Histone Acetylation Regulator-Mediated Acetylation Patterns Define Tumor Malignant Pathways and Tumor Microenvironment in Hepatocellular Carcinoma

Identification of HDAC10 as a candidate oncogene in clear cell renal carcinoma that facilitates tumor proliferation and metastasis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) remains one of the most lethal urological malignancies even though a great number of improvements in diagnosis and management have achieved over the past few decades. Accumulated evidence revealed that histone deacetylases (HDACs) play vital role in cell proliferation, differentiation and apoptosis. Nevertheless, the biological functions of histone deacetylation modification related genes in ccRCC remains poorly understood.

METHOD

Bulk transcriptomic data and clinical information of ccRCC patients were obtained from the TCGA database and collected from the Chinese PLA General Hospital. A total of 36 histone deacetylation genes were selected and studied in our research. Univariate cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) analysis, and protein-protein interaction (PPI) network analysis were applied to identify key genes affecting the prognosis of ccRCC. The 'oncoPredict' algorithm was utilized for drug-sensitive analysis. Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the potential biological function. The ssGSEA algorithm was used for tumor immune microenvironment analysis. The expression levels of HDAC10 were validated by RT-PCR and immunohistochemistry (IHC). 5-ethynyl-2'-deoxyuridine (EdU assay), CCK-8 assay, cell transwell migration and invasion assay and colony formation assay were performed to detect the proliferation and invasion ability of ccRCC cells. A nomogram incorporating HDAC10 and clinicopathological characteristics was established to predict the prognosis of ccRCC patients.

RESULT

Two machine learning algorithms and PPI analysis identified four histone deacetylation genes that have a significant association with the prognosis of ccRCC, with HDAC10 being the key gene among them. HDAC10 is highly expressed in ccRCC and its high expression is associated with poor prognosis for ccRCC patients. Pathway enrichment and the experiments of EdU staining, CCK-8 assay, cell transwell migration and invasion assay and colony formation assay demonstrated that HDAC10 mediated the proliferation and metastasis of ccRCC cells and involved in reshaping the tumor microenvironment (TME) of ccRCC. A clinically reliable prognostic predictive model was established by incorporating HDAC10 and other clinicopathological characteristics ( https://nomogramhdac10.shinyapps.io/HDAC10_Nomogram/ ).

CONCLUSION

Our study found the increased expression of HDAC10 was closely associated with poor prognosis of ccRCC patients. HDAC10 showed a pro-tumorigenic effect on ccRCC and promote the proliferation and metastasis of ccRCC, which may provide new light on targeted therapy for ccRCC.

Plant responses to abiotic stress regulated by histone acetylation

In eukaryotes, histone acetylation and deacetylation play an important role in the regulation of gene expression. Histone acetylation levels are reversibly regulated by histone acetyltransferases (HATs) and histone deacetylases (HDACs). Increasing evidence highlights histone acetylation plays essential roles in the regulation of gene expression in plant response to environmental stress. In this review, we discussed the recent advance of histone acetylation in the regulation of abiotic stress responses including temperature, light, salt and drought stress. This information will contribute to our understanding of how plants adapt to environmental changes. As the mechanisms of epigenetic regulation are conserved in many plants, research in this field has potential applications in improvement of agricultural productivity.

Gene Expression Reprogramming by Citrate Supplementation Reduces HepG2 Cell Migration and Invasion

Citrate, which is obtained from oxaloacetate and acetyl-CoA by citrate synthase in mitochondria, plays a key role in both normal and cancer cell metabolism. In this work, we investigated the effect of 10 mM extracellular citrate supplementation on HepG2 cells. Gene expression reprogramming was evaluated by whole transcriptome analysis using gene set enrichment analysis (GSEA). The transcriptomic data were validated through analyzing changes in the mRNA levels of selected genes by qRT-PCR. Citrate-treated cells exhibited the statistically significant dysregulation of 3551 genes; 851 genes were upregulated and 822 genes were downregulated. GSEA identified 40 pathways affected by differentially expressed mRNAs. The most affected biological processes were related to lipid and RNA metabolism. Several genes of the cytochrome P450 family were upregulated in treated cells compared to controls, including the CYP3A5 gene, a tumor suppressor in hepatocellular carcinoma (HCC) that plays an important protective role in HCC metastasis. The citrate-induced dysregulation of cytochromes could both improve the effectiveness of chemotherapeutics used in combination and reduce the aggressiveness of tumors by diminishing cell migration and invasion.

