TANK-Binding Kinase 1 (TBK1) Serves as a Potential Target for Hepatocellular Carcinoma by Enhancing Tumor Immune Infiltration

Statin prevents cancer development in chronic inflammation by blocking interleukin 33 expression

Chronic inflammation is a major cause of cancer worldwide. Interleukin 33 (IL-33) is a critical initiator of cancer-prone chronic inflammation; however, its induction mechanism by environmental causes of chronic inflammation is unknown. Herein, we demonstrate that Toll-like receptor (TLR)3/4-TBK1-IRF3 pathway activation links environmental insults to IL-33 induction in the skin and pancreas inflammation. An FDA-approved drug library screen identifies pitavastatin to effectively suppress IL-33 expression by blocking TBK1 membrane recruitment/activation through the mevalonate pathway inhibition. Accordingly, pitavastatin prevents chronic pancreatitis and its cancer sequela in an IL-33-dependent manner. The IRF3-IL-33 axis is highly active in chronic pancreatitis and its associated pancreatic cancer in humans. Interestingly, pitavastatin use correlates with a significantly reduced risk of chronic pancreatitis and pancreatic cancer in patients. Our findings demonstrate that blocking the TBK1-IRF3-IL-33 signaling axis suppresses cancer-prone chronic inflammation. Statins present a safe and effective prophylactic strategy to prevent chronic inflammation and its cancer sequela.

Emerging Targets and Therapeutics in Immuno-Oncology: Insights from Landscape Analysis

In the ever-evolving landscape of cancer research, immuno-oncology stands as a beacon of hope, offering novel avenues for treatment. This study capitalizes on the vast repository of immuno-oncology-related scientific documents within the CAS Content Collection, totaling over 350,000, encompassing journals and patents. Through a pioneering approach melding natural language processing with the CAS indexing system, we unveil over 300 emerging concepts, depicted in a comprehensive "Trend Landscape Map". These concepts, spanning therapeutic targets, biomarkers, and types of cancers among others, are hierarchically organized into eight major categories. Delving deeper, our analysis furnishes detailed quantitative metrics showcasing growth trends over the past three years. Our findings not only provide valuable insights for guiding future research endeavors but also underscore the merit of tapping the vast and unparalleled breadth of existing scientific information to derive profound insights.

Exploring the role of CDCA4 in liver hepatocellular carcinoma using bioinformatics analysis and experiments

Liver hepatocellular carcinoma (LIHC) encompasses diverse therapeutic approaches, among which targeted therapy has gained significant prominence in recent years. The identification of numerous targets and the increasing clinical application of targeted drugs have greatly improved LIHC treatment. However, the precise role of CDCA4 (Cell Division Cycle Associated 4), as well as its underlying mechanisms and prognostic implications in LIHC, remains unclear. CDCA4 expression levels in LIHC were analyzed using multiple databases including the cancer genome atlas (TCGA), gene expression profiling interactive analysis (GEPIA), and ULCAN, as well as the datasets E_TABM_36, GSE144269, GSE14520, and GSE54236. The prognostic value of CDCA4 was then evaluated. Subsequently, the association between CDCA4 and immune cells was investigated. Enrichment analysis (GSEA) was utilized to investigate the functional roles and pathways linked to CDCA4. Additionally, the methylation patterns and drug sensitivity of CDCA4 were examined. A predictive model incorporating immune genes related to CDCA4 was developed. The TISCH dataset was used to investigate the single-cell expression patterns of CDCA4. Finally, validation of CDCA4 expression levels was conducted through RT-PCR, Western blotting, and immunohistochemistry. CDCA4 exhibited significant overexpression in LIHC and demonstrated significant correlations with clinical features. High expression of CDCA4 is associated with a poorer prognosis. Analysis of immune infiltration and enrichment revealed its association with the immune microenvironment. Furthermore, its expression is correlated with methylation and mutation patterns. CDCA4 is associated with 19 drugs. Prognostic models utilizing CDCA4 demonstrate favorable effectiveness. T cell subtypes were found to be associated with CDCA4 through single-cell analysis. The conclusive experiment provided evidence of significant upregulation of CDCA4 in LIHC. The high expression of CDCA4 in LIHC is associated with prognostic significance and is highly expressed in T cell subtypes, providing a new therapeutic target and potential therapeutic strategy for LIHC.

