Weighted gene co-expression network analysis in identification of metastasis-related genes of lung squamous cell carcinoma based on the Cancer Genome Atlas database

Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value

BACKGROUND

Ovarian cancer (OC) is a severe gynecological malignancy with significant diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be used to adjust diagnosis and improve patient care. However, serous OC lacks effective biomarkers. We aimed to identify novel biomarkers for OC and their pathogenic causes.

METHODS

The present study used the differentially expressed genes (DEGs) obtained from the "Limma" package and WGCNA modules for intersection analysis to obtain DEGs in OC. Three hub genes were identified-claudin 3 (CLDN3), interferon regulatory factor 6 (IRF6), and prostasin (PRSS8)-by searching for hub genes through the PPI network and verifying them in GSE14407, GSE18520, GSE66957, and TCGA + GTEx databases. The correlation between IRF6 and the prognosis of OC patients was further confirmed in Kaplan-Miller Plotter. RT-qPCR and IHC confirmed the RNA and protein levels of IRF6 in the OC samples. The effect of IRF6 on OC was explored using transwell invasion and scratch wound assays. Finally, we constructed a ceRNA network of hub genes and used bioinformatics tools to predict drug sensitivity.

RESULTS

The joint analysis results of TCGA, GTEx, and GEO databases indicated that IRF6 RNA and protein levels were significantly upregulated in serous OC and were associated with OS and PFS. Cell function experiments revealed that IRF6 knockdown inhibited SKOV3 cell proliferation, migration and invasion.

CONCLUSION

IRF6 is closely correlated with OC development and progression and could be considered a novel biomarker and therapeutic target for OC patients.

Knockdown of RFC4 inhibits the cell proliferation of nasopharyngeal carcinoma in vitro and in vivo

Nasopharyngeal carcinoma (NPC) is a malignant tumor that mainly occurs in East and Southeast Asia. Although patients benefit from the main NPC treatments (e.g., radiotherapy and concurrent chemotherapy), persistent and recurrent diseases still occur in some NPC patients. Therefore, investigating the pathogenesis of NPC is of great clinical significance. In the present study, replication factor c subunit 4 (RFC4) is a key potential target involved in NPC progression via bioinformatics analysis. Furthermore, the expression and mechanism of RFC4 in NPC were investigated in vitro and in vivo. Our results revealed that RFC4 was more elevated in NPC tumor tissues than in normal tissues. RFC4 knockdown induced G2/M cell cycle arrest and inhibited NPC cell proliferation in vitro and in vivo. Interestingly, HOXA10 was confirmed as a downstream target of RFC4, and the overexpression of HOXA10 attenuated the silencing of RFC4-induced cell proliferation, colony formation inhibition, and cell cycle arrest. For the first time, this study reveals that RFC4 is required for NPC cell proliferation and may play a pivotal role in NPC tumorigenesis.

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses

Introduction

Lung cancer is one of the most common cancers and a significant cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancer cases. Therefore, it is crucial to identify effective diagnostic and therapeutic methods. In addition, transcription factors are essential for eukaryotic cells to regulate their gene expression, and aberrant expression transcription factors are an important step in the process of oncogenesis in NSCLC.

Methods

Differentially expressed transcription factors between NSCLC and normal tissues by analyzing mRNA profiling from The Cancer Genome Atlas (TCGA) database program were identified. Weighted correlation network analysis (WGCNA) and line plot of least absolute shrinkage and selection operator (LASSO) were performed to find prognosis-related transcription factors. The cellular functions of transcription factors were performed by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay, cell invasion assay in lung cancer cells.

Results

We identified 725 differentially expressed transcription factors between NSCLC and normal tissues. Three highly related modules for survival were discovered, and transcription factors highly associated with survival were obtained by using WGCNA. Then line plot of LASSO was applied to screen transcription factors related to prognosis and build a prognostic model. Consequently, SETDB2, SNAI3, SCML4, and ZNF540 were identified as prognosis-related transcription factors and validated in multiple databases. The low expression of these hub genes in NSCLC was associated with poor prognosis. The deletions of both SETDB2 and SNAI3 were found to promote proliferation, invasion, and stemness in lung cancer cells. Furthermore, there were significant differences in the proportions of 22 immune cells between the high- and low-score groups.

Discussion

Therefore, our study identified the transcription factors involved in regulating NSCLC, and we constructed a panel for the prediction of prognosis and immune infiltration to inform the clinical application of transcription factor analysis in the prevention and treatment of NSCLC.

Chronic Inhalation Exposure to Antimony Trioxide Exacerbates the MAPK Signaling in Alveolar Bronchiolar Carcinomas in B6C3F1/N Mice

Antimony trioxide (AT) is used as a flame retardant in fabrics and plastics. Occupational exposure in miners and smelters is mainly through inhalation and dermal contact. Chronic inhalation exposure to AT particulates in B6C3F1/N mice and Wistar Han rats resulted in increased incidences and tumor multiplicities of alveolar/bronchiolar carcinomas (ABCs). In this study, we demonstrated Kras (43%) and Egfr (46%) hotspot mutations in mouse lung tumors (n = 80) and only Egfr (50%) mutations in rat lung tumors (n = 26). Interestingly, there were no differences in the incidences of these mutations in ABCs from rats and mice at exposure concentrations that did and did not exceed the pulmonary overload threshold. There was increased expression of p44/42 mitogen-activated protein kinase (MAPK) (Erk1/2) protein in ABCs harboring mutations in Kras and/or Egfr, confirming the activation of MAPK signaling. Transcriptomic analysis indicated significant alterations in MAPK signaling such as ephrin receptor signaling and signaling by Rho-family GTPases in AT-exposed ABCs. In addition, there was significant overlap between transcriptomic data from mouse ABCs due to AT exposure and human pulmonary adenocarcinoma data. Collectively, these data suggest chronic AT exposure exacerbates MAPK signaling in ABCs and, thus, may be translationally relevant to human lung cancers.

V-Set and immunoglobulin domain containing (VSIG) proteins as emerging immune checkpoint targets for cancer immunotherapy

The development of immune checkpoint inhibitors is becoming a promising approach to fight cancers. Antibodies targeting immune checkpoint proteins such as CTLA-4 and PD-1 can reinvigorate endogenous antitumor T-cell responses and bring durable advantages to several malignancies. However, only a small subset of patients benefit from these checkpoint inhibitors. Identification of new immune checkpoints with the aim of combination blockade of multiple immune inhibitory pathways is becoming necessary to improve efficiency. Recently, several B7 family-related proteins, TIGIT, VSIG4, and VSIG3, which belong to the VSIG family, have attracted substantial attention as coinhibitory receptors during T-cell activation. By interacting with their corresponding ligands, these VSIG proteins inhibit T-cell responses and maintain an immune suppressive microenvironment in tumors. These results indicated that VSIG family members are becoming putative immune checkpoints in cancer immunotherapy. In this review, we summarized the function of each VSIG protein in regulating immune responses and in tumor progression, thus providing an overview of our current understanding of VSIG family members.

