SLC7A11 inhibits ferroptosis and downregulates PD-L1 levels in lung adenocarcinoma.

Introduction: Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer originating from lung glandular cells with low survival rates despite recent therapeutic advances due to its diverse and complex nature. Recent evidence suggests a link between ferroptosis and the effectiveness of anti-PD-L1 therapy, with potential synergistic effects. Methods: Our study comprehensively analyzed the expression patterns of ferroptosis regulators in LUAD and their association with prognosis and PD-L1 expression. Furthermore, we identified two distinct subtypes of LUAD through consensus clustering of ferroptosis regulators, revealing significant tumor heterogeneity, divergent PD-L1 expression, and varying prognoses between the subtypes. Results: Among the selected ferroptosis regulators, SLC7A11 emerged as an independent prognostic marker for LUAD patients and exhibited a negative correlation with PD-L1 expression. Subsequent investigations revealed high expression of SLC7A11 in the LUAD population. In vitro experiments demonstrated that overexpression of SLC7A11 led to reduced PD-L1 expression and inhibited ferroptosis in A549 cells, underscoring the significant role of SLC7A11 in LUAD. Additionally, pan-cancer analyses indicated an association between SLC7A11 and the expression of immune checkpoint genes across multiple cancer types with poor prognoses. Discussion: From a clinical standpoint, these findings offer a foundation for identifying and optimizing potential combination strategies to enhance the therapeutic effectiveness of immune checkpoint inhibitors and improve the prognosis of patients with LUAD.

Deciphering the heterogeneity dominated by tumor-associated macrophages for survival prognostication and prediction of immunotherapy response in lung adenocarcinoma.

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The "BayesPrism" and "Seurat" R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

Identifying an immunogenic cell death-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma.

BACKGROUND: Immunogenic cell death (ICD) is a regulated form of cell death that triggers an adaptive immune response. The objective of this study was to investigate the correlation between ICD-related genes (ICDGs) and the prognosis and the immune microenvironment of patients with lung adenocarcinoma (LUAD). METHODS: ICD-associated molecular subtypes were identified through consensus clustering. Subsequently, a prognostic risk model comprising 5 ICDGs was constructed using Lasso-Cox regression in the TCGA training cohort and further tested in the GEO cohort. Enriched pathways among the subtypes were analyzed using GO, KEGG, and GSVA. Furthermore, the immune microenvironment was assessed using ESTIMATE, CIBERSORT, and ssGSEA analyses. RESULTS: Consensus clustering divided LUAD patients into three ICDG subtypes with significant differences in prognosis and the immune microenvironment. A prognostic risk model was constructed based on 5 ICDGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of tumor purity. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor. The five hub genes were verified by TCGA database, cell sublocalization immunofluorescence analysis, IHC images and qRT-PCR, which were consistent with bioinformatics analysis. CONCLUSIONS: The molecular subtypes and a risk model based on ICDGs proposed in our study are both promising prognostic classifications in LUAD, which may provide novel insights for developing accurate targeted cancer therapies.

Unlocking the role of EIF5A: A potential diagnostic marker regulating the cell cycle and showing negative correlation with immune infiltration in lung adenocarcinoma.

BACKGROUND: Despite EIF5A upregulation related to tumor progression in LUAD (lung adenocarcinoma), the underlying mechanisms remain elusive. In addition, there are few comprehensive analyses of EIF5A in LUAD. METHODS: We investigated the EIF5A expression level in LUAD patients using data from the TCGA and GEO databases. We employed qRT-PCR and western blot to verify EIF5A expression in cell lines, while immunohistochemistry was utilized for clinical sample analysis. We analyzed EIF5A expression in tumor-infiltrating immune cells using the TISCH database and assessed its association with immune infiltration in LUAD using the "ESTIMATE" R package. Bioinformatics approaches were developed to discover the EIF5A-related genes and explore EIF5A potential mechanisms in LUAD. Proliferation ability was verified through CCK-8, clone formation, and EdU assays, while flow cytometry assessed apoptosis and cell cycle. Western blot was used to detect the expression of pathway-related proteins. RESULTS: EIF5A was significantly upregulated in LUAD. Moreover, we constructed a MAZ-hsa-miR-424-3p-EIF5A transcriptional network. We explored the potential mechanism of EIF5A in LUAD and further investigated the cAMP signaling pathway and the cell cycle. Finally, we proved that EIF5A silencing induced G1/S Cell Cycle arrest, promoted apoptosis, and inhibited proliferation via the cAMP/PKA/CREB signaling pathway. CONCLUSION: EIF5A serves as a prognostic biomarker with a negative correlation to immune infiltrates in LUAD. It regulated the cell cycle in LUAD by inhibiting the cAMP/PKA/CREB signaling pathway.

