The nuclear hypoxia-regulated NLUCAT1 long non-coding RNA contributes to an aggressive phenotype in lung adenocarcinoma through regulation of oxidative stress

CircLMBR1 inhibits phenotypic transformation of hypoxia-induced pulmonary artery smooth muscle via the splicing factor PUF60

Phenotypic transformation of pulmonary artery smooth muscle cells (PASMCs) contributes to vascular remodeling in hypoxic pulmonary hypertension (PH). Recent studies have suggested that circular RNAs (circRNAs) may play important roles in the vascular remodeling of hypoxia-induced PH. However, whether circRNAs cause pulmonary vascular remodeling by regulating the phenotypic transformation in PH has not been investigated. Microarray and RT-qPCR analysis identified that circLMBR1, a novel circRNA, decreased in mouse lung tissues of the hypoxia-SU5416 PH model, as well as in human PASMCs and mouse PASMCs exposed to hypoxia. Overexpression of circLMBR1 in the Semaxinib (SU5416) mouse model ameliorated hypoxia-induced PH and vascular remodeling in the lungs. Notably, circLMBR1 was mainly distributed in the nucleus and bound to the splicing factor PUF60. CircLMBR1 suppressed the phenotypic transformation of human PASMCs and vascular remodeling by inhibiting PUF60 expression. Furthermore, we identified U2AF65 as the downstream regulatory factor of PUF60. U2AF65 directly interacted with the pre-mRNA of the contractile phenotype marker smooth muscle protein 22-α (SM22α) and inhibited its splicing. Meanwhile, hypoxia exposure increased the formation of the PUF60-U2AF65 complex, thereby inhibiting SM22α production and inducing the transition of human PASMCs from a contractile phenotype to a synthetic phenotype. Overall, our results verified the important role of circLMBR1 in the pathological process of PH. We also proposed a new circLMBR1/PUF60-U2AF65/pre-SM22α pathway that could regulate the phenotypic transformation and proliferation of human PASMCs. This study may provide new perspectives for the diagnosis and treatment of PH.

Exploring the relationship between the interleukin family and lung adenocarcinoma through Mendelian randomization and RNA sequencing analysis

BACKGROUND

Lung adenocarcinoma (LUAD) is still one of the most prevalent malignancies. Interleukin factors are closely associated with the initiation and progression of cancer. However, the relationship between interleukin factors and LUAD has not been fully elucidated. This study aimed to use Mendelian randomization (MR) and RNA sequencing (RNA-seq) analyses to identify the interleukin factors associated with the onset and progression of LUAD.

METHODS

Exposure-related instrumental variables were selected from interleukin factor summary datasets. The LUAD summary dataset from FINGENE served as the outcome. MR and sensitivity analyses were conducted to screen for interleukin factors associated with LUAD occurrence. Transcriptome analyses revealed the role of interleukin factors in lung tissues. The results were validated through Western blotting and further confirmed with driver gene-negative patients from multiple centers. Potential mechanisms influencing LUAD occurrence and development were explored using bulk RNA-seq and single-cell RNA-seq data.

RESULTS

MR analysis indicated that elevated plasma levels of IL6RB, IL27RA, IL22RA1, and IL16 are causally associated with increased LUAD risk, while IL18R1 and IL11RA exhibit the opposite effect. Transcriptome analyses revealed that IL11RA, IL18R1, and IL16 were downregulated in tumor tissues compared with normal lung tissue, but only higher expression of IL11RA correlated with improved prognosis in patients with LUAD from different centers and persisted even in driver-gene negative patients. The IL11RA protein level was lower in various LUAD cell lines than in human bronchial epithelial cells. The genes co-expressed with IL11RA were enriched in the Ras signaling pathway and glycosylation processes. Fibroblasts were the primary IL11RA-expressing cell population, with IL11RA+fibroblasts exhibiting a more immature state. The genes differentially expressed between IL11RA+and IL11RA- fibroblasts were involved in the PI3K-Akt/TNF signaling pathway.

CONCLUSION

According to the MR and transcriptome analyses, the downregulation of IL11RA was closely related to the occurrence and development of LUAD.

Long non-coding RNA lung cancer-associated transcript-1 promotes glioblastoma progression by enhancing Hypoxia-inducible factor 1 alpha activity

BACKGROUND

Hypoxia is associated with poor prognosis in many cancers including glioblastoma (GBM). Glioma stem-like cells (GSCs) often reside in hypoxic regions and serve as reservoirs for disease progression. Long non-coding RNAs (lncRNAs) have been implicated in GBM. However, the lncRNAs that modulate GSC adaptations to hypoxia are poorly understood. Identification of these lncRNAs may provide new therapeutic strategies to target GSCs under hypoxia.

METHODS

lncRNAs induced by hypoxia in GSCs were identified by RNA-seq. Lung cancer-associated transcript-1 (LUCAT1) expression was assessed by qPCR, RNA-seq, Northern blot, single molecule FISH in GSCs, and interrogated in IvyGAP, The Cancer Genome Atlas, and CGGA databases. LUCAT1 was depleted by shRNA, CRISPR/Cas9, and CRISPR/Cas13d. RNA-seq, Western blot, immunohistochemistry, co-IP, ChIP, ChIP-seq, RNA immunoprecipitation, and proximity ligation assay were performed to investigate mechanisms of action of LUCAT1. GSC viability, limiting dilution assay, and tumorigenic potential in orthotopic GBM xenograft models were performed to assess the functional consequences of depleting LUCAT1.

RESULTS

A new isoform of Lucat1 is induced by Hypoxia inducible factor 1 alpha (HIF1α) and Nuclear factor erythroid 2-related factor 2 (NRF2) in GSCs under hypoxia. LUCAT1 is highly expressed in hypoxic regions in GBM. Mechanistically, LUCAT1 formed a complex with HIF1α and its co-activator CBP to regulate HIF1α target gene expression and GSC adaptation to hypoxia. Depletion of LUCAT1 impaired GSC self-renewal. Silencing LUCAT1 decreased tumor growth and prolonged mouse survival in GBM xenograft models.

CONCLUSIONS

A HIF1α-LUCAT1 axis forms a positive feedback loop to amplify HIF1α signaling in GSCs under hypoxia. LUCAT1 promotes GSC self-renewal and GBM tumor growth. LUCAT1 is a potential therapeutic target in GBM.

The Potential Links between lncRNAs and Drug Tolerance in Lung Adenocarcinoma

Lung cancer patients treated with targeted therapies frequently respond well but invariably relapse due to the development of drug resistance. Drug resistance is in part mediated by a subset of cancer cells termed "drug-tolerant persisters" (DTPs), which enter a dormant, slow-cycling state that enables them to survive drug exposure. DTPs also exhibit stem cell-like characteristics, broad epigenetic reprogramming, altered metabolism, and a mutagenic phenotype mediated by adaptive mutability. While several studies have characterised the transcriptional changes that lead to the altered phenotypes exhibited in DTPs, these studies have focused predominantly on protein coding changes. As long non-coding RNAs (lncRNAs) are also implicated in the phenotypes altered in DTPs, it is likely that they play a role in the biology of drug tolerance. In this review, we outline how lncRNAs may contribute to the key characteristics of DTPs, their potential roles in tolerance to targeted therapies, and the emergence of genetic resistance in lung adenocarcinoma.

Hypoxia-Inducible Factor-Dependent and Independent Mechanisms Underlying Chemoresistance of Hypoxic Cancer Cells

In hypoxic regions of malignant solid tumors, cancer cells acquire resistance to conventional therapies, such as chemotherapy and radiotherapy, causing poor prognosis in patients with cancer. It is widely recognized that some of the key genes behind this are hypoxia-inducible transcription factors, e.g., hypoxia-inducible factor 1 (HIF-1). Since HIF-1 activity is suppressed by two representative 2-oxoglutarate-dependent dioxygenases (2-OGDDs), PHDs (prolyl-4-hydroxylases), and FIH-1 (factor inhibiting hypoxia-inducible factor 1), the inactivation of 2-OGDD has been associated with cancer therapy resistance by the activation of HIF-1. Recent studies have also revealed the importance of hypoxia-responsive mechanisms independent of HIF-1 and its isoforms (collectively, HIFs). In this article, we collate the accumulated knowledge of HIF-1-dependent and independent mechanisms responsible for resistance of hypoxic cancer cells to anticancer drugs and briefly discuss the interplay between hypoxia responses, like EMT and UPR, and chemoresistance. In addition, we introduce a novel HIF-independent mechanism, which is epigenetically mediated by an acetylated histone reader protein, ATAD2, which we recently clarified.

