Cell fate regulation by reticulon-4 in human prostate cancers

Evaluation of miR-148a-3p and miR-106a-5p as Biomarkers for Prostate Cancer: Pilot Study

MicroRNAs (miRNAs) are a class of small non-coding RNAs that may function as tumor suppressors or oncogenes. Alteration of their expression levels has been linked to a range of human malignancies, including cancer. The objective of this investigation is to assess the relative expression levels of certain miRNAs to distinguish between prostate cancer (PCa) from benign prostatic hyperplasia (BPH). Blood plasma was collected from 66 patients diagnosed with BPH and 58 patients with PCa. Real-time PCR technology was used to evaluate the relative expression among the two groups for miR-106a-5p and miR-148a-3p. The significant downregulation of both miRNAs in plasma from PCa versus BPH patients suggests their potential utility as diagnostic biomarkers for distinguishing between these conditions. The concurrent utilization of these two miRNAs slightly enhanced the sensitivity for discrimination among the two analyzed groups, as shown in ROC curve analysis. Further validation of these miRNAs in larger patient cohorts and across different stages of PCa may strengthen their candidacy as clinically relevant biomarkers for diagnosis and prognosis.

Identification of Novel Senescent Markers in Small Extracellular Vesicles

Senescent cells exhibit several typical features, including the senescence-associated secretory phenotype (SASP), promoting the secretion of various inflammatory proteins and small extracellular vesicles (EVs). SASP factors cause chronic inflammation, leading to age-related diseases. Recently, therapeutic strategies targeting senescent cells, known as senolytics, have gained attention; however, noninvasive methods to detect senescent cells in living organisms have not been established. Therefore, the goal of this study was to identify novel senescent markers using small EVs (sEVs). sEVs were isolated from young and senescent fibroblasts using three different methods, including size-exclusion chromatography, affinity column for phosphatidylserine, and immunoprecipitation using antibodies against tetraspanin proteins, followed by mass spectrometry. Principal component analysis revealed that the protein composition of sEVs released from senescent cells was significantly different from that of young cells. Importantly, we identified ATP6V0D1 and RTN4 as novel markers that are frequently upregulated in sEVs from senescent and progeria cells derived from patients with Werner syndrome. Furthermore, these two proteins were significantly enriched in sEVs from the serum of aged mice. This study supports the potential use of senescent markers from sEVs to detect the presence of senescent cells in vivo.

Overexpression of SSR2 promotes proliferation of liver cancer cells and predicts prognosis of patients with hepatocellular carcinoma

Signal Sequence Receptor Subunit 2 (SSR2) is a key endoplasmic reticulum gene involved in protein folding and processing. Previous studies found that it was upregulated in several cancers, but its precise role in hepatocellular carcinoma (HCC) remains unclear. To have a better understanding of this gene in HCC, we examined the expression of SSR2 in HCC tissues by analysing The Cancer Genome Atlas (TCGA) data and immunohistochemistry. We also assessed the association between SSR2 expression and clinicopathological characteristics of HCC patients and patient survival. Potential function of SSR2 was predicted through GSEA and protein–protein interaction analysis. MTT, flowcytometry, transwell and a nude mice xenograft model were employed to investigate the biological functions in vivo and in vitro. The results showed that the expression of SSR2 was significantly increased in HCC tissues, and SSR2 expression was associated with several clinical characteristics. In addition, patients with higher SSR2 expression had poorer survival. Enrichment analysis suggested that SSR2 was probably involved in biological process or signalling pathways related to G2/M checkpoint, passive transmembrane transporter activity, ATF2_S_UP. V1_UP and ncRNA metabolic process. Further experimental study showed that SSR2 knockdown inhibited cell proliferation, migration and invasion ability and promoted apoptosis and cell cycle arrest in vitro. Moreover, downregulation of SSR2 also repressed the growth of HepG2 cells in vivo. In conclusion, our study suggests that SSR2 may act as an oncogene in HCC.

A deep convolutional neural network for segmentation of whole-slide pathology images identifies novel tumour cell-perivascular niche interactions that are associated with poor survival in glioblastoma

BACKGROUND

Glioblastoma is the most aggressive type of brain cancer with high-levels of intra- and inter-tumour heterogeneity that contribute to its rapid growth and invasion within the brain. However, a spatial characterisation of gene signatures and the cell types expressing these in different tumour locations is still lacking.