SAA suppresses α-PD-1 induced anti-tumor immunity by driving TH2 polarization in lung adenocarcinoma.

Cancer stem cells (CSCs) are believed to be crucial in the initiation, progression, and recurrence of cancer. CSCs are also known to be more resistant to cancer treatments. However, the interaction between CSCs and the immune microenvironment is complex and not fully understood. In current study we used single cell RNA sequence (scRNA-Seq, public dataset) technology to identify the characteristic of CSCs. We found that the lung adenocarcinoma cancer stem population is highly inflammatory and remodels the tumor microenvironment by secreting inflammatory factors, specifically the acute phase protein serum amyloid A (SAA). Next, we developed an ex-vivo autologous patient-derived organoids (PDOs) and peripheral blood mononuclear cells (PBMCs) co-culture model to evaluate the immune biological impact of SAA. We found that SAA not only promotes chemoresistance by inducing cancer stem transformation, but also restricts anti-tumor immunity and promotes tumor fibrosis by driving type 2 immunity, and α-SAA neutralization antibody could restrict treatment resistant and tumor fibrosis. Mechanically, we found that the malignant phenotype induced by SAA is dependent on P2X7 receptor. Our data indicate that cancer stem cells secreted SAA have significant biological impact to promote treatment resistant and tumor fibrosis by driving cancer stemness transformation and type 2 immunity polarization via P2X7 receptor. Notably, α-SAA neutralization antibody shows therapeutic potential by restricting these malignant phenotypes.

Spatial profiling of the microenvironment reveals low intratumoral heterogeneity and STK11-associated immune evasion in therapy-naïve lung adenocarcinomas.

OBJECTIVE: Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting. MATERIALS AND METHODS: We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype). For each sample the expression of 770 immunooncology-related genes was analyzed using the nCounter platform, while the mutational status was determined by hybrid capture-based next-generation sequencing (NGS) using a large panel covering more than 500 genes. RESULTS: Global unsupervised analyses revealed clustering of the samples into two groups corresponding to a 'hot' or 'cold' immunologic tumor contexture based on the abundance of immune cell infiltrates. All analyzed specific immune cell signatures (ICsig) showed a significantly higher intertumoral than intratumoral heterogeneity (p < 0.02), as most of the analyzed cases (14/19) showed a very homogenous spatial immune cell profile. PD-L1 exhibited a significantly higher intertumoral than intratumoral heterogeneity (p = 1.03e-13). We found a specific association with 'cold' TME for STK11 (11/14, p < 0.07), but not KRAS, TP53, LRP1B, MTOR, U2AF1 co-mutations, and validated this finding using The Cancer Genome Atlas (TCGA) data. CONCLUSION: Early-stage lung adenocarcinomas show considerable intertumoral, but limited intratumoral heterogeneity, which is clinically highly relevant as assessment before neoadjuvant treatment is based on small biopsies. STK11 mutations are specifically associated with a 'cold' TME, which could affect the efficacy of perioperative immunotherapy.

Antibodies against endogenous retroviruses promote lung cancer immunotherapy.

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

STING inhibits the reactivation of dormant metastasis in lung adenocarcinoma.