Risk assessment model based on nucleotide metabolism-related genes highlights SLC27A2 as a potential therapeutic target in breast cancer

PURPOSE

Breast cancer (BC) is the most prevalent malignant tumor worldwide among women, with the highest incidence rate. The mechanisms underlying nucleotide metabolism on biological functions in BC remain incompletely elucidated. MATERIALS AND METHODS: We harnessed differentially expressed nucleotide metabolism-related genes from The Cancer Genome Atlas-BRCA, constructing a prognostic risk model through univariate Cox regression and LASSO regression analyses. A validation set and the GSE7390 dataset were used to validate the risk model. Clinical relevance, survival and prognosis, immune infiltration, functional enrichment, and drug sensitivity analyses were conducted.

RESULTS

Our findings identified four signature genes (DCTPP1, IFNG, SLC27A2, and MYH3) as nucleotide metabolism-related prognostic genes. Subsequently, patients were stratified into high- and low-risk groups, revealing the risk model's independence as a prognostic factor. Nomogram calibration underscored superior prediction accuracy. Gene Set Variation Analysis (GSVA) uncovered activated pathways in low-risk cohorts and mobilized pathways in high-risk cohorts. Distinctions in immune cells were noted between risk cohorts. Subsequent experiments validated that reducing SLC27A2 expression in BC cell lines or using the SLC27A2 inhibitor, Lipofermata, effectively inhibited tumor growth.

CONCLUSIONS

We pinpointed four nucleotide metabolism-related prognostic genes, demonstrating promising accuracy as a risk prediction tool for patients with BC. SLC27A2 appears to be a potential therapeutic target for BC among these genes.

Research of saccharides and related biocomplexes: A review with recent techniques and applications

Saccharides and biocompounds as saccharide (sugar) complexes have various roles and biological functions in living organisms due to modifications via nucleophilic substitution, polymerization, and complex formation reactions. Mostly, mono-, di-, oligo-, and polysaccharides are stabilized to inactive glycosides, which are formed in metabolic pathways. Natural saccharides are important in food and environmental monitoring. Glycosides with various functionalities are significant in clinical and medical research. Saccharides are often studied with the chromatographic methods of hydrophilic interaction liquid chromatography and anion exchange chromatograpy, but also with capillary electrophoresis and mass spectrometry with their on-line coupling systems. Sample preparation is important in the identification of saccharide compounds. The cases discussed here focus on bioscience, clinical, and food applications.

Comprehensive analysis of histone acetylation-related genes in glioblastoma and lower-grade gliomas: Insights into drug sensitivity, molecular subtypes, immune infiltration, and prognosis

OBJECTIVES

The purpose of this research was to study the impact of histone acetylation on glioblastoma multiforme (GBM) and lower-grade gliomas (LGG) and its potential implications for patient prognosis. We aimed to assess the histone acetylation score (HAs) and its relationship with key genes involved in histone acetylation regulation.

METHOD

The TCGA-GBMLGG dataset, which provides comprehensive genomic and clinical information, was utilized for this study. We calculated the HAs by analyzing the expression levels of histone acetylation-related genes, including histone acetyltransferases and histone deacetylases, in GBM and LGG patients. Kaplan-Meier survival analysis was performed to evaluate the prognostic value of the HAs. Furthermore, correlation analysis and differential expression analysis were conducted to assess the relationship between the HAs and key genes involved in histone acetylation regulation, as well as the expression differences of immune checkpoint genes.

RESULTS

Our analysis revealed a significant association between the HAs and patient prognosis, with higher HAs correlating to poorer outcomes in GBM and LGG patients. We observed a positive correlation between the HAs and key genes involved in histone acetylation regulation, indicating their potential role in modulating histone acetylation levels. Moreover, we found significant expression differences for immune checkpoint genes between high and low HAs groups, suggesting a potential impact of histone acetylation on the immune response in GBM and LGG.

CONCLUSION

This study highlights the significance of histone acetylation in GBM and LGG. The HAs demonstrated prognostic value, indicating its potential as a clinically relevant biomarker. The correlation between the HAs and key genes involved in histone acetylation regulation provides insights into the underlying mechanisms driving histone acetylation dysregulation in GBM and LGG. Furthermore, the observed expression differences of immune checkpoint genes suggest a potential link between histone acetylation and the immune response. These findings contribute to our understanding of the molecular basis of GBM and LGG and have implications for personalized treatment approaches targeting histone acetylation and the immune microenvironment. Further validation and functional studies are needed to confirm these findings and explore potential therapeutic strategies.