Identification of cystic fibrosis transmembrane conductance regulator as a prognostic marker for juvenile myelomonocytic leukemia via the whole-genome bisulfite sequencing of monozygotic twins and data mining

BACKGROUND

Linked deoxyribonucleic acid (DNA) hypermethylation investigations of promoter methylation levels of candidate genes may help to increase the progressiveness and mortality rates of juvenile myelomonocytic leukemia (JMML), which is a unique myelodysplastic/myeloproliferative neoplasm caused by excessive monocyte and granulocyte proliferation in infancy/early childhood. However, the roles of hypermethylation in this malignant disease are uncertain.

METHODS

Bone marrow samples from a JMML patient and peripheral blood samples from a healthy monozygotic twin and an unrelated healthy donor were collected with the informed consent of the participant's parents. Whole-genome bisulfite sequencing (WGBS) was then performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to analyze specific differentially methylated region (DMG) related genes. The target genes were screened with Cytoscape and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), which are gene/protein interaction databases. A data mining platform was used to examine the expression level data of the healthy control and JMML patient tissues in Gene Expression Omnibus data sets, and a survival analysis was performed for all the JMML patients.

RESULTS

The STRING analysis revealed that the red node [i.e., the cystic fibrosis transmembrane conductance regulator (CFTR)] was the gene of interest. The gene-expression microarray data set analysis suggested that the CFTR expression levels did not differ significantly between the JMML patients and healthy controls (P=0.81). A statistically significant difference was observed in the CFTR promoter methylation level but not in the CFTR gene body methylation level. The overall survival analysis demonstrated that a high level of CFTR expression was associated with a worse survival rate in patients with JMML (P=0.039).

CONCLUSIONS

CFTR promoter hypermethylation may be a novel biomarker for the diagnosis, monitoring of disease progression, and prognosis of JMML.

Identification of Immune-Related Hub Genes in Thymoma: Defects in CD247 and Characteristics of Paraneoplastic Syndrome

Background: Thymomas (Ts) and thymic carcinomas (TCs) are rare primary tumors of the mediastinum. Paraneoplastic syndrome (PNS) is an important feature of thymoma, which presents great challenges to clinicians.

Methods: The present study uses the weighted gene co-expression network analysis (WGCNA) to identify possible immunologic mechanisms of thymoma. RNA sequencing data from thymoma samples were downloaded from the TCGA. Core genes were taken from the module that is closely related to the WHO’s stage of classification. Enhanced analysis using the online database “Metascape” and an overall survival (OS) analysis were carried out via the Kaplan–Meier method. The hub genes were obtained from the protein–protein interaction (PPI) network. In addition, we jointly analyzed multiple sets of PNS data related to thymomas from other sources to verify the correlation between thymomas and PNS. The impact of hub genes on the prognosis of PNS was evaluated via the ROC curve, with simultaneous analysis of immune infiltration by CIBERSORT.

Findings: The 14 immune hub genes closely related to thymomas were found to be jointly involved in the T-cell receptor signaling pathway. Compared to the normal thymus and type B1/B2 thymoma, there is a lower number of T-cells in type A/B3 thymoma and thymic carcinoma. The expression of genes related to the T-cell receptor signaling pathway appeared defective. The low expression of CD247 and the decrease in the number of mature T-cells are common features among thymomas, specific pulmonary fibrosis, rheumatoid arthritis, and systemic lupus erythematosus.

Data mining and mathematical models in cancer prognosis and prediction

Cancer is a fetal and complex disease. Individual differences of the same cancer type or the same patient at different stages of cancer development may require distinct treatments. Pathological differences are reflected in tissues, cells and gene levels etc. The interactions between the cancer cells and nearby microenvironments can also influence the cancer progression and metastasis. It is a huge challenge to understand all of these mechanistically and quantitatively. Researchers applied pattern recognition algorithms such as machine learning or data mining to predict cancer types or classifications. With the rapidly growing and available computing powers, researchers begin to integrate huge data sets, multi-dimensional data types and information. The cells are controlled by the gene expressions determined by the promoter sequences and transcription regulators. For example, the changes in the gene expression through these underlying mechanisms can modify cell progressing in the cell-cycle. Such molecular activities can be governed by the gene regulations through the underlying gene regulatory networks, which are essential for cancer study when the information and gene regulations are clear and available. In this review, we briefly introduce several machine learning methods of cancer prediction and classification which include Artificial Neural Networks (ANNs), Decision Trees (DTs), Support Vector Machine (SVM) and naive Bayes. Then we describe a few typical models for building up gene regulatory networks such as Correlation, Regression and Bayes methods based on available data. These methods can help on cancer diagnosis such as susceptibility, recurrence, survival etc. At last, we summarize and compare the modeling methods to analyze the development and progression of cancer through gene regulatory networks. These models can provide possible physical strategies to analyze cancer progression in a systematic and quantitative way.

Integrated analysis identified NPNT as a potential key regulator in tumor metastasis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the lethal malignancies worldwide. Tumor metastasis is the main cause of HCC related death. Although progress has been made in the mechanism study of HCC in the past decades, the underlying mechanism of HCC metastasis has not been fully illustrated. In the present study, bioinformatic analysis including weighted gene co-expression network analysis (WGCNA), differentially expressed gene analysis, and gene enrichment analysis were applied to discover genes correlated with HCC metastasis. Immunohistochemistry (IHC) assays were applied to detect the expression of NPNT in HCC samples. Cell transfection, wound healing, matrigel transwell assays, and western blot assays were utilized to evaluate the effects of NPNT on cell migration and invasion and signaling pathway variation. We found that NPNT was up-regulated in HCC tumor tissues compared with normal tissues. Especially, NPNT was highly expressed in metastatic tumor compared with non-metastatic HCC tumors. Down-regulation of NPNT via siRNA transfection inhibited cell migration, invasion, and FAK/PI3K/AKT signaling pathway in HCC. Our results demonstrate that NPNT is a potential key regulator in HCC metastasis.

