HMGA1 Promotes Hepatic Metastasis of Colorectal Cancer by Inducing Expression of Glucose Transporter 3 (GLUT3)

YAP Promotes Chemoresistance to 5-FU in Colorectal Cancer Through mTOR/GLUT3 Axis

Background: Although chemoresistance constitutes a significant barrier to the effectiveness of chemotherapy in colorectal cancer (CRC), its precise mechanisms remain unclear. YAP functions as an oncogene in various malignancies. However, the relationship between YAP and chemoresistance in CRC needs clarification. Methods: The expression level of YAP in CRC tissues was assessed through immunohistochemistry (IHC), and the impact of YAP on CRC cell chemoresistance was evaluated using the Cell Counting Kit-8, EdU, and flow cytometry assays. Meanwhile, tumor proliferation was assessed in vivo by analyzing the expression of PCNA and Ki-67 in subcutaneous tumors via IHC. In addition, the TUNEL assay was employed to evaluate tumor apoptosis levels and western blot was utilized to detect the mTOR/GLUT3 pathway-related protein expression to provide insights into the underlying mechanism. Results: YAP was highly expressed in CRC tissues and correlated with patient prognosis and clinicopathological features. Bioinformatic analysis based on the TCGA database revealed that YAP was associated with DNA replication, glycolysis, and the mTOR pathway. Meanwhile, YAP could enhance chemoresistance and glycolysis in CRC cells both in vitro and in vivo. Additional mechanistic experiments unveiled that YAP promoted CRC cell chemoresistance via the mTOR/GLUT3 axis. Conclusion: This study validated the role of YAP as an oncogene in CRC, as it promoted chemoresistance through the mTOR/GLUT3 axis. These results suggested YAP as a potential target for promoting the efficacy of chemotherapy in patients with CRC.

HMGA1 is a Prognostic Biomarker and Correlated with Glycolysis in Lung Adenocarcinoma

Purpose: Lung cancer is one of the leading causes with high morbidity and mortality. High mobility group A1 (HMGA1) protein participates in the process of tumorigenesis. This study seeks to explore the specific role of HMGA1 in prognostic value based on The Cancer Genome Atlas (TCGA) database of Lung adenocarcinoma (LUAD) and glycolysis progression in LUAD cells. Patients and Methods: In this research, we compared HMGA1 mRNA expression between tumor tissues and normal samples and evaluated the correlations with clinical characteristics in LUAD patients based on the data of TCGA database. The survival outcome with overall survival (OS), disease-specific survival (DSS) and clinicopathologic characteristics associated were performed using the Kaplan-Meier method and Cox regression. In addition, gene-set enrichment analysis (GSEA) was carried out to explore the biological pathways that related to HMGA1. Cell experiments including cell proliferation assay and glycolysis proteins were performed with A549 and H1299 cells. Results: Our results revealed that HMGA1 mRNA expression was higher in LUAD tissues than in normal tissues. Increased HMGA1 expression in LUAD was associated with Gender (p<0.01), Pathologic stage I&II vs stage III&IV (p<0.001), T1&T2 vs T3&T4 stage (p<0.05), N0 vs N2 stage (p<0.01). Furthermore, multivariate analysis revealed that HMGA1 was an independent risk factor of OS and DSS for LUAD patients (p<0.05). HMGA1 were positively correlated with glycolysis gluconeogenesis pathway and glycolysis markers (HK2, GLUT1, PKM2, LDHA) based on GSEA and Gene Expression Profiling Interactive Analysis (GEPIA) database. At the cellular level, the results of qRT-PCR and western blot assays showed that si-HMGA1 markedly decreased the expression of glycolysis markers. HMGA1 promoted cell glycolysis progression via PI3K/AKT pathway transfected with HMGA1-plasmid and the treatment with 20 μM LY294002. Relevant animal experiments were also synchronously validated and si-HMGA1 groups down-regulated xenograft growth including the weights and size in tumor xenografts. Conclusions: In conclusion, our results suggested that HMGA1 was significantly correlated with poor survival for LUAD tissues and involved in the process of glycolysis in LUAD cells.

