A Comprehensive Prognostic Analysis of POLD1 in Hepatocellular Carcinoma

Comprehensive genomic analysis of adrenocortical carcinoma reveals genetic profiles associated with patient survival

BACKGROUND

Adrenocortical carcinoma (ACC) is one of the most lethal endocrine malignancies and there is a lack of clinically useful markers for prognosis and patient stratification. Therefore our aim was to identify clinical and genetic markers that predict outcome in patients with ACC.

METHODS

Clinical and genetic data from a total of 162 patients with ACC were analyzed by combining an independent cohort consisting of tumors from Yale School of Medicine, Karolinska Institutet, and Düsseldorf University (YKD) with two public databases [The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)]. We used a novel bioinformatical pipeline combining differential expression and messenger RNA (mRNA)- and DNA-dependent survival. Data included reanalysis of previously conducted whole-exome sequencing (WES) for the YKD cohort, WES and RNA data for the TCGA cohort, and RNA data for the GEO cohort.

RESULTS

We identified 3903 significant differentially expressed genes when comparing ACC and adrenocortical adenoma, and the mRNA expression levels of 461/3903 genes significantly impacted survival. Subsequent analysis revealed 45 of these genes to be mutated in patients with significantly worse survival. The relationship was significant even after adjusting for stage and age. Protein-protein interaction showed previously unexplored interactions among many of the 45 proteins, including the cancer-related proteins DNA polymerase delta 1 (POLD1), aurora kinase A (AURKA), and kinesin family member 23 (KIF23). Furthermore 14 of the proteins had significant interactions with TP53 which is the most frequently mutated gene in the germline of patients with ACC.

CONCLUSIONS

Using a multiparameter approach, we identified 45 genes that significantly influenced survival. Notably, many of these genes have protein interactions not previously implicated in ACC. These findings may lay the foundation for improved prognostication and future targeted therapies.

Identification and validation of methylation-CpG prognostic signature for prognosis of hepatocellular carcinoma

Epigenetic biomarkers help predict the prognosis of cancer patients and evaluating the clinical outcome of immunization therapy. In this study, we present a personalized gene methylation-CpG signature to enhance the accuracy of survival prediction for individuals with hepatocellular carcinoma (HCC). Utilizing RNA sequencing and methylation datasets from GEO as well as TCGA, we conducted single sample GSEA (ssGSEA), WGCNA, as well as Cox regression. Through these analyses, we identified 175 oxidative stress and immune-related genes along with 4 CpG loci that are associated with the prognosis of HCC. Subsequently, we constructed a prognostic signature for HCC utilizing these 4 CpG sites, referred to as the HCC Prognostic Signature of Methylation-CpG sites (HPSM). Further investigation revealed an enrichment of immune-related signal pathways in the HPSM-low group, which demonstrated a positive correlation with better survival among HCC patients. Moreover, the methylation of the CpG sites in HPSM was found to be closely linked to drug sensitivity. In vitro experiments tentatively confirmed that promoter methylation regulated the expression of BMPER, one of the CpG sites within HPSM. The expression of BMPER was significantly correlated with cell death in the oxidative stress pathway, and overexpression of BMPER effectively inhibited HCC cell proliferation. Consequently, our findings suggest that HPSM is an independent predictive factor and holds promise for accurately predicting the prognosis of HCC patients.

Race, Prevalence of POLE and POLD1 Alterations, and Survival Among Patients With Endometrial Cancer

Importance

Black patients with endometrial cancer (EC) in the United States have higher mortality than patients of other races with EC. The prevalence of POLE and POLD1 pathogenic alterations in patients of different races with EC are not well studied.

Objective

To explore the prevalence of and outcomes associated with POLE and POLD1 alterations in differential racial groups.

Design, Setting, and Participants

This retrospective cohort study incorporated the largest available data set of patients with EC, including American Association for Cancer Research Project GENIE (Genomics Evidence Neoplasia Information Exchange; 5087 participants), Memorial Sloan Kettering-Metastatic Events and Tropisms (1315 participants), and the Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma (517 participants), collected from 2015 to 2023, 2013 to 2021, and 2006 to 2012, respectively. The prevalence of and outcomes associated with POLE or POLD1 alterations in EC were evaluated across self-reported racial groups.

Exposure

Patients of different racial groups with EC and with or without POLE or POLD1 alterations.

Main Outcomes and Measures

The main outcome was overall survival. Data on demographic characteristics, POLE and POLD1 alteration status, histologic subtype, tumor mutation burden, fraction of genome altered, and microsatellite instability score were collected.