Single-cell and bulk RNA-sequencing reveal SPP1 and CXCL12 as cell-to-cell communication markers to predict prognosis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) generally presents as an immunosuppressive microenvironment. The characteristics of cell-to-cell communication in the LUAD microenvironment has been unclear. In this study, the LUAD bulk RNA-seq data and single-cell RNA-seq data were retrieved from public dataset. Differential expression genes (DEGs) between LUAD tumor and adjacent non-tumor tissues were calculated by limma algorithm, and then detected by PPI, KEGG, and GO analysis. Cell-cell interactions were explored using the single-cell RNA-seq data. Finally, the first 15 CytoHubba genes were used to establish related pathways and these pathways were used to characterize the immune-related ligands and their receptors in LUAD. Our analyses showed that monocytes or macrophages interact with tissue stem cells and NK cells via SPP1 signaling pathway and tissue stem cells interact with T and B cells via CXCL signaling pathway in different states. Hub genes of SPP1 participated in SPP1 signaling pathway, which was negatively correlated with CD4+ T cell and CD8+ T cell. The expression of SPP1 in LUAD tumor tissues was negatively correlated with the prognosis. While CXCL12 participated in CXCL signaling pathway, which was positively correlated with CD4+ T cell and CD8+ T cell. The role of CXCL12 in LUAD tumor tissues exhibits an opposite effect to that of SPP1. This study reveals that tumor-associated monocytes or macrophages may affect tumor progression. Moreover, the SPP1 and CXCL12 may be the critic genes of cell-to-cell communication in LUAD, and targeting these pathways may provide a new molecular mechanism for the treatment of LUAD.

Detecting subtle transcriptomic perturbations induced by lncRNAs knock-down in single-cell CRISPRi screening using a new sparse supervised autoencoder neural network

Single-cell CRISPR-based transcriptome screens are potent genetic tools for concomitantly assessing the expression profiles of cells targeted by a set of guides RNA (gRNA), and inferring target gene functions from the observed perturbations. However, due to various limitations, this approach lacks sensitivity in detecting weak perturbations and is essentially reliable when studying master regulators such as transcription factors. To overcome the challenge of detecting subtle gRNA induced transcriptomic perturbations and classifying the most responsive cells, we developed a new supervised autoencoder neural network method. Our Sparse supervised autoencoder (SSAE) neural network provides selection of both relevant features (genes) and actual perturbed cells. We applied this method on an in-house single-cell CRISPR-interference-based (CRISPRi) transcriptome screening (CROP-Seq) focusing on a subset of long non-coding RNAs (lncRNAs) regulated by hypoxia, a condition that promote tumor aggressiveness and drug resistance, in the context of lung adenocarcinoma (LUAD). The CROP-seq library of validated gRNA against a subset of lncRNAs and, as positive controls, HIF1A and HIF2A, the 2 main transcription factors of the hypoxic response, was transduced in A549 LUAD cells cultured in normoxia or exposed to hypoxic conditions during 3, 6 or 24 h. We first validated the SSAE approach on HIF1A and HIF2 by confirming the specific effect of their knock-down during the temporal switch of the hypoxic response. Next, the SSAE method was able to detect stable short hypoxia-dependent transcriptomic signatures induced by the knock-down of some lncRNAs candidates, outperforming previously published machine learning approaches. This proof of concept demonstrates the relevance of the SSAE approach for deciphering weak perturbations in single-cell transcriptomic data readout as part of CRISPR-based screening.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

The Multifaceted Roles of NRF2 in Cancer: Friend or Foe?

Physiological concentrations of reactive oxygen species (ROS) play vital roles in various normal cellular processes, whereas excessive ROS generation is central to disease pathogenesis. The nuclear factor erythroid 2-related factor 2 (NRF2) is a critical transcription factor that regulates the cellular antioxidant systems in response to oxidative stress by governing the expression of genes encoding antioxidant enzymes that shield cells from diverse oxidative alterations. NRF2 and its negative regulator Kelch-like ECH-associated protein 1 (KEAP1) have been the focus of numerous investigations in elucidating whether NRF2 suppresses tumor promotion or conversely exerts pro-oncogenic effects. NRF2 has been found to participate in various pathological processes, including dysregulated cell proliferation, metabolic remodeling, and resistance to apoptosis. Herein, this review article will examine the intriguing role of phase separation in activating the NRF2 transcriptional activity and explore the NRF2 dual impacts on tumor immunology, cancer stem cells, metastasis, and long non-coding RNAs (LncRNAs). Taken together, this review aims to discuss the NRF2 multifaceted roles in both cancer prevention and promotion while also addressing the advantages, disadvantages, and limitations associated with modulating NRF2 therapeutically in cancer treatment.

Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village

Long noncoding RNAs (lncRNAs) are a distinct subtype of RNA that lack protein-coding capacity but exert significant influence on various cellular processes. In non-small cell lung cancer (NSCLC), dysregulated lncRNAs act as either oncogenes or tumor suppressors, contributing to tumorigenesis and tumor progression. LncRNAs directly modulate gene expression, act as competitive endogenous RNAs by interacting with microRNAs or proteins, and associate with RNA binding proteins. Moreover, lncRNAs can reshape the tumor immune microenvironment and influence cellular metabolism, cancer cell stemness, and angiogenesis by engaging various signaling pathways. Notably, lncRNAs have shown great potential as diagnostic or prognostic biomarkers in liquid biopsies and therapeutic strategies for NSCLC. This comprehensive review elucidates the significant roles and diverse mechanisms of lncRNAs in NSCLC. Furthermore, we provide insights into the clinical relevance, current research progress, limitations, innovative research approaches, and future perspectives for targeting lncRNAs in NSCLC. By summarizing the existing knowledge and advancements, we aim to enhance the understanding of the pivotal roles played by lncRNAs in NSCLC and stimulate further research in this field. Ultimately, unraveling the complex network of lncRNA-mediated regulatory mechanisms in NSCLC could potentially lead to the development of novel diagnostic tools and therapeutic strategies.

PBK correlates with prognosis, immune escape and drug response in LUAD

PBK (PDZ-binding kinase) is a protein-coding gene that encodes a serine/threonine protein kinase associated with the dual-specific mitogen-activated protein kinase (MAPKK) family. Overexpression of this gene is closely linked to tumor development. In this study, we aimed to investigate the role of PBK in lung adenocarcinoma (LUAD) progression, prognosis, and immune evasion. We conducted a pan-cancer analysis of PBK to examine its expression and prognostic value. In the LUAD cohort, we analyzed PBK expression, prognosis, mutational features, and immune infiltration in groups with different PBK expression levels. We constructed a PBK-associated genomic model, integrated it into a nomogram, and compared high and low-risk subgroups. In our pan-cancer analysis, PBK was significantly upregulated, particularly in LUAD patients, and displayed poor prognosis. The high PBK expression group had many deletion mutations but still showed gene upregulation. Immune infiltration analysis indicated that PBK-triggered immune escape in the high expression group might relate to antigen presentation, dendritic cell, and CD8+ T cell infiltration. We constructed a 5-gene prognostic model and a nomogram to quantify individual survival probabilities. The PBK-associated gene prognostic model reliably predicted patient prognosis and drug response. Our findings offer new insights into PBK-induced immune escape and targeted therapy during LUAD development, providing valuable suggestions for clinical treatment approaches.

ADAR1-mediated RNA editing promotes B cell lymphomagenesis

Diffuse large B cell lymphoma (DLBCL) is one of the most common types of aggressive lymphoid malignancies. Here, we explore the contribution of RNA editing to DLBCL pathogenesis. We observed that DNA mutations and RNA editing events are often mutually exclusive, suggesting that tumors can modulate pathway outcomes by altering sequences at either the genomic or the transcriptomic level. RNA editing targets transcripts within known disease-driving pathways such as apoptosis, p53 and NF-κB signaling, as well as the RIG-I-like pathway. In this context, we show that ADAR1-mediated editing within MAVS transcript positively correlates with MAVS protein expression levels, associating with increased interferon/NF-κB signaling and T cell exhaustion. Finally, using targeted RNA base editing tools to restore editing within MAVS 3'UTR in ADAR1-deficient cells, we demonstrate that editing is likely to be causal to an increase in downstream signaling in the absence of activation by canonical nucleic acid receptor sensing.

