KCNJ1 inhibits tumor proliferation and metastasis and is a prognostic factor in clear cell renal cell carcinoma

An analysis of the potential association between obstructive sleep apnea and osteoporosis from the perspective of transcriptomics and NHANES

BACKGROUND

Obstructive sleep apnea (OSA) and osteoporosis (OP) are prevalent diseases in the elderly. This study aims to reveal the clinical association between OSA and OP and explore potential crosstalk gene targets.

METHODS

Participants diagnosed with OSA in the National Health and Nutrition Examination Survey (NHANES) database (2015-2020) were included, and OP was diagnosed based on bone mineral density (BMD). We explored the association between OSA and OP, and utilized multivariate logistic regression analysis and machine learning algorithms to explore the risk factors for OP in OSA patients. Overlapping genes of comorbidity were explored using differential expression analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Random Forest (RF) methods.

RESULTS

In the OSA population, the weighted prevalence of OP was 7.0%. The OP group had more females, lower body mass index (BMI), and more low/middle-income individuals compared to the non-OP group. Female gender and lower BMI were identified as independent risk factors for OP in OSA patients. Gene expression profiling revealed 8 overlapping differentially expressed genes in OP and OSA patients. KCNJ1, NPR3 and WT1-AS were identified as shared diagnostic biomarkers or OSA and OP, all of which are associated with immune cell infiltration.

CONCLUSION

This study pinpointed female gender and lower BMI as OP risk factors in OSA patients, and uncovered three pivotal genes linked to OSA and OP comorbidity, offering fresh perspectives and research targets.

Endoplasmic reticulum stress in breast cancer: a predictive model for prognosis and therapy selection

Background

Breast cancer (BC) is a leading cause of mortality among women, underscoring the urgent need for improved therapeutic predictio. Developing a precise prognostic model is crucial. The role of Endoplasmic Reticulum Stress (ERS) in cancer suggests its potential as a critical factor in BC development and progression, highlighting the importance of precise prognostic models for tailored treatment strategies.

Methods

Through comprehensive analysis of ERS-related gene expression in BC, utilizing both single-cell and bulk sequencing data from varied BC subtypes, we identified eight key ERS-related genes. LASSO regression and machine learning techniques were employed to construct a prognostic model, validated across multiple datasets and compared with existing models for its predictive accuracy.

Results

The developed ERS-model categorizes BC patients into distinct risk groups with significant differences in clinical prognosis, confirmed by robust ROC, DCA, and KM analyses. The model forecasts survival rates with high precision, revealing distinct immune infiltration patterns and treatment responsiveness between risk groups. Notably, we discovered six druggable targets and validated Methotrexate and Gemcitabine as effective agents for high-risk BC treatment, based on their sensitivity profiles and potential for addressing the lack of active targets in BC.

Conclusion

Our study advances BC research by establishing a significant link between ERS and BC prognosis at both the molecular and cellular levels. By stratifying patients into risk-defined groups, we unveil disparities in immune cell infiltration and drug response, guiding personalized treatment. The identification of potential drug targets and therapeutic agents opens new avenues for targeted interventions, promising to enhance outcomes for high-risk BC patients and paving the way for personalized cancer therapy.

Screening of possible biomarkers and therapeutic targets in kidney renal clear cell carcinoma: Evidence from bioinformatic analysis

Renal cell carcinoma (RCC), as one of the most common urological malignancies, has many histologic and molecular subtypes, among which clear cell renal cell carcinoma (ccRCC) is one of the most common causes of tumor-related deaths. However, the molecular mechanism of ccRCC remains unclear. In order to identify the candidate genes that may exist in the occurrence and development of ccRCC, microarray datasets GSE6344, GSE16441, GSE36895, GSE53757 and GSE76351 had been downloaded from Gene Expression Omnibus (GEO) database. Apart from that, the differentially expressed genes (DEGs) were screened through Bioinformatics & Evolutionary Genomics. In addition, the protein-protein interaction network (PPI) was constructed, and the module analysis was performed using STRING and Cytoscape. By virtue of DAVID online database, GO/KEGG enrichment analysis of DEGs was performed. Consequently, a total of 118 DEGs were screened, including 24 up-regulated genes and 94 down-regulated genes. The plug-in MCODE of Cytoscape was adopted to analyze the most significant modules of DEGs. What’s more, the genes with degree greater than 10 in DEGs were selected as the hub genes. The overall survival (OS) and disease progression free survival (DFS) of 9 hub genes were analyzed through GEPIA2 online platform. As shown by the survival analysis, SLC34A1, SLC12A3, SLC12A1, PLG, and ENO2 were closely related to the OS of ccRCC, whereas SLC34A1 and LOX were closely related to DFS. Among 11 SLC members, 6 SLC members were highly expressed in non-cancerous tissues (SLC5A2, SLC12A1, SLC12A3, SLC34A1, SLC34A2, SLC34A3). Besides, SLC12A5 and SLC12A7 were highly expressed in ccRCC. Furthermore, SLC12A1-A7, SLC34A1 and SLC34A3 were closely related to OS, whereas SLC12A2/A4/A6/A7 and SLC34A1/A3 were closely related to DFS. In addition, 5 algorithms were used to analyze hub genes, the overlapping genes were AQP2 and KCNJ1. To sum up, hub gene can help us understand the molecular mechanism of the occurrence and development of ccRCC, thereby providing a theoretical basis for the diagnosis and targeted therapy of ccRCC.

