KIAA1522 potentiates TNFα-NFκB signaling to antagonize platinum-based chemotherapy in lung adenocarcinoma

Emerging role of tumor microenvironmental nutrients and metabolic molecules in ferroptosis: Mechanisms and clinical implications

In recent years, ferroptosis has gradually attracted increasing attention because of its important role in tumors. Ferroptosis resistance is an important cause of tumor metastasis, recurrence and drug resistance. Exploring the initiating factors and specific mechanisms of ferroptosis has become a key strategy to block tumor progression and improve drug sensitivity. As the external space in direct contact with tumor cells, the tumor microenvironment has a great impact on the biological function of tumor cells. The relationships between abnormal environmental characteristics (hypoxia, lactic acid accumulation, etc.) in the microenvironment and ferroptosis of tumor cells has not been fully characterized. This review focuses on the characteristics of the tumor microenvironment and summarizes the mechanisms of ferroptosis under different environmental factors, aiming to provide new insights for subsequent targeted therapy. Moreover, considering the presence of anticancer drugs in the microenvironment, we further summarize the mechanisms of ferroptosis to provide new strategies for the sensitization of tumor cells to drugs.

Ferroptosis-related genes DUOX1 and HSD17B11 affect tumor microenvironment and predict overall survival of lung adenocarcinoma patients

BACKGROUND

Recent studies have found that ferroptosis-related genes (FRGs) have broad applications in tumor therapy. However, the predictive potential of these genes in lung adenocarcinoma (LUAD) remains to be fully characterized. We aimed to investigate the FRGs that might be potential targets for LUAD.

METHODS

We screened the RNA sequencing samples from LUAD patients from the GEO database and analyzed the ferroptosis-related differentially expressed genes (DEGs). A functional analysis of DEGs was performed. The risk model was constructed to evaluation and validation FRGs. We explored the immune landscape of LUAD and controls. The value of FRGs in diagnosing LUAD was tested in the GSE30219, GSE37745, GSE0081 datasets, and qPCR was used to verify their diagnostic value in LUAD patients in our hospital.

RESULTS

A total of 1327 DEGs in quantitative proteomics were obtained, of which ferroptosis-related DEGs were 259. Enrichment analysis showed significant enrichment in the absorption and metabolism of fatty acids and arachidonic acid. The upregulated genes (GCLC, RRM2, AURKA, SLC7A5, and SLC2A1) and downregulated genes (ANGPTL7, ALOX15, ALOX15B, HSD17B11, IL33, TSC22D3, and DUOX1) were selected as core genes in tissue samples from 62 patients by qPCR. DUOX1 and HSD17B11 were obtained by bioinformatics analysis, both of which showed similar expression trends at the RNA and protein levels. The Kaplan-Meier method showed that DUOX1 and HSD17B11 were closely related to the overall survival (OS) of LUAD patients.

CONCLUSION SUBSECTIONS

Ferroptosis-related genes DUOX1 and HSD17B11 are of considerable value in the diagnosis of LUAD patients. Their low expression suggests an increased recurrence rate and leads to a decrease in the patient quality of life.

Characterization of immunogenic cell death regulators predicts survival and immunotherapy response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is highly lethal tumor; understanding immune response is crucial for current effective treatment. Research investigated immunogenic cell death (ICD) impact on LUAD through 75 ICD-related genes which encompass cell damage, endoplasmic reticulum stress, microenvironment, and immunity. Transcriptome data and clinical info were analyzed, revealing two ICD-related clusters: B, an immune osmotic subgroup, had better prognosis, stronger immune signaling, and higher infiltration, while A represented an immune-deficient subgroup. Univariate Cox analysis identified six prognostic genes (AGER, CD69, CD83, CLEC9A, CTLA4, and NT5E), forming a validated risk score model. It was validated across datasets, showing predictive performance. High-risk group had unfavorable prognosis, lower immune infiltration, and higher chemotherapy sensitivity. Conversely, low-risk group had better prognosis, higher immune infiltration, and favorable immunotherapy response. The key gene NT5E was examined via immunohistochemistry, with higher expression linked to poorer prognosis. NT5E was predominantly expressed in B cells, fibroblasts, and endothelial cells, correlated with immune checkpoints. These outcomes suggest that NT5E can serve as a LUAD therapeutic target. The study highlights gene predictive value, offers an efficient tumor assessment tool, guides clinical treatment strategies, and identifies NT5E as therapeutic target for LUAD.

