Neutrophils correlate with hypoxia microenvironment and promote progression of non-small-cell lung cancer

3D cell culture models in research: applications to lung cancer pharmacology

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, necessitating innovative research methodologies to improve treatment outcomes and develop novel strategies. The advent of three-dimensional (3D) cell cultures has marked a significant advancement in lung cancer research, offering a more physiologically relevant model compared to traditional two-dimensional (2D) cultures. This review elucidates the various types of 3D cell culture models currently used in lung cancer pharmacology, including spheroids, organoids and engineered tissue models, having pivotal roles in enhancing our understanding of lung cancer biology, facilitating drug development, and advancing precision medicine. 3D cell culture systems mimic the complex spatial architecture and microenvironment of lung tumours, providing critical insights into the cellular and molecular mechanisms of tumour progression, metastasis and drug responses. Spheroids, derived from commercialized cell lines, effectively model the tumour microenvironment (TME), including the formation of hypoxic and nutrient gradients, crucial for evaluating the penetration and efficacy of anti-cancer therapeutics. Organoids and tumouroids, derived from primary tissues, recapitulate the heterogeneity of lung cancers and are instrumental in personalized medicine approaches, supporting the simulation of in vivo pharmacological responses in a patient-specific context. Moreover, these models have been co-cultured with various cell types and biomimicry extracellular matrix (ECM) components to further recapitulate the heterotypic cell-cell and cell-ECM interactions present within the lung TME. 3D cultures have been significantly contributing to the identification of novel therapeutic targets and the understanding of resistance mechanisms against conventional therapies. Therefore, this review summarizes the latest findings in drug research involving lung cancer 3D models, together with the common laboratory-based assays used to study drug effects. Additionally, the integration of 3D cell cultures into lung cancer drug development workflows and precision medicine is discussed. This integration is pivotal in accelerating the translation of laboratory findings into clinical applications, thereby advancing the landscape of lung cancer treatment. By closely mirroring human lung tumours, these models not only enhance our understanding of the disease but also pave the way for the development of more effective and personalized therapeutic strategies.

Tertiary lymphoid structure-related immune infiltrates in NSCLC tumor lesions correlate with low tumor-reactivity of TIL products

Adoptive transfer of tumor infiltrating lymphocytes (TIL therapy) has proven highly effective for treating solid cancers, including non-small cell lung cancer (NSCLC). However, not all patients benefit from this therapy for yet unknown reasons. Defining markers that correlate with high tumor-reactivity of the autologous TIL products is thus key for achieving better tailored immunotherapies. We questioned whether the composition of immune cell infiltrates correlated with the tumor-reactivity of expanded TIL products. Unbiased flow cytometry analysis of immune cell infiltrates of 26 early-stage and 20 late-stage NSCLC tumor lesions was used for correlations with the T cell differentiation and activation status, and with the expansion rate and anti-tumor response of generated TIL products. The composition of tumor immune infiltrates was highly variable between patients. Spearman's Rank Correlation revealed that high B cell infiltration negatively correlated with the tumor-reactivity of the patient's expanded TIL products, as defined by cytokine production upon exposure to autologous tumor digest. In-depth analysis revealed that tumor lesions with high B cell infiltrates contained tertiary lymphoid structure (TLS)-related immune infiltrates, including BCL6+ antibody-secreting B cells, IgD+BCL6+ B cells and CXCR5+BLC6+ CD4+ T cells, and higher percentages of naïve CD8+ T cells. In conclusion, the composition of immune cell infiltrates in NSCLC tumors associates with the functionality of the expanded TIL product. Our findings may thus help improve patient selection for TIL therapy.

Construction of a TAN-associated risk score model with integrated multi-omics data analysis and clinical validation in gastric cancer

AIMS

An increasing number of studies have highlighted the biological significance of neutrophil activation and polarization in tumor progression. However, the characterization of tumor-associated neutrophils (TANs) is inadequately investigated.

MATERIALS AND METHODS

Patients' expression profiles were obtained from TCGA, GEO, and IMvigor210 databases. Six algorithms were used to assess immune cell infiltration. RNA sequencing was conducted to evaluate the differentially expressed genes between induced N1- and N2-like neutrophils. A TAN-associated risk score (TRS) model was established using a combination of weighted gene co-expression network analysis (WGCNA) and RNA-seq data and further assessed in pan-cancer. A clinical cohort of 117 GC patients was enrolled to assess the role of TANs in GC via immunohistochemistry (IHC).