Results

A total of 6919 EC cases were studied, of whom 444 (6.4%), 694 (10.0%), and 4869 (70.4%) patients were self-described as Asian, Black, and White, respectively. Within these large data sets, Black patients with EC exhibited a lower weighted average prevalence of pathogenic POLE alterations (0.5% [3 of 590 cases]) compared with Asian (6.1% [26 of 424]) or White (4.6% [204 of 4520]) patients. By contrast, the prevalence of POLD1 pathogenic alterations was 5.0% (21 cases), 3.2% (19 cases), and 5.6% (255 cases) in Asian, Black, and White patients with EC, respectively. Patients with POLD1 alterations had better outcomes regardless of race, histology, and TP53 alteration status. For a total of 241 clinically annotated Black patients with EC, a composite biomarker panel of either POLD1 or POLE alterations identified 7.1% (17 patients) with positive outcomes (1 event at 70 months follow up) in the small sample of available patients.

Conclusions and Relevance

In this retrospective clinicopathological study of patients of different racial groups with EC, a composite biomarker panel of either POLD1 or POLE alteration could potentially guide treatment de-escalation, which is especially relevant for Black patients.

Altered immunoexpression of DNA polymerase delta 1 catalytic subunit (POLD1) in colorectal cancer

Introduction

The study aimed to determine the immunoexpression levels of polymerase delta 1 catalytic subunit (POLD1), a catalytic and proofreading subunit of DNA polymerase delta, in the sections of colorectal cancer (CRC), and to evaluate the significance of POLD1 as a potential prognostic factor in CRC.

Material and methods

Paired, tumour and non-cancerous tissue samples of the large intestine distant to the neoplasm were collected from the postoperative material of 78 patients who underwent surgical resection of CRC tumours. Polymerase delta 1 catalytic subunit protein levels were determined using immunohistochemistry. Clinical, pathomorphological, and survival data of the patients were pooled. In addition, POLD1 mRNA expression levels of 599 CRC patients were extracted from The Cancer Genome Atlas (TCGA) datasets and subjected to statistical and survival analysis including the Kaplan-Meier method followed by the log-rank test.

Results

Immunoexpression of POLD1 was found in the nuclei of the tumour cells and epithelial cells of unchanged intestinal mucosa. Polymerase delta 1 catalytic subunit immunoreactivity in the tumour was heterogenous, and the average immunoreactivity score was decreased in cancer cells when compared to the mucosa of matched sections of unchanged large intestine (p = 0.0259). However, POLD1 expression at the protein and mRNA levels did not associate with clinicopathological characteristics of the patients and their survival.

Conclusions

Despite previous studies suggesting that POLD1 genetic alterations could be promising molecular biomarkers in CRC, our results do not support any prognostic significance of POLD1 expression in CRC.

Ovarian follicle transcriptome dynamics reveals enrichment of immune system process during transition from small to large follicles in cyclic Indian Ghoongroo pigs

Ovarian follicular development is a critical determinant of reproductive performance in litter bearing species like pigs, wherein economic gains depend on litter size. The study aimed to gain insight into the differentially expressed genes (DEGs) and signalling pathways regulating follicular growth and maturation in Ghoongroo pigs. Transcriptome profiling of porcine small follicles (SF) and large follicles (LF) was conducted using NovaSeq600 sequencing platform and DEGs were identified using DESeq2 with threshold of Padj. < 0.05 and log2 fold change cut off 0.58 (LF vs. SF). Functional annotations and bioinformatics analysis of DEGs were performed to find out biological functions, signalling pathways and hub genes regulating follicular dynamics. Transcriptome analysis revealed 709 and 479 genes unique to SF and LF stages, respectively, and 11,993 co-expressed genes in both the groups. In total, 507 DEGs (284 upregulated and 223 downregulated) were identified, which encoded for diverse proteins including transcription factors (TFs). These DEGs were functionally linked to response to stimulus, lipid metabolic process, developmental process, extracellular matrix organisation along with the immune system process, indicating wide-ranging mechanisms associated with follicular transition. The enriched KEGG pathways in LF stage consisted of ovarian steroidogenesis, cholesterol and retinol metabolism, cell adhesion molecules, cytokine receptor interaction and immune signalling pathways, depicting intra-follicular control of varied ovarian function. The hub gene analysis revealed APOE, SCARB1, MMP9, CYP17A1, TYROBP as key regulators of follicular development. This study identified candidate genes and TFs providing steroidogenic advantage to LFs which makes them fit for selection into the ovulatory pool of follicles.

Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning

Background and aims

Cuproptosis has been identified as a key player in the development of several diseases. In this study, we investigate the potential role of cuproptosis-related genes in the pathogenesis of nonalcoholic fatty liver disease (NAFLD).

Method

The gene expression profiles of NAFLD were obtained from the Gene Expression Omnibus database. Differential expression of cuproptosis-related genes (CRGs) were determined between NAFLD and normal tissues. Protein-protein interaction, correlation, and function enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was analyzed in both NAFLD patients and controls. Quantitative real-time PCR was employed to validate the expression of hub genes.

Results

Four datasets containing 115 NAFLD and 106 control samples were included for bioinformatics analysis. Three hub CRGs (NFE2L2, DLD, and POLD1) were identified through the intersection of three machine learning algorithms. The receiver operating characteristic curve was plotted based on these three marker genes, and the area under the curve (AUC) value was 0.704. In the external GSE135251 dataset, the AUC value of the three key genes was as high as 0.970. Further nomogram, decision curve, calibration curve analyses also confirmed the diagnostic predictive efficacy. Gene set enrichment analysis and gene set variation analysis showed these three marker genes involved in multiple pathways that are related to the progression of NAFLD. CIBERSORT and single-sample gene set enrichment analysis indicated that their expression levels in macrophages, mast cells, NK cells, Treg cells, resting dendritic cells, and tumor-infiltrating lymphocytes were higher in NAFLD compared with control liver samples. The ceRNA network demonstrated a complex regulatory relationship between the three hub genes. The mRNA level of these hub genes were further confirmed in a mouse NAFLD liver samples.

Conclusion

Our study comprehensively demonstrated the relationship between NAFLD and cuproptosis, developed a promising diagnostic model, and provided potential targets for NAFLD treatment and new insights for exploring the mechanism for NAFLD.

Prospects of POLD1 in Human Cancers: A Review

Cancer is the second leading cause of death globally, exceeded only by cardiovascular disease. Despite the introduction of several survival-prolonging treatment modalities, including targeted therapy and immunotherapy, the overall prognosis for the metastatic disease remains challenging. Therefore, the identification of new molecular biomarkers and therapeutic targets related to cancer diagnosis and prognosis is of paramount importance. DNA polymerase delta 1 (POLD1), a catalytic and proofreading subunit of the DNA polymerase δ complex, performs a crucial role in DNA replication and repair processes. Recently, germline and somatic mutations of the POLD1 gene have been acknowledged in several malignancies. Moreover, diversified POLD1 expression profiles have been reported in association with clinicopathological features in a variety of tumor types. With this review, we aim to summarize the current knowledge on the role of POLD1 in cancers. In addition, we discuss the future prospects and clinical applications of the assessment of POLD1 mutation and expression patterns in tumors.

Analysis of risk factors of hepatocellular carcinoma and establishment of a clinical prognosis model

Liver cancer is a common malignancy of the digestive system. Hepatocellular carcinoma (HCC) accounts for the most majority of these tumors and it has brought a heavy medical burden to underdeveloped countries and regions. Many factors affect the prognosis of HCC patients, however, there is no specific statistical model to predict the survival time of clinical patients. This study derived a risk factor signature of HCC and reliable clinical prediction model by statistically analyzing The Surveillance, Epidemiology, and End Results (SEER) database patient information using an open source package in the python environment.

POLD2 is activated by E2F1 to promote triple-negative breast cancer proliferation

Triple-negative breast cancer (TNBC) is a highly malignant breast cancer subtype with a poor prognosis. Improved insight into the molecular biology basis of TNBC progression is urgently needed. Herein, we reported that POLD2 was highly expressed in TNBC and patients with high POLD2 expression in their tumors had poor clinical outcomes. In functional studies, knockdown of POLD2 inhibited the proliferation of TNBC. Mechanistically, we revealed that transcription factor E2F1 directly bound to the promoter of POLD2 and regulated its expression in TNBC cells, which in turn contributed to the proliferation of TNBC. Additionally, rescue experiments validated that E2F1-mediated cell proliferation in TNBC was dependent on POLD2. Taken together, our results elucidated a novel mechanism of the E2F1-POLD2 axis in TNBC proliferation, and POLD2 may be a potential therapeutic target for TNBC treatment.