Therapies Targeting Immune Cells in Tumor Microenvironment for Non-Small Cell Lung Cancer

The role of immunotherapy in targeting tumor microenvironment in genitourinary cancers

Genitourinary (GU) cancers, including renal cell carcinoma, prostate cancer, bladder cancer, and testicular cancer, represent a significant health burden and are among the leading causes of cancer-related mortality worldwide. Despite advancements in traditional treatment modalities such as chemotherapy, radiotherapy, and surgery, the complex interplay within the tumor microenvironment (TME) poses substantial hurdles to achieving durable remission and cure. The TME, characterized by its dynamic and multifaceted nature, comprises various cell types, signaling molecules, and the extracellular matrix, all of which are instrumental in cancer progression, metastasis, and therapy resistance. Recent breakthroughs in immunotherapy (IO) have opened a new era in the management of GU cancers, offering renewed hope by leveraging the body's immune system to combat cancer more selectively and effectively. This approach, distinct from conventional therapies, aims to disrupt cancer's ability to evade immune detection through mechanisms such as checkpoint inhibition, therapeutic vaccines, and adoptive cell transfer therapies. These strategies highlight the shift towards personalized medicine, emphasizing the importance of understanding the intricate dynamics within the TME for the development of targeted treatments. This article provides an in-depth overview of the current landscape of treatment strategies for GU cancers, with a focus on IO targeting the specific cell types of TME. By exploring the roles of various cell types within the TME and their impact on cancer progression, this review aims to underscore the transformative potential of IO strategies in TME targeting, offering more effective and personalized treatment options for patients with GU cancers, thereby improving outcomes and quality of life.

Harnessing the tumor microenvironment: targeted cancer therapies through modulation of epithelial-mesenchymal transition

The tumor microenvironment (TME) is integral to cancer progression, impacting metastasis and treatment response. It consists of diverse cell types, extracellular matrix components, and signaling molecules that interact to promote tumor growth and therapeutic resistance. Elucidating the intricate interactions between cancer cells and the TME is crucial in understanding cancer progression and therapeutic challenges. A critical process induced by TME signaling is the epithelial-mesenchymal transition (EMT), wherein epithelial cells acquire mesenchymal traits, which enhance their motility and invasiveness and promote metastasis and cancer progression. By targeting various components of the TME, novel investigational strategies aim to disrupt the TME's contribution to the EMT, thereby improving treatment efficacy, addressing therapeutic resistance, and offering a nuanced approach to cancer therapy. This review scrutinizes the key players in the TME and the TME's contribution to the EMT, emphasizing avenues to therapeutically disrupt the interactions between the various TME components. Moreover, the article discusses the TME's implications for resistance mechanisms and highlights the current therapeutic strategies toward TME modulation along with potential caveats.