KEY FINDINGS

A TRS signature was built with 10 TAN-related genes (TRGs) and most TRGs were highly abundant in the TANs of the GC microenvironment. The TRS model could accurately predict patients' prognosis, as well as their responses to chemotherapy and immunotherapy. The TRS was positively correlated with pro-tumor immune cells and exhibited negative relationship with anti-tumor immune cells. Additional functional analyses revealed that the signature was positively related to pro-tumor and immunosuppression pathways, such as the hypoxia pathway, across pan-cancer. Furthermore, our clinical cohort demonstrated TANs as an independent prognostic factor for GC patients.

SIGNIFICANCE

This study constructed and confirmed the value of a novel TRS model for prognostic prediction of GC and pan-cancer. Further evaluation of TRS and TANs will help strengthen the understanding of the tumor microenvironment and guide more effective therapeutic strategies.

Neutrophil in the suppressed immune microenvironment: Critical prognostic factor for lung adenocarcinoma patients with KEAP1 mutation

Purpose

It is still unclear whether KEAP1 mutation is detrimental to immunotherapy of lung adenocarcinoma (LUAD) patients, we try to analyse the exact changes in the TME in LUAD patients with KEAP1 mutations and to identify key factors influencing prognosis.

Experimental design

A total of 1,029 patients with lung squamous carcinoma (LUSC) or LUAD with data obtained from The Cancer Genome Atlas were included in this study. The TME and OS of patients with LUAD stratified by mutant versus wild-type KEAP1 status were comprehensively measured. Moreover, we classified LUAD patients with KEAP1 mutations into three subtypes, by unsupervised consensus clustering. We further analysed the TME, OS, commutated genes and metabolic pathways of different subgroups. A total of 40 LUAD patients underwent immunotherapy were collected and classified into mutant KEAP1 group and wild-type KEAP1 group. We also conducted immunohistochemical staining in KEAP1-MT groups.

Result

Suppressed TME was observed not only in LUAD patients but also in LUSC patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than wild-type KEAP1. Unsupervised consensus clustering analysis suggested that the three subtypes of patients exhibited different densities of neutrophil infiltration and had different OS results: cluster 2 patients had significantly higher levels of neutrophils had significantly worse prognoses than those of patients in clusters 1 and 3 and patients with wild-type KEAP1. Univariate and multivariate Cox analyses proved that a high density of neutrophils was significantly associated with worse OS and immunohistochemical staining proved that shorter PFS showed high density of neutrophils.

Conclusion

KEAP1 mutation significantly suppresses the tumour immune microenvironment in LUAD patients. LUAD patients with mutant KEAP1 underwent immunotherapy had worse PFS than with wild-type KEAP1. Neutrophils may play an important role in the prognosis of LUAD patients with KEAP1 mutations and may provide a promising therapeutic target.

Hyaluronic Acid Interacting Molecules Mediated Crosstalk between Cancer Cells and Microenvironment from Primary Tumour to Distant Metastasis

Hyaluronic acid (HA) is a prominent component of the extracellular matrix, and its interactions with HA-interacting molecules (HAIMs) play a critical role in cancer development and disease progression. This review explores the multifaceted role of HAIMs in the context of cancer, focusing on their influence on disease progression by dissecting relevant cellular and molecular mechanisms in tumour cells and the tumour microenvironment. Cancer progression can be profoundly affected by the interactions between HA and HAIMs. They modulate critical processes such as cell adhesion, migration, invasion, and proliferation. The TME serves as a dynamic platform in which HAIMs contribute to the formation of a unique niche. The resulting changes in HA composition profoundly influence the biophysical properties of the TME. These modifications in the TME, in conjunction with HAIMs, impact angiogenesis, immune cell recruitment, and immune evasion. Therefore, understanding the intricate interplay between HAIMs and HA within the cancer context is essential for developing novel therapeutic strategies. Targeting these interactions offers promising avenues for cancer treatment, as they hold the potential to disrupt critical aspects of disease progression and the TME. Further research in this field is imperative for advancing our knowledge and the treatment of cancer.

Identification of hypoxia-related gene signatures based on multi-omics analysis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and one of the malignancies with the highest incidence rate and mortality worldwide. Hypoxia is a typical feature of tumour microenvironment (TME), which affects the progression of LUAD from multiple molecular levels. However, the underlying molecular mechanisms behind LUAD hypoxia are not fully understood. In this study, we estimated the level of hypoxia by calculating a score based on 15 hypoxia genes. The hypoxia scores were relatively high in LUAD patients with poor prognosis and were bound up with tumour node metastasis (TNM) stage, tumour size, lymph node, age and gender. By comparison of high hypoxia score group and low hypoxia score group, 1820 differentially expressed genes were identified, among which up-regulated genes were mainly about cell division and proliferation while down-regulated genes were primarily involved in cilium-related biological processes. Besides, LUAD patients with high hypoxia scores had higher frequencies of gene mutations, among which TP53, TTN and MUC16 had the highest mutation rates. As for DNA methylation, 1015 differentially methylated probes-related genes were found and may play potential roles in tumour-related neurobiological processes and cell signal transduction. Finally, a prognostic model with 25 multi-omics features was constructed and showed good predictive performance. The area under curve (AUC) values of 1-, 3- and 5-year survival reached 0.863, 0.826 and 0.846, respectively. Above all, our findings are helpful in understanding the impact and molecular mechanisms of hypoxia in LUAD.

