PRDM16 suppresses HIF-targeted gene expression in kidney cancer

Overexpression of PRDM16 attenuates acute kidney injury progression: genetic and pharmacological approaches

Acute kidney injury (AKI) presents as a condition marked by a sudden and rapid decrease in kidney function over a short timeframe, resulting from diverse causes. As a transcription factor, PR domain-containing 16 (PRDM16), has recently been implicated in brown fat biogenesis and heart diseases. Our recent works indicated that PRDM16 could suppress the occurrence of renal interstitial fibrosis in diabetic kidney disorder. Nonetheless, the effect and regulatory mechanism of PRDM16 in AKI remain elusive. Our study demonstrated that PRDM16 inhibited apoptosis induced by ischemic/reperfusion (I/R) in BUMPT (Boston University mouse kidney proximal tubular) cells and HK-2(Human Kidney-2) cells. Mechanistically, PRDM16 not only bound to the promoter region of S100 Calcium Binding Protein A6 (S100A6)and upregulated its expression but also interacted with its amino acids 945-949, 957-960, and 981-984 to suppress the p38MAPK and JNK axes via inhibition of PKC-η activity and mitochondrial reactive oxygen species (ROS) production. Furthermore, cisplatin- and I/R-stimulated AKI progression were ameliorated in PRDM16 proximal-tubule-specific knockin mice, whereas exacerbated in PRDM16 knockout proximal-tubule-specific mice). Moreover, we observed that formononetin ameliorated I/R- and cisplatin-triggered AKI progression in mice. Taken together, these findings reveal a novel self-protective mechanism in AKI, whereby PRDM16 regulates the S100A6/PKC-η/ROS/p38MAPK and JNK pathways to inhibit AKI progression.

Unravelling the function of prdm16 in human tumours: A comparative analysis of haematologic and solid tumours

Extensive research has shown that PR domain 16 (PRDM16) plays a critical role in adipose tissue metabolism, including processes such as browning and thermogenesis of adipocytes, beigeing of adipocytes, and adipogenic differentiation of myoblasts. These functions have been associated with diseases such as obesity and diabetes. Additionally, PRDM16 has been correlated with various other conditions, including migraines, heterochromatin abnormalities, metabolic syndrome, cardiomyopathy, sarcopenia, nonsyndromic cleft lip, and essential hypertension, among others. However, there is currently no systematic or comprehensive conclusion regarding the mechanism of PRDM16 in human tumours, including haematologic and solid tumours. The aim of this review is to provide an overview of the research progress on PRDM16 in haematologic and solid tumours by incorporating recent literature findings. Furthermore, we explore the prospects of PRDM16 in the precise diagnosis and treatment of human haematologic and solid tumours.

Integrative analysis of nanopore direct RNA sequencing data reveals a role of PUS7-dependent pseudouridylation in regulation of m 6 A and m 5 C modifications

Understanding the interactions between different RNA modifications is essential for unraveling their biological functions. Here, we report NanoPsiPy, a computational pipeline that employs nanopore direct RNA sequencing to identify pseudouridine (Ψ) sites and quantify their levels at single-nucleotide resolution. We validated NanoPsiPy by transcriptome-wide profiling of PUS7-dependent Ψ sites in poly-A RNA and rRNA. NanoPsiPy leverages Ψ-induced U-to-C basecalling errors in nanopore sequencing data, allowing detection of both low and high stoichiometric Ψ sites. We identified 8,624 PUS7-dependent Ψ sites in 1,246 mRNAs encoding proteins associated with ribosome biogenesis, translation, and energy metabolism. Importantly, integrative analysis revealed that PUS7 knockdown increases global mRNA N 6 -methyladenosine (m 6 A) and 5-methylcytosine (m 5 C) levels, suggesting an antagonistic relationship between Ψ and these modifications. Our study underscores the potential of nanopore direct RNA sequencing in revealing the co-regulation of RNA modifications and the capacity of NanoPsiPy in analyzing pseudouridylation and its impact on other RNA modifications.

Identification of a signature of histone modifiers in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.

l-2-Hydroxyglutarate remodeling of the epigenome and epitranscriptome creates a metabolic vulnerability in kidney cancer models

Tumor cells are known to undergo considerable metabolic reprogramming to meet their unique demands and drive tumor growth. At the same time, this reprogramming may come at a cost with resultant metabolic vulnerabilities. The small molecule l-2-hydroxyglutarate (l-2HG) is elevated in the most common histology of renal cancer. Similarly to other oncometabolites, l-2HG has the potential to profoundly impact gene expression. Here, we demonstrate that l-2HG remodels amino acid metabolism in renal cancer cells through combined effects on histone methylation and RNA N6-methyladenosine. The combined effects of l-2HG result in a metabolic liability that renders tumors cells reliant on exogenous serine to support proliferation, redox homeostasis, and tumor growth. In concert with these data, high-l-2HG kidney cancers demonstrate reduced expression of multiple serine biosynthetic enzymes. Collectively, our data indicate that high-l-2HG renal tumors could be specifically targeted by strategies that limit serine availability to tumors.

