A Critical Role of Peptidylprolyl Isomerase A Pseudogene 22/microRNA-197-3p/Peptidylprolyl Isomerase A Axis in Hepatocellular Carcinoma

CXCR7 promoted proliferation, migration and invasion in HCC Cells by inactivating Hippo-YAP signaling

BACKGROUND

CXCR7 (ACKR3) has been well-supported as a promoter of growth and metastasis in hepatocellular carcinoma (HCC). Both CXCR7 and Hippo signaling play roles in organ development. We aimed to verify the involvement of Hippo-YAP signaling in CXCR7-regulated HCC proliferation, migration, and invasion.

METHODS

HCCLM3 cells were transfected with si-CXCR7, pcDNA-CXCR7, or related control RNA/empty vector. Cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8), and mRNA and protein levels were measured via quantitative real-time PCR (qPCR) and Western blotting. Colony formation assays were conducted to evaluate proliferation capacity, and Transwell assays were used to assess invasion and migration. Transcriptome data from the TCGA-LIHC dataset were analyzed to investigate the potential effects of CXCR7 in HCC.

RESULTS

si-CXCR7 inhibited cell proliferation in HCCLM3 cells, while pcDNA-CXCR7 promoted it. Migration and invasion were suppressed by si-CXCR7 but enhanced by pcDNA-CXCR7. Patients with higher CXCR7 expression in the TCGA-LIHC dataset had lower overall survival rates and increased gene transcription. The CXCR7-high expressing samples were characterized by the activation of several pathways, including PI3K-AKT signaling, calcium signaling, and the Hippo signaling pathway. si-CXCR7 reduced the relative protein levels of Gαq/11 and GαS while increasing phosphorylated LATS and phosphorylated YAP. Opposite trends in these proteins were observed with pcDNA-CXCR7. Finally, the inhibitory effects of si-CXCR7 on cell proliferation, migration, and invasion were reversed by the YAP inhibitor verteporfin.

CONCLUSION

We suggest that CXCR7 promotes the growth and metastasis of HCC cells, at least in part, by inactivating the Hippo-YAP signaling pathway.

Integrating single-cell RNA sequencing, WGCNA, and machine learning to identify key biomarkers in hepatocellular carcinoma

The microarray and single-cell RNA-sequencing (scRNA-seq) datasets of hepatocellular carcinoma (HCC) were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to identify HCC-related biomarkers. Based on an analysis of scRNA-seq data, several marker genes expressed on tumor cells have been identified. Three machine-learning algorithms were used to identify shared diagnostic genes. Furthermore, logistic regression analysis was conducted to re-evaluate and identify essential biomarkers, which were then employed to develop a diagnostic prediction model. Additionally, AutoDockTools were used for molecular docking to investigate the association between the most sensitive drug and the core proteins. 44 genes were obtained by intersecting the WGCNA results, marker genes from scRNA-seq data, and up-regulated DEGs. Three machine-learning algorithms refined CDKN3, PPIA, PRC1, GMNN, and CENPW as hub biomarkers. GMNN and PRC1 were further selected by logistic regression analysis to build a nomogram. The molecular docking results showed that the drug NPK76-II-72-1 had a good binding ability with the GMNN and PRC1 proteins. The results highlighted CDKN3, PPIA, PRC1, GMNN, and CENPW as potential detection biomarkers for HCC patients. Our research offers novel insights into the diagnosis and treatment of HCC.

Kombo knife combined with sorafenib in liver cancer treatment: Efficacy and safety under immune function influence

BACKGROUND

In the quest to manage hepatocellular carcinoma (HCC), the focus has shifted to a more holistic approach encompassing both data analytics and innovative treatments. Analyzing rich data resources, such as the cancer genome atlas (TCGA), and examining progressive therapies can potentially reshape the trajectory of HCC treatment.

AIM

To elucidate the immunological genes and the underlying mechanism of the combined Kombo knife and sorafenib regimen for HCC by analyzing data from TCGA and machine learning data.

METHODS

Immune attributes were evaluated via TCGA's postablation HCC RNA sequencing data. Using weighted gene coexpression network analysis and machine learning, we identified genes with high prognostic value. The therapeutic landscape and safety metrics of the integrated treatment were critically evaluated across cellular and animal models.

RESULTS

Immune genes-specifically, peptidylprolyl isomerase A and solute carrier family 29 member 3-emerged as significant prognostic markers. Enhanced therapeutic outcomes, such as prolonged progression-free survival and an elevated overall response rate, characterize the combined approach, with peripheral blood mononuclear cells displaying potent effects on HCC dynamics.

CONCLUSION

The combination of Kombo knife with sorafenib is an innovative HCC treatment modality anchored in immune-centric strategies.

