Hyaluronan Mediated Motility Receptor (HMMR) Encodes an Evolutionarily Conserved Homeostasis, Mitosis, and Meiosis Regulator Rather than a Hyaluronan Receptor

Adipocytes Promote Endometrial Cancer Progression Through Activation of the SIRT1-HMMR Signaling Axis

Adipocyte is a predominant component of the omental adipose tissue that influences the tumor microenvironment and increases the risk of endometrial cancer progression (EC), however, little is known about the underlying mechanism. In this study, using a co-culture model, we found that the adipocyte-EC cell interaction promoted SIRT1 signaling in vitro and in vivo xenograft mice models. Furthermore, immunostaining of SIRT1 protein showed significantly higher expression of SIRT1 in endometrial cancer patients than in normal endometria. RNA sequencing analysis revealed HMMR (hyaluronan-mediated motility receptor), an oncogene, as a downstream effector of SIRT1 in adipocyte-associated EC. Transient knockdown and chromatin immunoprecipitation assays showed that SIRT1 inhibition impedes transcription of the HMMR gene via FOXM1, and reduced expression of HMMR in co-cultured EC cells blocks AURKA activation via TPX2, leading to cell cycle arrest. This is the first study to report the positive correlation between SIRT1 and HMMR in EC patient tumors and might be used as a potential biomarker in EC. Notably, SIRT1 regulates HMMR expression in a FOXM1-dependent manner, and interfering with SIRT1 may provide a promising strategy for the management of endometrial cancer.

Integrated single-cell transcriptomic analyses identify a novel lineage plasticity-related cancer cell type involved in prostate cancer progression

BACKGROUND

Cancer cell plasticity is the ability of neoplastic cells to alter their identity and acquire new biological properties under microenvironmental pressures. In prostate cancer (PCa), lineage plasticity often results in therapy resistance and trans-differentiation to neuroendocrine (NE) lineage. However, identifying the cancer cells harboring lineage plasticity-related status remains challenging.

METHODS

Based on 13 multi-center human PCa bulk transcriptomic cohorts (samples = 3314) and 9 bulk transcriptomic datasets derived from PCa experimental models, we established an integrated lineage plasticity-related gene signature, termed LPSig. Leveraging this gene signature, AUCell enrichment analysis was applied to identify the cell population with high lineage plasticity from a comprehensive single-cell RNA-sequencing (scRNA-seq) meta-atlas assembled by us, which consisted of 10 public human PCa scRNA-seq datasets (samples = 93, cells = 222,529). Moreover, additional scRNA-seq dataset of human PCa, multiplex immunohistochemistry staining for human PCa tissues, in vitro and in vivo functional experiments, as well as qPCR and Western blot analyses were employed to validate our findings.

FINDINGS

We found that LPSig could finely capture the dynamics of tumor lineage plasticity throughout the progression of PCa, accurately estimating the status of lineage plasticity. Based on LPSig, we identified a previously undefined minority population of lineage plasticity-related PCa cells (LPCs) from the human PCa scRNA-seq meta-atlas assembled by this study. Furthermore, in-depth dissection revealed pivotal roles of LPCs in trans-differentiation, tumor recurrence, and poor patient survival during PCa progression. Furthermore, we identified HMMR as a representative cell surface marker for LPCs, which was validated using additional scRNA-seq datasets and multiplexed immunohistochemistry. Moreover, HMMR was transcriptionally inhibited by androgen receptor (AR), and was required for the aggressive adenocarcinoma features and NE phenotype.

INTERPRETATION

Our study uncovers a novel population of lineage plasticity-related cells with low AR activity, stemness-like traits, and elevated HMMR expression, that may facilitate poor prognosis in PCa.

FUNDING

This work was supported by National Key R&D Program of China (2022YFA0807000), National Natural Science Foundation of China (82160584), Advanced Prostate Cancer Diagnosis and Treatment Technology Innovation Team of Kunming Medical University (CXTD202216), and Reserve Talents of Young and Middle-aged Academic Leaders in Yunnan Province (202105AC160013).

Microarray analysis points to LMNB1 and JUN as potential target genes for predicting metastasis promotion by etoposide in colorectal cancer

Etoposide is a second-line chemotherapy agent widely used for metastatic colorectal cancer. However, we discovered that etoposide treatment induced greater motility potential in four colorectal cancer cell lines. Therefore, we used microarrays to test the mRNA of these cancer cell lines to investigate the mechanisms of etoposide promoting colorectal cancer metastasis. Differentially expressed genes (DEGs) were identified by comparing the gene expression profiles in samples from etoposide-treated cells and untreated cells in all four colorectal cancer cell lines. Next, these genes went through the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway analysis. Among the top 10 genes including the upregulated and downregulated, eight genes had close interaction according to the STRING database: FAS, HMMR, JUN, LMNB1, MLL3, PLK2, STAG1 and TBL1X. After etoposide treatment, the cell cycle, metabolism-related and senescence signaling pathways in the colorectal cancer cell lines were significantly downregulated, whereas necroptosis and oncogene pathways were significantly upregulated. We suggest that the differentially expressed genes LMNB1 and JUN are potential targets for predicting colorectal cancer metastasis. These results provide clinical guidance in chemotherapy, and offer direction for further research in the mechanism of colorectal cancer metastasis.

FOXM1 mediates methotrexate resistance in osteosarcoma cells by promoting autophagy

Osteosarcoma (OS) is a primary bone cancer mostly found in adolescents and elderly individuals. The treatment of OS is still largely dependent on traditional chemotherapy. However, the high incidence of drug resistance remains one of the greatest impediments to limiting improvements in OS treatment. Recent findings have indicated that the transcription factor FOXM1 plays an important role in various cancer-related events, especially drug resistance. However, the possible role of FOXM1 in the resistance of OS to methotrexate (MTX) remains to be explored. Here, we find that FOXM1, which confers resistance to MTX, is highly expressed in OS tissues and MTX-resistant cells. FOXM1 overexpression promotes MTX resistance by enhancing autophagy in an HMMR/ATG7-dependent manner. Importantly, silencing of FOXM1 or inhibiting autophagy reverses drug resistance. These findings demonstrate a new mechanism for FOXM1-induced MTX resistance and provide a promising target for improving OS chemotherapy outcomes.

Unveiling the mechanism of high sugar diet induced advanced glycosylation end products damage skin structure via extracellular matrix-receptor interaction pathway

BACKGROUND

AGEs accumulate in the skin as a result of a high-sugar diet and play an important role in the skin aging process.

OBJECTIVES

The aim of this study was to characterize the mechanism underlying the effect of a high-sugar diet on skin aging damage at a holistic level.

METHODS

We established a high-sugar diet mouse model to compare and analyze differences in physiological indexes. The effect of a high-sugar diet on skin aging damage was analyzed by means of a transcriptome study and staining of pathological sections. Furthermore, the differences in the protein expression of AGEs and ECM components between the HSD and control groups were further verified by immunohistochemistry.

RESULTS

The skin in the HSD group mice tended toward a red, yellow, dark, and deep color. In addition, the epidermis was irregular with anomalous phenomena, the epidermis was thinned, and the dermis lost its normal structure and showed vacuolated changes. Transcriptomics results revealed significant downregulation of the ECM-receptor interaction pathway, significant upregulation of the expression of AGEs and significant downregulation of the expression levels of COLI, FN1, LM5, and TNC, among others ECM proteins and ECM receptors.

CONCLUSIONS

High-sugar diets cause skin aging damage by inducing the accumulation of AGEs, disrupting the expression of ECM proteins and their receptors, and downregulating the ECM-receptor interaction pathway, which affects cellular behavioral functions such as cell proliferation, migration, and adhesion, as well as normal skin tissue structure.

Comparative proteome analysis revealed potential biomarkers and the underlying immune mechanisms in Vibrio-resistant hybrid grouper, Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂

Vibrio alginolyticus is the causative agent of vibriosis, a common bacterial infection in grouper aquaculture that is associated with the development of haemorrhagic and non-haemorrhagic ulcerations on the fish. In the present study, comparative proteome analysis was performed on serum samples from Vibrio-resistant and Vibrio-susceptible grouper. Samples were analysed using high-throughput LC-MS/MS and identified 2770 unique peptides that corresponded to 344 proteins. Subsequent analysis identified 21 proteins that were significantly up-regulated in the resistant group compared to the control and the susceptible groups. Those proteins are associated with immunostimulatory effects, signalling and binding cascade, metabolism, and maintaining tissue integrity and physiological condition. Besides, potential protein biomarkers related to the immune system were identified, which could be associated with the disease-resistant phenotype. These data provide insights into the underlying immune mechanism of hybrid groupers upon Vibrio sp. infection.