MECOM: a bioinformatics and experimentally identified marker for the diagnosis and prognosis of lung adenocarcinoma

Objective: We aimed to explore the clinical value of MDS1 and EVI1 complex locus (MECOM) in lung adenocarcinoma (LUAD). Methods: Bioinformatics and experimental validation confirmed MECOM expression levels in LUAD. The value of MECOM was analyzed by receiver operating characteristic (ROC) curve and Cox regression analysis. Results: Serum MECOM levels were lower in LUAD and correlated with gender, TNM stage, tumor size, lymph node metastasis and distant metastasis. The ROC curve showed that the area under the curve of MECOM was 0.804 for LUAD and, of note, could reach 0.889 for advanced LUAD; specificity was up to 90%. Conclusion: MECOM may contribute to independently identifying LUAD patients, particularly in advanced stages.

Identification of the enhancer RNAs related to tumorgenesis of pituitary neuroendocrine tumors

Background

Pituitary neuroendocrine tumors (PitNETs), which originate from the pituitary gland, account for 10%-15% of all intracranial neoplasms. Recent studies have indicated that enhancer RNAs (eRNAs) exert regulatory effects on tumor growth. However, the mechanisms underlying the eRNA-mediated tumorigenesis of PitNETs have not been elucidated.

Methods

Normal pituitary and PitNETs tissues were used to identify the differentially expressed eRNAs (DEEs). Immune gene sets and hallmarks of cancer gene sets were quantified based on single sample gene set enrichment analysis (ssGSEA) algorithm using GSVA. The perspective of immune cells among all samples was calculated by the CIBERSORT algorithm. Moreover, the regulatory network composed of key DEEs, target genes of eRNAs, hallmarks of cancer gene sets, differentially expressed TF, immune cells and immune gene sets were constructed by Pearson correlation analysis. Small molecular anti-PitNETs drugs were explored by CMap analysis and the accuracy of the study was verified by in vitro and in vivo experiments, ATAC-seq and ChIP-seq.

Results

In this study, data of 134 PitNETs and 107 non-tumorous pituitary samples were retrieved from a public database to identify differentially expressed genes. In total, 1128 differentially expressed eRNAs (DEEs) (494 upregulated eRNAs and 634 downregulated eRNAs) were identified. Next, the correlation of DEEs with cancer-related and immune-related gene signatures was examined to establish a co-expression regulatory network comprising 18 DEEs, 50 potential target genes of DEEs, 5 cancer hallmark gene sets, 2 differentially expressed transcription factors, 4 immune cell types, and 4 immune gene sets. Based on this network, the following four therapeutics for PitNETs were identified using Connectivity Map analysis: ciclopirox, bepridil, clomipramine, and alexidine. The growth-inhibitory effects of these therapeutics were validated using in vitro experiments. Ciclopirox exerted potential growth-inhibitory effects on PitNETs. Among the DEEs, GNLY, HOXB7, MRPL33, PRDM16, TCF7, and ZNF26 were determined to be potential diagnostic and therapeutic biomarkers for PitNETs.

Conclusion

This study illustrated the significant influence of eRNAs on the occurrence and development of PitNETs. By constructing the co-expression regulation network, GNLY, HOXB6, MRPL33, PRDM16, TCF7, and ZNF26 were identified as relatively significant DEEs which were considered as the novel biomarkers of diagnosis and treatment of PitNETs. This study demonstrated the roles of eRNAs in the occurrence and development of PitNETs and revealed that ciclopirox was a potential therapeutic for pituitary adenomas.

Construction and validation of a chemokine family-based signature for the prediction of prognosis and therapeutic response in colon cancer

The role of chemokines in predicting the prognosis of colon cancer has not been mentioned. Chemokines have been shown to be associated with immune cell chemotaxis and activation, so the expression of chemokine genes in tumor tissue may be related to prognosis. We used a least absolute shrinkage and selection operator (LASSO) model based on chemokine gene families to construct a model that can predict the prognosis of colon cancer patients. We divided patients into high-risk groups and low-risk groups to study the prognosis. Then, we evaluated the relationship between the different risk groups in infiltration of immune cells. It was found that there was less immune cell infiltration in the high-risk group. We conducted a functional enrichment analysis based on model stratification, and explored the biological signal pathways enriched in the high and low-risk groups, which provided ideas for studying the mechanism behind its impact on prognosis. In addition, the chemokine-related gene signature could predict the response of patients to immunotherapy and chemotherapy.

Extensive intratumor regional epigenetic heterogeneity in clear cell renal cell carcinoma targets kidney enhancers and is associated with poor outcome

BACKGROUND

Clear cell renal cell cancer (ccRCC), the 8th leading cause of cancer-related death in the US, is challenging to treat due to high level intratumoral heterogeneity (ITH) and the paucity of druggable driver mutations. CcRCC is unusual for its high frequency of epigenetic regulator mutations, such as the SETD2 histone H3 lysine 36 trimethylase (H3K36me3), and low frequency of traditional cancer driver mutations. In this work, we examined epigenetic level ITH and defined its relationships with pathologic features, aspects of tumor biology, and SETD2 mutations.

