A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer

Background: Increasing evidence showed that the clinical significance of the interaction between hypoxia and immune status in tumor microenvironment. However, reliable biomarkers based on the hypoxia and immune status in triple-negative breast cancer (TNBC) have not been well established. This study aimed to explore a gene signature based on the hypoxia and immune status for predicting prognosis, risk stratification, and individual treatment in TNBC.

Methods: Hypoxia-related genes (HRGs) and Immune-related genes (IRGs) were identified using the weighted gene co-expression network analysis (WGCNA) method and the single-sample gene set enrichment analysis (ssGSEA Z-score) with the transcriptomic profiles from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Then, prognostic hypoxia and immune based genes were identified in TNBC patients from the METABRIC (N = 221), The Cancer Genome Atlas (TCGA) (N = 142), and GSE58812 (N = 107) using univariate cox regression model. A robust hypoxia-immune based gene signature for prognosis was constructed using the least absolute shrinkage and selection operator (LASSO) method. Based on the cross-cohort prognostic hypoxia–immune related gene signature, a comprehensive index of hypoxia and immune was developed and two risk groups with distinct hypoxia–immune status were identified. The prognosis value, hypoxia and immune status, and therapeutic response in different risk groups were analyzed. Furthermore, a nomogram was constructed to predict the prognosis for individual patients, and an independent cohort from the gene expression omnibus (GEO) database was used for external validation.

Results: Six cross-cohort prognostic hypoxia–immune related genes were identified to establish the comprehensive index of hypoxia and immune. Then, patients were clustered into high- and low-risk groups based on the hypoxia–immune status. Patients in the high-risk group showed poorer prognoses to their low-risk counterparts, and the nomogram we constructed yielded favorable performance to predict survival and risk stratification. Besides, the high-risk group had a higher expression of hypoxia-related genes and correlated with hypoxia status in tumor microenvironment. The high-risk group had lower fractions of activated immune cells, and exhibited lower expression of immune checkpoint markers. Furthermore, the ratio of complete response (CR) was greatly declined, and the ratio of breast cancer related events were significantly elevated in the high-risk group.

Conclusion: The hypoxia–immune based gene signature we constructed for predicting prognosis was developed and validated, which may contribute to the optimization of risk stratification for prognosis and personalized treatment in TNBC patients.

Expression and prognostic potential of PLEK2 in head and neck squamous cell carcinoma based on bioinformatics analysis

Background

PLEK2 (pleckstrin) could bind to membrane‐bound phosphatidylinositols and further promote cell spread. Recently, several studies have noted the importance of PLEK2 in tumor metastasis. However, the role of PLEK2 in head and neck squamous cell carcinoma (HNSCC) remains to be elucidated.

Methods

The PLEK2 expression in HNSCC was identified using Oncomine, Gene Expression Omnibus (GEO), UALCAN databases, and western blot analysis. Prognosis analysis was performed using Kaplan–Meier plotter, DriverDBv3, UALCAN, UCSC Xena, and GEO databases. Single‐cell functional analysis was further performed using the cancerSEA database. The PLEK2‐related co‑expressed genes were identified, and gene set enrichment analysis was performed using LinkedOmics. Furthermore, the top 10 hub genes were identified using the cytoHubba plug‐in of Cytoscape. Then, gene enrichment analysis, pathway activity, and drug sensitivity analyses of the hub genes were performed using the R package “clusterProfiler” and GSCAlite. Finally, the UCSC Xena browser was utilized to explore the hub gene most likely to play a synergic role with PLEK2 in HNSCC.

Results

Elevated expression of PLEK2 was observed in HNSCC and even in HNSCC subgroups based on diverse clinicopathological features, portending a poor prognosis in HNSCC. PLEK2 was correlated with metastasis and hypoxia in HNSCC, and the PLEK2‐related co‐expressed genes were mainly involved in the focal adhesion pathway. The top 10 hub genes were primarily enriched in focal adhesion, HPV infection, ECM‐receptor interaction, and PI3K‐AKT signaling pathway, and epithelial–mesenchymal transition pathway was activated. Furthermore, the expression levels of the hub genes were associated with sensitivity and resistance to various small molecules and anti‐cancer drugs. Further study suggested that ITGA3 and PLEK2 might be viewed as inextricably linked in facilitating HNSCC metastasis.

Conclusions

In general, PLEK2 might serve as a potential biomarker for the diagnosis of HNSCC and guide the development of targeted therapies for HNSCC.

Identification of Cancer Hub Gene Signatures Associated with Immune-Suppressive Tumor Microenvironment and Ovatodiolide as a Potential Cancer Immunotherapeutic Agent

Despite the significant advancement in therapeutic strategies, breast, colorectal, gastric, lung, liver, and prostate cancers remain the most prevalent cancers in terms of incidence and mortality worldwide. The major causes ascribed to these burdens are lack of early diagnosis, high metastatic tendency, and drug resistance. Therefore, exploring reliable early diagnostic and prognostic biomarkers universal to most cancer types is a clinical emergency. Consequently, in the present study, the differentially expressed genes (DEGs) from the publicly available microarray datasets of six cancer types (liver, lung colorectal, gastric, prostate, and breast cancers), termed hub cancers, were analyzed to identify the universal DEGs, termed hub genes. Gene set enrichment analysis (GSEA) and KEGG mapping of the hub genes suggested their crucial involvement in the tumorigenic properties, including distant metastases, treatment failure, and survival prognosis. Notably, our results suggested high frequencies of genetic and epigenetic alterations of the DEGs in association with tumor staging, immune evasion, poor prognosis, and therapy resistance. Translationally, we intended to identify a drug candidate with the potential for targeting the hub genes. Using a molecular docking platform, we estimated that ovatodiolide, a bioactive anti-cancer phytochemical, has high binding affinities to the binding pockets of the hub genes. Collectively, our results suggested that the hub genes were associated with establishing an immune-suppressive tumor microenvironment favorable for disease progression and promising biomarkers for the early diagnosis and prognosis in multiple cancer types and could serve as potential druggable targets for ovatodiolide.

Early B-cell factors involve in the tumorigenesis and predict the overall survival of gastric cancer

Gastric cancer (GC) is a heavy health burden around the world, which is the fifth most frequent tumor and leads to the third most common cancer-related deaths. It is urgent to identify prognostic markers as the guideline for personalized treatment and follow-up. We accessed the prognostic value of Early B-cell factors (EBFs) in GC. A total of 415 GC tissues and 34 normal tissues from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort, 616 external patients from GSE15459, GSE22377, GSE51105, GSE62245 were enrolled for analysis. Univariate and multivariate Cox regression analyses were employed to evaluate the sole and integrative prognostic value of EBFs, respectively. Genetic alterations, DNA methylation of EBFs were also evaluated, as well as the involved signaling pathways. We revealed that increased EBFs associated with the poor prognosis of GC patients, the prognostic model was established in TCGA-STAD cohort, and validated in Gene Expression Omnibus (GEO) cohorts, with effectiveness in both HER2 positive and negative patients. DNA methylation was involved in the impact on prognosis. Cell cycle, immune-associated, and MAPK pathways were influenced by EBFs. Anti-CTLA4 immunotherapy is more suitable for EBFs determining high-risk groups, but not anti-PD-1/PD-L1 therapy. 5-Fluorouracil, methotrexate, vorinostat are suitable to inhibit the function of EBFs. Our new findings provide novel insight into the prediction of prognosis and clinical treatment of GC patients based on EBFs.

Prognostic Prediction, Immune Microenvironment, and Drug Resistance Value of Collagen Type I Alpha 1 Chain: From Gastrointestinal Cancers to Pan-Cancer Analysis

Background: Gastrointestinal cancers patients might experience multiple primary tumors in the digestive tract. Therefore, identifying potential biomarkers can help us better understand the underlying mechanism. From the GEO database, four profiles of gastrointestinal cancers were gathered for the screening process, and six hub genes were found by bioinformatics analysis. Collagen type I alpha 1 chain (COL1A1), one of the hub genes, is a component of the extracellular matrix and is critical for tumor microenvironment. However, the expression level, signaling pathway, prognostic prediction, and immunological value of COL1A1 in different cancers remain unclear.

Methods: We comprehensively analyzed gene expression and genetic alteration patterns of COL1A1 among 33 types of malignancies from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression projects. Besides, we explored the correlation of COL1A1 with cancer prognosis, immune infiltrates, PD-L1, tumor mutational burden (TMB)/microsatellite instability status (MSI), and the pathway and drug sensitivity of co-expressed genes.

Results: The results showed that COL1A1 was highly expressed and associated with poor prognosis in the majority of cancers. The most common alteration type of COL1A1 was missense mutation, and COL1A1 was associated with poor prognosis in KIRP, LGG, MESO, SKCM, and STAD. For the immunologic significance, COL1A1 expression was closely related to high TMB in THYM, LAML, ACC, KICH, PRAD, and LGG, and high MSI in TGCT, MESO, PRAD, COAD, SARC, and CESC. In addition, COL1A1 was positively correlated with the abundance of CAFs, macrophages, and tumor-infiltrating lymphocytes. However, it was negatively correlated with CD8⁺ T cells mainly in CESC, HNSC-HPV+, and SKCM. Besides, as a component of the extracellular matrix, COL1A1 was involved in the activation of epithelial-mesenchymal transition (EMT), and high expression of HTRA1 was resistant to multiple drugs.

Conclusion:COL1A1 can serve as a prognostic and immunological biomarker in different cancers.

The role of YTH domain containing 2 in epigenetic modification and immune infiltration of pan-cancer

YTH domain containing 2 (YTHDC2) is the largest N6‐Methyladenosine (m⁶A) binding protein of the YTH protein family and the only member containing ATP‐dependent RNA helicase activity. For further analysing its biological role in epigenetic modification, we comprehensively explored YTHDC2 from gene expression, genetic alteration, protein‐protein interaction (PPI) network, immune infiltration, diagnostic value and prognostic value in pan‐cancer, using a series of databases and bioinformatic tools. We found that YTHDC2 with Missense mutation could cause a different prognosis in uterine corpus endometrial carcinoma (UCEC), and its different methylation level could lead to a totally various prognosis in adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), lung squamous cell carcinoma (LUSC) and UCEC. The main molecular mechanisms of YTHDC2 focused on catalytic activity, helicase activity, snRNA binding, spliceosome and mRNA surveillance. Additionally, YTHDC2 was notably correlated with tumour immune infiltration. Moreover, YTHDC2 had a high diagnostic value for seven cancer types and a prognostic value for brain lower grade glioma (LGG), rectum adenocarcinoma (READ) and skin cutaneous melanoma (SKCM). Collectively, YTHDC2 plays a significant role in epigenetic modification and immune infiltration and maybe a potential biomarker for diagnosis and prognosis in certain cancers.