HMMR triggers immune evasion of hepatocellular carcinoma by inactivation of phagocyte killing

Hepatocellular carcinoma (HCC) acquires an immunosuppressive microenvironment, leading to unbeneficial therapeutic outcomes. Hyaluronan-mediated motility receptor (HMMR) plays a crucial role in tumor progression. Here, we found that aberrant expression of HMMR could be a predictive biomarker for the immune suppressive microenvironment of HCC, but the mechanism remains unclear. We established an HMMR-/- liver cancer mouse model to elucidate the HMMR-mediated mechanism of the dysregulated "don't eat me" signal. HMMR knockout inhibited liver cancer growth and induced phagocytosis. HMMRhigh liver cancer cells escaped from phagocytosis via sustaining CD47 signaling. Patients with HMMRhighCD47high expression showed a worse prognosis than those with HMMRlowCD47low expression. HMMR formed a complex with FAK/SRC in the cytoplasm to activate NF-κB signaling, which could be independent of membrane interaction with CD44. Notably, targeting HMMR could enhance anti-PD-1 treatment efficiency by recruiting CD8+ T cells. Overall, our data revealed a regulatory mechanism of the "don't eat me" signal and knockdown of HMMR for enhancing anti-PD-1 treatment.

Hyaluronic Acid Interacting Molecules Mediated Crosstalk between Cancer Cells and Microenvironment from Primary Tumour to Distant Metastasis

Hyaluronic acid (HA) is a prominent component of the extracellular matrix, and its interactions with HA-interacting molecules (HAIMs) play a critical role in cancer development and disease progression. This review explores the multifaceted role of HAIMs in the context of cancer, focusing on their influence on disease progression by dissecting relevant cellular and molecular mechanisms in tumour cells and the tumour microenvironment. Cancer progression can be profoundly affected by the interactions between HA and HAIMs. They modulate critical processes such as cell adhesion, migration, invasion, and proliferation. The TME serves as a dynamic platform in which HAIMs contribute to the formation of a unique niche. The resulting changes in HA composition profoundly influence the biophysical properties of the TME. These modifications in the TME, in conjunction with HAIMs, impact angiogenesis, immune cell recruitment, and immune evasion. Therefore, understanding the intricate interplay between HAIMs and HA within the cancer context is essential for developing novel therapeutic strategies. Targeting these interactions offers promising avenues for cancer treatment, as they hold the potential to disrupt critical aspects of disease progression and the TME. Further research in this field is imperative for advancing our knowledge and the treatment of cancer.

Coupled scRNA-seq and Bulk-seq reveal the role of HMMR in hepatocellular carcinoma

Background

Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear.

Methods

The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks. Recursive partitioning analysis (RPA) was used to re-stage HCC patients. The IC50 values of various drugs were evaluated using the "pRRophetic" package. In addition, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm HMMR expression in an HCC tissue microarray. Flow cytometry (FCM) and cloning, Edu and wound healing assays were used to explore the capacity of HMMR to regulate HCC tumour.

Results

Multiple cohort studies and qRT-PCR demonstrated that HMMR was overexpressed in HCC tissue compared with normal tissue. In addition, HMMR had excellent diagnostic performance. HMMR knockdown inhibited the proliferation and migration of HCC cells in vitro. Moreover, high HMMR expression was associated with "G2M checkpoint" and "E2F targets" in bulk RNA and scRNA-seq, and FCM confirmed that HMMR could regulate the cell cycle. In addition, HMMR was involved in the regulation of the tumour immune microenvironment via immune cell infiltration and intercellular interactions. Furthermore, HMMR was positively associated with genomic heterogeneity with patients with high HMMR expression potentially benefitting more from immunotherapy. Moreover, HMMR was associated with poor prognosis in patients with HCC and the re-staging by recursive partitioning analysis (RPA) gave a good prognosis prediction value and could guide chemotherapy and targeted therapy.

Conclusion

The results of the present study show that HMMR could play a role in the diagnosis, prognosis, and treatments of patients with HCC based on bulk RNA-seq and scRAN-seq analyses and is a promising molecular marker for HCC.

Identification of key genes and molecular pathways associated with claw regeneration in mud crab (Scylla paramamosain)

The mud crab (Scylla paramamosain) possesses extensive regenerative abilities, enabling it to replace missing body parts, including claws, legs, and even eyes. Studying the genetic and molecular mechanisms underlying regenerative ability in diverse animal phyla has the potential to provide new insights into regenerative medicine in humans. In the present study, we performed mRNA sequencing to reveal the genetic mechanisms underlying the claw regeneration in mud crab. Several differentially expressed genes (DEGs) were expressed in biological pathways associated with cuticle synthase, collagen synthase, tissue regeneration, blastema formation, wound healing, cell cycle, cell division, and cell migration. The top GO enrichment terms were microtubule-based process, collagen trimer, cell cycle process, and extracellular matrix structural constituent. The most enriched KEGG pathways were ECM-receptor interaction and focal adhesion. The genes encoding key functional proteins, such as collagen alpha, cuticle protein, early cuticle protein, arthrodial cuticle protein, dentin sialophosphoprotein (DSPP), epidermal growth factor receptor (EGFR), kinesin family member C1 (KIFC1), and DNA replication licensing factor mcm2-like (MCM2) were the most significant and important DEGs suspected to participate in claw regeneration. The findings of this research offer a comprehensive and insightful understanding of the genetic and molecular mechanisms underlying claw regeneration in S. paramamosain. By elucidating the specific genes and molecular pathways implicated in this process, our study contributes significantly to the broader field of regenerative biology and offers potential avenues for further exploration in crustacean limb regeneration.

FIGNL1 Promotes Hepatocellular Carcinoma Formation via Remodeling ECM-receptor Interaction Pathway Mediated by HMMR

BACKGROUND

The development of novel biomarkers is crucial for the treatment of HCC. In this study, we investigated a new molecular therapeutic target for HCC. Fidgetin-like 1 (FIGNL1) has been reported to play a vital role in lung adenocarcinoma. However, the potential function of FIGNL1 in HCC is still unknown.

OBJECTIVE

This study aims to investigate the key regulatory mechanisms of FIGNL1 in the formation of HCC.

METHODS

The regulatory effect of FIGNL1 on HCC was studied by lentivirus infection. In vitro, the effects of FIGNL1 on the proliferation, migration and apoptosis of cells were investigated by CCK8, colony formation assay, transwell and flow cytometry. Meanwhile, the regulation of FIGNL1 on HCC formation in vivo was studied by subcutaneous transplanted tumors. In addition, using transcriptome sequencing technology, we further explored the specific molecular mechanism of FIGNL1 regulating the formation of HCC.

RESULTS

Functionally, we demonstrated that FIGNL1 knockdown significantly inhibited HCC cell proliferation, migration and promoted cell apoptosis in vitro. Similarly, the knockdown of FIGNL1 meaningfully weakened hepatocarcinogenesis in nude mice. Transcriptome sequencing revealed that FIGNL1 affected the expression of genes involved in extracellular matrix-receptor (ECM-receptor) interaction pathway, such as hyaluronan mediated motility receptor (HMMR). Further validation found that overexpression of HMMR based on knockdown FIGNL1 can rescue the expression abundance of related genes involved in the ECM-receptor interaction pathway.

CONCLUSION

Our study revealed that FIGNL1 could modulate the ECM-receptor interaction pathway through the regulation of HMMR, thus regulating the formation of HCC.

Comprehensive Analysis Identifies Hyaluronan Mediated Motility Receptor and Cell Division Cycle 25C as Potential Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, but its pathogenic mechanisms remain unclear. This study aimed to identify the potential biomarkers underlying the diagnosis and treatment of HNSCC.

METHODS

Weighted gene co-expression network analysis (WGCNA) followed by pathway enrichment analysis, analysis of infiltrating immune cells, survival analysis, and methylation analysis were applied to identify the potential hub genes underlying the prognosis of HNSCC. The expression of hub genes was validated by immunofluorescence staining.

RESULTS

A total of 10,274 differentially expressed genes (DEGs) were identified. Through WGCNA, the yellow module (R2 = 0.33, P = 2e-14) was confirmed to be the most significantly associated with the histological grade of HNSCC, and the "Cell Cycle" proved to be the most enriched signaling pathway. Based on the results of survival analysis and immune cell infiltration, 10 hub genes (HMMR, CENPK, AURKA, CDC25C, FEN1, CKS1B, MAJIN, PCLAF, SPC25, and STAG3) were identified. Eight of these (excluding MAJIN and STAG3) were confirmed by performing survival analysis using another dataset (GSE41613). Further, we identified 4 methylation loci in 3 hub genes (cg15122828 and cg20554926 in HMMR, cg12519992 in CDC25C, and cg2655739 in KIAA0101/PCLAF) as being significantly related to survival. Finally, we demonstrated the high mRNA and protein expression of HMMR and CDC25C in HNSCC patients.