Metastasis frequently develops from disseminated cancer cells that remain dormant after the apparently successful treatment of a primary tumour. These cells fluctuate between an immune-evasive quiescent state and a proliferative state liable to immune-mediated elimination1-6. Little is known about the clearing of reawakened metastatic cells and how this process could be therapeutically activated to eliminate residual disease in patients. Here we use models of indolent lung adenocarcinoma metastasis to identify cancer cell-intrinsic determinants of immune reactivity during exit from dormancy. Genetic screens of tumour-intrinsic immune regulators identified the stimulator of interferon genes (STING) pathway as a suppressor of metastatic outbreak. STING activity increases in metastatic progenitors that re-enter the cell cycle and is dampened by hypermethylation of the STING promoter and enhancer in breakthrough metastases or by chromatin repression in cells re-entering dormancy in response to TGFß. STING expression in cancer cells derived from spontaneous metastases suppresses their outgrowth. Systemic treatment of mice with STING agonists eliminates dormant metastasis and prevents spontaneous outbreaks in a T cell- and natural killer cell-dependent manner-these effects require cancer cell STING function. Thus, STING provides a checkpoint against the progression of dormant metastasis and a therapeutically actionable strategy for the prevention of disease relapse.

Single-cell spatial landscapes of the lung tumour immune microenvironment.

Single-cell technologies have revealed the complexity of the tumour immune microenvironment with unparalleled resolution1-9. Most clinical strategies rely on histopathological stratification of tumour subtypes, yet the spatial context of single-cell phenotypes within these stratified subgroups is poorly understood. Here we apply imaging mass cytometry to characterize the tumour and immunological landscape of samples from 416 patients with lung adenocarcinoma across five histological patterns. We resolve more than 1.6 million cells, enabling spatial analysis of immune lineages and activation states with distinct clinical correlates, including survival. Using deep learning, we can predict with high accuracy those patients who will progress after surgery using a single 1-mm2 tumour core, which could be informative for clinical management following surgical resection. Our dataset represents a valuable resource for the non-small cell lung cancer research community and exemplifies the utility of spatial resolution within single-cell analyses. This study also highlights how artificial intelligence can improve our understanding of microenvironmental features that underlie cancer progression and may influence future clinical practice.

RAGA prevents tumor immune evasion of LUAD by promoting CD47 lysosome degradation.

CD47 is a macrophage-specific immune checkpoint protein acting by inhibiting phagocytosis. However, the underlying mechanism maintaining CD47 protein stability in cancer is not clear. Here we show that CD47 undergoes degradation via endocytosis/lysosome pathway. The lysosome protein RAGA interacts with and promotes CD47 lysosome localization and degradation. Disruption of RAGA blocks CD47 degradation, leading to CD47 accumulation, high plasma membrane/intracellular CD47 expression ratio and reduced phagocytic clearance of cancer cells. RAGA deficiency promotes tumor growth due to the accumulation of CD47, which sensitizes the tumor to CD47 blockade. Clinical analysis shows that RAGA and CD47 proteins are negatively correlated in lung adenocarcinoma patient samples. High RAGA protein level is related to longer patient survival. In addition, RAGAhighCD47low patients show the longest overall survival. Our study thereby not only reveals a mechanism by which RAGA regulates CD47 lysosome degradation, but also suggests RAGA is a potential diagnostic biomarker of lung adenocarcinoma.

TTYH3 is a prognostic biomarker and associates with immune cell infiltrations of lung adenocarcinoma / TTYH3 es un biomarcador pronóstico y se asocia con infiltraciones de células inmunitarias del adenocarcinoma de pulmón

SUMMARY: We investigated Tweety Family Member 3 (TTYH3) level in lung adenocarcinoma (LUAD) and its relationship with immune infiltration in tumors by bioinformatics. Differential expressions of TTYH3 in lung cancer were analyzed with Oncomine, TIMER, GEO, UALCAN and HPA. Relationship of TTYH3 mRNA/protein levels with clinical parameters was analyzed by UALCAN. Co-expressed genes of TTYH3 in LUAD were analyzed using Cbioportal. Its relationship with LUAD prognosis was analyzed by Kaplan-Meier plotter. GO and KEGG analysis were performed. Correlation between TTYH3 and tumor immune infiltration were tested by TIMER, TISIDB and GEPIA. We found that TTYH3 was significantly increased in LUAD tissues. TTYH3 high expression was closely related to poor overall survival, post progression survival and first progression in LUAD patients. TTYH3 mRNA/protein levels were significantly associated with multiple pathways. Specifically, TTYH3 up-regulation was mostly related to biological regulation, metabolic process, protein blinding, extracellular matrix organization and pathways in cancer. Moreover, TTYH3 was positively associated with immune cell infiltration in LUAD. Finally, TTYH3 was highly expressed in LUAD as revealed by meta-analysis. TTYH3 is closely related to the prognosis of LUAD and immune cell infiltration, and it can be used as a prognostic biomarker for LUAD and immune infiltration.