Identification of Three Genes Associated with Metastasis in Melanoma and Construction of a Predictive Model: A Multiracial Identification

The aim of this study was to identify hub genes associated with metastasis and prognosis in melanoma. Weighted gene coexpression network analysis (WGCNA) was performed to screen and identify hub genes. ROC and K-M analyses were used to verify the hub genes in the internal and external data sets. The risk score model and nomogram model were constructed based on the IHC result. Through WGCNA, the three hub genes, SNRPD2, SNRPD3, and EIF4A3, were identified. In the external data set, the hub genes identified were associated with the worse prognosis (TCGA, SNRPD2, $P\le 0.02$ ; SNRPD3, $P=0.12$ ; EIF4A3, $P=0.11$ ; GSE65904, SNRPD2, $P=0.04$ ; SNRPD3, $P=0.10$ ; EIF4A3, $P<0.01$ ; GSE19234, SNRPD2, $P<0.01$ ; SNRPD3, $P<0.01$ ; EIF4A3, $P<0.01$ ). In the GSE8401, we found that the hub genes were highly expressed in the metastasis compared with the nonmetastasis group (SNRPD2, $988.5\pm 47.83$ vs. $738.4\pm 35.35$ , $P<0.01$ ; SNRPD3, $502.7\pm 25.7$ vs. $416.4\pm 23.88$ , $P=0.02$ ; EIF4A3, $567.6\pm 19.56$ vs. $495.2\pm 21.1$ , $P=0.01$ ). Moreover, the hub genes were identified by the IHC in our data set. The result was similar with the external data set. The hub genes could predict the metastasis and prognosis in the Chinese MM patients. Finally, the GSEA and Pearson analysis demonstrated that the SNRPD2 was associated with the immunotherapy. The three hub genes were identified and validated in MM patients in external and internal data sets. The risk factor model was constructed and verified as a powerful model to predict metastasis and prognosis in MM patients.

MicroRNA global profiling in cystic fibrosis cell lines reveals dysregulated pathways related with inflammation, cancer, growth, glucose and lipid metabolism, and fertility: an exploratory study

BACKGROUND AND AIM

Cystic fibrosis (CF), is due to CF transmembrane conductance regulator (CFTR) loss of function, and is associated with comorbidities. The increasing longevity of CF patients has been associated with increased cancer risk besides the other known comorbidities. The significant heterogeneity among patients, suggests potential epigenetic regulation. Little attention has been given to how CFTR influences microRNA (miRNA) expression and how this may impact on biological processes and pathways.

METHODS

We assessed the changes in miRNAs and subsequently identified the affected molecular pathways using CFBE41o-, and IB3 human immortalized cell lines since they reflect the most common genetic mutations in CF patients, and 16HBE14o- cells were used as controls.

RESULTS

In the CF cell lines, 41 miRNAs showed significant changes (FC (log2) ≥ +2 or FC (log2) ≤ -2 and p-value≤0.05). Gene target analysis evidenced 511 validated miRNA target genes. Gene Ontology analysis evidenced cancer, inflammation, body growth, glucose, and lipid metabolism as the biological processes most impacted by these miRNAs. Protein-protein interaction and pathway analysis highlighted 50 significantly enriched pathways among which RAS, TGF beta, JAK/STAT and insulin signaling.

CONCLUSIONS

CFTR loss of function is associated with changes in the miRNA network, which regulates genes involved in the major comorbidities that affect CF patients suggesting that further research is warranted.

Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis

BACKGROUND

Ovarian cancer (OC) is one of the worrisome gynecological cancers worldwide. Given its considerable mortality rate, it is necessary to investigate its oncogenesis.

METHODS

In this study, we used systems biology approaches to describe the key gene modules, hub genes, and regulatory drugs associated with serous OC as the novel biomarkers using weighted gene co-expression network analysis (WGCNA).

FINDINGS

Our findings have demonstrated that the blue module genes (r = 0.8, p-value = 1e-16) are involved in OC progression. Based on gene enrichment analysis, the genes in this module are frequently involved in biological processes such as the Cyclic adenosine monophosphate (cAMP) signaling pathway and the cellular response to transforming growth factor-beta stimulation. The co-expression network has been built using the correlated module's top hub genes, which are ADORA1, ANO9, CD24P4, CLDN3, CLDN7, ELF3, KLHL14, PRSS8, RASAL1, RIPK4, SERINC2, and WNT7A. Finally, a drug-target network has been built to show the interaction of the FDA-approved drugs with hub genes.

CONCLUSIONS

Our results have discovered that ADORA1, ANO9, SERINC2, and KLHL14 are hub genes associated with serous OC. These genes can be considered as novel candidate target genes for treating OC.

MicroRNA-2355-5p Promotes the Proliferation of Head and Neck Squamous Cell Carcinoma via Suppressing NISCH Expression

Background. MicroRNAs (miRNAs) have emerged as crucial regulators in various cancers. However, the potential role of miR-2355-5p in head and neck squamous cell carcinoma (HNSC) remains unclear. Methods. Bioinformatics methods were implemented to find the candidate target gene of miR-2355-5p. Quantitative real-time PCR was performed to detect RNA expression levels of miR-2355-5p and NISCH, while western blot was carried out for the detection of protein levels of NISCH and cell cycle-related biomarkers. CCK-8, EdU staining, and flow cytometry were employed to measure cell proliferation and cell cycle progression. Dual-luciferase assay and RNA pulldown were conducted to verify the binding relationship between miR-2355-5p and NISCH. Results. The expression levels of miR-2355-5p and NISCH were, respectively, higher and lower in HNSC tissues than those in normal adjacent tissues. The transfection of the miR-2355-5p inhibitor suppressed cell proliferation by arresting the cells at the G1/S transition. The results of luciferase activity and RNA pulldown assays indicated that miR-2355-5p directly targeted the NISCH 3′-untranslated region. Furthermore, the effects of miR-2355-5p inhibition on cell proliferation were reversed after treatment with siRNA against NISCH. Conclusion. In summary, our findings indicate that miR-2355-5p promotes cell cycle progression in HNSC by targeting NISCH. Hence, targeting miR-2355-5p could be a promising therapeutic strategy for the treatment of HNSC

MicroRNA-26b-5p suppresses the proliferation of tongue squamous cell carcinoma via targeting proline rich 11 (PRR11)

MicroRNAs (miRNAs) have been proved to be involved in many biological processes during tumorigenesis and progression, including cell proliferation and cell cycle progression. However, the potential role of miR-26b-5p in tongue squamous cell carcinoma (TSCC) remains unclear. In the present study, we demonstrated that miR-26b-5p was decreased in TSCC tissues in both TCGA-TSCC subset and eight paired samples from TSCC patients, while Proline Rich 11 (PRR11) was obviously increased. Transfection of miR-26b-5p mimics inhibited CALL7 cell proliferation by arresting the cells at the S/G2 transition. Meanwhile, miR-26b-5p inhibitor had the opposite biological functions. The results of luciferase activity and RNA-pulldown assays indicated that miR-26b-5p directly targeted the PRR11 3' -untranslated region in CAL27 cells. Furthermore, the effects of miR-26b-5p on cell cycle regulation were reversed after treatment with siRNA against PRR11. In summary, our findings indicate that miR-26b-5p induce cell cycle arrest in TSCC by targeting PRR11. Hence, targeting miR-26b-5p could be a promising therapeutic strategy for the treatment of TSCC.

Hypermethylation and Downregulation of UTP6 Are Associated With Stemness Properties, Chemoradiotherapy Resistance, and Prognosis in Rectal Cancer: A Co-expression Network Analysis

Background

To identify the hub genes associated with chemoradiotherapy resistance in rectal cancer and explore the potential mechanism.