RESULTS

A multi-region sampling approach coupled with EPIC DNA methylation arrays was conducted on a cohort of normal kidney and ccRCC. ITH was assessed using DNA methylation (5mC) and CNV-based entropy and Euclidian distances. We found elevated 5mC heterogeneity and entropy in ccRCC relative to normal kidney. Variable CpGs are highly enriched in enhancer regions. Using intra-class correlation coefficient analysis, we identified CpGs that segregate tumor regions according to clinical phenotypes related to tumor aggressiveness. SETD2 wild-type tumors overall possess greater 5mC and copy number ITH than SETD2 mutant tumor regions, suggesting SETD2 loss contributes to a distinct epigenome. Finally, coupling our regional data with TCGA, we identified a 5mC signature that links regions within a primary tumor with metastatic potential.

CONCLUSION

Taken together, our results reveal marked levels of epigenetic ITH in ccRCC that are linked to clinically relevant tumor phenotypes and could translate into novel epigenetic biomarkers.

The ALDH2, IGSF9, and PRDM16 Proteins as Predictive Biomarkers for Prognosis in Breast Cancer

INTRODUCTION

ALDH2, IGSF9, and PRDM16 play crucial roles in regulating diverse cellular pathophysiologic functions. The current study was to evaluate the effect of the 3 proteins on clinicopathologic features and prognosis of patients with breast cancer.

MATERIALS AND METHODS

The formalin-fixed and paraffin-embedded tissue specimens were collected from breast cancer patients by immunohistochemistry (IHC) were analyzed.

RESULTS

Of the 216 patients enrolled, ALDH2 high expression was significantly correlated with the age (p = .040), larger tumor size (p = .001), LVI (p < .001), LNM (p < .001), advanced TNM staging (p < .001), PR (p = .027), HER2 status (p = .002), and molecular subtype (p = .003). IGSF9 low expression was significantly correlated with the LV1 (p = .024), LNM (p = .024), advanced TNM staging (p = .001). The low expression of PRDM16 was significantly correlated with age (p = .023), and LNM (p = .014). The A⁺I^-P^- expression (13.4%) were markedly correlated with lymphatic vessel invasion (LVI) (p < .001), lymph node metastasis (LNM) (p < .001), advanced TNM staging (p < .001). Furthermore, patients with A⁺I^-P^- expression had significantly advanced-stage breast cancer [stage III (72.4%) vs. (23.0%)]. Univariate and multivariate analysis identified variables (ie, larger tumor size, lymph node involvement, and A⁺I^-P^- expression) as independent prognostic factors for survival.

CONCLUSION

Our results reveal ALDH2 high expression, IGSF9 and PRDM16 low expression, A⁺I^-P^- expression was associated with advanced clinicopathological characteristics, and shorter OS and DFS in breast cancer patients. The 3 proteins may be potential prognosis markers and therapeutic targets for breast cancer patients.

PRDM16, Negatively Regulated by miR-372-3p, Suppresses Cell Proliferation and Invasion in Prostate Cancer

Prostate cancer (PCa) is one of the most prevalent malignant tumors. The alternation of microRNA (miRNA) expression is associated with prostate cancer progression, whereas its way to influence progression of prostate cancer remains elusive. The expression levels of PRDM16 mRNA and miR-372-3p in PCa cell lines were analyzed using qRT-PCR. The protein expression of PRDM16 in PCa cell lines was also analyzed using western blot. CCK-8, wound healing, and Transwell assays were applied to examine cell proliferation, migration, and invasion in prostate cancer cells, respectively. Dual-luciferase reporter assay was utilized to validate the interaction between miR-372-3p and PRDM16. In the present study, markedly decreased PRDM16 mRNA and protein expression levels were observed in prostate cancer cells. PRDM16 overexpression hampered cellular proliferation, migration, and invasion, while silencing PRDM16 had the opposite effect. Moreover, miR-372-3p could target the regulation expression of PRDM16. Rescue experiments demonstrated that upregulating miR-372-3p conspicuously restored the inhibitory effect of increased PRDM16 on cell proliferation, migration, and invasion in PCa. Overall, our study clarifies the biological role of miR-372-3p/PRDM16 axis in prostate cancer progression, which may be effective biomarkers for clinical treatment of prostate cancer.

The Role of Histone Modification in DNA Replication-Coupled Nucleosome Assembly and Cancer

Histone modification regulates replication-coupled nucleosome assembly, DNA damage repair, and gene transcription. Changes or mutations in factors involved in nucleosome assembly are closely related to the development and pathogenesis of cancer and other human diseases and are essential for maintaining genomic stability and epigenetic information transmission. In this review, we discuss the role of different types of histone posttranslational modifications in DNA replication-coupled nucleosome assembly and disease. In recent years, histone modification has been found to affect the deposition of newly synthesized histones and the repair of DNA damage, further affecting the assembly process of DNA replication-coupled nucleosomes. We summarize the role of histone modification in the nucleosome assembly process. At the same time, we review the mechanism of histone modification in cancer development and briefly describe the application of histone modification small molecule inhibitors in cancer therapy.

