Expression of N6-methyladenosine (m6A) regulators correlates with immune microenvironment characteristics and predicts prognosis in diffuse large cell lymphoma (DLBCL)

The Potential of Exosomes for Osteoporosis Treatment: A Review

As a continuous process comprising bone resorption and formation, bone remodeling, plays an essential role in maintaining the balance of bone metabolism. One type of metabolic osteopathy is osteoporosis, which is defined by low bone mass and deteriorating bone microstructure. Osteoporosis patients are more likely to experience frequent osteoporotic fractures, which makes osteoporosis prevention and treatment crucial. A growing body of research has revealed that exosomes, which are homogenous vesicles released by most cell types, play a major role in mediating a number of pathophysiological processes, including osteoporosis. Exosomes may act as a mediator in cell-to-cell communication and offer a fresh perspective on information sharing. This review discusses the characteristics of exosomes and outlines the exosomes' underlying mechanism that contributes to the onset of osteoporosis. Recent years have seen a rise in interest in the role of exosomes in osteoporosis, which has given rise to innovative therapeutic approaches for the disease prevention and management.

Comprehensive analysis of HDAC7 expression and its prognostic value in diffuse large B cell lymphoma: A review

HDAC7 loss or dysregulation may lead to B cell-based hematological malignancies. This study aimed to explore the prognostic value of HDAC7 in patients with diffuse large B cell lymphoma (DLBCL). RNA sequencing data and clinical information for HDAC7 in DLBCL were collected from the cancer genome atlas database and analyzed using R software. Paired t and Mann-Whitney U tests were used to detect differences between DLBCL and adjacent normal tissues, and the pROC software package was used to generate receiver operator characteristic curves to detect cutoff values for HDAC7. Data from paraffin-embedded specimens from the 2 groups were used for validation of external immunohistochemical staining. The tumor immunity estimation resource and integrated repository portal for tumor immune system interactions databases were used to analyze the correlation between HDAC7 and DLBCL immune cell infiltration. Survival analysis of HDAC7 in patients with DLBCL was performed using the PrognoScan database. Compared with that in normal tissues, HDAC7 mRNA was overexpressed in DLBCL. The HDAC7 immunohistochemical staining scores of stage III and IV DLBCL patients were significantly lower than those of stage I and II DLBCL patients, which was associated with shorter overall survival and disease-specific survival. In addition, the higher expression of HDAC7 may play a role in the lower level of immune infiltration in DLBCL. Downregulation of HDAC7 expression was correlated with poor prognosis and immune infiltration in DLBCL patients.

KIAA1429-mediated m6A modification of CHST11 promotes progression of diffuse large B-cell lymphoma by regulating Hippo-YAP pathway

BACKGROUND

N⁶-methyladenosine (m6A) has been shown to participate in various essential biological processes by regulating the level of target genes. However, the function of m6A modification mediated by KIAA1429 [alias virus-like m6A methyltransferase-associated protein (VIRMA)] during the progression of diffuse large B-cell lymphoma (DLBCL) remains undefined.

METHODS

The expression and clinical significance of KIAA1429 were verified by our clinical data. CRISPR/Cas9 mediated KIAA1429 deletion, and CRISPR/dCas9-VP64 for activating endogenous KIAA1429 was used to evaluate its biological function. RNA sequencing (RNA-seq), methylated RNA immunoprecipitation sequencing (MeRIP-seq), RNA immunoprecipitation (RIP) assays, luciferase activity assay, RNA stability experiments, and co-immunoprecipitation were performed to investigate the regulatory mechanism of KIAA1429 in DLBCL. Tumor xenograft models were established for in vivo experiments.

RESULTS

Dysregulated expression of m6A regulators was observed, and a novel predictive model based on m6A score was established in DLBCL. Additionally, elevated KIAA1429 expression was associated with poor prognosis of patients with DLBCL. Knockout of KIAA1429 repressed DLBCL cell proliferation, facilitated cell cycle arrest in the G2/M phase, induced apoptosis in vitro, and inhibited tumor growth in vivo. Furthermore, carbohydrate sulfotransferase 11 (CHST11) was identified as a downstream target of KIAA1429, which mediated m6A modification of CHST11 mRNA and then recruited YTHDF2 for reducing CHST11 stability and expression. Inhibition of CHST11 diminished MOB1B expression, resulting in inactivation of Hippo-YAP signaling, reprogramming the expression of Hippo target genes.

CONCLUSIONS

Our results revealed a new mechanism by which the Hippo-YAP pathway in DLBCL is inactivated by KIAA1429/YTHDF2-coupled epitranscriptional repression of CHST11, highlighting the potential of KIAA1429 as a novel predictive biomarker and therapeutic target for DLBCL progression.