Epigenetic targets to enhance antitumor immune response through the induction of tertiary lymphoid structures

Tertiary lymphoid structures (TLS) are ectopic lymphoid aggregates found in sites of chronic inflammation such as tumors and autoimmune diseases. The discovery that TLS formation at tumor sites correlated with good patient prognosis has triggered extensive research into various techniques to induce their formation at the tumor microenvironment (TME). One strategy is the exogenous induction of specific cytokines and chemokine expression in murine models. However, applying such systemic chemokine expression can result in significant toxicity and damage to healthy tissues. Also, the TLS formed from exogenous chemokine induction is heterogeneous and different from the ones associated with favorable prognosis. Therefore, there is a need to optimize additional approaches like immune cell engineering with lentiviral transduction to improve the TLS formation in vivo. Similarly, the genetic and epigenetic regulation of the different phases of TLS neogenesis are still unknown. Understanding these molecular regulations could help identify novel targets to induce tissue-specific TLS in the TME. This review offers a unique insight into the molecular checkpoints of the different stages and mechanisms involved in TLS formation. This review also highlights potential epigenetic targets to induce TLS neogenesis. The review further explores epigenetic therapies (epi-therapy) and ongoing clinical trials using epi-therapy in cancers. In addition, it builds upon the current knowledge of tools to generate TLS and TLS phenotyping biomarkers with predictive and prognostic clinical potential.

Advances and challenges in thyroid cancer: The interplay of genetic modulators, targeted therapies, and AI-driven approaches

Thyroid cancer continues to exhibit a rising incidence globally, predominantly affecting women. Despite stable mortality rates, the unique characteristics of thyroid carcinoma warrant a distinct approach. Differentiated thyroid cancer, comprising most cases, is effectively managed through standard treatments such as thyroidectomy and radioiodine therapy. However, rarer variants, including anaplastic thyroid carcinoma, necessitate specialized interventions, often employing targeted therapies. Although these drugs focus on symptom management, they are not curative. This review delves into the fundamental modulators of thyroid cancers, encompassing genetic, epigenetic, and non-coding RNA factors while exploring their intricate interplay and influence. Epigenetic modifications directly affect the expression of causal genes, while long non-coding RNAs impact the function and expression of micro-RNAs, culminating in tumorigenesis. Additionally, this article provides a concise overview of the advantages and disadvantages associated with pharmacological and non-pharmacological therapeutic interventions in thyroid cancer. Furthermore, with technological advancements, integrating modern software and computing into healthcare and medical practices has become increasingly prevalent. Artificial intelligence and machine learning techniques hold the potential to predict treatment outcomes, analyze data, and develop personalized therapeutic approaches catering to patient specificity. In thyroid cancer, cutting-edge machine learning and deep learning technologies analyze factors such as ultrasonography results for tumor textures and biopsy samples from fine needle aspirations, paving the way for a more accurate and effective therapeutic landscape in the near future.

Histone lactylation regulates cancer progression by reshaping the tumor microenvironment

As a major product of glycolysis and a vital signaling molecule, many studies have reported the key role of lactate in tumor progression and cell fate determination. Lactylation is a newly discovered post-translational modification induced by lactate. On the one hand, lactylation introduced a new era of lactate metabolism in the tumor microenvironment (TME), and on the other hand, it provided a key breakthrough point for elucidation of the interaction between tumor metabolic reprogramming and epigenetic modification. Studies have shown that the lactylation of tumor cells, tumor stem cells and tumor-infiltrating immune cells in TME can participate in the development of cancer through downstream transcriptional regulation, and is a potential and promising tumor treatment target. This review summarized the discovery and effects of lactylation, as well as recent research on histone lactylation regulating cancer progression through reshaping TME. We also focused on new strategies to enhance anti-tumor effects via targeting lactylation. Finally, we discussed the limitations of existing studies and proposed new perspectives for future research in order to further explore lactylation targets. It may provide a new way and direction to improve tumor prognosis.

