NDUFA4L2 is associated with clear cell renal cell carcinoma malignancy and is regulated by ELK1

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell RCC (ccRCC) and non-clear cell RCC (non-ccRCC) for treatment based on the current NCCN Guidelines. Thus, the classification will be associated with therapeutic implications. This study aims to identify novel biomarkers to differentiate ccRCC from non-ccRCC using bioinformatics and machine learning. The gene expression profiles of ccRCC and non-ccRCC subtypes (including papillary RCC (pRCC) and chromophobe RCC (chRCC)), were obtained from TCGA. Differential expression genes (DEGs) were identified, and specific DEGs for ccRCC and non-ccRCC were explored using a Venn diagram. Gene Ontology and pathway enrichment analysis were performed using DAVID. The top ten expressed genes in ccRCC were then selected for machine learning analysis. Feature selection was operated to identify a minimum highly effective gene set for constructing a predictive model. The expression of best-performing gene set was validated on tissue samples from RCC patients using immunohistochemistry techniques. Subsequently, machine learning models for diagnosing RCC were developed using H-scores. There were 910, 415, and 835 genes significantly specific for DEGs in ccRCC, pRCC, and chRCC, respectively. Specific DEGs in ccRCC enriched in PD-1 signaling, immune system, and cytokine signaling in the immune system, whereas TCA cycle and respiratory, signaling by insulin receptor, and metabolism were enriched in chRCC. Feature selection based on Decision Tree Classifier revealed that the model with two genes, including NDUFA4L2 and DAT, had an accuracy of 98.89%. Supervised classification models based on H-score of NDUFA4L2, and DAT revealed that Decision Tree models showed the best performance with 82% accuracy and 0.9 AUC. NDUFA4L2 expression was associated with lymphovascular invasion, pathologic stage and pT stage in ccRCC. Using integrated bioinformatics and machine learning analysis, NDUFA4L2 and DAT were identified as novel biomarkers to differential diagnosis ccRCC from non-ccRCC.

Elevated of NDUFA4L2 expression in colon adenocarcinoma is correlated with an unfavorable prognosis and increased immune cell infiltration

Background

Colon adenocarcinoma (COAD) is a prevalent malignancy worldwide, yet, its underlying pathogenesis and genetic characteristics are still unclear. Previous studies have suggested that NADH dehydrogenase 1 alpha subcomplex subunit 4-like 2 (NDUFA4L2) may affect tumor progression across various cancers. However, this effect on COAD has rarely been reported. Thus, this study investigated NDUFA4L2's prognostic and diagnostic relevance and explored its potential connection with immune cell infiltration in COAD.

Methods

To achieve this, RNA sequencing data from Cancer Genome Atlas (TCGA) was analyzed to assess NDUFA4L2's prognostic value in COAD, and factors relevant to the prognosis of COAD, including NDUFA4L2, were scrutinized using Kaplan-Meier analyses as well as univariate and multivariate Cox regression. A nomogram model was created to project prognosis based on the results of multivariate Cox analysis. Furthermore, gene set enrichment analysis (GSEA) was employed to pinpoint key NDUFA4L2-related pathways, and single-sample GSEA (ssGSEA) on TCGA data was employed to investigate the connections of NDUFA4L2 with cancer immune infiltrations.

Results

Our findings revealed significant associations of high NDUFA4L2 expression with poor overall survival, progression-free interval, and disease-specific survival of COAD patients. GSEA indicated close links of NDUFA4L2 with several signaling pathways implicated in tumorigenesis, including extracellular matrix receptor interaction, the intestinal immune network for immunoglobulin A production, natural killer (NK) cell-mediated cytotoxicity, pathways in cancer, cell adhesion molecules, mitogen-activated protein kinase signaling pathway, Hedgehog signaling pathway, transforming growth factor beta signaling pathway, and chemokine signaling pathway. Additionally, ssGSEA identified a positive link between increased NDUFA4L2 expression and higher infiltration degree of various immune cells, such as immature dendritic cells, macrophages, NK cells and dendritic cells.

Conclusions

Collectively, our findings demonstrate the association of increased NDUFA4L2 expression with adverse prognosis and heightened immune cell infiltration in COAD patients.