Identification and Validation of PIK3CA as a Marker Associated with Prognosis and Immune Infiltration in Renal Clear Cell Carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is the most prevalent renal malignancy. The therapeutic strategies for advanced KIRC are very few, with only sunitinib being widely approved. Mutations in the PIK3CA gene can affect tumor cell proliferation, metastasis, and patients' survival.

Methods

Bioinformatics analysis was performed to explore the expression and clinical significance of PIK3CA in KIRC. Moreover, qRT-PCR was conducted to verify the result.

Results

Subgroup analyses of KIRC tissue based on gender, tumor grade, and cancer stage indicated downregulation of PIK3CA mRNA expression. The KIRC patients with high PIK3CA expression indicated a better overall survival, progression-free survival, and disease-free survival. A predictive nomogram was constructed and demonstrated that the calibration plots for the 3-year and 5-year OS rates were predicted relatively well compared with an ideal model in the TCGA KIRC cohort. The validation study revealed that downregulation of PIK3CA in KIRC tissues and low PIK3CA expression had a poor overall survival with an AUC of 0.775 in the ROC curve. Moreover, Cox regression analysis revealed that PIK3CA expression and clinical stage were independent factors affecting the prognosis of KIRC patients. PIK3CA expression was found to be significantly associated with the abundance of immune cells and immune biomarker sets. PIK3CA and associated genes were found to be mainly associated with immune response and the JAK-STAT signaling pathway.

Conclusion

We identified PIK3CA as a potential biomarker for prognosis correlated with immune infiltrates in KIRC. Further studies should focus on the functions of PIK3CA in KIRC carcinogenesis.

Comprehensive analysis of a new prognosis signature based on histone deacetylases in clear cell renal cell carcinoma

Histone deacetylases (HDAC) family is vital for tumorigenesis and tumor progression. However, the exact role of the HDAC family in clear cell renal cell carcinoma (ccRCC) remains unclear. Based on The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and The Human Protein Atlas (HPA) database, we investigated and validated the expression profile, clinical significance and prognostic value of HDAC family members in ccRCC. Moreover, we further explored the correlation between HDACs and tumor microenvironment, tumor stemness, drug activity and immune subtype. The HDAC8, HDAC10, and HDAC11 manifested potential clinical value for prognosis, and the correlation analyses reveals underlying molecular mechanisms, which deserve further investigation for ccRCC. This Integrated bioinformatics analysis, based on transcriptomics and proteomics, implied that HDAC8, HDAC10, and HDAC11 may serve as potential molecular biomarkers and therapeutic targets for ccRCC, but some underlying molecular mechanisms still need to be elucidated.

BC-N102 suppress breast cancer tumorigenesis by interfering with cell cycle regulatory proteins and hormonal signaling, and induction of time-course arrest of cell cycle at G1/G0 phase

Mechanisms of breast cancer progression and invasion, often involve alteration of hormonal signaling, and upregulation and/or activation of signal transduction pathways that input to cell cycle regulation. Herein, we describe a rationally designed first-in-class novel small molecule inhibitor for targeting oncogenic and hormonal signaling in ER-positive breast cancer. BC-N102 treatment exhibits dose-dependent cytotoxic effects against ER+ breast cancer cell lines. BC-N102 exhibited time course- and dose-dependent cell cycle arrest via downregulation of the estrogen receptor (ER), progesterone receptor (PR), androgen receptor (AR), phosphatidylinositol 3-kinase (PI3K), phosphorylated (p)-extracellular signal-regulated kinase (ERK), p-Akt, CDK2, and CDK4 while increasing p38 mitogen-activated protein kinase (MAPK), and mineralocorticoid receptor (MR) signaling in breast cancer cell line. In addition, we found that BC-N102 suppressed breast cancer tumorigenesis in vivo and prolonged the survival of animals. Our results suggest that the proper application of BC-N102 may be a beneficial chemotherapeutic strategy for ER+ breast cancer patients.

Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma

Background

More and more studies have proven that circular RNAs (circRNAs) play vital roles in cancer development via sponging miRNAs. However, the expression pattern of competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD) remains largely unclear. The current study explored functional roles and the regulatory mechanisms of circRNA as ceRNAs in LUAD and their potential impact on LUAD patient prognosis.

Methods

In this study, we systematically screened differential expression circRNAs (DEcircRNAs), miRNAs (DEmiRNAs) and mRNAs (DEGs) associated with LUAD. Then, DEcircRNAs, DEmiRNAs and DEGs were selected to construct a circRNA–miRNA–mRNA prognosis-related regulatory network based on interaction information from the ENCORI database. Subsequently, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the genes in the network to predict the potential underlying mechanisms and functions of circRNAs in LUAD. In addition, Kaplan–Meier survival analysis was performed to evaluate clinical outcomes of LUAD patients, and drug sensitivity analysis was used to screen potential biomarkers for drug treatment of patients with LUAD.

Results

As a result, 10 circRNAs were aberrantly expressed in LUAD tissues. The ceRNA network was built, which included 3 DEcircRNAs, 6 DEmiRNAs and 157 DEGs. The DEGs in the ceRNA network of hsa_circ_0049271 enriched in biological processes of cell proliferation and the Jak-STAT signaling pathway. We also detected 7 mRNAs in the ceRNA network of hsa_circ_0049271 that were significantly associated with the overall survival of LUAD patients (P < 0.05). Importantly, four genes (PDGFB, CCND2, CTF1, IL7R) identified were strongly associated with STAT3 activation and drugs sensitivity in GDSC.

Conclusions

In summary, a ceRNA network of hsa_circ_0049271 was successfully constructed, which including one circRNA, two miRNAs, and seven mRNAs. Seven mRNAs (PDGFB, TNFRSF19, CCND2, CTF1, IL11RA, IL7R and MAOA) were remarkably associated with the prognosis of LUAD patients. Among seven mRNA species, four genes (PDGFB, CCND2, CTF1, and IL7R) could be considered as drug targets in LUAD. Our research will provide new insights into the prognosis-related ceRNA network in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08462-8.

Organelle Crosstalk Regulators Are Regulated in Diseases, Tumors, and Regulatory T Cells: Novel Classification of Organelle Crosstalk Regulators

To examine whether the expressions of 260 organelle crosstalk regulators (OCRGs) in 16 functional groups are modulated in 23 diseases and 28 tumors, we performed extensive -omics data mining analyses and made a set of significant findings: (1) the ratios of upregulated vs. downregulated OCRGs are 1:2.8 in acute inflammations, 1:1 in metabolic diseases, 1:1.2 in autoimmune diseases, and 1:3.8 in organ failures; (2) sepsis and trauma-upregulated OCRG groups such as vesicle, mitochondrial (MT) fission, and mitophagy but not others, are termed as the cell crisis-handling OCRGs. Similarly, sepsis and trauma plus organ failures upregulated seven OCRG groups including vesicle, MT fission, mitophagy, sarcoplasmic reticulum–MT, MT fusion, autophagosome–lysosome fusion, and autophagosome/endosome–lysosome fusion, classified as the cell failure-handling OCRGs; (3) suppression of autophagosome–lysosome fusion in endothelial and epithelial cells is required for viral replications, which classify this decreased group as the viral replication-suppressed OCRGs; (4) pro-atherogenic damage-associated molecular patterns (DAMPs) such as oxidized low-density lipoprotein (oxLDL), lipopolysaccharide (LPS), oxidized-1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (oxPAPC), and interferons (IFNs) totally upregulated 33 OCRGs in endothelial cells (ECs) including vesicle, MT fission, mitophagy, MT fusion, endoplasmic reticulum (ER)–MT contact, ER– plasma membrane (PM) junction, autophagosome/endosome–lysosome fusion, sarcoplasmic reticulum–MT, autophagosome–endosome/lysosome fusion, and ER–Golgi complex (GC) interaction as the 10 EC-activation/inflammation-promoting OCRG groups; (5) the expression of OCRGs is upregulated more than downregulated in regulatory T cells (Tregs) from the lymph nodes, spleen, peripheral blood, intestine, and brown adipose tissue in comparison with that of CD4⁺CD25⁻ T effector controls; (6) toll-like receptors (TLRs), reactive oxygen species (ROS) regulator nuclear factor erythroid 2-related factor 2 (Nrf2), and inflammasome-activated regulator caspase-1 regulated the expressions of OCRGs in diseases, virus-infected cells, and pro-atherogenic DAMP-treated ECs; (7) OCRG expressions are significantly modulated in all the 28 cancer datasets, and the upregulated OCRGs are correlated with tumor immune infiltrates in some tumors; (8) tumor promoter factor IKK2 and tumor suppressor Tp53 significantly modulate the expressions of OCRGs. Our findings provide novel insights on the roles of upregulated OCRGs in the pathogenesis of inflammatory diseases and cancers, and novel pathways for the future therapeutic interventions for inflammations, sepsis, trauma, organ failures, autoimmune diseases, metabolic cardiovascular diseases (CVDs), and cancers.

Functional Roles of Bromodomain Proteins in Cancer

Histone acetylation is generally associated with an open chromatin configuration that facilitates many cellular processes including gene transcription, DNA repair, and DNA replication. Aberrant levels of histone lysine acetylation are associated with the development of cancer. Bromodomains represent a family of structurally well-characterized effector domains that recognize acetylated lysines in chromatin. As part of their fundamental reader activity, bromodomain-containing proteins play versatile roles in epigenetic regulation, and additional functional modules are often present in the same protein, or through the assembly of larger enzymatic complexes. Dysregulated gene expression, chromosomal translocations, and/or mutations in bromodomain-containing proteins have been correlated with poor patient outcomes in cancer. Thus, bromodomains have emerged as a highly tractable class of epigenetic targets due to their well-defined structural domains, and the increasing ease of designing or screening for molecules that modulate the reading process. Recent developments in pharmacological agents that target specific bromodomains has helped to understand the diverse mechanisms that bromodomains play with their interaction partners in a variety of chromatin processes, and provide the promise of applying bromodomain inhibitors into the clinical field of cancer treatment. In this review, we explore the expression and protein interactome profiles of bromodomain-containing proteins and discuss them in terms of functional groups. Furthermore, we highlight our current understanding of the roles of bromodomain-containing proteins in cancer, as well as emerging strategies to specifically target bromodomains, including combination therapies using bromodomain inhibitors alongside traditional therapeutic approaches designed to re-program tumorigenesis and metastasis.