Methods

Weighted gene co-expression network analysis (WGCNA) was performed to identify the gene modules correlated with the chemoradiotherapy resistance of rectal cancer.

Results

The mRNA expression of 31 rectal cancer patients receiving preoperative chemoradiotherapy was described in our previous study. Through WGCNA, we demonstrated that the chemoradiotherapy resistance modules were enriched for translation, DNA replication, and the androgen receptor signaling pathway. Additionally, we identified and validated UTP6 as a new effective predictor for chemoradiotherapy sensitivity and a prognostic factor for the survival of colorectal cancer patients using our data and the GSE35452 dataset. Low UTP6 expression was correlated with significantly worse disease-free survival (DFS), overall survival (OS), and event- and relapse-free survival both in our data and the R2 Platform. Moreover, we verified the UTP6 expression in 125 locally advanced rectal cancer (LARC) patients samples by immunohistochemical analysis. The results demonstrated that low UTP6 expression was associated with worse DFS and OS by Kaplan-Meier and COX regression model analyses. Gene set enrichment and co-expression analyses showed that the mechanism of the UTP6-mediated chemoradiotherapy resistance may involve the regulation of FOXK2 expression by transcription factor pathways.

Conclusion

Low expression of the UTP6 was found to be associated with chemoradiotherapy resistance and the prognosis of colorectal cancer possibly via regulating FOXK2 expression by transcription factor pathways.

Association of CASC18/miR-20a-3p/TGFB2 ceRNA axis with occult lymph node metastasis in tongue squamous cell carcinoma

Background

Tongue squamous cell carcinoma (TSCC) ranks as the most prevalent malignancy in the oral cavity. TSCC patients with occult lymph node metastasis (OLNM) are thought to be at risk of worse outcome. However, regulatory mechanisms underlying OLNM remain less investigated.

Methods

In the present study, CASC18/miR-20a-3p/TGFB2 axis was identified and evaluated by bioinformatic and qRT-PCR analyses. Effects of CASC18 knockdown on cell migration and invasion were determined by wound healing and transwell assays. Western blot, ELISA, RNA pulldown and luciferase reporter assays were performed for mechanism verification.

Results

CASC18 was identified up-regulating in TSCC tumours, and especially in those from patients with OLNM. Importantly, we found higher CASC18 expression was positively correlated with the presence of OLNM and worse outcome of TSCC patients. Furthermore, we demonstrated that CASC18 knockdown repressed cell migration and invasion through inhibiting epithelial-mesenchymal transition, which could be partly rescued by miR-20a-3p inhibitor. Regarding the molecular mechanism, we further confirmed that CASC18 functioned as a ceRNA to sponge miR-20a-3p to enhanceTGFB2 expression and secretion.

Conclusion

In conclusion, we have reported a novel CASC18/miR-20a-3p/TGFB2 ceRNA axis in OLNM of TSCC. Our findings will contribute to a deeper understanding of the molecular mechanism of OLNM in TSCC, and facilitate the development of diagnostic methods for assisting treatment decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00345-9.

Four Prognosis-Associated lncRNAs Serve as Biomarkers in Ovarian Cancer

Long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC) development. However, prognosis-associated lncRNAs (PALs) for OC have not been completely elucidated. Our study aimed to identify the PAL signature of OC. A total of 663 differentially expressed lncRNAs were identified in the databases. According to the weighted gene coexpression analysis, the highly correlated genes were clustered into seven modules related to the clinical phenotype of OC. A total of 25 lncRNAs that were significantly related to overall survival were screened based on univariate Cox regression analysis. The prognostic risk model constructed contained seven PALs based on the parameter λ_min, which could stratify OC patients into two risk groups. The results showed that the risk groups had different overall survival rates in both The Cancer Genome Atlas (TCGA) and two verified Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses confirmed that the risk model was an independent risk factor for OC. Gene enrichment analysis revealed that the identified genes were involved in some pathways of malignancy. The competitive endogenous RNA (ceRNA) network included five PALs, of which four were selected for cell function assays. The four PALs were downregulated in 33 collected OC tissues and 3 OC cell lines relative to the control. They were shown to regulate the proliferative, migratory, and invasive potential of OC cells via Cell Counting Kit-8 (CCK-8) and transwell assays. Our study fills the gaps of the four PALs in OC, which are worthy of further study.

Composition and function of ciliary inner-dynein-arm subunits studied in Chlamydomonas reinhardtii

Motile cilia (also interchangeably called "flagella") are conserved organelles extending from the surface of many animal cells and play essential functions in eukaryotes, including cell motility and environmental sensing. Large motor complexes, the ciliary dyneins, are present on ciliary outer-doublet microtubules and drive movement of cilia. Ciliary dyneins are classified into two general types: the outer dynein arms (ODAs) and the inner dynein arms (IDAs). While ODAs are important for generation of force and regulation of ciliary beat frequency, IDAs are essential for control of the size and shape of the bend, features collectively referred to as waveform. Also, recent studies have revealed unexpected links between IDA components and human diseases. In spite of their importance, studies on IDAs have been difficult since they are very complex and composed for several types of IDA motors, each unique in composition and location in the axoneme. Thanks in part to genetic, biochemical, and structural analysis of Chlamydomonas reinhardtii, we are beginning to understand the organization and function of the ciliary IDAs. In this review, we summarize the composition of Chlamydomonas IDAs particularly focusing on each subunit, and discuss the assembly, conservation, and functional role(s) of these IDA subunits. Furthermore, we raise several additional questions/challenges regarding IDAs, and discuss future perspectives of IDA studies.

Bioinformatics and integrated analyses of prognosis-associated key genes in lung adenocarcinoma

Background

The objective of the present study was to predict candidate genes with prognostic information for lung adenocarcinoma (LUAD).

Methods

Weighted correlation network analysis (WGCNA) was utilized to build the co-expression network of deferentially expressed genes (DEGs) in GSE32863. Key genes were identified as the intersecting genes of the modules of WGCNA and DEGs. Kaplan-Meier plotter was employed to conduct survival analysis. Enrichment analysis was performed. The expression of key genes in LUAD was validated. Then, we performed in vitro experiments to explore functions of key genes. We overexpressed DYNLRB2 in A549 cell. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting were test expression levels and functional analyses were performed, including cell viability, apoptosis.

Results

A total of 1,587 DEGs in GSE32863 were identified, including 649 up-regulated genes and 938 down-regulated genes. In coexpression analysis, there were 1,271 hubgenes from the modules that were chosen for further analysis. 15 key genes were identified as the intersecting genes of the modules of WGCNA and DEGs. The expressions of dynein light chain roadblock-type 2 (DYNLRB2) and mouse homolog of ß1 spectrin (SPTBN1) were lower in LUAD, and were associated with survival time of LUAD patients. GSEA results showed that high expressed DYNLRB2 and SPTBN1 were enriched in Drug metabolism cytochrome P450, Cardiac muscle contraction, Retinol metabolism. Down-regulated DYNLRB2 and SPTBN1 were associated with Homologous recombination, Progesterone mediated oocyte maturation, Base excision repair. The in vitro experiment confirmed the overexpression of DYNLRB2 in A549 transferred cells. The overexpress DYNLRB2 inhibited cell viability and induced apoptosis.