Cholesterol efflux pathways hinder KRAS-driven lung tumor progenitor cell expansion

Cholesterol efflux pathways could be exploited in tumor biology to unravel cancer vulnerabilities. A mouse model of lung-tumor-bearing KRAS^G12D mutation with specific disruption of cholesterol efflux pathways in epithelial progenitor cells promoted tumor growth. Defective cholesterol efflux in epithelial progenitor cells governed their transcriptional landscape to support their expansion and create a pro-tolerogenic tumor microenvironment (TME). Overexpression of the apolipoprotein A-I, to raise HDL levels, protected these mice from tumor development and dire pathologic consequences. Mechanistically, HDL blunted a positive feedback loop between growth factor signaling pathways and cholesterol efflux pathways that cancer cells hijack to expand. Cholesterol removal therapy with cyclodextrin reduced tumor burden in progressing tumor by suppressing the proliferation and expansion of epithelial progenitor cells of tumor origin. Local and systemic perturbations of cholesterol efflux pathways were confirmed in human lung adenocarcinoma (LUAD). Our results position cholesterol removal therapy as a putative metabolic target in lung cancer progenitor cells.

Risk factors and actionable molecular signatures in COVID-19-associated lung adenocarcinoma and lung squamous cell carcinoma patients

The molecular mechanism of COVID-19's pathogenic effect on lung cancer patients is yet unknown. In this study, we used differential gene expression pattern analysis to try to figure out the possible disease mechanism of COVID-19 and its associated risk factors in patients with the two most common types of non-small-cell lung cancer, lung adenocarcinoma and lung squamous cell carcinoma. We also used network-based approaches to identify potential diagnostic and molecular targets for COVID-19-infected lung cancer patients. Our study showed that lung cancer and COVID-19 patients share 36 genes that are expressed differently and in common. Most of these genes are expressed in lung tissues and are mostly involved in the pathogenesis of different respiratory tract diseases. Additionally, we also found that COVID-19 may affect the expression of several cancer-associated genes in lung cancer patients, such as the oncogenes JUN, TNC, and POU2AF1. Moreover, we also reported that COVID-19 may predispose lung cancer patients to other diseases like acute liver failure and respiratory distress syndrome. Also, our findings in concert with published literature suggest that molecular signatures like hsa-mir-93-5p, CCNB2, IRF1, CD163, and different immune cell-based approaches could help both diagnose and treat this group of patients. Overall, the scientific results of this research will aid in the formulation of suitable management strategies as well as the development of diagnostic and therapeutic methods for COVID-19-infected lung cancer patients.

Core genes in lung adenocarcinoma identified by integrated bioinformatic analysis

This study aims to identify potential core genes of lung adenocarcinoma (LUAD). Three datasets (GSE32863, GSE43458, and GSE116959) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between LUAD and normal tissues were filtrated by GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed via Metascape database. The protein-protein interaction (PPI) network was constructed and core genes were identified using STRING and Cytoscape. Core genes expressions and their relevant clinical characteristics were performed via Oncomine and UALCAN databases respectively. The correlation between core genes and immune infiltrates was investigated by TIMER database. Kaplan-Meier plotter was performed for survival analysis. The signal pathway network of core genes was mapped by KEGG Mapper analysis tool. In this study, ten core genes were significantly related to overall survival (OS) of LUAD patients, which can provide clues for prognosis of LUAD.

Molecular regulation of hypoxia through the lenses of noncoding RNAs and epitranscriptome

Cells maintain homeostasis in response to environmental stress through specific cell stress responses. Hypoxic stress, well known to be associated with diverse solid tumors, is one of the main reasons for cancer-related mortality. Although cells can balance themselves well during hypoxic stress, the underlying molecular mechanisms are not well understood. The enhanced appreciation of diverse roles played by noncoding transcriptome and epigenome in recent years has brought to light the involvement of noncoding RNAs and epigenetic modifiers in hypoxic regulation. The emergence of techniques like deep sequencing has facilitated the identification of large numbers of long noncoding RNAs (lncRNAs) that are differentially regulated in various cancers. Similarly, proteomic studies have identified diverse epigenetic modifiers such as HATs, HDACs, DNMTs, polycomb groups of proteins, and their possible roles in the regulation of hypoxia. The crosstalk between lncRNAs and epigenetic modifiers play a pivotal role in hypoxia-induced cancer initiation and progression. Besides the lncRNAs, several other noncoding RNAs like circular RNAs, miRNAs, and so forth are also expressed during hypoxic conditions. Hypoxia has a profound effect on the expression of noncoding RNAs and epigenetic modifiers. Conversely, noncoding RNAs/epigenetic modifies can regulate the hypoxia signaling axis by modulating the stability of the hypoxia-inducible factors (HIFs). The focus of this review is to illustrate the molecular orchestration underlying hypoxia biology, especially in cancers, which can help in identifying promising therapeutic targets in hypoxia-induced cancers. This article is categorized under: RNA Turnover and Surveillance > Regulation of RNA Stability RNA in Disease and Development > RNA in Disease RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.

Focus on the molecular mechanisms of cisplatin resistance based on multi-omics approaches

Cisplatin is commonly used in combination with other cytotoxic agents as a standard treatment regimen for a variety of solid tumors, such as lung, ovarian, testicular, and head and neck cancers. However, the effectiveness of cisplatin is accompanied by toxic side effects, for instance, nephrotoxicity and neurotoxicity. The response of tumors to cisplatin treatment involves multiple physiological processes, and the efficacy of chemotherapy is limited by the intrinsic and acquired resistance of tumor cells. Although enormous efforts have been made toward molecular mechanisms of cisplatin resistance, the development of omics provides new insights into the understanding of cisplatin resistance at genome, transcriptome, proteome, metabolome and epigenome levels. Mechanism studies using different omics approaches revealed the necessity of multi-omics applications, which provide information at different cellular function levels and expand our recognition of the peculiar genetic and phenotypic heterogeneity of cancer. The present work systematically describes the underlying mechanisms of cisplatin resistance in different tumor types using multi-omics approaches. In addition to the classical mechanisms such as enhanced drug efflux, increased DNA damage repair and changes in the cell cycle and apoptotic pathways, other changes like increased protein damage clearance, increased protein glycosylation, enhanced glycolytic process, dysregulation of the oxidative phosphorylation pathway, ferroptosis suppression and mRNA m6A methylation modification can also induce cisplatin resistance. Therefore, utilizing the integrated omics to identify key signaling pathways, target genes and biomarkers that regulate chemoresistance are essential for the development of new drugs or strategies to restore tumor sensitivity to cisplatin.

Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC.

Interplay between Non-Coding RNAs and NRF2 in Different Cancers: Spotlight on MicroRNAs and Long Non-Coding RNAs

Cancer is a multifactorial disease, and a wealth of information has enabled basic and clinical researchers to develop a better conceptual knowledge of the highly heterogeneous nature of cancer. Deregulations of spatio-temporally controlled transduction pathways play a central role in cancer progression. NRF2-driven signaling has engrossed significant attention because of its fundamentally unique features to dualistically regulate cancer progression. Context-dependent diametrically opposed roles of NRF2-induced signaling are exciting. More importantly, non-coding RNA (ncRNA) mediated regulation of NRF2 and interplay between NRF2 and ncRNAs have added new layers of complexity to already intricate nature of NRF2 signaling. There is a gradual enrichment in the existing pool of knowledge related to interplay between microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in different cancers. However, surprisingly, there are no clues about interplay between circular RNAs and NRF2 in various cancers. Therefore, future studies must converge on the functional characterization of additional important lncRNAs and circular RNAs, which regulated NRF2-driven signaling or, conversely, NRF2 transcriptionally controlled their expression to regulate various stages of cancer. SIGNIFICANCE STATEMENT: Recently, many researchers have focused on the NRF2-driven signaling in cancer progression. Excitingly, discovery of non-coding RNAs has added new layers of intricacy to the already complicated nature of KEAP1/NRF2 signaling in different cancers. These interactions are shaping the NRF2-driven signaling landscape, and better knowledge of these pathways will be advantageous in pharmacological modulation of non-coding RNA-mediated NRF2 signaling in various cancers.

Integrated bioinformatics analysis of microarray data from the GEO database to identify the candidate genes linked to poor prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common cancers with high morbidity and mortality and remains a crucial factor endangering human health.

OBJECTIVE

This study aimed to elucidate the potential treatment target and prognostic biomarker in patients with LUAD through a comprehensive bioinformatics analysis.

METHODS

The three public microarray datasets of GSE118370, GSE116959, and GSE43767 were obtained from the GEO data resource. The DEGs were explored between LUAD and non-malignant samples using GEO2R online tool in GEO data resource. GO along with KEGG analysis of DEGs were examined using WebGestalt tool. The STRING web resource was employed to develop the PPI network of DEGs, whereas Cytoscape software was employed to perform module analysis. Finally, the mRNA, protein expression along with survival analysis of hub genes were explored via GEPIA, HPA along with Kaplan-Meier plotter web resource, respectively.