The Prognostic Significance of KIAA1522 Expression in Non-Small-Cell Lung Cancer Patients

The majority of lung cancers belong to the non-small-cell lung cancer (NSCLC) category, which is linked to a high mortality rate despite significant progress in diagnosis and treatment. Therefore, there is a need for novel prognostic NSCLC biomarkers to improve prognosis which currently remains poor. Recent studies and analyses of gene expression data of NSCLC revealed that high expression of KIAA1522 was significantly associated with poor prognosis and decreased overall survival. We identified 98 patients who underwent radical curative surgical resections or metastasectomy for pulmonary adenocarcinoma and squamous cell carcinoma at our institution or the pathological diagnosis confirmed by our pathologists. Following the latest data, we utilized immunohistochemistry to assess the expression of KIAA1522 and investigated its association with various clinic-demographic parameters, pathological stages, recurrence rates, overall survival, and disease-free survival in patients who achieved complete remission. Notably, there were no significant differences in the expression profiles of KIAA1522 between adenocarcinoma and squamous cell carcinoma samples (p=0.6). Survival analysis was conducted using log-rank tests and a multivariate Cox proportional hazard model. Of the 98 samples, 54 (55.1%) exhibited high expression of KIAA1522, and patients with high KIAA1522 expression had a significantly shorter overall survival than the low-expression group (p=0.01). Multivariate Cox proportional hazard models in which metastatic patients were included revealed that along with older age, higher TNM stage (tumor, node, metastasis system), and Eastern Cooperative Oncology Group (ECOG) performance status, high expression of KIAA1522 served as an independent prognostic factor. A high expression profile was not significantly associated with relapses in those whose complete remission had been achieved. Still, those patients with high expression of KIAA1522 tended to exhibit a shorter disease-free survival rate. In conclusion, our findings suggest that KIAA1522 expression is an independent factor for predicting overall survival and may serve as a valuable prognostic indicator for relapse and disease-free survival in NSCLC patients.

Systematic characterization of cancer transcriptome at transcript resolution

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, cancer transcriptome has not been fully characterized at transcript resolution. Herein, we carry out a reference-based transcript assembly across >1000 cancer cell lines. We identify 498,255 transcripts, approximately half of which are unannotated. Unannotated transcripts are closely associated with cancer-related hallmarks and show clinical significance. We build a high-confidence RNA binding protein (RBP)-transcript regulatory network, wherein most RBPs tend to regulate transcripts involved in cell proliferation. We identify numerous transcripts that are highly associated with anti-cancer drug sensitivity. Furthermore, we establish RBP-transcript-drug axes, wherein PTBP1 is experimentally validated to affect the sensitivity to decitabine by regulating KIAA1522-a6 transcript. Finally, we establish a user-friendly data portal to serve as a valuable resource for understanding cancer transcriptome diversity and its potential clinical utility at transcript level. Our study substantially extends cancer RNA repository and will facilitate anti-cancer drug discovery.

