Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma

Single-Cell Transcriptional Analysis Reveals the Mechanism of AZD6738 in HCC Immunotherapy via EZH2 Targeting

Objective

This study aims to identify specific molecular targets sensitive to AZD6738 through the integration of network pharmacology and transcriptomic methods, and to assess their potential role in the treatment of hepatocellular carcinoma (HCC). Additionally, we explore the specific effects of AZD6738 on the tumor microenvironment and its ability to regulate immune responses.

Methods

We employed a combination of network pharmacology and transcriptomic analysis to identify specific molecules associated with HCC, including EZH2, CCNB1, PRKDC, CTSL, PSEN1, SLC6A3, and FKBP1A. Using these molecules and clinical features, we constructed a robust prognostic model for HCC. We further used single-cell transcriptomic technology to screen for core targets and performed spatial transcriptomic analysis to determine their spatial distribution. To validate the efficacy of AZD6738 in vivo, we established a subcutaneous tumor model, with the experimental group receiving oral administration of AZD6738 (75 mg/kg). Finally, we assessed the changes in the immune cell expression profile in tumor tissues post-AZD6738 treatment using flow cytometry.

Results

Our study indicates that the high expression of genes such as EZH2, CCNB1, PRKDC, and PSEN1 is associated with poor prognosis in HCC patients. Molecular docking and RT-PCR validation demonstrated that AZD6738 exhibits high affinity for these targets and significantly reduces the mRNA levels of EZH2, PRKDC, and CCNB1 in HCC cell lines, with EZH2 showing the most pronounced decrease. Animal experiments revealed that AZD6738 can enhance the immune microenvironment in liver cancer; specifically, AZD6738 not only promotes the proliferation of CD8+ T cells but also enhances their differentiation into effector memory T cells, indicating that the drug can potentiate anti-tumor immune responses.

Conclusion

This study reveals that AZD6738 demonstrates significant therapeutic efficacy by targeting the key molecule EZH2, thereby modulating the tumor microenvironment and enhancing anti-tumor immunity.

SHC1 serves as a prognostic and immunological biomarker in clear cell renal cell carcinoma: a comprehensive bioinformatics and experimental analysis

SHC1 plays a crucial regulatory role in various tumors, but its significance in predicting prognosis and immune response in clear cell renal cell carcinoma (ccRCC) is yet to be determined. In this study, we conducted a bioinformatics analysis of SHC1 expression, prognosis, and immunological functions in ccRCC using multiple databases. The association between SHC1 and immune infiltration, immune escape, and immunotherapy in ccRCC was systematically established. In addition, we validated our results by western blot of tumor and adjacent-tumor samples from nine ccRCC patients, as well as three renal carcinoma cell lines compared to a normal renal cell line. Our analysis revealed that the mRNA expression level of SHC1 in ccRCC tissues is significantly higher than that in normal tissues. Consistently, western blot experiment showed ccRCC tissues and cell lines exhibit higher protein levels that normal tissues and cell lines. Importantly, patients with low expression of SHC1 demonstrated a higher survival rate, indicating that SHC1 could serve as an independent prognostic factor for predicting survival in ccRCC. Additionally, high expression of SHC1 was associated with increased severe immune cell infiltration, enhanced immune escape, and higher immunotherapy scores. Hence, SHC1 emerges as a novel and easily detectable biomarker for predicting clinical outcomes, immune escape, and immunotherapy response in patients with ccRCC.

Prognostic Hypoxia-Angiogenesis-Related Gene Signature in Hepatocellular Carcinoma, in Which HILPDA Contributes to Tumor Progression

Objective

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer. Hypoxia can be involved in HCC tumor growth, invasion and metastasis through inducing angiogenesis. Nevertheless, the assessment of the impact of hypoxia and angiogenesis on the prognosis of HCC remains inadequate.

Methods

According to hypoxia-angiogenesis-related genes (HARGs) expression information and clinical data from patients within the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a prognostic model (HARG-score) using bioinformatic tools. In addition to assessing the predictive ability of this prognostic model in both Liver Cancer-Riken-Japan (LIRI-JP) and GSE14520 cohorts, we analyzed the correlation between HARG-score and clinical characteristics, immune infiltration and immunotherapy efficacy. Moreover, we investigated the exact role and underlying mechanism of key HARGs through molecular experiments.

