Identification of theranostic factors for patients developing metastasis after surgery for early-stage lung adenocarcinoma

AQP4-AS1 Can Regulate the Expression of Ferroptosis-Related Regulator ALOX15 through Competitive Binding with miR-4476 in Lung Adenocarcinoma

Background  The AQP4-AS1/miR-4476-ALOX15 regulatory axis was discovered in previous studies. We aimed to investigate the regulatory mechanism of the ferroptosis-related regulator ALOX15 by AQP4-AS1 and miR-4476 in lung adenocarcinoma (LUAD) and find new targets for clinical treatment. Methods  After bioinformatics analysis, we contained one ferroptosis-related gene (FRG), namely ALOX15. MicroRNAs (miRNAs) and long noncoding RNAs were predicted by miRWalk. Furthermore, we constructed overexpressed LUAD cell lines. Real-time quantitative polymerase chain reaction and western blot were used to determine the expression of mRNA and protein, respectively. Cell Counting Kit-8 (CCK-8) and EdU assay were used to detect the cell proliferation. Double luciferase assay was used to detect the binding relationship between AQP4-AS1 and miR-4464. Results  ALOX15 was the most significantly downregulated FRG compared with normal tissues. Furthermore, protein-protein interaction network analysis indicated that the AQP4-AS1-miR-4476-ALOX15 regulatory axis might be involved in the occurrence and development of LUAD and there might be direct interaction between AQP4-AS1 and miR-4476, and miR-4476 and ALOX15. Furthermore, AQP4-AS1 and ALOX15 were significantly downregulated in the LUAD tissue and cell lines, whereas miR-4476 showed the opposite results ( p  < 0.001). AQP4-AS1 overexpression improved the ALOX15 expression in LUAD cell lines. CCK-8 and EdU assay revealed that overexpression of AQP4-AS1 and ALOX15 inhibited the LUAD cell proliferation. Double luciferase assay results indicated that there was a combination between AQP4-AS1 and miRNA-4476. In addition, we found that overexpressed AQP4-AS1 activates the ferroptosis in LUAD cell lines. Conclusions  AQP4-AS1 can regulate the expression of ALOX15 through competitive binding with miR-4476, further activate ferroptosis and inhibit the proliferation of LUAD cells.

ADAM9 drives the immunosuppressive microenvironment by cholesterol biosynthesis-mediated activation of IL6-STAT3 signaling for lung tumor progression

Chronic inflammation associated with lung cancers contributes to immunosuppressive tumor microenvironments, reducing CD8+ T-cell function and leading to poor patient outcomes. A disintegrin and metalloprotease domain 9 (ADAM9) promotes cancer progression. Here, we aim to elucidate the role of ADAM9 in the immunosuppressive tumor microenvironment. A bioinformatic analysis of TIMER2.0 was used to investigate the correlation of ADAM9 and to infiltrate immune cells in the human lung cancer database and mouse lung tumor samples. Flow cytometry, immunohistochemistry, and RNA sequencing (RNA-seq) were performed to investigate the ADAM9-mediated immunosuppressive microenvironment. The coculture system of lung cancer cells with immune cells, cytokine array assays, and proteomic approach was used to investigate the mechanism. By analyzing the human LUAD database and the mouse lung cancer models, we showed that ADAM9 was associated with the immunosuppressive microenvironment. Additionally, ADAM9 released IL6 protein from cancer cells to inhibit IL12p40 secretion from dendritic cells, therefore leading to dendritic cell dysfunction and further affecting T-cell functions. Proteomic analysis indicated that ADAM9 promoted cholesterol biosynthesis and increased IL6-STAT3 signaling. Mechanistically, ADAM9 reduced the protein stability of LDLR, resulting in reduced cholesterol uptake and induced cholesterol biosynthesis. Moreover, LDLR reduction enhanced IL6-STAT3 activation. We reveal that ADAM9 has a novel biological function that drives the immunosuppressive tumor microenvironment by linking lung cancer's metabolic and signaling axes. Thus, by targeting ADAM9 an innovative and promising therapeutic opportunity was indicated for regulating the immunosuppression of lung cancer.