METHODS

We have used a deep convolutional neural network (DCNN) as a semantic segmentation model to segment seven different tumour regions including leading edge (LE), infiltrating tumour (IT), cellular tumour (CT), cellular tumour microvascular proliferation (CTmvp), cellular tumour pseudopalisading region around necrosis (CTpan), cellular tumour perinecrotic zones (CTpnz) and cellular tumour necrosis (CTne) in digitised glioblastoma histopathological slides from The Cancer Genome Atlas (TCGA). Correlation analysis between segmentation results from tumour images together with matched RNA expression data was performed to identify genetic signatures that are specific to different tumour regions.

RESULTS

We found that spatially resolved gene signatures were strongly correlated with survival in patients with defined genetic mutations. Further in silico cell ontology analysis along with single-cell RNA sequencing data from resected glioblastoma tissue samples showed that these tumour regions had different gene signatures, whose expression was driven by different cell types in the regional tumour microenvironment. Our results further pointed to a key role for interactions between microglia/pericytes/monocytes and tumour cells that occur in the IT and CTmvp regions, which may contribute to poor patient survival.

CONCLUSIONS

This work identified key histopathological features that correlate with patient survival and detected spatially associated genetic signatures that contribute to tumour-stroma interactions and which should be investigated as new targets in glioblastoma. The source codes and datasets used are available in GitHub: https://github.com/amin20/GBM_WSSM .

Identification of crucial genes and pathways associated with prostate cancer in multiple databases

OBJECTIVE

Prostate cancer (PCa) is a malignant neoplasm of the urinary system. This study aimed to use bioinformatics to screen for core genes and biological pathways related to PCa.

METHODS

The GSE5957 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were constructed by R language. Furthermore, protein-protein interaction (PPI) networks were generated to predict core genes. The expression levels of core genes were examined in the Tumor Immune Estimation Resource (TIMER) and Oncomine databases. The cBioPortal tool was used to study the co-expression and prognostic factors of the core genes. Finally, the core genes of signaling pathways were determined using gene set enrichment analysis (GSEA).

RESULTS

Overall, 874 DEGs were identified. Hierarchical clustering analysis revealed that these 24 core genes have significant association with carcinogenesis and development. LONRF1, CDK1, RPS18, GNB2L1 (RACK1), RPL30, and SEC61A1 directly related to the recurrence and prognosis of PCa.

CONCLUSIONS

This study identified the core genes and pathways in PCa and provides candidate targets for diagnosis, prognosis, and treatment.

A Novel Predictor Tool of Biochemical Recurrence after Radical Prostatectomy Based on a Five-MicroRNA Tissue Signature

Within five to ten years after radical prostatectomy (RP), approximately 15–34% of prostate cancer (PCa) patients experience biochemical recurrence (BCR), which is defined as recurrence of serum levels of prostate-specific antigen >0.2 µg/L, indicating probable cancer recurrence. Models using clinicopathological variables for predicting this risk for patients lack accuracy. There is hope that new molecular biomarkers, like microRNAs (miRNAs), could be potential candidates to improve risk prediction. Therefore, we evaluated the BCR prognostic capability of 20 miRNAs, which were selected by a systematic literature review. MiRNA expressions were measured in formalin-fixed, paraffin-embedded (FFPE) tissue RP samples of 206 PCa patients by RT-qPCR. Univariate and multivariate Cox regression analyses were performed, to assess the independent prognostic potential of miRNAs. Internal validation was performed, using bootstrapping and the split-sample method. Five miRNAs (miR-30c-5p/31-5p/141-3p/148a-3p/miR-221-3p) were finally validated as independent prognostic biomarkers. Their prognostic ability and accuracy were evaluated using C-statistics of the obtained prognostic indices in the Cox regression, time-dependent receiver-operating characteristics, and decision curve analyses. Models of miRNAs, combined with relevant clinicopathological factors, were built. The five-miRNA-panel outperformed clinically established BCR scoring systems, while their combination significantly improved predictive power, based on clinicopathological factors alone. We conclude that this miRNA-based-predictor panel will be worth to be including in future studies.