CONCLUSION

Two real hub genes (HMMR and CDC25C) and 3 methylation loci were identified that could potentially serve as prognostic and therapeutic targets for HNSCC, which is significant for studying the pathological mechanisms underlying HNSCC and for developing novel therapies for this disease.

Periportal hepatocyte proliferation at midgestation governs maternal glucose homeostasis in mice

The maternal liver is challenged by metabolic demands throughout pregnancy. However, hepatocyte dynamics and their physiological significance in pregnancy remain unclear. Here, we show in mice that hepatocyte proliferation is spatiotemporally regulated in each liver lobular zone during pregnancy, with transient proliferation of periportal and pericentral hepatocytes during mid and late gestation, respectively. Using adeno-associated virus (AAV)-8-mediated expression of the cell cycle inhibitor p21 in hepatocytes, we show that inhibition of hepatocyte proliferation during mid, but not late, gestation impairs liver growth. Transcriptionally, genes involved in glucose/glycogen metabolism are downregulated in late pregnancy when midgestational hepatocyte proliferation is attenuated. In addition, hepatic glycogen storage is abolished, with concomitant elevated blood glucose concentrations, glucose intolerance, placental glycogen deposition, and fetal overgrowth. Laser capture microdissection and RNA-seq analysis of each liver lobular zone show zone-specific changes in the transcriptome during pregnancy and identify genes that are periportally expressed at midgestation, including the hyaluronan-mediated motility receptor (Hmmr). Knockdown of Hmmr in hepatocytes by AAV8-shHmmr suppresses periportal hepatocyte proliferation at midgestation and induces impaired hepatic glycogen storage, glucose intolerance, placental glycogen deposition and fetal overgrowth. Our results suggest that periportal hepatocyte proliferation during midgestation is critical for maternal glycogen metabolism and fetal size.

Hmmr Acts as a Key Regulator in the ADSCs Proliferation and Mitosis

Obesity is a common chronic health problem that requires lifelong efforts for the successful treatment. The proliferation of ADSCs is an essential step in the development of obesity. Identifying key regulators of ADSCs will be a novel strategy for adipogenesis inhibition and obesity prevention. In this study, transcriptomes of 15532 ADSCs were firstly profiled by single cell RNA-sequencing. On the basis of gene expression patterns, 15 cell subpopulations (six defined cell types) were distinguished. A subpopulation was identified as CD168⁺ ADSCs, and it was demonstrated to play a vital role in ADSCs proliferation. Furthermore, Hmmr, a specific marker gene of CD168⁺ ADSCs was found to be a critical gene associated with ADSCs proliferation and mitosis. Hmmr knockout resulted that ADSCs growth nearly arrested and aberrant nuclear division occurred. Finally, it was revealed that Hmmr promoted ADSCs proliferation through the extracellular signal-regulated kinase 1/2 signaling pathway. This study identified Hmmr as a key regulator in ADSCs proliferation and mitosis, and suggested that Hmmr may be a novel target for obesity prevention.

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma

BACKGROUND

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC).

METHODS

From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression.

RESULTS

Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue.

CONCLUSION

Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

HMMR promotes prostate cancer proliferation and metastasis via AURKA/mTORC2/E2F1 positive feedback loop

Although dysregulated HMMR is linked to prostate cancer (PCa) prognosis, the precise mechanisms remain unclear. Here, we sought to elucidate the role of HMMR in PCa progression as well as underlying mechanism. Herein, we found that upregulation of HMMR frequently observed in PCa samples and was associated with poor prognosis. Additionally, HMMR significantly promoted PCa proliferation and metastasis through gain- and loss-of function approaches in vitro and in vivo. Mechanistically, HMMR may interact with AURKA and elevated AURKA protein level through inhibiting ubiquitination-mediated degradation, which subsequently activated mTORC2/AKT pathway to ensure the reinforcement of PCa progression. Moreover, upregulated E2F1 caused from sustained activation of mTORC2/AKT pathway in turn function as transcription factor to promote HMMR transcription, thereby forming a positive feedback loop to trigger PCa progression. Importantly, administration of the mTOR inhibitor partially antagonised HMMR-mediated PCa progression in vivo. In summary, we not only reveal a novel possible post-translation mechanism mediated by HMMR involved in AURKA regulation, but also describe a positive feedback loop that contributes to PCa deterioration, suggesting HMMR may serve as a potential promising therapeutic target in PCa.

HELLPAR/RRM2 axis related to HMMR as novel prognostic biomarker in gliomas

BACKGROUND

Gliomas are the most frequent type of central nervous system tumor, accounting for more than 70% of all malignant CNS tumors. Recent research suggests that the hyaluronan-mediated motility receptor (HMMR) could be a novel potential tumor prognostic marker. Furthermore, mounting data has highlighted the important role of ceRNA regulatory networks in a variety of human malignancies. The complexity and behavioural characteristics of HMMR and the ceRNA network in gliomas, on the other hand, remained unknown.

METHODS

Transcriptomic expression data were collected from TCGA, GTEx, GEO, and CGGA database.The relationship between clinical variables and HMMR was analyzed with the univariate and multivariate Cox regression. Kaplan-Meier method was used to assess OS. TCGA data are analyzed and processed, and the correlation results obtained were used to perform GO, GSEA, and ssGSEA. Potentially interacting miRNAs and lncRNAs were predicted by miRWalk and StarBase.

RESULTS

HMMR was substantially expressed in gliomas tissues compared to normal tissues. Multivariate analysis revealed that high HMMR expression was an independent predictive predictor of OS in TCGA and CGGA. Functional enrichment analysis found that HMMR expression was associated with nuclear division and cell cycle. Base on ssGSEA analysis, The levels of HMMR expression in various types of immune cells differed significantly. Bioinformatics investigation revealed the HEELPAR-hsa-let-7i-5p-RRM2 ceRNA network, which was linked to gliomas prognosis. And through multiple analysis, the good predictive performance of HELLPAR/RRM2 axis for gliomas patients was confirmed.

CONCLUSION

This study provides multi-layered and multifaceted evidence for the importance of HMMR and establishes a HMMR-related ceRNA (HEELPAR-hsa-let-7i-5p-RRM2) overexpressed network related to the prognosis of gliomas.

In silico analysis revealed the potential circRNA-miRNA-mRNA regulative network of non-small cell lung cancer (NSCLC)

BACKGROUND

The primary source of death in the world is non-small cell lung cancer (NSCLC). However, NSCLCs pathophysiology is still not completely understood. The current work sought to study the differential expression of mRNAs involved in NSCLC and their interactions with miRNAs and circRNAs.

METHODS

We utilized three microarray datasets (GSE21933, GSE27262, and GSE33532) from the GEO NCBI database to identify the differentially expressed genes (DEGs) in NSCLC. We employed DAVID Functional annotation tool to investigate the underlying GO biological process, molecular functions, and KEGG pathways involved in NSCLC. We performed the Protein-protein interaction (PPI) network, MCODE, and CytoHubba analysis from Cytoscape software to identify the significant DEGs in NSCLC. We utilized miRnet to anticipate and build interaction between miRNAs and mRNAs in NSCLC and ENCORI to predict the miRNA-circRNA relationships and build the ceRNA regulatory network. Finally, we executed the gene expression and Kaplan-Meier survival analysis to validate the significant DEGs in the ceRNA network utilizing TCGA NSCLC and GEPIA data.

RESULTS

We revealed a total of 156 overlapped DEGs (47 upregulated and 109 downregulated genes) in NSCLC. The PPI network, MCODE, and CytoHubba analysis revealed 12 hub genes (cdkn3, rrm2, ccnb1, aurka, nuf2, tyms, kif11, hmmr, ccnb2, nek2, anln, and birc5) that are associated with NSCLC. We identified that these 12 genes encode 12 mRNAs that are strongly linked with 8 miRNAs, and further, we revealed that 1 circRNA was associated with this 5 miRNA. We constructed the ceRNAs network that contained 1circRNA-5miRNAs-7mRNAs. The expression of these seven significant genes in LUAD & LUSC (NSCLC) was considerably higher in the TCGA database than in normal tissues. Kaplan-Meier survival plot reveals that increased expression of these hub genes was related to a poor survival rate in LUAD.

CONCLUSION

Overall, we developed a circRNA-miRNA-mRNA regulation network to study the probable mechanism of NSCLC.

