Prognosis Of Lung Adenocarcinoma Patients Research Articles

Upregulation and epigenetic modification of the creatine transporter SLC6A8 in non-small cell lung cancer.

Lung cancer is a major cause of cancer-related death worldwide and effective therapies, besides surgery, are available only for a small proportion of patients. Since cellular respiration is known to be broadly altered in malignant tumors, the cellular processes of respiration can be a potential therapeutic target. One important element of cellular respiration is creatine and its transport by the creatine transporter SLC6A8. Here we describe the expression of SLC6A8 at the RNA and protein level, epigenetic modifications as well as survival analysis in NSCLC tissues and matched controls. We analyzed epigenetic modifications of the SLC68A gene in 32 patients, of which 18 were additionally analyzed by transcriptome analysis. The expression of SLC6A8 at the protein level was assessed by immunohistochemistry using an independent cohort and correlated with clinicopathological data including survival. Kaplan-Meier analysis was performed to analyze the possible effects of the transcriptional levels of SLC6A8 in another separate cohort (n=1925). SLC6A8 loci are epigenetically modified in NSCLC compared with tumor-free controls. SLC6A8 is upregulated in NSCLC at the RNA and protein level. High mRNA expression of SLC6A8 was associated with an overall poor prognosis in lung adenocarcinoma patients and displayed the strongest adverse prognostic effect in male smokers with adenocarcinomas. Results of transcriptome analysis were partially confirmed at the protein level. Our results suggest an important role of creatine and its transport via SLC6A8 in NSCLC.

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature.

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma insitu (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

Downregulation of DIP2B as a prognostic marker inhibited cancer proliferation and migration and was associated with immune infiltration in lung adenocarcinoma via CCND1 and MMP2

BackgroundDIP2B is related to cancer progression. This study investigated the roles and pathways of DIP2B in lung adenocarcinoma (LUAD). MethodsDIP2B expression and the relationship between survival time of cancer patients and DIP2B expression were analyzed. The relationship between DIP2B expression and survival time in LUAD patients was evaluated by a meta-analysis. Cox and survival analyses were used to evaluate the prognostic factors and construct a prognostic nomogram. The mechanisms and effects of DIP2B and the relationship between DIP2B expression and the immune microenvironment were investigated using bioinformatics, CCK-8, western blotting, and transwell experiments. ResultsDIP2B was overexpressed in LUAD tissues. DIP2B overexpression was associated with shorter prognosis and was an unfavorable risk factor for prognosis in LUAD patients. DIP2B co-expressed genes were involved in cell division, DNA repair, cell cycle, and others. Inhibition of DIP2B expression could downregulate the proliferation, migration, and invasion of LUAD A549 and H1299 cells, which was related to the decrease in CCND1 and MMP2 protein expression. BRCA1 overexpression was associated with short prognosis, and the nomogram formed by DIP2B and BRCA1 was associated with a poor prognosis in LUAD patients. DIP2B expression correlated with immune cells (such as CD8 T cells, Tcm, and iDCs) and cell markers. ConclusionDIP2B is a potential biomarker of poor prognosis and the immune microenvironment in LUAD. Inhibition of DIP2B expression downregulated cancer cell proliferation, migration, and invasion, which might be related to the decrease in CCND1 and MMP2 protein expression. DIP2B-related nomograms might be useful tools for predicting the prognosis of LUAD patients.

Phosphorylation of LZTS2 by PLK1 activates the Wnt pathway

Lung adenocarcinoma (LUAD), responsible for nearly half of lung cancer cases, is one of the most prevalent and lethal malignant tumors globally. There is increasing evidence suggesting that the oncoprotein PLK1 plays a role in the onset and advancement of different types of cancer, including LUAD. Nonetheless, the precise mechanism by which PLK1 promotes tumorigenesis remains unclear. In this study, we demonstrate the upregulation of PLK1 in LUAD samples, which leads to a poor prognosis for LUAD patients. Intriguingly, PLK1 enables to bind to LZTS2 and promote its phosphorylation without affecting LZTS2 degradation. Furthermore, we identify that Ser451 is a key phosphorylation site in LZTS2 protein. LZTS2 exerts an anti-tumor effect by restricting the translocation of the transcription factor β-Catenin into the nucleus, thereby suppressing the Wnt pathway. PLK1 disrupts the interaction between LZTS2 and β-Catenin, resulting in the nuclear accumulation of β-Catenin and the activation of the Wnt pathway. Additionally, we reveal that LZTS2 inhibits the proliferation and migration of LUAD cells, which is rescued by PLK1. Finally, PLK1 inhibitors exhibit a dose-dependent suppression of LUAD cell proliferation and migration. Collectively, this study uncovers the pro-tumorigenic mechanism of PLK1, positioning it as a promising therapeutic target for Wnt-related LUAD.