An m6A-Driven Prognostic Marker Panel for Renal Cell Carcinoma Based on the First Transcriptome-Wide m6A-seq

To date, only a single transcriptome-wide m6A sequencing study of clear cell renal cell carcinoma (ccRCC) has been reported, with no validation so far. Herein, by TCGA analysis of the KIRC cohort (n = 530 ccRCC; n = 72 normal), an external expression validation of 35 preidentified m6A targets was performed. Further in-depth expression stratification enabled assessment of m6A-driven key targets. Overall survival (OS) analysis and gene set enrichment analyses (GSEA) were conducted to assess their clinical and functional impact on ccRCC. In the hyper-up cluster significant upregulation was confirmed for NDUFA4L2, NXPH4, SAA1, and PLOD2 (40%) and in the hypo-up cluster for FCHSD1 (10%). Significant downregulation was observed for UMOD, ANK3, and CNTFR (27.3%) in the hypo-down cluster and for CHDH (25%) in the hyper-down cluster. In-depth expression stratification showed consistent dysregulation in ccRCC only for 11.67%: NDUFA4L2, NXPH4, and UMOD (NNU-panel). Patients with strong NNU panel dysregulation had significantly poorer OS (p = 0.0075). GSEA identified 13 associated and significantly upregulated gene sets (all p-values < 0.5; FDR < 0.25). External validation of the only available m6A sequencing in ccRCC consistently reduced dysregulated m6A-driven targets on the NNU panel with highly significant effects on OS. Epitranscriptomics are a promising target for developing novel therapies and for identifying prognostic markers for daily clinical practice.

Accurate detection of benign and malignant renal tumor subtypes with MethylBoostER: An epigenetic marker-driven learning framework

Current gold standard diagnostic strategies are unable to accurately differentiate malignant from benign small renal masses preoperatively; consequently, 20% of patients undergo unnecessary surgery. Devising a more confident presurgical diagnosis is key to improving treatment decision-making. We therefore developed MethylBoostER, a machine learning model leveraging DNA methylation data from 1228 tissue samples, to classify pathological subtypes of renal tumors (benign oncocytoma, clear cell, papillary, and chromophobe RCC) and normal kidney. The prediction accuracy in the testing set was 0.960, with class-wise ROC AUCs >0.988 for all classes. External validation was performed on >500 samples from four independent datasets, achieving AUCs >0.89 for all classes and average accuracies of 0.824, 0.703, 0.875, and 0.894 for the four datasets. Furthermore, consistent classification of multiregion samples (N = 185) from the same patient demonstrates that methylation heterogeneity does not limit model applicability. Following further clinical studies, MethylBoostER could facilitate a more confident presurgical diagnosis to guide treatment decision-making in the future.

Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers

Background

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq).

Methods

We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level.

Results

Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC.

Conclusions

Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.

Single-Cell RNA-seq Identification of the Cellular Molecular Characteristics of Sporadic Bilateral Clear Cell Renal Cell Carcinoma

Bilateral renal cell carcinoma (RCC) is a rare disease that can be classified as either familial or sporadic. Studying the cellular molecular characteristics of sporadic bilateral RCC is important to provide guidance for clinical treatment. Cellular molecular characteristics can be expressed at the RNA level, especially at the single-cell degree. Single-cell RNA sequencing (scRNA-seq) was performed on bilateral clear cell RCC (ccRCC). A total of 3,575 and 3,568 high-quality single-cell transcriptome data were captured from the left and right tumour tissues, respectively. Gene characteristics were identified by comparing left and right tumours at the scRNA level. The complex cellular environment of bilateral ccRCC was presented by using scRNA-seq. Single-cell transcriptomic analysis revealed high similarity in gene expression among most of the cell types of bilateral RCCs but significant differences in gene expression among different site tumour cells. Additionally, the potential biological function of different tumour cell types was determined by gene ontology (GO) analysis. The transcriptome characteristics of tumour tissues in different locations at the single-cell transcriptome level were revealed through the scRNA-seq of bilateral sporadic ccRCC. This work provides new insights into the diagnosis and treatment of bilateral RCC.

Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response

Renal cell carcinomas (RCCs) are heterogeneous malignancies thought to arise from kidney tubular epithelial cells, and clear cell RCC is the most common entity. This study demonstrates that cell atlases generated from benign kidney and two common RCCs using single-cell RNA sequencing can predict putative cells of origin for more than 10 RCC subtypes. A focused analysis of distinct cell-type compartments reveals the potential role of tumor epithelia in promoting immune infiltration and other molecular attributes of the tumor microenvironment. Finally, an observed association between the lack of immunotherapy response and endothelial cell fraction has important clinical implications. The current study, therefore, significantly contributes toward understanding disease ontogenies and the molecular dynamics of tumor epithelia and the microenvironment.

Diverse subtypes of renal cell carcinomas (RCCs) display a wide spectrum of histomorphologies, proteogenomic alterations, immune cell infiltration patterns, and clinical behavior. Delineating the cells of origin for different RCC subtypes will provide mechanistic insights into their diverse pathobiology. Here, we employed single-cell RNA sequencing (scRNA-seq) to develop benign and malignant renal cell atlases. Using a random forest model trained on this cell atlas, we predicted the putative cell of origin for more than 10 RCC subtypes. scRNA-seq also revealed several attributes of the tumor microenvironment in the most common subtype of kidney cancer, clear cell RCC (ccRCC). We elucidated an active role for tumor epithelia in promoting immune cell infiltration, potentially explaining why ccRCC responds to immune checkpoint inhibitors, despite having a low neoantigen burden. In addition, we characterized an association between high endothelial cell types and lack of response to immunotherapy in ccRCC. Taken together, these single-cell analyses of benign kidney and RCC provide insight into the putative cell of origin for RCC subtypes and highlight the important role of the tumor microenvironment in influencing ccRCC biology and response to therapy.

The Role of Artificial Intelligence in the Diagnosis and Prognosis of Renal Cell Tumors

The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.

NDUFA4L2 in smooth muscle promotes vascular remodeling in hypoxic pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is characterized by a progressive increase in pulmonary vascular resistance and obliterative pulmonary vascular remodelling (PVR). The imbalance between the proliferation and apoptosis of pulmonary artery smooth muscle cells (PASMCs) is an important cause of PVR leading to PAH. Mitochondria play a key role in the production of hypoxia-induced pulmonary hypertension (HPH). However, there are still many issues worth studying in depth. In this study, we demonstrated that NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4 like 2 (NDUFA4L2) was a proliferation factor and increased in vivo and in vitro through various molecular biology experiments. HIF-1α was an upstream target of NDUFA4L2. The plasma levels of 4-hydroxynonene (4-HNE) were increased both in PAH patients and hypoxic PAH model rats. Knockdown of NDUFA4L2 decreased the levels of malondialdehyde (MDA) and 4-HNE in human PASMCs in hypoxia. Elevated MDA and 4-HNE levels might be associated with excessive ROS generation and increased expression of 5-lipoxygenase (5-LO) in hypoxia, but this effect was blocked by siNDUFA4L2. Further research found that p38-5-LO was a downstream signalling pathway of PASMCs proliferation induced by NDUFA4L2. Up-regulated NDUFA4L2 plays a critical role in the development of HPH, which mediates ROS production and proliferation of PASMCs, suggesting NDUFA4L2 as a potential new therapeutic target for PAH.

c-KIT-ERK1/2 signaling activated ELK1 and upregulated carcinoembryonic antigen expression to promote colorectal cancer progression

