor immune microenvironment (TIME). TME is marked by the presence of immunosuppressive factors, which inhibit the function of immune cells and expand tumor growth. In recent years, numerous strategies and adjuvants have been developed to extend immune responses in the TIME, to improve the efficacy of immunotherapy. In this comprehensive review, we outline the present knowledge of immune evasion mechanisms in lung TIME, explain the biology of immune cells and diverse effectors on these components, and discuss various approaches for overcoming suppressive barriers. We highlight the potential of novel adjuvants, including toll-like receptor (TLR) agonists, cytokines, phytochemicals, nanocarriers, and oncolytic viruses, for enhancing immune responses in the TME. Ultimately, we provide a summary of ongoing clinical trials investigating these strategies and adjuvants in lung cancer patients. This review also provides a broad overview of the current state-of-the-art in boosting immune responses in the TIME and highlights the potential of these approaches for improving outcomes in lung cancer patients.

Tumor Microenvironment Heterogeneity, Potential Therapeutic Avenues, and Emerging Therapies

OBJECTIVE

This review describes the comprehensive portrait of tumor microenvironment (TME). Additionally, we provided a panoramic perspective on the transformation and functions of the diverse constituents in TME, and the underlying mechanisms of drug resistance, beginning with the immune cells and metabolic dynamics within TME. Lastly, we summarized the most auspicious potential therapeutic strategies.

RESULTS

TME is a unique realm crafted by malignant cells to withstand the onslaught of endogenous and exogenous therapies. Recent research has revealed many small-molecule immunotherapies exhibiting auspicious outcomes in preclinical investigations. Furthermore, some pro-immune mechanisms have emerged as a potential avenue. With the advent of nanosystems and precision targeting, targeted therapy has now transcended the "comfort zone" erected by cancer cells within TME.

CONCLUSION

The ceaseless metamorphosis of TME fosters the intransigent resilience and proliferation of tumors. However, existing therapies have yet to surmount the formidable obstacles posed by TME. Therefore, scientists should investigate potential avenues for therapeutic intervention and design innovative pharmacological and clinical technologies.

Exosomal ITGB6 from dormant lung adenocarcinoma cells activates cancer-associated fibroblasts by KLF10 positive feedback loop and the TGF-β pathway

Background

Dormant cancer cells are commonly known to play a pivotal role in cancer recurrence and metastasis. However, the mechanism of tumor dormancy and recurrence remains largely unknown. This study aimed to investigate the mechanism by which exosomes derived from dormant lung adenocarcinoma (LUAD) cells activate cancer-associated fibroblasts (CAFs) to reconstruct the extracellular matrix (ECM), providing a novel idea for decoding the mechanism of tumor dormancy.

Methods

In this study, high-dose cisplatin was used to induce the dormant LUAD cells. Exosomes were extracted from the culture supernatant of normal and dormant cancer cells. The effects of selected exosomal proteins on the fibroblasts were evaluated. RNA-seq for fibroblasts and exosomal proteomics for normal and dormant cancer cells were used to identify and verify the mechanism of activating fibroblasts.

Results

We demonstrated that exosomes derived from dormant A549 cells could be taken by fibroblasts. Exosomal ITGB6 transferred into fibroblasts induced the activation of CAFs by activating the KLF10 positive feedback loop and transforming growth factor β (TGF-β) pathway. High ITGB6 expression was associated with activation of the TGF-β pathway and ECM remodeling.

Conclusions

In all, we demonstrated that CAFs were activated by exosomes from dormant lung cancer cells and reconstruct ECM. ITGB6 may be a critical molecule for activating the TGF-β pathway and remodeling ECM.

Cell Proteomic Footprinting: Advances in the Quality of Cellular and Cell-Derived Cancer Vaccines

In omics sciences, many compounds are measured simultaneously in a sample in a single run. Such analytical performance opens up prospects for improving cellular cancer vaccines and other cell-based immunotherapeutics. This article provides an overview of proteomics technology, known as cell proteomic footprinting. The molecular phenotype of cells is highly variable, and their antigenic profile is affected by many factors, including cell isolation from the tissue, cell cultivation conditions, and storage procedures. This makes the therapeutic properties of cells, including those used in vaccines, unpredictable. Cell proteomic footprinting makes it possible to obtain controlled cell products. Namely, this technology facilitates the cell authentication and quality control of cells regarding their molecular phenotype, which is directly connected with the antigenic properties of cell products. Protocols for cell proteomic footprinting with their crucial moments, footprint processing, and recommendations for the implementation of this technology are described in this paper. The provided footprints in this paper and program source code for their processing contribute to the fast implementation of this technology in the development and manufacturing of cell-based immunotherapeutics.