Centrosome Amplification Is a Potential Molecular Target in Paediatric Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most common form of cancer in children, with most cases arising from fetal B cell precursor, termed B-ALL. Here, we use immunofluorescence analysis of B-ALL cells to identify centrosome amplification events that require the centrosome clustering pathway to successfully complete mitosis. Our data reveals that primary human B-ALL cells and immortal B-ALL cell lines from both human and mouse sources show defective bipolar spindle formation, abnormal mitotic progression, and cell death following treatment with centrosome clustering inhibitors (CCI). We demonstrate that CCI-refractory B-ALL cells exhibit markers for increased genomic instability, including DNA damage and micronuclei, as well as activation of the cyclic GMP-AMP synthase (cGAS)-nuclear factor kappa B (NF-κB) signalling pathway. Our analysis of cGAS knock-down B-ALL clones implicates cGAS in the sensitivity of B-ALL cells to CCI treatment. Due to its integral function and specificity to cancer cells, the centrosome clustering pathway presents a powerful molecular target for cancer treatment while mitigating the risk to healthy cells.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

Development and validation of a combined metabolism and immune prognostic model in lung adenocarcinoma

Background

Tumor metabolism and immune response can affect the biological behavior of tumor cells. There is an obvious relationship between glycolysis and immune response. However, the association between metabolism and immune response and prognosis in lung adenocarcinoma (LUAD) has not yet been examined in a comprehensive and detailed manner. The establishment of reliable models for predicting the prognosis of LUAD based on glycolysis ability and immune status is still highly anticipated.

Methods

The expression of genes were obtained from online databases, and the differentially expressed genes in LUAD tissues and adjacent tissues were identified. We used LUAD samples in The Cancer Genome Atlas (TCGA) database as training set and the Gene Expression Omnibus (GEO) databases as validation sets. The best predictive model was constructed using least absolute selection and shrinkage operator (LASSO) regression and Cox regression. The receiver operator characteristic (ROC) curve is used to verify the accuracy of the model. The expression status of the Glycolysis-related genes (GRGs) and the status of the immune cells in LUCD patients were further analyzed. The protein levels of the 3 identified genes were then tested in LUAD patients.

Results

We identified 3 GRGs and immune-related genes (i.e., fibroblast growth factor 2, hyaluronan-mediated motor receptor, and nuclear receptor 0B2) and constructed a stable comprehensive index of glycolysis and immunity (CIGI) prediction model. The validation results for this CIGI model were quite stable across different datasets and patient subgroups and the CIGI score can be included as an independent prognostic factor for LUAD patients. The area under the curve (AUC) values of 1-, 3- and 5-year of the finally established nomogram model are 0.767, 0.735 and 0.769. Further analysis showed that LUAD patients in the low-risk group had lower levels of glycolytic gene expression than those in the high-risk group and exhibited an immunosuppressed state. Finally, hyaluronan-mediated motor receptor may play a role in inhibiting cancer, while fibroblast growth factor 2 and nuclear receptor 0B2 may play roles in promoting cancer.

Conclusions

In this study, we established a new prognostic prediction model for LUAD patients that combines glycolysis ability and immune status.

Development and validation of an epithelial–mesenchymal transition-related gene signature for predicting prognosis

BACKGROUND

Currently, there are many therapeutic methods for lung adenocarcinoma (LUAD), but the 5-year survival rate is still only 15% at later stages. Epithelial– mesenchymal transition (EMT) has been shown to be closely associated with local dissemination and subsequent metastasis of solid tumors. However, the role of EMT in the occurrence and development of LUAD remains unclear.

AIM

To further elucidate the value of EMT-related genes in LUAD prognosis.

METHODS

Univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were applied to establish and validate a new EMT-related gene signature for predicting LUAD prognosis. The risk model was evaluated by Kaplan–Meier survival analysis, principal component analysis, and functional enrichment analysis and was used for nomogram construction. The potential structures of drugs to which LUAD is sensitive were discussed with respect to EMT-related genes in this model.

RESULTS

Thirty-three differentially expressed genes related to EMT were found to be highly associated with overall survival (OS) by using univariate Cox regression analysis (log2FC ≥ 1, false discovery rate < 0.001). A prognostic signature of 7 EMT-associated genes was developed to divide patients into two risk groups by high or low risk scores. Kaplan–Meier survival analysis showed that the OS of patients in the high-risk group was significantly poorer than that of patients in the low-risk group (P < 0.05). Multivariate Cox regression analysis showed that the risk score was an independent risk factor for OS (HR > 1, P < 0.05). The results of receiver operator characteristic curve analysis suggested that the 7-gene signature had a perfect ability to predict prognosis (all area under the curves > 0.5).

CONCLUSION

The EMT-associated gene signature classifier could be used as a feasible indicator for predicting OS.

Identification of Co-Expression Modules and Genes Associated With Tumor Progression in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is a common head-and-neck cancer with a deficiency of early diagnosis and poor prognosis. To identify potential diagnostic and prognostic markers of OSCC, we firstly used weighted gene co-expression network analysis (WGCNA) to build a co-expression module from GSE42743. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on specified units from selected modules utilizing Database for Annotation, Visualization, and Integrated Discovery (DAVID). Additionally, we identified and validate hub genes of these specified modules from multiple datasets like GEPIA and TCGA. In total 16 co-expression modules were built by 17,238 genes of 74 tumor samples utilizing WGCNA. Through pathway and functional enrichment analysis, the turquoise module was most firmly relevant to the cell cycle, oocyte meiosis, and p53 signaling pathway. Hub genes VRK1, NUP37, HMMR, SPC25, and RUVBL1 were identified to be related to oral cancer at both molecular level and clinical levels. The expressions of these genes differed in tumor tissues and normal tissues. Meanwhile, patients with high hub gene expression had a poor prognosis clinically. To conclude, five hub genes were identified to be relevant to oral cancer from the molecular level and the clinical level. Therefore, the detection of these genes was of great significance. They can be regarded as diagnostic and prognostic biomarkers for oral cancer. Also, they could shed light on the improvement of patients’ overall survival and prognosis, which needs further analysis in the future.

The role of RHAMM in cancer: Exposing novel therapeutic vulnerabilities

Receptor for hyaluronic acid-mediated motility (RHAMM) is a cell surface receptor for hyaluronic acid that is critical for cell migration and a cell cycle protein involved in microtubule assembly and stability. These functions of RHAMM are required for cellular stress responses and cell cycle progression but are also exploited by tumor cells for malignant progression and metastasis. RHAMM is often overexpressed in tumors and is an independent adverse prognostic factor for a number of cancers such as breast and prostate. Interestingly, pharmacological or genetic inhibition of RHAMM in vitro and in vivo ablates tumor invasiveness and metastatic spread, implicating RHAMM as a potential therapeutic target to restrict tumor growth and improve patient survival. However, RHAMM’s pro-tumor activity is dependent on its subcellular distribution, which complicates the design of RHAMM-directed therapies. An alternative approach is to identify downstream signaling pathways that mediate RHAMM-promoted tumor aggressiveness. Herein, we discuss the pro-tumoral roles of RHAMM and elucidate the corresponding regulators and signaling pathways mediating RHAMM downstream events, with a specific focus on strategies to target the RHAMM signaling network in cancer cells.

A Novel Risk Score Model of Lactate Metabolism for Predicting over Survival and Immune Signature in Lung Adenocarcinoma

Simple Summary

Since the discovery of the WarBurg effect, the veil of the tumorigenic role of lactic acid has been gradually revealed. Recently, it was proposed that lactic acid that is produced by tumor cells was secreted into the extracellular space to create immunosuppressive tumor microenvironment (TME) in a variety of ways. However, the intersection genes and the association with immunotherapy are unclear. At present, we identified six lactate-metabolism-associated genes, which were thought to enable tumor progression, that were related to LUAD immunotherapy and we constructed an LAR-score risk model.

Abstract

Background: The role of lactate acid in tumor progression was well proved. Recently, it was found that lactate acid accumulation induced an immunosuppressive microenvironment. However, these results were based on a single gene and it was unclear that lactate acid genes were associated with immunotherapy and able to predict overall survival. Methods: Genes and survival data were acquired from TCGA, GEO and GENECARDS. PCA and TSNE were used to distinguish sample types according to lactate metabolism-associated gene expression. A Wilcox-test examined the expression differences between normal and tumor samples. The distribution in chromatin and mutant levels were displayed by Circo and MAfTools. The lactate metabolism-associated gene were divided into categories by consistent clustering and visualized by Cytoscape. Immune cell infiltration was evaluated by CIBERSORT and LM22 matrix. Enrichment analysis was performed by GSVA. We used the ConsensusClusterPlus package for consistent cluster analysis. A prognostic model was constructed by Univariate Cox regression and Lasso regression analysis. Clinical specimens were detected their expression of genes in model by IHC. Results: Most lactate metabolism-associated gene were significantly differently expressed between normal and tumor samples. There was a strong correlation between the expression of lactate metabolism-associated gene and the abundance of immune cells. We divided them into two clusters (lactate.cluster A,B) with significantly different survival. The two clusters showed a difference in signal, immune cells, immune signatures, chemokines, and clinical features. We identified 162 differential genes from the two clusters, by which the samples were divided into three categories (gene.cluster A,B,C). They also showed a difference in OS and immune infiltration. Finally, a risk score model that was composed of six genes was constructed. There was significant difference in the survival between the high and low risk groups. ROC curves of 1, 3, 5, and 10 years verified the model had good predictive efficiency. Gene expression were correlated with ORR and PFS in patients who received anti-PD-1/L1. Conclusion: The lactate metabolism-associated genes in LUAD were significantly associated with OS and immune signatures. The risk scoring model that was constructed by us was able to well identify and predict OS and were related with anti-PD-1/L1 therapy outcome.