Circ_UBAP2 exacerbates proliferation and metastasis of OS via targeting miR-665/miR-370-3p/HMGA1 axis

Circ_UBAP2 is extensively engaged in regulating the development of various malignancies, containing osteosarcoma (OS). However, its biological significance and function are not fully understood. In this study, we found that circ_UBAP2 and HMGA1 levels were up-regulated, and miR-370-3p and miR-665 expressions were decreased in osteosarcoma tissues. Inhibition of circ_UBAP2 or HMGA1 expression in OS cells, cell viability, invasion and migration abilitities were notably hindered, and cell apoptosis abilities were increased. Bioinformatics analysis predicted that miR-665 and miR-370-3p were the downstream targets of circ_UBAP2, and the dual luciferase experiment demonstrated the correlation between them. In addition, inhibition of miR-665 and miR-370-3p expression could significantly reverse the impact of knocking down circ_UBAP2 on OS cells. HMGA1 was discovered to become the downstream target of both miR-665 and miR-370-3p. It was shown that over-expression of miR-665 or miR-370-3p notably stimulated the cell growth, invasion, and migration of osteosarcoma cells, while hindered cell apoptosis. Nevertheless, this effect could be reversed by concurrent over-expression of HMGA1. Our data strongly prove that circ_UBAP2 makes a vital impact on promoting the proliferation, invasion as well as migration of osteosarcoma cells via down-regulating the level of miR-665 and miR-370-3p, and later up-regulating the level of HMGA1. In conclusion, circ_UBAP2 is upregulated in osteosarcoma, and it competitively adsorbs miR-370-3p and miR-665, resulting in up-regulation of HMGA1, thus promoting OS development.

Multilevel Heterogeneity of Colorectal Cancer Liver Metastasis

Colorectal cancer liver metastasis (CRLM) is a highly heterogeneous disease. Therapies that target both primary foci and liver metastasis are severely lacking. Therefore, understanding the features of metastatic tumor cells in the liver is valuable for the overall control of CRLM patients. In this review, we summarize the heterogeneity exhibited in CRLM from five aspects (gene, transcriptome, protein, metabolism, and immunity). In addition to genetic heterogeneity, the other four aspects exhibit significant heterogeneity. Compared to primary CRC, the dysregulation of epithelial-mesenchymal transition (EMT)-related proteins, the enhanced metabolic activity, and the increased infiltration of immunosuppressive cells are detected in CRLM. Preclinical evidence shows that targeting the EMT process or enhancing cellular metabolism may represent a novel approach to increasing the therapeutic efficacy of CRLM.

H19: An Oncogenic Long Non-coding RNA in Colorectal Cancer

Colorectal cancer (CRC) has been recorded amongst the most common cancers in the world, with high morbidity and mortality rates, and relatively low survival rates. With risk factors such as chronic illness, age, and lifestyle associated with the development of CRC, the incidence of CRC is increasing each year. Thus, the discovery of novel biomarkers to improve the diagnosis and prognosis of CRC has become beneficial. Long non-coding RNAs (lncRNAs) have been emerging as potential players in several tumor types, one among them is the lncRNA H19. The paternally imprinted oncofetal gene is expressed in the embryo, downregulated at birth, and reappears in tumors. H19 aids in CRC cell growth, proliferation, invasion, and metastasis via various mechanisms of action, significantly through the lncRNA-microRNA (miRNA)-messenger RNA (mRNA)-competitive endogenous RNA (ceRNA) network, where H19 behaves as a miRNA sponge. The RNA transcript of H19 obtained from the first exon of the H19 gene, miRNA-675 also promotes CRC carcinogenesis. Overexpression of H19 in malignant tissues compared to adjacent non-malignant tissues marks H19 as an independent prognostic marker in CRC. Besides its prognostic value, H19 serves as a promising target for therapy in CRC treatment.