Results

We constructed a 5-gene prognostic model HARG-score consisting of hypoxia-inducible lipid droplet-associated (HILPDA), erythropoietin (EPO), solute carrier family 2 member 1 (SLC2A1), proteasome subunit alpha type 7 (PSMA7) and cAMP responsive element-binding protein 1 (CREB1) through differentially expressed HARGs. The findings demonstrated that HARG-score was a good predictor of the prognosis of HCC patients from distinct cohorts and was correlated with clinical characteristics and immune infiltration. Furthermore, the HARG-score was identified as an independent prognostic factor. Lower HARG-score implied greater immunotherapy efficacy and better response. The expression and prognostic significance of these 5 genes were additionally validated in clinical data. In addition, experimental data revealed that the key gene HILPDA contributes to the progression of HCC through facilitating angiogenesis and affecting the expression of cytotoxic T-lymphocyte-associated protein 4 (CTLA4).

Conclusion

HARG-score has promising applications in prognosis prediction of HCC patients, in which HILPDA may be a latent prognostic biomarker and therapeutic target, providing a foundation for further research and treatment of HCC.

Molecular characterization and expression profile of the ALDH1A1 gene and its functions in yak luteal cells

The ALDH1A1 gene encodes a cytoplasmic member of the aldehyde dehydrogenase 1 family, which plays an important role in regulating animal reproductive performance, including estrus cycle and embryonic development. The aim of this study was to characterize ALDH1A1 activity in ovaries of 3-5 year-old yaks and to determine its effects on cell proliferation, apoptosis, and progesterone secretion in luteal cells (LCs). The coding sequence (CDS) of the ALDH1A1 gene was cloned by reverse transcription-PCR and immunohistochemical analysis was used to confirm localization of the ALDH1A1 protein in the ovary. To assess the activity of ALDH1A1 in regulating progesterone secretion, si-ALDH1A1 was transfected into LCs in vitro and progesterone levels in LC supernatants were measured by ELISA. The interference efficiency was assessed by real-time quantitative PCR (RT-qPCR) and immunofluorescence staining, and cell proliferation and apoptosis were evaluated by EdU and TUNEL staining, respectively. The cloned ALDH1A1 sequence contained 1462 bp, encoding 487 amino acids. Immunohistochemical analysis showed that ALDH1A1 protein expression, which was significantly higher in LCs, was mainly found in antral follicles and the corpus luteum (CL). The expression of ALDH1A1 mRNA in LCs was effectively inhibited by si-ALDH1A1transfection, and progesterone secretion was markedly decreased along with the significant down-regulation of progesterone pathway-related genes, STAR, CYP11A1, CYP19A1, CYP17A1, 3β-HSD, and HSD17B1. Knockdown of ALDH1A1 mRNA expression decreased cell proliferation and increased apoptosis in LCs. The mRNA expression of the proliferation-related genes, PCNA, CCND1, CCNB1 and CDC25A, was significantly down-regulated, while expression of the apoptosis-promoting CASP3 gene was significantly increased. In summary, we characterized the yak ALDH1A1 gene and revealed that ALDH1A1 knockdown promoted apoptosis, repressed cell proliferation, and decreased progesterone secretion by yak LCs, potentially by regulating the mRNA expression of genes related to proliferation, apoptosis, and progesterone synthesis and secretion.

Multi-Omics analysis elucidates tumor microenvironment and intratumor microbes of angiogenesis subtypes in colon cancer

BACKGROUND

Angiogenesis plays an important role in colon cancer (CC) progression.

AIM

To investigate the tumor microenvironment (TME) and intratumor microbes of angiogenesis subtypes (AGSs) and explore potential targets for antiangiogenic therapy in CC.

METHODS

The data were obtained from The Cancer Genome Atlas database and Gene Expression Omnibus database. K-means clustering was used to construct the AGSs. The prognostic model was constructed based on the differential genes between two subtypes. Single-cell analysis was used to analyze the expression level of SLC2A3 on different cells in CC, which was validated by immunofluorescence. Its biological functions were further explored in HUVECs.

RESULTS

CC samples were grouped into two AGSs (AGS-A and AGS-B) groups and patients in the AGS-B group had poor prognosis. Further analysis revealed that the AGS-B group had high infiltration of TME immune cells, but also exhibited high immune escape. The intratumor microbes were also different between the two subtypes. A convenient 6-gene angiogenesis-related signature (ARS), was established to identify AGSs and predict the prognosis in CC patients. SLC2A3 was selected as the representative gene of ARS, which was higher expressed in endothelial cells and promoted the migration of HUVECs.

CONCLUSION

Our study identified two AGSs with distinct prognoses, TME, and intratumor microbial compositions, which could provide potential explanations for the impact on the prognosis of CC. The reliable ARS model was further constructed, which could guide the personalized treatment. The SLC2A3 might be a potential target for antiangiogenic therapy.