New insights into T-cell exhaustion in liver cancer: from mechanism to therapy

Liver cancer is one of the most common malignancies. T-cell exhaustion is associated with immunosuppression of tumor and chronic infection. Although immunotherapies that enhance the immune response by targeting programmed cell death-1(PD-1)/programmed cell death ligand 1 (PD-L1) have been applied to malignancies, these treatments have shown limited response rates. This suggested that additional inhibitory receptors (IRs) also contributed to T-cell exhaustion and tumor prognosis. Exhausted T-cells (Tex) in the tumor immune microenvironment (TME) are usually in a dysfunctional state of exhaustion, such as impaired activity and proliferative ability, increased apoptosis rate, and reduced production of effector cytokines. Tex cells participate in the negative regulation of tumor immunity mainly through IRs on the cell surface, changes in cytokines and immunomodulatory cell types, causing tumor immune escape. However, T-cell exhaustion is not irreversible and targeted immune checkpoint inhibitors (ICIs) can effectively reverse the exhaustion of T-cells and restore the anti-tumor immune response. Therefore, the research on the mechanism of T-cell exhaustion in liver cancer, aimed at maintaining or restoring the effector function of Tex cells, might provide a new method for the treatment of liver cancer. In this review, we summarized the basic characteristics of Tex cells (such as IRs and cytokines), discussed the mechanisms associated with T-cell exhaustion, and specifically discussed how these exhaustion characteristics were acquired and shaped by key factors within TME. Then new insights into the molecular mechanism of T-cell exhaustion suggested a potential way to improve the efficacy of cancer immunotherapy, namely to restore the effector function of Tex cells. In addition, we also reviewed the research progress of T-cell exhaustion in recent years and provided suggestions for further research.

Establishment and validation of an immune infiltration predictive model for ovarian cancer

BACKGROUND

The most prevalent mutation in ovarian cancer is the TP53 mutation, which impacts the development and prognosis of the disease. We looked at how the TP53 mutation associates the immunophenotype of ovarian cancer and the prognosis of the disease.

METHODS

We investigated the state of TP53 mutations and expression profiles in culturally diverse groups and datasets and developed an immune infiltration predictive model relying on immune-associated genes differently expressed between TP53 WT and TP53 MUT ovarian cancer cases. We aimed to construct an immune infiltration predictive model (IPM) to enhance the prognosis of ovarian cancer and investigate the impact of the IPM on the immunological microenvironment.

RESULTS

TP53 mutagenesis affected the expression of seventy-seven immune response-associated genes. An IPM was implemented and evaluated on ovarian cancer patients to distinguish individuals with low- and high-IPM subgroups of poor survival. For diagnostic and therapeutic use, a nomogram is thus created. According to pathway enrichment analysis, the pathways of the human immune response and immune function abnormalities were the most associated functions and pathways with the IPM genes. Furthermore, patients in the high-risk group showed low proportions of macrophages M1, activated NK cells, CD8+ T cells, and higher CTLA-4, PD-1, PD-L1, and TIM-3 than patients in the low-risk group.

CONCLUSIONS

The IPM model may identify high-risk patients and integrate other clinical parameters to predict their overall survival, suggesting it is a potential methodology for optimizing ovarian cancer prognosis.

TRIP13 overexpression in hepatocellular carcinoma: implications for poor prognosis and immune cell infiltration

PURPOSE

The overexpression of TRIP13 has been observed in many types of cancer and has been identified as an oncogene. However, its role in hepatocellular carcinoma (HCC) has not been extensively studied. This study aimed to investigate the expression of TRIP13 in HCC and its impact on immune cell infiltration and prognosis.

