H2AFZ Is a Prognostic Biomarker Correlated to TP53 Mutation and Immune Infiltration in Hepatocellular Carcinoma

The "Ins and Outs and What-Abouts" of H2A.Z: A tribute to C. David Allis

In 2023, the brilliant chromatin biologist C. David Allis passed away leaving a large void in the scientific community and broken hearts in his family and friends. With this review, we want to tribute Dave's enduring inspiration by focusing on the histone variant H2A.Z, a nucleosome component he was the first to discover as hv1 in Tetrahymena. We summarize the latest findings from the past 5 years regarding the mammalian H2A.Z histone, focusing on its deposition and eviction mechanisms, its roles in transcriptional regulation, DNA damage repair, chromatin structure organization, and embryonic development, as well as how its deregulation or mutation(s) of its histone chaperones contribute to disease development. As Dave liked to say 'Every amino acid matters'; the discovery and characterization of functionally different H2A.Z's isoforms, which vary only in three amino acids, prove him-once again-right.

Deciphering the prognostic potential of a necroptosis-related gene signature in head and neck squamous cell carcinoma: a bioinformatic analysis

Background

Necroptosis, an alternative mode of programmed cell death (PCD) that overcomes apoptosis resistance, has been implicated in the progression and drug resistance of cancer. The aim of this study is to find the biological and prognostic significance of necroptosis in patients with head and neck squamous cell carcinoma (HNSCC).

Methods

Integrated clinical datasets from The Cancer Genome Atlas (TCGA) HNSCC cohort underwent analysis. R package "DESeq2" was used to conduct differential gene expression analysis between normal and tumor tissues in the cohort, resulting in the identification of 2,172 differentially expressed genes (DEGs). A total of 159 necroptosis-related genes (NRGs) were extracted and performed a Venn analysis to identify the optimal necroptosis-related DEGs, resulting in the selection of 25 genes specifically associated with necroptosis in HNSCC. Then prognostic analyze, Cox regression analysis and prognostic model were demonstrated the ability to predict the extent of immunological infiltration in HNSCC.

Results

Among these DEGs, five genes (FADD, H2AZ1, PYGL, JAK3, and ZBP1) were found to have prognostic value (P<0.05). Then, bioinformatic analyses were conducted, and the biological and clinical significance of these five genes were demonstrated. Furthermore, Cox regression analysis was performed to develop a prognostic gene model based on these genes, which effectively classified HNSCC patients into low- or high-risk groups. The prognostic model also demonstrated the ability to predict the extent of immunological infiltration in HNSCC. Additionally, a predictive nomogram based on the clinicopathological features of these five prognostic DEGs was constructed.

Conclusions

We performed a systematic bioinformatic analysis to identify necroptosis-related prognostic genes in HNSCC patients. These genes' prognostic value was synthesized into a predictive nomogram for forecasting HNSCC progression.

A comprehensive review of immune checkpoint inhibitors for cancer treatment

Immunology-based therapies are emerging as an effective cancer treatment, using the body's immune system to target tumors. Immune checkpoints, which regulate immune responses to prevent tissue damage and autoimmunity, are often exploited by cancer cells to avoid destruction. The discovery of checkpoint proteins like PD-1/PD-L1 and CTLA-4 was pivotal in developing cancer immunotherapy. Immune checkpoint inhibitors (ICIs) have shown great success, with FDA-approved drugs like PD-1 inhibitors (Nivolumab, Pembrolizumab, Cemiplimab), PD-L1 inhibitors (Atezolizumab, Durvalumab, Avelumab), and CTLA-4 inhibitors (Ipilimumab, Tremelimumab), alongside LAG-3 inhibitor Relatlimab. Research continues on new checkpoints like TIM-3, VISTA, B7-H3, BTLA, and TIGIT. Biomarkers like PDL-1 expression, tumor mutation burden, interferon-γ presence, microbiome composition, and extracellular matrix characteristics play a crucial role in predicting responses to immunotherapy with checkpoint inhibitors. Despite their effectiveness, not all patients experience the same level of benefit, and organ-specific immune-related adverse events (irAEs) such as rash or itching, colitis, diarrhea, hyperthyroidism, and hypothyroidism may occur. Given the rapid advancements in this field and the variability in patient outcomes, there is an urgent need for a comprehensive review that consolidates the latest findings on immune checkpoint inhibitors, covering their clinical status, biomarkers, resistance mechanisms, strategies to overcome resistance, and associated adverse effects. This review aims to fill this gap by providing an analysis of the current clinical status of ICIs, emerging biomarkers, mechanisms of resistance, strategies to enhance therapeutic efficacy, and assessment of adverse effects. This review is crucial to furthering our understanding of ICIs and optimizing their application in cancer therapy.