Leveraging an immune cell signature to improve the survival and immunotherapy response of lung adenocarcinoma

Background: Immune cells play a critical role in the prognosis of cancer. However, the function of different immune cell types in lung adenocarcinoma (LUAD) and the development of a prognostic signature based on immune cell types have not been comprehensively investigated. Methods: We collected and included a total of 2499 LUAD patients and performed calculations to determine the penetration level of 24 immune cells. This examination was conducted using the macro-gene-based approach provided by ImmuCellAI. We performed a meta-analysis using Lasso-Cox analysis to establish the immune cell pair score (ICPS). We conducted a survival analysis to measure differences in survival across ICPS-risk groups. Wilcox test was used to measure the difference in expression level. Spearman correlation analysis was used for the relevance assessment. Results: We collected a total of 24 immune cell types to construct cell pairs. Utilizing 17 immune cell pairs, we constructed and validated the ICPS, which plays a critical role in stratifying survival and dynamically monitoring the effectiveness of immunotherapy. Additionally, we identified several candidate drugs that target ICPS. Conclusions: The ICPS shows promise as a valuable tool for identifying suitable candidates for immunotherapy among patients. Our comprehensive assessment of immune cell interactions in LUAD contributes to a deeper understanding of infiltration patterns and functions, thereby guiding the development of more efficacious immunotherapy strategies.

CXCL6: A potential therapeutic target for inflammation and cancer

Chemokines were originally defined as cytokines that affect the movement of immune cells. In recent years, due to the increasing importance of immune cells in the tumor microenvironment (TME), the role of chemokines has changed from a single "chemotactic agent" to a key factor that can regulate TME and affect the tumor phenotype. CXCL6, also known as granulocyte chemoattractant protein-2 (GCP-2), can recruit neutrophils to complete non-specific immunity in the process of inflammation. Cancer-related genes and interleukin family can promote the abnormal secretion of CXCL6, which promotes tumor growth, metastasis, epithelial mesenchymal transformation (EMT) and angiogenesis in the TME. CXCL6 also has a role in promoting fibrosis and tissue damage repair. In this review, we focus on the regulatory network affecting CXCL6 expression, its role in the progress of inflammation and how it affects tumorigenesis and progression based on the TME, in an attempt to provide a potential target for the treatment of diseases such as inflammation and cancer.

Role of CCNB1, CENPF, and neutrophils in lung cancer diagnosis and prognosis

This study aimed to investigate CCNB1, CENPF, and Neutrophils as diagnostic predictors of lung cancer and to explore their association with clinical prognosis. Clinical data were obtained for a total of 52 patients. In addition, we downloaded 555 lung cancer-related samples from the cancer genome atlas (TCGA) database. Differentially expressed genes were further screened. Immune cell infiltration and survival analysis were performed. Immunohistochemistry was used to confirm gene expression. Peripheral blood analysis showed that neutrophil percentages were significantly reduced in patients with lung cancer. The least absolute shrinkage and selection operator and multivariate regression analysis revealed that CCNB1 and CENPF were lung cancer risk factors. Both CCNB1 and CENPF are overexpressed in lung cancer. The clinical diagnostic model constructed using CCNB1, CENPF, and neutrophils had a C-index of 0.994. This model area under the curve (AUC) and internal validation C-index values were 0.994 and 0.993, respectively. The elevated expression of CCNB1 and CENPF showed that the survival rate of lung cancer patients was reduced. CCNB1 and CENPF expression was positively correlated with the clinical stage of lung cancer. Further studies confirmed that CCNB1 and CENPF are overexpressed in lung cancer tissues. The clinically constructed model with high accuracy based on CCNB1, CENPF, and neutrophils demonstrated that these are crucial indicators for lung cancer diagnosis. High expression of CCNB1 and CENPF indicates a poor prognosis in patients with lung cancer.

Prognostic value of cancer-associated fibroblasts-related genes in lung adenocarcinoma

Background

The incidence of lung adenocarcinoma is in the forefront of malignant tumors in the world. The purpose of this study was to investigate the role of cancer-associated fibroblast-related genes (CAFRGs) in the occurrence, diagnosis and development of lung adenocarcinoma.