Prognostic value of long noncoding RNA LINC00924 in lung adenocarcinoma and its regulatory effect on tumor progression.

Long non-coding RNAs (lncRNAs) have been used in the study of tumor biomarkers in recent years. However, the prognostic role of lncRNA LINC00924 (LINC00924) in lung adenocarcinoma (LUAD) has not yet been concluded. Therefore, this study investigates the prognostic value of LINC00924 in LUAD and its regulatory effect on tumor progression. The LUAD tissues and adjacent normal tissues of 128 subjects were extracted, and the expressions of LINC00924 and miR-196a-5p in tissues and cells were detected by RT-qPCR. The prognostic value of LINC00924 in LUAD patients was obtained by Kaplan-Meier analysis and multivariate Cox regression test. The cell counting kit-8 (CCK-8) and Transwell assay were used to detect the effect of overexpression LINC00924 on LUAD cells. In LUAD tissues and cells, LINC00924 expression was down-regulated and miR-196a-5p expression was up-regulated compared with the normal control group. High expression of LINC00924 inhibited the proliferation level, migration ability and invasion situation of LUAD cells, which was more conducive to the survival and prognosis of LUAD patients. Bioinformatics studies indicated that overexpression of LINC00924 inhibited the development of LUAD by targeting miR-196a-5p, while miR-196a-5p mimic effectively weakened the inhibition. LINC00924 sponges of miR-196a-5p may be considered as a potential prognostic biomarker for LUAD.

Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma.

There is a correlation between tumors and immunity with the degree of immune cell infiltration in tumors being closely related to tumor growth and progression. Therefore, the present study identified immune-related prognostic genes and evaluated the immune infiltration level in lung adenocarcinoma (LUAD). This study performed Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene Set Enrichment Analysis (GSEA) enrichment analyses on differential immune-associated genes. A risk model was created and validated using six immune-related prognostic genes. Reverse transcription-quantitative PCR was used to assess the prognostic gene expression in non-small cell lung cancer cells. Immune cell infiltration in LUAD was analyzed using the CIBERSORT method. Single sample GSEA was used to compare Tumor Immune Dysfunction and Exclusion (TIDE) scores between high and low-risk groups and to assess the activation of thirteen immune-related pathways. Multifactor Cox proportional hazards model analysis identified six prognostic risk genes (S100A16, FURIN, FGF2, LGR4, TNFRSF11A and VIPR1) to construct a risk model. The survival and receiver operating characteristic curves indicated that patients with higher risk scores had lower overall survival rates. The expression levels of prognostic genes S100A16, FURIN, LGR4, TNFRSF11A and VIPR1 were significantly increased in LUAD. B cells naive, plasma cells, T cells CD4 memory activated, T cells follicular helper, T cells regulatory, NK cells activated, macrophages M1, macrophages M2, and Dendritic cells resting cells showed elevated expression in LUAD. The prognostic genes were differentially associated with individual immune cells. Immune-related function scores, such as those for antigen presenting cell (APC) co-stimulation, APC co-inhibition, check-point, Cytolytic-activity, chemokine receptor, parainflammation, major histocompatibility complex-class-I, type-I-IFN-reponse and T-cell-co-inhibition, were higher in the high-risk group compared with the low-risk group. Furthermore, the TIDE score of the high-risk group was significantly lower than the low-risk group. This immune-related gene prognostic model has the potential to predict the prognosis of LUAD patients, supporting the development of a personalized clinical diagnosis and treatment plan.

TMEM9 promotes lung adenocarcinoma progression via activating the MEK/ERK/STAT3 pathway to induce VEGF expression

Abnormal Transmembrane protein 9 (TMEM9) expression has been identified in various human tumors. However, the prognostic potential and mechanistic role of TMEM9 in lung adenocarcinoma (LUAD) remain unclear. Here, we first found a significant upregulation of TMEM9 in LUAD tissues, and TMEM9 expression was positively correlated with microvessel density (MVD), T stage, and clinical stage. Survival analysis demonstrated TMEM9 was an independent indicator of poor prognosis in LUAD patients. In addition, downregulation of TMEM9 suppressed tumor growth and metastasis in vitro and in vivo models, and reduced HUVEC proliferation, migration, and tube formation in a cancer cell/HUVEC coculture model. Furthermore, TMEM9 upregulated VEGF expression, and VEGF-neutralizing antibodies reversed HUVEC angiogenesis and cancer cell migration ability caused by overexpression of TMEM9. In contrast, recombinant VEGF (rVEGF) abolished the inhibitory effect of TMEM9-knockdown LUAD cells on HUVEC angiogenesis and tumor cell migration. Moreover, we showed that TMEM9 upregulated VEGF expression by activating the mitogen-activated protein kinase/extracellular signal-regulated kinase/STAT3 (MEK/ERK/STAT3) pathway. Together, our study provides mechanistic insights into the role of TMEM9 in LUAD and highlights the potential of targeting the TMEM9/MEK/ERK/STAT3/VEGF pathway as a novel therapy for preventing LUAD progression.