Exploring Prognostic Gene Factors in Breast Cancer via Machine Learning

Breast cancer remains the most prevalent cancer in women. To date, its underlying molecular mechanisms have not been fully uncovered. The determination of gene factors is important to improve our understanding on breast cancer, which can correlate the specific gene expression and tumor staging. However, the knowledge in this regard is still far from complete. Thus, this study aimed to explore these knowledge gaps by analyzing existing gene expression profile data from 3149 breast cancer samples, where each sample was represented by the expression of 19,644 genes and classified into Nottingham histological grade (NHG) classes (Grade 1, 2, and 3). To this end, a machine learning-based framework was designed. First, the profile data were analyzed by using seven feature ranking algorithms to evaluate the importance of features (genes). Seven feature lists were generated, each of which sorted features in accordance with feature importance evaluated from a special aspect. Then, the incremental feature selection method was applied to each list to determine essential features for classification and building efficient classifiers. Consequently, overlapping genes, such as AURKA, CBX2, and MYBL2, were deemed as potentially related to breast cancer malignancy and prognosis, indicating that such genes were identified to be important by multiple feature ranking algorithms. In addition, the study formulated classification rules to reflect special gene expression patterns for three NHG classes. Some genes and rules were analyzed and supported by recent literature, providing new references for studying breast cancer.

The Function of H2A Histone Variants and Their Roles in Diseases

Epigenetic regulation, which is characterized by reversible and heritable genetic alterations without changing DNA sequences, has recently been increasingly studied in diseases. Histone variant regulation is an essential component of epigenetic regulation. The substitution of canonical histones by histone variants profoundly alters the local chromatin structure and modulates DNA accessibility to regulatory factors, thereby exerting a pivotal influence on gene regulation and DNA damage repair. Histone H2A variants, mainly including H2A.Z, H2A.B, macroH2A, and H2A.X, are the most abundant identified variants among all histone variants with the greatest sequence diversity. Harboring varied chromatin occupancy and structures, histone H2A variants perform distinct functions in gene transcription and DNA damage repair. They are implicated in multiple pathophysiological mechanisms and the emergence of different illnesses. Cancer, embryonic development abnormalities, neurological diseases, metabolic diseases, and heart diseases have all been linked to histone H2A variant alterations. This review focuses on the functions of H2A histone variants in mammals, including H2A.Z, H2A.B, macroH2A, and H2A.X, and their current roles in various diseases.

Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution of tumor stem cells in facilitating tumor recurrence, metastasis, and treatment resistance. Despite this, there remains a lack of established cancer stem cells (CSCs)-associated genes signatures for effectively predicting the prognosis and guiding the treatment strategies for patients diagnosed with LIHC.