Methods

RNA data and corresponding clinical information of lung adenocarcinoma patients were acquired from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed to identify different molecular subgroups. The tumor immune states of different subgroups were determined by Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE; https://bioinformatics.mdanderson.org/estimate/index.html), microenvironment cell populations (MCP)-counter (which can reliably quantify the abundance of eight immune cell populations and two stromal cell populations), and single sample gene set enrichment analysis (ssGSEA) analyses. In order to elucidate the potential mechanism of CAFRGs, functional enrichment analysis including gene ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG), and GSEA analysis were performed on the differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis were used to construct the prognostic risk model, which was verified by lung adenocarcinoma data from Gene Expression Omnibus (GEO) dataset GSE37745.

Results

This study identified two molecular subgroups with significant differences in survival. High immunoscore and immune cell infiltration were more common in the subgroup with better prognosis. GO and KEGG analysis showed that DEGs between the two different subgroups were mainly concentrated in the mitotic cell cycle, cell proliferation, vascular development, and humoral immune response, adaptive immune-related pathways. GSEA analysis indicated that RNA degradation and P53 signaling pathway might be related to the increased invasiveness of lung adenocarcinoma. Risk models based on CAFRGs have demonstrated potent potential for predicting lung adenocarcinoma survival and have been validated in validation cohorts. The nomogram combined with risk model and clinical characteristics can predict the prognosis of patients with lung adenocarcinoma.

Conclusions

The expression of CAFRGs is related to tumor immune microenvironment (TIME) of lung adenocarcinoma patients, and can predict the prognosis of lung adenocarcinoma patients.

Managing the immune microenvironment of osteosarcoma: the outlook for osteosarcoma treatment

Osteosarcoma, with poor survival after metastasis, is considered the most common primary bone cancer in adolescents. Notwithstanding the efforts of researchers, its five-year survival rate has only shown limited improvement, suggesting that existing therapeutic strategies are insufficient to meet clinical needs. Notably, immunotherapy has shown certain advantages over traditional tumor treatments in inhibiting metastasis. Therefore, managing the immune microenvironment in osteosarcoma can provide novel and valuable insight into the multifaceted mechanisms underlying the heterogeneity and progression of the disease. Additionally, given the advances in nanomedicine, there exist many advanced nanoplatforms for enhanced osteosarcoma immunotherapy with satisfactory physiochemical characteristics. Here, we review the classification, characteristics, and functions of the key components of the immune microenvironment in osteosarcoma. This review also emphasizes the application, progress, and prospects of osteosarcoma immunotherapy and discusses several nanomedicine-based options to enhance the efficiency of osteosarcoma treatment. Furthermore, we examine the disadvantages of standard treatments and present future perspectives for osteosarcoma immunotherapy.

Clinical Characterization of the Expression of Insulin-Like Growth Factor Binding Protein 1 and Tumor Immunosuppression Caused by Ferroptosis of Neutrophils in Non-Small Cell Lung Cancer

Purpose

The efficacy of immunotherapy for non-small cell lung cancer (NSCLC) is limited owing to cold tumors and drug resistance. Therefore, it is important to identify the molecular mechanisms underlying immune evasion in NSCLC. Spontaneous ferroptosis of neutrophils has been suggested as a key mechanism of immunosuppression in cancer. Insulin-like growth factor binding protein 1 (IGFBP1) plays an important role in immune infiltration in several cancers. However, the role of IGFBP1 in NSCLC is unknown. Therefore, in this study, we aimed to investigate the association of IGFBP1 mRNA expression with infiltration of myeloid-derived suppressor cells and prognosis in NSCLC.

Patients and Methods

Retrospective RNA-seq data from 990 patients in the Cancer Genome Atlas (TCGA) database were analyzed in relation to patient clinical characteristics. The Timer2 database was used to assess immune infiltration, and the FerrDb V2 database was used to obtain ferroptosis-related genes. Finally, the results were validated by the proteomic analysis of serum samples collected from six patients with NSCLC and six healthy individuals.

Results

IGFBP1 expression was enriched in lung adenocarcinoma samples and positively correlated with the pathological grade of NSCLC. IGFBP1 expression was an independent prognostic factor for the overall survival of patients with NSCLC. In addition, IGFBP1 expression correlated with myeloid-derived suppressor cell infiltration. Notably, Gene Ontology analysis of IGFBP1-related genes revealed that the major molecular functions of their protein products were related to NADP⁺ 1-oxidoreductase activity. Furthermore, expression levels of multiple ferroptosis suppressor genes positively correlated with IGFBP1 expression.

