High KRT8 Expression Independently Predicts Poor Prognosis for Lung Adenocarcinoma Patients

Glycoproteomics Analysis of Triple Wild-Type Lung Adenocarcinoma Tissue Samples

Lung cancer has both high incidence and mortality, making it the leading cause of cancer-related mortality worldwide. It is a highly heterogeneous disease, with several histological subtypes and genetic alterations that influence prognosis and available treatment options. Here, we focus on the triple wild-type (TWT) subtype of lung adenocarcinoma (LUAD) that lacks the three most common actionable genetic alterations, subsequently making targeted therapies inaccessible. In this study, our aim was the mass spectrometry-based proteomic and N-glycoproteomic characterization of tumor and adjacent normal lung tissue regions from individuals (n = 12) with TWT LUAD. We found several proteins previously identified as potential prognostic or diagnostic biomarkers in LUAD and described dysregulated biological processes, giving an overview of the general differences between healthy and tumor tissue. Also, we highlight specific signatures detected using N-glycoproteomics and discuss their potential and importance based on data from databases and literature. To the best of our knowledge, this is the first N-glycoproteomics-focused study on TWT LUAD, and it could provide a valuable resource for further studies into this less well characterized subtype of lung cancer. For instance, we report altered N-glycosylation for several glycoproteins implicated in LUAD and other cancers that could have functional importance connected to the disease.

Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis

Invasiveness is a key indicator of tumor malignancy and is often linked to poor prognosis in breast cancer (BC). To explore the diverse characteristics of invasive cells, single-cell RNA sequencing (scRNA-seq) data from three ductal carcinoma stages were analyzed, classifying samples into invasion and non-invasion groups. Nine genes (MCTS1, PGK1, PCMT1, C8orf76, TMEM242, QPRT, SLC16A2, AFG1L, and SPINK8) were identified as key discriminators between these groups. A breast cancer invasion score (BCIS) model was developed using LASSO Cox regression, revealed that high BCIS correlated with poorer overall survival in TCGA-BRCA patients and was validated across GSE20685 and METABRIC datasets (five-year and ten-year survival). Functional experiments demonstrated that knockdown of PGK1 or PCMT1 inhibited tumor cell proliferation and reduced the phosphorylation levels of mTORC, P70S6K, S6, and AKT, indicating suppression of the PI3K/AKT/mTOR pathways. High-BCIS tumors exhibited enrichment in protein secretion and PI3K/AKT/mTOR pathways, associated with aggressiveness and therapy resistance. This study introduced the BCIS score, distinguishing invasion from non-invasion cells, linked to PI3K/AKT/mTOR pathways, offering insights into BRCA prognosis and tumor aggressiveness.

Integration of Single-Cell and Bulk Transcriptomes to Identify a Poor Prognostic Tumor Subgroup to Predict the Prognosis of Patients with Early-stage Lung Adenocarcinoma

Background: Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal technology for investigating novel therapeutic targets in cancer. Despite its significance, there remains a scarcity of studies utilizing this technology to address treatment strategies specifically tailored for early-stage lung adenocarcinoma (LUAD). Consequently, this study aimed to investigate the tumor microenvironment (TME) characteristics and develop a prognostic model for early-stage LUAD. Methods: The markers identifying cell types were obtained from the CellMarker database and published research. The SCEVAN package was employed for identifying malignant lung epithelial cells. Single-cell downstream analyses were conducted using the SCP package, encompassing gene set enrichment analysis, enrichment analysis, pseudotime trajectory analysis, and differential expression analysis. Calibration curves, receiver operating characteristic curves, and decision curve analysis were employed to assess the performance of the prognostic model for LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blot, cell transfection, cell proliferation, and cell invasion assays were performed to validate the expression and biological function. Results: Seven cell types were distinguished in the scRNA-seq dataset through the utilization of cell markers documented in published literature. Four subpopulations of early-stage LUAD tumor cells exhibited a high degree of heterogeneity. The prognostic model constructed by PERP and KRT8 showed a great prediction for distinguishing the early-stage LUAD and normal tissues. The validation of PERP and KRT8 expression levels was carried out through both RT-qPCR and western blot analyses. Eventually, in vitro experiments, including CCK8, colony formation, EdU, and transwell assays, confirmed that KRT8 and PERP could promote LUAD cell proliferation and migration. Conclusions: Our study provided a comprehensive characterization of the TME in LUAD through integrative single-cell and bulk transcriptomic analyses. We identified dynamic transitions from normal epithelial cells to tumor cells, revealing the heterogeneity and evolution of malignant LUAD cells. The novel prognostic model based on KRT8 and PERP demonstrated robust predictive performance, offering a promising tool for early-stage LUAD risk stratification. Functional experiments further confirmed that KRT8 and PERP promote tumor proliferation and migration, providing new insights into their roles as therapeutic targets.

Advancing rhodium nanoparticle-based photodynamic cancer therapy: quantitative proteomics and in vivo assessment reveal mechanisms targeting tumor metabolism, progression and drug resistance

Rhodium nanoparticles have been recently discovered as good photosensitizers with great potential in cancer photodynamic therapy by effectively inducing cytotoxicity in cancer cells under near-infrared laser. This study evaluates the molecular mechanisms underlying such antitumoral effect through quantitative proteomics. The results revealed that rhodium nanoparticle-based photodynamic therapy disrupts tumor metabolism by downregulating key proteins involved in ATP synthesis and mitochondrial function, leading to compromised energy production. The treatment also induces oxidative stress and apoptosis while targeting the invasion capacity of cancer cells. Additionally, key proteins involved in drug resistance are also affected, demonstrating the efficacy of the treatment in a multi-drug resistant cell line. In vivo evaluation using a chicken embryo model also confirmed the effectiveness of the proposed therapy in reducing tumor growth without affecting embryo viability.

Comprehensive analysis of multiple regulated cell death risk signatures in lung adenocarcinoma

Background

Regulated cell death (RCD) has considerable impact on tumor progress and sensitivity of treatment. Lung adenocarcinoma (LUAD) show a high resistance for conventional radiotherapies and chemotherapies. Currently, regulation of cancer cell death has been emerging as a new promising therapeutic avenue for LUAD patients. However, the crosstalk in each pattern RCD is unclear.

Methods

We integrated collected the hub-genes of 12 RCD subroutines and compressively analyzed these hub-genes synergistic effect in LUAD. The characters of RCD genes expression and prognosis were developed in The Cancer Genome Atlas (TCGA)-LUAD data. We developed and validated an RCD risk model based on TCGA and GSE70294 data set, respectively. Functional annotation and tumor immunotherapy based on the risk model were also investigated.

Results

28 RCD-related genes and two LUAD molecular cluster were identified. Survival analysis revealed that the prognosis in high-risk group was worser than those in low-risk group. Functional enrichment analysis indicated that the RCD risk model correlated with immune responses. Further analysis indicated that the high-risk group in RCD risk model exhibited an immunosuppressive microenvironment and a lowly immunotherapy responder ratio.

Conclusions

We present an RCD risk model which have a promising ability in predicting LUAD prognosis and immunotherapy response.

Keratin 8/18a.1 Expression Influences Embryonic Neural Crest Cell Dynamics and Contributes to Postnatal Corneal Regeneration in Zebrafish

A complete understanding of neural crest cell mechanodynamics during ocular development will provide insight into postnatal neural crest cell contributions to ophthalmic abnormalities in adult tissues and inform regenerative strategies toward injury repair. Herein, single-cell RNA sequencing in zebrafish during early eye development revealed keratin intermediate filament genes krt8 and krt18a.1 as additional factors expressed during anterior segment development. In situ hybridization and immunofluorescence microscopy confirmed krt8 and krt18a.1 expression in the early neural plate border and migrating cranial neural crest cells. Morpholino oligonucleotide (MO)-mediated knockdown of K8 and K18a.1 markedly disrupted the migration of neural crest cell subpopulations and decreased neural crest cell marker gene expression in the craniofacial region and eye at 48 h postfertilization (hpf), resulting in severe phenotypic defects reminiscent of neurocristopathies. Interestingly, the expression of K18a.1, but not K8, is regulated by retinoic acid (RA) during early-stage development. Further, both keratin proteins were detected during postnatal corneal regeneration in adult zebrafish. Altogether, we demonstrated that both K8 and K18a.1 contribute to the early development and postnatal repair of neural crest cell-derived ocular tissues.