RESULTS

Only 82 upregulated and 105 downregulated DEGs were found among the three datasets. Further, GO analysis illustrated that 187 DEGs were primary enriched in extracellular structure organization, tube development along with cell adhesion. The KEGG enrichments showed that these DEGs were primary linked to leukocyte transendothelial migration, vascular smooth muscle contraction along with ECM-receptor interaction. Among the 187 DEGs, the 10 hub genes (P4HB, SPP1, CP, GOLM1, COL1A1, MMP9, COL10A1, APOA1, COL4A6, and TIMP1) were identified. The mRNA along with protein levels of hub genes in LUAD tissues were further verified by Oncomine, UCSC Xena, GEPIA and HPA databases. Additionally, overall survival curves illustrated that LUAD patients with the higher levels of P4HB, SPP1, COL1A1, and MMP9 were dramatically linked to shorter overall survival.

CONCLUSIONS

The current study identified DEGs candidate genes (P4HB, SPP1, COL1A1, and MMP9) and pathways in LUAD using bioinformatics analysis, which could enhance our understanding of pathogenesis along with underlying molecular events in LUAD, and these hub genes and pathways may help provide candidate treatment targets for LUAD.

Glutathione peroxidase 2 overexpression promotes malignant progression and cisplatin resistance of KRAS‑mutated lung cancer cells

Kirsten rat sarcoma viral oncogene homolog (KRAS) aberrations frequently occur in patients with lung cancer. Oncogenic KRAS is characterized by excessive reactive oxygen species (ROS) accumulation, thus, ROS detoxification may contribute to KRAS‑driven lung tumorigenesis. In the present study, the influence of glutathione peroxidase 2 (GPX2) on malignant progression and cisplatin resistance of KRAS‑driven lung cancer was explored. The RNA sequencing data from TCGA lung cancer samples and GEO database were downloaded and analyzed. The effects of GPX2 on KRAS‑driven lung tumorigenesis were evaluated by western blotting, cell viability assay, soft agar assay, Transwell assay, tumor xenograft model, flow cytometry, BrdU incorporation assay, transcriptome RNA sequencing, luciferase reporter assay and RNA immunoprecipitation. In the present study, GPX2 was upregulated in patients with non‑small cell lung carcinoma (NSCLC), and positively correlated with poor overall survival. Ectopic GPX2 expression facilitated malignant progression of KRAS^G12C‑transformed BEAS‑2B cells. Moreover, GPX2 overexpression promoted growth, migration, invasion, tumor xenograft growth and cisplatin resistance of KRAS‑mutated NSCLC cells, while GPX2 knockdown exhibited the opposite effects. GPX2 overexpression reduced ROS accumulation and increased matrix metalloproteinase‑1 (MMP1) expression in KRAS‑mutated NSCLC cells. In addition, GPX2 was directly targeted by miR‑325‑3p, while MMP1 knockdown or miR‑325‑3p overexpression partially abrogated the effects of GPX2 in NSCLC cells. In conclusion, the results indicated that GPX2 facilitated malignant progression and cisplatin resistance of KRAS‑driven lung cancer, and inhibition of GPX2 may be a feasible strategy for lung cancer treatment, particularly in patients with active KRAS mutations.

CTpathway: a CrossTalk-based pathway enrichment analysis method for cancer research

BACKGROUND

Pathway enrichment analysis (PEA) is a common method for exploring functions of hundreds of genes and identifying disease-risk pathways. Moreover, different pathways exert their functions through crosstalk. However, existing PEA methods do not sufficiently integrate essential pathway features, including pathway crosstalk, molecular interactions, and network topologies, resulting in many risk pathways that remain uninvestigated.

METHODS

To overcome these limitations, we develop a new crosstalk-based PEA method, CTpathway, based on a global pathway crosstalk map (GPCM) with >440,000 edges by combing pathways from eight resources, transcription factor-gene regulations, and large-scale protein-protein interactions. Integrating gene differential expression and crosstalk effects in GPCM, we assign a risk score to genes in the GPCM and identify risk pathways enriched with the risk genes.

RESULTS

Analysis of >8300 expression profiles covering ten cancer tissues and blood samples indicates that CTpathway outperforms the current state-of-the-art methods in identifying risk pathways with higher accuracy, reproducibility, and speed. CTpathway recapitulates known risk pathways and exclusively identifies several previously unreported critical pathways for individual cancer types. CTpathway also outperforms other methods in identifying risk pathways across all cancer stages, including early-stage cancer with a small number of differentially expressed genes. Moreover, the robust design of CTpathway enables researchers to analyze both bulk and single-cell RNA-seq profiles to predict both cancer tissue and cell type-specific risk pathways with higher accuracy.

CONCLUSIONS

Collectively, CTpathway is a fast, accurate, and stable pathway enrichment analysis method for cancer research that can be used to identify cancer risk pathways. The CTpathway interactive web server can be accessed here http://www.jianglab.cn/CTpathway/ . The stand-alone program can be accessed here https://github.com/Bioccjw/CTpathway .

MDFI is a novel biomarker for poor prognosis in LUAD

Background

Approximately 80% of lung cancers are non-small cell lung cancers (NSCLC). Lung adenocarcinoma (LUAD) is the main subtype of NSCLC. The incidence and mortality of lung cancer are also increasing yearly. Myogenic differentiation family inhibitor (MDFI) as a transcription factor, its role in lung cancer has not yet been clarified.

Methods

LUAD data were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO), analyzed and plotted using the R language. Associations between Clinical information and MDFI expression were assessed using logistic regression analyses to explore the effects of MDFI on LUAD. Two sets of tissue microarrays (TMAs) further confirmed the overexpression of MDFI in LUAD and its impact on prognosis. In addition, we examined the correlation between MDFI and immune infiltration. To investigate the effect of MDFI on the biological behavior of LUAD tumor cells by GSEA and GO/KEGG analysis. The survival status and somatic mutational characteristics of patients according to MDFI levels were depicted and analyzed.

Results

Expression of high MDFI in LUAD tissues via analyzing TCGA dataset (P <0.001). Kaplan-Meier survival analysis indicated a poor prognosis for those patients with LUAD who had upregulated MDFI expression levels (P <0.001). This was also verified by two groups of TMAs (P=0.024). Using logistic statistics analysis, MDFI was identified as an independent predictive factor and was associated with poor prognosis in LUAD (P <0.001, P =0.021). Assessment of clinical characteristics, tumor mutation burden (TMB), and tumor microenvironment (TME) between high- and low-expression score groups showed lower TMB, richer immune cell infiltration, and better prognosis in the low-risk group.

Conclusion

This study showed that MDFI was overexpressed in LUAD and was significantly associated with poor prognosis, indicating that MDFI may be used as a potential novel biomarker for the diagnosis and prognosis of LUAD. MDFI is associated with immune infiltration of LUAD and it is reasonable to speculate that it plays an important role in tumor proliferation and spread. In view of the significant differences in MDFI expression between different biological activities, LUAD patients with MDFI overexpression may obtain more precise treatment strategies in the clinic.

A Risk-Assessing Signature Based on Hypoxia- and Immune-Related Genes for Prognosis of Lung Adenocarcinoma Patients

Lung Adenocarcinoma (LUAD) drastically influences human health. Tumor hypoxia and immunity impact hugely on the immunotherapeutic effect of LUAD patients. This study is aimed at exploring the prognostic markers associated with hypoxia and immunity in LUAD patients and evaluates their reliability. The relationship between hypoxia and immune-related genes and prognoses of LUAD patients was investigated by the univariate regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were used to reveal the enriched pathways and biological processes of prognosis-related genes. Univariate, LASSO, and multivariate Cox regression analyses were used to construct a prognostic signature and verify its independence. The reliability of the signature was evaluated by the Principal Component Analysis (PCA), the Kaplan-Meier (K-M) curve, and the receiver operating characteristic (ROC) curve. Gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and single-sample GSEA (ssGSEA) further verified the performance of the signature. Finally, a prognostic signature for LUAD was constructed based on 7 hypoxia- and immune-related genes. According to riskScores acquired from the signature, the test set was divided into groups, where the prognosis of high-risk patients was poor. The feature genes had good reliability, and the riskScore could be used as an independent prognostic factor for LUAD patients. Meanwhile, high TMB scores and low immune scores were found in high-risk patients, and feature genes were enriched in signaling pathways such as cell cycle and p53 signaling pathway. In sum, a prognostic signature based on 7 hypoxia- and immune-related genes was constructed.