METHODS

The single-cell RNA sequencing (scRNA-seq) and bulk RNA transcriptome data were obtained based on public datasets and computerized firstly using CytoTRACE package and One Class Linear Regression (OCLR) algorithm to evaluate stemness level, respectively. Then, we explored the association of stemness indicators (CytoTRACE score and stemness index, mRNAsi) with survival outcomes and clinical characteristics by combining clinical information and survival analyses. Subsequently, weighted co-expression network analysis (WGCNA) and Cox were applied to assess mRNAsi-related genes in bulk LIHC data and construct a prognostic model for LIHC patients. Single-sample gene-set enrichment analysis (ssGSEA), Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Tumor Immune Estimation Resource (TIMER) analysis were employed for immune infiltration assessment. Finally, the potential immunotherapeutic response was predicted by the Tumor Immune Dysfunction and Exclusion (TIDE), and the tumor mutation burden (TMB). Additionally, pRRophetic package was applied to evaluate the sensitivity of high and low-risk groups to common chemotherapeutic drugs.

RESULTS

A total of four genes (including STIP1, H2AFZ, BRIX1, and TUBB) associated with stemness score (CytoTRACE score and mRNAsi) were identified and constructed a risk model that could predict prognosis in LIHC patients. It was observed that high stemness cells occurred predominantly in the late stages of LIHC and that poor overall survival in LIHC patients was also associated with high mRNAsi scores. In addition, pathway analysis confirmed the biological uniqueness of the two risk groups. Personalized treatment predictions suggest that patients with a low risk benefited more from immunotherapy, while those with a high risk group may be conducive to chemotherapeutic drugs.

CONCLUSION

The current study developed a novel prognostic risk signature with genes related to CSCs, which provides novel ideas for the diagnosis, prognosis and treatment of LIHC.

Roles of Histone H2A Variants in Cancer Development, Prognosis, and Treatment

Histones are nuclear proteins essential for packaging genomic DNA and epigenetic gene regulation. Paralogs that can substitute core histones (H2A, H2B, H3, and H4), named histone variants, are constitutively expressed in a replication-independent manner throughout the cell cycle. With specific chaperones, they can be incorporated to chromatin to modify nucleosome stability by modulating interactions with nucleosomal DNA. This allows the regulation of essential fundamental cellular processes for instance, DNA damage repair, chromosomal segregation, and transcriptional regulation. Among all the histone families, histone H2A family has the largest number of histone variants reported to date. Each H2A variant has multiple functions apart from their primary role and some, even be further specialized to perform additional tasks in distinct lineages, such as testis specific shortH2A (sH2A). In the past decades, the discoveries of genetic alterations and mutations in genes encoding H2A variants in cancer had revealed variants' potentiality in driving carcinogenesis. In addition, there is growing evidence that H2A variants may act as novel prognostic indicators or biomarkers for both early cancer detection and therapeutic treatments. Nevertheless, no studies have ever concluded all identified variants in a single report. Here, in this review, we summarize the respective functions for all the 19 mammalian H2A variants and their roles in cancer biology whilst potentiality being used in clinical setting.

Integrated analysis of single-cell and bulk RNA sequencing data reveals the association between hypoxic tumor cells and exhausted T cells in predicting immune therapy response

Continuous stimulation of tumor neoantigens and various cytokines in the tumor microenvironment leads to T cell dysfunction, but the specific mechanisms by which these key factors are distributed among different cell subpopulations and how they affect patient outcomes and treatment response are incompletely characterized. By integrating single-cell and bulk sequencing data of non-small cell lung cancer patients, we constructed a clinical outcome-associated T cell exhaustion signature. We discovered a significant association between the T cell exhaustion state and tumor cell hypoxia. Hypoxic malignant cells were significantly correlated with the proportion of exhausted T cells, and they co-occurred in patients at advanced stage. By analyzing the ligand-receptor interactions between these two cell states, we observed that T cells were recruited towards tumor cells through production of chemokines such as CXCL16-CXCR6 axis and CCL3/CCL4/CCL5-CCR5 axis. Based on 15 immune checkpoint blockade (ICB)-treatment cohorts, we constructed an interaction signature that can be used to predict the response to immune checkpoint blockade therapy. Among genes composed of the signature, CXCR6 alone has similarly high prediction efficacy (Area Under Curve (AUC) = 1, 0.89 and 0.73 for GSE126044, GSE135222 and GSE93157, respectively) with the signature and thus could serve as a potential biomarker for predicting immunotherapy response. Together, we have discovered and validated a significant association between exhausted T cells and hypoxic malignant cells, elucidating key interaction factors that significantly associated with response to immunotherapy.

Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma

The H2A.Z variant histone 1 (H2AZ1) is aberrantly expressed in various tumors, correlating with an unfavorable prognosis. However, its role in hepatocellular carcinoma (HCC) remains unclear. We aimed to elucidate the pathways affected by H2AZ1 and identify promising therapeutic targets for HCC. Following bioinformatic analysis of gene expression and clinical data from The Cancer Genome Atlas and Gene Expression Omnibus database, we found 6,344 dysregulated genes related to H2AZ1 overexpression in HCC tissues (P < 0.05). We performed weighted gene co-expression network analysis to identify the gene module most related to H2AZ1. The H2AZ1-based index was further developed using Cox regression analysis, which revealed that the poor prognosis in the high H2AZ1-based index group could be attributed to elevated tumor stemness (P < 0.05). Moreover, the clinical model showed good prognostic potential (AUC > 0.7). We found that H2AZ1 knockdown led to reduced superoxide dismutase (SOD) activity, elevated malondialdehyde (MDA) levels, and increased apoptosis rate in tumor cells (P < 0.001). Thus, we developed an H2AZ1-based index model with the potential to predict the prognosis of patients with HCC. Our findings provide initial evidence that H2AZ1 overexpression plays a pivotal role in HCC initiation and progression.

The translational oscillation in oocyte and early embryo development

Translation is critical for development as transcription in the oocyte and early embryo is silenced. To illustrate the translational changes during meiosis and consecutive two mitoses of the oocyte and early embryo, we performed a genome-wide translatome analysis. Acquired data showed significant and uniform activation of key translational initiation and elongation axes specific to M-phases. Although global protein synthesis decreases in M-phases, translation initiation and elongation activity increases in a uniformly fluctuating manner, leading to qualitative changes in translation regulation via the mTOR1/4F/eEF2 axis. Overall, we have uncovered a highly dynamic and oscillatory pattern of translational reprogramming that contributes to the translational regulation of specific mRNAs with different modes of polysomal occupancy/translation that are important for oocyte and embryo developmental competence. Our results provide new insights into the regulation of gene expression during oocyte meiosis as well as the first two embryonic mitoses and show how temporal translation can be optimized. This study is the first step towards a comprehensive analysis of the molecular mechanisms that not only control translation during early development, but also regulate translation-related networks employed in the oocyte-to-embryo transition and embryonic genome activation.

Identifying genes associated with resistance to KRAS G12C inhibitors via machine learning methods

BACKGROUND

Targeted therapy has revolutionized cancer treatment, greatly improving patient outcomes and quality of life. Lung cancer, specifically non-small cell lung cancer, is frequently driven by the G12C mutation at the KRAS locus. The development of KRAS inhibitors has been a breakthrough in the field of cancer research, given the crucial role of KRAS mutations in driving tumor growth and progression. However, over half of patients with cancer bypass inhibition show limited response to treatment. The mechanisms underlying tumor cell resistance to this treatment remain poorly understood.

METHODS

To address above gap in knowledge, we conducted a study aimed to elucidate the differences between tumor cells that respond positively to KRAS (G12C) inhibitor therapy and those that do not. Specifically, we analyzed single-cell gene expression profiles from KRAS G12C-mutant tumor cell models (H358, H2122, and SW1573) treated with KRAS G12C (ARS-1620) inhibitor, which contained 4297 cells that continued to proliferate under treatment and 3315 cells that became quiescent. Each cell was represented by the expression levels on 8687 genes. We then designed an innovative machine learning based framework, incorporating seven feature ranking algorithms and four classification algorithms to identify essential genes and establish quantitative rules.