Prognostic Values of E2F1/2 Transcriptional Expressions in Chromophobe Renal Cell Carcinoma Patients: Evidence from Bioinformatics Analysis

Background

Numerous studies on the E2F transcription factors have led to increasing insights that E2Fs could be an important driver of the formation and progression of many human cancers. Little is known about the function of distinct E2Fs in chromophobe renal cell carcinoma (chRCC).

Methods

We utilized the UALCAN, GEPIA, Cancer Genome Atlas (TCGA) database, cBioPortal, Metascape, STRING, Cytoscape, GeneMANIA, TIMER, TISIDB, GSCALite, and MEXPRESS databases to investigate the transcription level, genetic alteration, methylation, and biological function of E2Fs in chRCC patients, and its association with the occurrence, progress, prognosis, and immune cell infiltration in patients with chRCC.

Results

We found that E2F1/2/4/7/8 were more expressed in chRCC tissues than in normal tissues, while the expression of E2F5/6 was lower in the former than in the latter, and the expression levels of E2F1/2/4/5/6//7/8 were also associated with the histological parameters of chRCC, including T-stage and N-stage. Higher expression of E2F1/2/7/8 was found to be significantly correlated with worse overall survival (OS) in chRCC patients. Cox regression and time-dependent ROC analysis further suggested that E2F1/2 could be the potential independent biomarkers for chRCC prognosis. Besides, a moderate mutation rate of E2Fs (34%) was noticed in chRCC, and the genetic mutations in E2Fs were associated with poor survival of chRCC patients. We noticed that the expression of E2Fs was statistically correlated with the immune cell infiltration in chRCC. Moreover, we also found that the expression of E2F1 was significantly correlated with tumor-infiltrating lymphocytes and immunomodulators, E2F7 expression was associated with MHC molecules, and the expression of E2F1/8 was correlated to their methylation levels.

Conclusion

Our results provide novel insights for selecting the prognostic biomarkers for chRCC and suggest that E2F1/2 could act as potential prognostic biomarkers for the survival of chRCC patients. However, more in-depth experiments are required to identify the underlying mechanisms and verify the clinical value of E2F1/2 in the prognosis of chRCC.

Identification of a Prognostic Index Based on a Metabolic-Genomic Landscape Analysis of Hepatocellular Carcinoma (HCC)

Background

Metabolic disorders have attracted increasing attention from scientists who conduct research on various tumours, especially hepatocellular carcinoma (HCC). The purpose of this study was to assess the prognostic significance of metabolism in HCC.

Methods

The expression profiles of metabolism-related genes (MRGs) of 349 surviving HCC patients were extracted from The Cancer Genome Atlas (TCGA) database. Subsequently, a series of biomedical computational algorithms were used to identify a seven-MRG signature as a prognostic model. GSEA indicated the function and pathway enrichment of these MRGs. Then, drug sensitivity analysis was used to identify the hub gene, which was tested using IHC staining.

Results

A total of 420 differential MRGs and 116 differentially expressed transcription factors (TFs) were identified in HCC patients based on data from the TCGA database. The GO and KEGG enrichment analyses indicated that metabolic disturbance might be involved in the development of HCC. LASSO regression analysis was used to construct a seven-MRG signature (DHDH, ENO1, G6PD, LPCAT1, PDE6D, PIGU and PPAT) that could predict the prognosis of HCC patients. GSEA revealed the functional and pathway enrichment of these seven MRGs. Then, drug sensitivity analysis indicated that G6PD might play a key role in the prognosis of HCC by promoting chemoresistance. Finally, we used IHC staining to demonstrate the relationship between G6PD expression levels and clinical parameters in HCC patients.

Conclusion

The results of this study provide a potential method for predicting the prognosis of HCC patients and avenues for further studies of HCC metabolism. Moreover, the function of G6PD may play a key role in the development and progression of HCC.

Study on HOXBs of Clear Cell Renal Cell Carcinoma and Detection of New Molecular Target

Our study examined the transcriptional and survival data of HOXBs in patients with clear cell renal cell carcinoma (ccRCC) from the ONCOMINE database, Human Protein Atlas, and STRING website. We discovered that the expression levels of HOXB3/5/6/8/9 were significantly lower in ccRCC than in normal nephritic tissues. In ccRCC, patients with a high expression of HOXB2/5/6/7/8/9 mRNA have a higher overall survival (OS) than patients with low expression. Further analysis by the GSCALite website revealed that the methylation of HOXB3/5/6/8 in ccRCC was significantly negatively correlated to gene expression, while HOXB5/9 was positively correlated to the CCT036477 drug target. As DNA abnormal methylation is one of the mechanisms of tumorigenesis, we hypothesized that HOXB5/6/8/9 are potential therapeutic targets for patients with ccRCC. We analyzed the function of enrichment data of HOXBs in patients with ccRCC from the Kyoto Encyclopedia of Genes and Genomes pathway enrichment and the PANTHER pathway. The results of the analysis show that the function of HOXBs might be associated with the Wnt pathway and that HOXB5/6/8/9 was coexpressed with multiple Wnt pathway classical genes and proteins, such as MYC, CTNNB, Cyclin D1 (CCND1), and tumor protein P53 (TP53), which further confirms that HOXBs inhibit the growth of renal carcinoma cells through the Wnt signaling pathway. In conclusion, our analysis of the family of HOXBs and their molecular mechanism may provide a theoretical basis for further research.

m6A Regulator-Mediated Methylation Modification Model Predicts Prognosis, Tumor Microenvironment Characterizations and Response to Immunotherapies of Clear Cell Renal Cell Carcinoma

BACKGROUND

This study aims to establish an N6-methyladenosine (m6A) RNA methylation regulators-mediated methylation model and explore its role in predicting prognostic accuracy of immune contexture and characterizations of clear cell renal cell carcinoma (ccRCC).

METHODS

The m6A modification subclasses (m6AMS) were identified by unsupervised cluster analysis and three clusters were determined by consensus clustering algorithm in a discovering cohort. Testing and real-world validation cohorts were used to identify predictive responses for immune checkpoint therapies (ICTs) of m6AMS.

RESULTS

Prognostic implications landscape of m6A regulators in cancers and its differential expression levels in ccRCC patients were identified. Based on discovering cohort, ccRCC were automatically divided into three m6AMS, and cluster 3 showed significant worse survival than cluster 1/2. Importantly, it was found that the immune checkpoint molecules expression was significantly elevated in cluster 3. Besides, m6A scoreLow group (cluster 1&2) have significantly elevated TIDE score compared with m6A scoreHigh group (cluster 3). There was conspicuous tertiary lymphoid tissue, aggressive phenotype, elevated glycolysis, expression of PD-L1, abundance of CD8+ T cells, CD4+ FOXP3+ Treg cells and TCRn immune cells infiltration in the high m6A score group. Interestingly, there are significantly increased patients with clinical benefit in m6A scoreHigh group in 368 patients receiving ICTs from testing IMvigor210 (n = 292) and validation FUSCC (n = 55) cohorts.

CONCLUSION

Our discovery highlights the relationship between tumor epigenetic heterogeneity and immune contexture. Immune-rejection cluster 3 has pro-tumorigenic immune infiltration, and shows significant clinical benefits for ccRCC patients receiving ICTs, enabling patient selection for future clinical treatment.

Evidence of Omics, Immune Infiltration, and Pharmacogenomic for SENP1 in the Pan-Cancer Cohort

Sentrin specific-protease 1 (SENP1) is a protein involved in deSUMOylation that is almost overexpressed in cancer. SENP1 has a determinative role in the activation of transcription programs in the innate immune responses and the development B of and C lymphocytes. We found, SENP1 possibly plays a critical role in immune infiltration and acts as an expression marker in PAAD, ESCA, and THYM. CD4+ T cells, CD8+ T cells, and macrophages were more key-related immune cells, indicating that SENP1 might be introduced as a potential target for cancer immunotherapy. We further showed that dysregulation of SENP1 is powerfully associated with decreased patient survival and clinical stage. Total SENP1 protein also increases in cancer. SENP1 is also controlled by transcription factors (TFs) CREB1, KDM5A, REST, and YY1 that regulates apoptosis, cell cycle, cell proliferation, invasion, tumorigenesis, and metastasis. These TFs were in a positive correlation with SENP1. MiR-138-5p, miR-129-1-3p, and miR-129-2-3p also inhibit tumorigenesis through targeting of SENP1. The SENP1 expression level positively correlated with the expression levels of UBN1, SP3, SAP130, NUP98, NUP153 in 32 tumor types. SENP1 and correlated and binding genes: SAP130, NUP98, and NUP153 activated cell cycle. Consistent with this finding, drug analysis was indicated SENP1 is sensitive to cell cycle, apoptosis, and RTK signaling regulators. In the end, SENP1 and its expression-correlated and functional binding genes were enriched in cell cycle, apoptosis, cellular response to DNA damage stimulus. We found that the cell cycle is the main way for tumorigenesis by SENP1. SENP1 attenuates the effect of inhibitory drugs on the cell cycle. We also introduced effective FDA-Approved drugs that can inhibit SENP1. Therefore in the treatments in which these drugs are used, SENP1 inhibition is a suitable approach. This study supplies a wide analysis of the SENP1 across The Cancer Genome Atlas (CGA) cancer types. These results suggest the potential roles of SENP1 as a biomarker for cancer. Since these drugs and the drugs that cause to resistance are applied to cancer treatment, then these two class drugs can use to inhibition of SENP1.