Identification of VEGFs-related gene signature for predicting microangiogenesis and hepatocellular carcinoma prognosis

Microangiogenesis is an important prognostic factor in various cancers, including hepatocellular carcinoma (HCC). The Vascular Endothelial Growth Factor (VEGF) has been shown to contribute to tumor angiogenesis. Recently, several studies have investigated the regulation of VEGF production by a single gene, with few researchers exploring all genes that affect VEGF production. In this study, we comprehensively analyzed all genes affecting VEGF production in HCC and developed a risk model and gene-based risk score based on VEGF production. Moreover, the model's predictive capacity on prognosis of HCCs was verified using training and validation datasets. The developed model showed good prediction of the overall survival rate. Patients with a higher risk score experienced poor outcomes compared to those with a lower risk score. Furthermore, we identified the immunological causes of the poor prognosis of patients with high-risk scores comparing with those with low-risk scores.

The anti-hepatocellular carcinoma effect of Aidi injection was related to the synergistic action of cantharidin, formononetin, and isofraxidin through BIRC5, FEN1, and EGFR

ETHNOPHARMACOLOGICAL RELEVANCE

Aidi injection (ADI) is a popular anti-tumor Chinese patent medicine, widely used in clinics for the treatment of hepatocellular carcinoma (HCC) with remarkable therapeutic effects through multiple targets and pathways. However, the scientific evidence of the synergistic role of the complex chemical component system and the potential mechanism for treating diseases are ignored and remain to be elucidated.

AIM OF THE STUDY

This study aimed to elucidate and verify the cooperative association between the potential active ingredient of ADI, which is of significance to enlarge our understanding of its anti-HCC molecular mechanisms.

MATERIALS AND METHODS

Firstly, the anti-HCC effect of ADI was evaluated in various HCC cells and the zebrafish xenograft model. Subsequently, a variety of bioinformatic technologies, including network pharmacology, weighted gene co-expression network analysis (WGCNA), meta-analysis of gene expression profiles, and pathway enrichment analysis were performed to construct the competitive endogenous RNA (ceRNA) network of ADI intervention in HCC and to establish the relationship between the critical targets/pathways and the key corresponding components, which were involved in ADI against HCC in a synergistic way and were validated by molecular biology experiments.

RESULTS

ADI exerted remarkable anti-HCC in vitro cells and in vivo zebrafish model, especially that the Hep 3B2.1-7 cell showed substantial sensibility to ADI. The ceRNA network revealed that the EGFR/PI3K/AKT signaling pathway was identified as the promising pathway. Furthermore, the meta-analysis also demonstrated the critical role of BIRC5 and FEN1 as key targets. Finally, the synergistic effect of ADI was revealed by discovering the inhibitory effect of cantharidin on BIRC5, formononetin on FEN1 and EGFR, as well as isofraxidin on EGFR.

CONCLUSION

Our study unveiled that the incredible protective effect of ADI on HCC resulted from the synergistic inhibition effect of cantharidin, formononetin, and isofraxidin on multiple targets/pathways, including BIRC5, FEN1, and EGFR/PI3K/AKT, respectively, providing a scientific interpretation of ADI against HCC and a typical example of pharmacodynamic evaluation of other proprietary Chinese patent medicine.

Integrative profiling analysis reveals prognostic significance, molecular characteristics, and tumor immunity of angiogenesis-related genes in soft tissue sarcoma

Background

Soft tissue sarcoma (STS) is a class of malignant tumors originating from mesenchymal stroma with a poor prognosis. Accumulating evidence has proved that angiogenesis is an essential hallmark of tumors. Nevertheless, there is a paucity of comprehensive research exploring the association of angiogenesis-related genes (ARGs) with STS.

Methods

The ARGs were extracted from previous literature, and the differentially expressed ARGs were screened for subsequent analysis. Next, the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were conducted to establish the angiogenesis-related signature (ARSig). The predictive performance of the novel ARSig was confirmed using internal and external validation, subgroup survival, and independent analysis. Additionally, the association of the ARSig with the tumor immune microenvironment, tumor mutational burden (TMB), and therapeutic response in STS were further investigated. Notably, we finally conducted in vitro experiments to verify the findings from the bioinformatics analysis.

Results

A novel ARSig is successfully constructed and validated. The STS with a lower ARSig risk score in the training cohort has an improved prognosis. Also, consistent results were observed in the internal and external cohorts. The receiver operating characteristic (ROC) curve, subgroup survival, and independent analysis further indicate that the novel ARSig is a promising independent prognostic predictor for STS. Furthermore, it is proved that the novel ARSig is relevant to the immune landscape, TMB, immunotherapy, and chemotherapy sensitivity in STS. Encouragingly, we also validate that the signature ARGs are significantly dysregulated in STS, and ARDB2 and SRPK1 are closely connected with the malignant progress of STS cells.