Histone regulator KAT2A acts as a potential biomarker related to tumor microenvironment and prognosis of diffuse large B cell lymphoma

BACKGROUND

Recent studies have indicated that epigenetic alterations contribute significantly to lymphoma pathogenesis. A type of epigenetic regulation known as histone acetylation plays a crucial role in transcriptional regulation in eukaryotic cells. Specifically, a significant effect of histone acetylation modifications on the abnormal progression and microenvironment of diffuse large B-cell lymphoma (DLBCL) has been observed.

METHODS

To provide insight into the significance of histone acetylation-related genes, we developed a HAscore model for analyzing histone acetylation patterns in DLBCL samples. Furthermore, KAT2A, a regulator of histone acetylation, was knocked down in DLBCL cell lines to investigate its role in proliferation, cell cycle, and apoptosis.

RESULTS

The HAscore model has been demonstrated to provide insight into the significance of these patterns, showing that patients with a low HAscore have distinct tumor immune microenvironments and poorer prognoses. Besides, KAT2A was identified as a potential biomarker related to immune infiltration and malignant pathways in DLBCL.

CONCLUSION

According to these findings, it is evident that the histone acetylation pattern score model is helpful in describing the immune status of DLBCL and that KAT2A may be used as a biomarker for its treatment.

Nrf2 Drives Hepatocellular Carcinoma Progression through Acetyl-CoA-Mediated Metabolic and Epigenetic Regulatory Networks

Correlations between the oxidative stress response and metabolic reprogramming have been observed during malignant tumor formation; however, the detailed mechanism remains elusive. The transcription factor Nrf2, a master regulator of the oxidative stress response, mediates metabolic reprogramming in multiple cancers. In a mouse model of hepatocellular carcinoma (HCC), through metabolic profiling, genome-wide gene expression, and chromatin structure analyses, we present new evidence showing that in addition to altering antioxidative stress response signaling, Nrf2 ablation impairs multiple metabolic pathways to reduce the generation of acetyl-CoA and suppress histone acetylation in tumors, but not in tumor-adjacent normal tissue. Nrf2 ablation and dysregulated histone acetylation impair transcription complex assembly on downstream target antioxidant and metabolic regulatory genes for expression regulation. Mechanistic studies indicate that the regulatory function of Nrf2 is low glucose dependent, the effect of which is demolished under energy refeeding. Together, our results implicate an unexpected effect of Nrf2 on acetyl-CoA generation, in addition to its classic antioxidative stress response regulatory activity, integrates metabolic and epigenetic programs to drive HCC progression.

IMPLICATIONS

This study highlights that Nrf2 integrates metabolic and epigenetic regulatory networks to dictate tumor progression and that Nrf2 targeting is therapeutically exploitable in HCC treatment.

Systematic analysis of histone acetylation regulators across human cancers

BACKGROUND

Histone acetylation (HA) is an important and common epigenetic pathway, which could be hijacked by tumor cells during carcinogenesis and cancer progression. However, the important role of HA across human cancers remains elusive.

METHODS

In this study, we performed a comprehensive analysis at multiple levels, aiming to systematically describe the molecular characteristics and clinical relevance of HA regulators in more than 10000 tumor samples representing 33 cancer types.

RESULTS

We found a highly heterogeneous genetic alteration landscape of HA regulators across different human cancer types. CNV alteration may be one of the major mechanisms leading to the expression perturbations in HA regulators. Furthermore, expression perturbations of HA regulators correlated with the activity of multiple hallmark oncogenic pathways. HA regulators were found to be potentially useful for the prognostic stratification of kidney renal clear cell carcinoma (KIRC). Additionally, we identified HDAC3 as a potential oncogene in lung adenocarcinoma (LUAD).

CONCLUSION

Overall, our results highlights the importance of HA regulators in cancer development, which may contribute to the development of clinical strategies for cancer treatment.

Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets

Over decades, researchers have focused on the epigenetic control of DNA-templated processes. Histone modification, DNA methylation, chromatin remodeling, RNA modification, and noncoding RNAs modulate many biological processes that are crucial to the development of cancers. Dysregulation of the epigenome drives aberrant transcriptional programs. A growing body of evidence suggests that the mechanisms of epigenetic modification are dysregulated in human cancers and might be excellent targets for tumor treatment. Epigenetics has also been shown to influence tumor immunogenicity and immune cells involved in antitumor responses. Thus, the development and application of epigenetic therapy and cancer immunotherapy and their combinations may have important implications for cancer treatment. Here, we present an up-to-date and thorough description of how epigenetic modifications in tumor cells influence immune cell responses in the tumor microenvironment (TME) and how epigenetics influence immune cells internally to modify the TME. Additionally, we highlight the therapeutic potential of targeting epigenetic regulators for cancer immunotherapy. Harnessing the complex interplay between epigenetics and cancer immunology to develop therapeutics that combine thereof is challenging but could yield significant benefits. The purpose of this review is to assist researchers in understanding how epigenetics impact immune responses in the TME, so that better cancer immunotherapies can be developed.