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.

Reactive Oxygen Species and Long Non-Coding RNAs, an Unexpected Crossroad in Cancer Cells

Long non-coding RNAs (lncRNA) have recently been identified as key regulators of oxidative stress in several malignancies. The level of reactive oxygen species (ROS) must be constantly regulated to maintain cancer cell proliferation and chemoresistance and to prevent apoptosis. This review will discuss how lncRNAs alter the ROS level in cancer cells. We will first describe the role of lncRNAs in the nuclear factor like 2 (Nrf-2) coordinated antioxidant response of cancer cells. Secondly, we show how lncRNAs can promote the Warburg effect in cancer cells, thus shifting the cancer cell’s “building blocks” towards molecules important in oxidative stress regulation. Lastly, we explain the role that lncRNAs play in ROS-induced cancer cell apoptosis and proliferation.

Drug resistance in NSCLC is associated with tumor micro-environment

BACKGROUND

Tumor cell resistance to chemotherapy is the most critical factor that influences the prognosis of cancer patients. It is generally believed that drug resistance is caused by genetic alterations in tumor cells; however, the relationship between drug resistance and the tumor microenvironment (TME) has not been adequately studied. Herein, we successfully identified drug resistance and sensitivity clusters using single-cell transcriptome sequencing data from GSE149383 and established a proportional hazards model to find genes that affected prognosis. The results showed that marker genes between resistant and sensitive clusters were significantly associated with the TME; additionally, the model showed good reliability. Furthermore, we used bulk RNA-seq data to analyze the expression of CD24 and CYP1B1, which revealed little difference in the levels of the two genes in normal and tumor tissues but a significant difference in their expression between drug-resistant and -sensitive cells. In conclusion, our study demonstrated a link between drug resistance and the TME, and we found that CD24 and CYP1B1 may be key regulators of drug resistance development in tumor cells via altering the TME.

Long noncoding RNA LINC00239 inhibits ferroptosis in colorectal cancer by binding to Keap1 to stabilize Nrf2

Ferroptosis, a novel regulated cell death induced by iron-dependent lipid peroxidation, plays an important role in tumor development and drug resistance. Long noncoding RNAs (lncRNAs) are associated with various types of cancer. However, the precise roles of many lncRNAs in tumorigenesis remain elusive. Here we explored the transcriptomic profiles of lncRNAs in primary CRC tissues and corresponding paired adjacent non-tumor tissues by RNA-seq and found that LINC00239 was significantly overexpressed in colorectal cancer tissues. Abnormally high expression of LINC00239 predicts poorer survival and prognosis in colorectal cancer patients. Concurrently, we elucidated the role of LINC00239 as a tumor-promoting factor in CRC through in vitro functional studies and in vivo tumor xenograft models. Importantly, overexpression of LINC00239 decreased the anti-tumor activity of erastin and RSL3 by inhibiting ferroptosis. Collectively, these data suggest that LINC00239 plays a novel and indispensable role in ferroptosis by nucleotides 1-315 of LINC00239 to interact with the Kelch domain (Nrf2-binding site) of Keap1, inhibiting Nrf2 ubiquitination and increasing Nrf2 protein stability. Considering the recurrence and chemoresistance constitute the leading cause of death in colorectal cancer (CRC), ferroptosis induction may be a promising therapeutic strategy for CRC patients with low LINC00239 expression.

The beginning of GPX2 and 30 years later

We published the first paper to characterize GPX2 (aka GSHPx-GI) as a selenoenzyme with glutathione peroxidase activity in 1993. Among the four Se-GPX isozymes, GPX1-4, GPX1 and GPX2 are closely related in terms of structure, substrate specificities, and subcellular localization. What sets them apart are distinct patterns of gene regulation, tissue distribution and response to selenium. While we identified the digestive tract epithelium as the main site of GPX2 expression, later work has shown GPX2 is found more widely in epithelial tissues with concentration of expression in stem cell and proliferative compartments. GPX2 expression is regulated over a wide range of levels by many pathways, including NRF2, WNT, p53, RARE and this often results in attaching undue significance to GPX2 as GPX2 is only a part of a system of hydroperoxidase activities, including GPX1, peroxiredoxins and catalase. These other activities may play equal or greater roles, particularly in cell lines cultured without selenium supplementation and often with very low GPX2 levels. This could be assessed by examining levels of mRNA and protein among these various peroxidases at the outset of studies. As an example, it was found that GPX1 responds to the absence of GPX2 in mouse ileum and colon epithelium with higher expression. As such, both Gpx1 and Gpx2 had to be knocked out in mice to produce ileocolitis. However, we note that the actual role of GPX1 and GPX2 in relation to peroxiredoxin function is unclear. There may be an interdependence that requires only low amounts of GPX1 and/or GPX2 in a supporting role to maintain proper peroxiredoxin function. GPX2 levels may be prognostic for cancer progression in colon, breast, prostate and liver, however, there is no consistent trend for higher or lower levels to be favorable.

Evaluating the Prognostic and Therapeutic Potentials of the Proteasome 26S Subunit, ATPase (PSMC) Family of Genes in Lung Adenocarcinoma: A Database Mining Approach

This study explored the prognostic and therapeutic potentials of multiple Proteasome 26S Subunit, ATPase (PSMC) family of genes (PSMC1-5) in lung adenocarcinoma (LUAD) diagnosis and treatment. All the PSMCs were found to be differentially expressed (upregulated) at the mRNA and protein levels in LUAD tissues. The promoter and multiple coding regions of PSMCs were reported to be differentially and distinctly methylated, which may serve in the methylation-sensitive diagnosis of LUAD patients. Multiple somatic mutations (alteration frequency: 0.6-2%) were observed along the PSMC coding regions in LUAD tissues that could assist in the high-throughput screening of LUAD patients. A significant association between the PSMC overexpression and LUAD patients' poor overall and relapse-free survival (p < 0.05; HR: >1.3) and individual cancer stages (p < 0.001) was discovered, which justifies PSMCs as the ideal targets for LUAD diagnosis. Multiple immune cells and modulators (i.e., CD274 and IDO1) were found to be associated with the expression levels of PSMCs in LUAD tissues that could aid in formulating PSMC-based diagnostic measures and therapeutic interventions for LUAD. Functional enrichment analysis of neighbor genes of PSMCs in LUAD tissues revealed different genes (i.e., SLIRP, PSMA2, and NUDSF3) previously known to be involved in oncogenic processes and metastasis are co-expressed with PSMCs, which could also be investigated further. Overall, this study recommends that PSMCs and their transcriptional and translational products are potential candidates for LUAD diagnostic and therapeutic measure discovery.

High expression of PTGES3 is an independent predictive poor prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Immune-infiltration was positively relationship with overall survival in lung adenocarcinoma (LUAD). Nevertheless, the potential clinical value of PTGES3, especially in terms of prognosis and tumor immune-infiltration in LUAD had not been fully elucidated.

METHODS

Original data available from TCGA and GEO databases and integrated via R3.6.3. Kaplan-Meier and Cox regression methods were used to examine the effect of PTGES3 expression in overall survival, and nomogram was performed to illustrate the correlation between the PTGES3 expression and the risk of LUAD. The associate between PTGES3 and cancer immune characteristics were analyzed via the TISIDB databases. Western blot and RT-qPCR were used to analyze PTGES3 expression in the clinical lung adenocarcinoma tissue samples or non-small cell lung cancer cell lines.

RESULTS

PTGES3 mRNA and protein expression were significantly elevated in LUAD compared with normal lung tissues. Up-regulated PTGES3 was significantly associated with pathologic stage and TM stage. Kaplan-Meier survival analysis and subgroup analysis showed that up-regulated PTGES3 was associated with a worse overall survival of LUAD (HR = 1.71 (1.27-2.31), p < 0.001). Multivariate Cox analysis showed that high PTGES3 expression was an independent factor affecting overall survival (HR = 1.64 (1.14-2.37), p < 0.001). GO and KEGG analysis revealed that the cell cycle, regulation of DNA replication, and regulation of innate immune response were enriched. A positive correlation between PTGES3 expression and immune infiltrating levels of Th2 cells was found.

CONCLUSION

PTGES3 may play an important role in the cell cycle and as an independent predictive prognostic biomarker correlates with immune infiltrates in lung adenocarcinoma.