Identification and validation of an immune-derived multiple programmed cell death index for predicting clinical outcomes, molecular subtyping, and drug sensitivity in lung adenocarcinoma

OBJECTIVES

Comprehensive cross-interaction of multiple programmed cell death (PCD) patterns in the patients with lung adenocarcinoma (LUAD) have not yet been thoroughly investigated.

METHODS

Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed an immune-derived multiple programmed cell death index (MPCDI) based on machine learning methods.

RESULTS

Using the median MPCDI scores, we categorized the LUAD patients into two groups: low-MPCDI and high-MPCDI. Our analysis of the TCGA-LUAD training cohort and three external GEO cohorts (GSE37745, GSE30219, and GSE68465) revealed that patients with high-MPCDI experienced a more unfavorable prognosis, whereas those with low-MPCDI had a better prognosis. Furthermore, the results of both univariate and multivariate Cox regression analyses further confirmed that MPCDI serves as a novel independent risk factor. By combining clinical characteristics with the MPCDI, we constructed a nomogram that provides an accurate and reliable quantitative tool for personalized clinical management of LUAD patients. The findings obtained from the analysis of C-index and the decision curve revealed that the nomogram outperformed various clinical variables in terms of net clinical benefit. Encouragingly, the low-MPCDI patients are more sensitive to commonly used chemotherapy drugs, which suggests that MPCDI scores have a guiding role in chemotherapy for LUAD patients.

CONCLUSION

Therefore, MPCDI can be used as a novel clinical diagnostic classifier, providing valuable insights into the clinical management and clinical decision-making for LUAD patients.

Development of a genome atlas for discriminating benign, preinvasive, and invasive lung nodules

To tackle misdiagnosis in lung cancer screening with low-dose computed tomography (LDCT), we aimed to compile a genome atlas for differentiating benign, preinvasive, and invasive lung nodules and characterize their molecular pathogenesis. We collected 432 lung nodule tissue samples from Chinese patients, spanning benign, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA). We performed comprehensive sequencing, examining somatic variants, gene expressions, and methylation levels. Our findings uncovered EGFR and TP53 mutations as key drivers in - early lung cancer development, with EGFR mutation frequency increasing with disease progression. Both EGFR mutations and EGF/EGFR hypo-methylation activated the EGFR pathway, fueling cancer growth. Transcriptome analysis identified four lung nodule subtypes (G1-4) with distinct molecular features and immune cell infiltrations: EGFR-driven G1, EGFR/TP53 co-mutation G2, inflamed G3, stem-like G4. Estrogen/androgen response was associated with the EGFR pathway, proposing a new therapy combining tyrosine kinase inhibitors with antiestrogens. Preinvasive nodules exhibited stem cell pathway enrichment, potentially hindering invasion. Epigenetic regulation of various genes was essential for lung cancer initiation and development. This study provides insights into the molecular mechanism of neoplastic progression and identifies potential diagnostic biomarkers and therapeutic targets for lung cancer.

F-53B mediated ROS affects uterine development in rats during puberty by inducing apoptosis

Perfluoroalkyl and polyfluoroalkyl substances (PFASs), as pollutants, can cause palpable environmental and health impacts around the world, as endocrine disruptors, can disrupt endocrine homeostasis and increase the risk of diseases. Chlorinated polyfluoroalkyl ether sulfonate (F-53B), as a substitute for PFAS, was determined to have potential toxicity. Puberty is the stage when sexual organs develop and hormones change dramatically, and abnormal uterine development can increase the risk of uterine lesions and lead to infertility. This study was designed to explore the impact of F-53B on uterine development during puberty. Four-week-old female SD rats were exposed to 0.125 and 6.25 mg/L F-53B during puberty. The results showed that F-53B interfered with growth and sex hormone levels and bound to oestrogen-related receptors, which affected their function, contributed to the accumulation of reactive oxygen species, promoted cell apoptosis and inhibited cell proliferation, ultimately causing uterine dysplasia.

Hepatotoxicity assessment of innovative nutritional supplements based on olive-oil formulations enriched with natural antioxidants

Introduction

This study focuses on the assessment of extra virgin olive-oil and olive fruit-based formulations enriched with natural antioxidants as potential nutritional supplements for alleviating symptoms and long-term consequences of illnesses whose molecular pathophysiology is affected by oxidative stress and inflammation, such as Alzheimer's disease (AD).

Methods

Besides evaluating cell viability and proliferation capacity of human hepatocellular carcinoma HepG2 cells exposed to formulations in culture, hepatotoxicity was also considered as an additional safety measure using quantitative real-time PCR on RNA samples isolated from the cell cultures and applying approaches of targeted molecular analysis to uncover potential pathway effects through gene expression profiling. Furthermore, the formulations investigated in this work contrast the addition of natural extract with chemical forms and evaluate the antioxidant delivery mode on cell toxicity.

Results

The results indicate minimal cellular toxicity and a significant beneficial impact on metabolic molecular pathways in HepG2 cell cultures, thus paving the way for innovative therapeutic strategies using olive-oil and antioxidants in dietary supplements to minimize the long-term effects of oxidative stress and inflammatory signals in individuals being suffered by disorders like AD.

Discussion

Overall, the experimental design and the data obtained support the notion of applying innovative molecular methodologies and research techniques to evidently advance the delivery, as well as the scientific impact and validation of nutritional supplements and dietary products to improve public health and healthcare outcomes.

Identification and validation of a novel apoptosis-related prognostic risk score model for lung adenocarcinoma

The prognostic roles of apoptosis-related genes (ARGs) in lung adenocarcinoma (LUAD) have not been fully elucidated. In this study, differentially expressed genes (DEGs) associated with apoptosis and the hub genes were further identified. The prognostic values of the ARGs were evaluated using the LASSO Cox regression method. Prognostic values were determined using Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves in the TCGA and GEO datasets. The correlations, mutation data, and protein expression of the 10 ARGs predictive models were also analyzed. We identified 130 differentially expressed ARGs. DEGs were used to split LUAD cases into two subtypes whose overall survival (OS) were significantly different (P = 0.025). We developed a novel 10-gene signature using LASSO Cox regression. In both TCGA and GEO datasets, the results of the K-M curve and log-rank test showed significant difference in the survival rate of patients in the high-risk group and low-risk group (P < 0.0001). According to the GO and KEGG analyses, ARGs were enriched in cancer-related terms. In both cohorts, the immune status of the high-risk group was significantly lower than that of the low-risk group. Based on the differential expression of the ARGs, we established a new risk model to predict the prognosis of patients with LUAD.

Keratin gene signature expression drives epithelial-mesenchymal transition through enhanced TGF-β signaling pathway activation and correlates with adverse prognosis in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) stands as the foremost histological subtype of non-small-cell lung cancer, accounting for approximately 40% of all lung cancer diagnoses. However, there remains a critical unmet need to enhance the prediction of clinical outcomes and therapy responses in LUAD patients. Keratins (KRTs), serving as the structural components of the intermediate filament cytoskeleton in epithelial cells, play a crucial role in the advancement of tumor progression. This study investigated the prognostic significance of the KRT family gene and developed a KRT gene signature (KGS) for prognostic assessment and treatment guidance in LUAD.

Methods

Transcriptome profiles and associated clinical details of LUAD patients were meticulously gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The KGS score was developed based on the expression of five prognostic KRT genes (KRT7, KRT8, KRT17, KRT18, and KRT80), and the upper quartile of the KGS score was chosen as the cutoff. The Kaplan-Meier method was evaluated to compare survival outcomes between KGS-high and KGS-low groups. The underlying mechanism was further investigated by GSEA, GSVA, and other bioinformatic algorithms.

Results

High expression of the KGS signature exhibited a robust association with poorer overall survival (OS) in the TCGA-LUAD dataset (HR: 1.81; 95% CI: 1.35-2.42, P = 0.00011). The association was further corroborated in three external GEO cohorts, including GSE31210 (HR: 3.31; 95% CI: 1.7-6.47, P = 0.00017), GSE72094 (HR: 1.95; 95% CI: 1.34-2.85, P = 0.00057) and GSE26939 (HR: 3.19; 95% CI: 1.74-5.84, P < 0.0001). Interestingly, KGS-high tumors revealed enrichments in TGF-β and WNT-β catenin signaling pathways, exhibited heightened activation of the epithelial-mesenchymal transition (EMT) pathway and proved intensified tumor stemness compared to their KGS-low counterparts. Additionally, KGS-high tumor cells exhibited increased sensitivity to several targeted agents, including gefitinib, erlotinib, lapatinib, and trametinib, in comparison to KGS-low cells.