Establishing a prognostic model of chromatin modulators and identifying potential drug candidates in renal clear cell patients

BACKGROUND

Renal carcinoma is a common malignant tumor of the urinary system. Advanced renal carcinoma has a low 5-year survival rate and a poor prognosis. More and more studies have confirmed that chromatin regulators (CRs) can regulate the occurrence and development of cancer. This article investigates the functional and prognostic value of CRs in renal carcinoma patients.

METHODS

mRNA expression and clinical information were obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and LASSO regression analysis were used to select prognostic chromatin-regulated genes and use them to construct a risk model for predicting the prognosis of renal cancer. Differences in prognosis between high-risk and low-risk groups were compared using Kaplan-Meier analysis. In addition, we analyzed the relationship between chromatin regulators and tumor immune infiltration, and explored differences in drug sensitivity between risk groups.

RESULTS

We constructed a model consisting of 11 CRs to predict the prognosis of renal cancer patients. We not only successfully validated its feasibility, but also found that the 11 CR-based model was an independent prognostic factor. Functional analysis showed that CRs were mainly enriched in cancer development-related signalling pathways. We also found through the TIMER database that CR-based models were also associated with immune cell infiltration and immune checkpoints. At the same time, the genomics of drug sensitivity in cancer database was used to analyze the commonly used drugs of renal clear cell carcinoma patients. It was found that patients in the low-risk group were sensitive to medicines such as axitinib, pazopanib, sorafenib, and gemcitabine. In contrast, those in the high-risk group may be sensitive to sunitinib.

CONCLUSION

The chromatin regulator-related prognostic model we constructed can be used to assess the prognostic risk of patients with clear cell renal cell carcinoma. The results of this study can bring new ideas for targeted therapy of clear cell renal carcinoma, helping doctors to take corresponding measures in advance for patients with different risks.

The role of lipid metabolic reprogramming in tumor microenvironment

Metabolic reprogramming is one of the most important hallmarks of malignant tumors. Specifically, lipid metabolic reprogramming has marked impacts on cancer progression and therapeutic response by remodeling the tumor microenvironment (TME). In the past few decades, immunotherapy has revolutionized the treatment landscape for advanced cancers. Lipid metabolic reprogramming plays pivotal role in regulating the immune microenvironment and response to cancer immunotherapy. Here, we systematically reviewed the characteristics, mechanism, and role of lipid metabolic reprogramming in tumor and immune cells in the TME, appraised the effects of various cell death modes (specifically ferroptosis) on lipid metabolism, and summarized the antitumor therapies targeting lipid metabolism. Overall, lipid metabolic reprogramming has profound effects on cancer immunotherapy by regulating the immune microenvironment; therefore, targeting lipid metabolic reprogramming may lead to the development of innovative clinical applications including sensitizing immunotherapy.

A Lamin Family-Based Signature Predicts Prognosis and Immunotherapy Response in Hepatocellular Carcinoma

Background. Lamin family members play crucial roles in promoting oncogenesis and cancer development. The values of lamin family in predicting prognosis and immunotherapy response remain largely unclarified. Our research is aimed at comprehensively estimating the clinical significance of lamin family in hepatocellular carcinoma and constructing a novel lamin family-based signature to predict prognosis and guide the precise immunotherapy. Methods. The expression features and prognostic value of LMNA, LMNB1, and LMNB2 were explored in the TCGA and GEO databases. The biological functions of LMNB1 and LMNB2 were validated by in vitro assays. A lamin family-based signature was built using the TCGA training set. The TCGA test set, entire TCGA set, and GSE14520 set were used to validate its predictive power. Univariate and multivariate analyses were performed to evaluate the independence of the lamin family-based signature from other clinicopathological characteristics. A nomogram was constructed using the lamin family-based signature and TNM stage. The associations of this signature with molecular pathways, clinical characteristics, immune cell infiltration, and immunotherapy response were analyzed. Results. Lamin family members were upregulated in HCC. Upregulation of LMNB1 and LMNB2 promoted HCC proliferation, migration, and invasion. The predictive signature was initially established based on LMNB1 and LMNB2 which could effectively identify differences in overall survival, immune cell infiltration, and clinicopathological characteristics of high- and low-risk patients. The nomogram showed high prognostic predictive accuracy. Importantly, the lamin family-based signature was correlated with immune suppression and expression of immune checkpoint molecules. Conclusions. The lamin family-based signature is a robust biomarker to predict overall survival and immunotherapy response in HCC. High-risk score patients have a poorer overall survival and might be more sensitive to immunotherapy. This signature may contribute to improving individualized prognosis prediction and precision immunotherapy for HCC patients.