Genomics of Dwarfism in Italian Local Chicken Breeds

The identification of the dwarf phenotype in chicken is based on body weight, height, and shank length, leaving the differentiation between dwarf and small breeds ambiguous. The aims of the present study were to characterize the sequence variations associated with the dwarf phenotype in three Italian chicken breeds and to investigate the genes associated with their phenotype. Five hundred and forty-one chickens from 23 local breeds (from 20 to 24 animals per breed) were sampled. All animals were genotyped with the 600 K chicken SNP array. Three breeds were described as “dwarf”, namely, Mericanel della Brianza (MERI), Mugellese (MUG), and Pepoi (PPP). We compared MERI, MUG, and PPP with the four heaviest breeds in the dataset by performing genome-wide association studies. Results showed significant SNPs associated with dwarfism in the MERI and MUG breeds, which shared a candidate genomic region on chromosome 1. Due to this similarity, MERI and MUG were analyzed together as a meta-population, observing significant SNPs in the LEMD3 and HMGA2 genes, which were previously reported as being responsible for dwarfism in different species. In conclusion, MERI and MUG breeds seem to share a genetic basis of dwarfism, which differentiates them from the small PPP breed.

Long Noncoding RNA MAGI2-AS3 Represses Cell Progression in Clear Cell Renal Cell Carcinoma by Modulating the miR-629-5p/PRDM16 Axis

The objective of this study was to determine the regulatory mechanism of MAGI2-AS3 in clear cell renal cell carcinoma (ccRCC), thereby supplying a new insight for ccRCC treatment. Expression data in TCGA-KIRC were obtained. Target gene lncRNA for research was determined using expression analysis and clinical analysis. lncRNA's downstream regulatory miRNA and mRNA were predicted by bioinformatics databases. ccRCC cell malignant phenotypes were detected via CCK-8, colony formation, Transwell migration, and invasion assays. The targeting relationship between genes was assessed through dual-luciferase reporter gene analysis. Kaplan-Meier (K-M) analysis was carried out to verify the effect of MAGI2-AS3, miR-629-5p, and PRDM16 on the survival rate of ccRCC patients. MAGI2-AS3 expression in ccRCC tissue and cells was shown to be markedly decreased and its expression to continuously decline with tumor progression. MAGI2-AS3 suppresses ccRCC proliferation and migration. Dual-luciferase assay showed that MAGI2-AS3 binds miR-629-5p and that miR-629-5p binds PRDM16. In addition, functional experiments showed that MAGI2-AS3 facilitates PRDM16 expression by repressing miR-629-5p expression, thereby suppressing ccRCC cell aggression. K-M analysis showed that upregulation of either MAGI2-AS3 or PRDM16 significantly improves ccRCC patient survival, while upregulation of miR-629-5p has no significant impact. MAGI2-AS3 sponges miR-629-5p to modulate PRDM16 to mediate ccRCC development. Meanwhile, the MAGI2-AS3/miR-629-5p/PRDM16 axis, as a regulatory pathway of ccRCC progression, may be a possible therapeutic target and prognostic indicator of ccRCC.

Identifying Tumor-Associated Genes from Bilayer Networks of DNA Methylation Sites and RNAs

Network theory has attracted much attention from the biological community because of its high efficacy in identifying tumor-associated genes. However, most researchers have focused on single networks of single omics, which have less predictive power. With the available multiomics data, multilayer networks can now be used in molecular research. In this study, we achieved this with the construction of a bilayer network of DNA methylation sites and RNAs. We applied the network model to five types of tumor data to identify key genes associated with tumors. Compared with the single network, the proposed bilayer network resulted in more tumor-associated DNA methylation sites and genes, which we verified with prognostic and KEGG enrichment analyses.

PRDM1/BLIMP1 induces cancer immune evasion by modulating the USP22-SPI1-PD-L1 axis in hepatocellular carcinoma cells

Programmed death receptor-1 (PD-1) blockade have achieved some efficacy but only in a fraction of patients with hepatocellular carcinoma (HCC). Programmed cell death 1 ligand 1 (PD-L1) binds to its receptor PD1 on T cells to dampen antigen-tumor immune responses. However, the mechanisms underlying PD-L1 regulation are not fully elucidated. Herein, we identify that tumoral Prdm1 overexpression inhibits cell growth in immune-deficient mouse models. Further, tumoral Prdm1 overexpression upregulates PD-L1 levels, dampening anti-tumor immunity in vivo, and neutralizes the anti-tumor efficacy of Prdm1 overexpression in immune-competent mouse models. Mechanistically, PRDM1 enhances USP22 transcription, thus reducing SPI1 protein degradation through deubiquitination, which enhances PD-L1 transcription. Functionally, PD-1 mAb treatment reinforces the efficacy of Prdm1-overexpressing HCC immune-competent mouse models. Collectively, we demonstrate that the PRDM1-USP22-SPI1 axis regulates PD-L1 levels, resulting in infiltrated CD8⁺ T cell exhaustion. Furthermore, PRDM1 overexpression combined with PD-(L)1 mAb treatment provides a therapeutic strategy for HCC treatment.