Conclusion

This study developed a KGS score that independently predicts the prognosis in LUAD. High expression of KGS score, accompanied by upregulation of TGF-β and WNT-β catenin signaling pathways, confers more aggressive EMT and tumor progression.

Multidimensional progressive single-cell sequencing reveals cell microenvironment composition and cancer heterogeneity in lung cancer

Despite substantial advances in cancer biology and treatment, the clinical outcomes of patients with lung cancer remain unsatisfactory. The tumor microenvironment (TME) is a potential target. Using single-cell RNA sequencing, we could distinguish eight distinct cell types in the lung cancer microenvironment, demonstrating substantial intratumoral heterogeneity in 19 different lung cancer tumor samples. Through the re-dimensional grouping of cancer-associated fibroblasts (CAFs), myeloid cells, epithelial cells, natural killer (NK) cells, and T cells, the difference in the TME of lung cancer was revealed. We discovered SFTPB, SFN, and KRT8 as possible predictive biomarkers for lung cancer by assessing the gene expression patterns in epithelial cells. Examining cell-to-cell communications showed a robust association between the quantity of matrix CAFs, epithelial cells, and macrophages in the thrombospondin signaling pathway. Additionally, we found that the amyloid precursor protein signaling pathway primarily originated from the matrix, and inflammatory cancer-associated endothelial and fibroblast cells showed a co-expression relationship with myeloid cells and B cells. Through cell-to-cell correlation analysis, we found positive regulation between NK cells, regulatory T cells, GZMB-CD8 T cells, and GZMK-CD8 T cells, which could play a role in developing immune TMEs. These findings support studies on cancer heterogeneity and add to our understanding of lung cancer's cellular microenvironment.

Vaccination with post-translational modified, homocitrullinated peptides induces CD8 T-cell responses that mediate antitumor immunity

BACKGROUND

Post-translational modification of proteins has the potential to alter the ability of T cells to recognize major histocompatibility complex (MHC) class -I and class-II restricted antigens, thereby resulting in altered immune responses. One such modification is carbamylation (homocitrullination) that results in the formation of homocitrulline (Hcit) residues in a non-enzymatic reaction of cyanate with the lysine residues in the polypeptide chain. Homocitrullination occurs in the tumor microenvironment and CD4-mediated immune responses to Hcit epitopes can target stressed tumor cells and provide a potent antitumor response in mouse models.

METHODS

Homocitrullinated peptides were identified and assessed in vitro for HLA-A2 binding and in vivo in human leukocyte antigen (HLA) transgenic mouse models for immunogenicity. CD8 responses were assessed in vitro for cytotoxicity and in vivo tumor therapy. Human tumor samples were analyzed by targeted mass spectrometry for presence of homocitrullinated peptides.

RESULTS

Homocitrullinated peptides from aldolase and cytokeratin were identified, that stimulated CD8-mediated responses in vivo. Modified peptides showed enhanced binding to HLA-A2 compared with the native sequences and immunization of HLA-A2 transgenic mice generated high avidity modification specific CD8 responses that killed peptide expressing target cells. Importantly, in vivo the homocitrullinated aldolase specific response was associated with efficient CD8 dependent antitumor therapy of the aggressive murine B16 tumor model indicating that this epitope is naturally presented in the tumor. In addition, the homocitrullinated aldolase epitope was also detected in human tumor samples.

CONCLUSION

This is the first evidence that homocitrullinated peptides can be processed and presented via MHC-I and targeted for tumor therapy. Thus, Hcit-specific CD8 T-cell responses have potential in the development of future anticancer therapy.

Identification of lysosomal genes associated with prognosis in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, representing 40% of all cases of this tumor. Despite immense improvements in understanding the molecular basis, diagnosis, and treatment of LUAD, its recurrence rate is still high.

Methods

RNA-seq data from The Cancer Genome Atlas (TCGA) LUAD cohort were download from Genomic Data Commons Portal. The GSE13213 dataset from Gene Expression Omnibus (GEO) was used for external validation. Differential prognostic lysosome-related genes (LRGs) were identified by overlapping survival-related genes obtained via univariate Cox regression analysis with differentially expressed genes (DEGs). The prognostic model was built using Kaplan-Meier curves and least absolute shrinkage and selection operator (LASSO) analyses. In addition, univariate and multivariate Cox analyses were employed to identify independent prognostic factors. The responses of patients to immune checkpoint inhibitors (ICIs) were further predicted. The pRRophetic package and rank-sum test were used to compute the half maximal inhibitory concentrations (IC50) of 56 chemotherapeutic drugs and their differential effects in the low- and high-risk groups. Moreover, quantitative real-time polymerase chain reaction, Western blot, and human protein atlas (HPA) database were used to verify the expression of the four prognostic biomarkers in LUAD.

Results

Of the nine candidate differential prognostic LRGs, GATA2, TFAP2A, LMBRD1, and KRT8 were selected as prognostic biomarkers. The prediction of the risk model was validated to be reliable. Cox independent prognostic analysis revealed that risk score and stage were independent prognostic factors in LUAD. Furthermore, the nomogram and calibration curves of the independent prognostic factors performed well. Differential analysis of ICIs revealed CD276, ICOS, PDCD1LG2, CD27, TNFRSF18, TNFSF9, ENTPD1, and NT5E to be expressed differently in the low- and high-risk groups. The IC50 values of 12 chemotherapeutic drugs, including epothilone.B, JNK.inhibitor.VIII, and AKT.inhibitor.VIII, significantly differed between the two risk groups. KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in LUAD cell lines. In addition, KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in tumor tissues.

Conclusions

Four key prognostic biomarkers-GATA2, TFAP2A, LMBRD1, and KRT8-were used to construct a significant prognostic model for LUAD patients.

Analysis of transcriptome expression profiling data in oral leukoplakia and early and late‑stage oral squamous cell carcinoma

The present study screened, potential prognostic biomarkers for oral carcinogenesis. The GSE85195 dataset, which consisted of oral leukoplakia (OL) and early and late-stage oral squamous cell carcinoma (OSCC) samples, was used. The differentially expressed genes (DEGs) in early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups were screened using the limma package in R. The Short Time-series Expression Miner software package was used to cluster DEGs with similar expression patterns in the course of disease progression (from OL to early and then late-stage OSCC). Moreover, the Database for Annotation, Visualization and Integrated Discovery online analysis tool was used to perform Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction (PPI) network was also constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Reverse transcription-quantitative PCR was performed to assess the mRNA expression levels of hub node genes in clinical samples, and receiver operating characteristic curve analysis was performed to assess the prognostic value of the hub genes. A total of 4,595, 6,042 and 2,738 DEGs were screened in the early OSCC vs. OL, late OSCC vs. OL and late OSCC vs. early OSCC groups, respectively. A total of 665 overlapping genes were identified when the screened DEGs were compared. Cluster 1 and cluster 7 were identified as the significant clusters, which contained 496 and 341 DEGs, respectively. A PPI network was constructed with 440 interaction pairs. There were five differentially expressed hub nodes identified in different stages from OL to OSCC. The results of the present study indicated that fibronectin 1, signal transducer and activator of transcription 1, collagen type II α1 chain, collagen type X α1 chain and collagen type IV α6 chain might serve as independent diagnostic factors for OL and OSCC, and as prognostic biomarkers for OL carcinogenesis.

Application of Cytochrome C-Related Genes in Prognosis and Treatment Prediction of Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of nonsmall cell lung cancer. Cytochrome c (Cyt c), which is produced from mitochondria, interacts with a protein called Apaf-1 to form the heptameric apoptosome. This heptameric apoptosome then activates the caspase cascade, which ultimately results in the execution of apoptosis. The purpose of our research was to discover a new prognostic model that is based on cytochrome c-related genes (CCRGs) for LUAD patients. Through LASSO regression analysis conducted on the LUAD datasets included in the TCGA datasets, a CCRGs signature was created. The diagnostic accuracy of the multigene signature was verified by an independent source using the GSE31210 and GSE72094 datasets. The GO and KEGG enrichment analysis were performed. In this study, there were 159 differentially expressed CCRGs in the TCGA dataset, while there were 68 differentially expressed CCRGs in the GSE31210 dataset. Additionally, there were 57 genes that overlapped across the two datasets. Using LASSO and Cox regression analysis, a signature consisting of 12 differentially expressed CCRGs was developed from the total of 57 such genes. On the basis of their risk ratings, patients were categorized into high-risk and low-risk categories, with low-risk patients having lower risk scores and a greater likelihood of surviving the disease. Univariate and multivariate analyses both concluded that this signature is an independent risk factor for LUAD. ROC curves demonstrated that this risk signature is capable of accurately predicting the 1-year, 2-year, 3-year, and 5-year survival rates of patients who have LUAD. The infiltration of antigen-presenting cells was higher in the low-risk group, such as aDCs, DCs, pDCs, and iDCs. The expression of multiple immune checkpoints was significantly higher in the low-risk group, such as BTLA, CD28, and CD86. Finally, we showed that the signature can be used to predict the drug sensitivity of already available or under investigational drugs. Overall, patient classification and individualized therapy options may benefit from this study’s development of a powerful gene signature with high value for prognostic prediction in LUAD.