Conclusions

Our study suggested that DYNLRB2 and SPTBN1 might be potential tumor suppressor genes and could serve as biomarkers for predicting the prognosis of LUAD patients.

Identification of LncRNAs Associated With FOLFOX Chemoresistance in mCRC and Construction of a Predictive Model

Oxaliplatin, fluorouracil plus leucovorin (FOLFOX) regimen is the first-line chemotherapy of patients with metastatic colorectal cancer (mCRC). However, studies are limited regarding long non-coding RNAs (lncRNAs) associated with FOLFOX chemotherapy response and prognosis. This study aimed to identify lncRNAs associated with FOLFOX chemotherapy response and prognosis in mCRC patients and to construct a predictive model. We analyzed lncRNA expression in 11 mCRC patients treated with FOLFOX chemotherapy before surgery (four sensitive, seven resistant) by Gene Array Chip. The top eight lncRNAs (AC007193.8, CTD-2008N3.1, FLJ36777, RP11-509J21.4, RP3-508I15.20, LOC100130950, RP5-1042K10.13, and LINC00476) for chemotherapy response were identified according to weighted correlation network analysis (WGCNA). A competitive endogenous RNA (ceRNA) network was then constructed. The crucial functions of the eight lncRNAs enriched in chemotherapy resistance were mitogen-activated protein kinase (MAPK) and proteoglycans signaling pathway. Receiver operating characteristic (ROC) analysis demonstrated that the eight lncRNAs were potent predictors for chemotherapy resistance of mCRC patients. To further identify a signature model lncRNA chemotherapy response and prognosis, the validation set consisted of 196 CRC patients from our center was used to validate lncRNAs expression and prognosis by quantitative PCR (qPCR). The expression of the eight lncRNAs expression between CRC cancerous and adjacent non-cancerous tissues was also verified in the validation data set to determine the prognostic value. A generalized linear model was established to predict the probability of chemotherapy resistance and survival. Our findings showed that the eight-lncRNA signature may be a novel biomarker for the prediction of FOLFOX chemotherapy response and prognosis of mCRC patients.

Secretoglobin 3A2 eliminates human cancer cells through pyroptosis

Non-canonical inflammasome activation that recognizes intracellular lipopolysaccharide (LPS) causes pyroptosis, the inflammatory death of innate immune cells. The role of pyroptosis in innate immune cells is to rapidly eliminate pathogen-infected cells and limit the replication niche in the host body. Whether this rapid cell elimination process of pyroptosis plays a role in elimination of cancer cells is largely unknown. Our earlier study demonstrated that a multi-functional secreted protein, secretoglobin (SCGB) 3A2, chaperones LPS to cytosol, and activates caspase-11 and the non-canonical inflammasome pathway, leading to pyroptosis. Here we show that SCGB3A2 exhibits marked anti-cancer activity against 5 out of 11 of human non-small cell lung cancer cell lines in mouse xenographs, while no effect was observed in 6 of 6 small cell lung cancer cell lines examined. All SCGB3A2-LPS-sensitive cells express syndecan 1 (SDC1), a SCGB3A2 cell surface receptor, and caspase-4 (CASP4), a critical component of the non-canonical inflammasome pathway. Two epithelial-derived colon cancer cell lines expressing SDC1 and CASP4 were also susceptible to SCGB3A2-LPS treatment. TCGA analysis revealed that lung adenocarcinoma patients with higher SCGB3A2 mRNA levels exhibited better survival. These data suggest that SCGB3A2 uses the machinery of pyroptosis for the elimination of human cancer cells via the non-canonical inflammasome pathway, and that SCGB3A2 may serve as a novel therapeutic to treat cancer, perhaps in combination with immuno and/or targeted therapies.

A bird eye view on cystic fibrosis: An underestimated multifaceted chronic disorder

Cystic fibrosis (CF) is an autosomal recessive disease which involves the mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. CF involves in the inflammatory processes and is considered as a multisystem disorder that is not confined to lungs, but it also affects other vital organs that leads to numerous co-morbidities. The respiratory disorder in the CF results in mortality and morbidity which is characterized by series of serious events involving mucus hypersecretion, microbial infections, airways obstruction, inflammation, destruction of epithelium, tissue remodeling and terminal lung diseases. Mucins are the high molecular weight glycoproteins important for the viscoelastic properties of the mucus, play a significant role in the disease mechanisms. Determining the functional association between the CFTR and mucins might help to identify the putative target for specific therapeutic approach. In fact, furin enzyme which helps in the entry of novel COVID-19 virus into the cell, is upregulated in CF and this can also serve as a potential target for CF treatment. Moreover, the use of nano-formulations for CF treatment is an area of research being widely studied as they have also demonstrated promising outcomes. The in-depth knowledge of non-coding RNAs like miRNAs and lncRNAs and their functional association with CFTR gene expression and mutation can provide a different range of opportunity to identify the promising therapeutic approaches for CF.

Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder

An effective feature extraction method is key to improving the accuracy of a prediction model. From the Gene Expression Omnibus (GEO) database, which includes 13,487 genes, we obtained microarray gene expression data for 238 samples from colorectal cancer (CRC) samples and normal samples. Twelve gene modules were obtained by weighted gene co-expression network analysis (WGCNA) on 173 samples. By calculating the Pearson correlation coefficient (PCC) between the characteristic genes of each module and colorectal cancer, we obtained a key module that was highly correlated with CRC. We screened hub genes from the key module by considering module membership, gene significance, and intramodular connectivity. We selected 10 hub genes as a type of feature for the classifier. We used the variational autoencoder (VAE) for 1159 genes with significantly different expressions and mapped the data into a 10-dimensional representation, as another type of feature for the cancer classifier. The two types of features were applied to the support vector machines (SVM) classifier for CRC. The accuracy was 0.9692 with an AUC of 0.9981. The result shows a high accuracy of the two-step feature extraction method, which includes obtaining hub genes by WGCNA and a 10-dimensional representation by variational autoencoder (VAE).

What Role Does CFTR Play in Development, Differentiation, Regeneration and Cancer?

One of the key features associated with the substantial increase in life expectancy for individuals with CF is an elevated predisposition to cancer, firmly established by recent studies involving large cohorts. With the recent advances in cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies and the increased long-term survival rate of individuals with cystic fibrosis (CF), this is a novel challenge emerging at the forefront of this disease. However, the mechanisms linking dysfunctional CFTR to carcinogenesis have yet to be unravelled. Clues to this challenging open question emerge from key findings in an increasing number of studies showing that CFTR plays a role in fundamental cellular processes such as foetal development, epithelial differentiation/polarization, and regeneration, as well as in epithelial–mesenchymal transition (EMT). Here, we provide state-of-the-art descriptions on the moonlight roles of CFTR in these processes, highlighting how they can contribute to novel therapeutic strategies. However, such roles are still largely unknown, so we need rapid progress in the elucidation of the underlying mechanisms to find the answers and thus tailor the most appropriate therapeutic approaches.