FBXO32-mediated degradation of PTEN promotes lung adenocarcinoma progression.

FBXO32, a member of the F-box protein family, is known to play both oncogenic and tumor-suppressive roles in different cancers. However, the functions and the molecular mechanisms regulated by FBXO32 in lung adenocarcinoma (LUAD) remain unclear. Here, we report that FBXO32 is overexpressed in LUAD compared with normal lung tissues, and high expression of FBXO32 correlates with poor prognosis in LUAD patients. Firstly, we observed with a series of functional experiments that FBXO32 alters the cell cycle and promotes the invasion and metastasis of LUAD cells. We further corroborate our findings using in vivo mouse models of metastasis and confirmed that FBXO32 positively regulates LUAD tumor metastasis. Using a proteomic-based approach combined with computational analyses, we found a positive correlation between FBXO32 and the PI3K/AKT/mTOR pathway, and identified PTEN as a FBXO32 interactor. More important, FBXO32 binds PTEN via its C-terminal substrate binding domain and we also validated PTEN as a bona fide FBXO32 substrate. Finally, we demonstrated that FBXO32 promotes EMT and regulates the cell cycle by targeting PTEN for proteasomal-dependent degradation. In summary, our study highlights the role of FBXO32 in promoting the PI3K/AKT/mTOR pathway via PTEN degradation, thereby fostering lung adenocarcinoma progression.

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature.

The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promising therapeutic modality, demonstrating remarkable potential for substantially prolonging the overall survival of individuals afflicted with LUAD. However, there is currently a lack of reliable signatures for identifying patients who would benefit from immunotherapy. We conducted a comparative analysis of two immunotherapy cohorts (OAK and POPLAR) and utilized single-factor COX regression to identify genes that significantly impact the prognosis of LUAD. Based on the TCGA-LUAD dataset, we employed a combination of 101 machine learning algorithms to construct a model and selected the optimal model. The model was validated on five GEO datasets and compared with 144 previously published signatures to assess its performance. Subsequently, we explored the underlying biological mechanisms through tumor mutation burden analysis, enrichment analysis, and immune infiltration analysis. An immunotherapy prognostic prediction signature (IPPS) was constructed based on 13 genes, showing robust performance in the TCGA-LUAD dataset. IPPS exhibited consistent predictive accuracy in the validation cohorts. Compared to 144 previously published signatures, IPPS consistently ranked among the top in terms of C-index values. Further exploration revealed differences between high and low-IPPS groups in terms of tumor mutation burden, pathway enrichment, and immune infiltration. IPPS demonstrates strong predictive capabilities for the prognosis of LUAD patients, offering the potential to identify suitable candidates for immunotherapy and contribute to precision treatment strategies for LUAD.

Tumor lymphangiogenesis index reveals the immune landscape and immunotherapy response in lung adenocarcinoma.

Lymphangiogenesis (LYM) has an important role in tumor progression and is strongly associated with tumor metastasis. However, the clinical application of LYM has not progressed as expected. The potential value of LYM needs to be further developed in lung adenocarcinoma (LUAD) patients. The Sequencing data and clinical characteristics of LUAD patients were downloaded from The Cancer Genome Atlas and GEO databases. Multiple machine learning algorithms were used to screen feature genes and develop the LYM index. Immune cell infiltration, immune checkpoint expression, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and drug sensitivity analysis were used to explore the correlation of LYM index with immune profile and anti-tumor therapy. We screened four lymphangiogenic feature genes (PECAM1, TIMP1, CXCL5 and PDGFB) to construct LYM index based on multiple machine learning algorithms. We divided LUAD patients into the high LYM index group and the low LYM index group based on the median LYM index. LYM index is a risk factor for the prognosis of LUAD patients. In addition, there was a significant difference in immune profile between high LYM index and low LYM index groups. LUAD patients in the low LYM index group seemed to benefit more from immunotherapy based on the results of TIDE algorithm. Overall, we confirmed that the LYM index is a prognostic risk factor and a valuable predictor of immunotherapy response in LUAD patients, which provides new evidence for the potential application of LYM.