Comprehensive Analysis and Reinforcement Learning of Hypoxic Genes Based on Four Machine Learning Algorithms for Estimating the Immune Landscape, Clinical Outcomes, and Therapeutic Implications in Patients With Lung Adenocarcinoma

Background

Patients with lung adenocarcinoma (LUAD) exhibit significant heterogeneity in therapeutic responses and overall survival (OS). In recent years, accumulating research has uncovered the critical roles of hypoxia in a variety of solid tumors, but its role in LUAD is not currently fully elucidated. This study aims to discover novel insights into the mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers by exploring the potential association between hypoxia and LUAD.

Methods

Four machine learning approaches were implemented to screen out potential hypoxia-related genes for the prognosis of LUAD based on gene expression profile of LUAD samples obtained from The Cancer Genome Atlas (TCGA), then validated by six cohorts of validation datasets. The risk score derived from the hypoxia-related genes was proven to be an independent factor by using the univariate and multivariate Cox regression analyses and Kaplan-Meier survival analyses. Hypoxia-related mechanisms based on tumor mutational burden (TMB), the immune activity, and therapeutic value were also performed to adequately dig deeper into the clinical value of hypoxia-related genes. Finally, the expression level of hypoxia genes was validated at protein level and clinical samples from LUAD patients at transcript levels.

Results

All patients in TCGA and GEO-LUAD group were distinctly stratified into low- and high-risk groups based on the risk score. Survival analyses demonstrated that our risk score could serve as a powerful and independent risk factor for OS, and the nomogram also exhibited high accuracy. LUAD patients in high-risk group presented worse OS, lower TMB, and lower immune activity. We found that the model is highly sensitive to immune features. Moreover, we revealed that the hypoxia-related genes had potential therapeutic value for LUAD patients based on the drug sensitivity and chemotherapeutic response prediction. The protein and gene expression levels of 10 selected hypoxia gene also showed significant difference between LUAD tumors tissues and normal tissues. The validation experiment showed that the gene transcript levels of most of their genes were consistent with the levels of their translated proteins.

Conclusions

Our study might contribute to the optimization of risk stratification for survival and personalized management of LUAD patients by using the hypoxia genes, which will provide a valuable resource that will guide both mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers.

Expressional regulation of NKG2DLs is associated with the tumor development and shortened overall survival in lung adenocarcinoma

Natural killer group 2D ligands (NKG2DLs) are expressed on tumor cells as a ligand for Natural killer group 2D (NKG2D) receptors. NKG2DLs interact with NKG2D to induce immune cell-mediated cytotoxicity for eliminating tumors. Studies demonstrated that tumor cells can reduce NKG2DLs' expression to escape from anti-tumor immunity, leading to an aggressive cancer phenotype and poor prognosis in some cancers. However, these studies are limited and there is no comprehensive work on the regulation of NKG2DLs in lung adenocarcinoma (LUAD) which is one of the deadliest cancers worldwide. Here, we conducted an in silico analysis to evaluate the changes in NKG2DLs in LUAD by analyzing The Cancer Genome Atlas and the Gene Expression Omnibus datasets including tumor vs. normal comparisons, TNM stages, survival and infiltrating immune estimation profile. Results indicated that some members of NKG2DL were downregulated in LUAD as compared to normal samples. We determined that MICA (MHC class I polypeptide-related sequence A) was the most and significantly downregulated ligand among others and the results were nearly consistent with the different datasets which we used. Furthermore, survival analysis revealed that down-regulated MICA transcript expression might be one of the prognostic indicators of LUAD. Interestingly, according to the immune cell infiltrating analysis, there wasn't a direct correlation between the MICA transcript expression and immune cell infiltration, while for MICB there was. In addition, in genetic alteration, DNA methylation and miRNA analyses, we did not observe critical outcomes that would clarify the down-regulated MICA expression in detail. Regardless, this study is highly comprehensive and contributes valuable suggestions to further functional studies about the regulation of NKG2DLs and promising immunotherapeutic approaches in LUAD.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Background

Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients.

Methods

OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration.

Results

We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells.

Conclusion

In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.

Long non-coding RNAs and exosomal lncRNAs: Potential functions in lung cancer progression, drug resistance and tumor microenvironment remodeling

Among the different kinds of tumors threatening human life, lung cancer is one that is commonly observed in both males and females. The aggressive behavior of lung cancer and interactions occurring in tumor microenvironment enhances the malignancy of this tumor. The lung tumor cells have demonstrated capacity in developing chemo- and radio-resistance. LncRNAs are a category of non-coding RNAs that do not encode proteins, but their aberrant expression is responsible for tumor development, especially lung cancer. In the present review, we focus on both lncRNAs and exosomal lncRNAs in lung cancer, and their ability in regulating proliferation and metastasis. Cell cycle progression and molecular mechanisms related to lung cancer metastasis such as EMT and MMPs are regulated by lncRNAs. LncRNAs interact with miRNAs, STAT, Wnt, EZH2, PTEN and PI3K/Akt signaling pathways to affect progression of lung cancer cells. LncRNAs demonstrate both tumor-suppressor and tumor-promoting functions in lung cancer. They can be considered as biomarkers in lung cancer and especially exosomal lncRNAs present in body fluids are potential tools for minimally invasive diagnosis. Furthermore, we discuss regulation of lncRNAs by anti-cancer drugs and genetic tools as well as the role of these factors in therapy response of lung cancer cells.

MYC/MAX-Activated LINC00958 Promotes Lung Adenocarcinoma by Oncogenic Transcriptional Reprogramming Through HOXA1 Activation

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer. The role of the long non-coding RNA (lncRNA) LINC00958, which regulates the malignant behavior of multiple tumors, in LUAD has not been elucidated.

METHODS

Tissue microarray, FISH, and qRT-PCR were used to detect the expression of LINC00958. Plasmid and viral infections were used to manipulate gene expression. The role of LINC00958 in LUAD was studied by cell proliferation analysis, cell apoptosis analysis, cell migration and invasion analysis, and subcutaneous inoculation of animal models. At the same time, RNA-Seq, RNA pull-down, ChIRP, ChIP, and luciferase reporter gene assays were performed to clarify the mechanism.

RESULTS

The expression of LINC00958 in LUAD tissues was significantly upregulated when compared with that in adjacent tissues and could independently predict poor survival of patients with LUAD. LINC00958 knockdown significantly inhibited the growth and metastasis of lung cancer cells in vitro and in vivo. LINC00958 localized to the nucleus, regulated oncogenes and metabolism-related and immune response-related genes, and interacted with histones. The targets of LINC00958 were TRPV3, STAP2, and EDN2 promoters with motifs of HOXA1, NANOG, FOSL2, JUN, and ATF4. Moreover, HOXA1 overexpression mitigated the LINC00958 knockdown-induced oncogenic phenotype. MYC/MAX motif, which was detected at the cis-element of LINC00958, trans-activated the LINC00958 promoter.

CONCLUSIONS

MYC/MAX-trans-activated LINC00958 promotes the malignant behavior of LUAD by recruiting HOXA1 and inducing oncogenic reprogramming.

The crosstalk between reactive oxygen species and noncoding RNAs: from cancer code to drug role

Oxidative stress (OS), characterized by the excessive accumulation of reactive oxygen species (ROS), is an emerging hallmark of cancer. Tumorigenesis and development driven by ROS require an aberrant redox homeostasis, that activates onco-signaling and avoids ROS-induced programmed death by orchestrating antioxidant systems. These processes are revealed to closely associate with noncoding RNAs (ncRNAs). On the basis of the available evidence, ncRNAs have been widely identified as multifarious modulators with the involvement of several key redox sensing pathways, such as NF-κB and Nrf2 signaling, therefore potentially becoming effective targets for cancer therapy. Furthermore, the vast majority of ncRNAs with property of easy detected in fluid samples (e.g., blood and urine) facilitate clinicians to monitor redox homeostasis, indicating a novel method for cancer diagnosis. Herein, focusing on carcinoma initiation, metastasis and chemoradiotherapy resistance, we aimed to discuss the ncRNAs-ROS network involved in cancer progression, and the potential clinical application as biomarkers and therapeutic targets.

KRAS-related long noncoding RNAs in human cancers

KRAS is one of the most widely prevalent proto-oncogenes in human cancers. The constitutively active KRAS oncoprotein contributes to both tumor onset and cancer development by promoting cell proliferation and anchorage-independent growth in a MAPK pathway-dependent manner. The expression of microRNAs (miRNAs) and the KRAS oncogene are known to be dysregulated in various cancers, while long noncoding RNAs (lncRNAs) can act as regulators of the miRNAs targeting KRAS oncogene in different cancers and have gradually become a focus of research in recent years. In this review article, we summarize recent advances in the research on lncRNAs that have sponging effects on KRAS-targeting miRNAs as crucial mediators of KRAS expression in different cell types and organs. A deeper understanding of lncRNA function in KRAS-driven cancers is of major fundamental importance and will provide a valuable clinical tool for the diagnosis, prognosis, and eventual treatment of cancers.