Polymorphism and expression of the HMGA1 gene and association with tail fat deposition in Hu sheep

Hu sheep is an excellent short fat-tailed breed in China. Fat deposition in Hu sheep tail affects carcass quality and consumes a lot of energy, leading to an increase in feed cost. The objective of this study was to analyze the effects of HMGA1 polymorphism on tail fat weight in Hu sheep. Partial coding and non-coding sequences of HMGA1 were amplified with PCR and single nucleotide polymorphisms (SNP) of HMGA1 in 1163 Hu sheep were detected using DNA sequencing and KASPar technology. RT-qPCR analysis was performed to test HMGA1 expression in different tissues. The results showed that the expression of HMGA1 was higher in the duodenum, liver, spleen, kidney, and lung than in the heart, muscle, rumen, tail fat, and lymph. A mutation, g.5312 C > T, was detected in HMGA1; g.5312 C > T was significantly associated with tail fat weight, relative weight of tail fat (body weight), and relative weight of tail fat (carcass) (p < 0.05). The tail fat weight of the TT genotype was remarkably higher than that of the CC and TC genotypes. Therefore, HMGA1 can be used as a genetic marker for marker-assisted selection of tail fat weight in Hu sheep.

Reversal of HMGA1-Mediated Immunosuppression Synergizes with Immunogenic Magnetothermodynamic for Improved Hepatocellular Carcinoma Therapy

Magnetothermodynamic (MTD) therapy can activate antitumor immune responses by inducing potent immunogenic tumor cell death. However, tumor development is often accompanied by multifarious immunosuppressive mechanisms that can counter the efficacy of immunogenic MTD therapy. High-mobility group protein A1 (HMGA1) is overexpressed within hepatocellular carcinoma tissues and plays a crucial function in the generation of immunosuppressive effects. The reversal of HMGA1-mediated immunosuppression could enhance immunogenic tumor cell death-induced immune responses. A ferrimagnetic vortex-domain iron oxide (FVIO) nanoring-based nanovehicle was developed, which is capable of efficiently mediating an alternating magnetic field for immunogenic tumor cell death induction, while concurrently delivering HMGA1 small interfering (si)RNA (siHMGA1) to the cytoplasm of hepatocellular carcinoma Hepa 1-6 cells for HMGA1 pathway interference. Using siHMGA1-FVIO-mediated MTD therapy, the proliferation of hepatocellular carcinoma Hepa 1-6 tumors was inhibited, and the survival of a mouse model was improved. We also demonstrated that siHMGA1-FVIO-mediated MTD achieved synergistic antitumor effects in a subcutaneous hepatocellular carcinoma Hepa 1-6 and H22 tumor model by promoting dendritic cell maturation, enhancing antigen-presenting molecule expression (both major histocompatibility complexes I and II), improving tumor-infiltrating T lymphocyte numbers, and decreasing immunosuppressive myeloid-derived suppressor cells, interleukin-10, and transforming growth factor-β expression. The nanoparticle system outlined in this paper has the potential to target HMGA1 and, in combination with MTD-induced immunotherapy, is a promising approach for hepatocellular carcinoma treatment.

A novel transcription factor-based signature to predict prognosis and therapeutic response of hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common aggressive malignancies with increasing incidence worldwide. The oncogenic roles of transcription factors (TFs) were increasingly recognized in various cancers. This study aimed to develop a predicting signature based on TFs for the prognosis and treatment of HCC. Methods: Differentially expressed TFs were screened from data in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Univariate and multivariate Cox regression analyses were applied to establish a TF-based prognostic signature. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the signature. Subsequently, correlations of the risk model with clinical features and treatment response in HCC were also analyzed. The TF target genes underwent Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, followed by protein-protein-interaction (PPI) analysis. Results: A total of 25 differentially expressed TFs were screened, 16 of which were related to the prognosis of HCC in the TCGA-LIHC cohort. A 2-TF risk signature, comprising high mobility group AT-hook protein 1 (HMGA1) and MAF BZIP transcription factor G (MAFG), was constructed and validated to negatively related to the overall survival (OS) of HCC. The ROC curve showed good predictive efficiencies of the risk score regarding 1-year, 2-year and 3-year OS (mostly AUC >0.60). Additionally, the risk score independently predicted OS for HCC patients both in the training cohort of TCGA-LIHC dataset (HR = 2.498, p = 0.007) and in the testing cohort of ICGC-LIRI-JP dataset (HR = 5.411, p < 0.001). The risk score was also positively correlated to progressive characteristics regarding tumor grade, TNM stage and tumor invasion. Patients with a high-risk score were more resistant to transarterial chemoembolization (TACE) treatment and agents of lapatinib and erlotinib, but sensitive to chemotherapeutics. Further enrichment and PPI analyses demonstrated that the 2-TF signature distinguished tumors into 2 clusters with proliferative and metabolic features, with the hub genes belonging to the former cluster. Conclusion: Our study identified a 2-TF prognostic signature that indicated tumor heterogeneity with different clinical features and treatment preference, which help optimal therapeutic strategy and improved survival for HCC patients.