Potassium channel-related genes are a novel prognostic signature for the tumor microenvironment of renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for 80% of renal cell carcinomas (RCCs), and its morbidity and prognosis are unfavorable. Surgical resection is the first-line treatment for ccRCC, but the oncogenesis of ccRCC is very complex. With the development of high-throughput sequencing technology, it is necessary to analyze the transcriptome to determine more effective treatment methods. The tumor microenvironment (TME) is composed of tumor cells, various immune-infiltrating cells, fibroblasts, many cytokines, and catalysts. It is a complex system with a dynamic balance that plays an essential role in tumor growth, invasion, and metastasis. Previous studies have confirmed that potassium channels can affect the immune system, especially T lymphocytes that require potassium channel activation. However, the effect of potassium channels on the TME of ccRCC remains to be studied. Therefore, this study aims to construct a prognostic signature for ccRCC patients based on potassium ion channel-related genes (PCRGs), assess patient risk scores, and divide patients into high- and low-risk groups based on the cutoff value. In addition, we investigated whether there were differences in immune cell infiltration, immune activator expression, somatic mutations, and chemotherapeutic responses between the high- and low-risk groups. Our results demonstrate that the PCRG signature can accurately assess patient prognosis and the tumor microenvironment and predict chemotherapeutic responses. In summary, the PCRG signature could serve as an auxiliary tool for the precision treatment of ccRCC.

Common pathways and functional profiles reveal underlying patterns in Breast, Kidney and Lung cancers

Background

Cancer is a major health problem which presents a high heterogeneity. In this work we explore omics data from Breast, Kidney and Lung cancers at different levels as signalling pathways, functions and miRNAs, as part of the CAMDA 2019 Hi-Res Cancer Data Integration Challenge. Our goal is to find common functional patterns which give rise to the generic microenvironment in these cancers and contribute to a better understanding of cancer pathogenesis and a possible clinical translation down further studies.

Results

After a tumor versus normal tissue comparison of the signaling pathways and cell functions, we found 828 subpathways, 912 Gene Ontology terms and 91 Uniprot keywords commonly significant to the three studied tumors. Such features interestingly show the power to classify tumor samples into subgroups with different survival times, and predict tumor state and tissue of origin through machine learning techniques. We also found cancer-specific alternative activation subpathways, such as the ones activating STAT5A in ErbB signaling pathway. miRNAs evaluation show the role of miRNAs, such as mir-184 and mir-206, as regulators of many cancer pathways and their value in prognoses.

Conclusions

The study of the common functional and pathway activities of different cancers is an interesting approach to understand molecular mechanisms of the tumoral process regardless of their tissue of origin. The existence of platforms as the CAMDA challenges provide the opportunity to share knowledge and improve future scientific research and clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13062-021-00293-8.

Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood

BACKGROUND

DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development.

METHODS

In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status.

RESULTS

We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls.

CONCLUSION

The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.

pH-Channeling in Cancer: How pH-Dependence of Cation Channels Shapes Cancer Pathophysiology

Tissue acidosis plays a pivotal role in tumor progression: in particular, interstitial acidosis promotes tumor cell invasion, and is a major contributor to the dysregulation of tumor immunity and tumor stromal cells. The cell membrane and integral membrane proteins commonly act as important sensors and transducers of altered pH. Cell adhesion molecules and cation channels are prominent membrane proteins, the majority of which is regulated by protons. The pathophysiological consequences of proton-sensitive ion channel function in cancer, however, are scarcely considered in the literature. Thus, the main focus of this review is to highlight possible events in tumor progression and tumor immunity where the pH sensitivity of cation channels could be of great importance.

Combination of the PI3K inhibitor Idelalisib with the conventional cytostatics cytarabine and dexamethasone leads to changes in pathway activation that induce anti-proliferative effects in B lymphoblastic leukaemia cell lines

BACKGROUND

The introduction of combined conventional cytostatics and pathway-specific inhibitors has opened new treatment options for several cancer types including hematologic neoplasia such as leukaemias. As the detailed understanding of the combination-induced molecular effects is often lacking, the identification of combination-induced molecular mechanisms bears significant value for the further development of interventional approaches.

METHODS

Combined application of conventional cytostatic agents (cytarabine and dexamethasone) with the PI3K-inhibitor Idelalisib was analysed on cell-biologic parameters in two acute pro-B lymphoblastic leukaemia (B-ALL) cell lines. In particular, for comparative characterisation of the molecular signatures induced by the combined and mono application, whole transcriptome sequencing was performed. Emphasis was placed on pathways and genes exclusively regulated by drug combinations.