The Genetic Association Identified Between Intervertebral Disc Degeneration and Associated Risk Factors Based on a Systems Biology Approach

STUDY DESIGN

Genetic cross-over study of intervertebral disc degeneration (IDD) and its associated risk factors.

OBJECTIVE

The purpose is to identify molecular biomarkers that may be involved in the IDD process and to provide effective recommendations in combination with drug analysis via systems biology methods.

SUMMARY OF BACKGROUND DATA

The pathogenesis and genetic links of IDD are still unclear. Related research is mainly based on a single data set or gene, and the impact of related risk factors on IDD is often ignored.

METHODS

Identifying disease-associated biomarkers and therapeutic targets through a systems biology approach that Integrative network-based gene and multi-omics analysis. In this study, the differential expression of genes was analyzed through NCBI datasets, followed by enrichment analysis. The central protein was identified through the establishment of protein-protein interaction (PPI) network. Key genes were screened out by VENN diagram and reasonable suggestions were put forward based on gene-chemical drug analysis.

RESULTS

The IDD database analysis revealed 669 differentially expressed genes (DEGs) which were 22, 26, 168, 5, 38, 36, and 16 common DEGs with AG, SM, DEP, NAD, CED, OB, and HFD, respectively. GO and KEGG enrichment analysis may reveal the pathway by which these DEGs were involved. PPI network identified 10 central proteins including CCNB1, RETN, HMMR, BUB1, MPO, OIP5, HP, KIF11, BUB1B, and CDC25A. Three key genes BUB1, BUB1B, and CCNB1 were screened out and their expression might be related to the pathogenesis of IDD. According to the three chemical Dexamethasone, Nicotine, and Resvera-trol obtained from the analysis of genes-chemical drugs, reasonable treatment suggestions were put forward.

CONCLUSION

Genetic association between IDD and risk factors in the general population was revealed by association network. Important gene-related molecular pathways and chemical drugs closely related to IDD have been found. Further study can provide guidance for the treatment and prognosis of IDD.Level of Evidence: N/A.

Identification and construction of a 13-gene risk model for prognosis prediction in hepatocellular carcinoma patients

We attempted to screen out the feature genes associated with the prognosis of hepatocellular carcinoma (HCC) patients through bioinformatics methods, to generate a risk model to predict the survival rate of patients. Gene expression information of HCC was accessed from GEO database, and differentially expressed genes (DEGs) were obtained through the joint analysis of multi-chip. Functional and pathway enrichment analyses of DEGs indicated that the enrichment was mainly displayed in biological processes such as nuclear division. Based on TCGA-LIHC data set, univariate, LASSO, and multivariate Cox regression analyses were conducted on the DEGs. Then, 13 feature genes were screened for the risk model. Also, the hub genes were examined in our collected clinical samples and GEPIA database. The performance of the risk model was validated by Kaplan-Meier survival analysis and receiver operation characteristic (ROC) curves. While its universality was verified in GSE76427 and ICGC (LIRI-JP) validation cohorts. Besides, through combining patients' clinical features (age, gender, T staging, and stage) and risk scores, univariate and multivariate Cox regression analyses revealed that the risk score was an effective independent prognostic factor. Finally, a nomogram was implemented for 3-year and 5-year overall survival prediction of patients. Our findings aid precision prediction for prognosis of HCC patients.

NcRNA-Mediated High Expression of HMMR as a Prognostic Biomarker Correlated With Cell Proliferation and Cell Migration in Lung Adenocarcinoma

Background

Hyaluronan-mediated motility receptor (HMMR) plays a pivotal role in cell proliferation in various cancers, including lung cancer. However, its function and biological mechanism in lung adenocarcinoma (LUAD) remain unclear.

Methods

Data on HMMR expression from several public databases were extensively analyzed, including the prognosis of HMMR in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using DAVID and gene set enrichment analysis (GSEA) software. The correlation between HMMR expression and immune cell infiltration was analyzed in the Tumor Immune Estimation Resource (TIMER) database, and the gene and protein networks were examined using the GeneMANIA and STRING databases. Experimentally, the expression of HMMR in LUAD and lung cancer cell lines was determined using immunohistochemistry and quantitative RT-PCR assays. Besides, the function of HMMR on cancer cell proliferation and migration was examined using cell growth curve and colony formation, Transwell, and wound healing assays.

Results

In this study, we found that HMMR was elevated in LUAD and that its high expression was associated with poor clinicopathological features and adverse outcomes in LUAD patients. Furthermore, our results demonstrated that the expression of HMMR was positively correlated with immune cell infiltration and immune modulation. Interestingly, diverse immune cell infiltration affects the prognosis of LUAD. In the functional assay, depletion of HMMR significantly repressed the cancer cell growth and migration of LUAD. Mechanically, we found that that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR in LUAD. Depletion of TMPO-AS1 and overexpression of let-7b-5p could result in the decreased expression of HMMR in LUAD cells. Furthermore, we found that TMPO-AS1 was positively correlated with HMMR, yet negatively correlated with let-7b-5p expression in LUAD.

Conclusions

Our findings elucidated that the DNA methylation/TMPO-AS1/let-7b-5p axis mediated the high expression of HMMR, which may be considered as a biomarker to predict prognosis in LUAD.

The critical role of B4GALT4 in promoting microtubule spindle assembly in HCC through the regulation of PLK1 and RHAMM expression

Beta 1,4-galactosyltransferase (B4GALT)-family glycosyltransferases are involved in multiple biological processes promoting cancer progression, regulating the dynamic network of cancer cell proliferation and apoptosis, and are associated with metastasis. However, their roles in the dysregulation of expressions and functions in hepatocellular carcinoma (HCC) remain unclear. Herein, bioinformatic approaches have been applied to investigate their expression profiles, and to obtain correlations between gene expressions and clinicopathological parameters as well as downstream target genes in HCC. Multiple databases were used to screen the expressions of B4GALT family members in tumor tissues, and to evaluate their prognostic value among HCC patients in different aspects. Results indicated an overall upregulation of B4GALTs' transcription levels in tumor tissues and a strong correlation with poor prognosis. Through Gene Ontology analysis, gene set enrichment analysis, and verification of single-cell RNA sequencing data, we established a connection between the B4GALT family and microtubule spindle assembly, which particularly highlighted the role of B4GALT4 in this phenomenon. B4GALT4 knockdown downregulated the production of lumican, and repressed the expressions of polo-like kinase 1 and RHAMM by regulating the transforming growth factor-beta pathway, thus suggesting that B4GALT4 is a critical promotor for HCC. We believe that these studies will provide valuable insight into the role of B4GALT family members in HCC and lead to the development of new strategies to improve the outcomes for patients with HCC.

Role of hyaluronan mediated motility receptor gene in oral squamous cell carcinoma and clinical prognosis

OBJECTIVES

To screen genes related to the prognosis of oral squamous cell carcinoma (OSCC), and to explore its role and mechanism in the occurrence and development of OSCC.