METTL3 enhances the effect of YTHDF1 on NEDD1 mRNA stability by m6A modification in diffuse large B-cell lymphoma cells

AIM

Diffuse large B-cell lymphoma (DLBCL) remains the most frequent subpopulation of lymphoma, and N6-methyladenosine (m6A) was implicated in the DLBCL progression. Herein, we sought to decipher the m6A-asociated mechanism of NEDD1 in DLBCL development.

METHODS

The NEDD1 expression profile in DLBCL was assessed by quantitative real-time polymerase chain reaction (RT-qPCR) and Western blot. NEDD1 was artificially downregulated or upregulated in DLBCL cells, followed by EdU, Transwell assays and flow cytometry. The Hedgehog pathway activity was assayed by a dual-luciferase assay. The m6A methylation of NEDD1 in DLBCL was assessed by meRIP-qPCR, and the regulatory mechanism of METTL3 on NEDD1 was validated. The LDH assay was conducted to examine the impact of CD8⁺ T cells on DLBCL cells. The DLBCL cells were administrated into mice to evaluate the tumorigenic activity and ki-67 activity in tumor tissues.

RESULTS

NEDD1 was overexpressed in DLBCL. Depletion of NEDD1 inhibited the aggressiveness of SU-DHL-8 and OCI-LY1 cells, whereas overexpression of NEDD1 expedited the aggressiveness of SU-DHL-8 and OCI-LY1 cells. METTL3 promoted NEDD1 translation in an m6A-dependent manner via YTHDF1. Depletion of METTL3 inhibited SU-DHL-8 and OCI-LY1 cell activity through regulation of NEDD1. NEDD1 reversed the repressive effect of METTL3 loss on the aggressiveness of SU-DHL-8 and OCI-LY1 cells. NEDD1 activated the Hedgehog signaling to promote immune escape of DLBCL.

CONCLUSIONS

METTL3 promotes translation of NEDD1 via YTHDF1-depedndent m6A modification, thereby activating the Hedgehog signaling pathway to promote immune escape of DLBCL cells.

N6-methyladenosine in hematological malignancies: a concise review

PURPOSE OF REVIEW

Hematological malignancies are a kind of systemic cancers mostly related to abnormal differentiation of blood stem cells. Because of the poor prognosis, chemotherapy resistance and common recurrence, new mechanisms and treatment therapies are looking forward to be discovered.

RECENT FINDINGS

Over the years, epigenetic abnormalities have been known to act a key part in occurrence and development of hematological tumors. In the internal modifications on long noncoding eukaryotic mRNA, there is a common type called N6-methyladenosine that can change the expression of target genes and participate in the translation, degradation and splicing of mRNA. M6A is related to a wealth of cancers, such as HNRNPA2B1's elevation in multiple myeloma, METTLE3's elevation in acute myeloid leukemia and lung cancer. Immune cells, playing a significant role in hematological cancers, can also be regulated by m6A.

SUMMARY

In the review, we summarized the recent progress on hematological malignancies associating with m6A and immune cells, which may offer a new road for the treatment of them.

Identification of an autophagy-related gene signature for predicting prognosis and immune activity in pancreatic adenocarcinoma

Adenocarcinoma of the pancreas (PAAD) is a cancerous growth that deteriorates rapidly and has a poor prognosis. Researchers are investigating autophagy in PAAD to identify a new biomarker and treatment target. An autophagy-related gene (ARG) model for overall survival (OS) was constructed using multivariate Cox regression analyses. A cohort of the Cancer Genome Atlas (TCGA)-PAAD was used as the training group as a basis for model construction. This prediction model was validated with several external datasets. To evaluate model performance, the analysis with receiver operating characteristic curves (ROC) was performed. The Human Protein Atlas (HPA) and Cancer Cell Line Encyclopedia (CCLE) were investigated to validate the effects of ARGs expression on cancer cells. Comparing the levels of immune infiltration between high-risk and low-risk groups was finished through the use of CIBERSORT. The differentially expressed genes (DEGs) between the low-/high-risk groups were analyzed further via Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, which were used to identify potential small-molecule compounds in Connectivity Map (CMap), followed by half-maximal inhibitory concentration (IC50) examination with PANC-1 cells. The risk score was finally calculated as follows: BAK1 × 0.34 + ITGA3 × 0.38 + BAG3 × 0.35 + APOL1 × 0.26-RAB24 × 0.67519. ITGA3 and RAB24 both emerged as independent prognostic factors in multivariate Cox regression. Each PAAD cohort had a significantly shorter OS in the high-risk group than in the low-risk group. The high-risk group exhibited infiltration of several immune cell types, including naive B cells (p = 0.003), plasma cells (p = 0.044), and CD8 T cells (nearly significant, p = 0.080). Higher infiltration levels of NK cells (p = 0.025), resting macrophages (p = 0.020), and mast cells (p = 0.007) were found in the high-risk group than the low-risk group. The in vitro and in vivo expression of signature ARGs was consistent in the CCLE and HPA databases. The top 3 enriched Gene Ontology biological processes (GO-BPs) were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were MAPK, cAMP, and cell adhesion molecules. Four potential small-molecule compounds (piperacetazine, vinburnine, withaferin A and hecogenin) that target ARGs were also identified. Taking the results together, our research shows that the ARG signature may serve as a useful prognostic indicator and reveal potential therapeutic targets in patients with PAAD.