HMGA1 As a Potential Prognostic and Therapeutic Biomarker in Breast Cancer

Background

High-mobility group AT-hook1 (HMGA1) protein plays an important role in various diseases. However, the contribution of HMGA1 in breast cancer remains to be tapped.

Methods

The expression of HMGA1 was analyzed in The Cancer Genome Atlas (TCGA) and TIMER database, and immunohistochemistry was performed in 39 breast cancer (BC) patients. The correlation between HMGA1 expression and prognosis was evaluated using Kaplan-Meier plotter (KM plotter) in patients with breast cancer. Then, cBioPortal and bc-GenExMiner were requisitioned to analyze the contribution of HMGA1 expression to clinical features. In order to reveal the function of HMGA1 in breast cancer cells, enrichment analysis was performed using the clusterProfiler R software package. Moreover, CCK8 assay, EdU assay, and Cell Cycle Assay were performed to assess the proliferation, and transwell assay was used to evaluate cell migration and invasion. Flow cytometry was used to explore the role of HMGA1 on cell apoptosis. After that, the effect of HMGA1 on signaling pathways in BC cells was detected by western blot.

Results

HMGA1 was highly expressed in a variety of tumors tissues, including BC. High HMGA1 expression was correlated with poor prognosis in BC patients. Meanwhile, HMGA1 expression was increased in molecular phenotypes with poor prognosis (ER-, PR-, and HER2+) and associated with high-grade group, lymph node metastasis, and NPI (Nottingham Prognostic Index). Further, function analysis revealed HMGA1 was enriched in DNA replication and cell cycle pathways in breast cancer. Moreover, knockdown of HMGA1 caused apoptosis, inhibited proliferation, migration, and invasion of MCF-7 and MDA-MB-231 cells, in which the oncogenic signaling pathway of PI3K/AKT/MMP9 played a critical role.

Conclusions

HMGA1 was important for breast cancer progression and was a critical prognostic indicator, prompting a potential therapeutic target of breast cancer.

Comprehensive Analysis of the Role of SLC2A3 on Prognosis and Immune Infiltration in Head and Neck Squamous Cell Carcinoma

Background. SLC2A3 is upregulated in various cancer types and promotes proliferation, invasion, and metabolism. However, its role in the prognosis and immune regulation of head and neck squamous cell carcinoma (HNSCC) is still obscure. This study is aimed at exploring the prognostic and immunotherapeutic potential of SLC2A3 in HNSCC. Methods. All data were downloaded from TCGA database and integrated via R software. SLC2A3 expression was evaluated using R software, TIMER, CPTAC, and HPA databases. The association between SLC2A3 expression and clinicopathologic characteristics was assessed by R software. The effect of SLC2A3 on survival was analyzed by R software and Kaplan-Meier Plotter. Genomic alterations in SLC2A3 were investigated using the cBioPortal database. Coexpression of SLC2A3 was studied using LinkedOmics and STRING, and enrichment analyses were performed with R software. The relationship between SLC2A3 expression and immune infiltration was determined using TIMER and TISIDB databases. Immune checkpoints and ESTIMATE score were analyzed via the SangerBox database. Results. SLC2A3 expression was upregulated in HNSCC tissues compared to normal tissues. It was significantly related to TNM stage, histological grade, and alcohol history. High SLC2A3 expression was associated with poor prognosis in HNSCC. Coexpression analysis indicated that SLC2A3 mostly participated in the HIF-1 signaling pathway and glycolysis. Furthermore, SLC2A3 expression strongly correlated with tumor-infiltrating lymphocytes in HNSCC. Conclusion. SLC2A3 could serve as a potential prognostic biomarker for tumor immune infiltration in HNSCC.