METHODS

The data and the biological information in 330 OSCC tumor samples with head and neck squamous cell carcinoma (HNSCC) (OSCC group) and 37 normal samples (normal sample group) were screened and included, which came from the cancer genome atlas (TCGA) database. The differentially expressed genes were screened out by biological information analysis between the 2 groups. Furthermore, according to the tumor T grade (T1+T2 group: 114 cases, T3+T4 group: 216 cases), metastasis (positive group: 163 cases, negative group: 167 cases) and pathological grade (G1+G2 group: 244 cases, G3 +G4 group: 86 cases), the samples were divided into different groups respectively, and the differential genes were obtained separately, then the intersections of the differential expressed genes related to the prognosis of OSCC were screened. The different gene with the largest different multiples [hyaluronan mediated motility receptor (HMMR)] was selected for the next step in order to explore the relationship between HMMR and clinical grading (Stage I+II group: 69 cases, Stage III +IV group: 261 cases), as well as the relationship between T grade, metastasis and pathological grade. According to the median value of HMMR expression, the samples were divided into a high expression group and a low expression group (high expression group: 165 cases, low expression group: 165 cases); Kaplan-Meier survival analysis was used to explore the relationship between HMMR expression and prognosis. Tumor tissue specimens and corresponding normal oral mucosal tissue specimens in 50 OSCC patients, who underwent surgery in the First Affiliated Hospital of Hunan University of Traditional Chinese Medicine from January 2014 to January 2016, were collected. Real-time RT-PCR and Western blotting and immunohistochemistry were used to verify the bioinformatics analysis results. Kaplan-Meier survival analysis was used to examine the relationship between the positive and negative expression of HMMR immunohistochemical staining (positive group: 32 cases, negative group: 18 cases) and prognostic related factors, and Cox regression analysis model was used to explore the prognostic risk factors of OSCC. The cell proliferation experiment and the cell scratch experiment were used to evaluate the effect of down-regulation of HMMR on the proliferation and migration of OSCC cells.

RESULTS

HMMR was highly expressed in OSCC tissues. Compared with the low HMMR expression group, the prognostic related factors in the HMMR high expression group was significantly lower, with significant difference (all P<0.05); the high expression of HMMR was significantly related with the T grade (RR=1.33, P<0.05), lymphonodus metastasis (RR=1.74, P<0.05), the clinical stage (RR=1.49, P<0.05), and it was an independent prognostic risk factor for OSCC (RR=1.45, P<0.05). Down-regulation of HMMR can inhibit the proliferation and migration of OSCC cells, with significant difference (P<0.05 or P<0.01).

CONCLUSIONS

HMMR, as a proto-oncogene of OSCC, can promote the occurrence and development of OSCC, and it may be used as a potential early diagnostic marker and a new target for therapy.

Identification and Validation of a Novel Six-Gene Expression Signature for Predicting Hepatocellular Carcinoma Prognosis

Background

Hepatocellular carcinoma (HCC) is a highly lethal disease. Effective prognostic tools to guide clinical decision-making for HCC patients are lacking.

Objective

We aimed to establish a robust prognostic model based on differentially expressed genes (DEGs) in HCC.

Methods

Using datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Genome Consortium (ICGC), DEGs between HCC tissues and adjacent normal tissues were identified. Using TCGA dataset as the training cohort, we applied the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analyses to identify a multi-gene expression signature. Proportional hazard assumptions and multicollinearity among covariates were evaluated while building the model. The ICGC cohort was used for validation. The Pearson test was used to evaluate the correlation between tumor mutational burden and risk score. Through single-sample gene set enrichment analysis, we investigated the role of signature genes in the HCC microenvironment.

Results

A total of 274 DEGs were identified, and a six-DEG prognostic model was developed. Patients were stratified into low- or high-risk groups based on risk scoring by the model. Kaplan-Meier analysis revealed significant differences in overall survival and progression-free interval. Through univariate and multivariate Cox analyses, the model proved to be an independent prognostic factor compared to other clinic-pathological parameters. Time-dependent receiver operating characteristic curve analysis revealed satisfactory prediction of overall survival, but not progression-free interval. Functional enrichment analysis showed that cancer-related pathways were enriched, while immune infiltration analyses differed between the two risk groups. The risk score did not correlate with levels of PD-1, PD-L1, CTLA4, or tumor mutational burden.

Conclusions

We propose a six-gene expression signature that could help to determine HCC patient prognosis. These genes may serve as biomarkers in HCC and support personalized disease management.

4-Methylumbelliferone induces antitumor effects independently of hyaluronan synthesis inhibition in human acute leukemia cell lines

AIMS

Despite continuous improvement in the treatment of acute leukemia, new therapies are still needed to overcome resistance and reduce adverse effects. The aim of this work was to study the tumor-suppressive effects of 4-methylumbelliferone (4MU) in human acute leukemia cell lines. In addition, we aimed to address the extent of these effects in relation to the inhibition of hyaluronic acid (HA) synthesis.

MAIN METHODS

HA levels were measured by an ELISA-like assay. Human acute leukemia cell lines were treated with 4MU, HA or their combination. Cell proliferation was assessed by the [³H]-Tdr uptake assay, metabolic activity by the XTT assay and cell death was determined by DAPI, AO/EB and AnnexinV-PE/7-AAD staining. Senescence induction was evaluated by SA-β-Gal and C12FDG staining. Total and surface RHAMM expression levels were assessed by flow cytometry and fluorescence microscopy.

KEY FINDINGS

4MU reduced metabolic activity and inhibited cell proliferation in all leukemia cells, and these effects were explained by the induction of senescence or cell death depending on the cell line evaluated. Exogenous HA failed to prevent most of the tumor-suppressive effects observed. Results from this work suggest that the tumor-suppressive effects exerted by 4MU would be explained by HA-synthesis-independent mechanisms.

SIGNIFICANCE

These findings broaden the knowledge of 4MU as a potential treatment in acute leukemia. We report for the first time the existence of tumor-suppressive effects of 4MU on human acute leukemia cell lines that are independent of its role as HA-synthesis inhibitor.

Identification of key genes and carcinogenic pathways in hepatitis B virus-associated hepatocellular carcinoma through bioinformatics analysis

Backgrounds/Aims

Mechanisms for the development of hepatocellular carcinoma (HCC) in hepatitis B virus (HBV)-infected patients remain unclear. The aim of the present study was to identify genes and pathways involved in the development of HBV-associated HCC.

Methods

The GSE121248 gene dataset, which included 70 HCCs and 37 adjacent liver tissues, was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) in HCCs and adjacent liver tissues were identified. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analyses were then performed.

Results

Of 134 DEGs identified, 34 were up-regulated and 100 were down-regulated in HCCs. The 34 up-regulated DEGs were mainly involved in nuclear division, organelle fission, spindle and midbody formation, histone kinase activity, and p53 signaling pathway, whereas the 100 down-regulated DEGs were involved in steroid and hormone metabolism, collagen-coated extracellular matrix, oxidoreductase activity, and activity on paired donors, including incorporation or reduction of molecular oxygen, monooxygenase activity, and retinol metabolism. Analyses of protein-protein interaction networks with a high degree of connectivity identified significant modules containing 14 hub genes, including ANLN, ASPM, BUB1B, CCNB1, CDK1, CDKN3, ECT2, HMMR, NEK2, PBK, PRC1, RACGAP1, RRM2, and TOP2A, which were mainly associated with nuclear division, organelle fission, spindle formation, protein serine/threonine kinase activity, p53 signaling pathway, and cell cycle.

Conclusions

This study identified key genes and carcinogenic pathways that play essential roles in the development of HBV-associated HCC. This may provide important information for the development of diagnostic and therapeutic targets for HCC.

Systematic Analysis of the Clinical Significance of Hyaluronan-Mediated Motility Receptor in Colorectal Cancer

Background: The role of hyaluronan-mediated motility receptor (HMMR) in colorectal cancer (CRC) remains unclear. The present study aimed to explore the association of HMMR with the development and prognosis of CRC using sequence datasets, clinical tissues, blood samples, and cell lines.

Methods: CRC datasets were downloaded from TCGA and GEO databases. Forty CRC tissue samples, 120 CRC blood samples, and 100 healthy controls were collected. Four CRC cell lines (HCT116, HT-29, LoVo, and SW480) and one normal human colon mucosal epithelial cell line (NCM460) were cultured. RT-qPCR was used to determine the expression of HMMR in the tissues and cell lines. ELISA was used to measure HMMR levels in the blood samples.

Results: The expression of HMMR was significantly increased in CRC tissues than in corresponding adjacent tissues based on TCGA and GEO datasets, and clinical CRC tissues. No associations were found between the expression of HMMR and the TNM stage or other clinical parameters. The expression of HMMR varied in different CRC cell lines. The blood levels of HMMR tended to be higher in patients with CRC than in healthy controls. TCGA and GEO datasets showed inconsistent results regarding the association of HMMR expression with the survival of patients with CRC.

Conclusion: The expression of HMMR is increased in CRC tissues but not in the blood. The expression of HMMR is independent of CRC development and has no prognostic significance in patients with CRC.

Comprehensive Bioinformatics Analysis to Identify the Gene HMMR Associated With Lung Adenocarcinoma Prognosis and Its Mechanism of Action in Multiple Cancers

Background

Lung cancer is the third most frequently diagnosed cancer in the world, with lung adenocarcinoma (LUAD) as the most common pathological type. But studies on the predictive effect of a single gene on LUAD are limited. We aimed to discover new predictive markers for LUAD.

