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Background: Accounting for tumor heterogeneity, cancer stem cells (CSC) are involved in tumor metastasis, relapse, and drug resistance. Genes regulating CSC characteristics in lung adenocarcinoma (LUAD) were explored and validated in this study., Methods: The mRNA stemness index (mRNAsi) of more than 500 LUAD cases from The Cancer Genome Atlas database were calculated using a one-class logistic regression machine learning algorithm based on the mRNA expression of pluripotent stem cells and their differentiated progeny. mRNAsi-related key genes were identified by weighted correlation network analysis. The expression levels and prognostic roles of key genes were analyzed in Oncomine, PrognoScan, and Kaplan-Meier plotter databases, and validated using data from our center., Results: The mRNAsi was significantly higher in LUAD compared with normal lung tissues. LUAD patients of advanced stage exhibited a higher mRNAsi and worse overall survival (OS). Eight key genes were identified: heat shock 70 kDa protein 4 (HSPA4), cell division cycle associated 7 (CDCA7), cell division cycle 20 (CDC20), cyclin-dependent kinase 1 (CDK1), CAP-GLY domain containing linker protein 1 (CLIP1), cyclin B1 (CCNB1), H2A histone family, member X (H2AFX), and Bloom syndrome, RecQ helicase-like (BLM). These genes were differentially expressed in various types of malignancies and validated in the LUAD cases. LUAD patients with low expression of CDC20, CDK1, CCNB1, H2AFX, or BLM had a significantly better OS, whereas OS was reduced for patients with low expression of CLIP1. In addition, the expression of CDCA7 did not significantly impact the OS of LUAD patients. The protein-protein interaction networks evaluated by STRING demonstrated strong relationships between these key genes, which were validated in our cases., Conclusions: The mRNAsi was significantly higher in LUAD compared with normal samples. Eight mRNAsi-related key genes were associated with prognosis and the cell cycle, and were strongly correlated with each other and differentially expressed in tumor and normal samples. We provide a new strategy for exploring stemness-related genes in LUAD cases.

Ferroptosis is a recently discovered form of cell death that plays an important role in tumor growth and holds promise as a target for antitumor therapy. However, evidence in the regulation of ferroptosis in lung adenocarcinoma (LUAD) remains elusive. Here, we show that retinoic acid receptor alpha (RARA) is upregulated with the treatment of ferroptosis inducers (FINs). Pharmacological activation of RARA increases the resistance of LUAD to ferroptosis according to cell viability and lipid peroxidation assays, while RARA inhibitor or knockdown (KD) does the opposite. Through transcriptome sequencing in RARA-KD cells and chromatin immunoprecipitation (CHIP)-Seq data, we identify thioredoxin (TXN) and protein phosphatase 1 F (PPM1F) as downstream targets of RARA, both of which inhibit ferroptosis. We confirm that RARA binds to the promotor region of TXN and PPM1F and promotes their transcription by CHIP-qPCR and dual-luciferase assays. Overexpression of TXN and PPM1F reverses the effects of RARA knockdown on ferroptosis in vitro and vivo. Clinically, RARA knockdown or inhibitor increases cells' sensitivity to pemetrexed and cisplatin (CDDP). Immunohistochemistry (IHC) of LUAD from our cohort shows the same expression tendency of RARA and the downstream targets. Our study uncovers that RARA inhibits ferroptosis in LUAD by promoting TXN and PPM1F, and inhibiting RARA-TXN/PPM1F axis represents a promising strategy for improving the efficacy of FINs or chemotherapy in the treatment of LUAD patients. This study reveals RARA's role in inhibiting ferroptosis through the promotion of TXN and PPM1F, offering a potential therapeutic strategy for LUAD treatment by increasing efficacy of ferroptosis inducers or chemotherapy. [ABSTRACT FROM AUTHOR]