Prognostic Cell Death Index for Lung Adenocarcinoma: A Comprehensive Transcriptome-Based Analysis of Twelve Programmed Cell Death Pattern Genes.

Lung adenocarcinoma (LUAD) is a prominent contributor to global cancer mortality, characterized by constrained prognosis. This study aimed to develop a novel prognostic indicator, the Cell Death Index (CDI), utilizing twelve programmed cell death (PCD) pattern genes, to predict the immune infiltration and prognosis in LUAD patients. We collected PCD-related genes and identified prognostic PCD genes in the Cancer Genome Atlas (TCGA)-LUAD dataset, and made rigorous validation in the Clinical Proteomic Tumor Analysis Consortium (CPTAC)-LUAD cohorts. CDI was calculated using a multivariable Cox regression model. Functional enrichment and tumor microenvironment were evaluated. Drug sensitivity prediction and nomogram development were performed to assess CDI's potential value. The results revealed 10 PCD genes (ERO1A, CDK5R1, TRIM6, DNASE2B, ITPRIP, MRGPRX2, FGA, NDUFA13, NLRP2, and CD68) significantly associated with LUAD prognosis. The CDI was constructed and showed high accuracy in predicting patient survival with C-index values of 0.801 and 0.794 in the prognosis cohort and validation cohort, respectively. CDI is also indicative of variations in biological functions, tumor microenvironment, and immune cell infiltration including neutrophils, activated mast cells, activated dendritic cells, M0 macrophages, resting natural killer cells, γδT cells, and activated memory CD4+T cells. Furthermore, drug sensitivity analysis indicated potential targeted strategies. The CDI, based on PCD genes, serves as a robust prognostic tool for LUAD, offering profound insights into tumor biology, immune response, and personalized treatment strategies. This study underscores the pivotal role of PCD mechanisms in LUAD pathogenesis and identifies potential therapeutic targets.

Anoikis-related gene signatures predict prognosis of lung adenocarcinoma patients and reveal immune infiltration.

Lung adenocarcinoma (LUAD), a type of lung cancer, is one of the most aggressive and deadly malignancies worldwide. Malignant tumor cells exhibit strong anti-anoikis properties to achieve distant metastasis through the circulatory system. However, more research is needed to understand how anoikis is involved in the progression, metastasis and especially the prognosis of LUAD. We obtained anoikis-related genes (ARGs) from two websites, Harmonizome and Genecards, and integrated them to select and model the genes associated with LUAD prognosis. In addition, we investigated differences in the immune cell microenvironment and pathways of enrichment analysis between subtypes. We finally constructed a nomogram based on ARGs and used decision curve analysis (DCA) to demonstrate that this model could help clinicians make clinical decisions. Sixty-four differentially expressed genes (DEGs) were found to be associated with survival, and of these, six were chosen to build a prognostic model. The time-dependent receiver operating characteristic (ROC) curves showed that the model had a satisfactory predictive ability. Enrichment analysis and immune microenvironment analysis revealed that the immune status and drug sensitivity of populations at high and low risk were different. We integrated the clinicopathological features of LUAD with the risk score to build the nomogram. The nomogram was shown to be a good predictor of short- and long-term survival in LUAD patients through DCA analysis. This new model based on six ARGs and nomograms in our study could help patients with LUAD develop personalized treatment plans.

Identification and validation of tryptophan metabolism-related lncRNAs in lung adenocarcinoma prognosis and immune response