Conclusion

In sum, we construct a novel ARSig for STS, which could act as a promising prognostic factor for STS and give a strategy for future clinical decisions, immune landscape, and personalized treatment of STS.

A DNA Damage Response Related Signature to Predict Prognosis in Patients with Acute Myeloid Leukemia

The prognosis of acute myeloid leukemia (AML) is disappointing in most subtypes and varies widely. DNA damage response (DDR) is associated with prognosis and immunotherapy in multiple cancers. Here, we identify a signature of eight DDR-related genes associated with overall survival, which stratifies AML patients into high- and low-risk groups. Patients in low-risk group were more likely to respond to sorafenib. The signature could be an independent prognostic predictor for patients treated with ADE and ADE plus gemtuzumab ozogamicin. Therefore, this DDR prognostic signature might be applied to prognostic stratification and treatment selection in AML patients, which warrants further studies.

Genes Modulating Butyrate Metabolism for Assessing Clinical Prognosis and Responses to Systematic Therapies in Hepatocellular Carcinoma

Butyrate, one of the major products of the gut microbiota, has played notable roles in diverse therapies for multiple tumors. Our study aimed to determine the roles of genes that modulate butyrate metabolism (BM) in predicting the clinical prognosis and responses to systemic therapies in hepatocellular carcinoma (HCC). The genes modulating BM were available from the GeneCard database, and gene expression and clinical information were obtained from TCGA-LIHC, GEO, ICGC-JP, and CCLE databases. Candidate genes from these genes that regulate BM were then identified by univariate Cox analysis. According to candidate genes, the patients in TCGA were grouped into distinct subtypes. Moreover, BM- related gene signature (BMGs) was created via the LASSO Cox algorithm. The roles of BMGs in identifying high-risk patients of HCC, assessing the prognoses, and predicting systematic therapies were determined in various datasets. The statistical analyses were fulfilled with R 4.1.3, GraphPad Prism 8.0 and Perl 5.30.0.1 software. In the TCGA cohort, most butyrate-related genes were over-expressed in the B cluster, and patients in the B cluster showed worse prognoses. BMGs constructed by LASSO were composed of eight genes. BMGs exhibited a strong performance in evaluating the prognoses of HCC patients in various datasets, which may be superior to 33 published biomarkers. Furthermore, BMGs may contribute to the early surveillance of HCC, and BMGs could play active roles in assessing the effectiveness of immunotherapy, TACE, ablation therapy, and chemotherapeutic drugs for HCC. BMGs may be served as novel promising biomarkers for early identifying high-risk groups of HCC, as well as assessing prognoses, drug sensitivity, and the responses to immunotherapy, TACE, and ablation therapy in patients with HCC.

Overexpression of KITLG predicts unfavorable clinical outcomes and promotes lymph node metastasis via the JAK/STAT pathway in nasopharyngeal carcinoma

Lymph node metastasis (LNM) is an early clinical sign and a contributor to the treatment failure in patients with nasopharyngeal carcinoma (NPC). The molecular mechanisms of LNM in NPC remain unclear. We aimed to identify and validate the possible key genes that play a crucial role in the LNM of NPC. The study included a discovery and validation phase. In the discovery phase, the key gene was identified by bioinformatics analysis. In the validation phase, the mRNA and protein expression of the key gene was detected by RT-PCR in NPC cells and by immunohistochemistry in a tissue microarray. Then, the effect of the key gene expression on cell invasion and migration was explored in vitro and in vivo. As a result, KITLG was identified as the key gene. The overexpression of KITLG was detected in NPC cells, which was correlated with neck lymph node metastasis and poor prognosis in patients with NPC. The suppression of KITLG inhibited the proliferation, invasion, and metastasis of NPC cells in vitro and in vivo. JAK/STAT signaling pathway might mediate the enhancement of cell invasion and metastasis caused by KITLG. In summary, the overexpression of KITLG in NPC cells might play a crucial role in the LNM of NPC, raising the possibility of KITLG as a prognostic factor and a potential target for NPC treatment.

Prognostic model and immunotherapy prediction based on molecular chaperone-related lncRNAs in lung adenocarcinoma

Introduction: Molecular chaperones and long non-coding RNAs (lncRNAs) have been confirmed to be closely related to the occurrence and development of tumors, especially lung cancer. Our study aimed to construct a kind of molecular chaperone-related long non-coding RNAs (MCRLncs) marker to accurately predict the prognosis of lung adenocarcinoma (LUAD) patients and find new immunotherapy targets.