RESULTS

Idelalisib + cytostatics combinations changed pathway activation for, e.g., "Retinoblastoma in cancer", "TGF-b signalling", "Cell cycle" and "DNA-damage response" to a greater extent than the two cytostatics alone. Analyses of the top-20 regulated genes revealed that both combinations induce characteristic gene expression changes.

CONCLUSION

A specific set of genes was exclusively deregulated by the drug combinations, matching the combination-specific anti-proliferative cell-biologic effects. The addition of Idelalisib suggests minor synergistic effects which are rather to be classified as additive.

Integrative Epigenetic and Gene Expression Analysis of Renal Tumor Progression to Metastasis

The Cancer Genome Atlas (TCGA) and other large-scale genomic data pipelines have been integral to the current understanding of the molecular events underlying renal cell carcinoma (RCC). These data networks have focused mostly on primary RCC, which often demonstrates indolent behavior. However, metastatic disease is the major cause of mortality associated with RCC and data sets examining metastatic tumors are sparse. Therefore, a more comprehensive analysis of gene expression and DNA methylome profiling of metastatic RCC in addition to primary RCC and normal kidney was performed. Integrative analysis of the methylome and transcriptome identified over 30 RCC-specific genes whose mRNA expression inversely correlated with promoter methylation, including several known targets of hypoxia inducible factors. Notably, genes encoding several metabolism-related proteins were identified as differentially regulated via methylation including hexokinase 2, aldolase C, stearoyl-CoA desaturase, and estrogen-related receptor-γ (ESRRG), which has a known role in the regulation of nuclear-encoded mitochondrial metabolism genes. Several gene expression changes could portend prognosis in the TCGA cohort. Mechanistically, ESRRG loss occurs via DNA methylation and histone repressive silencing mediated by the polycomb repressor complex 2. Restoration of ESRRG in RCC lines suppresses migratory and invasive phenotypes independently of its canonical role in mitochondrial metabolism. IMPLICATIONS: Collectively, these data provide significant insight into the biology of aggressive RCC and demonstrate a novel role for DNA methylation in the promotion of HIF signaling and invasive phenotypes in renal cancer.

Expression of KATP channels in human cervical cancer: Potential tools for diagnosis and therapy

Various ion channels, including ATP-sensitive potassium (K_ATP) channels, are expressed in cancer and have been suggested as potential tumor markers and therapeutic targets. K_ATP channels are composed of at least two types of subunit, an inwardly rectifying K⁺ channel (Kir6.x) and a sulfonylurea receptor (SUR). However, the association between K_ATP channels and cervical cancer remains elusive. The present study determined that the Kir6.2, SUR1 and SUR2 subunits are expressed in cervical cancer cell lines and/or human biopsies. The potential association of subunit expression with tumor differentiation and invasion was analyzed. The effect of the K_ATP channel blocker glibenclamide on the proliferation of cervical cancer cell lines was also studied. Five cervical cancer cell lines, two primary cultures of cervical cancer cells, one normal keratinocyte cell line and 74 human biopsies were used in the experiments. The mRNA and protein levels of the Kir6.2 subunit were assessed by reverse transcription-polymerase chain reaction and immunochemistry, respectively. Cell proliferation was evaluated by MTT assay. Kir6.2 subunit overexpression compared with control, was observed in some cervical cancer cell lines and cervical tumor tissues. Additionally, increased K_ATP channel expression was observed in high-grade, poorly differentiated and invasive human cervical cancer biopsies. Kir6.2 subunit expression was not observed in the majority of the non-cancerous cervical tissues. The effect of the K_ATP channel blocker glibenclamide on the proliferation of five different cervical cancer cell lines was studied, revealing that as Kir6.2 mRNA expression increased, the inhibitory effect of glibenclamide also increased. The results of the present study suggest, for the first time to the best of our knowledge, that the K_ATP channel subunits, Kir6.2 and SUR2, could potentially represent tools for diagnosing and treating cervical cancer.

Pan-organ transcriptome variation across 21 cancer types

It is widely accepted that some messenger RNAs are evolutionarily conserved across species, both in sequence and tissue-expression specificity. To date, however, little effort has been made to exploit the transcriptome divergence between cancer and adjacent normal tissue at the pan-organ level. In this work, a transcriptome sequencing dataset from 675 normal-tumor pairs, representing 21 solid organs in The Cancer Genome Atlas, is used to evaluate expression evolution. The results show that in most cancer types, gene expression divergence and organ-specificity are reduced in cancer tissue compared to adjacent normal tissue. Furthermore, we observe that all cancers share cell cycle dysregulation through interrogating differentially expressed protein coding genes. Meanwhile, weighted correlation network analysis is used to detect of the gene module structure variation between cancer and adjacent normal tissue. And modules consisting of tightly co-regulated genes in cancer change substantially compared with those in adjacent normal tissue. We thus assume that the destruction of a coordinated regulatory network might result in tumorigenesis and tumor progression. Our results provide new insights into the complex cancer biology and shed light on the mysterious regulation mode for cancer.