RESULTS

Our analysis identified some top-ranked genes, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5, that are known to be associated with the progression of multiple cancers.

CONCLUSION

Above genes were relevant to tumor cell resistance to targeted therapy. This study provides important insights into the molecular mechanisms underlying tumor cell resistance to KRAS inhibitor treatment.

Isoliquiritigenin suppresses the progression of malignant melanoma via targeting H2A.Z.1-E2F1 pathway

Cutaneous melanoma is one of the most prevalent tumors, and it is still a huge challenge in the current clinical treatment. Isoliquiritigenin (ISL), which is isolated from Glycyrrhiza uralensis Fisch., has been reported for its anti-tumor effect. However, the underlying mechanism and targets of ISL are still not be revealed clearly. In this study, differentiallyexpressedproteins were identified bylabel-free quantitative mass spectrometry. Two isoforms of the histone variant H2A.Z, including H2A.Z.1 and H2A.Z.2, were significantly down regulated after administration of ISL in melanoma. H2A.Z.1 was highly expressed in melanoma and correlated with poor prognosis of melanoma. The expression of H2A.Z was inhibited by ISL in a concentration-dependent manner. Overexpression of H2A.Z.1 in melanoma cell lines partly restored the repressed cell proliferation and cell cycle by ISL. Moreover, E2F1 was identified as one downstream target of H2A.Z.1, which was also highly expressed in melanoma and correlated with poor prognosis of melanoma. Furthermore, in vivo assays validated the inhibitory role of ISL in melanoma proliferation and the expression of H2A.Z.1 and E2F1.Aboveall,it is indicated that ISL inhibit melanoma proliferation via targeting H2A.Z.1-E2F1 pathway. These findings explain the anti-tumor mechanism of ISL and provide potential therapeutic targets for melanoma.

C18ORF54 promotes immune infiltration and poor prognosis as a potential biomarker for hepatocellular carcinoma

OBJECTIVE

The morbidity of hepatocellular carcinoma (HCC) is increasing annually. The aim of this study is to investigate the molecular mechanisms of upregulated genes in HCC using bioinformatic methods, so as to identify new potential biological markers.

METHODS

The Gene Expression Omnibus database (GEO database) was mined for HCC datasets, which were screened for hub genes and subjected to (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis. The hub genes were analyzed in terms of Receiver Operating Characteristic (ROC) and methylation levels. Validation of hub genes was completed through basic pathological alterations based on the protein and gene expression level of hub genes. The correlation of genes with immune infiltration in HCC was analyzed based on the database Timer 2.0, and the prognosis as well as survival of hub genes in HCC was analyzed using R studio software. Finally, we performed a gene combination drug analysis on the potential therapeutic targets in HCC.

RESULTS

Expression-up-regulated genes were screened via differential analysis, which were mainly enriched in cell cycles and DNA replication pathways. Five hub genes, BRCA1 associated RING domain 1 (BARD1), Mismatch Repair Protein (MSH2), Recombinant H2A Histone Family, Member X (H2AFX), Recombinant H2A Histone Family, Member z (H2AFZ) and Chromosome 18 Open Reading Frame 54 (C18orf54) were identified using a Protein-Protein Interaction Networks (PPI). After a comprehensive analysis of ROC curves and methylation gene mutation sites, C18orf54 was localized followed by basic experiments, so as to verify the C18orf54 upregulated in HCC. Based on the online database Timer 2.0, the immune infiltration of C18orf54 gene in HCC was analyzed, which was found to be negatively correlated with CD4+ T cells and macrophages in HCC, meanwhile a further refinement of the immune checkpoint correlation analysis revealed that C18orf54 was mainly correlated with Hepatitis A virus cellular receptor 2 (HAVCR2), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Cytotoxic T lymphocyte associate protein-4 (CTLA4). The prognosis and survival of patients with HCC expressing C18orf54 were also analyzed, and it was found that such patients had a higher incidence of adjacent liver tissue inflammation, a higher child-Pugh grade score and a higher rate of residual tumor recurrence. Similarly, the prognosis was worse in the subset of patients with C18orf54. Finally, we performed a combined genetic analysis, which suggested that cyclosporine, quercetin, testosterone and calcitriol might be effective in reducing C18orf54 mRNA expression.