Methods: In this study, we acquired molecular chaperone genes from two databases, Genecards and molecular signatures database (MsigDB). And then, we downloaded transcriptome data, clinical data, and mutation information of LUAD patients through the Cancer Genome Atlas (TCGA). MCRLncs were determined by Spearman correlation analysis. We used univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to construct risk models. Kaplan-meier (KM) analysis was used to understand the difference in survival between high and low-risk groups. Nomogram, calibration curve, concordance index (C-index) curve, and receiver operating characteristic (ROC) curve were used to evaluate the accuracy of the risk model prediction. In addition, we used gene ontology (GO) enrichment analysis and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses to explore the potential biological functions of MCRLncs. Immune microenvironmental landscapes were constructed by using single-sample gene set enrichment analysis (ssGSEA), tumor immune dysfunction and exclusion (TIDE) algorithm, “pRRophetic” R package, and “IMvigor210” dataset. The stem cell index based on mRNAsi expression was used to further evaluate the patient’s prognosis.

Results: Sixteen MCRLncs were identified as independent prognostic indicators in patients with LUAD. Patients in the high-risk group had significantly worse overall survival (OS). ROC curve suggested that the prognostic features of MCRLncs had a good predictive ability for OS. Immune system activation was more pronounced in the high-risk group. Prognostic features of the high-risk group were strongly associated with exclusion and cancer-associated fibroblasts (CAF). According to this prognostic model, a total of 15 potential chemotherapeutic agents were screened for the treatment of LUAD. Immunotherapy analysis showed that the selected chemotherapeutic drugs had potential application value. Stem cell index mRNAsi correlates with prognosis in patients with LUAD.

Conclusion: Our study established a kind of novel MCRLncs marker that can effectively predict OS in LUAD patients and provided a new model for the application of immunotherapy in clinical practice.

BIRC5 Modulates PD-L1 Expression and Immune Infiltration in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most prevalent thoracic cancer with the highest incidence and mortality worldwide. Baculoviral IAP Repeat Containing 5 (BIRC5) is well studied in many malignancies, its prognosis value and correlation with the tumor microenvironment (TME) in LAUD remains largely elusive.

Methods: The Wilcoxon signed-rank test and logistic regression were used to evaluate the relationship between clinical features and BIRC5 expression in LUAD. To assess the impact of BIRC5 on prognosis, the Kaplan-Meier plotter analysis and Cox regression were used, as well as a receiver operating characteristic (ROC) curve and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were recruited to predict the association between BIRC5 and immune cell infiltrations. Furthermore, qRT-PCR and western bolt were utilized to confirm gene expression on mRNA and protein levels. The proliferation of A549 and H1299 cells was evaluated using CCK8 and EdU assay. Cell mobility was tested by transwell assay and wound healing assay. Detection of PD-L1 and infiltrated CD8 T cells in xenograft tumors was done by flow cytometry.

Results: BIRC5 expression was found to be substantially greater in LUAD patients. According to KM-plotter analysis, patients with high levels of BIRC5 had shorter survival rates. Multivariate Cox analysis revealed that elevated BIRC5 expression was an independent risk factor for OS and PFS in LUAD patients. High BIRC5 expression was predicted to be associated with chemokine activity and immune cell chemotaxis, whereas ssGSEA suggested that BIRC5 is highly associated with CD8 T cell infiltration and PD-L1 levels. In vitro experiments suggested overexpression of BIRC5 promoted the proliferation, mobility, and PD-L1 level of A549 cells, and vice versa in H1299 cells. Furthermore, in vivo study suggested elevated tumor weight and PD-L1 levels in xenograft tumors generated from LLC cells with overexpressed BIRC5.

Conclusion: BIRC5 promotes lung adenocarcinoma progression by modulating PD-L1 expression and inducing tumor immune evasion.

Identification of Potential Prognostic Biomarkers Associated with Monocyte Infiltration in Lung Squamous Cell Carcinoma

The five-year survival rate of lung squamous cell carcinoma is significantly lower than that of other cancer types. It is therefore urgent to discover novel prognosis biomarkers and therapeutic targets and understand their correction with infiltrating immune cells to improve the prognosis of patients with lung squamous cell carcinoma. In this study, we employed robust rank aggregation algorithms to overcome the shortcomings of small sizes and potential bias in each Gene Expression Omnibus dataset of lung squamous cell carcinoma and identified 513 robust differentially expressed genes including 220 upregulated and 293 downregulated genes from six microarray datasets. Functional enrichment analysis showed that these robust differentially expressed genes were obviously involved in the extracellular matrix and structure organization, epidermis development, cell adhesion molecule binding, p53 signaling pathway, and interleukin-17 signaling pathway to affect the progress of lung squamous cell carcinoma. We further identified six hub genes from 513 robust differentially expressed genes by protein-protein interaction network and 10 topological analyses. Moreover, the results of immune cell infiltration analysis from six integrated Gene Expression Omnibus datasets and our sequencing transcriptome data demonstrated that the abundance of monocytes was significantly lower in lung squamous cell carcinoma compared to controls. Immune correlation analysis and survival analysis of hub genes suggested that three hub genes, collagen alpha-1(VII) chain, mesothelin, and chordin-like protein 1, significantly correlated with tumor-infiltrating monocytes as well as may be potential prognostic biomarkers and therapy targets in lung squamous cell carcinoma. The investigation of the correlation of hub gene markers and infiltrating monocytes can also improve to well understand the molecular mechanisms of lung squamous cell carcinoma development.