FBXW4 Acts as a Protector of FOLFOX-Based Chemotherapy in Metastatic Colorectal Cancer Identified by Co-Expression Network Analysis

Background

FOLFOX chemotherapy is one of the most commonly used treatments for colorectal cancer (CRC) patients. However, the efficacy and tolerance of FOLFOX therapy varies between patients. The purpose of this study was to explore hub genes associated with primary chemotherapy-resistance and to explore the possible mechanisms involved from non-European patients.

Method

A weighted gene co-expression network was constructed to identify gene modules associated with chemotherapy resistance in mCRC from China.

Results

A Gene Array Chip was used to detect mRNA expression in 11 mCRC patients receiving preoperative FOLFOX chemotherapy. The immune response was associated with chemotherapy-resistance in microarray data. Through the use of WGCNA, we demonstrated that the crucial functions enriched in chemotherapy-resistance modules were cell proliferation, MAPK signaling pathways, and PI3K signaling pathways. Additionally, we identified and validated FBXW4 as a new effective predictor for chemotherapy sensitivity and a prognostic factor for survival of CRC patients by using our own data and GSE69657. Furthermore, a meta-analysis of 15 Gene Expression Omnibus–sourced datasets showed that FBXW4 messenger RNA levels were significantly lower in CRC tissues than in normal colon tissues. An analysis of the data from the R2: Genomics Analysis and Visualization Platform showed that low FBXW4 expression was correlated with a significantly worse event- and relapse-free survival. Gene set enrichment analysis showed that the mechanism of FBXW4-mediated chemotherapy resistance may involve the DNA replication signal pathway and the cell cycle.

Conclusion

FBXW4 is associated with chemotherapy resistance and prognosis of CRC probably by regulating DNA replication signaling pathways and the cell cycle.

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

Identification of a novel synthetic lethal vulnerability in non-small cell lung cancer by co-targeting TMPRSS4 and DDR1

Finding novel targets in non-small cell lung cancer (NSCLC) is highly needed and identification of synthetic lethality between two genes is a new approach to target NSCLC. We previously found that TMPRSS4 promotes NSCLC growth and constitutes a prognostic biomarker. Here, through large-scale analyses across 5 public databases we identified consistent co-expression between TMPRSS4 and DDR1. Similar to TMPRSS4, DDR1 promoter was hypomethylated in NSCLC in 3 independent cohorts and hypomethylation was an independent prognostic factor of disease-free survival. Treatment with 5-azacitidine increased DDR1 levels in cell lines, suggesting an epigenetic regulation. Cells lacking TMPRSS4 were highly sensitive to the cytotoxic effect of the DDR1 inhibitor dasatinib. TMPRSS4/DDR1 double knock-down (KD) cells, but not single KD cells suffered a G0/G1 cell cycle arrest with loss of E2F1 and cyclins A and B, increased p21 levels and a larger number of cells in apoptosis. Moreover, double KD cells were highly sensitized to cisplatin, which caused massive apoptosis (~40%). In vivo studies demonstrated tumor regression in double KD-injected mice. In conclusion, we have identified a novel vulnerability in NSCLC resulting from a synthetic lethal interaction between DDR1 and TMPRSS4.

Distinct signatures of lung cancer types: aberrant mucin O-glycosylation and compromised immune response

BACKGROUND

Genomic initiatives such as The Cancer Genome Atlas (TCGA) contain data from -omics profiling of thousands of tumor samples, which may be used to decipher cancer signaling, and related alterations. Managing and analyzing data from large-scale projects, such as TCGA, is a demanding task. It is difficult to dissect the high complexity hidden in genomic data and to account for inter-tumor heterogeneity adequately.

METHODS

In this study, we used a robust statistical framework along with the integration of diverse bioinformatic tools to analyze next-generation sequencing data from more than 1000 patients from two different lung cancer subtypes, i.e., the lung adenocarcinoma (LUAD) and the squamous cell carcinoma (LUSC).

RESULTS

We used the gene expression data to identify co-expression modules and differentially expressed genes to discriminate between LUAD and LUSC. We identified a group of genes which could act as specific oncogenes or tumor suppressor genes in one of the two lung cancer types, along with two dual role genes. Our results have been validated against other transcriptomics data of lung cancer patients.

CONCLUSIONS

Our integrative approach allowed us to identify two key features: a substantial up-regulation of genes involved in O-glycosylation of mucins in LUAD, and a compromised immune response in LUSC. The immune-profile associated with LUSC might be linked to the activation of three oncogenic pathways, which promote the evasion of the antitumor immune response. Collectively, our results provide new future directions for the design of target therapies in lung cancer.

Exploration of the hub genes and miRNAs in lung adenocarcinoma

In order to investigate the oncogenic mechanisms of lung adenocarcinoma (LUAD), hub genes can be identified by constructing co-expression networks, and the potential linkages between hub genes, transcription factors (TFs) and microRNAs (miRNAs/miRs) can be visualized and identified. In the present study, a total of 12 co-expressed modules were constructed, and 9 of these were significantly correlated with clinical traits in LUAD. The differentially expressed genes and differentially expressed miRNAs were determined, and the targets of differentially expressed miRNA were identified from the hub genes or TFs. The results of the present study demonstrated that 10 hub genes and 12 TFs are the predicted targets for the 5 and 8 differentially expressed miRNAs, respectively. Genes in pink and red modules, which have a high correlation with the clinical trait of days to death, are significantly enriched in 'nucleosome assembly' and 'microtubule-based process', respectively. These results indicated that miR-206, miR-137, miR-153, hub genes and enriched TFs in the pink and red modules exert a potentially pivotal function in the development of LUAD.

Is cellular senescence involved in cystic fibrosis?

Pulmonary disease is the main cause of the morbidity and mortality of patients affected by cystic fibrosis (CF). The lung pathology is dominated by excessive recruitment of neutrophils followed by an exaggerated inflammatory process that has also been reported to occur in the absence of apparent pathogenic infections. Airway surface dehydration and mucus accumulation are the driving forces of this process. The continuous release of reactive oxygen species and proteases by neutrophils contributes to tissue damage, which eventually leads to respiratory insufficiency. CF has been considered a paediatric problem for several decades. Nevertheless, during the last 40 years, therapeutic options for CF have been greatly improved, turning CF into a chronic disease and extending the life expectancy of patients. Unfortunately, chronic inflammatory processes, which are characterized by a substantial release of cytokines and chemokines, along with ROS and proteases, can accelerate cellular senescence, leading to further complications in adulthood. The alterations and mechanisms downstream of CFTR functional defects that can stimulate cellular senescence remain unclear. However, while there are correlative data suggesting that cellular senescence may be implicated in CF, a causal or consequential relationship between cellular senescence and CF is still far from being established. Senescence can be both beneficial and detrimental. Senescence may suppress bacterial infections and cooperate with tissue repair. Additionally, it may act as an effective anticancer mechanism. However, it may also promote a pro-inflammatory environment, thereby damaging tissues and leading to chronic age-related diseases. In this review, we present the most current knowledge on cellular senescence and contextualize its possible involvement in CF.