Integrative Characterization of Immune-relevant Genes in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Tumor microenvironment plays an essential role in cancer development and progression. Cancer immunotherapy has become a promising approach for the treatment of hepatocellular carcinoma (HCC). We aimed to analyze the HCC immune microenvironment characteristics to identify immune-related genetic changes.

METHODS

Key immune-relevant genes (KIRGs) were obtained through integrating the differentially expressed genes of The Cancer Genome Atlas, immune genes from the Immunology Database and Analysis Portal, and immune differentially expressed genes determined by single-sample gene set enrichment analysis scores. Cox regression analysis was performed to mine therapeutic target genes. A regulatory network based on KIRGs, transcription factors, and immune-related long non-coding RNAs (IRLncRNAs) was also generated. The outcomes of risk score model were validated in a testing cohort and in clinical samples using tissue immunohistochemistry staining. Correlation analysis between risk score and immune checkpoint genes and immune cell infiltration were investigated.

RESULTS

In total, we identified 21 KIRGs, including programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte associated protein 4 (CTLA4), and found IKBKE, IL2RG, EDNRA, and IGHA1 may be equally important to PD-1 or CTLA4. Meanwhile, KIRGs, various transcription factors, and IRLncRNAs were integrated to reveal that the NRF1-AC127024.5-IKBKE axis might be involved in tumor immunity regulation. Furthermore, the immune-related risk score model was established according to KIRGs and key IRLncRNAs, and verified more obvious discriminating power in the testing cohort. Correlation analysis indicated TNFSF4 , LGALS9 , KIAA1429 , IDO2, and CD276 were closely related to the risk score, and CD4 T cells, macrophages, and neutrophils were the primary immune infiltration cell types.

CONCLUSIONS

Our results highlight the importance of immune genes in the HCC microenvironment and further unravel the underlying molecular mechanisms in the development of HCC.

Insights of fibroblast growth factor receptor 3 aberrations in pan-cancer and their roles in potential clinical treatment

Fibroblast growth factor receptor 3 (FGFR3) alters frequently across various cancer types and is a common therapeutic target in bladder urothelial carcinoma (BLCA) with FGFR3 variants. Although emerging evidence supports the role of FGFR3 in individual cancer types, no pan-cancer analysis is available. In this work, we used the open comprehensive datasets, covering a total of 10,953 patients with 10,967 samples across 32 TCGA cancer types, to identify the full alteration spectrum of FGFR3. FGFR3 abnormal expression, methylation patterns, alteration frequency, mutation location distribution, functional impact, and prognostic implications differed greatly from cancer to cancer. The overall alteration frequency of FGFR3 was relatively low in all cancers. Targetable mutations were mainly detected in BLCA, and S249C, Y373C, G370C, and R248C were hotspot mutations that could be targeted by an FDA approved erdafitinib. Genetic fusions were mainly observed in glioma, followed by BLCA. FGFR3-TACC3 was the most common fusion type which was proposed as novel therapeutic targets in glioma and was targetable with erdafitinib in BLCA. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were two lung cancer subtypes, FGFR3 fusion and hotspot mutation like S249C were observed more commonly in LUSC but not in LUAD. DNA methylation was correlated with the expression of FGFR3 and its downstream genes in some tumors. FGFG3 abnormal expression and alterations exhibited clinical correlations with patient prognosis in several tumors. This work exhibited the full alteration spectrum of FGFR3 and indicated several new clues for their application as potential therapeutic targets and prognostic indicators.

A Comprehensive Bioinformatics Analysis of Notch Pathways in Bladder Cancer

Simple Summary

The Notch pathway is important in embryology and numerous tumor diseases. However, its role in bladder cancer (BCa) has not been deeply investigated thus far. Gene expression data are available for BCa, and bioinformatics analysis can provide insights into a possible role of the Notch pathway in BCa development and prognosis. Using this information can help in better understanding the origin of BCa, finding novel biomarkers for prediction of disease progression, and potentially opening new avenues to improved treatment. Our analysis identified the Notch receptors NOTCH2/3 and their ligand DLL4 as potential drivers of BCa by direct interaction with basic cell functions and indirect by modulating the immune response.

Abstract

Background: A hallmark of Notch signaling is its variable role in tumor biology, ranging from tumor-suppressive to oncogenic effects. Until now, the mechanisms and functions of Notch pathways in bladder cancer (BCa) are still unclear. Methods: We used publicly available data from the GTEx and TCGA-BLCA databases to explore the role of the canonical Notch pathways in BCa on the basis of the RNA expression levels of Notch receptors, ligands, and downstream genes. For statistical analyses of cancer and non-cancerous samples, we used R software packages and public databases/webservers. Results: We found differential expression between control and BCa samples for all Notch receptors (NOTCH1, 2, 3, 4), the delta-like Notch ligands (DLL1, 3, 4), and the typical downstream gene hairy and enhancer of split 1 (HES1). NOTCH2/3 and DLL4 can significantly differentiate non-cancerous samples from cancers and were broadly altered in subgroups. High expression levels of NOTCH2/3 receptors correlated with worse overall survival (OS) and shorter disease-free survival (DFS). However, at long-term (>8 years) follow-up, NOTCH2 expression was associated with a better OS and DFS. Furthermore, the cases with the high levels of DLL4 were associated with worse OS but improved DFS. Pathway network analysis revealed that NOTCH2/3 in particular correlated with cell cycle, epithelial–mesenchymal transition (EMT), numbers of lymphocyte subtypes, and modulation of the immune system. Conclusions: NOTCH2/3 and DLL4 are potential drivers of Notch signaling in BCa, indicating that Notch and associated pathways play an essential role in the progression and prognosis of BCa through directly modulating immune cells or through interaction with cell cycle and EMT.

Prognostic Value of MEG3 and Its Correlation With Immune Infiltrates in Gliomas

Accumulating evidence has revealed that dysregulated lncRNA expression contributes to the onset and progression of cancer. However, the mechanistic role of lncRNA in glioma progression and tumor immunology remains largely unknown. This study aimed to evaluate the significance of maternally expressed gene 3 (MEG3) in the prognosis of and its immune-related roles in gliomas. The expression levels of MEG3 were analyzed using Oncomine and TIMER database. As an important imprinted gene, the copy number variation (CNV) of MEG3 in both glioblastoma multiforme (GBM) and low-grade glioma (LGG) were analyzed using GSCALite database, whereas its prognostic significance was assessed using PrognoScan and GEPIA databases. The relationship between MEG3 and tumor-infiltrated immune cells was analyzed using TIMER. Results showed that MEG3 expression was lower in most of the human cancer tissues than in the normal tissues. We also found that heterozygous deletion of MEG3 occurred more frequent than heterozygous amplification in gliomas, and mRNA expression of MEG3 was significantly positively correlated with its CNV in both the GBM and LGG group. Survival analysis showed that the CNV level of MEG3 had significant correlation with overall survival (OS) and progression-free survival (PFS) compared with wild type in LGG. Lower MEG3 expression was related with poor prognosis. Further analysis showed that in GBM, MEG3 expression level was significantly positively correlated with that of infiltrating CD8⁺ T cells and significantly negatively correlated with that of infiltrating dendritic cells. In LGG, MEG3 expression level was significantly negatively correlated with levels of infiltrating B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and dendritic cells. Univariate Cox survival analysis demonstrated that only the level of infiltrating dendritic cells significantly affected the survival time of patients with GBM, while all six types of immune cells had a significant effect on the survival time of patients with LGG. Furthermore, MEG3 expression showed strong correlations with multiple immune markers in gliomas, especially in LGG. The current findings suggest that MEG3 expression might serve as a possible prognostic marker and potential immunotherapeutic target for gliomas.

MicroRNAs expression analysis shows key affirmation of Synaptopodin-2 as a novel prognostic and therapeutic biomarker for colorectal and cervical cancers

MicroRNAs play a crucial role in tumorigenesis, tumor progression, and metastasis, and thus they contribute in development of different malignancies including cervical cancer (CC) and colorectal cancer (CRC). Through integrated strategies of computational biology, this study aims to identify prognostic biomarkers responsible for CRC and CC prognosis, and potential therapeutic agents to halt the progression of these cancers. Expression analysis of miRNA datasets of CRC and CC identified 17 differentially expressed miRNAs (DEMs). SYNPO2, NEGR1, FGF7, LIFR, RUNX1T1, CFL2, BNC2, EPHB2, PMAIP1, and CDC25A differentially expressed genes (DEGs) regulated by these DEMs were classified as candidate genes responsible for CRC and CC. Down-regulation of Synaptopodin-2 (SYNPO2) is involved in emergence and progression of these cancers by activating ER, PI3K/AKT, and EMT pathways as well as by suppressing DNA damage response, and cell cycle pathways. Higher methylation rate in promoter region of SYNPO2 could be a possible reason for lowering the expression of SYNPO2 in tumor stages. Hence, the lower expression of SYNPO2 is associated with poor prognosis of CRC and CC and could function as prognostic biomarker and therapeutic target. Fourteen transcription factors were recognized which can activate/inhibit the transcription of SYNPO2 and may be a potential target to regulate expression of SYNPO2 in CRC and CC. Retinoic acid and Estradiol were identified as putative therapeutic drugs for CRC and CC patients. This study will thus help in understanding the underlying molecular events in CRC and CC that may improve the detection of malignant lesions in primary screening and will broaden the clinical applications.