Investigamos por bioinformática el nivel de Tweety Family Member 3 (TTYH3) con adenocarcinoma de pulmón (LUAD) y su relación con la infiltración inmune en tumores. Las expresiones diferenciales de TTYH3 en cáncer de pulmón se analizaron con Oncomine, TIMER, GEO, UALCAN y HPA. Con UALCAN se analizó la relación de los niveles de ARNm/proteína de TTYH3 con los parámetros clínicos. Los genes coexpresados de TTYH3 en LUAD se analizaron utilizando Cbioportal. Su relación con el pronóstico LUAD se analizó mediante plotter de Kaplan- Meier. Se realizaron análisis GO y KEGG. TIMER, TISIDB y GEPIA probaron la correlación entre TTYH3 y la infiltración inmune tumoral. Encontramos que TTYH3 aumentó significativamente en los tejidos LUAD. La alta expresión de TTYH3 estuvo estrechamente relacionada con una supervivencia general deficiente, supervivencia posterior a la progresión y primera progresión en pacientes con LUAD. Los niveles de ARNm/ proteína de TTYH3 se asociaron significativamente con múltiples vías. Específicamente, la regulación positiva de TTYH3 se relacionó principalmente con la regulación biológica, el proceso metabólico, el cegamiento de proteínas, la organización de la matriz extracelular y las vías en el cáncer. Además, TTYH3 se asoció positivamente con la infiltración de células inmunitarias en LUAD. Finalmente, TTYH3 se expresó altamente en LUAD como lo reveló el metanálisis. TTYH3 está estrechamente relacionado con el pronóstico de LUAD y la infiltración de células inmunitarias, y se puede utilizar como biomarcador pronóstico para LUAD y la infiltración de células inmunitarias.

Integrative stemness characteristics associated with prognosis and the immune microenvironment in lung adenocarcinoma.

BACKGROUND: To comprehensively analyze the stemness characteristics related to prognosis and the immune microenvironment in lung adenocarcinoma (LUAD). METHODS: The OCLR machine learning method was used to calculate the stemness index (mRNAsi) of the LUAD samples. DEGs common between the low mRNAsi, normal, and high mRNAsi groups were screened and the immune-stemness genes were obtained. Then the PPI network was created and enrichment analyses were performed. Moreover, different subtypes based on immune-stemness genes associated with prognosis were identified, and the relationships between LUAD stemness and TIME variables were systematically analyzed, followed by TMB analysis. RESULTS: Patients in the high mRNAsi groups with poor prognosis were screened along with 144 immune-stemness genes. IL-6, FPR2, and RLN3 showed a higher degree in the PPI network. A total of 26 immune-stemness genes associated with prognosis were screened. Two clusters were obtained (cluster 1 and cluster 2). Survival analysis revealed that patients in cluster 2 had a poor prognosis. A total of 12 immune cell subpopulations exhibited significant differences between cluster 1 and cluster 2 (P < 0.05). A total of 10 immune checkpoint genes exhibited significantly higher expression in cluster 1 (P < 0.05) than in cluster 2. Further, the TMB value in cluster 2 was higher than that in cluster 1 (P < 0.05). CONCLUSION: Immune-stemness genes, including L-6, FPR2, and RLN3, might play significant roles in LUAD development via cytokine-cytokine receptor interaction, neuroactive ligand‒receptor interaction, and the JAK‒STAT pathway. Immune-stemness genes were related to tumor-infiltrating immune cells, TMB, and expression of immune checkpoint gene.