Carcinoembryonic antigen (CEA) is highly expressed in embryo and colorectal cancer (CRC) and has been widely used as a marker for CRC. Emerging evidence has demonstrated that elevated CEA levels promote CRC progression. However, the mechanism of the increased CEA expression in patients with primary and recurrent CRC is still an open question. In this study, we showed that c‐KIT, ELK1, and CEA were hyperexpressed in patients with CRC, especially patients with recurrent disease. From bioinformatics analysis, we picked ELK1 as a candidate transcription factor (TF) for CEA; the binding site of ELK1 within the CEA promoter was confirmed by chromatin immunoprecipitation and dual luciferase reporter assays. Overexpression of ELK1 increased CEA expression in vitro, while knockdown of ELK1 decreased CEA. Upregulated ELK1 promoted the adhesion, migration, and invasion of CRC cells, however knockdown of CEA blocked the activities of ELK1‐overexpressed CRC cells. Furthermore, we explored the role of c‐KIT‐ERK1/2 signaling in activation of ELK1. Blocking c‐KIT signaling using Imatinib or ISCK03 reduced p‐ELK1 expression and consequently decreased CEA levels in CRC cells, as did blocking the ERK1/2 pathway by U0126. Compared with wild type littermates, the c‐kit loss‐of‐functional Wads^m/m mice showed lowered c‐KIT, ELK1, and CEA expression. In conclusion, our study revealed that ELK1, which was activated by c‐KIT‐ERK1/2 signaling, was a key TF for CEA expression. Blocking ELK1 or its upstream signaling could be an alternative way to decelerate CRC progression. Besides being a biomarker for CRC, CEA could be used for guiding targeted therapy.

NDUFA4L2 Regulated by HIF-1α Promotes Metastasis and Epithelial-Mesenchymal Transition of Osteosarcoma Cells Through Inhibiting ROS Production

Osteosarcoma (OS) accounts for a large proportion of the types of bone tumors that are newly diagnosed, and is a relatively common bone tumor. However, there are still no effective treatments for this affliction. One interesting avenue is related to the mitochondrial NDUFA4L2 protein, which is encoded by the nuclear gene and is known to be a critical mediator in the regulation of cell survival. Thus, in this study, we aimed to investigate the effect of NDUFA4L2 upon the metastasis and epithelial–mesenchymal transition of OS. We found that NDUFA4L2 protein expression was upregulated in hypoxic conditions. We also used 2-ME and DMOG, which are HIF-1α inhibitors and agonists, respectively, to assess the effects related to decreasing or increasing HIF-1α expression. 2-ME caused a significant decrease of NDUFA4L2 expression and DMOG had the opposite effect. It was obvious that down-regulation of NDUFA4L2 had a direct interaction with the apoptosis of OS cells. Western blotting, wound healing analyses, Transwell invasion assays, and colony formation assays all indicated and supported the conclusion that NDUFA4L2 promoted OS cell migration, invasion, proliferation, and the epithelial–mesenchymal transition. During experiments, we incidentally discovered that autophagy and the ROS inhibitor could be used to facilitate the rescuing of tumor cells whose NDUFA4L2 was knocked down. Our findings will help to further elucidate the dynamics underlying the mechanism of OS cells and have provided a novel therapeutic target for the treatment of OS.

Evaluating the clinical significance of SHMT2 and its co-expressed gene in human kidney cancer

Background

Kidney cancer is one of the most common cancers in the world. It is necessary to clarify its underlying mechanism and find its prognostic biomarkers. Current studies showed that SHMT2 may be participated in several kinds of cancer.

Methods

Our studies investigated the expression of SHMT2 in kidney cancer by Oncomine, Human Protein Atlas database and ULCAN database. Meanwhile, we found its co-expression gene by cBioPortal online tool and validated their relationship in A498 and ACHN cells by cell transfection, western blot and qRT-PCR. Besides these, we also explored their prognostic values via the Kaplan–Meier plotter database in different types of kidney cancer patients.

Results

SHMT2 was found to be increased in 7 kidney cancer datasets, compared to normal renal tissues. For the cancer stages, ages and races, there existed significant difference in the expression of SHMT2 among different groups by mining of the UALCAN database. High SHMT2 expression is associated with poor overall survival in patients with kidney cancer. Among all co-expressed genes, NDUFA4L2 and SHMT2 had a high co-expression efficient. SHMT2 overexpression led to the increased expression of NDUFA4L2 at both mRNA and protein levels. Like SHMT2, overexpressed NDUFA4L2 also was associated with worse overall survival in patients with kidney cancer.

Conclusion

Based on above results, overexpressed SHMT2 and its co-expressed gene NDUFA4L2 were all correlated with the prognosis in kidney cancer. The present study might be benefit for better understanding the clinical significance of SHMT2 and provided a potential therapeutic target for kidney cancer in future.