Multiomics analyses and machine learning of nuclear receptor coactivator 6 reveal its essential role in hepatocellular carcinoma

Nuclear receptor coactivator 6 (NCOA6), a coactivator of numerous nuclear receptors and transcription factors, regulates multiple critical cellular functions. Nuclear receptor coactivator 6 is dysregulated in various cancers, including hepatocellular carcinoma (HCC); however, its role remains largely unknown. Here we reported that NCOA6 was highly expressed in HCC compared to the adjacent liver tissue, and NCOA6 overexpression was significantly correlated with poor HCC prognosis. Experiments revealed that the knockdown of NCOA6 damaged the proliferation, migration, and invasion of HCC cells. Multiomics and immune infiltration analyses showed a close relationship between NCOA6 expression, multiple cancer-related malignant pathways, and the immunosuppressive microenvironment. Finally, we established an effective NCOA6-related microRNA (miRNA) signature to distinguish HCC from hepatitis\liver cirrhosis patients. To the best of our knowledge, this study is the first to provide a comprehensive analysis of NCOA6 expression in HCC. We found that NCOA6 plays an important role in HCC development and has a potential mechanism of action. Establishing an NCOA6-related miRNA signature will help develop novel diagnostic strategies for HCC patients.

Construction and validation of a histone acetylation-related lncRNA prognosis signature for ovarian cancer

Ovarian cancer (OC) leads to the most deaths among gynecological malignancies. The various epigenetic regulatory mechanisms of histone acetylation in cancer have attracted increasing attention from scientists. Long non-coding RNA (lncRNA) also plays an important role in multiple biology processes linked to OC. This study aimed to identify the histone acetylation-related lncRNAs (HARlncRNAs) with respect to the prognosis in OC. We obtained the transcriptome data from Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA); HARlncRNAs were first identified by co-expression and differential expression analyses, and then univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) were used to construct the HARlncRNAs risk signature. Kaplan–Meier analysis, time-dependent receiver operating characteristics (ROC), univariate Cox regression, multivariate Cox regression, nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analysis (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. A risk signature with 14 HARlncRNAs in OC was finally established and further validated in the International Cancer Genome Consortium (ICGC) cohort; the 1-, 3-, and 5-year ROC value, nomogram, and calibration results confirmed the good prediction power of this model. The patients were grouped into high- and low-risk subgroups according to the risk score by the median value. The low-risk group patients exhibited a higher homologous recombination deficiency (HRD) score, LOH_frac_altered, and mutLoad_nonsilent. Furthermore, consensus clustering analysis was employed to divide OC patients into three clusters based on the expression of the 14 HARlncRNAs, which presented different survival probabilities. Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) were also performed to evaluate the three clusters. In conclusion, the risk signature composed of 14 HARlncRNAs might function as biomarkers and prognostic indicators with respect to predicting the response to the anti-cancer drugs in OC.

KAT2A/E2F1 Promotes Cell Proliferation and Migration via Upregulating the Expression of UBE2C in Pan-Cancer

Various studies have shown that lysine acetyltransferase 2A (KAT2A), E2F transcription factor 1 (E2F1), and ubiquitin conjugating enzyme E2 C (UBE2C) genes regulated the proliferation and migration of tumor cells through regulating the cell cycle. However, there is a lack of in-depth and systematic research on their mechanisms of action. This study analyzed The Cancer Genome Atlas (TCGA) to screen potential candidate genes and the regulation network of KAT2A and E2F1 complex in pan-cancer. Quantitative real-time PCR (qRT-PCR) and Western blotting (WB), cell phenotype detection, immunofluorescence co-localization, chromatin immunoprecipitation assay (ChIP), and RNA-Seq techniques were used to explore the functional of a candidate gene, UBE2C. We found that the expression of these three genes was significantly higher in more than 10 tumor types compared to normal tissue. Moreover, UBE2C was mainly expressed in tumor cells, which highlighted the impacts of UBE2C as a specific therapeutic strategy. Moreover, KAT2A and E2F1 could promote cell proliferation and the migration of cancer cells by enhancing the expression of UBE2C. Mechanically, KAT2A was found to cooperate with E2F1 and be recruited by E2F1 to the UBE2C promoter for elevating the expression of UBE2C by increasing the acetylation level of H3K9.