Inhibition of ADAM9 promotes the selective degradation of KRAS and sensitizes pancreatic cancers to chemotherapy

Kirsten rat sarcoma virus (KRAS) signaling drives pancreatic ductal adenocarcinoma (PDAC) malignancy, which is an unmet clinical need. Here, we identify a disintegrin and metalloproteinase domain (ADAM)9 as a modulator of PDAC progression via stabilization of wild-type and mutant KRAS proteins. Mechanistically, ADAM9 loss increases the interaction of KRAS with plasminogen activator inhibitor 1 (PAI-1), which functions as a selective autophagy receptor in conjunction with light chain 3 (LC3), triggering lysosomal degradation of KRAS. Suppression of ADAM9 by a small-molecule inhibitor restricts disease progression in spontaneous models, and combination with gemcitabine elicits dramatic regression of patient-derived tumors. Our findings provide a promising strategy to target the KRAS signaling cascade and demonstrate a potential modality to enhance sensitivity to chemotherapy in PDAC.

Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies

BACKGROUND

This study aimed to identify metabolic subtypes in ESCA, explore their relationship with immune landscapes, and establish a metabolic index for accurate prognosis assessment.

METHODS

Clinical, SNP, and RNA-seq data were collected from 80 ESCA patients from the TCGA database and RNA-seq data from the GSE19417 dataset. Metabolic genes associated with overall survival (OS) and progression-free survival (PFS) were selected, and k-means clustering was performed. Immune-related pathways, immune infiltration, and response to immunotherapy were predicted using bioinformatic algorithms. Weighted gene co-expression network analysis (WGCNA) was conducted to identify metabolic genes associated with co-expression modules. Lastly, cell culture and functional analysis were performed using patient tissue samples and ESCA cell lines to verify the identified genes and their roles.

RESULTS

Molecular subtypes were identified based on the expression profiles of metabolic genes, and univariate survival analysis revealed 163 metabolic genes associated with ESCA prognosis. Consensus clustering analysis classified ESCA samples into three distinct subtypes, with MC1 showing the poorest prognosis and MC3 having the best prognosis. The subtypes also exhibited significant differences in immune cell infiltration, with MC3 showing the highest scores. Additionally, the MC3 subtype demonstrated the poorest response to immunotherapy, while the MC1 subtype was the most sensitive. WGCNA analysis identified gene modules associated with the metabolic index, with SLC5A1, NT5DC4, and MTHFD2 emerging as prognostic markers. Gene and protein expression analysis validated the upregulation of MTHFD2 in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.

CONCLUSION

The established metabolic index and identified metabolic genes offer potential for prognostic assessment and personalized therapeutic interventions for ESCA, underscoring the importance of targeting metabolism-immune interactions in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.

The key cellular senescence related molecule RRM2 regulates prostate cancer progression and resistance to docetaxel treatment

BACKGROUND

Prostate cancer is a leading cause of cancer-related deaths among men worldwide. Docetaxel chemotherapy has proven effective in improving overall survival in patients with castration-resistant prostate cancer (CRPC), but drug resistance remains a considerable clinical challenge.

METHODS

We explored the role of Ribonucleotide reductase subunit M2 (RRM2), a gene associated with senescence, in the sensitivity of prostate cancer to docetaxel. We evaluated the RRM2 expression, docetaxel resistance, and ANXA1 expression in prostate cancer cell lines and tumour xenografts models. In addition, We assessed the impact of RRM2 knockdown, ANXA1 over-expression, and PI3K/AKT pathway inhibition on the sensitivity of prostate cancer cells to docetaxel. Furthermore, we assessed the sensitivity of prostate cancer cells to the combination treatment of COH29 and docetaxel.

RESULTS

Our results demonstrated a positive association between RRM2 expression and docetaxel resistance in prostate cancer cell lines and tumor xenograft models. Knockdown of RRM2 increased the sensitivity of prostate cancer cells to docetaxel, suggesting its role in mediating resistance. Furthermore, we observed that RRM2 stabilizes the expression of ANXA1, which in turn activates the PI3K/AKT pathway and contributes to docetaxel resistance. Importantly, we found that the combination treatment of COH29 and docetaxel resulted in a synergistic effect, further augmenting the sensitivity of prostate cancer cells to docetaxel.