MIR29A Impedes Metastatic Behaviors in Hepatocellular Carcinoma via Targeting LOX, LOXL2, and VEGFA

Primary liver cancer accounts for the third most deadly type of malignant tumor globally, and approximately 80% of the cases are hepatocellular carcinoma (HCC), which highly relies on the activity of hypoxia responsive pathways to bolster its metastatic behaviors. MicroRNA-29a (MIR29A) has been shown to exert a hepatoprotective effect on hepatocellular damage and liver fibrosis induced by cholestasis and diet stress, while its clinical and biological role on the activity hypoxia responsive genes including LOX, LOXL2, and VEGFA remains unclear. TCGA datasets were retrieved to confirm the differential expression and prognostic significance of all genes in the HCC and normal tissue. The Gene Expression Omnibus (GEO) dataset was used to corroborate the differential expression and diagnostic value of MIR29A. The bioinformatic identification were conducted to examine the interaction of MIR29A with LOX, LOXL2, and VEGFA. The suppressive activity of MIR29A on LOX, LOXL2, and VEGF was verified by qPCR, immunoblotting, and luciferase. The effect of overexpression of MIR29A-3p mimics in vitro on apoptosis markers (caspase-9, -3, and poly (ADP-ribose) polymerase (PARP)); cell viability and wound healing performance were examined using immunoblot and a WST-1 assay and a wound healing assay, respectively. The HCC tissue presented low expression of MIR29A, yet high expression of LOX, LOXL2, and VEGFA as compared to normal control. Serum MIR29A of HCC patients showed decreased levels as compared to that of normal control, with an area under curve (AUC) of 0.751 of a receiver operating characteristic (ROC) curve. Low expression of MIR29A and high expression of LOX, LOXL2, and VEGFA indicated poor overall survival (OS). MIR29A-3p was shown to target the 3'UTR of LOX, LOXL2, and VEGFA. Overexpression of MIR29A-3p mimic in HepG2 cells led to downregulated gene and protein expression levels of LOX, LOXL2, and VEGFA, wherein luciferase reporter assay confirmed that MIR29A-3p exerts the inhibitory activity via directly binding to the 3'UTR of LOX and VEGFA. Furthermore, overexpression of MIR29A-3p mimic induced the activity of caspase-9 and -3 and PARP, while it inhibited the cell viability and wound healing performance. Collectively, this study provides novel insight into a clinical-applicable panel consisting of MIR29, LOX, LOXL2, and VEGFA and demonstrates an anti-HCC effect of MIR29A via comprehensively suppressing the expression of LOX, LOXL2, and VEGFA, paving the way to a prospective theragnostic approach for HCC.

ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

MOTIVATION

Gene expression and regulation, a key molecular mechanism driving human disease development, remains elusive, especially at early stages. Integrating the increasing amount of population-level genomic data and understanding gene regulatory mechanisms in disease development are still challenging. Machine learning has emerged to solve this, but many machine learning methods were typically limited to building an accurate prediction model as a 'black box', barely providing biological and clinical interpretability from the box.

RESULTS

To address these challenges, we developed an interpretable and scalable machine learning model, ECMarker, to predict gene expression biomarkers for disease phenotypes and simultaneously reveal underlying regulatory mechanisms. Particularly, ECMarker is built on the integration of semi- and discriminative-restricted Boltzmann machines, a neural network model for classification allowing lateral connections at the input gene layer. This interpretable model is scalable without needing any prior feature selection and enables directly modeling and prioritizing genes and revealing potential gene networks (from lateral connections) for the phenotypes. With application to the gene expression data of non-small-cell lung cancer patients, we found that ECMarker not only achieved a relatively high accuracy for predicting cancer stages but also identified the biomarker genes and gene networks implying the regulatory mechanisms in the lung cancer development. In addition, ECMarker demonstrates clinical interpretability as its prioritized biomarker genes can predict survival rates of early lung cancer patients (P-value < 0.005). Finally, we identified a number of drugs currently in clinical use for late stages or other cancers with effects on these early lung cancer biomarkers, suggesting potential novel candidates on early cancer medicine.

AVAILABILITYAND IMPLEMENTATION

ECMarker is open source as a general-purpose tool at https://github.com/daifengwanglab/ECMarker.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Establishment of a Prognostic Model for Hepatocellular Carcinoma Based on Endoplasmic Reticulum Stress-Related Gene Analysis

Hepatocellular carcinoma (HCC) is one of the most common types of cancer worldwide and its incidence continues to increase year by year. Endoplasmic reticulum stress (ERS) caused by protein misfolding within the secretory pathway in cells and has an extensive and deep impact on cancer cell progression and survival. Growing evidence suggests that the genes related to ERS are closely associated with the occurrence and progression of HCC. This study aimed to identify an ERS-related signature for the prospective evaluation of prognosis in HCC patients. RNA sequencing data and clinical data of patients from HCC patients were obtained from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC). Using data from TCGA as a training cohort (n=424) and data from ICGC as an independent external testing cohort (n=243), ERS-related genes were extracted to identify three common pathways IRE1, PEKR, and ATF6 using the GSEA database. Through univariate and multivariate Cox regression analysis, 5 gene signals in the training cohort were found to be related to ERS and closely correlated with the prognosis in patients of HCC. A novel 5-gene signature (including HDGF, EIF2S1, SRPRB, PPP2R5B and DDX11) was created and had power as a prognostic biomarker. The prognosis of patients with high-risk HCC was worse than that of patients with low-risk HCC. Multivariate Cox regression analysis confirmed that the signature was an independent prognostic biomarker for HCC. The results were further validated in an independent external testing cohort (ICGC). Also, GSEA indicated a series of significantly enriched oncological signatures and different metabolic processes that may enable a better understanding of the potential molecular mechanism mediating the progression of HCC. The 5-gene biomarker has a high potential for clinical applications in the risk stratification and overall survival prediction of HCC patients. In addition, the abnormal expression of these genes may be affected by copy number variation, methylation variation, and post-transcriptional regulation. Together, this study indicated that the genes may have potential as prognostic biomarkers in HCC and may provide new evidence supporting targeted therapies in HCC.

PLAU Promotes Cell Proliferation and Epithelial-Mesenchymal Transition in Head and Neck Squamous Cell Carcinoma

Plasminogen activator, urokinase (uPA) is a secreted serine protease whose Dysregulation is often accompanied by various cancers. However, the biological functions and potential mechanisms of PLAU in head and neck squamous cell carcinoma (HNSCC) remain undetermined. Here, the expression, prognosis, function, and coexpression genetic networks of PLAU in HNSCC were investigated by a series of public bioinformatics tools. A Higher PLAU level predicted a poorer clinical outcome. Meanwhile, functional network analysis implied that PLAU and associated genes mainly regulated cell-substrate adhesion, tissue migration, and extracellular matrix binding. The top 4 significantly associated genes are C10orf55, ITGA5, SERPINE1, and TNFRSF12A. Pathway enrichment analysis indicated that PLAU might activate the epithelial-to-mesenchymal transition (EMT) process, which could explain the poor prognosis in HNSCC. Besides, genes associated with PLAU were also enriched in EMT pathways. We further validated the bioinformatics analysis results by in vivo and in vitro experiments. Then, we found that much more PLAU was detected in HNSCC tissues, and the silencing of PLAU inhibit the proliferation, migration, and EMT process of CAL27 cell lines. Notably, the downregulation of PLAU decreased the expression of TNFRSF12A. Moreover, knockdown TNFRSF12A also inhibits cell proliferation and migration. In vivo experiment results indicated that PLAU inhibition could suppress tumor growth. Collectively, PLAU is necessary for tumor progression and can be a diagnostic and prognostic biomarker in HNSCC.

ADORA1 is a diagnostic-related biomarker and correlated with immune infiltrates in papillary thyroid carcinoma

Background: Adenosine A1 Receptor (ADORA1) is an adenosine receptor particularly relevant to the immunomodulatory process of malignant tumors. There are growing evidences that dysregulated overexpression of ADORA1 can promote many types of tumorigenesis. However, the expression and prognostic value and mechanism of ADORA1 in thyroid papillary carcinoma have not been reported. Methods: TCGA, ONCOMINE, UALCAN, cBioPortal, GeneMANIA, LinkedOmics, TIMER, GSCALite, TISIDB and EPIC tools were used in this study. Results: ADORA1 was overexpressed in papillary thyroid carcinoma compared to paracancerous tissue. And ADORA1 was positively correlated with lymph node metastasis as well as pathological stage in PTC. ADORA1 had diagnostic and prognostic value for PTC. The functions of ADORA1 co-expressed genes were mainly enriched in immune response, immune response-regulation signaling pathway, regulation of leukocyte activation and cancer-related pathways. Besides, ADORA1 expression was significantly correlated with tumor-infiltrating cells and immune biomarkers in PTC. Finally, the high expression of ADORA1 was sensitive to JW-55 drug. Conclusion: ADORA1 is a diagnostic and a prognostic biomarker for PTC. The expression of ADORA1 is positively correlated with many immunoregulatory factors in PTC.

Functions of CXC chemokines as biomarkers and potential therapeutic targets in the hepatocellular carcinoma microenvironment

Background

Several studies have indicated that CXC chemokines influence the prognosis and therapy in patients with hepatocellular carcinoma (HCC). However, there are limited studies on the roles of CXC chemokines in HCC based on data acquired from various databases. This study aimed to conduct an in-depth and comprehensive bioinformatic analysis of the expression and functions of CXC chemokines in HCC.

Methods

Data was obtained from various databases including ONCOMINE, UALCAN, STRING, GeneMinia, DAVID, Kaplan-Meier plotter, TIMER, GSCALite and NetworkAnalyst for the analysis of the expression and functions of the CXC chemokines in HCC.

Results

Analysis of the differential expression levels of CXC chemokines between HCC and adjacent normal tissues revealed that the mRNA expression levels of CXCL1/2/5/6/7/12/14 were significantly lower in HCC tissues than those in adjacent normal tissues, whereas the mRNA expression levels of CXCL9/16/17 were significantly higher in HCC tissues. Analysis of the relationship between CXC chemokines and overall survival revealed that high mRNA expression levels of CXCL1/3/5/6/8 were associated with poor overall survival, whereas high mRNA expression levels of CXCL2/4/7/9/10/12 were associated with better overall survival. The functions of CXC chemokines and related genes were associated with cytokine-cytokine receptor interactions and chemokine signaling pathway. Analysis of the association between CXC chemokines and activity of cancer pathways indicated that the DNA damage response and hormone androgen receptor (AR) signaling pathways were inhibited, whereas apoptosis, epithelial-mesenchymal transition (EMT) and Ras/mitogen-activated protein kinase (MAPK) signaling pathways were activated. The expression of CXC chemokines was positively correlated with the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells).

Conclusions

This study has demonstrated that CXC chemokines can influence survival of patients with HCC by recruiting different types of immune cells into the tumor microenvironment.

In silico development and clinical validation of novel 8 gene signature based on lipid metabolism related genes in colon adenocarcinoma

BACKGROUND

Changes in lipid metabolism pathways play a major role in colon carcinogenesis and development. Hence, we conducted a systematic analysis of lipid metabolism-related genes to explore new markers that predict the prognosis of colon adenocarcinoma (COAD).