Genomic Assessment of Cancer Susceptibility in the Threatened Catalina Island Fox (Urocyon littoralis catalinae)

Small effective population sizes raise the probability of extinction by increasing the frequency of potentially deleterious alleles and reducing fitness. However, the extent to which cancers play a role in the fitness reduction of genetically depauperate wildlife populations is unknown. Santa Catalina island foxes (Urocyon littoralis catalinae) sampled in 2007-2008 have a high prevalence of ceruminous gland tumors, which was not detected in the population prior to a recent bottleneck caused by a canine distemper epidemic. The disease appears to be associated with inflammation from chronic ear mite (Otodectes) infections and secondary elevated levels of Staphyloccus pseudointermedius bacterial infections. However, no other environmental factors to date have been found to be associated with elevated cancer risk in this population. Here, we used whole genome sequencing of the case and control individuals from two islands to identify candidate loci associated with cancer based on genetic divergence, nucleotide diversity, allele frequency spectrum, and runs of homozygosity. We identified several candidate loci based on genomic signatures and putative gene functions, suggesting that cancer susceptibility in this population may be polygenic. Due to the efforts of a recovery program and weak fitness effects of late-onset disease, the population size has increased, which may allow selection to be more effective in removing these presumably slightly deleterious alleles. Long-term monitoring of the disease alleles, as well as overall genetic diversity, will provide crucial information for the long-term persistence of this threatened population.

Cell Trajectory-Related Genes of Lung Adenocarcinoma Predict Tumor Immune Microenvironment and Prognosis of Patients

Background

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer which typically exhibits a diverse progression trajectory. Our study sought to explore the cell differentiation trajectory of LUAD and its clinical relevance.

Methods

Utilizing a single-cell RNA-sequencing dataset (GSE117570), we identified LUAD cells of distinct differential status along with differentiation-related genes (DRGs). DRGs were applied to the analysis of bulk-tissue RNA-sequencing dataset (GSE72094) to classify tumors into different subtypes, whose clinical relevance was further analyzed. DRGs were also applied to gene co-expression network analysis (WGCNA) using another bulk-tissue RNA-sequencing dataset (TCGA-LUAD). Genes from modules that demonstrated a significant correlation with clinical traits and were differentially expressed between normal tissue and tumors were identified. Among these, genes with significant prognostic relevance were used for the development of a prognostic nomogram, which was tested on TCGA-LUAD dataset and validated in GSE72094. Finally, CCK-8, EdU, cell apoptosis, cell colony formation, and Transwell assays were used to verify the functions of the identified genes.

Results

Four clusters of cells with distinct differentiation status were characterized, whose DRGs were predominantly correlated with pathways of immune regulation. Based on DRGs, tumors could be clustered into four subtypes associated with distinct immune microenvironment and clinical outcomes. DRGs were categorized into four modules. A total of nine DRGs (SFTPB, WFDC2, HLA-DPA1, TIMP1, MS4A7, HLA-DQA1, VCAN, KRT8, and FABP5) with most significant survival-predicting power were integrated to develop a prognostic model, which outperformed the traditional parameters in predicting clinical outcomes. Finally, we verified that knockdown of WFDC2 inhibited proliferation, migration, and invasion but promoted the apoptosis of A549 cells in vitro.

Conclusion

The cellular composition and cellular differentiation status of tumor mass can predict the clinical outcomes of LUAD patients. It also plays an important role in shaping the tumor immune microenvironment.

A Ubiquitin-Proteasome Gene Signature for Predicting Prognosis in Patients With Lung Adenocarcinoma

Background: Dysregulation of the ubiquitin-proteasome system (UPS) can lead to instability in the cell cycle and may act as a crucial factor in both tumorigenesis and tumor progression. However, there is no established prognostic signature based on UPS genes (UPSGs) for lung adenocarcinoma (LUAD) despite their value in other cancers.

Methods: We retrospectively evaluated a total of 703 LUAD patients through multivariate Cox and Lasso regression analyses from two datasets, the Cancer Genome Atlas (n = 477) and GSE31210 (n = 226). An independent dataset (GSE50081) containing 128 LUAD samples were used for validation.

Results: An eight-UPSG signature, including ARIH2, FBXO9, KRT8, MYLIP, PSMD2, RNF180, TRIM28, and UBE2V2, was established. Kaplan-Meier survival analysis and time-receiver operating characteristic curves for the training and validation datasets revealed that this risk signature presented with good performance in predicting overall and relapsed-free survival. Based on the signature and its associated clinical features, a nomogram and corresponding web-based calculator for predicting survival were established. Calibration plot and decision curve analyses showed that this model was clinically useful for both the training and validation datasets. Finally, a web-based calculator (https://ostool.shinyapps.io/lungcancer) was built to facilitate convenient clinical application of the signature.

Conclusion: An UPSG based model was developed and validated in this study, which may be useful as a novel prognostic predictor for LUAD.

KRT8 Serves as a Novel Biomarker for LUAD and Promotes Metastasis and EMT via NF-κB Signaling

Keratin 8 (KRT8) is the major component of the intermediate filament cytoskeleton and aberrant expression in multiple tumors. However, the role of KRT8 in lung adenocarcinoma (LUAD) remains unclear. In the present study, KRT8 expression was found to be upregulated along with prognosis and metastasis in LUAD. Kaplan-Meier analysis presented that the 5-year OS and DSS rates were significantly better among patients with low KRT8 expression compared to those with high expression. Correlation analysis showed that KRT8 expression was significantly associated with gender (P = 0.027), advanced T stage (P = 0.001), advanced N stage (P = 0.048), and advanced pathologic stage (P = 0.025). Univariate Cox analysis demonstrated that KRT8 was a predictor of OS [hazard ratio (HR) = 1.526; 95% confidence interval (CI) 1.141-2.040; P = 0.004] and DSS (HR = 1.625; 95% CI 1.123-2.353; P = 0.010) in the TCGA database. Importantly, downregulation of KRT8 obviously suppressed cell proliferation, cell migration, invasion, and EMT as well as induced cell apoptosis. KRT8 knockdown significantly inhibited NF-κB signaling, suggesting a potential mechanism. Overall, our results indicated that KRT8 could regulate lung carcinogenesis and may serve as a potential target for antineoplastic therapies.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

OSgc: A Web Portal to Assess the Performance of Prognostic Biomarkers in Gastric Cancer

Evaluating the prognostic value of genes of interest in different populations of gastric cancer (GC) is difficult and time-consuming for basic and translational researchers even though many datasets are available in public dataset depositories. In the current study, we developed a robust web-based portal called OSgc (Online consensus Survival analysis of gastric cancer) that enables easy and swift verification of known and novel biomarker candidates in GC. OSgc is composed of gene expression profiling data and clinical follow-up information of 1,824 clinical GC cases, which are collected from 7 public independent datasets derived from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). By OSgc, users input the official gene symbol and will promptly retrieve the Kaplan-Meier survival plot with hazard ratio (HR) and log rank p value on the output webpage, by which users could assess the prognostic value of interesting genes for GC patients. Five survival end points containing overall survival, progression-free survival, progression-free interval, relapse-free survival, and disease-free survival could be measured in OSgc. OSgc can greatly help cancer biologists and clinicians to explore the effect of gene expression on patient survival. OSgc is freely available without restrictions at http://bioinfo.henu.edu.cn/GC/GCList.jsp.

Overexpression of abnormal spindle-like microcephaly-associated (ASPM) increases tumor aggressiveness and predicts poor outcome in patients with lung adenocarcinoma

Background

Cumulative evidence points to abnormal spindle-like microcephaly-associated (ASPM) protein being overexpressed in various cancers, and the aberrant expression of ASPM has been shown to promote cancer tumorigenicity and progression. However, its role and clinical significance in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the expression patterns of ASPM and its clinical significance in LUAD.