Exploring the nucleotide molecular mechanism of compound kushen injection for lung adenocarcinoma based on network pharmacology and molecular docking

Compound kushen injection is an effective traditional Chinese medicine for the treatment of lung cancer. However, its influence on the survival and prognosis of patients with lung adenocarcinoma patients was less studied; especially its pharmacological mechanism remains to be further elucidated. In the present study, we adopted a network pharmacology (NP)-based approach to screening effective compounds, screening and predicting target genes, analyzing biological functions and pathways, constructing a regulatory network and protein interaction network, and screening the key targets. Moreover, mass survival analysis and molecular docking were conducted. In the end, 35 key compounds and four possible central target genes were screened out, which could be used for the treatment of lung adenocarcinoma and affected the survival and prognosis of patients with lung adenocarcinoma. In addition, their key compounds had good docking affinity. Enrichment analysis showed that CKI might affect the treatment and prognosis of lung adenocarcinoma patients by regulating the PI3K-Akt signaling pathway, TNF signaling pathway, non-small cell lung cancer, Hepatitis C, etc. We discussed the pharmacological mechanisms and potential therapeutic targets of CKI in the treatment of lung adenocarcinoma, which verified the effect of CKI on the prognosis and survival of patients. The present study might promote the further clinical application of CKI and provide a theoretical basis for further experimental studies.

Prognostic Modeling of Lung Adenocarcinoma Based on Hypoxia and Ferroptosis-Related Genes

Background. It is well known that hypoxia and ferroptosis are intimately connected with tumor development. The purpose of this investigation was to identify whether they have a prognostic signature. To this end, genes related to hypoxia and ferroptosis scores were investigated using bioinformatics analysis to stratify the risk of lung adenocarcinoma. Methods. Hypoxia and ferroptosis scores were estimated using The Cancer Genome Atlas (TCGA) database-derived cohort transcriptome profiles via the single sample gene set enrichment analysis (ssGSEA) algorithm. The candidate genes associated with hypoxia and ferroptosis scores were identified using weighted correlation network analysis (WGCNA) and differential expression analysis. The prognostic genes in this study were discovered using the Cox regression (CR) model in conjunction with the LASSO method, which was then utilized to create a prognostic signature. The efficacy, accuracy, and clinical value of the prognostic model were evaluated using an independent validation cohort, Receiver Operator Characteristic (ROC) curve, and nomogram. The analysis of function and immune cell infiltration was also carried out. Results. Here, we appraised 152 candidate genes expressed not the same, which were related to hypoxia and ferroptosis for prognostic modeling in The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort, and these genes were further validated in the GSE31210 cohort. We found that the 14-gene-based prognostic model, utilizing MAPK4, TNS4, WFDC2, FSTL3, ITGA2, KLK11, PHLDB2, VGLL3, SNX30, KCNQ3, SMAD9, ANGPTL4, LAMA3, and STK32A, performed well in predicting the prognosis in lung adenocarcinoma. ROC and nomogram analyses showed that risk scores based on prognostic signatures provided desirable predictive accuracy and clinical utility. Moreover, gene set variance analysis showed differential enrichment of 33 hallmark gene sets between different risk groups. Additionally, our results indicated that a higher risk score will lead to more fibroblasts and activated CD4 T  cells but fewer myeloid dendritic cells, endothelial cells, eosinophils, immature dendritic cells, and neutrophils. Conclusion. Our research found a 14-gene signature and established a nomogram that accurately predicted the prognosis in patients with lung adenocarcinoma. Clinical decision-making and therapeutic customization may benefit from these results, which may serve as a valuable reference in the future.

A Novel Immune-Related Gene Signature Predicts Prognosis of Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common form of lung cancer, accounting for 30% of all cases and 40% of all non-small-cell lung cancer cases. Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The present study was aimed at finding an immune-related gene signature for predicting LUAD patient outcomes.

Methods

First, we chose the TCGA-LUAD project in the TCGA database as the training cohort for model training. For model validating, we found the datasets of GSE72094 and GSE68465 in the GEO database and took them as the candidate cohorts. We obtained 1793 immune-related genes from the ImmPort database and put them into a univariate Cox proportional hazard model to initially look for the genes with potential prognostic ability using the data of the training cohort. These identified genes then entered into a random survival forests-variable hunting algorithm for the best combination of genes for prognosis. In addition, the LASSO Cox regression model tested whether the gene combination can be further shrinkage, thereby constructing a gene signature. The Kaplan-Meier, Cox model, and ROC curve were deployed to examine the gene signature's prognosis in both cohorts. We conducted GSEA analysis to study further the mechanisms and pathways that involved the gene signature. Finally, we performed integrating analyses about the 22 TICs, fully interpreted the relationship between our signature and each TIC, and highlighted some TICs playing vital roles in the signature's prognostic ability.