METHODS

The non-negative Matrix Factorization (NMF) algorithm was applied to identify the molecular subtypes based on lipid metabolism-related genes. A weighted correlation network analysis (WCGNA) was used to identify co-expressed genes, and Lasso multivariate Cox analysis was performed to build a risk prognosis model. A timer database was used to analyze the immune infiltration of the gene signature and the GSCALite database was used for genome-wide analysis of the gene signature.

RESULTS

TCGA-COAD samples were divided into 3 subtypes based on lipid metabolism-related genes. 2739 genes were identified by WGCNA analysis. Finally, an 8-gene signature (RTN2, FYN, HEYL, FAM69A, FBXL5, HMGN2, LGALS4, STOX1) was constructed that demonstrated good robustness in different datasets, as well as an independent risk factor for colon cancer patients' prognosis. In addition, our model's predictive efficacy overall was higher than that of the other published models, and the 8 genes' expression analysis indicated that RTN2, HEYL, and STOX1 were all expressed highly significantly in COAD, while FAM69A, FBXL5, LGALS4, FYN and HMGN2 were expressed significantly poorly in cancer tissues, which was confirmed in immunohistochemistry. The 8 genes were expressed significantly differently in COAD immune subtypes and correlated with clinical variables. Genome-wide analysis revealed that the STOX1 mutation frequency was the highest, and genome methylation influenced HEYL, FAM69A, and STOX1 gene expression significantly; further, the expression of HEYL and FBXL5 was correlated positively with Copy number variation (CNV) and was regulated significantly by CNV in most cancers. FBXL5 was correlated significantly with austocystin d and bafilomycin and played an important role in anti-tumor and immunotherapy. The HEYL, FYN, FAM69A, and RTN2 genes' expression was associated with the EMT pathway's activation, while LGALS4 and STOX1 were associated significantly with the EMT pathway's inhibition.

CONCLUSION

This study constructed an 8-gene signature as a novel marker to predict colon cancer patients' survival.

Interferon regulatory factor transcript levels correlate with clinical outcomes in human glioma

Members of the interferon regulatory factor (IRF) gene family are crucial regulators of type I interferon signaling, which may play a role in the resistance of glioma to immune checkpoint blockade. However, the expression profiles, potential functions, and clinical significance of IRF family members remain largely unknown. Here, we examined IRF transcript levels and clinicopathological data from glioma patients using several bioinformatic databases, including ONCOMINE, GEPIA, TCGA, and cBioPortal. We found that IRF1, IRF2, IRF5, IRF8 and IRF9 were significantly upregulated in glioma compared to normal brain tissue. Higher IRF1, IRF2, IRF3, IRF4, IRF5, IRF7, IRF8 and IRF9 mRNA levels correlated with more advanced tumor grades and poorer outcomes. Moreover, although IRFs mutation rates were low (ranging from 0.5% to 2.3%) in glioma patients, genetic alterations in IRFs were associated with more favorable patient survival. Functional analysis showed that IRFs participated in glioma pathology mainly through multiple inflammation- and immunity-related pathways. Additionally, correlations were identified between IRFs and infiltration of immune cells within glioma tissues. Collectively, these results indicate that IRF family members, including IRF1, IRF2, IRF5, IRF8 and IRF9, may serve as prognostic biomarkers and indicators of immune status in glioma patients.

Employing hypoxia characterization to predict tumour immune microenvironment, treatment sensitivity and prognosis in hepatocellular carcinoma

The hypoxic microenvironment was recognized as a major driving force of the malignant phenotype in hepatocellular carcinoma (HCC), which contributes to tumour immune microenvironment (TIM) remodeling and tumor progression. Dysregulated hypoxia-related genes (HRGs) result in treatment resistance and poor prognosis by reshaping tumor cellular activities and metabolism. Approaches to identify the relationship between hypoxia and tumor progression provided new sight for improving tumor treatment and prognosis. But, few practical tools, forecasting relationship between hypoxia, TIM, treatment sensitivity and prognosis in HCC were reported. Here, we pooled mRNA transcriptome and clinical pathology data from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), and later developed a hypoxia risk model including four HRGs (DCN, DDIT4, PRKCA and NDRG1). The high-risk group displayed poor clinical characteristics, a malignant phenotype with carcinogenesis/proliferation pathways activation (MTORC1 and E2F) and immunosuppressive TIM (decreased immune cell infiltrations and upregulated immunosuppressive cytokines). Meanwhile, activated B cells, effector memory CD8 T cells and EZH2 deregulation were associated with patient’s survival, which might be the core changes of HCC hypoxia. Finally, we validated the ability of the hypoxia risk model to predict treatment sensitivity and found high hypoxia risk patients had poor responses to HCC treatment, including surgical resection, Sorafenib, Transarterial Chemoembolization (TACE) and immunotherapy. In conclusion, based on 4 HRGs, we developed and validated a hypoxia risk model to reflect pathological features, evaluate TIM landscape, predict treatment sensitivity and compounds specific to hypoxia signatures in HCC patients.

A Pancancer Analysis of the Expression Landscape and Clinical Relevance of Fibroblast Growth Factor Receptor 2 in Human Cancers

Background: Fibroblast growth factor receptor 2 (FGFR2) is frequently altered in tumors and one of the top therapeutic targets in cholangiocarcinoma (CHOL) with FGFR2 fusions. Although there have been several studies on individual tumors, a comprehensive analysis of FGFR2 genetic aberrations and their simultaneous clinical implications across different tumors have not been reported. Methods: In this study, we used the large comprehensive datasets available, covering over 10,000 tumor samples across more than 30 cancer types, to analyze FGFR2 abnormal expression, methylation, alteration (mutations/fusions and amplification/deletion), and their clinical associations. Results: Alteration frequency, mutation location distribution, oncogenic effects, and therapeutic implications varied among different cancers. The overall mutation rate of FGFR2 is low in pancancer. CHOL had the highest mutation frequency, and fusion accounted for the major proportion. All these fusion aberrations in CHOL were targetable, and an FDA-approved drug was approved recently. Uterine corpus endometrial carcinoma (UCEC) had the highest number of FGFR2 mutations, and the most frequently mutated positions were S252W and N549K, where the functional impact was oncogenic, but targeted therapy was less effective. Additionally, DNA methylation was associated with FGFR2 expression in several cancers. Moreover, FGFG2 expression and genetic aberrations showed clinical associations with patient survival in several cancers, indicating their potential for application as new tumor markers and therapeutic targets. Conclusions: This study showed the full FGFR2 alteration spectrum and provided a broad molecular perspective of FGFR2 in a comprehensive manner, suggesting some new directions for clinical targeted therapy of cancers.

Multi-omics analysis of the prognosis and therapeutic significance of circadian clock in ovarian cancer

Ovarian cancer (OV) is one of the most common female malignancies with high morbidity and mortality, but its mechanism is not fully understood. The circadian clock is involved in the regulation of the immune system and the tumor microenvironment, regulating biological processes and behaviors in multiple ways. Circadian rhythm disorders are considered a risk factor for tumorigenesis. Multi-omics analysis was performed to comprehensively illustrate the roles of circadian clock genes in OV, we found that most of circadian clock genes undergo epigenetic alterations in OV and are strongly correlated with overall and progression-free patient survival. These clock genes are mainly involved in the inhibition of Apoptosis pathway, Cell Cycle pathway and DNA Damage Response pathway, as well as the activation of RAS/MAPK pathway and RTK pathway. Drug sensitivity model indicate that the expression of core clock genes may associate with drug resistance. Further, immune infiltrates analysis shows that different mutant forms of core genes can not only suppress immune infiltration, but also affect clinical outcome of ovarian cancer patients. Overall, our results may provide novel insights for the potential selection of immunotherapeutic targets.

TYK2 is a prognostic biomarker and associated with immune infiltration in the lung adenocarcinoma microenvironment

BACKGROUND

Lung adenocarcinoma (LUAD) remains a major disease with high morbidity and mortality. The Janus kinases (JAKs) play a significant part in cellular biological process, inflammation and immunity. The role of JAK family in LUAD is still ambiguous.

METHODS

Various bioinformatics web portals were applied to explore the prognostic value of JAK family and their correlation with immune infiltration in LUAD.

RESULTS

JAK1/2 was downregulated, whereas JAK3/TYK2 was upregulated in patients with LUAD compared with the healthy controls in subgroup analyses based on gender, age, smoking habits, cancer stage, TP53 mutation status, and nodal metastasis status. Drug sensitivity indicated that low expression of JAK3 and TYK2 were resistant to most of the small molecules or drugs. High TYK2 expression was associated with favorable overall survival and relapse free survival in LUAD. Moreover, univariate and multivariate analysis revealed that clinical stage, lymphatic node metastasis and TYK2 expression were the independent factors affecting the prognosis of LUAD patients. TYK2 expression in LUAD patients was positively associated with the abundance of immune cells (B cells, CD8+ T cells, CD4+ T cells, neutrophils, and dendritic cells) and immune biomarker sets. Moreover, TYK2 was mainly involved in RNA binding, transcriptional mis-regulation in cancer and cell cycles. We also identified several TYK2-associated miRNA or transcription factor targets in LUAD.

CONCLUSION

Our results indicated that TYK2 was a biomarker and associated with prognosis and immune infiltration in LUAD, laying a foundation for further study about the role of TYK2 in the carcinogenesis and progression of LUAD.

Bioinformatics identification of CCL8/21 as potential prognostic biomarkers in breast cancer microenvironment

BACKGROUND

Breast cancer (BC) is the most common malignancy among females worldwide. The tumor microenvironment usually prevents effective lymphocyte activation and infiltration, and suppresses infiltrating effector cells, leading to a failure of the host to reject the tumor. CC chemokines play a significant role in inflammation and infection.

METHODS

In our study, we analyzed the expression and survival data of CC chemokines in patients with BC using several bioinformatics analyses tools.