Exploring the Molecular Therapeutic Mechanisms of Gemcitabine through Quantitative Proteomics

Gemcitabine (GEM) is widely employed in the treatment of various cancers, including pancreatic cancer. Despite their clinical success, challenges related to GEM resistance and toxicity persist. Therefore, a deeper understanding of its intracellular mechanisms and potential targets is urgently needed. In this study, through mass spectrometry analysis in data-dependent acquisition mode, we carried out quantitative proteomics (three independent replications) and thermal proteome profiling (TPP, two independent replications) on MIA PaCa-2 cells to explore the effects of GEM. Our proteomic analysis revealed that GEM led to the upregulation of the cell cycle and DNA replication proteins. Notably, we observed the upregulation of S-phase kinase-associated protein 2 (SKP2), a cell cycle and chemoresistance regulator. Combining SKP2 inhibition with GEM showed synergistic effects, suggesting SKP2 as a potential target for enhancing the GEM sensitivity. Through TPP, we pinpointed four potential GEM binding targets implicated in tumor development, including in breast and liver cancers, underscoring GEM's broad-spectrum antitumor capabilities. These findings provide valuable insights into GEM's molecular mechanisms and offer potential targets for improving treatment efficacy.

Transforming 'Junk' DNA into Cancer Warriors: The Role of Pseudogenes in Hepatocellular Carcinoma

In the dynamic landscape of hepatocellular carcinoma (HCC) or the liver cancer research, pseudogenes have emerged from the shadows of genetic obscurity to become central figures, significantly influencing the disease molecular development and clinical trajectory. This review explores a transformative shift in perspective, recognizing pseudogenes not as genetic remnants without function, but as critical regulators in the molecular underpinnings of HCC. Engaging in complex interactions such as microRNA sponging, gene expression modulation, and signaling pathway disruptions, pseudogenes orchestrate a part of the molecular complexity driving tumor genesis, progression, and drug resistance in the liver cancer. Their unique expression patterns in hepatoma tissues herald new opportunities for early HCC detection, offering insights into patient prognosis, and identifying novel targets for therapeutic intervention of this disease. Such advancements underscore the importance of pseudogenes in enriching our understanding and management of HCC, paving the way for more effective diagnostic strategies and targeted therapies in the ongoing battle against this challenging malignancy.

Bioinformatics analysis and experimental validation of tumorigenic role of PPIA in gastric cancer

Gastric cancer (GC) is a malignant tumor with high incidence rate and mortality. Due to the lack of effective diagnostic indicators, most patients are diagnosed in late stage and have a poor prognosis. An increasing number of studies have proved that Peptidylprolyl isomerase A (PPIA) can play an oncogene role in various cancer types. However, the precise mechanism of PPIA in GC is still unclear. Herein, we analyzed the mRNA levels of PPIA in pan-cancer. The prognostic value of PPIA on GC was also evaluated using multiple databases. Additionally, the relationship between PPIA expression and clinical factors in GC was also examined. We further confirmed that PPIA expression was not affected by genetic alteration and DNA methylation. Moreover, the upstream regulator miRNA and lncRNA of PPIA were identified, which suggested that LINC10232/miRNA-204-5p/PPIA axis might act as a potential biological pathway in GC. Finally, this study revealed that PPIA was negatively correlated with immune checkpoint expression, immune cell biomarkers, and immune cell infiltration in GC.

Exploration and validation of a novel signature of seven necroptosis-related genes to improve the clinical outcome of hepatocellular carcinoma

Necroptosis has been reported to be involved in cancer progression and associated with cancer prognosis. However, the prognostic values of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC) remain largely unknown. This study aimed to build a signature on the basis of NRGs to evaluate the prognosis of HCC patients. In this study, using bioinformatic analyses of transcriptome sequencing data of HCC (n = 370) from The Cancer Genome Atlas (TCGA) database, 63 differentially expressed NRGs between HCC and adjacent normal tissues were determined. 24 differentially expressed NRGs were found to be related with overall survival (OS). Seven optimum NRGs, determined using Lasso regression and multivariate Cox regression analysis, were used to construct a new prognostic risk signature for predicting the prognosis of HCC patients. Then survival status scatter plots and survival curves demonstrated that the prognosis of patients with high-Riskscore was worse. The prognostic value of this 7-NRG signature was validated by the International Cancer Genome Consortium (ICGC) cohort and a local cohort (Wenzhou, China). Notably, Riskscore was defined as an independent risk factor for HCC prognosis using multivariate cox regression analysis. Immune infiltration analysis suggested that higher macrophage infiltration was found in patients in the high-risk group. Finally, enhanced 7 NRGs were found in HCC tissues by immunohistochemistry. In conclusion, a novel 7-NRG prognostic risk signature is generated, which contributes to the prediction in the prognosis of HCC patients for the clinicians.

Clinical and Prognostic Value of PPIA, SQSTM1, and CCL20 in Hepatocellular Carcinoma Patients by Single-Cell Transcriptome Analysis

Hepatocellular carcinoma (HCC) is the most malignant and poor-prognosis subtype of primary liver cancer. The scRNA-seq approach provides unique insight into tumor cell behavior at the single-cell level. Cytokine signaling in the immune system plays an important role in tumorigenesis and has both pro-tumorigenic and anti-tumorigenic functions. A biomarker of cytokine signaling in immune-related genes (CSIRG) is urgently required to assess HCC patient diagnosis and treatment. By analyzing the expression profiles of HCC single cells, TCGA, and ICGC data, we discovered that three important CSIRG (PPIA, SQSTM1, and CCL20) were linked to the overall survival of HCC patients. Cancer status and three hub CSIRG were taken into account while creating a risk nomogram. The nomogram had a high level of predictability and accuracy. Based on the CSIRG risk score, a distinct pattern of somatic tumor mutational burden (TMB) was detected between the two groups. The enrichment of the pyrimidine metabolism pathway, purine metabolism pathway, and lysosome pathway in HCC was linked to the CSIRG high-risk scores. Overall, scRNA-seq and bulk RNA-seq were used to create a strong CSIRG signature for HCC diagnosis.