Genes associated with diagnosis and prognosis of Burkitt lymphoma

Burkitt lymphoma (BL) is one of the most aggressive forms of non-Hodgkin's lymphomas that affect children and young adults. The expression of genes and other molecular markers during carcinogenesis can be the basis for diagnosis, prognosis and the design of new and effective drugs for the management of cancers. The aim of this study was to identify genes that can serve as prognostic and therapeutic targets for BL. We analysed RNA-seq data of BL transcriptome sequencing projects in Africa using standard RNA-seq analyses pipeline. We performed pathway enrichment analyses, protein-protein interaction networks, gene co-expression and survival analyses. Gene and pathway enrichment analyses showed that the differentially expressed genes are involved in tube development, signalling receptor binding, viral protein interaction, cell migration, external stimuli response, serine hydrolase activity and PI3K-Akt signalling pathway. Protein-protein interaction network analyses revealed the genes to be highly interconnected, whereas module analyses revealed 25 genes to possess the highest interaction score. Overall survival analyses delineated six genes (ADAMTSL4, SEMA5B, ADAMTS15, THBS2, SPON1 and THBS1) that can serve as biomarkers for prognosis for BL management.

LINC00589-dominated ceRNA networks regulate multiple chemoresistance and cancer stem cell-like properties in HER2+ breast cancer

Resistance to human epidermal growth factor receptor 2 (HER2)-targeted therapy (trastuzumab), cancer stem cell (CSC)-like properties and multiple chemoresistance often concur and intersect in breast cancer, but molecular links that may serve as effective therapeutic targets remain largely unknown. Here, we identified the long noncoding RNA, LINC00589 as a key regulatory node for concurrent intervention of these processes in breast cancer cells in vitro and in vivo. We demonstrated that the expression of LINC00589 is clinically valuable as an independent prognostic factor for discriminating trastuzumab responders. Mechanistically, LINC00589 serves as a ceRNA platform that simultaneously sponges miR-100 and miR-452 and relieves their repression of tumor suppressors, including discs large homolog 5 (DLG5) and PR/SET domain 16 (PRDM16, a transcription suppressor of mucin4), thereby exerting multiple cancer inhibitory functions and counteracting drug resistance. Collectively, our results disclose two LINC00589-initiated ceRNA networks, the LINC00589-miR-100-DLG5 and LINC00589-miR-452-PRDM16- mucin4 axes, which regulate trastuzumab resistance, CSC-like properties and multiple chemoresistance of breast cancer, thus providing potential diagnostic and prognostic markers and therapeutic targets for HER2-positive breast cancer.

The evolving view of thermogenic fat and its implications in cancer and metabolic diseases

The incidence of metabolism-related diseases like obesity and type 2 diabetes mellitus has reached pandemic levels worldwide and increased gradually. Most of them are listed on the table of high-risk factors for malignancy, and metabolic disorders systematically or locally contribute to cancer progression and poor prognosis of patients. Importantly, adipose tissue is fundamental to the occurrence and development of these metabolic disorders. White adipose tissue stores excessive energy, while thermogenic fat including brown and beige adipose tissue dissipates energy to generate heat. In addition to thermogenesis, beige and brown adipocytes also function as dynamic secretory cells and a metabolic sink of nutrients, like glucose, fatty acids, and amino acids. Accordingly, strategies that activate and expand thermogenic adipose tissue offer therapeutic promise to combat overweight, diabetes, and other metabolic disorders through increasing energy expenditure and enhancing glucose tolerance. With a better understanding of its origins and biological functions and the advances in imaging techniques detecting thermogenesis, the roles of thermogenic adipose tissue in tumors have been revealed gradually. On the one hand, enhanced browning of subcutaneous fatty tissue results in weight loss and cancer-associated cachexia. On the other hand, locally activated thermogenic adipocytes in the tumor microenvironment accelerate cancer progression by offering fuel sources and is likely to develop resistance to chemotherapy. Here, we enumerate current knowledge about the significant advances made in the origin and physiological functions of thermogenic fat. In addition, we discuss the multiple roles of thermogenic adipocytes in different tumors. Ultimately, we summarize imaging technologies for identifying thermogenic adipose tissue and pharmacologic agents via modulating thermogenesis in preclinical experiments and clinical trials.

PRDM16, negatively regulated by miR-372-3p, suppresses cell proliferation and invasion in prostate cancer

Prostate cancer (PCa) is one of the most prevalent malignant tumours. The alternation of microRNAs (miRNAs) expression is associated with prostate cancer progression, whereas its way to influence progression of prostate cancer remains elusive. The expression levels of PRDM16 mRNA and miR-372-3p in PCa cell lines were analysed using qRT-PCR. The protein expression of PRDM16 in PCa cell lines was also analysed using Western blot. CCK-8, wound healing and Transwell assays were applied to examine cell proliferation, migration, and invasion in prostate cancer cells, respectively. Dual-luciferase reporter assay was utilised to validate the interaction between miR-372-3p and PRDM16. In the present study, markedly decreased PRDM16 mRNA and protein expression levels were observed in prostate cancer cells. PRDM16 overexpression hampered cellular proliferation, migration, and invasion, while silencing PRDM16 had the opposite effect. Moreover, miR-372-3p could target the regulation expression of PRDM16. Rescue experiments demonstrated that upregulating miR-372-3p conspicuously restored the inhibitory effect of increased PRDM16 on cell proliferation, migration, and invasion in PCa. Overall, our study clarifies the biological role of miR-372-3p/PRDM16 axis in prostate cancer progression, which may be effective biomarkers for clinical treatment of prostate cancer.