RESULTS

The mRNA expression of CCL2/3/4/5/7/8/11/17/19/20/22 was remarkably increased while CCL14/21/23/28 was significantly down-regulated in BC tissues compared with normal tissues. Methylation could down-regulate expression of CCL2/5/15/17/19/20/22/23/24/25/26/27 in BC. Low expression of CCL3/4/23 was found to be associated with drug resistance in BC. Results from Kaplan-Meier plotter and BC Gene-Expression Miner v4.2 (bcGenExMiner) v4.2 demonstrated that BC patients with high CCL8 and low CCL19/21/22 expression were more likely to have a worse prognosis. CCL8 expression was significantly up-regulated in BC tissues compared with normal tissues. High CCL8 expression was significantly correlated with negative PR, negative ER, positive nodal status, triple-negative BC subtype, basal-like BC subtype, triple-negative and basal-like BC subtype and high grades. CCL21 was down-regulated in BC, while high levels of CCL21 was associated with negative PR, triple-negative subtype, basal-like subtype and low tumor grade. Functional analysis demonstrated that CCL8 and CCL21 were involved in carcinogenesis, tumor immune escape and chemoresistance in BC.

CONCLUSION

Integrative bioinformatics analysis demonstrated CCL8/21 as potential prognostic biomarkers in BC microenvironment.

Computational resources for identification of cancer biomarkers from omics data

Cancer is one of the most prevailing, deadly and challenging diseases worldwide. The advancement in technology led to the generation of different types of omics data at each genome level that may potentially improve the current status of cancer patients. These data have tremendous applications in managing cancer effectively with improved outcome in patients. This review summarizes the various computational resources and tools housing several types of omics data related to cancer. Major categorization of resources includes-cancer-associated multiomics data repositories, visualization/analysis tools for omics data, machine learning-based diagnostic, prognostic, and predictive biomarker tools, and data analysis algorithms employing the multiomics data. The review primarily focuses on providing comprehensive information on the open-source multiomics tools and data repositories, owing to their broader applicability, economic-benefit and usability. Sections including the comparative analysis, tools applicability and possible future directions have also been discussed in detail. We hope that this information will significantly benefit the researchers and clinicians, especially those with no sound background in bioinformatics and who lack sufficient data analysis skills to interpret something from the plethora of cancer-specific data generated nowadays.

Identification of DNA-Repair-Related Five-Gene Signature to Predict Prognosis in Patients with Esophageal Cancer

Esophageal cancer (ESCA) is a leading cause of cancer-related mortality, with poor prognosis worldwide. DNA damage repair is one of the hallmarks of cancer. Loss of genomic integrity owing to inactivation of DNA repair genes can increase the risk of cancer progression and lead to poor prognosis. We aimed to identify a novel gene signature related to DNA repair to predict the prognosis of ESCA patients. Based on gene expression profiles of ESCA patients from The Cancer Genome Atlas and gene set enrichment analysis, 102 genes related to DNA repair were identified as candidates. After stepwise Cox regression analysis, we established a five-gene prognostic model comprising DGCR8, POM121, TAF9, UPF3B, and BCAP31. Kaplan-Meier survival analysis confirmed a strong correlation between the prognostic model and survival. Moreover, we verified the clinical value of the prognostic signature under the influence of different clinical parameters. We found that small-molecule drugs (trametinib, selumetinib, and refametinib) could help to improve patient survival. In summary, our study provides a novel and promising prognostic signature based on DNA-repair-related genes to predict survival of patients with ESCA. Systematic data mining provides a theoretical basis for further exploring the molecular pathogenesis of ESCA and identifying therapeutic targets.

Identification and validation of a prognostic index based on a metabolic-genomic landscape analysis of ovarian cancer

PURPOSE

Tumour metabolism has become a novel factor targeted by personalised cancer drugs. This research evaluated the prognostic significance of metabolism-related genes (MRGs) in ovarian serous cystadenocarcinoma (OSC).

METHODS

MRGs in 379 women surviving OSC were obtained using The Cancer Genome Atlas (TCGA) database. Then, several biomedical computational algorithms were employed to identify eight hub prognostic MRGs that were significantly relevant to OSC survival. These eight genes have important clinical significance and prognostic value in OSC. Subsequently, a prognostic index was constructed. Drug sensitivity analysis was used to screen the key genes in eight MRGs. Immunohistochemistry (IHC) staining confirmed the expression levels of key genes and their correlations with clinical parameters and prognosis for patients.

RESULTS

A total of 701 differentially expressed MRGs were confirmed in women with OSC by the TCGA database. The random walking with restart (RWR) algorithm and the univariate Cox and lasso regression analyses indicated a prognostic signature based on eight MRGs (i.e., ENPP1, FH, CYP2E1, HPGDS, ADCY9, NDUFA5, ADH1B and PYGB), which performed moderately well in prognostic predictions. Drug sensitivity analysis indicated that PYGB played a key role in the progression of OSC. Also, IHC staining confirmed that PYGB has a close correlation with clinical parameters and poor prognosis in OSC.

CONCLUSION

The results of the present study may help to establish a foundation for future research attempting to predict the prognosis of OSC patients and to characterise OSC metabolism.

Single-cell analysis reveals metastatic cell heterogeneity in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.

Pan-cancer analysis identifies ITIH1 as a novel prognostic indicator for hepatocellular carcinoma

Although a previous pan-cancer study has reported the expression patterns of ITIHs in various tumors, their analyses have been restricted to limited cancer types. We thus comprehensively analyzed the expression profiles and clinical significances of ITIHs in a broader spectrum of cancers from TCGA. Our results showed that ITIHs were primarily down-regulated in tested cancers. The ITIH members were associated with either survival advantage or disadvantage, depending on the cancer type tested and the genes queried. Importantly, we for the first time demonstrated that ITIH1 had substantially decreased expression in liver hepatocellular carcinoma (LIHC) compared with corresponding normal tissue, and its down-regulation adversely impacted patient outcome. Moreover, ITIH1 expression was consistently declining during the progression of LIHC. Further analysis revealed that ITIH1 may be involved in cellular metabolic processes. Our findings established ITIH1 as a potential diagnostic and prognostic biomarker for LIHC, which awaits future experimental validation.

Molecular Characteristics, Prognostic Value, and Immune Characteristics of m6A Regulators Identified in Head and Neck Squamous Cell Carcinoma

N6-methyladenosine (m6A) plays crucial roles in a diverse range of physiological and pathological processes, and it is believed that it tremendously promotes neoplasia and progression. However, knowledge of the molecular characteristics of m6A modification, its prognostic value, and the infiltration of immune cell populations in head and neck squamous cell carcinoma (HNSCC) is still insufficient. Therefore, a pan-cancer genomic analysis was systematically performed here by examining m6A regulators at the molecular level within 33 multiple cancer types, and the correlations between the expression of m6A molecules were researched using datasets from The Cancer Genome Atlas (TCGA). Based on the above analysis, insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) is upregulated in HNSCC and may serve as an independent prognostic factor of overall survival, thus showing potential as a prognostic biomarker in HNSCC. Genetic alteration analyses elucidated the reasons for the abnormal upregulation of IGF2BP2 in HNSCC. As a result, IGF2BP2 was selected for further univariate and multivariate analyses. The functions of the related genes were annotated through gene set enrichment analysis, and the activation states of multiple biological pathways were shown by gene set variation analysis. We found that LRRC59 and STIP1 may act as IGF2BP2-associated genes to have a regulatory function in the m6A modification. In addition, we found that the status of immune cell infiltration was correlated with the level of IGF2BP2 gene expression. Our results provide supplementation at the molecular level for epigenetic regulation in HNSCC and insight into effective immunotherapy targets and strategies.

SLC1A4: A Powerful Prognostic Marker and Promising Therapeutic Target for HCC

SLC1A4, a Na-dependent neutral amino acid transporter, was considered to participate in the various pathobiological process, including tumorigenesis. However, the correlation between SLC1A4 and Hepatocellular Carcinoma (HCC) remains unclear. In our study, integrative bioinformatics and functional profiling were performed to reveal the prognosis and potential function of SLC1A4 in HCC. The results showed that the mRNA and protein levels of SLC1A4 were elevated in HCC, and it was a powerful independent prognostic marker for overall survival (OS). The co-expressed genes analysis and GSEA analysis showed that SLC1A4 was related to cell cycle, metabolism, cancer-related pathway. Furthermore, the functional analysis revealed that silenced SLC1A4 inhibited cell proliferation, migration, cell cycle, and promoted cell apoptosis in HCC. Next, immune analysis showed that SLC1A4 expression was positively associated with immune infiltration and immune-related chemokine expression in HCC. Silenced SLC1A4 evidently reduced these chemokines expression in HCC cells. Finally, drug sensitivity analysis revealed potential five sensitivity drugs for HCC patients with high-expressed SLC1A4. In conclusion, our results suggested that SLCIA4 could be a novel predictor prognosis and immunotherapeutic targets of HCC, and the sensitivity drugs may be effective therapeutic strategy for HCC patients with high-expressed SLC1A4.

Interferon regulatory factor 6 correlates with the progression of non-small cell lung cancer and can be regulated by miR-320

OBJECTIVES

The expression of interferon regulatory factor 6 (IRF6) has been reported in several cancer types, but its roles underlying the progression of lung cancer have not been detailedly investigated.

METHODS

The pairs of lung cancer tissues and para-carcinoma tissues and The Cancer Genome Atlas database were collected to detect IRF6 expression. Cell counting kit-8, transwell and terminal-deoxynucleoitidyl transferase-mediated nick end labelling assays were used to evaluate cell proliferation, migration and apoptosis.

KEY FINDINGS

A significant up-regulation of IRF6 in both lung adenocarcinoma and lung squamous cell carcinoma tissues compared with normal non-tumor tissues. Subsequently, Immunostaining also revealed that canceration of lung tissues predisposed to evoke IRF6 expression. In vitro experiments revealed the antitumour effects, including growth and migration inhibition, of IRF6 siRNA transfection. Considering miR-320 as an endogenous inhibitor to IRF6, miR-320 mimics transfection led to the inhibition of proliferation and migration of lung cancer cells. However, overexpressed IRF6 neutralized the antineoplastic activities of miR-320 in lung cancer cells.

CONCLUSIONS

The miR-320/IRF6 signalling axis was implicated in pulmonary canceration. miR-320 as an endogenous inhibitor of IRF6 provided a novel therapeutic strategy for the treatment of lung cancer.