BackgroundTryptophan (Trp) is an essential amino acid. Increasing evidence suggests that tryptophan metabolism plays a complex role in immune escape from Lung adenocarcinoma (LUAD). However, the role of long non-coding RNAs (lncRNAs) in tryptophan metabolism remains to be investigated.MethodsThis study uses The Cancer Genome Atlas (TCGA)-LUAD dataset as the training cohort, and several datasets from the Gene Expression Omnibus (GEO) database are merged into the validation cohort. Genes related to tryptophan metabolism were identified from the Molecular Signatures Database (MSigDB) database and further screened for lncRNAs with Trp-related expression. Subsequently, a prognostic signature of lncRNAs related to tryptophan metabolism was constructed using Cox regression analysis, (Least absolute shrinkage and selection operator regression) and LASSO analysis. The predictive performance of this risk score was validated by Kaplan–Meier (KM) survival analysis, (receiver operating characteristic) ROC curves, and nomograms. We also explored the differences in immune cell infiltration, immune cell function, tumor mutational load (TMB), tumor immune dysfunction and exclusion (TIDE), and anticancer drug sensitivity between high- and low-risk groups. Finally, we used real-time fluorescence quantitative PCR, CCK-8, colony formation, wound healing, transwell, flow cytometry, and nude mouse xenotransplantation models to elucidate the role of ZNF8-ERVK3-1 in LUAD.ResultsWe constructed 16 tryptophan metabolism-associated lncRNA prognostic models in LUAD patients. The risk score could be used as an independent prognostic indicator for the prognosis of LUAD patients. Kaplan–Meier survival analysis, ROC curves, and risk maps validated the prognostic value of the risk score. The high-risk and low-risk groups showed significant differences in phenotypes, such as the percentage of immune cell infiltration, immune cell function, gene mutation frequency, and anticancer drug sensitivity. In addition, patients with high-risk scores had higher TMB and TIDE scores compared to patients with low-risk scores. Finally, we found that ZNF8-ERVK3-1 was highly expressed in LUAD tissues and cell lines. A series of in vitro experiments showed that knockdown of ZNF8-ERVK3-1 inhibited cell proliferation, migration, and invasion, leading to cell cycle arrest in the G0/G1 phase and increased apoptosis. In vivo experiments with xenografts have shown that knocking down ZNF8-ERVK3-1 can significantly inhibit tumor size and tumor proliferation.ConclusionWe constructed a new prognostic model for tryptophan metabolism-related lncRNA. The risk score was closely associated with common clinical features such as immune cell infiltration, immune-related function, TMB, and anticancer drug sensitivity. Knockdown of ZNF8-ERVK3-1 inhibited LUAD cell proliferation, migration, invasion, and G0/G1 phase blockade and promoted apoptosis.

A Novel Gene Signature Based on Immune Cell Infiltration Landscape Predicts Prognosis in Lung Adenocarcinoma Patients.

The tumor microenvironment (TME) is created by the tumor and dominated by tumor-induced interactions. Long-term survival of lung adenocarcinoma (LUAD) patients is strongly influenced by immune cell infiltration in TME. The current article intends to construct a gene signature from LUAD ICI for predicting patient outcomes. For the initial phase of the study, the TCGA-LUAD dataset was chosen as the training group for dataset selection. We found two datasets named GSE72094 and GSE68465 in the Gene Expression Omnibus (GEO) database for model validation. Unsupervised clustering was performed on the training cohort patients using the ICI profiles. We employed Kaplan-Meier estimators and univariate Cox proportional-hazard models to identify prognostic differentially expressed genes in immune cell infiltration (ICI) clusters. These prognostic genes are then used to develop a LASSO Cox model that generates a prognostic gene signature. Validation was performed using Kaplan-Meier estimation, Cox, and ROC analysis. Our signature and vital immune-relevant signatures were analyzed. Finally, we performed gene set enrichment analysis (GSEA) and immune infiltration analysis on our finding gene signature to further examine the functional mechanisms and immune cellular interactions. Our study found a sixteen-gene signature (EREG, HPGDS, TSPAN32, ACSM5, SFTPD, SCN7A, CCR2, S100P, KLK12, MS4A1, INHA, HOXB9, CYP4B1, SPOCK1, STAP1, and ACAP1) to be prognostic based on data from the training cohort. This prognostic signature was certified by Kaplan-Meier, Cox proportional-hazards, and ROC curves. 11/15 immune-relevant signatures were related to our signature. The GSEA results indicated our gene signature strongly correlates with immune-related pathways. Based on the immune infiltration analysis findings, it can be deduced that a significant portion of the prognostic significance of the signature can be attributed to resting mast cells. We used bioinformatics to determine a new, robust sixteen-gene signature. We also found that this signature's prognostic ability was closely related to the resting mast cell infiltration of LUAD patients.

Abstract 4372: Epithelial-to-mesenchymal transition-driven secretory program underlies vulnerabilities in lung cancer