Identification of chromatin organization-related gene signature for hepatocellular carcinoma prognosis and predicting immunotherapy response

BACKGROUND

Chromatin organization is associated with tumorigenesis; however, information on its role in hepatocellular carcinoma (HCC) is limited. Moreover, although immune checkpoint inhibitors (ICIs) have proven effective against HCC, the optimal index remains unknown. In this study, we aimed to construct a chromatin organization-related gene signature (CORGS) for prognosis and predicting response to ICIs in HCC.

METHODS

HCC-related data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Construction (ICGC). Chromatin organization-related genes (CORGs) were retrieved from Gene Set Enrichment Analysis. Differentially expressed genes (DEGs) and prognostic genes were then applied to select candidate genes using advanced statistical methods, including learning vector quantization, random forest, and lasso regression. Subsequently, the CORGS was established based on chromatin organization-related hub genes using multivariate Cox regression analysis, evaluated with Kaplan-Meier survival curves, and verified in 64 samples of HCC patients from Fujian Provincial Hospital (FPH) via quantitative PCR. Subsequently, functional enrichment analysis, tumor somatic mutation analysis, and tumor immune analysis were performed to evaluate the potential value of the CORGS.

RESULTS

Three hundred and thirty-nine CORGs were identified as DEGs, and 186 were associated with HCC prognosis (all P < 0.05). Four intersection genes were selected to establish the CORGS using TCGA cohort, which was found to serve as an independent risk factor for HCC patients. CORGS was then validated in an ICGC cohort. In addition, CORGS reliability was verified in 64 samples from HCC patients and 26 adjacent non-tumorous tissues, collected from the FPH. The CORGS was also associated with tumor immune microenvironment characteristics and ICI response. Moreover, data from "IMvigor 210" revealed that more patients in the low CORGS group responded to atezolizumab compared to high CORGS patients (P < 0.05). Finally, a nomogram of tumor characteristics and the CORGS was established, exhibiting superior discrimination and calibration compared to the current staging system and published models.

CONCLUSIONS

CORGS may serve as an effective predictive biomarker for HCC as well as a potential index of the tumor immune microenvironment and ICI response.

ALDH1A1 in Cancers: Bidirectional Function, Drug Resistance, and Regulatory Mechanism

Aldehyde dehydrogenases 1 family member A1(ALDH1A1) gene codes a cytoplasmic enzyme and shows vital physiological and pathophysiological functions in many areas. ALDH1A1 plays important roles in various diseases, especially in cancers. We reviewed and summarized representative correlative studies and found that ALDH1A1 could induce cancers via the maintenance of cancer stem cell properties, modification of metabolism, promotion of DNA repair. ALDH1A1 expression is regulated by several epigenetic processes. ALDH1A1 also acted as a tumor suppressor in certain cancers. The detoxification of ALDH1A1 often causes chemotherapy failure. Currently, ALDH1A1-targeted therapy is widely used in cancer treatment, but the mechanism by which ALDH1A1 regulates cancer development is not fully understood. This review will provide insight into the status of ALDH1A1 research and new viewpoint for cancer therapy.

A Necroptosis-Related lncRNA Signature Predicts Prognosis and Indicates the Immune Microenvironment in Soft Tissue Sarcomas

Background: The necroptosis and long noncoding RNA (lncRNA) are critical in the occurrence and development of malignancy, while the association between the necroptosis-related lncRNAs (NRlncRNAs) and soft tissue sarcoma (STS) remains controversial. Therefore, the present study aims to construct a novel signature based on NRlncRNAs to predict the prognosis of STS patients and investigate its possible role.

Methods: The transcriptome data and clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression database (GTEx). A novel NRlncRNA signature was established and verified by the COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the K-M survival analysis, ROC, univariate, multivariate Cox regression analysis, and nomogram were used to evaluate the predictive value of the signature. Also, a variety of bioinformatic analysis algorithms explored the differences between the potential mechanism, tumor immune status, and drug sensitivity in the two-risk group. Finally, the RT-qPCR was performed to evaluate the expression of signature NRlncRNAs.