CONCLUSION

Our findings suggest that RRM2 regulates docetaxel resistance in prostate cancer by stabilizing ANXA1-mediated activation of the PI3K/AKT pathway. Targeting RRM2 or ANXA1 may offer a promising therapeutic strategy to overcome docetaxel resistance in prostate cancer.

Development and validation of a nomogram based on preoperative variables for predicting recurrence-free survival in stage IA lung adenocarcinoma

BACKGROUND

This study aimed to establish a nomogram for predicting risk of recurrence and provide a model for decision-making between lobectomy and sublobar resection in patients with stage IA lung adenocarcinoma.

METHODS

Patients diagnosed with stage IA lung adenocarcinoma (LUAD) between December 2010 and October 2018 from Cancer Hospital Chinese Academy of Medical Sciences were included. Patients were randomly assigned to training and validation cohorts, accounting for 70% and 30% of the total cases, respectively. We collected laboratory variables before surgery. Univariate and multivariate analyses were performed in the training cohort to identify variables significantly associated with recurrence-free survival (RFS) which were subsequently used to construct a nomogram. Validation was conducted in both cohorts. A receiver operating characteristic curve was used to determine the optional cutoff values of the scores calculated from the nomogram. Patients were then divided into low- and high-risk groups. Survival was performed to determine if the nomogram could guide the operation method.

RESULTS

A total of 543 patients were included in this study. Gender, albumin level, carcinoembryonic antigen level and cytokeratin-19-fragment level were included in the nomogram. In both cohorts, the nomogram stratified the patients into high- and low-risk groups in terms of RFS. In particular, there was a significant difference in RFS between lobectomy and sublobar resection in the high-risk group.

CONCLUSIONS

Gender, albumin level, carcinoembryonic antigen level and cytokeratin-19-fragment level are valuable markers in predicting recurrence and can guide surgical practice in patients with stage IA LUAD.

MTHFD2 promotes PD-L1 expression via activation of the JAK/STAT signalling pathway in bladder cancer

Although combination chemotherapy is widely used for bladder cancer (BC) treatment, the recurrence and progression rates remain high. Therefore, novel therapeutic targets are required. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) contributes to tumourigenesis and immune evasion in several cancers; however, its biological function in BC remains unknown. This study aimed to investigate the expression, prognostic value and protumoural function of MTHFD2 in BC and elucidate the mechanism of programmed death-ligand 1 (PD-L1) upregulation by MTHFD2. An analysis using publicly available databases revealed that a high MTHFD2 expression was correlated with clinical features and a poor prognosis in BC. Furthermore, MTHFD2 promoted the growth, migration, invasion and tumourigenicity and decreased the apoptosis of BC cells in vivo and in vitro. The results obtained from databases showed that MTHFD2 expression was correlated with immune infiltration levels, PD-L1 expression, and the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway. The expression of MTHFD2, PD-L1 and JAK/STAT signalling pathway-related proteins increased after interferon gamma treatment and decreased after MTHFD2 knockdown. Moreover, addition of a JAK/STAT pathway activator partially reduced the effect of MTHFD2 knockdown on BC cells. Collectively, our findings suggest that MTHFD2 promotes the expression of PD-L1 through the JAK/STAT signalling pathway in BC.

The hypoxia-associated genes in immune infiltration and treatment options of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a common lung cancer with a poor prognosis under standard chemotherapy. Hypoxia is a crucial factor in the development of solid tumors, and hypoxia-related genes (HRGs) are closely associated with the proliferation of LUAD cells.

Methods

In this study, LUAD HRGs were screened, and bioinformatics analysis and experimental validation were conducted. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to gather LUAD RNA-seq data and accompanying clinical information. LUAD subtypes were identified by unsupervised cluster analysis, and immune infiltration analysis of subtypes was conducted by GSVA and ssGSEA. Cox regression and LASSO regression analyses were used to obtain prognosis-related HRGs. Prognostic analysis was used to evaluate HRGs. Differences in enrichment pathways and immunotherapy were observed between risk groups based on GSEA and the TIDE method. Finally, RT-PCR and in vitro experiments were used to confirm prognosis-related HRG expression in LUAD cells.