Abstract Epithelial-to-mesenchymal transition (EMT) is a driving force behind lung adenocarcinoma (LUAD) progression. Although substantial evidence has been attained in the involvement of EMT and its regulatory mechanisms in cancer, few effective EMT-targeted therapies have been available in the clinic thus far. It is urgent to develop new therapeutic strategies for improving patient outcomes. We have identified RAB6A as a master regulator of EMT-driven secretory trafficking, which coordinates cancer cell invasion and immunosuppression in LUAD. We found that RAB6A expression was associated with a poor prognosis in LUAD patients and that RAB6A inhibition in our LUAD models reversed resistance to immune checkpoint inhibition with PD-L1 blockade, an emerging clinical problem. Thus, RAB6A machinery is a therapeutic target of interest in EMT-driven cancers. Screening approaches to identify selective RAB inhibitors are in their infancy, a challenge that can be overcome only by obtaining insights into the regulation of RAB6A. RAB6A is a small GTPase whose activity is controlled by guanine nucleotide exchange factors (GEFs) like RIC1 and RGP1, and GTPase activating proteins (GAPs) like RABGAP1, as well as other effector proteins. While these GEFs, GAPs, and effectors are all known regulators of RAB6A function and are frequently amplified in different cancer types, their specific functions in cancer progression are still unknown. To establish the causal relationship between these proteins and EMT-driven LUAD progression, we utilize human and murine LUAD cell lines that have been characterized with respect to EMT status. Our findings here show that the intervention of RAB6A activity via depletion of these regulators impairs the recruitment of RAB6A to the Golgi. We demonstrate that knocking down the GEFs, RIC1 and RGP1, significantly decreases invasion while having negligible effects on the migrative and proliferative abilities of these cells. RABGAP1 depletion, on the other hand, reduces cell proliferation but has no effects on the migration and invasion of the cells. Consistent with these results, inactivation of RAB6A abolishes the EMT-dependent pro-metastatic secretion. Mechanistically, the EMT activator, ZEB1, upregulates RGP1 via silencing miR-148a that targets this GEF to activate RAB6A. These findings elucidate the regulatory mechanisms underlying the EMT-driven secretory program, providing a foundation for therapeutic intervention to prevent the progression of LUAD. Citation Format: Kevin L. Fulp, Oluwafunminiyi E. Obaleye, Guan-Yu Xiao. Epithelial-to-mesenchymal transition-driven secretory program underlies vulnerabilities in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4372.

Abstract 5047: Identifying genomic features associated with pathologic lymph node metastasis in lung adenocarcinoma patients

Abstract Introduction: Lymph node metastasis evaluation in solid tumors is mainly complicated by the diagnostic yield of standard imaging modalities and tumor size contradictions. Exploring clinical/molecular features that complement the use of radiologic and bronchoscopy findings may provide significant values for a more accurate pathologic determination of nodal metastasis. Methods: We analyzed surgery-resected tumor samples from 72 treatment-naïve lung adenocarcinoma (LUAD) patients via whole-exome sequencing (WES). Mutational profiles of patients categorized based on their pathologic lymph node metastasis (pN) status were assessed, and the association between metastatic-driving features and overall survival (OS) was then explored in both the study cohort and the Cancer Genome Atlas Program (TCGA) external cohort. Results: Among all 72 patients, 41 (56.9%) were pathologically confirmed as positive for lymph node metastasis (pN-positive), while 31 (43.1%) were categorized as pN-negative. The most frequently mutated gene was TP53 in both subgroups (54.8% and 53.7%, respectively), and the aberrant KEAP1-NRF2 signaling pathway was found significantly more enriched in pN-negative patients. Copy-number variant analysis showed that chromosome 7p amplifications (X7p_amp) at the arm level and EGFR amplifications at the focal gene level were more frequently identified in pN-positive patients (P=0.008 and P=0.004, respectively). Importantly, these amplifications were associated with worse OS in both the study cohort and the TCGA external dataset. Consistent with the unfavorable prognosis, pN-positive patients demonstrated a higher chromosome instability score (CIS) (median: 0.32 vs. 0.14, P=0.14) and a lower tumor mutation burden (TMB) (median: 1.83 vs. 3.85 muts/Mb, P=0.048) compared to pN-negative patients. Conclusion: Our findings suggest that X7p_amp, particularly EGFR amplification, might be associated with pathologic involvement of lymph nodes and an unfavorable prognosis in LUAD patients. Our study highlights the importance of integrating clinical and genomic data into conventional radiologic modalities for a more accurate determination of pathologic nodal involvement. Citation Format: Shijie Wang, Zhiwei Zhou, Song Wang, Rongyun Guo, Zeming Ma, Dachuan Zhao, Liang Wang, Yinan Liu, Yuanyuan Ma, Jianzhi Zhang, Sha Wang, Yedan Chen, Haimeng Tang, Qiuxiang Ou, Jinfeng Chen. Identifying genomic features associated with pathologic lymph node metastasis in lung adenocarcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5047.