CFTR activation suppresses glioblastoma cell proliferation, migration and invasion

The aim of this study was to investigate the function of Cystic fibrosis transmembrane conductance regulator (CFTR) in human glioblastoma (GBM) cells. Data dining results of the Human Protein Atlas showed that low CFTR expression was associated with poor prognosis for GBM patients. We found that CFTR protein expression was lower in U87 and U251 GBM cells than that in normal humane astrocyte cells. CFTR activation significantly reduced GBM cell proliferation. In addition, CFTR activation significantly abrogated migration and invasion of GBM cells. Besides, CFTR activator Forskolin treatment markedly reduced MMP-2 protein expression. These effects of CFTR activation were significantly inhibited by CFTR inhibitor CFTRinh-172 pretreatment. Our findings suggested that JAK2/STAT3 signaling was involved in the anti-glioblastoma effects of CFTR activation. Moreover, CFTR overexpression in combination with Forskolin induced a synergistic anti-proliferative response in U87 cells. Overall, our findings demonstrated that CFTR activation suppressed GBM cell proliferation, migration and invasion likely through the inhibition of JAK2/STAT3 signaling.

GLIS2 redundancy causes chemoresistance and poor prognosis of gastric cancer based on co‑expression network analysis

Gastric cancer is currently the fourth most common cancer and the third leading cause of cancer-associated mortality worldwide. Studies have identified that certain biomarkers contribute to the prognosis, diagnosis and treatment of gastric cancer. However, the biomarkers of gastric cancer are rarely used clinically. Therefore, it is imperative to define novel molecular networks and key genes to guide the further study and clinical treatment of gastric cancer. In the present study, raw RNA sequencing data and clinicopathological information on patients with gastric cancer were downloaded from The Cancer Genome Atlas, and a weighted gene co-expression network analysis was conducted. Additionally, functional enrichment and protein-protein interaction analyses were implemented to further examine the significant modules. As a result, 16 modules of highly correlated genes were acquired and colour coded, and the yellow module containing 174 genes associated with chemotherapy resistance and prognosis in gastric cancer was further analysed. The biological processes of the yellow module were primarily associated with cell adhesion, vasculature development and the regulation of cell proliferation. In addition, the Kyoto Encyclopedia of Genes and Genomes pathways primarily involved the transforming growth factor-β signalling pathway, the cellular tumour antigen p53 signalling pathway, extracellular matrix-receptor interactions and focal adhesions. Notably, survival analysis and cell verification confirmed that high expression of GLIS family zinc finger 2 is significantly associated with chemoresistance and a worse prognosis in gastric cancer, and that this high expression is likely to be an important biomarker for the guidance of clinical treatment and prognostic evaluation.

Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis

BACKGROUND RUNXl plays a key regulatory role in the process of hematopoiesis and is a common target for multiple chromosomal translocations in human acute leukemia. Mutations of RUNX1 gene can lead to acute leukemia and affect the prognosis of AML patients. We aimed to identify pivotal genes and pathways involved in RUNX1-mutated patients of with acute myeloid leukemia (AML) and to explore possible molecular markers for novel therapeutic targets of the disease. MATERIAL AND METHODS The RNA sequencing datasets of 151 cases of AML were obtained from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified using edgeR of the R platform. PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS A total of 379 genes were identified as DEGs. The KEGG enrichment analysis of DEGs showed significantly enriched pathways in cancer, extracellular matrix (ECM)-receptor interaction pathway, and cyclic adenosine monophosphate (cAMP) signaling pathway. The top 10 genes ranked by degree were PRKACG, ANKRD7, RNFL7, ROPN11, TEX14, PRMT8, OTOA, CFAP99, NRXN1, and DMRT1, which were identified as hub genes from the protein-protein interaction network (PPI). Statistical analysis revealed that RUNX1-mutated patients with AML had a shorter median survival time (MST) with poor clinical outcome and an increased risk of death when compared with those without RUNX1 mutations. CONCLUSIONS DEGs and pathways identified in the present study will help understand the molecular mechanisms underlying RUNX1 mutations in AML and develop effective therapeutic strategies for RUNX1-mutation AML.

Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis

BACKGROUND RUNXl plays a key regulatory role in the process of hematopoiesis and is a common target for multiple chromosomal translocations in human acute leukemia. Mutations of RUNX1 gene can lead to acute leukemia and affect the prognosis of AML patients. We aimed to identify pivotal genes and pathways involved in RUNX1-mutated patients of with acute myeloid leukemia (AML) and to explore possible molecular markers for novel therapeutic targets of the disease. MATERIAL AND METHODS The RNA sequencing datasets of 151 cases of AML were obtained from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified using edgeR of the R platform. PPI (protein-protein interaction) network clustering modules were analyzed with ClusterONE, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses for modules were performed. RESULTS A total of 379 genes were identified as DEGs. The KEGG enrichment analysis of DEGs showed significantly enriched pathways in cancer, extracellular matrix (ECM)-receptor interaction pathway, and cyclic adenosine monophosphate (cAMP) signaling pathway. The top 10 genes ranked by degree were PRKACG, ANKRD7, RNFL7, ROPN11, TEX14, PRMT8, OTOA, CFAP99, NRXN1, and DMRT1, which were identified as hub genes from the protein-protein interaction network (PPI). Statistical analysis revealed that RUNX1-mutated patients with AML had a shorter median survival time (MST) with poor clinical outcome and an increased risk of death when compared with those without RUNX1 mutations. CONCLUSIONS DEGs and pathways identified in the present study will help understand the molecular mechanisms underlying RUNX1 mutations in AML and develop effective therapeutic strategies for RUNX1-mutation AML.

Weighted gene co‑expression network analysis in identification of key genes and networks for ischemic‑reperfusion remodeling myocardium

Acute myocardial infarction induces ventricular remodeling, which is implicated in dilated heart and heart failure. The pathogenical mechanism of myocardium remodeling remains to be elucidated. The aim of the present study was to identify key genes and networks for myocardium remodeling following ischemia-reperfusion (IR). First, the mRNA expression data from the National Center for Biotechnology Information database were downloaded to identify differences in mRNA expression of the IR heart at days 2 and 7. Then, weighted gene co-expression network analysis, hierarchical clustering, protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to identify key genes and networks for the heart remodeling process following IR. A total of 3,321 differentially expressed genes were identified during the heart remodeling process. A total of 6 modules were identified through gene co-expression network analysis. GO and KEGG analysis results suggested that each module represented a different biological function and was associated with different pathways. Finally, hub genes of each module were identified by PPI network construction. The present study revealed that heart remodeling following IR is a complicated process, involving extracellular matrix organization, neural development, apoptosis and energy metabolism. The dysregulated genes, including SRC proto-oncogene, non-receptor tyrosine kinase, discs large MAGUK scaffold protein 1, ATP citrate lyase, RAN, member RAS oncogene family, tumor protein p53, and polo like kinase 2, may be essential for heart remodeling following IR and may be used as potential targets for the inhibition of heart remodeling following acute myocardial infarction.