CD73 Severed as a Potential Prognostic Marker and Promote Lung Cancer Cells Migration via Enhancing EMT Progression

To investigate the expression levels and prognostic value of CD73 in lung cancer. And moreover, to identify the effect and potential mechanism of CD73 on lung cancer cells proliferation and migration. CD73 expression levels in lung cancer were analyzed base on GEPIA2 and GEO database. GEPIA2 and Kaplan-Meier Plotter (KM Plotter) was used to analyzed the correlation between CD73 expression and prognosis. GEO dataset were analyzed via GEO2R. CD73 overexpression cell model was construction via recombinant lentivirus transfection into A549 and NCI-H520 cells. CCK8 assay were used to investigate cells proliferation. Migration and invasion ability were evaluated by scratch and transwell methods. Base on GEPIA2, GSE32683, GSE116959 and GSE37745 dataset, we found that CD73 expression were significant higher in tumor tissues of lung adenocarcinoma (LUAD) compared with that in non-tumor normal tissues and in lung squamous cell carcinoma (LUSC), while there were no significant difference of CD73 expression between LUSC and normal control tissues. Interestingly, a high CD73 level predict poor overall survival (OS) of LUSC. However, GEPIA2 and KM plotter showed the opposite conclusion of prognostic value of CD73 in LUAD. By using cell experiments, we found that CD73 overexpression promoted proliferation and migration of LUAD A549 cells. However, there was no significant effect of CD73 overexpression on LUSC NCI-H520 cells. Furthermore, CD73 overexpression facilitates epithelial to mesenchymal transition (EMT) progression of A549 cells. In conclusion, our results indicated that CD73 expression were increased in LUAD and might be an poor prognostic marker for LUSC patients. CD73 play an important role in LUAD cells proliferation and migration. These data allowed to support CD73 as a therapeutic target for LUAD.

Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation (RRA) method between tumor and normal tissues from six Gene Expression Omnibus databases (GSE43458, GSE62949, GSE68465, GSE115002, GSE116959, and GSE118370), followed by a selection of prognostic modules using weighted gene co-expression network analysis. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were applied to identify nine hub genes (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) that constructed a prognostic risk model. The RNA expressions of nine hub genes were validated in tumor and normal tissues by RNA-sequencing and single-cell RNA-sequencing, while immunohistochemistry staining from the Human Protein Atlas database showed consistent results in the protein levels. The risk model revealed that high-risk patients were associated with poor prognoses, including advanced stages and low survival rates. Furthermore, a multivariate Cox regression analysis suggested that the prognostic risk model could be an independent prognostic factor for LUAD patients. A nomogram that incorporated the signature and clinical features was additionally built for prognostic prediction. Moreover, the levels of hub genes were related to immune cell infiltration in LUAD microenvironments. A CMap analysis identified 13 small molecule drugs as potential agents based on the risk model for LUAD treatment. Thus, we identified a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 as novel biomarkers and validated their prognostic and predicted values for LUAD.

Integrated analysis of hypoxia-associated lncRNA signature to predict prognosis and immune microenvironment of lung adenocarcinoma patients

Lung adenocarcinoma (LUAD) represents the main lung cancer (LC) subtype that possesses a disappointing clinical outcome over the decades. Tumor hypoxia is closely bound up with dismal survival for malignant tumor cases. We identified hypoxia-associated long non-coding RNA (lncRNA) signature to be an explicit indicator for predicting prognosis. The present work acquired RNA-seq and associated clinical data from The Cancer Genome Atlas (TCGA) database. Consensus cluster analysis characterized the hypoxia status of LUAD patients. Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) method determined significantly prognosis-related lncRNAs which were used to create a prognostic model. Diverse statistical approaches like the Kaplan-Meier curve, receiver operating characteristic (ROC) curve, and nomogram were adopted to verify the accuracy of the risk score. The potential immune environment landscape was unearthed by the CIBERSORT algorithm. Three hypoxia-related clusters were determined and 221 differentially expressed hypoxia-related lncRNAs were screened out. We developed a new predictive model based on seven lncRNAs (LINC00941, AC022784.1, AC079949.2, LINC00707, AL161431.1, AC010980.2 and AC090001.1). Kaplan-Meier curves and ROC plots uncovered the reliable predictive power of the risk score model. In addition, the immunosuppressive landscape was presented in the high-risk group by immune cell infiltration analysis. The seven hypoxia lncRNAs survival signature in our article are robust, accurate tools for predicting overall survival in LUAD patients.

Cisplatin and phenanthriplatin modulate long-noncoding RNA expression in A549 and IMR90 cells revealing regulation of microRNAs, Wnt/β-catenin and TGF-β signaling

The monofunctional platinum(II) complex, phenanthriplatin, acts by blocking transcription, but its regulatory effects on long-noncoding RNAs (lncRNAs) have not been elucidated relative to traditional platinum-based chemotherapeutics, e.g., cisplatin. Here, we treated A549 non-small cell lung cancer and IMR90 lung fibroblast cells for 24 h with either cisplatin, phenanthriplatin or a solvent control, and then performed microarray analysis to identify regulated lncRNAs. RNA22 v2 microRNA software was subsequently used to identify microRNAs (miRNAs) that might be suppressed by the most regulated lncRNAs. We found that miR-25-5p, -30a-3p, -138-5p, -149-3p, -185-5p, -378j, -608, -650, -708-5p, -1253, -1254, -4458, and -4516, were predicted to target the cisplatin upregulated lncRNAs, IMMP2L-1, CBR3-1 and ATAD2B-5, and the phenanthriplatin downregulated lncRNAs, AGO2-1, COX7A1-2 and SLC26A3-1. Then, we used qRT-PCR to measure the expression of miR-25-5p, -378j, -4516 (A549) and miR-149-3p, -608, and -4458 (IMR90) to identify distinct signaling effects associated with cisplatin and phenanthriplatin. The signaling pathways associated with these miRNAs suggests that phenanthriplatin may modulate Wnt/β-catenin and TGF-β signaling through the MAPK/ERK and PTEN/AKT pathways differently than cisplatin. Further, as some of these miRNAs may be subject to dissimilar lncRNA targeting in A549 and IMR90 cells, the monofunctional complex may not cause toxicity in normal lung compared to cancer cells by acting through distinct lncRNA and miRNA networks.

Regulation of Nrf2 signaling pathway in heart failure: Role of extracellular vesicles and non-coding RNAs

The balance between pro- and antioxidant molecules has been established as an important driving force in the pathogenesis of cardiovascular disease. Chronic heart failure is associated with oxidative stress in the myocardium and globally. Redox balance in the heart and brain is controlled, in part, by antioxidant proteins regulated by the transcription factor Nuclear factor erythroid 2-related factor 2 (Nrf2), which is reduced in the heart failure state. Nrf2 can, in turn, be regulated by a variety of mechanisms including circulating microRNAs (miRNAs) encapsulated in extracellular vesicles (EVs) derived from multiple cell types in the heart. Here, we review the role of the Nrf2 and antioxidant enzyme signaling pathway in mediating redox balance in the myocardium and the brain in the heart failure state. This review focuses on Nrf2 and antioxidant protein regulation in the heart and brain by miRNA-enriched EVs in the setting of heart failure. We discuss EV-mediated intra- and inter-organ communications especially, communication between the heart and brain via an EV pathway that mediates cardiac function and sympatho-excitation in heart failure. Importantly, we speculate how engineered EVs with specific miRNAs or antagomirs may be used in a therapeutic manner in heart failure.

Identification of SHMT2 as a Potential Prognostic Biomarker and Correlating with Immune Infiltrates in Lung Adenocarcinoma

It has attracted growing attention that the role of serine hydroxy methyl transferase 2 (SHMT2) in various types of cancers. However, the prognostic role of SHMT2 in lung adenocarcinoma (LUAD) and its relationship with immune cell infiltration is not clear. In this study, the information of mRNA expression and clinic data in LUAD were, respectively, downloaded from the GEO and TCGA database. We conducted a biological analysis to select the signature gene SHMT2. Online databases including Oncomine, GEPIA, TISIDB, TIMER, and HPA were applied to analyze the characterization of SHMT2 expression, prognosis, and the correlation with immune infiltration in LUAD. The mRNA expression and protein expression of SHMT2 in LUAD tissues were higher than in normal tissue. A Kaplan-Meier analysis showed that patients with lower expression level of SHMT2 had a better overall survival rate. Multivariate analysis and the Cox proportional hazard regression model revealed that SHMT2 expression was an independent prognostic factor in patients with LUAD. Meanwhile, the gene SHMT2 was highly associated with tumor-infiltrating lymphocytes in LUAD. These results suggest that the SHMT2 gene is a promising candidate as a potential prognostic biomarker and highly associated with different types of immune cell infiltration in LUAD.