Conclusion

High IGFBP1 expression indicates a poor prognosis in patients with NSCLC, which may be related to tumor immunosuppression caused by neutrophil ferroptosis.

Tumor microenvironment in non-melanoma skin cancer resistance to photodynamic therapy

Non-melanoma skin cancer has recently seen an increase in prevalence, and it is estimated that this grow will continue in the coming years. In this sense, the importance of therapy effectiveness has increased, especially photodynamic therapy. Photodynamic therapy has attracted much attention as a minimally invasive, selective and repeatable approach for skin cancer treatment and prevention. Although its high efficiency, this strategy has also faced problems related to tumor resistance, where the tumor microenvironment has gained a well-deserved role in recent years. Tumor microenvironment denotes a wide variety of elements, such as cancer-associated fibroblasts, immune cells, endothelial cells or the extracellular matrix, where their interaction and the secretion of a wide diversity of cytokines. Therefore, the need of designing new strategies targeting elements of the tumor microenvironment to overcome the observed resistance has become evident. To this end, in this review we focus on the role of cancer-associated fibroblasts and tumor-associated macrophages in the resistance to photodynamic therapy. We are also exploring new approaches consisting in the combination of new and old drugs targeting these cells with photodynamic therapy to enhance treatment outcomes of non-melanoma skin cancer.

A Novel Hypoxia Related Marker in Blood Link to Aid Diagnosis and Therapy in Osteoarthritis

Osteoarthritis (OA) is a common chronic degenerative arthritis. Its treatment options are very limited. At present, hypoxia is a prominent factor in OA. This study aimed to re-explore the mechanism between hypoxia and OA, which provides new insights into the diagnosis and therapy of OA. We acquired the OA-related expression profiles of GSE48556, GSE55235, and GSE55457 for our analysis. Using gene set variation analysis (GSVA), we found significant differences in hypoxia. These differences result from multiple pathways, such as the p53 signaling pathway, cell senescence, the NF-kappa B signaling pathway, Ubiquitin-mediated proteolysis, and apoptosis. Meanwhile, the single-sample gene set enrichment analysis (ssGSEA) showed that hypoxia was significantly associated with the level of immune cell infiltration in the immune microenvironment. Thus, we believe that hypoxia is useful for the diagnosis and treatment of OA. We successfully constructed a novel hypoxia-related index (HRI) based on seven hypoxia-related genes (ADM, CDKN3, ENO1, NDRG1, PGAM1, SLC2A1, VEGFA) by least absolute shrinkage and binary logistic regression of the generalized linear regression. HRI showed potential for improving OA diagnosis through receiver operation characteristic (ROC) analysis (AUC training cohort = 0.919, AUC testing cohort = 0.985). Moreover, we found that celastrol, droxinostat, torin-2, and narciclasine may be potential therapeutic compounds for OA based on the Connectivity Map (CMap). In conclusion, hypoxia is involved in the development and progression of OA. HRI can improve diagnosis and show great potential in clinical application. Celastrol, droxinostat, torin-2, and narciclasine may be potential compounds for the treatment of OA patients.

A novel mTOR-associated gene signature for predicting prognosis and evaluating tumor immune microenvironment in lung adenocarcinoma

BACKGROUND

The mechanistic target of rapamycin (mTOR) was proven to have great impact on apoptosis, cell proliferation, autophagy, and many other fundamental cellular processes; moreover, it closely correlates with tumor occurrence and development. However, few studies have constructed signatures based on mTOR-associated genes to assess multiple indicators of prognosis in lung adenocarcinoma (LUAD) patients.

METHODS

mTOR-associated gene sets, whole mRNA expression matrices, and clinical information of LUAD patients in training and validation cohorts were obtained from multiple public databases. Multiple methods were used to screen candidate genes, construct signatures, validate internally and externally, and conduct further studies: differentially expressed gene analysis, LASSO Cox regression analysis, Cox regression analysis, risk factor analysis, nomogram analysis, functional enrichment analysis, analyses in tumor immune microenvironment, and therapy.

RESULTS

A prognostic signature containing 8 genes (LDHA, SLA, WNT7A, PLK1, CCT6A, BTG2, TXNRD1, and DDIT4) was constructed. It performed well in both internal and external validation. Subsequent analysis found that the prognostic signature was of great significance in evaluating the tumor immune microenvironment and could guide the treatment of patients with LUAD to a certain extent.

CONCLUSION

The constructed mTOR-associated gene signature accurately predicted the prognostic pattern of patients with LUAD and is expected to be extremely useful in guiding LUAD therapy.