METHODS

We analyzed TCGA and GSE62232 datasets to assess TRIP13 expression in HCC. Kaplan-Meier and subgroup analysis were performed to examine the correlation between TRIP13 expression and HCC. Univariate and Cox regression analysis were conducted to determine the predictive value of TRIP13 in assessing patient outcomes. A nomogram was developed using TRIP13 mRNA expression to predict HCC prognosis. TRIP13 expression was validated using immunohistochemistry in our patient cohort. Survival and subgroup analyses were conducted to investigate the role of TRIP13 in HCC prognosis.

RESULTS

The results indicated that TRIP13 upregulation in HCC was a strong independent predictor of poor outcome, as determined by Kaplan-Meier and Cox regression analyses. A high AUC value of 0.982 from ROC curves suggested that TRIP13 upregulation could serve as a reliable diagnostic indicator for HCC. The immunohistochemical validation of TRIP13 expression in the patient cohort confirmed its prognostic significance, and high TRIP13 expression was found to be associated with increased infiltration of Th2 cells and decreased infiltration of neutrophils, Th17 cells, and dendritic cells.

CONCLUSION

These findings suggest that TRIP13 could be a potential prognostic biomarker for HCC.

Serine/threonine kinase TBK1 promotes cholangiocarcinoma progression via direct regulation of β-catenin

Cholangiocarcinoma (CCA) is a highly heterogeneous and metastatic malignancy with a poor prognosis even after curative hepatectomy. Studies exploring its pathogenesis and identifying effective therapeutic targets are urgently needed. In this study, we found that TANK-binding kinase 1 (TBK1), a serine/threonine-protein kinase, showed a dynamic increase during the different stages of murine spontaneous CCA carcinogenesis (hyperplasia, dysplasia, and CCA). TBK1 was upregulated in human tissues, including intrahepatic (n = 182) and extrahepatic (n = 40) CCA tissues, compared with nontumor tissues, and the elevated expression of TBK1 was positively correlated with larger tumour diameter, lymph node metastasis, and advanced TNM stage. Functional studies indicated that TBK1 promoted CCA growth and metastasis both in vitro and in vivo. TBK1 directly interacts with β-catenin, promoting its phosphorylation at the S552 site and its nuclear translocation, which further activates EMT-related transcriptional reprogramming. GSK-8612, a TBK1 inhibitor or a kinase-inactivating mutation, effectively suppresses the above processes. In addition, we found that low-density lipoprotein receptor (LDLR), which mediates the endocytosis of cholesterol, was upregulated in CCA. Therefore, we designed a cholesterol-conjugated DNA/RNA heteroduplex oligonucleotide targeting TBK1 (Cho-TBK1-HDO), which could accumulate in CCA cells via LDLR, reduce the TBK1 mRNA level and inhibit intrahepatic metastasis of CCA. Besides, in the experimental group of 182 ICC patients, high TBK1 expression combined with high nuclear β-catenin expression predicted a worse prognosis. In summary, TBK1 might serve as a potential prognostic biomarker and therapeutic target for patients with CCA.

TBK1 promotes thyroid cancer progress by activating the PI3K/Akt/mTOR signaling pathway

Introduction

Thyroid cancer has received increasing attention; however, its detailed pathogenesis and pathological processes remain unclear. We investigated the role of TANK‐binding kinase 1 (TBK1) in the progression of thyroid cancer.

Methods

The expression of TBK1 in thyroid cancer and normal control tissues was analyzed using real‐time quantitative polymerase chain reaction. The function of TBK1 on thyroid cancer cells was detected using MTT, colony formation, wound healing, and Transwell assays. The xenograft assay was carried out to check on the role of TBK1 in thyroid cancer.