Oncogenic role of abnormal spindle‑like microcephaly‑associated protein in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant cancer worldwide. It is urgent to explore its underlying molecular mechanism and identify novel diagnostic biomarkers. Abnormal spindle-like microcephaly (ASPM) has recently received considerable attention due to its function in tumor progression. However, its role in LUAD is unclear. The present study aimed to explore the clinical role of ASPM in LUAD. Seven pairs of LUAD and adjacent normal tissues were collected to identify potential LUAD biomarkers using transcriptome sequencing. The association between ASPM expression and LUAD progression was evaluated using bioinformatics analysis and data obtained from clinical specimens. Using small interfering RNA technology, the function of ASPM was analyzed in the LUAD H1299 and A549 cell lines. Transcriptional profiling of ASPM-deficient H1299 cells was then performed to determine the downstream targets of ASPM. Using databases and clinical specimens, it was revealed that ASPM expression was frequently elevated in LUAD tissues, and this upregulation was highly associated with LUAD progression. ASPM served as an oncogenic regulator of LUAD cell proliferation and metastasis. Mechanistically, ASPM facilitated epithelial-mesenchymal transition (EMT) via the PI3K/AKT signaling pathway and 740 Y-P, an activator of this pathway, restored the migratory ability of ASPM-knockdown LUAD cells. The current study identified ASPM as an independent prognostic biomarker of LUAD that served an important oncogenic role in regulating LUAD cell metastasis by promoting EMT via the PI3K/AKT signaling pathway. Targeting ASPM may therefore be a therapeutic strategy for treating LUAD.

COL1A1 is a prognostic biomarker and correlated with immune infiltrates in lung cancer

Objective

Lung cancer (LC) is one of the top ten malignant tumors and the first leading cause of cancer-related death among both men and women worldwide. It is imperative to identify immune-related biomarkers for early LC diagnosis and treatment.

Methods

Three Gene Expression Omnibus (GEO) datasets were selected to acquire the differentially expressed genes(DEGs) between LC and normal lung samples through GEO2R tools of NCBI. To identify hub genes, the DEGs were performed functional enrichment analysis, the protein-protein interaction (PPI) network construction, and Lasso regression. Then, a nomogram was constructed to predict the prognosis of patients with carcinoma based on hub genes. We further evaluated the influence of COL1A1 on clinical prognosis using GSE3141, GSE31210, and TCGA database. Also, the correlations between COL1A1 and cancer immune infiltrates and the B7-CD28 family was investigated via TIMER and GEPIA. Further analysis of immunohistochemistry shown that the COL1A1 expression level is positively correlated with CD276 expression level.

Results

By difference analysis, there were 340 DEGs between LC and normal lung samples. Then, we picked out seven hub genes, which were identified as components of the risk signature to divide LC into low and high-risk groups. Among them, the expression of COL1A1 is highly correlated with overall survival(OS) and progression-free survival (PFS) (p < 0.05). Importantly, there is a moderate to strong positive relationships between COL1A1 expression level and infiltration level of CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level.

Conclusion

These findings suggest that COL1A1 is correlated with prognosis and immune infiltrating levels, including CD4+ T cells, Macrophage, Neutrophil, and Dendritic cell, as well as CD276 expression level, indicating COL1A1 can be a potential immunity-related biomarker and therapeutic target in LC.

Role of long non-coding RNAs on the regulation of Nrf2 in chronic diseases

Studies have identified dysregulated long non-coding RNA (lncRNA) in several diseases at transcriptional, translational, and post-translational levels. Although our mechanistic knowledge on the regulation of lncRNAs is still limited, one of the mechanisms of action attributed is binding and regulating transcription factors, thus controlling gene expression and protein function. One such transcription factor is nuclear factor erythroid 2-related factor 2 (Nrf2), which plays a critical biological role in maintaining cellular homeostasis at multiple levels in physiological and pathophysiological conditions. The levels of Nrf2 were found to be down-regulated in many chronic diseases, signifying that Nrf2 can be a key therapeutic target. Few lncRNAs like lncRNA ROR, ENSMUST00000125413, lncRNA ODRUL, Nrf2-lncRNA have been associated with the Nrf2 signaling pathway in response to various stimuli, including stress. This review discusses the regulation of Nrf2 in different responses and the potential role of specific lncRNA in modulating its transcriptional activities. This review further helps to enhance our knowledge on the regulatory role of the critical antioxidant transcription factor, Nrf2.

NRF2 Regulation by Noncoding RNAs in Cancers: The Present Knowledge and the Way Forward

Simple Summary

The NRF2 pathway represents one of the most intriguing pathways that promotes chemo- and radioresistance of neoplastic cells. Increasing findings suggest that the NRF2 signaling can be modulated by multiple epigenetic factors such as noncoding RNAs, which influence a large number of oncogenic mechanisms, both at transcriptional and at post-transcriptional levels. As a consequence, the identification and characterization of specific noncoding RNAs as biomarkers related to oxidative stress may help to clarify the relationship between them and NRF2 signaling in the tumor context, in terms of positive and negative modulation, also referring to their intersection with other NRF2 crosstalking pathways. In this review, we summarize the recent updates on NRF2 network regulation by noncoding RNAs in tumors, thus paving the way toward the potential translational role of these small RNAs as key tumor biomarkers of neoplastic processes.

Abstract

Nuclear factor erythroid 2-related factor 2 (NRF2) is the key transcription factor triggered by oxidative stress that moves in cells of the antioxidant response element (ARE)-antioxidant gene network against reactive oxygen species (ROS) cellular damage. In tumors, the NRF2 pathway represents one of the most intriguing pathways that promotes chemo- and radioresistance of neoplastic cells and its activity is regulated by genetic and epigenetic mechanisms; some of these being poorly investigated in cancer. The noncoding RNA (ncRNA) network is governed by microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) and modulates a variety of cellular mechanisms linked to cancer onset and progression, both at transcriptional and post-transcriptional levels. In recent years, the scientific findings about the effects of ncRNA landscape variations on NRF2 machines are rapidly increasing and need to be continuously updated. Here, we review the latest knowledge about the link between NRF2 and ncRNA networks in cancer, thus focusing on their potential translational significance as key tumor biomarkers.

DNA Repair-Based Gene Expression Signature and Distinct Molecular Subtypes for Prediction of Clinical Outcomes in Lung Adenocarcinoma

Objective: To conduct a robust prognostic gene expression signature and characterize molecular subtypes with distinct clinical characteristics for lung adenocarcinoma (LUAD).

Methods: Based on DNA repair genes from the GSEA database, a prognostic signature was conducted in the TCGA-LUAD training set via univariate and multivariate cox regression analysis. Its prediction power was validated by overall survival analysis, relative operating characteristic (ROC) curves and stratification analysis in the GSE72094 verification set. Involved pathways in the high- and low-risk groups were analyzed by GSEA. A nomogram was built based on the signature and clinical features and its performance was assessed by calibration plots. LUAD samples were clustered via the ConsensusClusterPlus package. The differences in clinical outcomes, single nucleotide polymorphism (SNP) and sensitivity to chemotherapy drugs between molecular subtypes were analyzed.

Results: A 13-DNA repair gene-signature was constructed for LUAD prognosis. Following validation, it can robustly and independently predict patients' clinical outcomes. The GSEA results exhibited the differences in pathways between high- and low- risk groups. A nomogram combining the signature and stage could accurately predict 1-, 3-, and 5-year survival probability. Two distinct molecular subtypes were characterized based on DNA repair genes. Patients in the Cluster 2 exhibited a worse prognosis and were more sensitive to common chemotherapy than those in the Cluster 1.

Conclusion:This study proposed a 13-DNA repair gene-signature as a prognostic factor for LUAD patients, which can independently predict clinical outcomes by complement of the stage. Moreover, we characterized two LUAD subtypes with distinct clinical outcomes, somatic gene mutations, and drug sensitivity in cancer based on DNA repair genes.