Systematical analysis reveals a strong cancer relevance of CREB1-regulated genes

The needle in the haystack: Identifying and validating common genes of depression, insomnia, and inflammation

BACKGROUND

Insomnia, inflammation, and depression are often co-occurring conditions. The mechanisms underlying these conditions remain unclear.

MATERIALS AND METHODS

We collected microarray datasets of depression and insomnia from GEO and analyzed them for differentially expressed genes (DEGs). We then overlapped the DEGs with a list of inflammatory response-related genes to identify genes associated with all three conditions. We next performed analyses of enrichment analyses, KEGG mapping, and protein-protein interaction to identify hub genes. Furthermore, we established a depression rat model with inflammation and insomnia to validate the potential genes. At last, a two-sample Mendelian randomization (MR) study was conducted to confirm the association of identified target genes with depression outcomes.

RESULTS

We obtained 32 common DEGs associated with the depression, insomnia and inflammatory, and found that the PI3K-AKT signaling pathway might be involved in the inflammatory response in insomnia and depression. CREB1, CYBB, FYN, and CCR5 were identified as targets for the next validation. In model rats, the CCR5 and PI3K-AKT pathways were significantly up-regulated, while the model group exhibited significantly lower hippocampal p-CREB protein expression. The MR study suggested a potential causal relationship between CREB1 and the risk of depression (OR = 1.11, p = 0.013).

LIMITATIONS

The identified potential genes and pathways require further laboratory and clinical evidence verification.

CONCLUSION

We identified four potential inflammatory related-genes (CREB1, CYBB, FYN, and CCR5). CREB1 may be a potential inflammatory response-related biomarker and drug target for depression and insomnia, as validated by the followed rat model and MR study.

Uncharacterized Proteins CxORFx: Subinteractome Analysis and Prognostic Significance in Cancers

Functions of about 10% of all the proteins and their associations with diseases are poorly annotated or not annotated at all. Among these proteins, there is a group of uncharacterized chromosome-specific open-reading frame genes (CxORFx) from the 'Tdark' category. The aim of the work was to reveal associations of CxORFx gene expression and ORF proteins' subinteractomes with cancer-driven cellular processes and molecular pathways. We performed systems biology and bioinformatic analysis of 219 differentially expressed CxORFx genes in cancers, an estimation of prognostic significance of novel transcriptomic signatures and analysis of subinteractome composition using several web servers (GEPIA2, KMplotter, ROC-plotter, TIMER, cBioPortal, DepMap, EnrichR, PepPSy, cProSite, WebGestalt, CancerGeneNet, PathwAX II and FunCoup). The subinteractome of each ORF protein was revealed using ten different data sources on physical protein-protein interactions (PPIs) to obtain representative datasets for the exploration of possible cellular functions of ORF proteins through a spectrum of neighboring annotated protein partners. A total of 42 out of 219 presumably cancer-associated ORF proteins and 30 cancer-dependent binary PPIs were found. Additionally, a bibliometric analysis of 204 publications allowed us to retrieve biomedical terms related to ORF genes. In spite of recent progress in functional studies of ORF genes, the current investigations aim at finding out the prognostic value of CxORFx expression patterns in cancers. The results obtained expand the understanding of the possible functions of the poorly annotated CxORFx in the cancer context.

Network Biology-Inspired Machine Learning Features Predict Cancer Gene Targets and Reveal Target Coordinating Mechanisms

Anticipating and understanding cancers' need for specific gene activities is key for novel therapeutic development. Here we utilized DepMap, a cancer gene dependency screen, to demonstrate that machine learning combined with network biology can produce robust algorithms that both predict what genes a cancer is dependent on and what network features coordinate such gene dependencies. Using network topology and biological annotations, we constructed four groups of novel engineered machine learning features that produced high accuracies when predicting binary gene dependencies. We found that in all examined cancer types, F1 scores were greater than 0.90, and model accuracy remained robust under multiple hyperparameter tests. We then deconstructed these models to identify tumor type-specific coordinators of gene dependency and identified that in certain cancers, such as thyroid and kidney, tumors' dependencies are highly predicted by gene connectivity. In contrast, other histologies relied on pathway-based features such as lung, where gene dependencies were highly predictive by associations with cell death pathway genes. In sum, we show that biologically informed network features can be a valuable and robust addition to predictive pharmacology models while simultaneously providing mechanistic insights.