Results: A novel signature consisting of seven NRlncRNAs was successfully established and verified with stable prediction performance and general applicability for STS. Next, the GSEA showed that the patients in the high-risk group were mainly enriched with tumor-related pathways, while the low-risk patients were significantly involved in immune-related pathways. In parallel, we found that the STS patients in the low-risk group had a better immune status than that in the high-risk group. Additionally, there were significant differences in the sensitivity to anti-tumor agents between the two groups. Finally, the RT-qPCR results indicated that these signature NRlncRNAs were abnormally expressed in STS.

Conclusion: To the best of our knowledge, it is the first study to construct an NRlncRNA signature for STS. More importantly, the novel signature displays stable value and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in STS.

Construction of a Six-Gene Prognostic Risk Model Related to Hypoxia and Angiogenesis for Cervical Cancer

Background: The prognosis of cervical cancer (CC) is poor and not accurately reflected by the primary tumor node metastasis staging system. Our study aimed to develop a novel survival-prediction model.

Methods: Hallmarks of CC were quantified using single-sample gene set enrichment analysis and univariate Cox proportional hazards analysis. We linked gene expression, hypoxia, and angiogenesis using weighted gene co-expression network analysis (WGCNA). Univariate and multivariate Cox regression was combined with the random forest algorithm to construct a prognostic model. We further evaluated the survival predictive power of the gene signature using Kaplan-Meier analysis and receiver operating characteristic (ROC) curves.

Results: Hypoxia and angiogenesis were the leading risk factors contributing to poor overall survival (OS) of patients with CC. We identified 109 candidate genes using WGCNA and univariate Cox regression. Our established prognostic model contained six genes (MOCSI, PPP1R14A, ESM1, DES, ITGA5, and SERPINF1). Kaplan-Meier analysis indicated that high-risk patients had worse OS (hazard ratio = 4.63, p < 0.001). Our model had high predictive power according to the ROC curve. The C-index indicated that the risk score was a better predictor of survival than other clinicopathological variables. Additionally, univariate and multivariate Cox regressions indicated that the risk score was the only independent risk factor for poor OS. The risk score was also an independent predictor in the validation set (GSE52903). Bivariate survival prediction suggested that patients exhibited poor prognosis if they had high z-scores for hypoxia or angiogenesis and high risk scores.

Conclusions: We established a six-gene survival prediction model associated with hypoxia and angiogenesis. This novel model accurately predicts survival and also provides potential therapeutic targets.

Pan-Cancer Study of SHC-Adaptor Protein 1 (SHC1) as a Diagnostic, Prognostic and Immunological Biomarker in Human Cancer

Background: Recent studies highlight the carcinogenesis role of SHC-adaptor protein 1 (SHC1) in cancer initiation, development, and progression. However, its aberrant expression, diagnostic and prognostic value remain unknown in a variety of tumors.

Methods: The SHC1 expression profiles were analyzed using GTEx database, TCGA database, Oncomine and CPTAC database. The survival analysis was conducted using GEPIA2, Kaplan-Meier Plotter, UALCAN, and PrognoScan. The diagnostic values of SHC1 were calculated with the “pROC” package in R software. The genetic alteration of SHC1 and mutations were analyzed using cBioPortal. TIMER2 was employed to estimate the correlations between SHC1 expression and tumor-infiltrating immune cells in the TCGA cohort. Enrichment analysis of SHC1 was conducted using the R package “clusterProfiler.”

Results: SHC1 was ubiquitously highly expressed and closely associated with worse prognosis of multiple major cancer types (all p < 0.05). Further, SHC1 gene mutations were strongly linked to poor OS and DFS in SKCM (all p < 0.05). An enhanced phosphorylation level of SHC1 at the S139 site was observed in clear cell RCC. Additionally, the results revealed SHC1 expression was strongly linked to TMB, MMRs, MSI, TAMs, DNA methylation, m6A RNA methylation, tumor-associated immune infiltration, and immune checkpoints in multiple cancers (all p < 0.05). In addition, the results of the ROC analysis indicated the SHC1 exhibited strong diagnostic capability for KICH (AUC = 0.92), LIHC (AUC = 0.95), and PAAD (AUC = 0.95). Finally, enrichment analysis indicated that SHC1 may potentially involve in the regulation of numerous signaling pathways in cancer metabolism and protein phosphorylation-related functions.

Conclusions: These findings highlight that SHC1 plays an important role in the tumor immune microenvironment, and SHC1 has been identified to have prognostic and diagnostic value in multiple cancers. Thus, SHC1 is a potential target for cancer immunotherapy and effective prognostic and diagnostic biomarker.