Macrophage HIF-1α Is an Independent Prognostic Indicator in Kidney Cancer

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is frequently associated with inactivation of the von Hippel-Lindau tumor suppressor, resulting in activation of HIF-1α and HIF-2α. The current paradigm, established using mechanistic cell-based studies, supports a tumor promoting role for HIF-2α, and a tumor suppressor role for HIF-1α. However, few studies have comprehensively examined the clinical relevance of this paradigm. Furthermore, the hypoxia-associated factor (HAF), which regulates the HIFs, has not been comprehensively evaluated in ccRCC.

EXPERIMENTAL DESIGN

To assess the involvement of HAF/HIFs in ccRCC, we analyzed their relationship to tumor grade/stage/outcome using tissue from 380 patients, and validated these associations using tissue from 72 additional patients and a further 57 patients treated with antiangiogenic therapy for associations with response. Further characterization was performed using single-cell mRNA sequencing (scRNA-seq), RNA-in situ hybridization (RNA-ISH), and IHC.

RESULTS

HIF-1α was primarily expressed in tumor-associated macrophages (TAMs), whereas HIF-2α and HAF were expressed primarily in tumor cells. TAM-associated HIF-1α was significantly associated with high tumor grade and increased metastasis and was independently associated with decreased overall survival. Furthermore, elevated TAM HIF-1α was significantly associated with resistance to antiangiogenic therapy. In contrast, high HAF or HIF-2α were associated with low grade, decreased metastasis, and increased overall survival. scRNA-seq, RNA-ISH, and Western blotting confirmed the expression of HIF-1α in M2-polarized CD163-expressing TAMs.

CONCLUSIONS

These findings highlight a potential role of TAM HIF-1α in ccRCC progression and support the reevaluation of HIF-1α as a therapeutic target and marker of disease progression.

m6A RNA modification modulates gene expression and cancer-related pathways in clear cell renal cell carcinoma

Aim: To systematically profile the global m⁶A modification pattern in clear cell renal cell carcinoma (ccRCC). Methods: m⁶A modification patterns in ccRCC and normal tissues were described via m⁶A sequencing and RNA sequencing, followed by bioinformatics analysis. m⁶A-related RNAs were immunoprecipitated and validated by quantitative real-time PCR (qPCR). Results: In total, 6919 new m⁶A peaks appeared with the disappearance of 5020 peaks in ccRCC samples. The unique m⁶A-related genes in ccRCC were associated with cancer-related pathways. We identified differentially expressed mRNA transcripts with hyper-methylated or hypo-methylated m⁶A peaks in ccRCC. Conclusion: This study presented the first m⁶A transcriptome-wide map of human ccRCC, which may shed lights on possible mechanisms of m⁶A-mediated gene expression regulation.

Hypertonicity-Affected Genes Are Differentially Expressed in Clear Cell Renal Cell Carcinoma and Correlate with Cancer-Specific Survival

The heterogeneity of renal cell carcinoma (RCC) subtypes reflects the cell type of origin in the nephron, with consequences for therapy and prognosis. The transcriptional cues that determine segment-specific gene expression patterns are poorly understood. We recently showed that hypertonicity in the renal medulla regulates nephron-specific gene expression. Here, we analyzed a set of 223 genes, which were identified in the present study by RNA-Seq to be differentially expressed by hypertonicity, for the prediction of cancer-specific survival (CSS). Cluster analyses of these genes showed discrimination between tumor and non-tumor samples of clear cell RCC (ccRCC). Refinement of this gene signature to a four-gene score (OSM score) through statistical analyses enabled prediction of CSS in ccRCC patients of The Cancer Genome Atlas (TCGA) (n = 436) in univariate (HR = 4.1; 95% CI: 2.78−6.07; p = 4.39 × 10⁻¹³), and multivariate analyses including primary tumor (T); regional lymph node (N); distant metastasis (M); grading (G)(p = 2.3 × 10⁻⁵). The OSM score could be validated in an independent ccRCC study (n = 52) in univariate (HR = 1.29; 95% CI = 1.05–1.59; p = 0.011) and multivariate analyses (p = 0.016). Cell culture experiments using RCC cell lines demonstrated that the expression of the tumor suppressor ELF5 could be restored by hypertonicity. The innovation of our novel gene signature is that these genes are physiologically regulated only by hypertonicity, thereby providing the possibility to be targeted for therapy.