The Ion Channel Gene KCNAB2 Is Associated with Poor Prognosis and Loss of Immune Infiltration in Lung Adenocarcinoma.

The malignancy with the greatest global mortality rate is lung cancer. Lung adenocarcinoma (LUAD) is the most common subtype. The evidence demonstrated that voltage-gated potassium channel subunit beta-2 (KCNAB2) significantly participated in the initiation of colorectal cancer and its progression. However, the biological function of KCNAB2 in LUAD and its effect on the tumor immune microenvironment are still unknown. In this study, we found that the expression of KCNAB2 in tissues of patients with LUAD was markedly downregulated, and its downregulation was linked to accelerated cancer growth and poor clinical outcomes. In addition, low KCNAB2 expression was correlated with a deficiency in immune infiltration. The mechanism behind this issue might be that KCNAB2 influenced the immunological process such that the directed migration of immune cells was affected. Furthermore, overexpression of KCNAB2 in cell lines promoted the expression of CCL2, CCL3, CCL4, CCL18, CXCL9, CXCL10, and CXCL12, which are necessary for the recruitment of immune cells. In conclusion, KCNAB2 may play a key function in immune infiltration and can be exploited as a predictive biomarker for evaluating prognosis and a possible immunotherapeutic target.

Potential impact of WTAP and YTHDF2 on tumor immunity in lung adenocarcinoma.

WTAP and N6-methyladenosine (m6A) reader proteins (YTHDF2) are N6-methyladenosine (m6A) methyltransferase and m6A reading proteins, respectively. In recent years, the tumor immune environment has received more and more attention in the progress and treatment of cancer. The aim of this study was to investigate the relationship between N6-methyladenosine (m6A) methyltransferase (WTAP)/YTHDF2 and the immunological characteristics of lung adenocarcinoma (LUAD). Based on the expression of WTAP and YTHDF2 in the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database, LUAD patients were divided into 2 clusters by coherently clustering method, and performed gene set enrichment analysis (GSEA) to identify the functional differences. Immunoinvasion analysis was performed using ESTIMATE, CIBERSORT, and single-sample GSEA (ssGSEA), and expression of immune checkpoint inhibitors (ICIs) targets was assessed, while tumor mutation burden (TMB) was calculated in tumor samples. Weighted gene co-expression network analysis (WGCNA) was used to identify the genes related to both WTAP/YTHDF2 expression and immunity. The immunological characteristics between the 2 clusters were externally verified based on GSE39582. The expression of WTAP was higher in cluster 1 and YTHDF2 was lower, but it was opposite in cluster 2. Cluster 1 had stronger immune infiltration, more ICIs target expression, more TMB. In addition, WGCNA identified 22 genes associated with WTAP/YTHDF2 expression and immune score, including TIM3 (HAVCR2) and CD86. WTAP and YTHDF2 influence immune contexture and may be novel prognostic and druggable targets associated with the immune system of LUAD.

Cuproptosis-related lncRNA predict prognosis and immune response of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) accounts for 50% of lung cancers, with high mortality and poor prognosis. Long non-coding RNA (lncRNA) plays a vital role in the progression of tumors. Cuproptosis is a newly discovered form of cell death that is highly investigated. Therefore, in the present study, we aimed to investigate the role of cuproptosis-related lncRNA signature in clinical prognosis prediction and immunotherapy and the relationship with drug sensitivity. MATERIAL AND METHODS: Genomic and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and cuproptosis-related genes were obtained from cuproptosis-related studies. The prognostic signature was constructed by co-expression analysis and Cox regression analysis. Patients were divided into high and low risk groups, and then, a further series of model validations were carried out to assess the prognostic value of the signature. Subsequently, lncRNAs were analyzed for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes Enrichment (KEGG), immune-related functions, and tumor mutation burden (TMB). Finally, we used tumor immune dysfunction and exclusion (TIDE) algorithms on immune escape and immunotherapy of cuproptosis-related lncRNAs, thereby identifying its sensitivity toward potential drugs for LUAD. RESULTS: A total of 16 cuproptosis-related lncRNAs were obtained, and a prognostic signature was developed. We found that high-risk patients had worse overall survival (OS) and progression-free survival (PFS) and higher mortality. Independent prognostic analyses, ROC, C-index, and nomogram showed that the cuproptosis-related lncRNAs can accurately predict the prognosis of patients. The nomogram and heatmap showed a distinct distribution of the high- and low-risk cuproptosis-related lncRNAs. Enrichment analysis showed that the biological functions of lncRNAs are associated with tumor development. We also found that immune-related functions, such as antiviral activity, were suppressed in high-risk patients who had mutations in oncogenes. OS was poorer in patients with high TMB. TIDE algorithms showed that high-risk patients have a greater potential for immune escape and less effective immunotherapy. CONCLUSION: To conclude, the 16 cuproptosis-related lncRNAs can accurately predict the prognosis of patients with LUAD and may provide new insights into clinical applications and immunotherapy.