Results

Two hypoxia-associated subtypes of LUAD were distinguished, demonstrating significant differences in prognostic analysis and immunological characteristics between subtypes. A prognostic model based on six HRGs (HK1, PDK3, PFKL, SLC2A1, STC1, and XPNPEP1) was developed for LUAD. HK1, SLC2A1, STC1, and XPNPEP1 were found to be risk factors for LUAD. PDK3 and PFKL were protective factors in LUAD patients.

Conclusion

This study demonstrates the effect of hypoxia-associated genes on immune infiltration in LUAD and provides options for immunotherapy and therapeutic strategies in LUAD.

Fibroblast Growth Factor 11 Enables Tumor Cell Immune Escape by Promoting T Cell Exhaustion and Predicts Poor Prognosis in Patients with Lung Adenocarcinoma

Fibroblast growth factor 11 (FGF11) accelerates tumor proliferation in a variety of cancer types. This study aimed to examine the link between FGF11 and the prognosis of lung adenocarcinoma. FGF11 was searched in the Tumor Cancer Genome Atlas (TCGA) and ImmProt databases. The link between FGF11 and lung cancer clinical data was investigated using TCGA and Kaplan-Meier (KM)-plotter databases, and we developed a prediction model. Putative mechanisms of action were investigated using Gene Ontology (GO) and KEGG enrichment analyses. The GeneMANIA and STRING databases were used to search for genes that interact with FGF11, and the Tumor Immune Estimation Resource (TIMER) database was used to discover connections between FGF11 and immune cells, as well as any correlations with immune-related genes. We found that FGF11 expression was higher in the lung adenocarcinoma tissue than in the paracancerous tissue, and patients with high FGF11 expression had a lower overall survival, progression-free survival, and disease specific survival rate than those with low FGF11 expression. The expression of FGF11 was inversely linked to six types of infiltrating immune cells in the TIMER database and was associated with EGFR, VEGFA, BRAF, and MET expressions. The FGF11 gene is negatively correlated with the expression of most immune cells, mainly with various functional T cells including Th1, Th1-like, Treg, and Resting Treg characterization genes. These results indicate that FGF11 has the potential to be a new lung adenocarcinoma biomarker. It increases tumor cell immune escape by boosting T cell exhaustion in the tumor microenvironment, contributing to the poor prognosis of the patients with lung adenocarcinoma. These results provide incentive to further research FGF11 as a possible biomarker and drug target for patients with lung adenocarcinoma.

Significance of macrophage infiltration in the prognosis of lung adenocarcinoma patients evaluated by scRNA and bulkRNA analysis

Purpose

To investigate the significance of macrophage infiltration to the prognosis of lung adenocarcinoma.

Methods

R language bioinformatics analysis technology, was used to obtain macrophage infiltration-related module genes through WGCNA (Weighted Gene Co-Expression Network Analysis). Marker genes of macrophage subtypes were identified using single-cell sequencing of lung adenocarcinoma tissue. Risk score models were constructed and validated using external data cohorts and clinical samples.

Results

Analysis of cohorts TCGA-LUAD, GSE11969, GSE31210, GSE50081, GSE72094 and GSE8894, revealed a negative correlation between macrophage infiltration and survival. Immunohistochemical analyses of clinical samples were consistent with these data. Based on cell-cluster-markers and TAMs-related-genes, TOP8 genes were obtained (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, and TK1) with a significant association to prognosis. Risk score models including 9 factors (C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65) for prognosis were constructed. The efficacy, stability and generalizability of the risk score models were validated using multiple data cohorts (GSE19188, GSE26939, GSE31210, GSE50081, GSE42127, and GSE72094).

Conclusions

Macrophage infiltration negatively correlates with prognosis in patients with lung adenocarcinoma. Based on cell-cluster-markers and TAMs-related-genes, both TOP8 genes (C1QTNF6, CCNB1, FSCN1, HMMR, KPNA2, PRC1, RRM2, TK1) and risk score models using C1QTNF6, FSCN1, KPNA2, GLI2, TYMS, BIRC3, RBBP7, KRT8, GPR65 could predict disease prognosis.

