Promising key genes associated with tumor microenvironments and prognosis of hepatocellular carcinoma

Dissecting microenvironment in cystadenomas and hepatic cysts based on single nucleus RNA-sequencing data

Hepatic cystadenoma is a rare disease, accounting for about 5% of all cystic lesions, with a high tendency of malignant transformation. The preoperative diagnosis of cystadenoma is difficult, and some cystadenomas are easily misdiagnosed as hepatic cysts at first. Hepatic cyst is a relatively common liver disease, most of which are benign, but large hepatic cysts can lead to pressure on the bile duct, resulting in abnormal liver function. To better understand the difference between the microenvironment of cystadenomas and hepatic cysts, we performed single-nuclei RNA-sequencing on cystadenoma and hepatic cysts samples. In addition, we performed spatial transcriptome sequencing of hepatic cysts. Based on nucleus RNA-sequencing data, a total of seven major cell types were identified. Here we described the tumor microenvironment of cystadenomas and hepatic cysts, particularly the transcriptome signatures and regulators of immune cells and stromal cells. By inferring copy number variation, it was found that the malignant degree of hepatic stellate cells in cystadenoma was higher. Pseudotime trajectory analysis demonstrated dynamic transformation of hepatocytes in hepatic cysts and cystadenomas. Cystadenomas had higher immune infiltration than hepatic cysts, and T cells had a more complex regulatory mechanism in cystadenomas than hepatic cysts. Immunohistochemistry confirms a cystadenoma-specific T-cell immunoregulatory mechanism. These results provided a single-cell atlas of cystadenomas and hepatic cyst, revealed a more complex microenvironment in cystadenomas than in hepatic cysts, and provided new perspective for the molecular mechanisms of cystadenomas and hepatic cyst.

A novel model based on ubiquitination-related gene to predict prognosis and immunotherapy response in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a common cancer that is increasingly becoming a global health problem and a major public health concern. In order to improve patient outcomes, additional biomarkers and targets must be explored. Ubiquitination-related genes (URGs), as tumor regulators, exhibit multiple functions in tumor development. Our objective was to examine the influence of URGs on the prognosis of patients with HCC.

Methods

By utilizing unsupervised cluster analysis, we were able to identify URGs in the database and create a risk score profile for predicting the prognosis of patients with HCC. The model's clinical application was explored using subject operating characteristic curves, survival analysis, and correlation analysis. We additionally examined the variances in clinical traits, immune infiltration, somatic genetic alterations, and responsiveness to treatment among high- and low-risk populations identified by the prognostic model. Scores for immune cell infiltration and immune-related pathway activity were determined by performing ssGSEA enrichment analysis. Additionally, to investigate potential mechanisms, we utilized GO, KEGG and GSVA analyses.

Results

We developed a risk scoring model that relies on genes associated with ubiquitination. As the risk score increased, the malignancy and prognosis of the tumor worsened. The high-risk and low-risk groups exhibited notable disparities in relation to the immune microenvironment, genes associated with immune checkpoints, sensitivity to drugs, and response to immunotherapy.

Conclusion

The utilization of a risk model that relies on genes associated with ubiquitination can serve as a biomarker to assess the prognosis of patients with HCC, and aid in the selection of suitable therapeutic agents.

The human factor H protein family - an update

Complement is an ancient and complex network of the immune system and, as such, it plays vital physiological roles, but it is also involved in numerous pathological processes. The proper regulation of the complement system is important to allow its sufficient and targeted activity without deleterious side-effects. Factor H is a major complement regulator, and together with its splice variant factor H-like protein 1 and the five human factor H-related (FHR) proteins, they have been linked to various diseases. The role of factor H in inhibiting complement activation is well studied, but the function of the FHRs is less characterized. Current evidence supports the main role of the FHRs as enhancers of complement activation and opsonization, i.e., counter-balancing the inhibitory effect of factor H. FHRs emerge as soluble pattern recognition molecules and positive regulators of the complement system. In addition, factor H and some of the FHR proteins were shown to modulate the activity of immune cells, a non-canonical function outside the complement cascade. Recent efforts have intensified to study factor H and the FHRs and develop new tools for the distinction, quantification and functional characterization of members of this protein family. Here, we provide an update and overview on the versatile roles of factor H family proteins, what we know about their biological functions in healthy conditions and in diseases.

KLRB1 is a novel prognostic biomarker in endometrial cancer and is associated with immune infiltration

Background

Endometrial cancer (EC) has the characteristics of high mortality and poor prognosis in the advanced stage, which seriously threatens women's health. Killer cell lectin-like receptor B1 (KLRB1) is a promising immune checkpoint of which the expression level can regulate the killing effect on tumor cells of the immune system, thereby affecting the survival and prognosis of tumor patients. However, it is still unclear whether KLRB1 is associated with survival and prognosis in patients with EC. Therefore, our study focused on the relationship between KLRB1 and immune cells to explore the role of KLRB1 on the immune microenvironment, and to further explore its feasibility as a prognostic marker in EC.