Methods

In total, 4 original worldwide LUAD microarray mRNA expression datasets (N=1,116) with clinical and follow-up annotations were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The expression of ASPM protein in LUAD patients was detected by immunohistochemistry. Survival analysis and Cox regression analysis were used to examine the prognostic value of ASPM expression. Gene set enrichment analysis (GSEA) was performed to investigate the relationship between ASPM and LUAD.

Results

Dataset analyses and immunohistochemistry revealed that ASPM expression was significantly higher in the LUAD tissues compared with normal lung tissues, especially in the advanced tumor stage. Additionally, overexpression of ASPM was significantly correlated with shorter overall survival (OS) and relapse-free survival (RFS) in LUAD. Univariate and multivariate Cox regression analyses revealed that the overexpression of ASPM was a potential independent predictor of poor OS and RFS. However, ASPM overexpression was not significantly associated with predicting OS in lung squamous cell carcinoma. GSEA analysis demonstrated that ASPM was significantly enriched in the cell cycle, DNA replication, homologous recombination, RNA degradation, mismatch repair, and p53 signaling pathways.

Conclusions

These findings demonstrate the important role of ASPM in the tumorigenesis and progression of LUAD.

Identification of Immune-Related lncRNA Prognostic Signature and Molecular Subtypes for Glioblastoma

Background

Glioblastoma multiforme (GBM) is extensively genetically and transcriptionally heterogeneous, which poses challenges for classification and management. Long noncoding RNAs (lncRNAs) play a critical role in the development and progression of GBM, especially in tumor-associated immune processes. Therefore, it is necessary to develop an immune-related lncRNAs (irlncRNAs) signature.

Methods

Univariate and multivariate Cox regression analyses were utilized to construct a prognostic model. GBM-specific CeRNA and PPI network was constructed to predict lncRNAs targets and evaluate the interactions of immune mRNAs translated proteins. GO and KEGG pathway analyses were used to show the biological functions and pathways of CeRNA network-related immunity genes. Consensus Cluster Plus analysis was used for GBM gene clustering. Then, we evaluated GBM subtype-specific prognostic values, clinical characteristics, genes and pathways, immune infiltration access single cell RNA-seq data, and chemotherapeutics efficacy. The hub genes were finally validated.

Results

A total of 17 prognostically related irlncRNAs were screened to build a prognostic model signature based on six key irlncRNAs. Based on GBM-specific CeRNAs and enrichment analysis, PLAU was predicted as a target of lncRNA-H19 and mainly enriched in the malignant related pathways. GBM subtype-A displayed the most favorable prognosis, high proportion of genes (IDH1, ATRX, and EGFR) mutation, chemoradiotherapy, and low risk and was characterized by low expression of four high-risk lncRNAs (H19, HOTAIRM1, AGAP2-AS1, and AC002456.1) and one mRNA KRT8. GSs with poor survival were mainly infiltrated by mesenchymal stem cells (MSCs) and astrocyte, and were more sensitive to gefitinib and roscovitine. Among GSs, three hub genes KRT8, NGFR, and TCEA3, were screened and validated to potentially play feasible oncogenic roles in GBM.

Conclusion

Construction of lncRNAs risk model and identification of GBM subtypes based on 17 irlncRNAs, which suggesting that irlncRNAs had the promising potential for clinical immunotherapy of GBM.

Integrated bioinformatics analysis reveals CDK1 and PLK1 as potential therapeutic targets of lung adenocarcinoma

ABSTRACT

This study is to identify potential biomarkers and therapeutic targets for lung adenocarcinoma (LUAD).GSE6044 and GSE118370 raw data from the Gene Expression Omnibus database were normalized with Robust Multichip Average. After merging these two datasets, the combat function of sva packages was used to eliminate batch effects. Then, limma packages were used to filtrate differentially expressed genes. We constructed protein-protein interaction relationships using STRING database and hub genes were identified based on connectivity degrees. The cBioportal database was used to explore the alterations of the hub genes. The promoter methylation of cyclin dependent kinase 1 (CDK1) and polo-like Kinase 1 (PLK1) and their association with tumor immune infiltration in patients with LUAD were investigated using DiseaseMeth version 2.0 and TIMER databases. The Cancer Genome Atlas-LUAD dataset was used to perform gene set enrichment analysis.We identified 10 hub genes, which were upregulated in LUAD, among which 8 were successfully verified in the Cancer Genome Atlas and Oncomine databases. Kaplan-Meier analysis indicated that the expressions of CDK1 and PLK1 in LUAD patients were associated with overall survival and disease-free survival. The methylation levels in the promoter regions of these 2 genes in LUAD patients were lower than those in normal lung tissues. Their expressions in LUAD were associated with tumor stages and relative abundance of tumor infiltrating immune cells, such as B cells, CD4+ T cells, and macrophages. Moreover, cell cycle, DNA replication, homologous recombination, mismatch repair, P53 signaling pathway, and small cell lung cancer signaling were significantly enriched in CDK1 and PLK1 high expression phenotype.CDK1 and PLK1 may be used as potential biomarkers and therapeutic targets for LUAD.

Development of a gene signature associated with iron metabolism in lung adenocarcinoma

There are few studies on the role of iron metabolism genes in predicting the prognosis of lung adenocarcinoma (LUAD). Therefore, our research aims to screen key genes and to establish a prognostic signature that can predict the overall survival rate of lung adenocarcinoma patients. RNA-Seq data and corresponding clinical materials of 594 adenocarcinoma patients from The Cancer Genome Atlas(TCGA) were downloaded. GSE42127 of Gene Expression Omnibus (GEO) database was further verified. The multi-gene prognostic signature was constructed by the Cox regression model of the Least Absolute Shrinkage and Selection Operator (LASSO). We constructed a prediction signature with 12 genes (HAVCR1, SPN, GAPDH, ANGPTL4, PRSS3, KRT8, LDHA, HMMR, SLC2A1, CYP24A1, LOXL2, TIMP1), and patients were split into high and low-risk groups. The survival graph results revealed that the survival prognosis between the high and low-risk groups was significantly different (TCGA: P < 0.001, GEO: P = 0.001). Univariate and multivariate Cox regression analysis confirmed that the risk value is a predictor of patient OS (P < 0.001). The area under the time-dependent ROC curve (AUC) indicated that our signature had a relatively high true positive rate when predicting the 1-year, 3-year, and 5-year OS of the TCGA cohort, which was 0.735, 0.711, and 0.601, respectively. In addition, immune-related pathways were highlighted in the functional enrichment analysis. In conclusion, we developed and verified a 12-gene prognostic signature, which may be help predict the prognosis of lung adenocarcinoma and offer a variety of targeted options for the precise treatment of lung cancer.

Homocitrullination of lysine residues mediated by myeloid-derived suppressor cells in the tumor environment is a target for cancer immunotherapy

Background

Homocitrullination is the post-translational modification of lysine that is recognized by T cells.

Methods

This study identified homocitrullinated peptides from aldolase, enolase, cytokeratin and binding immunoglobulin protein and used human leukocyte antigen (HLA) transgenic mice to assess immunogenicity by enzyme-linked immunosorbent spot assay. Vaccine efficacy was assessed in tumor therapy studies using HLA-matched B16 melanoma expressing constitutive or interferon γ (IFNγ)-inducible major histocompatibility complex class II (MHC-II) as represented by most human tumors. To determine the mechanism behind the therapy, immune cell infiltrates were analyzed using flow cytometry and therapy studies in the presence of myeloperoxidase (MPO) inhibitor and T-cell depletion performed. We assessed the T-cell repertoire to homocitrullinated peptides in patients with cancer and healthy donors using flow cytometry.

Results

Homocitrulline (Hcit) peptide vaccination stimulated strong CD4 T-cell responses and induced significant antitumor therapy in an established tumor model. The antitumor response was dependent on CD4 T cells and the effect was driven mainly via direct tumor recognition, as responses were only observed if the tumors were induced to express MHC-II. In vitro proliferation assays show that healthy donors and patients with cancer have an oligoclonal CD4 T-cell repertoire recognizing homocitrullinated peptides. Inhibition of cyanate generation, which mediates homocitrullination, by MPO inhibition reduced tumor therapy by the vaccine induced T cells (p=0.0018). Analysis of the tumor microenvironment (TME) suggested that myeloid-derived suppressor cells (MDSCs) were a potential source of MPO. The selected B16 melanoma model showed MDSC infiltration and was appropriate to see if the Hcit vaccine could overcome the immunosuppression associated with MDSCs. The vaccine was very effective (90% survival) as the induced CD4 T cells directly targeted the homocitrullinated tumor and likely reversed the immunosuppressive environment.