Results

A nine-gene signature was produced from the data of the training cohort. The Kaplan-Meier estimator, Cox proportional hazard model, and ROC curve confirmed the independence and predictive ability of the signature, using the data from the validation cohort. The GSEA analysis results illustrated the gene signature's mechanism and emphasized the importance of immune-related pathways for the gene signature. 22 TICs immune infiltration analysis revealed resting mast cells' key roles in contributing to gene signature's prognostic ability.

Conclusions

This study discovered a novel immune-related nine-gene signature (BTK, CCR6, S100A10, SEMA3C, GPI, SCG2, TNFRSF11A, CCL20, and DKK1) that predicts LUAD prognosis precisely and associates with resting mast cells strongly.

Cancer-associated fibroblast-induced lncRNA UPK1A-AS1 confers platinum resistance in pancreatic cancer via efficient double-strand break repair

The tumor stroma of pancreatic ductal adenocarcinoma (PDAC) is characterized by an abundant and heterogeneous population of cancer-associated fibroblasts (CAFs), which are critically involved in chemoresistance. However, the underlying mechanism of CAFs in chemoresistance is unclear. Here, we show that CAFR, a CAF subset derived from platinum-resistant PDAC patients, assumes an iCAF phenotype and produces more IL8 than CAFS isolated from platinum-sensitive PDAC patients. CAFR-derived IL8 promotes oxaliplatin chemoresistance in PDAC. Based on long noncoding RNA (lncRNA) profiling in tumor cells incubated with CAF-CM, we found that UPK1A-AS1, whose expression is directly induced by IL8/NF-kappa B signaling, functions as a chemoresistance-promoting lncRNA and is critical for active IL8-induced oxaliplatin resistance. Impressively, blocking the activation of UPK1A-AS1 expression increases the oxaliplatin sensitivity of tumor cells in vivo. Mechanistically, UPK1A-AS1 strengthens the interaction between Ku70 and Ku80 to facilitate nonhomologous end joining (NHEJ), thereby enhancing DNA double-strand break (DSB) repair. Clinically, UPK1A-AS1 expression is positively correlated with IL8 expression, a poor chemotherapeutic response and a shorter progression-free survival (PFS) time in advanced PDAC patients. Collectively, our study reveals a lncRNA-mediated mechanism of CAF-derived paracrine IL8-dependent oxaliplatin resistance and highlights UPK1A-AS1 as a potential therapeutic target.

Cognitive adverse effects of chemotherapy and immunotherapy: are interventions within reach?

One in three people will be diagnosed with cancer during their lifetime. The community of cancer patients is growing, and several common cancers are becoming increasingly chronic; thus, cancer survivorship is an important part of health care. A large body of research indicates that cancer and cancer therapies are associated with cognitive impairment. This research has mainly concentrated on chemotherapy-associated cognitive impairment but, with the arrival of immunotherapies, the focus is expected to widen and the number of studies investigating the potential cognitive effects of these new therapies is rising. Meanwhile, patients with cognitive impairment and their healthcare providers are eagerly awaiting effective approaches to intervene against the cognitive effects of cancer treatment. In this Review, we take stock of the progress that has been made and discuss the steps that need to be taken to accelerate research into the biology underlying cognitive decline following chemotherapy and immunotherapy and to develop restorative and preventive interventions. We also provide recommendations to clinicians on how to best help patients who are currently experiencing cognitive impairment.

Prognostic and immune implications of a novel ferroptosis-related ten-gene signature in lung adenocarcinoma

Background

Lung cancer has been the focus of attention for many researchers in recent years due to its leading contribution to cancer-related death worldwide, with lung adenocarcinoma (LUAD) being the most common histological type. Ferroptosis, a novel iron-dependent form of regulated cell death, can be induced by sorafenib. Emerging evidence shows that triggering ferroptosis has potential as a cancer therapy. This work aimed to build a ferroptosis-related gene signature for predicting the outcome of LUAD.