ZNRF2 as an oncogene is transcriptionally regulated by CREB1 in breast cancer models

E3 ubiquitin ligase Zinc and Ring Finger 2 (ZNRF2) has been demonstrated to be engaged in the development of multiple cancers. Nevertheless, the function of ZNRF2 in breast cancer (BC) still unclear. In this work, we firstly analyzed the differentially expressed genes in BC by bioinformatics and found that ZNRF2 was highly expressed in BC. Consistently, we further confirmed that ZNRF2 was upregulated in BC tissues compared with adjacent normal tissues, and this was positively correlated with the poor prognosis and the higher pathological grades of patients with BC. Functional assays performed on HCC1937 and MCF-7 cells indicated that silencing of ZNRF2 suppressed cell proliferation, as evidenced by the decrease in the expression of cyclin A, PCNA and cyclin D1. Flow cytometry and Hoechst staining showed that knockdown of ZNRF2 induced cell apoptosis, which was verified by the upregulation of apoptosis genes such as Bax, cleaved PARP and Bim. ZNRF2 knockdown also inhibited in vivo tumor growth. But, instead, ZNRF2-overexpressed BC cells exhibited obvious malignant phenotypes. Additionally, we observed that cAMP response element binding protein 1 (CREB1) directly bound to the promoter sequence of ZNRF2 and thus activating its transcription, suggesting that ZNRF2 is transcriptionally regulated by CREB1. Additionally, ZNRF2 knockdown could reverse the proliferation-promoting action of CREB1 on BC cells, Hence, this study demonstrated that ZNRF2 might serve as a prospective therapeutic target for BC.

Targeting lactate-related cell cycle activities for cancer therapy

Lactate has long been considered as a metabolic by-product of aerobic glycolysis for cancer. However, more and more studies have shown that lactate can regulate cancer progression via multiple mechanisms such as cell cycle regulation, immune suppression, energy metabolism and so on. A recent discovery of lactylation attracted a lot of attention and is already a hot topic in the cancer field. In this review, we summarized the latest functions of lactate and its underlying mechanisms in cancer. We also included our analysis of protein lactylation in different rat organs and compared them with other published lactylation data. The unresolved challenges in this field were discussed, and the potential application of these new discoveries of lactate-related cell cycle activities for cancer target therapy was speculated.

Cyclic adenosine monophosphate/phosphodiesterase 4 pathway associated with immune infiltration and PD-L1 expression in lung adenocarcinoma cells

Background

The cyclic adenosine monophosphate/phosphodiesterase 4 (cAMP/PDE4) pathway is involved in inflammation and immune regulation; however, the effect of cAMP/PDE4 on immune infiltration and immune evasion in lung adenocarcinoma (LUAD) remains unclear.

Methods

CBioPortal, which is the The Cancer Genome Atlas (TCGA) online database, and the Kaplan Meier plotter were used to analyze the association between genes and the prognosis of TCGA-LUAD. Tumor Immune Estimation Resource (TIMER) was used to analyze the association between gene expression and immune infiltration. The Genecards database was used to identify the transcription factors of related genes. The lung adenocarcinoma cell line H1299 and A549 were treated with cAMP pathway drugs. Flow cytometry and qRT-PCR were used to detect the PD-L1 protein and gene expression, respectively. A one-way analysis of variance with Tukey’s post-hoc test or a Student’s t-test were used.