Abstract 205: Adaptive membrane trafficking activated by epithelial-to-mesenchymal transition drives lung adenocarcinoma progression

Abstract Cancer cells can become metastatic and develop resistance to targeted therapies through epithelial-to-mesenchymal transition (EMT), which is regulated by epigenetic factors. Our ultimate objective is to understand the molecular mechanisms behind EMT-driven cancer progression and identify potential targets for preventing cancer metastasis. Recently, we made groundbreaking discoveries indicating that EMT can modify membrane trafficking machinery to coordinate cancer cell invasion and immunosuppression in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD). To dissect the “adaptive” membrane trafficking program, we initiated a CRISPRi in vivo screen to assess more than 2000 trafficking-related genes in syngeneic mouse LUAD models for their requirements for tumorigenesis both with and without immune selective pressure. We identified a panel of membrane trafficking regulators that specifically “dropped out” in immunocompetent mice, suggesting their essential roles in the immunosuppressive TME. Of particular interest is REEP2. REEPs are an evolutionarily conserved protein family that is critical to the endoplasmic reticulum (ER) function and potentially regulates secretory trafficking. We discovered that REEP2 is specifically linked to poor prognosis in LUAD patients and is highly correlated with a z-normalized, 16-gene EMT score (P = 1.32e-27) that was previously reported. Our previous studies demonstrated that the EMT activator, ZEB1, accelerates membrane trafficking dynamics by silencing a microRNA network that targets multiple membrane trafficking components. Analysis of REEP2 3’-untranslated regions (3’-UTRs) identified predicted binding sites for several microRNAs, which are silenced by ZEB1. Thus, we hypothesize that ZEB1 coordinates a microRNA network to activate REEP2-driven ER trafficking. We show that REEP2 depletion significantly reduces the invasion of cancer cells but does not affect their migration and proliferation. These findings suggest that REEP2 plays a significant role in extracellular matrix (ECM) modification to enhance the invasion of metastatic cells, conferring a vulnerability in EMT-driven LUAD metastasis. Citation Format: Oluwafunminiyi E. Obaleye, Kevin L. Fulp, Guan-Yu Xiao. Adaptive membrane trafficking activated by epithelial-to-mesenchymal transition drives lung adenocarcinoma progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 205.

Abstract 6219: Type V collagen promotes lung adenocarcinoma metastasis by regulating tumor mechanical stress and the implication for prognosis and therapeutic strategies

Abstract Introduction: The mechanical environment of the human body influences physiological and pathological processes, and understanding these biomechanical aspects holds promise for medical research. Tumor microenvironment changes, including extracellular matrix (ECM) alterations, result the changing of mechanical characteristics of the tissue, play a crucial role in cancer progression and metastasis, including lung adenocarcinoma (LUAD), one of a major histology type of lung cancer. This study focuses on elucidating how mechanical characteristics, especially those related to the ECM, influence LUAD and the signaling pathways involved. Methods: Cell culture, transfection, Western blot, immunofluorescence, immunohistochemistry, Transwell assay, scratch wound-healing assay were used to investigate the behavior changes of LUAD cells under different treatment. Bioinformatics analyses, and machine learning-based integrative approaches were employed to build the SVM_Score, which was built with relevant base membrane (BM) genes. Patient-derived tumor organoids, myofibroblasts, and co-culture systems were established. Sorafenib, which can inhibited collagen and fibronectin synthesis, was used to explore the proliferation and migration changing of lung cancer cells co-cultured with myofibroblasts. Results: Mechanical stress, simulated by matrix application, enhanced LUAD cell migration and invasion, correlating with ECM alterations and EMT pathway activation. SVM_Score predicted LUAD patient prognosis and EMT propensity across multiple datasets, revealing its robust prognostic capabilities. Lower SVM_Scores were associated with worse survival outcomes, increased cancer-related pathways, higher Tumor Mutation Burden and altered immune microenvironment characteristics. SVM_Score was also linked to myofibroblast-secreted COL5A1, a key marker for mechanical stress. Patient tissues with low SVM_Scores exhibited higher COL5A1 expression, enhanced EMT propensity, and increased internal mechanical stress. Sorafenib, by inhibiting COL5A1 secretion, attenuated the pro-tumor effects of myofibroblasts, inhibiting proliferation and migration of LUAD cells, and rendering LUAD cells more sensitive to chemotherapy. Conclusion: This comprehensive study unveils the intricate relationship between mechanical stress, ECM alterations, and LUAD progression. SVM_Score emerges as a potent prognostic tool, reflects tumor mechanical characteristics. Sorafenib intervention targeting COL5A1 secretion provides a potential therapeutic strategy to mitigate LUAD aggressiveness. These findings contribute to a deeper understanding of the biomechanical aspects of LUAD, offering insights for future research and clinical applications. Citation Format: Guangsheng Zhu, Yanan Wang, Yingjie Wang, Chen, Yongwen Li, Hongyu Liu, Jun Chen. Type V collagen promotes lung adenocarcinoma metastasis by regulating tumor mechanical stress and the implication for prognosis and therapeutic strategies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6219.