Prognostic Value of an Integrin-Based Signature in Hepatocellular Carcinoma and the Identification of Immunological Role of LIMS2

Objective

Evidence proves that integrins affect almost every step of hepatocellular carcinoma (HCC) progression. The current study aimed at constructing an integrin-based signature for prognostic prediction of HCC.

Methods

TCGA-LIHC and ICGC-LIRI-JP cohorts were retrospectively analyzed. Integrin genes were analyzed via univariate Cox regression, followed by generation of a prognostic signature with LASSO approach. Independent factors were input into the nomogram. WGCNA was adopted to select this signature-specific genes. Gene Ontology (GO) enrichment together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the function of the dysregulated genes. The abundance of tumor microenvironment components was estimated with diverse popular computational methods. The relative importance of genes from this signature was estimated through random-forest method.

Results

Eight integrin genes (ADAM15, CDC42, DAB2, ITGB1BP1, ITGB5, KIF14, LIMS2, and SELP) were adopted to define an integrin-based signature. Each patient was assigned the riskScore. High-riskScore subpopulation exhibited worse overall survival, with satisfying prediction efficacy. Also, the integrin-based signature was independent of routine clinicopathological parameters. The nomogram (comprising integrin-based signature, and stage) accurately inferred prognostic outcome, with the excellent net benefit. Genes with the strongest positive interaction to low-riskScore were primarily linked to biosynthetic, metabolic, and catabolic processes and immune pathways; those with the strongest association with high-riskScore were principally associated with diverse tumorigenic signaling. The integrin-based signature was strongly linked with tumor microenvironment components. Among the genes from this signature, LIMS2 possessed the highest importance, and its expression was proven through immunohistochemical staining.

Conclusion

Altogether, our study defined a quantitative integrin-based signature that reliably assessed HCC prognosis and tumor microenvironment features, which possessed the potential as a tool for prognostic prediction.

The molecular subtypes of triple negative breast cancer were defined and a ligand-receptor pair score model was constructed by comprehensive analysis of ligand-receptor pairs

Background

Intercellular communication mediated by ligand-receptor interactions in tumor microenvironment (TME) has a profound impact on tumor progression. This study aimed to explore the molecular subtypes mediated by ligand-receptor (LR) pairs in triple negative breast cancer (TNBC), identify the most important LR pairs to construct a prognostic risk model, and study their effect on TNBC immunotherapy.

Methods

LR pairs subclasses of TNBC were categorized by consensus clustering based on LR Pairs in METABRIC dataset. Least absolute shrinkage and selection operator (LASSO) Cox regression and stepwise Akaike information criterion (stepAIC) were conducted to build a LR pairs score model. The relationship between LR pairs score and immune cell infiltration, stromal score and immune score associated with TME was analyzed, and the prediction of drug therapy and immunotherapy efficacy by LR pairs score was evaluated.

Results

According to the expression pattern of 145 TNBC prognostic LR pairs, the samples were divided into three subclasses with different survival outcomes, copy number variation (CNV), TME immune cell infiltration, stromal score and immune score. The LR pairs score model constructed in the METABRIC dataset was composed of four LR pairs, and its predictive significance for TNBC prognosis was verified in GSE58812 and GSE21653 cohorts. In addition, LR pairs score was negatively correlated with several immune pathways regulating immunity and immune score, and related to the sensitivity of anti-neoplastic drugs and the effect of anti-PD-L1 therapy.

Conclusion

Our study confirmed the impact of LR pairs on the molecular heterogeneity of TNBC, characterized three LR pairs subtypes with different survival outcomes and TME patterns, and proposed a LR pairs score system with predictive significance for TNBC prognosis and anti-PD-L1 therapeutic effect, which provides a potential evaluation scheme for TNBC management.