Results

TBK1 was highly expressed in thyroid tumors. High expression of TBK1 raised viability, proliferation, migration, and invasion of thyroid cancer cells. Gene set enrichment analysis revealed that TBK1 activated the phosphatidylinositol‐3‐kinase/protein kinase B/mammalian target of rapamycin pathway. In addition, Myc‐associated zinc finger protein (MAZ) was overexpressed in thyroid cancer and transcriptionally activated BK1. MAZ silence reversed the effects of TBK1 overexpression on thyroid cancer progression. Cotransfection with MAZ small‐interfering RNA(siRNA) and TBK1 siRNA did not strengthen the inhibitory effect of TBK1 silencing on the thyroid cancer cells. The xenograft tumor assay showed that TBK1 short hairpinRNA inhibited tumor growth.

Conclusion

MAZ silencing inhibited tumor progress of thyroid cancer cells, whereas this inhibitory effect was reversed by TBK1 overexpression.

Statin prevents cancer development in chronic inflammation by blocking interleukin 33 expression

Chronic inflammation is a major cause of cancer worldwide. Interleukin 33 (IL-33) is a critical initiator of cancer-prone chronic inflammation; however, its induction mechanism by the environmental causes of chronic inflammation is unknown. Herein, we demonstrate that Toll-like receptor (TLR)3/4-TBK1-IRF3 pathway activation links environmental insults to IL-33 induction in the skin and pancreas. FDA-approved drug library screen identified pitavastatin as an effective IL-33 inhibitor by blocking TBK1 membrane recruitment/activation through the mevalonate pathway inhibition. Accordingly, pitavastatin prevented chronic pancreatitis and its cancer sequela in an IL-33-dependent manner. IRF3-IL-33 axis was highly active in chronic pancreatitis and its associated pancreatic cancer in humans. Interestingly, pitavastatin use correlated with a significantly reduced risk of chronic pancreatitis and pancreatic cancer in patients. Our findings demonstrate that blocking the TBK1-IRF3 signaling pathway suppresses IL-33 expression and cancer-prone chronic inflammation. Statins present a safe and effective therapeutic strategy to prevent chronic inflammation and its cancer sequela.

Cannot Target What Cannot Be Seen: Molecular Imaging of Cancer Stem Cells

Cancer stem cells are known to play a key role in tumour development, proliferation, and metastases. Their unique properties confer resistance to therapy, often leading to treatment failure. It is believed that research into the identification, targeting, and eradication of these cells can revolutionise oncological treatment. Based on the principle that what cannot be seen, cannot be targeted, a primary step in cancer management is the identification of these cells. The current review aims to encompass the state-of-the-art functional imaging techniques that enable the identification of cancer stem cells via various pathways and mechanisms. The paper presents in vivo molecular techniques that are currently available or await clinical implementation. Challenges and future prospects are highlighted to open new research avenues in cancer stem cell imaging.

STING pathway contributes to the prognosis of hepatocellular carcinoma and identification of prognostic gene signatures correlated to tumor microenvironment

Background

Hepatocellular carcinoma (HCC) is one of the most malignant solid tumors worldwide. Recent evidence shows that the stimulator of interferon genes (STING) pathway is essential for anti-tumor immunity via inducing the production of downstream inflammatory cytokines. However, its impact on the prognosis and tumor microenvironment of HCC was still limited known.

Methods

We obtained gene expression profiles of HCC from GEO, TCGA, and ICGC databases, and immune-related genes (IRGs) from the ImmPort database. Multivariate Cox regression was performed to identify independent prognostic factors. Nomogram was established to predict survival probability for individual patients. Kaplan–Meier curve was used to evaluate the survival difference. Afterward, ESTIMATE, TISCH, and TIMER databases were combined to assess the immune cell infiltration. Furthermore, the qPCR, western blotting, and immunohistochemistry were done to evaluate gene expression, and in vitro cell models were built to determine cell migratory ability.