Methods

Differentially high-expressed genes at each stage were obtained from the TCGA and GTEx databases. The functions of these genes were investigated through GO enrichment and KEGG pathway analyses. Then, the key genes were selected by applying whole gene overall survival time. The expression of the key gene was studied in LUAD, and survival analysis was performed using Kaplan-Meier mapper, followed by univariate and multifactorial COX analysis. Finally, the gene expression and its prognostic significance in the pan-cancer were examined.

Results

A total of 10,106 DEGs were obtained from the two datasets. The top 266 differentially upregulated genes intersected with the top 1,497 overall survival-related genes, and 87 key genes were identified. High-expressed HMMR was associated with a poor prognosis of LUAD. Univariate and multifactorial Cox analysis showed that HMMR was an independent prognostic factor for LUAD patients. A high HMMR expression was strongly associated with the overall survival (OS) and disease-specific survival (DSS) in 11 cancer types and with poorer OS, DSS, and PFI in 10 cancer types.

Conclusion

HMMR may be an independent prognostic indicator and an important biomarker in diagnosing and predicting the survival of LUAD patients. Also, HMMR may be a key predictor of a variety of cancers.

Identification of a DNA Methylation-Driven Genes-Based Prognostic Model and Drug Targets in Breast Cancer: In silico Screening of Therapeutic Compounds and in vitro Characterization

DNA methylation is a vital epigenetic change that regulates gene transcription and helps to keep the genome stable. The deregulation hallmark of human cancer is often defined by aberrant DNA methylation which is critical for tumor formation and controls the expression of several tumor-associated genes. In various cancers, methylation changes such as tumor suppressor gene hypermethylation and oncogene hypomethylation are critical in tumor occurrences, especially in breast cancer. Detecting DNA methylation-driven genes and understanding the molecular features of such genes could thus help to enhance our understanding of pathogenesis and molecular mechanisms of breast cancer, facilitating the development of precision medicine and drug discovery. In the present study, we retrospectively analyzed over one thousand breast cancer patients and established a robust prognostic signature based on DNA methylation-driven genes. Then, we calculated immune cells abundance in each patient and lower immune activity existed in high-risk patients. The expression of leukocyte antigen (HLA) family genes and immune checkpoints genes were consistent with the above results. In addition, more mutated genes were observed in the high-risk group. Furthermore, a in silico screening of druggable targets and compounds from CTRP and PRISM databases was performed, resulting in the identification of five target genes (HMMR, CCNB1, CDC25C, AURKA, and CENPE) and five agents (oligomycin A, panobinostat, (+)-JQ1, voxtalisib, and arcyriaflavin A), which might have therapeutic potential in treating high-risk breast cancer patients. Further in vitro evaluation confirmed that (+)-JQ1 had the best cancer cell selectivity and exerted its anti-breast cancer activity through CENPE. In conclusion, our study provided new insights into personalized prognostication and may inspire the integration of risk stratification and precision therapy.

The fellowship of the RING: BRCA1, its partner BARD1 and their liaison in DNA repair and cancer

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

RHAMM Is a Multifunctional Protein That Regulates Cancer Progression

The functional complexity of higher organisms is not easily accounted for by the size of their genomes. Rather, complexity appears to be generated by transcriptional, translational, and post-translational mechanisms and tissue organization that produces a context-dependent response of cells to specific stimuli. One property of gene products that likely increases the ability of cells to respond to stimuli with complexity is the multifunctionality of expressed proteins. Receptor for hyaluronan-mediated motility (RHAMM) is an example of a multifunctional protein that controls differential responses of cells in response-to-injury contexts. Here, we trace its evolution into a sensor-transducer of tissue injury signals in higher organisms through the detection of hyaluronan (HA) that accumulates in injured microenvironments. Our goal is to highlight the domain and isoform structures that generate RHAMM's function complexity and model approaches for targeting its key functions to control cancer progression.

Validating HMMR Expression and Its Prognostic Significance in Lung Adenocarcinoma Based on Data Mining and Bioinformatics Methods

Hyaluronic acid-mediated motility receptor (HMMR), a tumor-related gene, plays a vital role in the occurrence and progression of various cancers. This research is aimed to reveal the effect of HMMR in lung adenocarcinoma (LUAD). We first obtained the gene expression profiles and clinical data of patients with LUAD from The Cancer Genome Atlas (TCGA) database. Then, based on the TCGA cohort, the HMMR expression difference between LUAD tissues and nontumor tissues was detected and verified with public tissue microarrays (TMAs), clinical LUAD specimen cohort, and Gene Expression Omnibus (GEO) cohort. Logistic regression analysis and chi-square test were adopted to study the correlation between HMMR expression and clinicopathological parameters. The effect of HMMR expression on survival was evaluated by Kaplan–Meier survival analysis and using the Cox regression model. Furthermore, Gene Set Enrichment Analysis (GSEA) was utilized to screen out signaling pathways related to LUAD and the co-expression analysis was employed to build the protein–protein interaction (PPI) network. The HMMR expression level in LUAD tissues was dramatically higher than that in nontumor tissues. Logistic regression analysis and chi-square test demonstrated that the high HMMR expression in LUAD has relation with gender, pathological stage, T classification, lymph node metastasis, and distant metastasis. The Kaplan–Meier curve suggested a poor prognosis for LUAD patients with high HMMR expression. Multivariate analysis implied that the high HMMR expression was a vital independent predictor of poor overall survival (OS). GSEA indicated that a total of 15 signaling pathways were enriched in samples with the high HMMR expression phenotype. The PPI network gave 10 genes co-expressed with HMMR. HMMR may be an oncogene in LUAD and is expected to become a potential prognostic indicator and therapeutic target for LUAD.

Hyaluronan-mediated motility receptor expression functions as a prognostic biomarker in uterine carcinosarcoma based on bioinformatics analysis

OBJECTIVE

Uterine carcinosarcoma (UCS) is a rare, aggressive tumour with a high metastasis rate and poor prognosis. This study aimed to explore potential key genes associated with the prognosis of UCS.

METHODS

Transcriptional expression data were downloaded from the Gene Expression Profiling Interactive Analysis database and differentially expressed genes (DEGs) were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses using Metascape. A protein-protein interaction network was constructed using the STRING website and Cytoscape software, and the top 30 genes obtained through the Maximal Clique Centrality algorithm were selected as hub genes. These hub genes were validated by clinicopathological and sequencing data for 56 patients with UCS from The Cancer Genome Atlas database.

RESULTS

A total of 1894 DEGs were identified, and the top 30 genes were considered as hub genes. Hyaluronan-mediated motility receptor (HMMR) expression was significantly higher in UCS tissues compared with normal tissues, and elevated expression of HMMR was identified as an independent prognostic factor for shorter survival in patients with UCS.

CONCLUSIONS

These results suggest that HMMR may be a potential biomarker for predicting the prognosis of patients with UCS.

Prognostic Implication of a Novel Metabolism-Related Gene Signature in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the main causes of cancer-associated deaths globally, accounts for 90% of primary liver cancers. However, further studies are needed to confirm the metabolism-related gene signature related to the prognosis of patients with HCC.

Methods

Using the “limma” R package and univariate Cox analysis, combined with LASSO regression analysis, a metabolism-related gene signature was established. The relationship between the gene signature and overall survival (OS) of HCC patients was analyzed. RT-qPCR was used to evaluate the expression of metabolism-related genes in clinical samples. GSEA and ssGSEA algorithms were used to evaluate differences in metabolism and immune status, respectively. Simultaneously, data downloaded from ICGC were used as an external verification set.

Results

From a total of 1,382 metabolism-related genes, a novel six-gene signature (G6PD, AKR1B15, HMMR, CSPG5, ELOVL3, FABP6) was constructed based on data from TCGA. Patients were divided into two risk groups based on risk scores calculated for these six genes. Survival analysis showed a significant correlation between high-risk patients and poor prognosis. ROC analysis demonstrated that the gene signature had good predictive capability, and the mRNA expression levels of the six genes were upregulated in HCC tissues than those in adjacent normal liver tissues. Independent prognosis analysis confirmed that the risk score and tumor grade were independent risk factors for HCC. Furthermore, a nomogram of the risk score combined with tumor stage was constructed. The calibration graph results demonstrated that the OS probability predicted by the nomogram had almost no deviation from the actual OS probability, especially for 3-year OS. Both the C-index and DCA curve indicated that the nomogram provides higher reliability than the tumor stage and risk scores. Moreover, the metabolic and immune infiltration statuses of the two risk groups were significantly different. In the high-risk group, the expression levels of immune checkpoints, TGF-β, and C-ECM genes, whose functions are related to immune escape and immunotherapy failure, were also upregulated.

