A novel prognostic signature based on four glycolysis-related genes predicts survival and clinical risk of hepatocellular carcinoma

Activation of the PI3K/AKT signaling pathway by ARNTL2 enhances cellular glycolysis and sensitizes pancreatic adenocarcinoma to erlotinib

BACKGROUND

Pancreatic adenocarcinoma (PC) is an aggressive malignancy with limited treatment options. The poor prognosis primarily stems from late-stage diagnosis and when the disease has become therapeutically challenging. There is an urgent need to identify specific biomarkers for cancer subtyping and early detection to enhance both morbidity and mortality outcomes. The addition of the EGFR tyrosine kinase inhibitor (TKI), erlotinib, to gemcitabine chemotherapy for the first-line treatment of patients with advanced pancreatic cancer slightly improved outcomes. However, restricted clinical benefits may be linked to the absence of well-characterized criteria for stratification and dependable biomarkers for the prediction of treatment effectiveness.

METHODS AND RESULTS

We examined the levels of various cancer hallmarks and identified glycolysis as the primary risk factor for overall survival in PC. Subsequently, we developed a glycolysis-related score (GRS) model to accurately distinguish PC patients with high GRS. Through in silico screening of 4398 compounds, we discovered that erlotinib had the strongest therapeutic benefits for high-GRS PC patients. Furthermore, we identified ARNTL2 as a novel prognostic biomarker and a predictive factor for erlotinib treatment responsiveness in patients with PC. Inhibition of ARNTL2 expression reduced the therapeutic efficacy, whereas increased expression of ARNTL2 improved PC cell sensitivity to erlotinib. Validation in vivo using patient-derived xenografts (PDX-PC) with varying ARNTL2 expression levels demonstrated that erlotinib monotherapy effectively halted tumor progression in PDX-PC models with high ARNTL2 expression. In contrast, PDX-PC models lacking ARNTL2 did not respond favorably to erlotinib treatment. Mechanistically, we demonstrated that the ARNTL2/E2F1 axis-mediated cellular glycolysis sensitizes PC cells to erlotinib treatment by activating the PI3K/AKT signaling pathway.

CONCLUSIONS

Our investigations have identified ARNTL2 as a novel prognostic biomarker and predictive indicator of sensitivity. These results will help to identify erlotinib-responsive cases of PC and improve treatment outcomes. These findings contribute to the advancement of precision oncology, enabling more accurate and targeted therapeutic interventions.

Unraveling the enigma of B cells in diffuse large B-cell lymphoma: unveiling cancer stem cell-like B cell subpopulation at single-cell resolution

Background

Diffuse large B-cell lymphoma (DLBCL) represents the most prevalent form of aggressive non-Hodgkin lymphoma. Despite receiving standard treatment, a subset of patients undergoes refractory or recurrent cases, wherein the involvement of cancer stem cells (CSCs) could be significant.

Methods

We comprehensively characterized B cell subpopulations using single-cell RNA sequencing data from three DLBCL samples and one normal lymph tissue. The CopyKat R package was employed to assess the malignancy of B cell subpopulations based on chromosomal copy number variations. CIBERSORTx software was utilized to estimate the proportions of B cell subpopulations in 230 DLBCL tissues. Furthermore, we employed the pySCENIC to identify key transcription factors that regulate the functionality of B cell subpopulations. By employing CellphoneDB, we elucidated the interplay among tumor microenvironment components within the B cell subpopulations. Finally, we validated our findings through immunofluorescence experiments.

Results

Our analysis revealed a specific cancer stem cell-like B cell subpopulation exhibiting self-renewal and multilineage differentiation capabilities based on the exploration of B cell subpopulations in DLBCL and normal lymph tissues at the single-cell level. Notably, a high infiltration of cancer stem cell-like B cells correlated with a poor prognosis, potentially due to immune evasion mediated by low expression of major histocompatibility complex molecules. Furthermore, we identified key transcription factor regulatory networks regulated by HMGB3, SAP30, and E2F8, which likely played crucial roles in the functional characterization of the cancer stem cell-like B cell subpopulation. The existence of cancer stem cell-like B cells in DLBCL was validated through immunofluorescent staining. Finally, cell communication between B cells and tumor-infiltrating T cell subgroups provided further insights into the functional characterization of the cancer stem cell-like B cell subpopulation.