Results

We found that gene markers of NLRC3, STING1, TBK1, TRIM21, and XRCC6 within STING pathway were independent prognostic factors in HCC patients. Underlying the finding, a predictive nomogram was constructed in TCGA-training cohort and further validated in TCGA-all and ICGC datasets, showing credible performance. Experimentally, up-regulated TBK1 promotes the ability of HCC cell migration. Next, the survival-related immune-related co-expressed gene signatures (IRCGS) (VAV1, RHOA, and ZC3HAV1) were determined in HCC cohorts and their expression was verified in human HCC cells and clinical samples. Furthermore, survival-related IRCGS was associated with the infiltration of various immune cell subtypes in HCC, the transcriptional expression of prominent immune checkpoints, and immunotherapeutic response.

Conclusion

Collectively, we constructed a novel prognostic nomogram model for predicting the survival probability of individual HCC patients. Moreover, an immune-related prognostic gene signature was determined. Both might function as potential therapeutic targets for HCC treatment in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02734-4.

Pharmacological Inhibition of STING/TBK1 Signaling Attenuates Myeloid Fibroblast Activation and Macrophage to Myofibroblast Transition in Renal Fibrosis

Renal fibrosis is an important pathological biomarker of chronic kidney disease (CKD). Stimulator of interferon genes/TANK binding kinase 1 (STING/TBK1) axis has been identified as the main regulator of innate immune response and closely related to fibrotic disorder. However, the role of STING/TBK1 signaling pathway in kidney fibrosis is still unknown. In this study, we investigated the effect of pharmacological inhibition of STING/TBK1 signaling on renal fibrosis induced by folic acid (FA). In mice, TBK1 was significantly activated in interstitial cells of FA-injured kidneys, which was markedly inhibited by H-151 (a STING inhibitor) treatment. Specifically, pharmacological inhibition of STING impaired bone marrow-derived fibroblasts activation and macrophage to myofibroblast transition in folic acid nephropathy, leading to reduction of extracellular matrix proteins expression, myofibroblasts formation and development of renal fibrosis. Furthermore, pharmacological inhibition of TBK1 by GSK8612 reduced myeloid myofibroblasts accumulation and impeded macrophage to myofibroblast differentiation, resulting in less deposition of extracellular matrix protein and less severe fibrotic lesion in FA-injured kidneys. In cultured mouse bone marrow-derived monocytes, TGF-β1 activated STING/TBK1 signaling. This was abolished by STING or TBK1 inhibitor administration. In addition, GSK8612 treatment decreased levels of α-smooth muscle actin and extracellular matrix proteins and prevents bone marrow-derived macrophages to myofibroblasts transition in vitro. Collectively, our results revealed that STING/TBK1 signaling has a critical role in bone marrow-derived fibroblast activation, macrophages to myofibroblasts transition, and kidney fibrosis progression.

Knockdown of TANK-Binding Kinase 1 Enhances the Sensitivity of Hepatocellular Carcinoma Cells to Molecular-Targeted Drugs

The protein kinase, TANK-binding kinase 1 (TBK1), not only regulates various biological processes but also functions as an important regulator of human oncogenesis. However, the detailed function and molecular mechanisms of TBK1 in hepatocellular carcinoma (HCC), especially the resistance of HCC cells to molecular-targeted drugs, are almost unknown. In the present work, the role of TBK1 in regulating the sensitivity of HCC cells to molecular-targeted drugs was measured by multiple assays. The high expression of TBK1 was identified in HCC clinical specimens compared with paired non-tumor tissues. The high level of TBK1 in advanced HCC was associated with a poor prognosis in patients with advanced HCC who received the molecular-targeted drug, sorafenib, compared to patients with advanced HCC patients and a low level of TBK1. Overexpression of TBK1 in HCC cells induced their resistance to molecular-targeted drugs, whereas knockdown of TBK1 enhanced the cells’ sensitivity to molecular-targeted dugs. Regarding the mechanism, although overexpression of TBK1 enhanced expression levels of drug-resistance and pro-survival-/anti-apoptosis-related factors, knockdown of TBK1 repressed the expression of these factors in HCC cells. Therefore, TBK1 is a promising therapeutic target for HCC treatment and knockdown of TBK1 enhanced sensitivity of HCC cells to molecular-targeted drugs.