Conclusion

We propose that MPO, potentially produced by MDSCs, catalyzes the buildup of cyanate in the TME which diffuses into tumor cells causing homocitrullination of cytoplasmic proteins which are degraded and, in the presence of IFNγ, presented by MHC-II for direct CD4 T-cell recognition. Homocitrullinated proteins are a new target for cancer vaccines and may be particularly effective against tumors containing high levels of MPO expressing MDSCs.

MCT4 is induced by metastasis-enhancing pathogenic mitochondrial NADH dehydrogenase gene mutations and can be a therapeutic target

Pathogenic mitochondrial NADH dehydrogenase (ND) gene mutations enhance the invasion and metastasis of various cancer cells, and they are associated with metastasis in human non-small cell lung cancer (NSCLC). Moreover, monocarboxylate transporter 4 (MCT4) is overexpressed in solid cancers and plays a role in cancer cell proliferation and survival. Here, we report that MCT4 is exclusively expressed in mouse transmitochondrial cybrids with metastasis-enhancing pathogenic ND6 mutations. A high level of MCT4 is also detected in human NSCLC cell lines and tissues predicted to carry pathogenic ND mutations and is associated with poor prognosis in NSCLC patients. MCT4 expression in the cell lines is suppressed by N-acetyl-L-cysteine. Phosphatidylinositol-3 kinase (PI3K), AMP-activated protein kinase (AMPK) and mechanistic target of rapamycin (mTOR) are involved in the regulation of MCT4 expression in the transmitochondrial cybrid cells. An MCT1/4 inhibitor effectively kills NSCLC cells with predicted pathogenic ND mutations, but an MCT1/2 inhibitor does not have the same effect. Thus, MCT4 expression is augmented by pathogenic ND mutations and could be a biomarker and a therapeutic target in pathogenic ND mutation-harbouring metastatic tumours.

Integrative Data Analytic Framework to Enhance Cancer Precision Medicine

With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.

LncRNA HCG18 Promotes Clear Cell Renal Cell Carcinoma Progression by Targeting miR-152-3p to Upregulate RAB14

Background

Long noncoding RNAs (lncRNAs) have been regarded as crucial regulators in many cancers, including clear cell renal cell carcinoma (ccRCC). This research aimed to explore the biological role and molecular mechanism of lncRNA HCG18 in ccRCC.

Materials and Methods

The expression levels of HCG18, miR-152-3p and RAB14 were examined by RT-qPCR. Cell viability, migration and invasion were examined by CCK-8 and transwell assays. Luciferase reporter and RIP assays were adopted to verify the interaction between miR-152-3p and HCG18 or RAB14.

Results

It was found that HCG18 expression was highly expressed in ccRCC tissues and cells, and patients with high expression of HCG18 had a short overall survival time. Moreover, HCG18 depletion attenuated ccRCC cell viability, migration and invasion. In addition, miR-152-3p was confirmed as a downstream target of HCG18 and was inversely regulated by HCG18, and RAB14 was a target of miR-152-3p. Functional assays demonstrated that miR-152-3p silencing or RAB14 addition abolished the inhibitory effects of HCG18 knockdown on ccRCC progression.

Conclusion

The results of the present study indicated that HCG18 accelerated the development and progression of ccRCC by upregulating RAB14 via sponging miR-152-3p, suggesting a potential therapeutic target for patients with ccRCC.

The Role of Keratin-8 and Keratin-18 Polymorphisms and Protein Levels in the Occurrence and Progression of Vocal Leukoplakia

OBJECTIVE

This study aimed to evaluate the association between the single-nucleotide polymorphism (SNP) and tissue protein level of keratin-8/18 and the occurrence and progression of vocal leukoplakia.

METHODS

The case-control study enrolled 158 patients with vocal leukoplakia, 326 patients with laryngeal squamous cell carcinoma (LSCC), and 268 healthy controls, which were tested for genotype analysis with keratin-8 and keratin-18 gene polymorphisms using pyrosequencing. The tissue protein expression levels of keratin-8 and keratin-18 were evaluated using immunohistochemistry.

RESULTS

The keratin-8 SNP RS1907671 showed an obvious increased risk for vocal leukoplakia (OR 1.56, p = 0.002), while the other SNPs (RS2035875, RS2035878, RS4300473) were tested as protective factors for vocal leukoplakia and LSCC (OR <1, p < 0.05). In keratin-18 SNP test, both RS2070876 and RS2638526 polymorphisms demonstrated decreased risks for vocal leukoplakia and LSCC (OR <1, p < 0.05). The protein levels of keratin-8 and keratin-18 in vocal leukoplakia group were significantly higher than those of the LSCC group (p < 0.05).

CONCLUSIONS

Keratin-8 and keratin-18 polymorphisms and protein levels are associated with the occurrence and progression of vocal leukoplakia.

Identification of 5-Gene Signature Improves Lung Adenocarcinoma Prognostic Stratification Based on Differential Expression Invasion Genes of Molecular Subtypes

Background

The acquisition of invasive tumor cell behavior is considered to be the cornerstone of the metastasis cascade. Thus, genetic markers associated with invasiveness can be stratified according to patient prognosis. In this study, we aimed to identify an invasive genetic trait and study its biological relevance in lung adenocarcinoma.

Methods

250 TCGA patients with lung adenocarcinoma were used as the training set, and the remaining 250 TCGA patients, 500 ALL TCGA patients, 226 patients with GSE31210, 83 patients with GSE30219, and 127 patients with GSE50081 were used as the verification data sets. Subtype classification of all TCGA lung adenocarcinoma samples was based on invasion-associated genes using the R package ConsensusClusterPlus. Kaplan-Meier curves, LASSO (least absolute contraction and selection operator) method, and univariate and multivariate Cox analysis were used to develop a molecular model for predicting survival.

Results

As a consequence, two molecular subtypes for LUAD were first identified from all TCGA all data sets which were significant on survival time. C1 subtype with poor prognosis has higher clinical characteristics of malignancy, higher mutation frequency of KRAS and TP53, and a lower expression of immune regulatory molecules. 2463 differentially expressed invasion genes between C1 and C2 subtypes were obtained, including 580 upregulation genes and 1883 downregulation genes. Functional enrichment analysis found that upregulated genes were associated with the development of tumor pathways, while downregulated genes were more associated with immunity. Furthermore, 5-invasion gene signature was constructed based on 2463 genes, which was validated in four data sets. This signature divided patients into high-risk and low-risk groups, and the LUDA survival rate of the high-risk group is significantly lower than that of the low-risk group. Multivariate Cox analysis revealed that this gene signature was an independent prognostic factor for LUDA. Compared with other existing models, our model has a higher AUC.

Conclusion

In this study, two subtypes were identified. In addition, we developed a 5-gene signature prognostic risk model, which has a good AUC in the training set and independent validation set and is a model with independent clinical characteristics. Therefore, we recommend using this classifier as a molecular diagnostic test to assess the prognostic risk of patients with LUDA.

OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan–Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

CREB1 Suppresses Transcription of microRNA-186 to Promote Growth, Invasion and Epithelial-Mesenchymal Transition of Gastric Cancer Cells Through the KRT8/HIF-1α Axis

Background

The cAMP response element-binding protein 1 (CREB1) was initiated as a potential target for cancer treatment. This research was conducted to probe the effect of CREB1 in the progression of gastric cancer (GC) and the molecules involved.

Materials and Methods

CREB1 expression in GC tissues and cell lines (AGS and MKN-45) as well as that in normal tissues and in gastric mucosa cell line (GES-1) was detected. The correlation between CREB1 expression and prognosis of GC patients was determined. Artificial silencing of CREB1 was introduced to evaluate its effect on biological behaviors of GC cells. The target microRNA (miRNA) of CREB1 and the target mRNA of miR-186 were predicted and validated. Altered expression of miR-186, KRT8 and HIF-1α was introduced to confirm their functions in GC progression.