Methods

The TCGA-LUAD dataset was set as the training cohort, and the GSE72094 and GSE68465 datasets were set as the validation cohorts. Sixty-two ferroptosis-related genes were retrieved from the literature. A univariate Cox regression model was constructed for the training cohort to preliminarily screen for potential prognostic ferroptosis-related genes. A gene signature was generated from a LASSO Cox regression model and assessed with the training and validation cohorts through Kaplan-Meier, Cox, and ROC analyses. In addition, the correlation between the risk score and autophagy-related genes was determined by the Pearson test. Finally, GSEA and immune infiltrating analyses were performed to better study the functional annotation of the signature and the role of each kind of immune cell.

Results

A ten-gene signature was constructed from the training cohort and validated in three cohorts by Kaplan-Meier and Cox regression analyses, revealing its independent prognostic value in LUAD. Moreover, a ROC analysis conducted with all cohort data confirmed the predictive ability of the ten-gene signature for LUAD prognosis. A total of 62.85% (308/490) of autophagy-related genes were found to be significantly correlated with risk scores. GSEA detailed the exact pathways related to the gene signature, and immune-infiltrating analyses identified crucial roles for resting mast cells and resting dendritic cells in the prognosis of LUAD.

Conclusions

We identified a novel ferroptosis-related ten-gene signature (PHKG2, PGD, PEBP1, NCOA4, GLS2, CISD1, ATP5G3, ALOX15, ALOX12B, and ACSL3) that can accurately predict LUAD prognosis and is closely linked to resting mast cells and resting dendritic cells.

Development and Validation of a Robust Ferroptosis-Related Prognostic Signature in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Ferroptosis is a newly recognized process of cell death, which is different from other forms of cell death in morphology, biochemistry, and genetics, and has played a vital role in cancer biology. This study aimed to identify a ferroptosis-related gene signature associated with LUAD prognosis.

Methods

Dataset TCGA-LUAD which came from the TCGA portal was taken as the training cohort. GSE72094 and GSE68465 from the GEO database were treated as validation cohorts. Two hundred fifty-nine ferroptosis-related genes were retrieved from the FerrDb database. In the training cohort, Kaplan–Meier and univariate Cox analyses were conducted for preliminary screening of ferroptosis-related genes with potential prognostic capacity. These genes then entered into the LASSO Cox regression model, constructing a gene signature. The latter was then evaluated in the training and validation cohorts via Kaplan–Meier, Cox, and ROC analyses. In addition, the correlations between risk score and autophagy were examined by Pearson correlation coefficient. The analyses of GSEA and immune infiltrating were performed for better studying the function annotation of the gene signature and the character of each kind of immune cells played in the tumor microenvironment.

Results

A 15-gene signature was found from the training cohort and validated by Kaplan–Meier and Cox regression analyses, revealing its independent prognosis value in LUAD. Moreover, the ROC analysis was conducted, confirming a strong predictive ability that this signature owned for LUAD prognosis. One hundred fifty-one of 222 (68.01%) autophagy-related genes were discovered significantly correlated with risk scores. Analyses of GSEA and immune infiltration exhibited in detail the specific pathways that associate with the 15-gene signature and identified the crucial roles of resting mast cells and resting dendritic cells owned in the prognosis of the 15-gene signature.

Conclusion

In this present study, a novel ferroptosis-related 15-gene signature (RELA, ACSL3, YWHAE, EIF2S1, CISD1, DDIT4, RRM2, PANX1, TLR4, ARNTL, LPIN1, HERPUD1, NCOA4, PEBP1, and GLS2) was built. It could accurately predict the prognosis of LUAD and was related to resting mast cells and resting dendritic cells, which provide potential for the personalized outcome prediction and the development of new therapies in LUAD population.