Semaphorin 4B promotes tumor progression and associates with immune infiltrates in lung adenocarcinoma.

BACKGROUND: Semaphorins have been found to play important roles in multiple malignancy-related processes. However, the role of Semaphorin 4B (SEMA4B) in lung cancer remains unclear. Here, we aimed to explore the biological functions of SEMA4B in through bioinformatic analysis, in vitro and in vivo assays. In the present study, the possible mechanism by which SEMA4B affected the tumor growth and microenvironment of lung adenocarcinoma (LUAD) were investigated. METHODS: The expression of SEMA4B in LUAD was analyzed by bioinformatic analysis and verified by the immunohistochemistry staining. The prognostic value of SEMA4B in LUAD was investigated using the Kaplan-Meier survival and Cox's regression model. After silencing SEMA4B expression, the functions of SEMA4B in LUAD cells were investigated by in vitro experiments, including CCK-8 and plate clone formation. And the effect of SEMA4B on tumor growth and immune infiltration was explored in C57BL/6 mice tumor-bearing models. RESULTS: SEMA4B expression was upregulated in LUAD tissues and correlated with later pathological stages and poor prognosis of LUAD patients. Further study found that SEMA4B silencing suppressed the proliferation of lung cancer cells both in vitro and in vivo. Bioinformatic analysis showed that SEMA4B expression was correlated with the increased infiltration of myeloid-derived suppressor cells (MDSCs), T-regs and the decreased infiltration of CD8+ T cell in LUAD. Importantly, in vivo study verified that the infiltration of T-regs and MDSCs in tumor microenvironment (TME) of Xenograft tissues was decreased after SEMA4B silencing. CONCLUSIONS: These findings demonstrated SEMA4B might play an oncogenic role in LUAD progression, and be a promising therapeutic target for lung cancer.

Establishing an 8-gene immune prognostic model based on TP53 status for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) results in a majority of cancer burden worldwide. TP53 is the most commonly mutated in LUAD. This study aimed to reveal the relation between TP53 and tumor microenvironment (TME) for improving LUAD treatment. METHODS: Differentially expressed genes (DEGs) related to immunity were analyzed between TP53-WT and TP53-MUT groups. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to screen prognostic DEGs. Two independent datasets were included to evaluate the robustness of the prognostic model. RESULTS: An 8-gene prognostic model containing ANLN, CCNB1, DLGAP5, FAM83A, GJB2, NAPSA, SFTPB, and SLC2A1 was established based on DEGs. LUAD samples were classified into high- and low-risk groups with differential overall survival in the two datasets. M0 macrophages, M1 macrophages, and activated memory CD4 T cells were more enriched in high-risk group. Immune checkpoints of PDCD1, LAG3, and CD274 were also high-expressed in high-risk group. CONCLUSION: The study improved the understanding of the role of TP53 in the TME modulation. The 8-gene model had robust performance to predict LUAD prognosis in clinical practice. In addition, the eight prognostic genes may also serve as potential targets for designing therapeutic drugs for LUAD patients.

Comprehensive analysis of KCTD family genes associated with hypoxic microenvironment and immune infiltration in lung adenocarcinoma.