A novel epithelial-mesenchymal transition (EMT)-related gene signature of predictive value for the survival outcomes in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a remarkably heterogeneous and aggressive disease with dismal prognosis of patients. The identification of promising prognostic biomarkers might enable effective diagnosis and treatment of LUAD. Aberrant activation of epithelial-mesenchymal transition (EMT) is required for LUAD initiation, progression and metastasis. With the purpose of identifying a robust EMT-related gene signature (E-signature) to monitor the survival outcomes of LUAD patients. In The Cancer Genome Atlas (TCGA) database, least absolute shrinkage and selection operator (LASSO) analysis and cox regression analysis were conducted to acquire prognostic and EMT-related genes. A 4 EMT-related and prognostic gene signature, comprising dickkopf-like protein 1 (DKK1), lysyl oxidase-like 2 (LOXL2), matrix Gla protein (MGP) and slit guidance ligand 3 (SLIT3), was identified. By the usage of datum derived from TCGA database and Western blotting analysis, compared with adjacent tissue samples, DKK1 and LOXL2 protein expression in LUAD tissue samples were significantly higher, whereas the trend of MGP and SLIT3 expression were opposite. Concurrent with upregulation of epithelial markers and downregulation of mesenchymal markers, knockdown of DKK1 and LOXL2 impeded the migration and invasion of LUAD cells. Simultaneously, MGP and SLIT3 silencing promoted metastasis and induce EMT of LUAD cells. In the TCGA-LUAD set, receiver operating characteristic (ROC) analysis indicated that our risk model based on the identified E-signature was superior to those reported in literatures. Additionally, the E-signature carried robust prognostic significance. The validity of prediction in the E-signature was validated by the three independent datasets obtained from Gene Expression Omnibus (GEO) database. The probabilistic nomogram including the E-signature, pathological T stage and N stage was constructed and the nomogram demonstrated satisfactory discrimination and calibration. In LUAD patients, the E-signature risk score was associated with T stage, N stage, M stage and TNM stage. GSEA (gene set enrichment analysis) analysis indicated that the E-signature might be linked to the pathways including GLYCOLYSIS, MYC TARGETS, DNA REPAIR and so on. In conclusion, our study explored an innovative EMT based prognostic signature that might serve as a potential target for personalized and precision medicine.

Comprehensive analysis of a novel signature incorporating lipid metabolism and immune-related genes for assessing prognosis and immune landscape in lung adenocarcinoma

Background

As the crosstalk between metabolism and antitumor immunity continues to be unraveled, we aim to develop a prognostic gene signature that integrates lipid metabolism and immune features for patients with lung adenocarcinoma (LUAD).

Methods

First, differentially expressed genes (DEGs) related to lipid metabolism in LUAD were detected, and subgroups of LUAD patients were identified via the unsupervised clustering method. Based on lipid metabolism and immune-related DEGs, variables were determined by the univariate Cox and LASSO regression, and a prognostic signature was established. The prognostic value of the signature was evaluated by the Kaplan–Meier method, time-dependent ROC, and univariate and multivariate analyses. Five independent GEO datasets were employed for external validation. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to investigate the underlying mechanisms. The sensitivity to common chemotherapeutic drugs was estimated based on the GDSC database. Finally, we selected PSMC1 involved in the signature, which has not been reported in LUAD, for further experimental validation.

Results

LUAD patients with different lipid metabolism patterns exhibited significant differences in overall survival and immune infiltration levels. The prognostic signature incorporated 10 genes and stratified patients into high- and low-risk groups by median value splitting. The areas under the ROC curves were 0.69 (1-year), 0.72 (3-year), 0.74 (5-year), and 0.74 (10-year). The Kaplan–Meier survival analysis revealed a significantly poorer overall survival in the high-risk group in the TCGA cohort (p < 0.001). In addition, both univariate and multivariate Cox regression analyses indicated that the prognostic model was the individual factor affecting the overall survival of LUAD patients. Through GSEA and GSVA, we found that tumor progression and inflammatory and immune-related pathways were enriched in the high-risk group. Additionally, patients with high-risk scores showed higher sensitivity to chemotherapeutic drugs. The in vitro experiments further confirmed that PSMC1 could promote the proliferation and migration of LUAD cells.