Cystic fibrosis transmembrane conductance regulator-emerging regulator of cancer

Mutations of cystic fibrosis transmembrane conductance regulator (CFTR) cause cystic fibrosis, the most common life-limiting recessive genetic disease among Caucasians. CFTR mutations have also been linked to increased risk of various cancers but remained controversial for a long time. Recent studies have begun to reveal that CFTR is not merely an ion channel but also an important regulator of cancer development and progression with multiple signaling pathways identified. In this review, we will first present clinical findings showing the correlation of genetic mutations or aberrant expression of CFTR with cancer incidence in multiple cancers. We will then focus on the roles of CFTR in fundamental cellular processes including transformation, survival, proliferation, migration, invasion and epithelial-mesenchymal transition in cancer cells, highlighting the signaling pathways involved. Finally, the association of CFTR expression levels with patient prognosis, and the potential of CFTR as a cancer prognosis indicator in human malignancies will be discussed.

Integrated TCGA analysis implicates lncRNA CTB-193M12.5 as a prognostic factor in lung adenocarcinoma

Background

Lung cancer is a malignant tumor with the highest incidence and mortality around the world. Recent advances in RNA sequencing technology have enabled insights into long non-coding RNAs (lncRNAs), a previously largely overlooked species in dissecting lung cancer pathology.

Methods

In this study, we used a comprehensive bioinformatics analysis strategy to identify lncRNAs closely associated with lung adenocarcinoma, using the RNA sequencing datasets collected from more than 500 lung adenocarcinoma patients and deposited at The Cancer Genome Atlas (TCGA) database.

Results

Differential expression analysis highlighted lncRNAs CTD-2510F5.4 and CTB-193M12.5, both of which were significantly upregulated in cancerous specimens. Moreover, network analyses showed highly correlated expression levels of both lncRNAs with those of differentially expressed protein-coding genes, and suggested central regulatory roles of both lncRNAs in the gene co-expression network. Importantly, expression of CTB-193M12.5 showed strong negative correlation with patient survival.

Conclusions

Our study mined existing TCGA datasets for novel factors associated with lung adenocarcinoma, and identified a largely unknown lncRNA as a potential prognostic factor. Further investigation is warranted to characterize the roles and significance of CTB-193M12.5 in lung adenocarcinoma biology.

Electronic supplementary material

The online version of this article (10.1186/s12935-018-0513-3) contains supplementary material, which is available to authorized users.

From systems biology to P4 medicine: applications in respiratory medicine

Human health and disease are emergent properties of a complex, nonlinear, dynamic multilevel biological system: the human body. Systems biology is a comprehensive research strategy that has the potential to understand these emergent properties holistically. It stems from advancements in medical diagnostics, “omics” data and bioinformatic computing power. It paves the way forward towards “P4 medicine” (predictive, preventive, personalised and participatory), which seeks to better intervene preventively to preserve health or therapeutically to cure diseases. In this review, we: 1) discuss the principles of systems biology; 2) elaborate on how P4 medicine has the potential to shift healthcare from reactive medicine (treatment of illness) to predict and prevent illness, in a revolution that will be personalised in nature, probabilistic in essence and participatory driven; 3) review the current state of the art of network (systems) medicine in three prevalent respiratory diseases (chronic obstructive pulmonary disease, asthma and lung cancer); and 4) outline current challenges and future goals in the field.

Systems biology and network medicine have the potential to transform medical research and practicehttp://ow.ly/r3jR30hf35x

Identification of two novel biomarkers of rectal carcinoma progression and prognosis via co-expression network analysis

mRNA expression profiles provide important insights on a diversity of biological processes involved in rectal carcinoma (RC). Our aim was to comprehensively map complex interactions between the mRNA expression patterns and the clinical traits of RC. We employed the integrated analysis of five microarray datasets and The Cancer Genome Atlas rectal adenocarcinoma database to identify 2118 consensual differentially expressed genes (DEGs) in RC and adjacent normal tissue samples, and then applied weighted gene co-expression network analysis to parse DEGs and eight clinical traits in 66 eligible RC samples. A total of 16 co-expressed gene modules were identified. The green-yellow and salmon modules were most appropriate to the pathological stage (R = 0.36) and the overall survival (HR =13.534, P = 0.014), respectively. A diagnostic model of the five pathological stage hub genes (SCG3, SYP, CDK5R2, AP3B2, and RUNDC3A) provided a powerful classification accuracy between localized RC and non-localized RC. We also found increased Secretogranin III (SCG3) expression with higher pathological stage and poorer prognosis in the test and validation set. The increased Homer scaffolding protein 2 (HOMER2) expression with the favorable survival prediction efficiency significantly correlated with the markedly reduced overall survival of RC patients and the higher pathological stage during the test and validation set. Our findings indicate that the SCG3 and HOMER2 mRNA levels should be further evaluated as predictors of pathological stage and survival in patients with RC.

DNA Mutations May Not Be the Cause of Cancer

Cancer is the most challenging disease of our time with increasing numbers of new cases each year, worldwide. Great achievements have been reached in cancer research through deep sequencing which helped define druggable targets. However, the still-evolving targeted therapy suffers resistance suggesting that DNA mutations considered as drivers may not have a role in tumor initiation. The present work discusses the role of DNA mutations as drivers and passengers in cancer initiation and development. First, it is important to discern the role of these DNA mutations as initiating events causing cancer or as contributors crucial for the development of a tumor once it has initiated. Second, breast cancer shown here illustrates how identification of DNA mutations in cancerous cells has influenced our approach for anti-cancer drug design. The cancer trilogy we have reached and described as: initial drug; resistance/recurrence; drug/treatment combinations, calls for a paradigm shift. To design more effective cancer drugs with durable and positive outcome, future cancer research needs to move beyond the sequencing era and explore changes which are taking place in cancer cells at levels other than the DNA. Evolutionary constraints may be acting as a barrier to preserve the human species from being transformed and, for that matter, all multi-cellular species which can incur cancer. Furthermore, mutations in the DNA do occur and for a multitude of reasons but without necessarily causing cancer. New directions will draw themselves when more focus is given to the event responsible for the switch of a cell from normalcy to malignancy. Until then, targeted therapy will certainly continue to improve the outcome of patients; however, it is unlikely to eradicate breast cancer depicted here.