Conclusions

Our research provides a systematic description of a specific cancer stem cell-like B cell subpopulation associated with a poor prognosis in DLBCL. This study enhances our understanding of CSCs and identifies potential therapeutic targets for refractory or recurrent DLBCL patients.

CDCA8 induced by NF-YA promotes hepatocellular carcinoma progression by regulating the MEK/ERK pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors. Cell division cycle associated 8 (CDCA8) is an important multifactorial regulator in cancers. However, its up and downstream targets and effects in HCC are still unclear.

METHODS

A comprehensive bioinformatics analysis was performed using The Cancer Genome Atlas dataset (TCGA) to explore novel core oncogenes. We quantified CDCA8 levels in HCC tumors using qRT-PCR. HCC cell's proliferative, migratory, and invasive abilities were detected using a Cell Counting Kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, clone formation, and a Transwell assay. An orthotopic tumor model and tail vein model were constructed to determine the effects of CDCA8 inhibition in vivo. The mechanism underlying CDCA8 was investigated using RNA sequencing. The prognostic value of CDCA8 was assessed with immunohistochemical staining of the tissue microarrays.

RESULTS

CDCA8 was identified as a novel oncogene during HCC development. The high expression of CDCA8 was an independent predictor for worse HCC outcomes both in publicly available datasets and in our cohort. We found that CDCA8 knockdown inhibited HCC cell proliferation, colony formation, and migration by suppressing the MEK/ERK pathway in vitro. Moreover, CDCA8 deficiency significantly inhibited tumorigenesis and metastasis. Next-generation sequencing and laboratory validation showed that CDCA8 silencing inhibited the expression of TPM3, NECAP2, and USP13. Furthermore, NA-YA overexpression upregulated the expression of CDCA8. CDCA8 knockdown could attenuate NF-YA-mediated cell invasion in vitro. The expression of NF-YA alone or in combined with CDCA8 were validated as significant independent risk factors for patient survival.

CONCLUSION

Our findings revealed that the expression of CDCA8 alone or in combined with NF-YA contributed to cancer progression, and could serve as novel potential therapeutic targets for HCC patients.

Identification of Hypoxia-Related Prognostic Signature and Competing Endogenous RNA Regulatory Axes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common type of liver cancer and one of the highly lethal diseases worldwide. Hypoxia plays an important role in the development and prognosis of HCC. This study aimed to construct a new hypoxia-related prognosis signature and investigate its potential ceRNA axes in HCC. RNA profiles and hypoxia genes were downloaded, respectively, from the Cancer Genome Atlas hepatocellular carcinoma database and Gene Set Enrichment Analysis website. Cox regression analyses were performed to select the prognostic genes and construct the risk model. The ENCORI database was applied to build the lncRNA-miRNA-mRNA prognosis-related network. The TIMER and CellMiner databases were employed to analyze the association of gene expression in ceRNA with immune infiltration and drug sensitivity, respectively. Finally, the co-expression analysis was carried out to construct the potential lncRNA/miRNA/mRNA regulatory axes. We obtained a prognostic signature including eight hypoxia genes (ENO2, KDELR3, PFKP, SLC2A1, PGF, PPFIA4, SAP30, and TKTL1) and further established a hypoxia-related prognostic ceRNA network including 17 lncRNAs, six miRNAs, and seven mRNAs for hepatocellular carcinoma. Then, the analysis of immune infiltration and drug sensitivity showed that gene expression in the ceRNA network was significantly correlated with the infiltration abundance of multiple immune cells, the expression level of immune checkpoints, and drug sensitivity. Finally, we identified three ceRNA regulatory axes (SNHG1/miR-101-3p/PPFIA4, SNHG1/miR-101-3p/SAP30, and SNHG1/miR-101-3p/TKTL1) associated with the progression of HCC under hypoxia. Here, we constructed a prognosis gene signature and a ceRNA network related to hypoxia for hepatocellular carcinoma. Among the ceRNA network, six highly expressed lncRNAs (AC005540.1, AC012146.1, AC073529.1, AC090772.3, AC138150.2, AL390728.6) and one highly expressed mRNA (PPFIA4) were the potential biomarkers of hepatocellular carcinoma which we firstly reported. The three predicted hypoxia-related regulatory axes may play a vital role in the progression of hepatocellular carcinoma.