Establishment of potential lncRNA-related hub genes involved competitive endogenous RNA in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, the associations between lncRNA-related hub genes (LRHGs) expression and the corresponding outcomes have not been fully understood in lung adenocarcinoma (LUAD). Here, a total of 71 patients diagnosed with LUAD and 60 healthy volunteers at The First Affiliated Hospital of Huzhou University from April, 2023 to December, 2023 were enrolled in the present study. A LRHGs model was established using least absolute shrinkage and selection operator analyses of The Cancer Genome Atlas-LUAD datasets. The underlying mechanisms of the LRHGs were investigated via Gene Set Enrichment Analysis and Gene Set Variation Analysis. Additionally, the diagnostic role of serum HOXD cluster antisense RNA 2 (HOXD-AS2) was assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples were divided into high- and low-HOXD-AS2 expression groups based on the median expression. The associations between HOXD-AS2 expression and miR-4538 as well as Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels were conducted through Pearson correlation analysis. A comprehensive analysis identified 141 differentially expressed lncRNAs between 539 LUAD tissues and 59 normal samples. A prognostic marker for overall survival was established by constructing a predictive signature consisting of 9 LRHGs. Subsequently, 474 LUAD samples were categorized into a high or low-risk group based on the median of the risk score. An independent prognostic model was constructed to confirm the validity of this categorization. Further comparisons of the clinicopathological features and LRHG-related pathways were performed between the two groups. Examinations of LRHG expression in two LUAD clusters and of the association between LRHG expression and immune infiltration were also conducted. HOXD-AS2 expression was shown to be elevated in LUAD tissues compared with matched normal tissues, and the serum HOXD-AS2 level was also notably increased in LUAD samples compared with healthy controls. The results of the ROC analysis indicated that the sensitivity and specificity of HOXD-AS2 were higher than that of cytokeratin-19 fragment (CYFRA21-1), which is a serum marker for LUAD. Pearson analyses indicated that miR-4538 level was negatively associated with HOXD-AS2 expression, but CAMK2B level showed positive correlation in LUAD. The results of the present study therefore indicated that the constructed LRHG model, particularly HOXD-AS2, could independently diagnose and predict the prognosis of LUAD, which suggested the underlying mechanism of the HOXD-AS2/miR-4538/CAMK2B, and might offer efficient strategies for LUAD treatment.

Advanced tumor organoid bioprinting strategy for oncology research

Bioprinting is a groundbreaking technology that enables precise distribution of cell-containing bioinks to construct organoid models that accurately reflect the characteristics of tumors in vivo. By incorporating different types of tumor cells into the bioink, the heterogeneity of tumors can be replicated, enabling studies to simulate real-life situations closely. Precise reproduction of the arrangement and interactions of tumor cells using bioprinting methods provides a more realistic representation of the tumor microenvironment. By mimicking the complexity of the tumor microenvironment, the growth patterns and diffusion of tumors can be demonstrated. This approach can also be used to evaluate the response of tumors to drugs, including drug permeability and cytotoxicity, and other characteristics. Therefore, organoid models can provide a more accurate oncology research and treatment simulation platform. This review summarizes the latest advancements in bioprinting to construct tumor organoid models. First, we describe the bioink used for tumor organoid model construction, followed by an introduction to various bioprinting methods for tumor model formation. Subsequently, we provide an overview of existing bioprinted tumor organoid models.

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.

Lipid alterations play a role in the integration of PD-1/PD-L1 inhibitors and anlotinib for the treatment of advanced non-small-cell lung cancer

BACKGROUND

Studies have shown that integrating anlotinib with programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors enhances survival rates among progressive non-small-cell lung cancer (NSCLC) patients lacking driver mutations. However, not all individuals experience clinical benefits from this therapy. As a result, it is critical to investigate the factors that contribute to the inconsistent response of patients. Recent investigations have emphasized the importance of lipid metabolic reprogramming in the development and progression of NSCLC.

METHODS

The objective of this investigation was to examine the correlation between lipid variations and observed treatment outcomes in advanced NSCLC patients who were administered PD-1/PD-L1 inhibitors alongside anlotinib. A cohort composed of 30 individuals diagnosed with advanced NSCLC without any driver mutations was divided into three distinct groups based on the clinical response to the combination treatment, namely, a group exhibiting partial responses, a group manifesting progressive disease, and a group demonstrating stable disease. The lipid composition of patients in these groups was assessed both before and after treatment.

RESULTS

Significant differences in lipid composition among the three groups were observed. Further analysis revealed 19 differential lipids, including 2 phosphatidylglycerols and 17 phosphoinositides.

CONCLUSION

This preliminary study aimed to explore the specific impact of anlotinib in combination with PD-1/PD-L1 inhibitors on lipid metabolism in patients with advanced NSCLC. By investigating the effects of using both anlotinib and PD-1/PD-L1 inhibitors, this study enhances our understanding of lipid metabolism in lung cancer treatment. The findings from this research provide valuable insights into potential therapeutic approaches and the identification of new therapeutic biomarkers.