Prognostic and Diagnostic Values of Semaphorin 5B and Its Correlation With Tumor-Infiltrating Immune Cells in Kidney Renal Clear-Cell Carcinoma

Background: Semaphorin 5B (SEMA5B) has been described to be involved in the development and progression of cancer. However, the potential diagnostic and prognosis roles and its correlation with tumor-infiltrating immune cells in KIRC have not been clearly reported yet. Methods: The mRNA level of SEMA5B was analyzed via the TCGA and GTEx database as well as the CCLE dataset and verified by GSE53757 and GSE40435 datasets. Meanwhile, the protein level of SEMA5B was analyzed by CPTAC and validated by HPA. The diagnostic value of SEMA5B was analyzed according to the TCGA database and validated by GSE53757, GSE46699, and GSE11024 + GSE46699 datasets. Then, the survival analysis was conducted using GEPIA2. R software (v3.6.3) was applied to investigate the relevance between SEMA5B and immune checkpoints and m6A RNA methylation regulator expression. The correlation between SEMA5B and MMRs and DNMT expression and tumor-infiltrating immune cells was explored via TIMER2. Co-expressed genes of SEMA5B were assessed by cBioPortal, and enrichment analysis was conducted by Metascape. The methylation analysis was conducted with MEXPRESS and MethSurv online tools. Gene set enrichment analysis (GSEA) was applied to annotate the biological function of SEMA5B. Results: SEMA5B was significantly upregulated at both the mRNA and protein levels in KIRC. Further analysis demonstrated that the mRNA expression of SEMA5B was significantly correlated with gender, age, T stage, pathologic stage, and histologic grade. High levels of SEMA5B were found to be a favorable prognostic factor and novel diagnostic biomarker for KIRC. SEMA5B expression was shown to be significantly associated with the abundance of immune cells in KIRC. Also, SEMA5B expression was significantly correlated with the abundance of MMR genes, DNMTs, and m6A regulators in KIRC. Enrichment analysis indicated that the co-expressed genes may involve in crosslinking in the extracellular matrix (ECM). GSEA disclosed that SYSTEMIC_LUPUS_ERYTHEMATOSUS and NABA_ECM_REGULATORS were prominently enriched in the SEMA5B low-expression phenotype. Finally, the methylation analysis demonstrated a correlation between hypermethylation of the SEMA5B gene and a poor prognosis in KIRC. Conclusion: Increased SEMA5B expression correlated with immune cell infiltration, which can be served as a favorable prognostic factor and a novel diagnostic biomarker for KIRC.

PRDM16 Regulating Adipocyte Transformation and Thermogenesis: A Promising Therapeutic Target for Obesity and Diabetes

Given that obesity and diabetes have been major public health concerns and that disease morbidities have been rising continuously, effective treatment for these diseases is urgently needed. Because adipose tissue metabolism is involved in the progression of obesity and diabetes, it might be efficient to target adipocyte metabolic pathways. Positive regulatory domain zinc finger region protein 16 (PRDM16), a transcription factor that is highly expressed in adipocytes, plays a key role in adipose tissue metabolism, such as the browning and thermogenesis of adipocytes, the beigeing of adipocytes, the adipogenic differentiation of myoblasts, and the conversion of visceral adipocytes to subcutaneous adipocytes. Furthermore, clinical and basic studies have shown that the expression of PRDM16 is associated with obesity and diabetes and that PRDM16 signaling participates in the treatment of the two diseases. For example, metformin promotes thermogenesis and alleviates obesity by activating the AMPK/αKG/PRDM16 signaling pathway; rosiglitazone alleviates obesity under the synergistic effect of PRDM16; resveratrol plays an antiobesity role by inducing the expression of PRDM16; liraglupeptide improves insulin resistance by inducing the expression of PRDM16; and mulberry leaves play an anti-inflammatory and antidiabetes role by activating the expression of brown fat cell marker genes (including PRDM16). In this review, we summarize the evidence of PRDM16 involvement in the progression of obesity and diabetes and that PRDM16 may be a promising therapy for obesity and diabetes.

MECOM/PRDM3 and PRDM16 Serve as Prognostic-Related Biomarkers and Are Correlated With Immune Cell Infiltration in Lung Adenocarcinoma

Background

The MDS1 and EVI1 complex locus (MECOM, also called PRDM3) and PR domain containing 16 (PRDM16) are two highly related zinc finger transcription factors associated with many malignancies. However, the mechanisms of MECOM and PRDM16 in prognosis and tumor immune infiltration in lung adenocarcinoma (LUAD) remain uncertain.

Methods

The Cancer Genome Atlas (TCGA), Oncomine, UALCAN, GEPIA, and TIMER databases were searched to determine the relationship between the expression of MECOM and PRDM16, clinicopathological features, immune infiltration, and prognosis in LUAD. Coexpressed genes of the two genes were investigated by CBioPortal, and the potential mechanism of MECOM- and PRDM16-related genes was elucidated by GO and KEGG analyses. STRING database was utilized to further construct the protein-protein interaction network of the coexpressed genes, and the hub genes were identified by Cytoscape. Finally, qRT-PCR was performed to identify the mRNA levels of the target genes in LUAD.