Purpose: Macrophages (MΦs) play a dual role in the promotion and suppression of lung adenocarcinoma (LUAD), the function of which is influenced by the metabolic status. The role of protein tyrosine phosphatase receptor type F (PTPRF) in cancer has not been elucidated, and its role in MΦs remains to be seen. Methods: The Seahorse XFe 96 Cell Flow Analyzer detected glucose metabolism in tumor cells and macrophages. The expressions of FSCN1, M-CSF, IL4, PTPRF and IGF1 in macrophages were detected by Western blotting and qRT-PCR. Binding of FSCN1 and IGF1R was detected by co-immunoprecipitation. The tumor status in animals was observed using the IVIS Lumina III imaging system. Results: We found that Fascin Actin-Bundling Protein 1 (FSCN1) activates the PI3K-AKT and JAK-STAT signaling pathways in LUAD cells via binding to IGF-1R, thereby promoting the secretion of cytokines such as IL4 and M-CSF. IL4 and M-CSF promote the expression of PTPRF in MΦs, leading to M2 polarization of MΦs by increasing glucose intake and lactate production. In return, M2-type MΦs act on LUAD cells by secreting cytokines such as IGF-1, CCL2, and IL10, which ultimately promote tumor progression. In vivo experiments proved that the knockdown of FSCN1 in A549 cells and PTPRF in MΦs greatly reduced LUAD proliferative and metastatic capacity, which was consistent with the in vitro findings. Conclusions: This study investigated the reprogramming effects of FSCN1 and PTPRF on inflammatory cytokines in the LUAD microenvironment, revealing potential mechanisms by which FSCN1 and PTPRF promote tumor progression and providing a new experimental basis for LUAD treatment. [ABSTRACT FROM AUTHOR]

Metformin's effect on tumor treatment was complex, because it significantly reduced cancer cell proliferation in vitro , but made no difference in prognosis in several clinical cohorts. Our transcriptome sequencing results revealed that tumor-associated macrophage (TAM) infiltration significantly increased in active lung adenocarcinoma (LUAD) patients with long-term metformin use. We further identified that the tumor suppressive effect of metformin was more significant in mice after the depletion of macrophages, suggesting that TAMs might play an important role in metformin's effects in LUAD. Combining 10X Genomics single-cell sequencing of tumor samples, transcriptome sequencing of metformin-treated TAMs, and the ChIP-Seq data of the Encode database, we identified and validated that metformin significantly increased the expression and secretion of S100A9 of TAMs through AMPK-CEBP/β pathway. For the downstream, S100A9 binds to RAGE receptors on the surface of LUAD cells, and then activates the NF-κB pathway to promote EMT and progression of LUAD, counteracting the inhibitory effect of metformin on LUAD cells. In cell-derived xenograft models (CDX) and patient-derived xenograft models (PDX) models, our results showed that neutralizing antibodies targeting TAM-secreted S100A9 effectively enhanced the tumor suppressive effect of metformin in treating LUAD. Our results will enable us to better comprehend the complex role of metformin in LUAD, and advance its clinical application in cancer treatment. • Metformin has pro-tumorigenic molecular mechanisms in vivo that partially counteract the anti-tumor effect. • Metformin promotes TAM secreting S100A9 through the AMPK-CEBP/β pathway, which promotes LUAD progression through RAGE-NFkB- EMT. • Blocking antibody of TAM-secreted S100A9 significantly promotes the antitumor effects of metformin in vitro and in vivo. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) patients with different American Joint Committee on Cancer stages have different overall 5‐year survival rates. The tumor microenvironment (TME) and intra‐tumor heterogeneity (ITH) have been shown to play a crucial role in the occurrence and development of tumors. However, the TME and ITH in different lesions of LUAD have not been extensively explored. Methods: We present a 204,157‐cell catalog of the TME transcriptome in 29 lung samples to systematically explore the TME and ITH in the different stages of LUAD. Traditional RNA sequencing data and complete clinical information were downloaded from publicly available databases. Results: Based on these high‐quality cells, we constructed a single‐cell network underlying cellular and molecular features of normal lung, early LUAD, and advanced LUAD cells. In contrast with early malignant cells, we noticed that advanced malignant cells had a remarkably more complex TME and higher ITH level. We also found that compared with other immune cells, more differences in CD8+/CTL T cells, regulatory T cells, and follicular B cells were evident between early and advanced LUAD. Additionally, cell‐cell communication analyses, revealed great diversity between different lesions of LUAD at the single‐cell level. Flow cytometry and qRT‐PCR were used to validate our results. Conclusion: Our results revealed the cellular diversity and molecular complexity of cell lineages in different stages of LUAD. We believe our research, which serves as a basic framework and valuable resource, can facilitate exploration of the pathogenesis of LUAD and identify novel therapeutic targets in the future. [ABSTRACT FROM AUTHOR]