The role of TBK1 in cancer pathogenesis and anticancer immunity

The TANK-binding kinase 1 (TBK1) is a serine/threonine kinase belonging to the non-canonical inhibitor of nuclear factor-κB (IκB) kinase (IKK) family. TBK1 can be activated by pathogen-associated molecular patterns (PAMPs), inflammatory cytokines, and oncogenic kinases, including activated K-RAS/N-RAS mutants. TBK1 primarily mediates IRF3/7 activation and NF-κB signaling to regulate inflammatory cytokine production and the activation of innate immunity. TBK1 is also involved in the regulation of several other cellular activities, including autophagy, mitochondrial metabolism, and cellular proliferation. Although TBK1 mutations have not been reported in human cancers, aberrant TBK1 activation has been implicated in the oncogenesis of several types of cancer, including leukemia and solid tumors with KRAS-activating mutations. As such, TBK1 has been proposed to be a feasible target for pharmacological treatment of these types of cancer. Studies suggest that TBK1 inhibition suppresses cancer development not only by directly suppressing the proliferation and survival of cancer cells but also by activating antitumor T-cell immunity. Several small molecule inhibitors of TBK1 have been identified and interrogated. However, to this point, only momelotinib (MMB)/CYT387 has been evaluated as a cancer therapy in clinical trials, while amlexanox (AMX) has been evaluated clinically for treatment of type II diabetes, nonalcoholic fatty liver disease, and obesity. In this review, we summarize advances in research into TBK1 signaling pathways and regulation, as well as recent studies on TBK1 in cancer pathogenesis. We also discuss the potential molecular mechanisms of targeting TBK1 for cancer treatment. We hope that our effort can help to stimulate the development of novel strategies for targeting TBK1 signaling in future approaches to cancer therapy.

Construction and Validation of Two Hepatocellular Carcinoma-Progression Prognostic Scores Based on Gene Set Variation Analysis

Background: Liver hepatocellular carcinoma (LIHC) remains a global health challenge with a low early diagnosis rate and high mortality. Therefore, finding new biomarkers for diagnosis and prognosis is still one of the current research priorities.

Methods: Based on the variation of gene expression patterns in different stages, the LIHC-development genes (LDGs) were identified by differential expression analysis. Then, prognosis-related LDGs were screened out to construct the LIHC-unfavorable gene set (LUGs) and LIHC-favorable gene set (LFGs). Gene set variation analysis (GSVA) was conducted to build prognostic scoring models based on the LUGs and LFGs. ROC curve analysis and univariate and multivariate Cox regression analysis were carried out to verify the diagnostic and prognostic utility of the two GSVA scores in two independent datasets. Additionally, the key LCGs were identified by the intersection analysis of the PPI network and univariate Cox regression and further evaluated their performance in expression level and prognosis prediction. Single-sample GSEA (ssGSEA) was performed to understand the correlation between the two GSVA enrichment scores and immune activity.

Result: With the development of LIHC, 83 LDGs were gradually upregulated and 247 LDGs were gradually downregulated. Combining with LIHC survival analysis, 31 LUGs and 32 LFGs were identified and used to establish the LIHC-unfavorable GSVA score (LUG score) and LIHC-favorable GSVA score (LFG score). ROC curve analysis and univariate/multivariate Cox regression analysis suggested the LUG score and LFG score could be great indicators for the early diagnosis and prognosis prediction. Four genes (ESR1, EHHADH, CYP3A4, and ACADL) were considered as the key LCGs and closely related to good prognosis. The frequency of TP53 mutation and copy number variation (CNV) were high in some LCGs. Low-LFG score patients have active metabolic activity and a more robust immune response. The high-LFG score patients characterized immune activation with the higher infiltration abundance of type I T helper cells, DC, eosinophils, and neutrophils, while the high-LUG score patients characterized immunosuppression with the higher infiltration abundance of type II T helper cells, TRegs, and iDC. The high- and low-LFG score groups differed significantly in immunotherapy response scores, immune checkpoints expression, and IC50 values of common drugs.