Conclusions

We developed and validated a novel signature incorporating both lipid metabolism and immune-related genes for all-stage LUAD patients. This signature can be applied not only for survival prediction but also for guiding personalized chemotherapy and immunotherapy regimens.

ATF4/MYC Regulates MTHFD2 to Promote NSCLC Progression by Mediating Redox Homeostasis

Purpose. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) has been reported to be overexpressed in non-small-cell lung cancer (NSCLC) and to correlate with malignant proliferation. However, the mechanism of high MTHFD2 expression in NSCLC has not been clarified. Methods. qPCR, western blot, and immunofluorescence experiments were used to measure the expression of related mRNAs and proteins. Cell apoptosis was measured by flow cytometry and TUNEL assays. The CCK-8 assay was used to determine cell viability. Flow cytometry was used to analyze the cell cycle. ROS, H2O2, MDA, SOD, and NADPH/NADP+ were evaluated by relevant assay kits. Transfection of siRNA or vectors was used to downregulate or upregulate gene expression. Dual-luciferase reporter gene assays were used to evaluate the regulated relationship between MTHFD2 and ATF4 or MYC. Results. MTHFD2 was highly expressed in NSCLC cells. Knockdown of MTHFD2 inhibited proliferation and increased apoptosis. Furthermore, oxidative factors significantly increased, while antioxidant factors significantly decreased in NSCLC cells with MTHFD2 knockdown, indicating that MTHFD2 was involved in NSCLC progression through the redox pathway. Although MTHFD2 was downregulated with ATF4 silencing, the dual-luciferase reporter assay suggested that ATF4 did not directly mediate MTHFD2 transcription. Further studies revealed that MYC had a transcriptional effect on MTHFD2 and was also regulated by ATF4. PCR, and western blotting experiments with ATF4 knockdown and MYC overexpression as well as ATF4 overexpression and MYC knockdown proved that ATF4 stimulated MTHFD2 through MYC mediation. Conclusions. ATF4 promoted high expression of MTHFD2 in NSCLC dependent on MYC.

Role of exosomes in lung cancer: A comprehensive insight from immunomodulation to theragnostic applications

Exosomes are 30 to 150 nm-diameter lipid bilayer-enclosed extracellular vesicles that enable cell-to-cell communication through secretion and uptake. The exosomal cargoes contain RNA, lipids, proteins, and metabolites which can be delivered to recipient cells in vivo. In a healthy lung, exosomes facilitate interaction between adaptive and innate immunity and help maintain normal lung physiology. However, tumor-derived exosomes in lung cancer (LC) can, on the other hand, restrict immune cell proliferation, cause apoptosis in activated CD8+ T effector cells, reduce natural killer cell activity, obstruct monocyte differentiation, and promote proliferation of myeloid-derived suppressor and regulatory T cells. In addition, exosomes in the tumor microenvironment may also play a critical role in cancer progression and the development of drug resistance. In this review, we aim to comprehensively examine the current updates on the role of exosomes in lung carcinogenesis and their potential application as a diagnostic, prognostic, and therapeutic tool in lung cancer.

Predicting Differences in Treatment Response and Survival Time of Lung Adenocarcinoma Patients Based on a Prognostic Risk Model of Glycolysis-Related Genes

Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified.

Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score.

Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups.

Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.

High RRM2 expression has poor prognosis in specific types of breast cancer

BACKGROUND

RRM2 plays an important role in different malignant tumors, but there are few studies in breast cancer. Public databases were used to analyze the expression of RRM2 in breast cancer and its prognostic value.

MATERIALS AND METHODS

A total of 2,509 breast cancer samples were downloaded from the METABRIC database. The relationship between RRM2 expression and clinical pathology was evaluated. Using the BCIP database and real-time-PCR, and western blotting, RRM2 mRNA and protein expression of RRM2 in breast cancer tissues and cell lines were evaluated. Univariate and multivariate analysis defined independent prognostic factors that affected the overall survival of patients with breast cancer. The Kaplan-Meier method was used to study the relationship between the high expression of RRM2 and overall survival and distant metastasis-free survival (DMFS) of breast cancer patients. Finally, We performed Gene Set Enrichment Analysis (GSEA) and obtained the relevant pathways associated with high expression of RRM2 potentially influencing breast cancer progression.