Results

It was found that PDE4B and CREB1, which are downstream genes of the cAMP/PDE4 axis, were differentially expressed in LUAD and adjacent tissues and are correlated with the prognosis and immune infiltration of LUAD. In the CBioPortal database, cAMP pathway genes are closely related to programmed cell death-ligand 1 (PD-L1) expression in TCGA-LUAD. The protein-protein interaction revealed that there was a direct interaction between CREB1/CREBBP, which are the downstream molecules of the cAMP/PDE4 axis, and MYC; additionally, MYC was predicted to bind to the PD-L1 transcription site and regulate PD-L1 expression. CREB1 was also predicted to transcriptionally bind to both MYC and PD-L1. These results predicted the interaction network of cAMP/PDE4/CREB1/CREBP/MYC/PD-L1, and the core factor may be related to MYC. In the cell experiment, forskolin (an adenylate cyclase activator) and zardaverine (a PDE4 inhibitor) enhance the cAMP pathway and decrease PD-L1 expression, while SQ2253 (an adenylate cyclase inhibitor) inhibits the cAMP pathway and increases PD-L1 expression of the LUAD cell lines H1299 and A549, and MYC regulation by these drugs was positively correlated with PD-L1 regulation, which verified the regulation of the cAMP/PDE4 pathway on MYC and PD-L1.

Conclusions

This study showed that the cAMP/PDE4 pathway may play an important role in PD-L1 regulation and immune infiltration in LUAD.

CircEZH2/miR-133b/IGF2BP2 aggravates colorectal cancer progression via enhancing the stability of m6A-modified CREB1 mRNA

BACKGROUND

Aberrant expression of circular RNAs (circRNAs) contributes to the initiation and progression of human malignancies, but the underlying mechanisms remain largely elusive.

METHODS

High-throughput sequencing was performed to screen aberrantly expressed circRNAs or miRNAs in colorectal cancer (CRC) and adjacent normal tissues. A series of gain- and loss-of-function studies were conducted to evaluate the biological behaviors of CRC cells. RNA pulldown, mass spectrometry, RIP, qRT-PCR, Western blot, luciferase reporter assays and MeRIP-seq analysis were further applied to dissect the detailed mechanisms.

RESULTS

Here, a novel circRNA named circEZH2 (hsa_circ_0006357) was screened out by RNA-seq in CRC tissues, whose expression is closely related to the clinicpathological characteristics and prognosis of CRC patients. Biologically, circEZH2 facilitates the proliferation and migration of CRC cells in vitro and in vivo. Mechanistically, circEZH2 interacts with m⁶A reader IGF2BP2 and blocks its ubiquitination-dependent degradation. Meanwhile, circEZH2 could serve as a sponge of miR-133b, resulting in the upregulation of IGF2BP2. Particularly, circEZH2/IGF2BP2 enhances the stability of CREB1 mRNA, thus aggravating CRC progression.

CONCLUSIONS

Our findings not only reveal the pivotal roles of circEZH2 in modulating CRC progression, but also advocate for attenuating circEZH2/miR-133b/IGF2BP2/ CREB1 regulatory axis to combat CRC.

Emerging Role of CREB in Epithelial to Mesenchymal Plasticity of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive solid malignancy with a high rate of metastasis and therapeutic resistance as its major hallmarks. Although a defining mutational event in pancreatic cancer initiation is the presence of oncogenic KRAS, more advanced PDAC lesions accumulate additional genomic alterations, including loss of tumor suppressor gene TP53. Co-occurrence of mutant KRAS and TP53 in PDAC promotes hyperactivation of cancer cell signaling pathways driving epithelial to mesenchymal plasticity (EMP). The cellular process of EMP influences the biological behavior of cancer cells by increasing their migratory and invasive properties, thus promoting metastasis. Our previous work has demonstrated that oncogenic KRAS-mediated activation of cyclic AMP response element-binding protein 1 (CREB) is one of the critical drivers of PDAC aggressiveness. The therapeutic approach of targeting this key transcription factor attenuates tumor burden in genetically engineered mouse models (GEMMs) of this disease. Herein, we discuss the significant role of CREB in perpetuating disease aggressiveness and therapeutic resistance through the EMP process. Furthermore, this review updates the therapeutic implications of targeting CREB, highlighting the challenges and emerging approaches in PDAC.