Conclusions

In summary, we developed a novel metabolism-related gene signature to provide more powerful prognostic evaluation information with potential ability to predict the immunotherapy efficiency and guide early treatment for HCC.

Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China.

Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes’ protein expression levels.

Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC.

Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

High Expression of Hyaluronan-Mediated Motility Receptor Predicts Adverse Outcomes: A Potential Therapeutic Target for Head and Neck Squamous Cell Carcinoma

Background: Several studies have shown that the hyaluronan-mediated motility receptor (HMMR) is overexpressed in various cancers and could be a potential prognostic factor. However, further research is still required to determine the prognostic value and potential function of HMMR in head and neck squamous cell carcinoma (HNSCC).

Materials and Methods: Transcriptomic expression data were collected from the Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus and the differences in HMMR expression between normal and tumor tissues were analyzed. The correlation between the methylation level of HMMR and its mRNA expression was analyzed via cBioPortal. Additionally, the data obtained from TCGA was analyzed with MethSurv to determine the prognostic value of the HMMR methylation levels in HNSCC. Gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA) were used to explore the potential biological functions of HMMR.

Results: HMMR was highly expressed in HNSCC tumor tissue compared to normal tissue (p < 0.001). Multivariate analysis (MAV) showed that high HMMR mRNA expression was an independent prognostic factor of overall survival (OS) in TCGA (HR = 1.628, 95% CI: 1.169–2.266, p = 0.004) and GSE41613 data (HR = 2.238, p = 0.013). The methylation level of HMMR negatively correlated with the HMMR expression (R = −0.12, p < 0.001), and patients with low HMMR methylation had worse OS than patients with high methylation (p < 0.001). GSEA found that HMMR expression was associated with the KARS, EMT, and G2M checkpoint pathways, as well as the interferon-gamma and interferon-alpha responses, whereas ssGSEA showed that HMMR expression positively correlated with the infiltration level of Th2 cells. MAV confirmed that high HMMR protein expression was an inferior independent factor for OS (HR = 2.288, p = 0.045) and progression-free survival (HR = 2.247, p = 0.038) in 70 HNSCC.

Conclusions: This study demonstrated that the upregulation of HMMR mRNA and protein in HNSCC is a biomarker for poor prognosis. The biological functions of HMMR are potentially related to the KARS, EMT, and G2M checkpoint pathways, as well as the interferon-gamma and interferon-alpha responses. These findings help to elucidate the role of HMMR in carcinogenesis and lay a foundation for further study.

The scrambled story between hyaluronan and glioblastoma

Advances in cancer biology are revealing the importance of the cancer cell microenvironment on tumorigenesis and cancer progression. Hyaluronan (HA), the main glycosaminoglycan in the extracellular matrix, has been associated with the progression of glioblastoma (GBM), the most frequent and lethal primary tumor in the central nervous system, for several decades. However, the mechanisms by which HA impacts GBM properties and processes have been difficult to elucidate. In this review, we provide a comprehensive assessment of the current knowledge on HA's effects on GBM biology, introducing its primary receptors CD44 and RHAMM and the plethora of relevant downstream signaling pathways that can scramble efforts to directly link HA activity to biological outcomes. We consider the complexities of studying an extracellular polymer and the different strategies used to try to capture its function, including 2D and 3D in vitro studies, patient samples, and in vivo models. Given that HA affects not only migration and invasion, but also cell proliferation, adherence, and chemoresistance, we highlight the potential role of HA as a therapeutic target. Finally, we review the different existing approaches to diminish its protumor effects, such as the use of 4-methylumbelliferone, HA oligomers, and hyaluronidases and encourage further research along these lines in order to improve the survival and quality of life of GBM patients.

Comprehensive analysis of the relationship between competitive endogenous RNA (ceRNA) networks and tumor infiltrating-cells in hepatocellular carcinoma

Background

The innovation of immune checkpoint blockade (ICB) represents a promising shift in the treatment of advanced hepatocellular carcinoma (HCC). However, response to ICB has varied largely due to the high tumor heterogeneity and complex tumor microenvironment (TME). The competitive endogenous RNA (ceRNA) network also plays an important role in tumor occurrence and progression, but its relation with tumor-infiltrating immune cells (TICs) remains largely unexplored in HCC. The overriding objective of our study was thus to construct a prognosis-related risk model and to further evaluate the relationship between ceRNA networks and TICs.

Methods

Differentially expressed gene (DEG) analysis was performed to identify the differentially expressed RNAs. Lasso and multivariable Cox regression analyses were used to construct risk models, which were assessed by the area under the receiver operating characteristic curve (AUC of ROC) and Kaplan-Meier (K-M) curves. Then, a single-sample gene set enrichment analysis (ssGSEA) algorithm was adopted to dissect the TICs in HCC samples. Nomograms were constructed and calibration curves were used to verify the discrimination and accuracy of the nomograms. Finally, integration analysis was performed to validate the correlation of ceRNA and TICs.

Results

In the study, 7 differentially expressed RNAs [5 messenger RNA s (mRNAs) and 2 micro RNAs (miRNAs)] were incorporated to construct a ceRNA risk model. The AUC of the 1-, 3-, and 5-year overall survival (OS) were 0.784, 0.685, and 0.691 respectively. Likewise, 7 types TICs were in the TICs signature model and the AUC of the 1-, 3-, and 5-year OS were 0.706, 0.731, and 0.721 respectively. The integration analysis showed that 7 pairs of mRNA-TICs and 1 pair of miRNA-TICs had a close relation (all correlation coefficients >0.2, P<0.001).

Conclusions

Through constructing two risk models based on ceRNA network and TICs, we identified the hub RNAs and key TICs in the progression and prognosis of HCC, and further explored the relationship between ceRNA and TME. Importantly, targeting these hub RNAs may facilitate the remodeling of the TME and be a potential therapeutic alternative to enhancing the response to ICB, thus improving the prognosis of HCC patients.

A Novel Prognostic Index Based on the Analysis of Glycolysis-Related Genes in Head and Neck Squamous Cell Carcinomas

Aims

The preferential dependence on glycolysis as a pathway of energy metabolism is a hallmark of cancer cells. However, the prognostic significance of glycolysis-related genes in head and neck squamous cell carcinoma (HNSCC) remains obscure. The purpose of this study was to identify glycolysis-related genes of prognostic value in HNSCC.

Results

Transcriptional and clinical data of 544 HNSCC samples were obtained from The Cancer Genome Atlas (TCGA) dataset. By gene set enrichment analysis (GSEA) and by employing a univariate and subsequently a stepwise multivariate Cox proportional regression model, eight glycolysis-related genes of prognostic significance in HNSCC (KIF2A, JMJD8, HMMR, STC2, HK1, EXT2, GPR8, and STC1) were identified. The patients were clustered into two groups (high and low risk) based on the expression of these genes. High-risk patients had significantly a shorter overall survival than low-risk patients. Furthermore, a new prognostic indicator based on selected glycolysis-related genes was developed by multivariate Cox analysis that proved to be a better predictor of patient outcome compared to other clinical factors.

Conclusion

Our findings provide new insights into the role of glycolysis in HNSCC. The identified genes predict the patient prognosis and might substantially contribute to the development of individualized treatments.

Oleate acid-stimulated HMMR expression by CEBPα is associated with nonalcoholic steatohepatitis and hepatocellular carcinoma

Non-alcoholic steatohepatitis (NASH) is a type of nonalcoholic fatty liver disease and has become a major risk factor for hepatocellular carcinoma (HCC). However, the underlying pathophysiological mechanisms are still elusive. Here, we identify hyaluronan-mediated motility receptor (HMMR) as a critical gene associated with NASH/HCC by combination of bioinformatic analysis and functional experiments. Analysis of differentially expressed genes (DEGs) between normal controls and NASH/HCC identified 5 hub genes (HMMR, UBE2T, TYMS, PTTG1 and GINS2). Based on the common DEGs, analyses of univariate and multivariate Cox regression and the area under the curve (AUC) value of the receiver operating characteristic (ROC) indicate that HMMR is the most significant gene associated with NASH/HCC among five hub genes. Oleate acid (OA), one of fatty acids that induce cellular adipogenesis, stimulates HMMR expression via CCAAT/enhancer-binding protein α (CEBPα). CEBPα increases the expression of HMMR through binding to its promoter. HMMR promotes HCC cell proliferation in vitro via activation of G1/S and G2/M checkpoint transitions, concomitant with a marked increase of the positive cell cycle regulators, including cyclin D1, cyclin E, and cyclin B1. Knockdown of HMMR suppresses HCC tumor growth in nude mice. Our study identifies an important role of HMMR in NASH/HCC, and suggests that HMMR may be a useful target for therapy and prognostic prediction of NASH/HCC patients.