The tumor microenvironment (TME) plays an essential role in the occurrence and progression of malignancy. The potential prognostic TME-related biomarkers of lung adenocarcinoma (LUAD) remained unclear, which were investigated in this research. The RNA-sequencing profiles and corresponding clinical parameters were extracted from TCGA and GEO databases, based on which the stromal and immune scores were calculated through the ESTIMATE algorithm. Overlapping differentially expressed genes between stromal and immune score group were analyzed by the LASSO and Random Forrest algorithms and validated in cases from our center. And a prognostic 8-gene signature was constructed using Cox regression. The infiltration of 22 hematopoietic cell phenotypes was assessed by the CIBERSORT algorithms. We found that female, elder patients, and solid predominant subtype had obviously higher stromal and immune scores. And patients with early stage LUAD received a prominently higher immune score. A high stromal or immune score meant a good prognosis. Subsequently, eight TME-related prognostic genes (ATAD5, CYP4F3, CYP4F12, ESPNL, FXYD2, GPX2, NLGN4Y, and SERPINC1) were identified by both LASSO regression and Radom Forest algorithms. High 8-gene signature group exhibited worse overall survival. Furthermore, B cell naïve, plasma cells, T cell follicular helper, and macrophages M1 were prominently more in high signature group. Nevertheless, fewer T cells CD4 memory resting, monocytes, and dendritic cell resting were identified in the high signature group. The composition of the tumor microenvironment significantly affected the prognosis of LUAD patients. We provided a new strategy for the exploration of prognostic TME-related biomarkers and immunotherapy. [ABSTRACT FROM AUTHOR]

Purpose: To comprehensively elucidate the landscape of the tumor environment (TME) of lung adenocarcinoma (LUAD), which has a profound impact on prognosis and response to immunotherapy. Methods and materials: Using a large dataset of LUAD patients from The Cancer Genome Atlas, Gene Expression Omnibus database (GEO), and our institution (n = 1411), we estimated the infiltration pattern of 24 immune cell populations in each sample and systematically correlated the TME phenotypes with genomic traits and clinicopathologic characteristics. Results: The LUAD microenvironment was classified into two distinct TME clusters (A and B), and a random forest classifier model was constructed. TMEcluster A was characterized by sparse distribution of immune cell infiltration, relatively low levels of immunomodulators and slightly higher mutation load. By contrast, enrichment of both cytotoxic T cells and immunosuppressor cells was observed in TMEcluster B. Moreover, several immune-related cytokines or markers including IFN-γ, TNF-β, and several immune checkpoint molecules such as PD-L1 were also upregulated in TMEcluster B. Multivariable Cox analysis revealed that the TMEcluster was an independent prognostic factor (TMEcluster B vs. A, hazard ratio = 0.68, 95% confidence interval = 0.50–0.91, p = 0.010). These findings were all externally validated in the data from the GEO database and our institution. Conclusions: Our findings describe a comprehensive landscape of LUAD immune infiltration pattern and integrate several previously proposed biomarkers associated with distinct immunophenotypes, thus shedding light on how tumors interact with immune microenvironment. Our results may guide a more precise immune therapeutic strategy for LUAD patients. [ABSTRACT FROM AUTHOR]