CONCLUSION

C18orf54 is involved in the immune infiltration and promotes the poor prognosis of HCC, which could be a candidate biomarker for HCC.

TIGIT, a novel immune checkpoint therapy for melanoma

Melanoma is the most aggressive and deadliest type of skin cancer. In the last 10 years, immune checkpoint blockades (ICBs) including PD-1/PD-L1 and CTLA-4 inhibitor has been shown to be effective against melanoma. PD-1/PD-L1 and CTLA-4 inhibitors have shown varying degrees of drug resistance in the treatment of melanoma patients. Furthermore, the clinical benefits of ICBs are also accompanied by severe immune toxicity. Therefore, there is an urgent need to develop new immune checkpoint inhibitors to optimize melanoma therapy and reduce cytotoxicity. T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibition motif domain (TIGIT) is thought to activate inhibitory receptors in T cells, natural killer (NK) cells, and regulatory T cells (Tregs), and has become a promising target for immunotherapy. Studies have found that TIGIT can be detected in different stages of melanoma, which is closely related to the occurrence, development, and prognosis of melanoma. This review mainly describes the immunosuppressive mechanism of TIGIT and its role in antitumor immunity of melanoma, so as to provide new ideas and schemes for the clinical treatment of melanoma with targeted TIGIT.

Comprehensive analysis reveals TSEN54 as a robust prognosis biomarker and promising immune-related therapeutic target for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma represents the most common primary malignancy of all liver cancer types and its prognosis is usually unsatisfactory. TSEN54 encodes a protein constituting a subunit of the tRNA splicing endonuclease heterotetramer. Previous researches concentrated on the contribution of TSEN54 in pontocerebellar hypoplasia, but no studies have yet reported its role in HCC.

METHODS

TIMER, HCCDB, GEPIA, HPA, UALCAN, MEXPRESS, SMART, TargetScan, RNAinter, miRNet, starBase, Kaplan-Meier Plotter, cBioPortal, LinkedOmics, GSEA, TISCH, TISIDB, GeneMANIA, PDB, GSCALite were applied in this research.

RESULTS

We identified the upregulation of TSEN54 expression in HCC and related it to multiple clinicopathological features. Hypomethylation of TSEN54 was closely associated with its high expression. HCC sufferers who held high TSEN54 expression typically had shorter survival expectations. Enrichment analysis showed the involvement of TSEN54 in the cell cycle and metabolic processes. Afterward, we observed that TSEN54 expression level had a positive relationship to the infiltration level of multiple immune cells and the expression of several chemokines. We additionally identified that TSEN54 was related to the expression level of several immune checkpoints and TSEN54 was linked to several m6A-related regulators.

CONCLUSIONS

TSEN54 is a prognostic marker of HCC. TSEN54 could become a prospective candidate for HCC diagnosis and therapy.

Comparative functional analysis of macrophage phagocytosis in Dagu chickens and Wenchang chickens