To obtain novel insights into the tumor biology and therapeutic targets of LUAD, we performed a comprehensive analysis of the KCTD family genes. The expression patterns and clinical significance of the KCTD family were identified through multiple bioinformatics mining. Moreover, the molecular functions and potential mechanisms of differentially expressed KCTDs were evaluated using TIMER 2.0, cBioPortal, GeneMANIA, LinkedOmics and GSEA. The results indicated that the mRNA and protein expression levels of KCTD9, KCTD10, KCTD12, KCTD15 and KCTD16 were significantly decreased in LUAD, while those of KCTD5 were significantly increased. High KCTD5 expression was significantly associated with advanced tumor stage, lymph node metastasis, TP53 mutation and poor prognosis. In addition, KCTD5 was positively correlated with CD8 + T cell, neutrophil, macrophage and dendritic cell infiltration. Additionally, KCTDs demonstrate promising prospects in the diagnosis of LUAD. Importantly, high KCTD5 expression was enriched in signaling pathways associated with the malignant progression of tumors, including the inflammatory response, the IL6/JAK/STAT3 signaling pathway, EMT and hypoxia. Further association analysis showed that KCTD5 was positively correlated with hypoxia-related genes such as HIF1. Overall, KCTDs can be used as molecular targets for the treatment of LUAD, as well as effective molecular biomarkers for diagnosis and prognosis prediction.

Immune Subtypes in LUAD Identify Novel Tumor Microenvironment Profiles With Prognostic and Therapeutic Implications.

The six transcriptomic immune subtypes (ISs) (C1 - C6) were reported to have complex and different interplay between TME and cancer cells in TCGA (The Cancer Genome Atlas) pan-cancer cohort. Our study specifically explored how the consequence of interplay determines the prognosis and the response to therapy in LUAD cohorts. Clinical and molecular information of LUAD patients were from TCGA and Gene Expression Omnibus (GEO). The immune cell populations and gene/pathway enrichment analysis were performed to explore the molecular differences among the C3 IS and other ISs in the LUAD population. The proportion of C3 inflammatory IS was identified as the most common IS in both TCGA (N = 457) and GEO (N = 901) cohorts. The C3 IS was also found to be the most accurate prognostic subtype, which was associated with significantly longer OS (p <0.001) and DFS (p <0.001). The C3 IS presented higher levels of CD8 T, M1 macrophage, and myeloid dendritic cells, while lower levels of M2 macrophages and cancer-associated fibroblast cells. Moreover, the C3 subtype was enriched in the antigen process and presenting, interferon-gamma response, T cell receptor signaling, and natural killer cell-mediated cytotoxicity pathways than C1/C2. In contrast, the C1/C2 presented greater activation of pathways related to the cell cycles, DNA repair, and p53 signaling pathways. The immune-related C3 IS had a great ability to stratify the prognosis of LUAD, providing clues for further pathogenic research. This classification might help direct precision medicine screenings of LUAD patients, thus possibly improving their prognoses.

Glutaminase inhibition impairs CD8 T cell activation in STK11-/Lkb1-deficient lung cancer.

The tumor microenvironment (TME) contains a rich source of nutrients that sustains cell growth and facilitate tumor development. Glucose and glutamine in the TME are essential for the development and activation of effector T cells that exert antitumor function. Immunotherapy unleashes T cell antitumor function, and although many solid tumors respond well, a significant proportion of patients do not benefit. In patients with KRAS-mutant lung adenocarcinoma, KEAP1 and STK11/Lkb1 co-mutations are associated with impaired response to immunotherapy. To investigate the metabolic and immune microenvironment of KRAS-mutant lung adenocarcinoma, we generated murine models that reflect the KEAP1 and STK11/Lkb1 mutational landscape in these patients. Here, we show increased glutamate abundance in the Lkb1-deficient TME associated with CD8 T cell activation in response to anti-PD1. Combination treatment with the glutaminase inhibitor CB-839 inhibited clonal expansion and activation of CD8 T cells. Thus, glutaminase inhibition negatively impacts CD8 T cells activated by anti-PD1 immunotherapy.