Novel Gene Signatures as Prognostic Biomarkers for Predicting the Recurrence of Hepatocellular Carcinoma

Simple Summary

A high percentage of patients who undergo surgical resection for hepatocellular carcinoma (HCC) experience recurrence. Therefore, identification of accurate molecular markers for predicting recurrence of HCC is important. We analyzed recurrence and non-recurrence HCC tissues using two public omics datasets comprising microarray and RNA-sequencing and found novel gene signatures associated with recurrent HCC. These molecules might be used to not only predict for recurrence of HCC but also act as potential prognostic indicators for patients with HCC.

Abstract

Hepatocellular carcinoma (HCC) has a high rate of cancer recurrence (up to 70%) in patients who undergo surgical resection. We investigated prognostic gene signatures for predicting HCC recurrence using in silico gene expression analysis. Recurrence-associated gene candidates were chosen by a comparative analysis of gene expression profiles from two independent whole-transcriptome datasets in patients with HCC who underwent surgical resection. Five promising candidate genes, CETN2, HMGA1, MPZL1, RACGAP1, and SNRPB were identified, and the expression of these genes was evaluated using quantitative reverse transcription PCR in the validation set (n = 57). The genes CETN2, HMGA1, RACGAP1, and SNRPB, but not MPZL1, were upregulated in patients with recurrent HCC. In addition, the combination of HMGA1 and MPZL1 demonstrated the best area under the curve (0.807, 95% confidence interval [CI] = 0.681–0.899) for predicting HCC recurrence. In terms of clinicopathological correlation, CETN2, MPZL1, RACGAP1, and SNRPB were upregulated in patients with microvascular invasion, and the expression of MPZL1 and SNRPB was increased in proportion to the Edmonson tumor differentiation grade. Additionally, overexpression of CETN2, HMGA1, and RACGAP1 correlated with poor overall survival (OS) and disease-free survival (DFS) in the validation set. Finally, Cox regression analysis showed that the expression of serum alpha-fetoprotein and RACGAP1 significantly affected OS, whereas platelet count, microvascular invasion, and HMGA1 expression significantly affected DFS. In conclusion, HMGA1 and RACGAP1 may be potential prognostic biomarkers for predicting the recurrence of HCC after surgical resection.

lncRNA TMPO antisense RNA 1 promotes the malignancy of cholangiocarcinoma cells by regulating let-7g-5p/ high-mobility group A1 axis

Cholangiocarcinoma (CHOL) is often diagnosed at an advanced stage; therefore, exploring its key regulatory factors is important for earlier diagnosis and treatment. This study aimed to identify the mechanisms of long non-coding RNA (lncRNA) TMPO Antisense RNA 1 (TMPO-AS1), microRNA let-7 g-5p, and high-mobility group A1 (HMGA1) proteins in CHOL. Our results, through quantitative real-time PCR and Western blot detection, showed that TMPO-AS1 and HMGA1 were overexpressed while let-7 g-5p was underexpressed in CHOL. Cell function experiments in CHOL cells revealed that TMPO-AS1 knockdown inhibited cell proliferation, colony formation, and cell migration, but induced apoptosis. TMPO-AS1 knockdown also suppressed tumor growth in vivo. Together with luciferase assay and Western blotting, we found that TMPO-AS1 could sponge let-7 g-5p to promote HMGA1 expression. Moreover, HMGA1 overexpression attenuated the effect of TMPO-AS1 downregulation in CHOL cells. Overall, our findings identified the oncogenic effect of TMPO-AS1 on CHOL cells, which may put forward a novel methodology for CHOL diagnosis and therapy.

Identification of Hub Genes and Construction of a Transcriptional Regulatory Network Associated With Tumor Recurrence in Colorectal Cancer by Weighted Gene Co-expression Network Analysis

Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.