Phagocytosis of macrophages constitutes a powerful barrier to innate immunity. Differences in the phagocytic function of macrophages among chicken breeds have rarely been reported, and the molecular mechanisms underlying phagocytosis remain poorly understood. This study compared functional difference of macrophages in Dagu chickens, originated in Zhuanghe, Liaoning Province, China, and Wenchang chickens, originated from Hainan Island in the South China Sea, and explored the potential molecular mechanisms by integrated analysis of mRNA expression profiles of macrophages and whole genome sequencing. Immunological parameters in peripheral blood indicated that Dagu chickens were more resistant to Salmonella challenge at 28 days old. Phagocytosis index and phagocytosis rate of macrophages displayed Dagu chickens performed a significantly higher phagocytic ability of macrophages at 14 and 28 days old. Furthermore, comparative analysis of mRNA expression profiles of macrophages of two breeds at 28 days old revealed that 1136 differentially expressed genes (DEGs), and 22 DEGs (e.g., H2AFZ, SNRPA1, CUEDC2, S100A12) were found to be hub genes regulating phagocytosis by participating in different immunological biological signaling pathways. In addition, many DEGs and hub genes were under strong differentiation in genome between two breeds, the H2AFZ gene was an intersection of DEGs and hub genes. These results provided a comprehensive functional comparison and transcriptomic profiles of macrophages in Chinese native chicken breeds, and deepened our understanding of the genetic mechanism of innate immunity.

Adipocyte-mediated epigenomic instability in human T-ALL cells is cytotoxic and phenocopied by epigenetic-modifying drugs

The world’s population with obesity is reaching pandemic levels. If current trends continue, it is predicted that there will be 1.5 billion people with obesity by 2030. This projection is alarming due to the association of obesity with numerous diseases including cancer, with recent studies demonstrating a positive association with acute myeloid leukemia (AML) and B cell acute lymphoblastic leukemia (B-ALL). Interestingly, several epidemiological studies suggest the converse relationship may exist in patients with T cell acute lymphoblastic leukemia (T-ALL). To determine the relationship between obesity and T-ALL development, we employed the diet-induced obesity (DIO) murine model and cultured human T-ALL cells in adipocyte-conditioned media (ACM), bone marrow stromal cell-conditioned media, stromal conditioned media (SCM), and unconditioned media to determine the functional impact of increased adiposity on leukemia progression. Whereas only 20% of lean mice transplanted with T-ALL cells survived longer than 3 months post-inoculation, 50%–80% of obese mice with leukemia survived over this same period. Furthermore, culturing human T-ALL cells in ACM resulted in increased histone H3 acetylation (K9/K14/K18/K23/K27) and methylation (K4me3 and K27me3) posttranslational modifications (PTMs), which preceded accelerated cell cycle progression, DNA damage, and cell death. Adipocyte-mediated epigenetic changes in human T-ALL cells were recapitulated with the H3K27 demethylase inhibitor GSK-J4 and the pan-HDAC inhibitor vorinostat. These drugs were also highly cytotoxic to human T-ALL cells at low micromolar concentrations. In summary, our data support epidemiological studies demonstrating that adiposity suppresses T-ALL pathogenesis. We present data demonstrating that T-ALL cell death in adipose-rich microenvironments is induced by epigenetic modifications, which are not tolerated by leukemia cells. Similarly, GSK-J4 and vorinostat treatment induced epigenomic instability and cytotoxicity profiles that phenocopied the responses of human T-ALL cells to ACM, which provides additional support for the use of epigenetic modifying drugs as a treatment option for T-ALL.

H2A.Z's 'social' network: functional partners of an enigmatic histone variant

The histone variant H2A.Z has been extensively studied to understand its manifold DNA-based functions. In the past years, researchers identified its specific binding partners, the 'H2A.Z interactome', that convey H2A.Z-dependent chromatin changes. Here, we summarize the latest findings regarding vertebrate H2A.Z-associated factors and focus on their roles in gene activation and repression, cell cycle regulation, (neuro)development, and tumorigenesis. Additionally, we demonstrate how protein-protein interactions and post-translational histone modifications can fine-tune the complex interplay of H2A.Z-regulated gene expression. Last, we review the most recent results on interactors of the two isoforms H2A.Z.1 and H2A.Z.2.1, which differ in only three amino acids, and focus on cancer-associated mutations of H2A and H2A.Z, which reveal fascinating insights into the functional importance of such minuscule changes.

Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

BACKGROUND

Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival.

METHODS

We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients' tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University.

RESULTS

We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC.

CONCLUSIONS

By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

A Data Science Approach for the Identification of Molecular Signatures of Aggressive Cancers

The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, kidney, prostate, and thyroid) into classes of high (H) and low (L) aggressiveness considering the TCGA data, and their correlations between Shannon entropy and 5-year overall survival (OS). Then, we used principal component analysis (PCA), a random forest classifier (RFC), and protein-protein interactions (PPI) to find the genes that correlated with aggressiveness. Using PCA, we found GRB2, CTNNB1, SKP1, CSNK2A1, PRKDC, HDAC1, YWHAZ, YWHAB, and PSMD2. Except for PSMD2, the RFC analysis showed a different list, which was CAD, PSMD14, APH1A, PSMD2, SHC1, TMEFF2, PSMD11, H2AFZ, PSMB5, and NOTCH1. Both methods use different algorithmic approaches and have different purposes, which explains the discrepancy between the two gene lists. The key genes of aggressiveness found by PCA were those that maximized the separation of H and L classes according to its third component, which represented 19% of the total variance. By contrast, RFC classified whether the RNA-seq of a tumor sample was of the H or L type. Interestingly, PPIs showed that the genes of PCA and RFC lists were connected neighbors in the PPI signaling network of WNT and cross-linked pathways.

Exploration of the Shared Gene and Molecular Mechanisms Between Endometriosis and Recurrent Pregnancy Loss

Endometriosis (EMs) is a common benign gynecological disease in women of childbearing age, which usually causes pelvic pain, secondary dysmenorrhea, and infertility. EMs has been linked to recurrent pregnancy loss (RPL) in epidemiological data. The relationship of both, however, remains unknown. The purpose of this study is to explore the underlying pathological mechanisms between EMs and RPL. We searched Gene Expression Omnibus (GEO) database to obtain omics data of EMs and RPL. Co-expression modules for EMs and RPL were investigated by using weighted gene co-expression network analysis (WGCNA). The intersections of gene modules with the strong correlation to EMs or RPL obtained by WGCNA analysis were considered as shared genes. MicroRNAs (miRNAs) and their corresponding target genes linked to EMs and RPL were found though the Human MicroRNA Disease Database (HMDD) and the miRTarbase database. Finally, we constructed miRNAs-mRNAs regulatory networks associated with the two disorders by using the intersection of previously obtained target genes and shared genes. We discovered as significant modules for EMs and RPL, respectively, by WGCNA. The energy metabolism might be the common pathogenic mechanism of EMs and RPL, according to the findings of a Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. We discovered several target genes that might be linked to these two disorders, as well as the potential mechanisms. RAB8B, GNAQ, H2AFZ, SUGT1, and LEO1 could be therapeutic candidates for RPL and EMs. The PI3K-Akt signaling pathway and platelet activation were potentially involved in the mechanisms of EM-induced RPL. Our findings for the first time revealed the underlying pathological mechanisms of EM-induced RPL and identified several useful biomarkers and potential therapeutic targets.

Spotlight on histone H2A variants: From B to X to Z

Chromatin, the functional organization of DNA with histone proteins in eukaryotic nuclei, is the tightly-regulated template for several biological processes, such as transcription, replication, DNA damage repair, chromosome stability and sister chromatid segregation. In order to achieve a reversible control of local chromatin structure and DNA accessibility, various interconnected mechanisms have evolved. One of such processes includes the deposition of functionally-diverse variants of histone proteins into nucleosomes, the building blocks of chromatin. Among core histones, the family of H2A histone variants exhibits the largest number of members and highest sequence-divergence. In this short review, we report and discuss recent discoveries concerning the biological functions of the animal histone variants H2A.B, H2A.X and H2A.Z and how dysregulation or mutation of the latter impacts the development of disease.