RESULTS

RRM2 expression was significantly correlated with age, tumor size, grade, menopausal status, molecular typing, ER, PR, and Her-2 of patients with breast cancer(P<0.05). Univariate and multivariate regression analysis showed that RRM2, the number of positive lymph nodes, ER, Her-2, tumor size, and tumor stage can be used as independent prognostic factors for overall survival of patients with breast cancer. Kaplan-Meier analysis showed that in patients with Luminal A and Normal like breast cancers and Stage1 and stage2 breast cancers, patients with high expression of RRM2 had worse overall survival and DMFS. The analysis of the GSEA pathway showed that RRM2 is mainly enriched in the ERBB signaling pathway and other pathways.

CONCLUSION

The high expression of RRM2 has a worse prognosis in patients with breast cancer with specific features. It can be used as a biomarker for the prognosis of breast cancer.

Construction of a Novel Ferroptosis-Related Gene Signature for Predicting Survival of Patients With Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most diagnosed subtype of lung cancer; ferroptosis is widely involved in the pathological cell death associated with various cancers, including lung cancer. However, the comprehensive relationship between ferroptosis and LUAD is little known in molecular levels until now. In the present study, 513 LUAD patients could be aggregated into three clusters by consensus clustering based on RNA sequencing data of 291 ferroptosis-related genes (FRGs) in The Cancer Genome Atlas (TCGA) database; cluster2 had significant survival advantage compared to the other two clusters. A novel prognostic model of 8 differential FRGs was constructed to effectively divide LUAD patients into high- or low-risk group according to the risk scores by the Cox and LASSO regression analyses. The overall survival of LUAD patients in the high-risk group was significantly worse in the TCGA and GEO cohorts. Moreover, patients with radiation therapy or high clinical stage had obviously higher risk scores. We validated the differential mRNA and protein expression of four FRGs in paired tumor and normal samples from our clinical cohort. Our study constructed a novel FRG signature to predict the prognosis of LUAD patients, which might provide a new prognostic tool and potential therapeutic targets for LUAD.

Lipid metabolism-related gene prognostic index (LMRGPI) reveals distinct prognosis and treatment patterns for patients with early-stage pulmonary adenocarcinoma

Background: Lipid metabolism plays a pivotal role in cancer progression and metastasis. This study aimed to investigate the prognostic value of lipid metabolism-related genes (LMRGs) in early-stage lung adenocarcinoma (LUAD) and develop a lipid metabolism-related gene prognostic index (LMRGPI) to predict their overall survival (OS) and treatment response. Methods: A total of 774 early-stage LUAD patients were identified from The Cancer Genome Atlas (TCGA, 403 patients) database and Gene Expression Omnibus (GEO, 371 patients) database. The non-negative Matrix Factorization (NMF) algorithm was used to identify different population subtypes based on LMRGs. The Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analyses were used to develop the LMRGPI, with receiver operating characteristic (ROC) curves and concordance index being used to evaluate its performance. The characteristics of mutation landscape, enriched pathways, tumor microenvironment (TME), and treatment response between different LMRGPI groups were also investigated. Results: We identified two population subtypes based on LMRGs in the TCGA-LUAD cohort, with distinct prognosis, TME, and immune status being observed. LMRGPI was developed based on the expression levels of six LMRGs, including ANGPTL4, NPAS2, SLCO1B3, ACOXL, ALOX15, and B3GALNT1. Higher LMRGPI was correlated with poor OS both in TCGA and GSE68465 cohorts. Two nomograms were established to predict the survival probability of early-stage LUAD, with higher consistencies being observed between the predicted and actual OS. Higher LMRGPI was significantly correlated with more frequent TP53 mutation, higher tumor mutation burden (TMB), and up-regulation of CD274. Besides, patients with higher LMRGPI presented unremarkable responses for gefitinib, erlotinib, cisplatin, and vinorelbine, while they tend to have a favorable response for immune checkpoint inhibitors (ICIs). The opposite results were observed in the low-LMRGPI group. Conclusions: We comprehensively investigated the prognostic value of LMRGs in early-stage LUAD. Given its good prognostic ability, LMRGPI could serve as a promising biomarker to predict the OS and treatment response of these patients.

ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

BACKGROUND

Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study.

METHODS

Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells.

RESULTS

We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes.

CONCLUSION

Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

LncRNA DUXAP10 Upregulation and the Hedgehog Pathway Activation Are Critically Involved in Chronic Cadmium Exposure-Induced Cancer Stem Cell-Like Property

Cadmium (Cd) is a well-known lung carcinogen. However, the mechanism of Cd carcinogenesis remains to be clearly defined. Cd has been shown to act as a weak mutagen, suggesting that it may exert tumorigenic effect through nongenotoxic ways, such as epigenetic mechanisms. Long noncoding RNAs (lncRNAs) refer to RNA molecules that are longer than 200 nucleotides in length but lack protein-coding capacities. Regulation of gene expressions by lncRNAs is considered as one of important epigenetic mechanisms. The goal of this study is to investigate the mechanism of Cd carcinogenesis focusing on the role of lncRNA dysregulations. Cd-induced malignant transformation of human bronchial epithelia BEAS-2B cells was accomplished by a 9-month low-dose Cd (CdCl2, 2.5 µM) exposure. The Cd-exposed cells formed significantly more colonies in soft agar, displayed cancer stem cell (CSC)-like property, and formed tumors in nude mice. Mechanistically, chronic low-dose Cd exposure did not cause significant genotoxic effects but dysregulated lncRNA expressions. Further Q-PCR analysis confirmed the significant upregulation of the oncogenic lncRNA DUXAP10 in Cd-transformed cells. DUXAP10 knockdown in Cd-transformed cells significantly reduced their CSC-like property. Further mechanistic studies showed that the Hedgehog pathway is activated in Cd-transformed cells and inhibition of this pathway reduces Cd-induced CSC-like property. DUXAP10 knockdown caused the Hedgehog pathway inactivation in Cd-transformed cells. Furthermore, Pax6 expression was upregulated in Cd-transformed cells and Pax6 knockdown significantly reduced their DUXAP10 levels and CSC-like property. In summary, these findings suggest that the lncRNA DUXAP10 upregulation may play an important role in Cd carcinogenesis.

Integrative analysis and experiments to explore angiogenesis regulators correlated with poor prognosis, immune infiltration and cancer progression in lung adenocarcinoma

Angiogenesis is the process of capillary sprouting from pre-existing vessels and it plays a critical role in the carcinogenic process of lung adenocarcinoma (LUAD). However, the association of angiogenesis regulators with the prognosis and progression of LUAD needs to be further elucidated. In this study, we adopted differential expression analysis, Cox proportional hazards (PH) regression analysis and experimental validation to identify angiogenesis regulators correlated with a poor prognosis, immune infiltration and cancer progression in LUAD. These results showed that the diagnostic and prognostic models based on COL5A2 and EPHB2 served as independent biomarkers with superior predictive ability. The patients in the high-risk group exhibited a worse prognosis in the TCGA cohort (P < 0.001, HR = 1.72, 95% CI 1.28-2.30), GSE310210 cohort (P = 0.005, HR = 2.87, 95% CI 1.46-5.61), and GSE31019 cohort (P = 0.01, HR = 2.14, 95% CI 1.19-3.86) than patients in the low-risk group. The high prognostic risk patients had a higher TMB (P < 0.001); higher fractions of M0 macrophages, neutrophils, NK cells resting, and T cells CD4 memory activated (P < 0.05); and higher expression of immune checkpoints PD-1, PDL-1, PDL-2, and B7H3 (P < 0.001). Patients in the high-risk group were more sensitive to chemotherapeutic drugs and molecular targeted drugs such as cisplatin, doxorubicin, gefitinib, and bosutinib (P < 0.0001). In addition, inhibition of COL5A2 and EPHB2 effectively suppressed the proliferation and migration of LUAD cells. The current study identified angiogenesis regulators as potential biomarkers and therapeutic targets for LUAD and may help to further optimize cancer therapy.