Quantitative proteomics identifies FOLR1 to drive sorafenib resistance via activating autophagy in hepatocellular carcinoma cells

Sorafenib is commonly used to treat advanced human hepatocellular carcinoma (HCC). However, clinical efficacy has been limited by drug resistance. In this study, we used label-free quantitative proteomic analysis to systematically investigate the underlying mechanisms of sorafenib resistance in HCC cells. A total of 1709 proteins were confidently quantified. Among them, 89 were differentially expressed and highly enriched in the processes of cell-cell adhesion, negative regulation of apoptosis, response to drug and metabolic processes involving in sorafenib resistance. Notably, folate receptor α (FOLR1) was found to be significantly upregulated in resistant HCC cells. In addition, in vitro studies showed that overexpression of FOLR1 decreased the sensitivity of HCC cells to sorafenib, whereas siRNA-directed knockdown of FOLR1 increased the sensitivity of HCC cells to sorafenib. Immunoprecipitation-mass spectrometry analysis suggested a strong link between FOLR1 and autophagy-related proteins. Further biological experiments found that FOLR1-related sorafenib resistance was accompanied by the activation of autophagy, whereas inhibition of autophagy significantly reduced FOLR1-induced cell resistance. These results suggest the driving role of FOLR1 in HCC resistance to sorafenib, which may be exerted through FOLR1-induced autophagy. Therefore, this study may provide new insights into understanding the mechanism of sorafenib resistance.

A Deep Look into the Program of Rapid Tumor Growth of Hepatocellular Carcinoma

BACKGROUND AND AIMS

Great efforts have been made towards increasing our understanding of the pathogenesis involved in hepatocellular carcinoma (HCC), but the rapid growth inherent to such tumor development remains to be explored.

METHODS

We identified distinct gene coexpression modes upon liver tumor growth using weighted gene coexpression network analysis. Modeling of tumor growth as signaling activity was employed to understand the main cascades responsible for the growth. Hub genes in the modules were determined, examined in vitro, and further assembled into the growth signature.

RESULTS

We revealed modules related to the different growth states in HCC, especially the fastest growth module, which is preserved among different HCC cohorts. Moreover, signaling flux in the cell cycle pathway was found to act as a driving force for rapid growth. Twenty hub genes in the module were identified and assembled into the growth signature, and two genes (NCAPH, and RAD54L) were tested for their growth potential in vitro. Genetic alteration of the growth signature affected the global gene expression. The activity of the signature was associated with tumor metabolism and immunity in HCC. Finally, the prognosis effect of the growth signature was reproduced in nine cancers.

CONCLUSIONS

These results collectively demonstrate the molecule organization of rapid tumor growth in HCC, which is a highly synergistic process, with implications for the future management of patients.

Strongly preserved modules between cancer tissue and cell line contribute to drug resistance analysis across multiple cancer types

The existence and emergence of drug resistance in tumor cells is the main burden of cancer treatment. Most cancer drug resistance analyses are based entirely on cell line data and ignore the discordance between human tumors and cell lines, leading to biased preclinical model transformation. Based on cancer tissue data in TCGA and cancer cell line data in CCLE, this study identified and excluded non-preserved module (NP module) between cancer tissue and cell lines. We used strongly preserved module (SP module) for clinically relevant drug resistance analysis and identified 2068 "cancer-drug-module" pairs of 7 cancer types and 212 drugs based on data in GDSC. Furthermore, we identified potentially ineffective combination therapy (PICT) from multiple perspectives. Finally, we found 1608 sets of predictors that can predict drug response. These results provide insights and clues for the clinical selection of effective chemotherapy drugs to overcome cancer resistance in a new perspective.

Upregulation of hsa-miR-196a-5p is associated with MIR196A2 methylation and affects the malignant biological behaviors of glioma

Hsa-miR-196a-5p is involved in tumorigenesis and progression. However, the driving factors for hsa-miR-196a-5p overexpression and its correlation with the clinicopathological features and prognosis of patients remain unclear in glioma. Thus, this study aimed to investigate the prognostic value of hsa-miR-196a-5p and its correlation with MIR196A2 methylation in glioma. We observed that hsa-miR-196a-5p expression was upregulated in glioma. Next, 112 patients were divided into high (n = 56) and low (n = 56) hsa-miR-196a-5p expression groups. The chi-square test showed that hsa-miR-196a-5p expression was significantly related to age, WHO grade, histopathology, IDH mutation status, and 1p/19q codeletion. Univariate and multivariate Cox regression analyses showed that hsa-miR-196a-5p expression was an independent prognostic factor. GO and KEGG enrichment analyses showed that hsa-miR-196a-5p may be involved in the MAPK signaling, focal adhesion and cancer-related pathways. Compared with the normal astrocyte cell line, glioma cell lines had an unregulated MIR196A2 methylation level, which was confirmed by TCGA data. The hypermethylated CpG sites of MIR196A2 were mainly concentrated in the gene body region, which was significantly associated with hsa-miR-196a-5p overexpression. Kaplan-Meier curves revealed that MIR196A2 hypermethylation was a poor prognostic factor. These findings suggest that hsa-miR-196a-5p overexpression may be involved in malignant biological behaviors, and MIR196A2 hypermethylation of the gene body was significantly associated with hsa-miR-196a-5p overexpression, which was a poor prognostic factor of glioma. Therefore, MIR196A2 hypermethylation may act as an early marker of prognosis of patients with glioma.

Expression Profile Analysis Identifies a Novel Seven Immune-Related Gene Signature to Improve Prognosis Prediction of Glioblastoma

Glioblastoma multiform (GBM) is a malignant central nervous system cancer with dismal prognosis despite conventional therapies. Scientists have great interest in using immunotherapy for treating GBM because it has shown remarkable potential in many solid tumors, including melanoma, non-small cell lung cancer, and renal cell carcinoma. The gene expression patterns, clinical data of GBM individuals from the Cancer Genome Atlas database (TCGA), and immune-related genes (IRGs) from ImmPort were used to identify differentially expressed IRGs through the Wilcoxon rank-sum test. The association between each IRG and overall survival (OS) of patients was investigated by the univariate Cox regression analysis. LASSO Cox regression assessment was conducted to explore the prognostic potential of the IRGs of GBM and construct a risk score formula. A Kaplan–Meier curve was created to estimate the prognostic role of IRGs. The efficiency of the model was examined according to the area under the receiver operating characteristic (ROC) curve. The TCGA internal dataset and two GEO external datasets were used for model verification. We evaluated IRG expression in GBM and generated a risk model to estimate the prognosis of GBM individuals with seven optimal prognostic expressed IRGs. A landscape of 22 types of tumor-infiltrating immune cells (TIICs) in glioblastoma was identified, and we investigated the link between the seven IRGs and the immune checkpoints. Furthermore, there was a correlation between the IRGs and the infiltration level in GBM. Our data suggested that the seven IRGs identified in this study are not only significant prognostic predictors in GBM patients but can also be utilized to investigate the developmental mechanisms of GBM and in the design of personalized treatments for them.

Identification of MCM family as potential therapeutic and prognostic targets for hepatocellular carcinoma based on bioinformatics and experiments

AIMS

The minichromosome maintenance (MCM) complex is highly conserved, which has drawn increasing attention on physiology and pathology process. However, the role of MCM in hepatocellular carcinoma (HCC) remains largely unclear. We aimed to conduct systematic analysis of expression patterns, prognostic values and potential functions of nine MCM genes in HCC, thus identifying their role in HCC.

MAIN METHODS

In our study, we systemically analyzed the role of MCM in prognosis and HCC progression by several bioinformatics analysis tools. Immunohistochemical (IHC) assays were utilized to valid the protein expression of MCM in HCC and in vitro experiments were used to confirm the functions of MCMs in HCC proliferation.

KEY FINDINGS

Overexpression of MCM2-8 and MCM10 were found to be significantly associated with clinical parameters and poor prognosis of HCC patients. The function of MCM was mainly enriched in DNA replication. Moreover, MCM were also associated with several cancer pathway and drug sensitivity in HCC. Close correlations were observed between immune cell infiltration and MCM in HCC. Cell Counting Kit-8 (CCK-8) and clone formation assays suggested the role of MCM2-8 and MCM10 in HCC proliferation.

SIGNIFICANCE

These results have implied that deregulated MCM played an important role in HCC progression and might be considered as potential therapeutic and prognostic targets for HCC.

Identification of Hypoxia-Related Differentially Expressed Genes and Construction of the Clinical Prognostic Predictor in Hepatocellular Carcinoma by Bioinformatic Analysis

Background. Hypoxia closely relates to malignant progression and appears to be prognostic for outcome in hepatocellular carcinoma (HCC). Our research is aimed at mining the hypoxic-related genes (HRGs) and constructing a prognostic predictor (PP) model on clinical prognosis in HCC patients. Methods. RNA-sequencing data about HRGs and clinical data of patients with HCC were obtained from The Cancer Genome Atlas (TCGA) database portal. Differentially expressed HRGs between HCC and para-carcinoma tissue samples were obtained by applying the Wilcox analysis in R statistical software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for gene functional enrichment analyses. Then, the patients who were asked to follow up for at least one month were enrolled in the following study. Cox proportional risk regression model was applied to obtain key HRGs which related to overall survival (OS) in HCC. PP was constructed and defined, and the accuracy of PP was validated by constructing the signature in a training set and validation set. Connectivity map (CMap) was used to find potential drugs, and gene set cancer analysis (GSCA) was also performed to explore the underlying molecular mechanisms. Results. Thirty-seven differentially expressed HRGs were obtained. It contained 28 upregulated and 9 downregulated genes. After the univariate Cox regression model analysis, we obtained 27 prognosis-related HRGs. Of these, 25 genes were risk factors for cancer, and 2 genes were protective factors. The PP was composed by 12 key genes (HDLBP, SAP30, PFKP, DPYSL4, SLC2A1, HMOX1, PGK1, ERO1A, LDHA, ENO2, SLC6A6, and TPI1). GSCA results showed the overall activity of these 12 key genes in 10 cancer-related pathways. Besides, CMap identified deferoxamine, crotamiton, talampicillin, and lycorine might have effects with HCC. Conclusions. This study firstly reported 12 prognostic HRGs and constructed the model of the PP. This comprehensive research of multiple databases helps us gain insight into the biological properties of HCC and provides deferoxamine, crotamiton, talampicillin, and lycorine as potential drugs to fight against HCC.