The Role of N6-Methyladenosine (m6A) Methylation Modifications in Hematological Malignancies

Simple Summary

Recently, despite the common application of various novel therapies (e.g., immunotherapy and stem cell transplantation) in hematologic tumors, hematologic malignancies remain suboptimal and have a worse prognosis due to the lack of donors and their high heterogeneity. Among them, epigenetic alterations (e.g., the abnormal modification of m⁶A) are essential to facilitate the progression of tumors and drug resistance. Our purpose in this study is to pinpoint the molecular targets of pathogenesis, as well as to analyze the oncogenic characteristics of m⁶A modifications. In this article, we, therefore, elaborate on the mechanisms of m⁶A modification and its role in normal hematopoietic regulation and malignant tumorigenesis, thus contributing to the refinement of molecularly targeted therapies.

Abstract

Epigenetics is identified as the study of heritable modifications in gene expression and regulation that do not involve DNA sequence alterations, such as DNA methylation, histone modifications, etc. Importantly, N⁶-methyladenosine (m⁶A) methylation modification is one of the most common epigenetic modifications of eukaryotic messenger RNA (mRNA), which plays a key role in various cellular processes. It can not only mediate various RNA metabolic processes such as RNA splicing, translation, and decay under the catalytic regulation of related enzymes but can also affect the normal development of bone marrow hematopoiesis by regulating the self-renewal, proliferation, and differentiation of pluripotent stem cells in the hematopoietic microenvironment of bone marrow. In recent years, numerous studies have demonstrated that m⁶A methylation modifications play an important role in the development and progression of hematologic malignancies (e.g., leukemia, lymphoma, myelodysplastic syndromes [MDS], multiple myeloma [MM], etc.). Targeting the inhibition of m⁶A-associated factors can contribute to increased susceptibility of patients with hematologic malignancies to therapeutic agents. Therefore, this review elaborates on the biological characteristics and normal hematopoietic regulatory functions of m⁶A methylation modifications and their role in the pathogenesis of hematologic malignancies.

Identification and Validation of a Prognostic Prediction Model in Diffuse Large B-Cell Lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous group with varied pathophysiological, genetic, and clinical features, accounting for approximately one-third of all lymphoma cases worldwide. Notwithstanding that unprecedented scientific progress has been achieved over the years, the survival of DLBCL patients remains low, emphasizing the need to develop novel prognostic biomarkers for early risk stratification and treatment optimization.

METHOD

In this study, we screened genes related to the overall survival (OS) of DLBCL patients in datasets GSE117556, GSE10846, and GSE31312 using univariate Cox analysis. Survival-related genes among the three datasets were screened according to the criteria: hazard ratio (HR) >1 or <1 and p-value <0.01. Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis were used to optimize and establish the final gene risk prediction model. The TCGA-NCICCR datasets and our clinical cohort were used to validate the performance of the prediction model. CIBERSORT and ssGSEA algorithms were used to estimate immune scores in the high- and low-risk groups.

RESULTS

We constructed an eight-gene prognostic signature that could reliably predict the clinical outcome in training, testing, and validation cohorts. Our prognostic signature also performed distinguished areas under the ROC curve in each dataset, respectively. After stratification based on clinical characteristics such as cell-of-origin (COO), age, eastern cooperative oncology group (ECOG) performance status, international prognostic index (IPI), stage, and MYC/BCL2 expression, the difference in OS between the high- and low-risk groups was statistically significant. Next, univariate and multivariate analyses revealed that the risk score model had a significant prediction value. Finally, a nomogram was established to visualize the prediction model. Of note, we found that the low-risk group was enriched with immune cells.

CONCLUSION

In summary, we identified an eight-gene prognostic prediction model that can effectively predict survival outcomes of patients with DLBCL and built a nomogram to visualize the perdition model. We also explored immune alterations between high- and low-risk groups.

Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.

METHODS

Autophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P<0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.

RESULTS

Risk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p<0.001), Treg cells (r=-0.31, p<0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p<0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.

CONCLUSION

Our results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.