Conclusion: Overall, the LIHC-progression characteristic genes can be great diagnostic and prognostic signatures and the two GSVA score systems may become promising indices for guiding the tumor treatment of LIHC patients.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma

Purpose

Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC.

Patients and Methods

Various statistical methods such as Kaplan–Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1.

Results

QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages.

Conclusion

Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

Development and Validation of a Novel Hypoxia-Related Long Noncoding RNA Model With Regard to Prognosis and Immune Features in Breast Cancer

Background: Female breast cancer is currently the most frequently diagnosed cancer in the world. This study aimed to develop and validate a novel hypoxia-related long noncoding RNA (HRL) prognostic model for predicting the overall survival (OS) of patients with breast cancer. Methods: The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 200 hypoxia-related mRNAs were obtained from the Molecular Signatures Database. The co-expression analysis between differentially expressed hypoxia-related mRNAs and lncRNAs based on Spearman's rank correlation was performed to screen out 166 HRLs. Based on univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis in the training set, we filtered out 12 optimal prognostic hypoxia-related lncRNAs (PHRLs) to develop a prognostic model. Kaplan-Meier survival analysis, receiver operating characteristic curves, area under the curve, and univariate and multivariate Cox regression analyses were used to test the predictive ability of the risk model in the training, testing, and total sets. Results: A 12-HRL prognostic model was developed to predict the survival outcome of patients with breast cancer. Patients in the high-risk group had significantly shorter median OS, DFS (disease-free survival), and predicted lower chemosensitivity (paclitaxel, docetaxel) compared with those in the low-risk group. Also, the risk score based on the expression of the 12 HRLs acted as an independent prognostic factor. The immune cell infiltration analysis revealed that the immune scores of patients in the high-risk group were lower than those of the patients in the low-risk group. RT-qPCR assays were conducted to verify the expression of the 12 PHRLs in breast cancer tissues and cell lines. Conclusion: Our study uncovered dozens of potential prognostic biomarkers and therapeutic targets related to the hypoxia signaling pathway in breast cancer.

RPL19 Is a Prognostic Biomarker and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies, and the therapeutic outcome remains undesirable due to its recurrence and metastasis. Gene dysregulation plays a pivotal role in the occurrence and progression of cancer, and the molecular mechanisms are largely unknown.

Methods

The differentially expressed genes of HCC screened from the GSE39791 dataset were used to conduct weighted gene co-expression network analysis. The selected hub genes were validated in The Cancer Genome Atlas (TCGA) database and 11 HCC datasets from the Gene Expression Omnibus (GEO) database. Then, a tissue microarray comprising 90 HCC specimens and 90 adjacent normal specimens was used to validate the hub genes. Moreover, the Hallmark, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to identify enriched pathways. Then, we conducted the immune infiltration analysis.

Results

A total of 17 co-expression modules were obtained by weighted gene co-expression network analysis. The green, blue, and purple modules were the most relevant to HCC samples. Four hub genes, RPL19, RPL35A, RPL27A, and RPS12, were identified. Interestingly, we found that all four genes were highly expressed in HCC and that their high expression was related to a poor prognosis by analyzing the TCGA and GEO databases. Furthermore, we investigated RPL19 in HCC tissue microarrays and demonstrated that RPL19 was overexpressed in tumor tissues compared with non-tumor tissues (p = 0.016). Moreover, overexpression of RPL19 predicted a poor prognosis in hepatocellular carcinoma (p < 0.0007). Then, enrichment analysis revealed that cell cycle pathways were significantly enriched, and bile acid metabolism-related pathways were significantly down-regulated when RPL19 was highly expressed. Furthermore, immune infiltration analysis showed that immune response was suppressed.

Conclusion

Our study demonstrates that RPL19 may play an important role in promoting tumor progression and is correlated with a poor prognosis in HCC. RPL19 may serve as a promising biomarker and therapeutic target for the precise diagnosis and treatment of HCC in the future.