Effects of PAMK on lncRNA, miRNA, and mRNA expression profiles of thymic epithelial cells

Polysaccharides from Atractylodes macrocephala Koidz (PAMK) can promote the proliferation of thymocytes and improve the body's immunity. However, the effect of PAMK on thymic epithelial cells has not been reported. Studies have shown that miRNAs and lncRNAs are key factors in regulating cell proliferation. In this study, we found that PAMK could promote the proliferation of mouse medullary thymic epithelial cell line 1 (MTEC1) cells through CCK-8 and EdU experiments. To further explore its mechanism, we detected the effect of PAMK on the expression profiles of lncRNAs, miRNAs, and mRNAs in MTEC1 cells. The results showed that PAMK significantly affected the expression of 225 lncRNAs, 29 miRNAs, and 800 mRNAs. Functional analysis showed that these differentially expressed genes were significantly enriched in cell cycle, cell division, NF-kappaB signaling, apoptotic process, and MAPK signaling pathway. Finally, we used Cytoscape to visualize lncRNA-miRNA-mRNA(14 lncRNAs, 17 miRNAs, 171 mRNAs) networks based on ceRNA theory. These results suggest that lncRNAs and miRNAs may be involved in the effect of PAMK on the proliferation of MTEC1 cells, providing a new research direction for exploring the molecular mechanism of PAMK promoting the proliferation of thymic epithelial cells.

Classification and Prognostic Characteristics of Hepatocellular Carcinoma Based on Glycolysis Cholesterol Synthesis Axis

Background

Liver hepatocellular carcinoma (LIHC) is among the most frequent causes of cancer-related death across the world with a considerably poor prognosis. The current study targeted providing a new type of LIHC from the perspective of the glycolysis/cholesterol synthesis axis, predicting its prognostic characteristics, and exploring the potential role and mechanism of the glycolysis/cholesterol synthesis axis in the occurrence and development of LIHC.

Methods

Based on the two expression profile data and clinical information of LIHC in The Cancer Genome Atlas (TCGA) database and hepatocellular carcinoma database (HCCDB), as well as glycolysis/cholesterol-related genes from the Molecular Signatures Database (MSigDB), unsupervised consistent clustering method was used to identify molecular subtypes. In addition, the differential genes were identified by limma package, and then the gene set was enriched, analyzed, and annotated by WebGestaltR package. At the same time, the immune infiltration analysis of tumor samples was carried out using the ESTIMATE to evaluate the tumor immune score of the samples. Finally, the differences in clinical characteristics among molecular subtypes were measured using univariate and multivariate Cox analyses.

Results

According to the median standardized expression levels of glycolysis/cholesterol production genes, samples were divided into four groups (molecular subtypes): Quiescent group, Glycolysis group, Cholesterol group, and Mixed group. Significant prognostic differences were observed among the four groups. In both TCGA and HCCDB18 datasets, the prognosis of subtype Mixed was the worst, while Quiescent had a good prognosis. Cell cycle and oncogenic pathways were significantly enriched in the Mixed group. In addition, glycolysis and cholesterol production gene expressions were related to the prognostic LIHC subtype classification genes' expression levels.

Conclusion

Metabolic classification regarding glycolysis and cholesterol production pathways provided new insights into the biological aspects of LIHC molecular subtypes and might help to develop personalized therapies for unique tumor metabolic profiles.