Results

mRNA levels of MECOM and PRDM16 were downregulated in LUAD (p < 0.05), and the low expression of the two genes was associated with the age, gender, smoking duration, tissue subtype, poor stage, nodal metastasis status, TP53 mutation, and prognosis in LUAD (p < 0.05). MECOM and PRDM16 were also found to be correlated with the expression of a variety of immune cell subsets and their markers. KEGG analysis showed that both of them were mainly enriched in the cell cycle, cellular senescence, DNA replication, and p53 signaling pathway. Importantly, the mRNA levels of the two genes were also found to be decreased in the clinical samples of LUAD by qRT-PCR.

Conclusion

MECOM and PRDM16 may serve as potential prognostic biomarkers which govern immune cell recruitment to LUAD.

Pan-Cancer Survey of Tumor Mass Dormancy and Underlying Mutational Processes

Tumor mass dormancy is the key intermediate step between immune surveillance and cancer progression, yet due to its transitory nature it has been difficult to capture and characterize. Little is understood of its prevalence across cancer types and of the mutational background that may favor such a state. While this balance is finely tuned internally by the equilibrium between cell proliferation and cell death, the main external factors contributing to tumor mass dormancy are immunological and angiogenic. To understand the genomic and cellular context in which tumor mass dormancy may develop, we comprehensively profiled signals of immune and angiogenic dormancy in 9,631 cancers from the Cancer Genome Atlas and linked them to tumor mutagenesis. We find evidence for immunological and angiogenic dormancy-like signals in 16.5% of bulk sequenced tumors, with a frequency of up to 33% in certain tissues. Mutations in the CASP8 and HRAS oncogenes were positively selected in dormant tumors, suggesting an evolutionary pressure for controlling cell growth/apoptosis signals. By surveying the mutational damage patterns left in the genome by known cancer risk factors, we found that aging-induced mutations were relatively depleted in these tumors, while patterns of smoking and defective base excision repair were linked with increased tumor mass dormancy. Furthermore, we identified a link between APOBEC mutagenesis and dormancy, which comes in conjunction with immune exhaustion and may partly depend on the expression of the angiogenesis regulator PLG as well as interferon and chemokine signals. Tumor mass dormancy also appeared to be impaired in hypoxic conditions in the majority of cancers. The microenvironment of dormant cancers was enriched in cytotoxic and regulatory T cells, as expected, but also in macrophages and showed a reduction in inflammatory Th17 signals. Finally, tumor mass dormancy was linked with improved patient survival outcomes. Our analysis sheds light onto the complex interplay between dormancy, exhaustion, APOBEC activity and hypoxia, and sets directions for future mechanistic explorations.

Integrated Analysis of the Roles of RNA Binding Proteins and Their Prognostic Value in Clear Cell Renal Cell Carcinoma

Methods

We downloaded the RNA sequencing data of ccRCC from the Cancer Genome Atlas (TCGA) database and identified differently expressed RBPs in different tissues. In this study, we used bioinformatics to analyze the expression and prognostic value of RBPs; then, we performed functional analysis and constructed a protein interaction network for them. We also screened out some RBPs related to the prognosis of ccRCC. Finally, based on the identified RBPs, we constructed a prognostic model that can predict patients' risk of illness and survival time. Also, the data in the HPA database were used for verification.

Results

In our experiment, we obtained 539 ccRCC samples and 72 normal controls. In the subsequent analysis, 87 upregulated RBPs and 38 downregulated RBPs were obtained. In addition, 9 genes related to the prognosis of patients were selected, namely, RPL36A, THOC6, RNASE2, NOVA2, TLR3, PPARGC1A, DARS, LARS2, and U2AF1L4. We further constructed a prognostic model based on these genes and plotted the ROC curve. This ROC curve performed well in judgement and evaluation. A nomogram that can judge the patient's life span is also made.

Conclusion

In conclusion, we have identified differentially expressed RBPs in ccRCC and carried out a series of in-depth research studies, the results of which may provide ideas for the diagnosis of ccRCC and the research of new targeted drugs.

Identification of Key Functional Gene Signatures Indicative of Dedifferentiation in Papillary Thyroid Cancer

Background: Differentiated thyroid cancer (DTC) is the most common type of thyroid cancer. Many of them can relapse to dedifferentiated thyroid cancer (DDTC) and exhibit different gene expression profiles. The underlying mechanism of dedifferentiation and the involved genes or pathways remained to be investigated.

Methods: A discovery cohort obtained from patients who received surgical resection in the Fudan University Shanghai Cancer Center (FUSCC) and two validation cohorts derived from Gene Expression Omnibus (GEO) database were used to screen out differentially expressed genes in the dedifferentiation process. Weighted gene co-expression network analysis (WGCNA) was constructed to identify modules highly related to differentiation. Gene Set Enrichment Analysis (GSEA) was used to identify pathways related to differentiation, and all differentially expressed genes were grouped by function based on the GSEA and literature reviewing data. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to control the number of variables in each group. Next, we used logistic regression to build a gene signature in each group to indicate differentiation status, and we computed receiver operating characteristic (ROC) curve to evaluate the indicative performance of each signature.