Interplays between non-coding RNAs and chemokines in digestive system cancers

Within tumors, chemokines and their cognate receptors are expressed by infiltrated leukocytes, cancerous cells, and related cells of stroma, like tumor-associated fibroblasts and tumor-associated macrophages. In malignancies, the altered expression of chemokines/chemokine receptors governs leukocyte infiltration and activation, epithelial-mesenchymal transition (EMT), cancer cell proliferation, angiogenesis, and metastasis. Non-coding RNAs (ncRNAs) contribute to multiple physiological and pathophysiological processes. Some miRNAs can exert anti-tumorigenic activity in digestive system malignancies by repressing the expression of tumor-promoting chemokines/chemokine receptors or by upregulating tumor-suppressing chemokines/chemokine receptors. However, many miRNAs exert pro-tumorigenic activity by suppressing the expression of chemokines/chemokine receptors or by upregulating tumor-promoting chemokines/chemokine receptors. LncRNA and circRNAs also exert pro- and anti-tumorigenic effects by targeting downstream miRNAs influencing the expression of tumor-promoting and tumor-suppressor chemokines/chemokine receptors. On the other side, some chemokines influence the expression of ncRNAs affecting tumor formation. The current review explains the communications between ncRNAs and chemokines/chemokine receptors in certain digestive system malignancies, such as gastric, colorectal, and pancreatic cancers and hepatocellular carcinoma to gain better insights into their basic crosstalk as well as possible therapeutic modalities.

Noncoding RNA-mediated macrophage and cancer cell crosstalk in hepatocellular carcinoma

The tumor microenvironment (TME) is a well-recognized system that plays an essential role in tumor initiation, development, and progression. Intense intercellular communication between tumor cells and other cells (especially macrophages) occurs in the TME and is mediated by cell-to-cell contact and/or soluble messengers. Emerging evidence indicates that noncoding RNAs (ncRNAs) are critical regulators of the relationship between cells within the TME. In this review, we provide an update on the regulation of ncRNAs (primarily micro RNAs [miRNAs], long ncRNAs [lncRNAs], and circular RNAs [circRNAs]) in the crosstalk between macrophages and tumor cells in hepatocellular carcinoma (HCC). These ncRNAs are derived from macrophages or tumor cells and act as oncogenes or tumor suppressors, contributing to tumor progression not only by regulating the physiological and pathological processes of tumor cells but also by controlling macrophage infiltration, activation, polarization, and function. Herein, we also explore the options available for clinical therapeutic strategies targeting crosstalk-related ncRNAs to treat HCC. A better understanding of the relationship between macrophages and tumor cells mediated by ncRNAs will uncover new diagnostic biomarkers and pharmacological targets in cancer.

Comprehensive Genomic Characterization Analysis Identifies an Oncogenic Pseudogene RP11-3543B.1 in Human Gastric Cancer

Background: Gastrointestinal Cancer (GICs) is the most common group of malignancies, and many of its types are the leading causes of cancer related death worldwide. Pseudogenes have been revealed to have critical regulatory roles in human cancers. The objective of this study is to comprehensive characterize the pseudogenes expression profiling and identify key pseudogenes in the development of gastric cancer (GC).

Methods: The pseudogenes expression profiling was analyzed in six types of GICs cancer from The Cancer Genome Atlas RNA-seq data to identify GICs cancer related pseudogenes. Meanwhile, the genomic characterization including somatic alterations of pseudogenes was analyzed. Then, CCK8 and colony formation assays were performed to evaluate the biological function of RP11-3543B.1 and miR-145 in gastric cancer cells. The mechanisms of pseudogene RP11-3543B.1 in GC cells were explored via using bioinformatics analysis, next generation sequencing and lucifarese reporter assay.

Results: We identified a great number of pseudogenes with significantly altered expression in GICs, and some of these pseudogenes expressed differently among the six cancer types. The amplification or deletion in the pseudogenes-containing loci involved in the alterations of pseudogenes expression in GICs. Among these altered pseudogenes, RP11-3543B.1 is significantly upregulated in gastric cancer. Down-regulation of RP11-3543B.1 expression impaired GC cells proliferation both in vitro and in vivo. RP11-3543B.1 exerts oncogene function via targeting miR-145-5p to regulate MAPK4 expression in gastric cancer cells.

Conclusion: Our study reveals the potential of pseudogenes expression as a new paradigm for investigating GI cancer tumorigenesis and discovering prognostic biomarkers for patients.