MiR-326: Promising Biomarker for Cancer

MicroRNAs (miRNAs) are small non-coding and highly conserved RNAs that act in biological processes including cell proliferation, invasion, apoptosis, metabolism, signal transduction, and tumorigenesis. The previously identified miRNA-326 (miR-326) has been reported to participate in cellular apoptosis, tumor growth, cell invasion, embryonic development, immunomodulation, chemotherapy resistance, and oncogenesis. This review presents a detailed overview of what is known about the effects of miR-326 on cell invasion, metastasis, drug resistance, proliferation, apoptosis, and its involvement in signaling pathways.

Efficient proximal gradient algorithm for inference of differential gene networks

Background

Gene networks in living cells can change depending on various conditions such as caused by different environments, tissue types, disease states, and development stages. Identifying the differential changes in gene networks is very important to understand molecular basis of various biological process. While existing algorithms can be used to infer two gene networks separately from gene expression data under two different conditions, and then to identify network changes, such an approach does not exploit the similarity between two gene networks, and it is thus suboptimal. A desirable approach would be clearly to infer two gene networks jointly, which can yield improved estimates of network changes.

Results

In this paper, we developed a proximal gradient algorithm for differential network (ProGAdNet) inference, that jointly infers two gene networks under different conditions and then identifies changes in the network structure. Computer simulations demonstrated that our ProGAdNet outperformed existing algorithms in terms of inference accuracy, and was much faster than a similar approach for joint inference of gene networks. Gene expression data of breast tumors and normal tissues in the TCGA database were analyzed with our ProGAdNet, and revealed that 268 genes were involved in the changed network edges. Gene set enrichment analysis identified a significant number of gene sets related to breast cancer or other types of cancer that are enriched in this set of 268 genes. Network analysis of the kidney cancer data in the TCGA database with ProGAdNet also identified a set of genes involved in network changes, and the majority of the top genes identified have been reported in the literature to be implicated in kidney cancer. These results corroborated that the gene sets identified by ProGAdNet were very informative about the cancer disease status. A software package implementing the ProGAdNet, computer simulations, and real data analysis is available as Additional file 1.

Conclusion

With its superior performance over existing algorithms, ProGAdNet provides a valuable tool for finding changes in gene networks, which may aid the discovery of gene-gene interactions changed under different conditions.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2749-x) contains supplementary material, which is available to authorized users.

Mitochondrial NDUFA4L2 protein promotes the vitality of lung cancer cells by repressing oxidative stress

BACKGROUND

Non-small cell lung cancer (NSCLC) accounts for a significant proportion of cancer-related deaths and lacks an effective treatment strategy. NSCLC tissues are generally found in a low oxygen environment. The NDUFA4L2 protein, located in the mitochondria, is encoded by the nucleus genome and is considered a crucial mediator that regulates cell survival. A better understanding of the mechanism of NDUFA4L2 in NSCLC survival in hypoxic environments is essential to design new therapeutic methods.

METHODS

Twenty NSCLC and corresponding paired non-tumorous lung tissue samples were collected. NSCLC cell lines were cultured in hypoxic conditions to investigate the mechanism of NDUFA4L2 in NSCLC. The role of NDUFA4L2 was confirmed by using Western blotting, reactive oxygen species measurement, flow cytometry, immunofluorescence analysis, and wound healing and colony formation assays.

RESULTS

The expression of HIF-1α and mitochondrial NDUFA4L2 increased in NSCLC cell lines cultured in hypoxic conditions (1% O₂ ). NDUFA4L2 was drastically overexpressed in human NSCLC tissues and cell lines cultured in hypoxic conditions. HIF-1α regulated the expression of NDUFA4L2. Knockdown of NDUFA4L2 notably increased mitochondrial reactive oxygen species production, which suppressed the viability of NSCLC.

CONCLUSION

In conclusion, overexpression of NDUFA4L2 is a key factor for maintaining NSCLC growth, suggesting that mitochondrial NDUFA4L2 may be a potential target for the treatment of lung cancer.