A Novel Hypoxic-Angiogenesis-Immune-Related Gene Model for Prognostic and Therapeutic Effect Prediction in Hepatocellular Carcinoma Patients

Background

Hepatocellular carcinoma (HCC) is one of the most heterogeneous malignant tumors that have been discovered so far, which makes the prognostic prediction difficult. The hypoxia, angiogenesis, and immunity-related genes (HAIRGs) are closely related to the development of liver cancer. However, the prognostic and treatment effect of hypoxia, angiogenesis, and immunity-related genes in HCC continues to be further clarified.

Methods

The gene expression quantification data and clinical information in patients with liver cancer were downloaded from the TCGA database, and HAIRG signature was built by using the least absolute shrinkage and selection operator (LASSO) technique. Patient from the ICGC database validated the model. Then, tumor immune dysfunction and exclusion (TIDE) algorithm was applied to estimate the clinical response to immunotherapy and the sensitivity of drugs was evaluated by the half-maximal inhibitory concentration (IC₅₀).

Result

The HAIRGs were identified between the HCC patients and normal patients in the TCGA database. In univariate Cox regression analysis, seventeen differentially expressed genes (DEGs) were associated with overall survival (OS). An eight HAIRG signature model was constructed and was used to divide the patients into two groups according to the median value of the risk score base on the TCGA dataset. Patients in the high-risk group had a significant reduction in OS compared to those in the low-risk group (P < 0.001 in the TCGA, P < 0.001 in the ICGC). For TCGA and ICGC databases of univariate Cox regression analyses, the risk score was used as an independent predictor of OS (HR > 1, P < 0.001). Functional analysis showed that the relevant immune pathways and immune responses were enriched, cellular component analysis showed that the immunoglobulin complex and other related substances were enriched, and immune status existed a difference in the high- and low-risk groups. Then, the tumor immune dysfunction and exclusion (TIDE) algorithm presented differences in immune response in the high- and low-risk groups (P < 0.05), and based on drug sensitivity prediction, patients in the high-risk group were more sensitive to cisplatin compared to those in the low-risk group in both the TCGA and ICGC cohorts (P < 0.05).

Conclusions

HAIRG signature can be utilized for prognostic prediction in HCC, while it can be considered a prediction model for clinical evaluation of immunotherapy response and chemotherapy sensitivity in HCC.

Identification and Validation of Pyroptosis-Related Gene Signature to Predict Prognosis and Reveal Immune Infiltration in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and accounts for the fourth common cause of cancer-related deaths. Recently, pyroptosis has been revealed to be involved in the progression of multiple cancers. However, the role of pyroptosis in the HCC prognosis remains elusive.

Methods: The clinical information and RNA-seq data of the HCC patients were collected from the TCGA-LIHC datasets, and the differential pyroptosis-related genes (PRG) were firstly explored. The univariate Cox regression and consensus clustering were applied to recognize the HCC subtypes. The prognostic PRGs were then submitted to the LASSO regression analysis to build a prognostic model in the TCGA training cohort. We further evaluated the predictive model in the TCGA test cohort and ICGC validation cohort (LIRI-JP). The accuracy of prediction was validated using the Kaplan—Meier (K-M) and receiver operating characteristic (ROC) analyses. The single-sample gene set enrichment analysis (ssGSEA) was used to determine the differential immune cell infiltrations and related pathways. Finally, the expression of the prognostic genes was validated by qRT-PCR in vivo and in vitro.

Results: We identified a total of 26 differential PRGs, among which three PRGs comprising GSDME, GPX4, and SCAF11 were subsequently chosen for constructing a prognostic model. This model significantly distinguished the HCC patients with different survival years in the TCGA training, test, and ICGC validation cohorts. The risk score of this model was confirmed as an independent prognostic factor. A nomogram was generated indicating the survival years for each HCC patient. The ssGSEA demonstrated several tumor-infiltrating immune cells to be remarkably associated with the risk scores. The qRT-PCR results also showed the apparent dysregulation of PRGs in HCC. Finally, the drug sensitivity was analyzed, indicating that Lenvatinib might impact the progression of HCC via targeting GSDME, which was also validated in human Huh7 cells.

Conclusion: The PRG signature comprised of GSDME, GPX4, and SCAF11 can serve as an independent prognostic factor for HCC patients, which would provide further evidence for more clinical and functional studies.

Comprehensive Analysis to Identify the Epithelial-Mesenchymal Transition-Related Immune Signatures as a Prognostic and Therapeutic Biomarkers in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction.

Aim: To construct a risk model composed of the epithelial–mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity.

Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods.

Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C.

Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.