Results: A total of 307 upregulated and 313 downregulated genes in poorly differentiated thyroid cancer (PDTC) compared with papillary thyroid cancer (PTC) and normal thyroid (NT) were screened out in FUSCC cohort and validated in two GEO cohorts. WGCNA of 620 differential genes yielded the seven core genes with the highest correlation with thyroid differentiation score (TDS). Furthermore, 395 genes significantly correlated with TDS in univariate logistic regression analysis were divided into 11 groups. The areas under the ROC curve (AUCs) of the gene signature of group transcription and epigenetic modification, signal and substance transport, extracellular matrix (ECM), and metabolism in the training set [The Cancer Genome Atlas (TCGA) cohort] and validation set (combined GEO cohort) were both >0.75. The gene signature based on group transcription and epigenetic modification, cilia formation and movement, and proliferation can reflect the patient's disease recurrence state.

Conclusion: The dedifferentiation of DTC is affected by a variety of mechanisms including many genes. The gene signature of group transcription and epigenetic modification, signal and substance transport, ECM, and metabolism can be used as biomarkers for DDTC.

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival

N6-methyladenosine (m6A) modification on RNA plays an important role in tumorigenesis and metastasis, which could change gene expression and even function at multiple levels such as RNA splicing, stability, translocation, and translation. In this study, we aim to conduct a comprehensive analysis on m6A RNA methylation-related genes, including m6A RNA methylation regulators and m6A RNA methylation-modified genes, in liver hepatocellular carcinoma, and their relationship with survival and clinical features. Data, which consist of the expression of widely reported m6A RNA methylation-related genes in liver hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), were analyzed by one-way ANOVA, Univariate Cox regression, a protein–protein interaction network, gene enrichment analysis, feature screening, a risk prognostic model, correlation analysis, and consensus clustering analysis. In total, 405 of the m6A RNA methylation-related genes were found based on one-way ANOVA. Among them, DNA topoisomerase 2-alpha (TOP2A), exodeoxyribonuclease 1 (EXO1), ser-ine/threonine-protein kinase Nek2 (NEK2), baculoviral IAP repeat-containing protein 5 (BIRC5), hyaluronan mediated motility receptor (HMMR), structural maintenance of chromosomes protein 4 (SMC4), bloom syndrome protein (BLM), ca-sein kinase I isoform epsilon (CSNK1E), cytoskeleton-associated protein 5 (CKAP5), and inner centromere protein (INCENP), which were m6A RNA methylation-modified genes, were recognized as the hub genes based on the protein–protein interaction analysis. The risk prognostic model showed that gender, AJCC stage, grade, T, and N were significantly different between the subgroup with the high and low risk groups. The AUC, the evaluation parameter of the prediction model which was built by RandomForest, was 0.7. Furthermore, two subgroups were divided by consensus clustering analysis, in which stage, grade, and T differed. We identified the important genes expressed significantly among two clusters, including uridine-cytidine kinase 2 (UCK2), filensin (BFSP1), tubulin-specific chaperone D (TBCD), histone-lysine N-methyltransferase PRDM16 (PRDM16), phosphorylase b ki-nase regulatory subunit alpha (PHKA2), serine/threonine-protein kinase BRSK2 (BRSK2), Arf-GAP with coiled-coil (ACAP3), general transcription factor 3C polypep-tide 2 (GTF3C2), and guanine nucleotide exchange factor MSS4 (RABIF). In our study, the m6A RNA methylation-related genes in liver hepatocellular carcinoma were analyzed systematically, including the expression, interaction, function, and prognostic values, which provided an important theoretical basis for m6A RNA methylation in liver cancer. The nine important m6A-related genes could be prognostic markers in the survival time of patients.

Identification of Novel MeCP2 Cancer-Associated Target Genes and Post-Translational Modifications

Abnormal regulation of DNA methylation and its readers has been associated with a wide range of cellular dysfunction. Disruption of the normal function of DNA methylation readers contributes to cancer progression, neurodevelopmental disorders, autoimmune disease and other pathologies. One reader of DNA methylation known to be especially important is MeCP2. It acts a bridge and connects DNA methylation with histone modifications and regulates many gene targets contributing to various diseases; however, much remains unknown about how it contributes to cancer malignancy. We and others previously described novel MeCP2 post-translational regulation. We set out to test the hypothesis that MeCP2 would regulate novel genes linked with tumorigenesis and that MeCP2 is subject to additional post-translational regulation not previously identified. Herein we report novel genes bound and regulated by MeCP2 through MeCP2 ChIP-seq and RNA-seq analyses in two breast cancer cell lines representing different breast cancer subtypes. Through genomics analyses, we localize MeCP2 to novel gene targets and further define the full range of gene targets within breast cancer cell lines. We also further examine the scope of clinical and pre-clinical lysine deacetylase inhibitors (KDACi) that regulate MeCP2 post-translationally. Through proteomics analyses, we identify many additional novel acetylation sites, nine of which are mutated in Rett Syndrome. Our study provides important new insight into downstream targets of MeCP2 and provide the first comprehensive map of novel sites of acetylation associated with both pre-clinical and FDA-approved KDACi used in the clinic. This report examines a critical reader of DNA methylation and has important implications for understanding MeCP2 regulation in cancer models and identifying novel molecular targets associated with epigenetic therapies.