Results

CREB1 was abundantly expressed in GC tissues and cells and linked to dismal prognosis in patients. Silencing of CREB1 or upregulation of miR-186 suppressed the malignant behaviors such as growth, epithelial-mesenchymal transition (EMT) and invasion of GC cells, while artificial overexpression of KRT8 led to reversed trends. KRT8 was a target mRNA of miR-186, and CREB1 transcriptionally suppressed miR-186 expression to further up-regulate KRT8. KRT8 was also found to increase HIF-1α expression. Upregulation of HIF-1α was found to block the suppressing role of CREB1 silencing in GC cell malignancy.

Conclusion

This study evidenced that silencing of CREB1 inhibits growth, invasion, EMT and resistance to apoptosis of GC cells involving the upregulation of miR-186 and the following downregulation of KRT8 and HIF-1α.

OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer

Lung cancer is the principal cause of leading cancer-related incidence and mortality in the world. Various studies have excavated the potential prognostic biomarkers for cancer patients based on gene expression profiles. However, most of these reported biomarkers lack independent validation in multiple cohorts. Herein, we collected 35 datasets with long-term follow-up clinical information from TCGA (2 cohorts), GEO (32 cohorts), and Roepman study (1 cohort), and developed a web server named OSluca (Online consensus Survival for Lung Cancer) to assess the prognostic value of genes in lung cancer. The input of OSluca is an official gene symbol, and the output web page of OSluca displays the survival analysis summary with a forest plot and a survival table from Cox proportional regression in each cohort and combined cohorts. To test the performance of OSluca, 104 previously reported prognostic biomarkers in lung carcinoma were evaluated in OSluca. In conclusion, OSluca is a highly valuable and interactive prognostic web server for lung cancer. It can be accessed at http:// bioinfo.henu.edu.cn/LUCA/LUCAList.jsp.

OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles

Background

Cutaneous melanoma is one of the most aggressive and lethal skin cancers. It is greatly important to identify prognostic biomarkers to guide the clinical management. However, it is technically challenging for untrained researchers to process high dimensional profiling data and identify potential prognostic genes in profiling datasets.

Methods

In this study, we developed a webserver to analyze the prognostic values of genes in cutaneous melanoma using data from TCGA and GEO databases. The webserver is named Online consensus Survival webserver for Skin Cutaneous Melanoma (OSskcm) which includes 1085 clinical melanoma samples. The OSskcm is hosted in a windows tomcat server. Server-side scripts were developed in Java script. The database system is managed by a SQL Server, which integrates gene expression data and clinical data. The Kaplan–Meier (KM) survival curves, Hazard ratio (HR) and 95% confidence interval (95%CI) were calculated in a univariate Cox regression analysis.

Results

In OSskcm, by inputting official gene symbol and selecting proper options, users could obtain KM survival plot with log-rank P value and HR on the output web page. In addition, clinical characters including race, stage, gender, age and type of therapy could also be included in the prognosis analysis as confounding factors to constrain the analysis in a subgroup of melanoma patients.

Conclusion

The OSskcm is highly valuable for biologists and clinicians to perform the assessment and validation of new or interested prognostic biomarkers for melanoma. OSskcm can be accessed online at: http://bioinfo.henu.edu.cn/Melanoma/MelanomaList.jsp.

High TXLNA Expression Predicts Favourable Outcome for Pancreatic Adenocarcinoma Patients

TXLNA (taxilin alpha), a binding partner of the syntaxin family, was identified as a key factor in the coordination of intracellular vesicle trafficking and highly expressed in various tumor cells. However, the accurate relation between TXLNA and tumorigenesis and progression of pancreatic adenocarcinoma (PAAD) is still unclear. The present study was designed to examine the expression profile of TXLNA and explore its prognostic significance in PAAD patients and the possible molecular regulatory mechanism by analyzing a series of data from databases, including GEPIA, LOGpc, STRING, and GeneMANIA. The results indicate that TXLNA mRNA and protein were remarkably increased in PAAD tissues compared with normal pancreatic tissues. The high TXLNA expression was significantly correlated with superior overall survival (OS), disease-free interval (DFI), disease specific survival (DSS), and progression-free interval (PFI) for PAAD patients. In summary, high TXLNA expression could predict favourable OS, DFI, DSS, and PFI for PAAD patients, and it might be as potential prognostic biomarkers and targets for PAAD.

OSgbm: An Online Consensus Survival Analysis Web Server for Glioblastoma

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system. GBM causes poor clinical outcome and high mortality rate, mainly due to the lack of effective targeted therapy and prognostic biomarkers. Here, we developed a user-friendly Online Survival analysis web server for GlioBlastoMa, abbreviated OSgbm, to assess the prognostic value of candidate genes. Currently, OSgbm contains 684 samples with transcriptome profiles and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA). The survival analysis results can be graphically presented by Kaplan-Meier (KM) plot with Hazard ratio (HR) and log-rank p value. As demonstration, the prognostic value of 51 previously reported survival associated biomarkers, such as PROM1 (HR = 2.4120, p = 0.0071) and CXCR4 (HR = 1.5578, p < 0.001), were confirmed in OSgbm. In summary, OSgbm allows users to evaluate and develop prognostic biomarkers of GBM. The web server of OSgbm is available at http://bioinfo.henu.edu.cn/GBM/GBMList.jsp.

Dimethylarsinic acid (DMA) enhanced lung carcinogenesis via histone H3K9 modification in a transplacental mouse model

Pregnant CD-1 mice received 200 ppm dimethylarsinic acid (DMA) in the drinking water from gestation day 8-18, and tumor formation was assessed in offspring at the age of 84 weeks. DMA elevated the incidence of lung adenocarcinoma (10.0%) and total tumors (33.3%) in male offspring compared to male control offspring (1.9 and 15.1%, respectively). DMA also elevated the incidence of hepatocellular carcinoma (10.0%) in male offspring compared to male control offspring (0.0%). DMA and its metabolites were detected in the lungs of transplacental DMA-treated neonatal mice. Transplacental DMA exposure increased cell proliferation in the epithelium in the lungs of both neonatal and 6-week-old male mice. Microarray and real-time PCR analyses detected high expression of keratin 8 (Krt8) in the lungs of both neonatal and 6-week-old DMA-treated mice. Western blot analysis indicated that DMA elevated methylation of histone H3K9, but not H3K27, in the lungs of male mice. Importantly, chromatin immunoprecipitation sequencing (ChIP-seq) analysis using an H3K9me3 antibody found differences in heterochromatin formation between mice exposed to DMA and the controls. Notably, ChIP-seq analysis also found regions of lower heterochromatin formation in DMA-treated mice, and one of these regions contained the Krt8 gene, agreeing with the results obtained by microarray analysis. High expression of Krt8 was also detected in adenoma and adenocarcinoma of the lung in male offspring. Overall, these data indicate that transplacental DMA treatment enhanced lung and liver carcinogenesis in male mice. In the lung, DMA caused aberrant methylation of histone H3K9, increased Krt8 expression, and enhanced cell proliferation.

Integrated analysis of the roles and prognostic value of RNA binding proteins in lung adenocarcinoma

Lung cancer is the top cause of carcinoma-associated deaths worldwide. RNA binding proteins (RBPs) dysregulation has been reported in various malignant tumors, and that dysregulation is closely associated with tumorigenesis and tumor progression. However, little is known about the roles of RBPs in lung adenocarcinoma (LUAD). In this study, we downloaded the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) database and determined the differently expressed RBPs between normal and cancer tissues. We then performed an integrative analysis to explore the expression and prognostic significance of these RBPs. A total of 164 differently expressed RBPs were identified, including 40 down-regulated and 124 up-regulated RBPs. Pathway and Gene ontology (GO) analysis indicated that the differently expressed RBPs were mainly related to RNA processing, RNA metabolic process, RNA degradation, RNA transport, splicing, localization, regulation of translation, RNA binding, TGF-beta signaling pathway, mRNA surveillance pathway, and aminoacyl-tRNA biosynthesis. Survival analysis revealed that the high expression of BOP1 or GNL3 or WDR12 or DCAF13 or IGF2BP3 or IGF2BP1 were associated with poor overall survival (OS). Conversely, overexpression of KHDRBS2/SMAD predicted high OS in these patients. ROC curve analysis showed that the eight hub genes with a better diagnostic accuracy to distinguish lung adenocarcinoma. The results provided novel insights into the pathogenesis of LUAD and the development of treatment targets and prognostic molecular markers.

Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Prognostic biomarkers are of great significance to predict the outcome of patients with cancer, to guide the clinical treatments, to elucidate tumorigenesis mechanisms, and offer the opportunity of identifying therapeutic targets. To screen and develop prognostic biomarkers, high throughput profiling methods including gene microarray and next-generation sequencing have been widely applied and shown great success. However, due to the lack of independent validation, only very few prognostic biomarkers have been applied for clinical practice. In order to cross-validate the reliability of potential prognostic biomarkers, some groups have collected the omics datasets (i.e., epigenetics/transcriptome/proteome) with relative follow-up data (such as OS/DSS/PFS) of clinical samples from different cohorts, and developed the easy-to-use online bioinformatics tools and web servers to assist the biomarker screening and validation. These tools and web servers provide great convenience for the development of prognostic biomarkers, for the study of molecular mechanisms of tumorigenesis and progression, and even for the discovery of important therapeutic targets. Aim to help researchers to get a quick learning and understand the function of these tools, the current review delves into the introduction of the usage, characteristics and algorithms of tools, and web servers, such as LOGpc, KM plotter, GEPIA, TCPA, OncoLnc, PrognoScan, MethSurv, SurvExpress, UALCAN, etc., and further help researchers to select more suitable tools for their own research. In addition, all the tools introduced in this review can be reached at http://bioinfo.henu.edu.cn/WebServiceList.html.

OSdlbcl: An online consensus survival analysis web server based on gene expression profiles of diffuse large B-cell lymphoma

Diffuse large B‐cell lymphoma (DLBCL) is the most common subtype of non‐Hodgkin lymphoma (NHL) and is a clinical, pathological, and molecular heterogeneous disease with highly variable clinical outcomes. Currently, valid prognostic biomarkers in DLBCL are still lacking. To optimize targeted therapy and improve the prognosis of DLBCL, the performance of proposed biomarkers needs to be evaluated in multiple cohorts, and new biomarkers need to be investigated in large datasets. Here, we developed a consensus Online Survival analysis web server for Diffuse Large B‐Cell Lymphoma, abbreviated OSdlbcl, to assess the prognostic value of individual gene. To build OSdlbcl, we collected 1100 samples with gene expression profiles and clinical follow‐up information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In addition, DNA mutation data were also collected from the TCGA database. Overall survival (OS), progression‐free survival (PFS), disease‐specific survival (DSS), disease‐free interval (DFI), and progression‐free interval (PFI) are important endpoints to reflect the survival rate in OSdlbcl. Moreover, clinical features were integrated into OSdlbcl to allow data stratifications according to the user's special needs. By inputting an official gene symbol and selecting desired criteria, the survival analysis results can be graphically presented by the Kaplan‐Meier (KM) plot with hazard ratio (HR) and log‐rank p value. As a proof‐of‐concept demonstration, the prognostic value of 23 previously reported survival associated biomarkers, such as transcription factors FOXP1 and BCL2, was evaluated in OSdlbcl and found to be significantly associated with survival as reported (HR = 1.73, P < .01; HR = 1.47, P = .03, respectively). In conclusion, OSdlbcl is a new web server that integrates public gene expression, gene mutation data, and clinical follow‐up information to provide prognosis evaluations for biomarker development for DLBCL. The OSdlbcl web server is available at https://bioinfo.henu.edu.cn/DLBCL/DLBCLList.jsp.

Expression and prognostic analyses of ITGA11, ITGB4 and ITGB8 in human non-small cell lung cancer

Background

Integrins play a crucial role in the regulation process of cell proliferation, migration, differentiation, tumor invasion and metastasis. ITGA11, ITGB4 and ITGB8 are three encoding genes of integrins family. Accumulative evidences have proved that abnormal expression of ITGA11, ITGB4 and ITGB8 are a common phenomenon in different malignances. However, their expression patterns and prognostic roles for patients with non-small cell lung cancer (NSCLC) have not been completely illustrated.

Methods

We investigated the expression patterns and prognostic values of ITGA11, ITGB4 and ITGB8 in patients with NSCLC through using a series of databases and various datasets, including ONCOMINE, GEPIA, HPA, TCGA and GEO datasets.

Results

We found that the expression levels of ITGA11 and ITGB4 were significantly upregulated in both LUAD and LUSC, while ITGB8 was obviously upregulated in LUSC. Additionally, higher expression level of ITGB4 revealed a worse OS in LUAD.

Conclusion

Our findings suggested that ITGA11 and ITGB4 might have the potential ability to act as diagnostic biomarkers for both LUAD and LUSC, while ITGB8 might serve as diagnostic biomarker for LUSC. Furthermore, ITGB4 could serve as a potential prognostic biomarker for LUAD.

OScc: an online survival analysis web server to evaluate the prognostic value of biomarkers in cervical cancer

Aim: To establish a web server that can mutually validate prognostic biomarkers of cervical cancer. Methods: Four datasets including expression profiling and relative clinical follow-up data were collected from Gene Expression Omnibus and The Cancer Genome Atlas. The web server was developed by R software. Results: The web server was named OScc including 690 patients and can be accessed at http://bioinfo.henu.edu.cn/CESC/CESCList.jsp . The Kaplan–Meier survival curves with log-rank p-value and hazard ratio will be generated of interested gene in OScc. Compared with previous predictive tools, OScc had the advantages of registration-free, larger sample size and subgroup analysis. Conclusion: The OScc is highly valuable to perform the preliminary assessment and validation of new or interested prognostic biomarkers for cervical cancer.

OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan–Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.

Kinesin Family Member 18A (KIF18A) Contributes to the Proliferation, Migration, and Invasion of Lung Adenocarcinoma Cells In Vitro and In Vivo

OBJECTIVE

To determine the expression levels of KIF18A in lung adenocarcinoma and its relationship with the clinicopathologic features of patients undergoing radical colectomy and explore the potential role in the progression of lung adenocarcinoma.

METHODS

Immunohistochemical assays were performed to explore the expression levels of KIF18A in 82 samples of lung adenocarcinoma and corresponding normal tissues. According to the levels of KIF18A expression in lung adenocarcinoma tissue samples, patients were classified into the KIF18A high expression group and low expression group. Clinical data related to the perioperative clinical features (age, gender, smoking, tumor size, differentiation, clinical stage, and lymph node metastasis), the potential correlation between KIF18A expression levels, and clinical features were analyzed, and the effects of KIF18A on lung adenocarcinoma cell proliferation, migration, and invasion were measured by colony formation assay, MTT assay, wound healing assay, and transwell assays. The possible effects of KIF18A on tumor growth and metastasis were measured in mice through tumor growth and tumor metastasis assays in vivo.

RESULTS

KIF18A in lung adenocarcinoma tissues. Further, KIF18A was significantly associated to clinical characteristic features including the tumor size (P = 0.033) and clinical stage (P = 0.041) of patients with lung adenocarcinoma. Our data also investigated that KIF18A depletion dramatically impairs the proliferation, migration, and invasion capacity of lung adenocarcinoma cells in vitro and inhibits tumor growth and metastasis in mice.

CONCLUSIONS

Our study reveals the involvement of KIF18A in the progression and metastasis of lung adenocarcinoma and provides a novel therapeutic target for the treatment of lung adenocarcinoma.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan-Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp.

OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system. The discovery of prognostic biomarkers is still one of the major challenges to improve clinical treatment of BC patients. In order to assist biologists and clinicians in easily evaluating the prognostic potency of genes in BC patients, we developed a user-friendly Online consensus Survival tool for bladder cancer (OSblca), to analyze the prognostic value of genes. The OSblca includes gene expression profiles of 1,075 BC patients and their respective clinical follow-up information. The clinical follow-up data include overall survival (OS), disease specific survival (DSS), disease free interval (DFI), and progression free interval (PFI). To analyze the prognostic value of a gene, users only need to input the official gene symbol and then click the “Kaplan-Meier plot” button, and Kaplan-Meier curve with the hazard ratio, 95% confidence intervals and log-rank P-value are generated and graphically displayed on the website using default options. For advanced analysis, users could limit their analysis by confounding factors including data source, survival type, TNM stage, histological type, smoking history, gender, lymph invasion, and race, which are set up as optional parameters to meet the specific needs of different researchers. To test the performance of the web server, we have tested and validated its reliability using previously reported prognostic biomarkers, including KPNA2, TP53, and MYC etc., which had their prognostic values validated as reported in OSblca. In conclusion, OSblca is a useful tool to evaluate and discover novel prognostic biomarkers in BC. The web server can be accessed at http://bioinfo.henu.edu.cn/BLCA/BLCAList.jsp.