Tanshinone I attenuates proliferation and chemoresistance of cervical cancer in a KRAS-dependent manner

Chemoresistance is a common occurrence during advanced or recurrent cervical cancer therapy when treated by conventional treatment, platinum-based chemotherapy. This study aimed to investigate the effect and underlying mechanism of tanshinone I on attenuating proliferation and chemoresistance of cervical cancer cells. In cervical cancer cells, cell proliferation was examined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), cell count, and soft-agar colony-formation assay. rVista analysis and luciferase reporter assay were used to explore the upstream regulator of KRAS, and the expression levels of key genes were also detected. Western blot analysis showed that tanshinone I significantly suppressed KRAS expression and inhibited AKT phosphorylation. rVista analysis and luciferase reporter assay demonstrated that ELK1 can binds directly to KRAS promoter and positively regulates KRAS expression. MTT assay showed that KRAS or ELK1 overexpression significantly attenuated the suppressive effects of tanshinone I on HeLa cells proliferation. In addition, tanshinone I recovered the cisplatin sensitivity of HeLa CR cells, whereas KRAS or ELK1 overexpression significantly inhibited this phenomenon. Our results suggested that tanshinone I had anticancer effects on cervical cancer cells via inhibiting ELK1 and downregulating KRAS-AKT axis, which subsequently suppressed the proliferation and cisplatin resistance of cervical cancer cells.

Downregulation of miR‑224‑5p in prostate cancer and its relevant molecular mechanism via TCGA, GEO database and in silico analyses

The function of the expression of microRNA (miR)-224-5p in prostate adenocarcinoma (PCa) remains to be elucidated, therefore, the present study aimed to investigate the clinical significance and potential molecular mechanism of miR-224-5p in PCa. Data on the expression of miR-224-5p in PCa were extracted from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), ArrayExpress and previous literature, and meta-analyses with standardized mean difference (SMD) and summary receiver operating characteristic (sROC) methods were performed for statistical analyses. The prospective target genes of miR-224-5p were collected by overlapping the differentially expressed mRNAs in TCGA and GEO, and target genes predicted by miRWalk2.0. Subsequently, in silico analysis was performed to examine the associated pathways of miR-224-5p in PCa. The expression of miR-224-5p was markedly lower in PCa; the overall SMD was −0.562, and overall sROC area under the curve was 0.80. In addition, Kyoto Encyclopedia of Genes and Genomes analysis revealed that the prospective target genes of miR-224-5p were largely enriched in the amino sugar and nucleotide sugar metabolism signaling pathway, and three genes [UDP-N-acetylglucosamine pyrophosphorylase 1 (UAP1), hexokinase 2 (HK2) and chitinase 1 (CHIT1)] enriched in this pathway showed higher expression (P<0.05). In addition, key genes in the protein-protein interaction network analysis [DNA topoisomerase 2-α (TOP2A), ATP citrate lyase (ACLY) and ribonucleotide reductase regulatory subunit M2 (RRM2)] exhibited significantly increased expression (P<0.05). The results suggested that the downregulated expression of miR-224-5p may be associated with the clinical progression and prognosis of PCa. Furthermore, miR-224-5p likely exerts its effects by targeting genes, including UAP1, HK2, CHIT1, TOP2A, ACLY and RRM2. However, in vivo and in vitro experiments are required to confirm these findings.

Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors

Messenger RNA encodes cellular function and phenotype. In the context of human cancer, it defines the identities of malignant cells and the diversity of tumor tissue. We studied 72,501 single-cell transcriptomes of human renal tumors and normal tissue from fetal, pediatric, and adult kidneys. We matched childhood Wilms tumor with specific fetal cell types, thus providing evidence for the hypothesis that Wilms tumor cells are aberrant fetal cells. In adult renal cell carcinoma, we identified a canonical cancer transcriptome that matched a little-known subtype of proximal convoluted tubular cell. Analyses of the tumor composition defined cancer-associated normal cells and delineated a complex vascular endothelial growth factor (VEGF) signaling circuit. Our findings reveal the precise cellular identities and compositions of human kidney tumors.