Over-Expression of EFNA2 in Lung Adenocarcinoma: EFNA2 Gene Expression Correlates with Shortened Survival

Background: The incidence of lung adenocarcinoma (LUAD) is increasing worldwide with different prognosis. Ephrin-A2（EFNA2), a member of the Eph/ephrin family, is associated with tumor progression. However, the correlations of EFNA2 with prognosis in LUAD remain unclear. The purpose of this article is to analyze the impact of EFNA2 on the prognosis of LUAD patients through TCGA, Oncomine, and GEPIA databases, and to explore its possible mechanisms. Methods: This article found a significant correlation between EFNA2 and shortened survival in LUAD patients through TCGA, Oncomine, and GEPIA database analysis. Therefore, we further invested the relationship between the expression and prognostic value of the EFNA2 gene in LUAD patients. Sequential data filtering (survival analysis, independent prognostic analysis, and clinicalcorrelation analysis) was performed. EFNA2 expression was analyzed by the Oncomine database and Tumor Immune Estimation Resource (TIMER). We evaluated the influence of EFNA2 on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). The correlation between EFNA2 and cancer immune infiltrates was investigated by TIMER. In addition, correlations between EFNA2 expression and gene marker sets of immune infiltrates were analyzed by TIMER and GEPIA. In addition, gene enrichment analysis was performed by Metascape. Finally, a co-expression analysis was performed by the Oncomine database. Results: A cohort of LUAD patients showed that high EFNA2 expression was associated with poorer overall survival (OS), disease-free survival (DFS) by TCGA, and EFNA2 was significantly associated with stage in LUAD. In addition, EFNA2 expression was positively correlated with infiltrating levels of B cells and CD8+ T cells. Moreover, the differential expression of EFNA2 was significantly higher in lung adenocarcinoma compared with that in normal controls. Specifically, EFNA2 was positively associated with ADAMTSL5, REEP6, PCSK4, C19orf25, and ANAPC2. Conclusions: Our data indicate that EFNA2 is a potential diagnostic and prognostic biomarker and a promising molecular therapeutic target to attenuate LUAD progression.

NEAT1_1 confers gefitinib resistance in lung adenocarcinoma through promoting AKR1C1-mediated ferroptosis defence

Gefitinib is one of the most extensively utilized epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) for treating advanced lung adenocarcinoma (LUAD) patients harboring EGFR mutation. However, the emergence of drug resistance significantly compromised the clinical efficacy of EGFR-TKIs. Gaining further insights into the molecular mechanisms underlying gefitinib resistance holds promise for developing novel strategies to overcome the resistance and improve the prognosis in LUAD patients. Here, we identified that the inhibitory efficacy of gefitinib on EGFR-mutated LUAD cells was partially dependent on the induction of ferroptosis, and ferroptosis protection resulted in gefitinib resistance. Among the ferroptosis suppressors, aldo-keto reductase family 1 member C1 (AKR1C1) exhibited significant upregulation in gefitinib-resistant strains of LUAD cells and predicted poor progression-free survival (PFS) and overall survival (OS) of LUAD patients who received first-generation EGFR-TKI treatment. Knockdown of AKR1C1 partially reversed drug resistance by re-sensitizing the LUAD cells to gefitinib-mediated ferroptosis. The decreased expression of miR-338-3p contributed to the aberrant upregulation of AKR1C1 in gefitinib-resistant LUAD cells. Furthermore, upregulated long non-coding RNA (lncRNA) nuclear paraspeckle assembly transcript 1_1 (NEAT1_1) sponged miR-338-3p to neutralize its suppression on AKR1C1. Dual-luciferase reporter assay and miRNA rescue experiment confirmed the NEAT1_1/miR-338-3p/AKR1C1 axis in EGFR-mutated LUAD cells. Gain- and loss-of-function assays demonstrated that the NEAT1_1/miR-338-3p/AKR1C1 axis promoted gefitinib resistance, proliferation, migration, and invasion in LUAD cells. This study reveals the effects of NEAT1_1/miR-338-3p/AKR1C1 axis-mediated ferroptosis defence in gefitinib resistance in LUAD. Thus, targeting NEAT1_1/miR-338-3p/AKR1C1 axis might be a novel strategy for overcoming gefitinib resistance in LUAD harboring EGFR mutation.