Methods

In this study, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analyze the messenger RNA (mRNA) expression level of KLRB1 in normal endometrial and EC tissues. The University of Alabama at Birmingham Cancer data analysis Portal (UALCAN) database was used to determine the correlation between KLRB1 mRNA expression and clinical features among the EC patients. KLRB1 expression levels were investigated in the Tumor IMmune Estimation Resource (TIMER) database to reveal its relationship with immune cell infiltration of EC. Finally, using the R package clusterProfiler, enrichment analysis was performed on KLRB1 to study its potential function.

Results

The results suggested that KLRB1 expression varied in different tumor tissues, and the EC group had lower mRNA expression levels than did the control group. It was also found that patients with high expression of KLRB1 had a better prognosis. According to further enrichment and immune infiltration analyses, KLRB1 expression had a closed relationship with the level of infiltration of some immune cell types, such as B cells memory, eosinophils, and Tregs, among others.

Conclusions

KLRB1 expression is associated with the infiltration of immune cells and can be used as a prognostic biomarker in EC.

A predictive model of immune infiltration and prognosis of head and neck squamous cell carcinoma based on cell adhesion-related genes: including molecular biological validation

Background

Focal adhesion serves as a bridge between tumour cells and the extracellular matrix (ECM) and has multiple roles in tumour invasion, migration, and therapeutic resistance. However, studies on focal adhesion-related genes (FARGs) in head and neck squamous cell carcinoma (HNSCC) are limited.

Methods

Data on HNSCC samples were obtained from The Cancer Genome Atlas and GSE41613 datasets, and 199 FARGs were obtained from the Molecular Signatures database. The integrated datasets' dimensions were reduced by the use of cluster analysis, which was also used to classify patients with HNSCC into subclusters. A FARG signature model was developed and utilized to calculate each patient's risk score using least extreme shrinkage and selection operator regression analysis. The risk score was done to quantify the subgroups of all patients. We evaluated the model's value for prognostic prediction, immune infiltration status, and therapeutic response in HNSCC. Preliminary molecular and biological experiments were performed to verify these results.

Results

Two different HNSCC molecular subtypes were identified according to FARGs, and patients with C2 had a shorter overall survival (OS) than those with C1. We constructed an FARG signature comprising nine genes. We constructed a FARG signature consisting of nine genes. Patients with higher risk scores calculated from the FARG signature had a lower OS, and the FARG signature was considered an independent prognostic factor for HNSCC in univariate and multivariate analyses. FARGs are associated with immune cell invasion, gene mutation status, and chemosensitivity. Finally, we observed an abnormal overexpression of MAPK9 in HNSCC tissues, and MAPK9 knockdown greatly impeded the proliferation, migration, and invasion of HNSCC cells.

Conclusion

The FARG signature can provide reliable prognostic prediction for patients with HNSCC. Apart from that, the genes in this model were related to immune invasion, gene mutation status, and chemosensitivity, which may provide new ideas for targeted therapies for HNSCC.

The prognostic significance of KLRB1 and its further association with immune cells in breast cancer

Background

Killer cell lectin-like receptor B1 (KLRB1) is an important member of the natural killer cell gene family. This study explored the potential value of KLRB1 as a breast cancer (BC) biomarker and its close association with the tumor immune microenvironment during the development of BC.

Methods

We examined the differential expression of KLRB1 in pan-cancer. Clinical and RNA-Seq data from BC samples were evaluated in The Cancer Genome Atlas (TCGA) and validated in Gene Expression Omnibus (GEO) datasets and by immunohistochemistry (IHC) staining. The relationship between KLRB1 and clinical parameters was explored through Chi-square tests. The diagnostic value of KLRB1 was evaluated using a receiver operating characteristic (ROC) curve. Survival analysis was tested by Kaplan-Meier curves to demonstrate the relationship between KLRB1 and survival. Univariable and multivariate cox regression analyses were carried out as well. The analysis of immune infiltration level and gene set enrichment analysis (GSEA) were conducted to examine KLRB1's mechanism during the progression of BC. We used the Tumor Immune Estimation Resource (TIMER), the Cancer Single-cell Expression Map (CancerSCEM) database, the Tumor Immune Single-cell Hub (TISCH) database, and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method to explore KLRB1's association with immune infiltration level and different quantitative distribution of immune cells. The relevant signaling pathways in BC associated with KLRB1 were identified using GSEA.

Results

The expression of KLRB1 was downregulated across the majority of cancers including BC. The lower KLRB1 expression group exhibited shorter relapse free survival (RFS) and overall survival (OS). IHC staining showed that KLRB1 staining was weaker in breast tumor tissues than in paratumors. Additionally, GSEA identified several pathway items distinctly enriched in BC. KLRB1 expression level was also positively related to the infiltrating number of immune cells in BC. Moreover, the CancerSCEM and TISCH databases as well as the CIBERSORT method demonstrated the close relationship between KLRB1 and immune cells, particularly macrophages.

Conclusion

Low KLRB1 expression was considered an independent prognostic biomarker and played an important role in the tumor immune microenvironment of BC patients.

Comprehensive analysis of the prognosis and immune infiltration of TMC family members in renal clear cell carcinoma

Renal cancer is a common malignancy of the urinary system, and renal clear cell carcinoma (RCCC) is the most common pathological type. Transmembrane channel-like (TMC) protein is an evolutionarily conserved gene family containing 8 members, however there is still a lack of comprehensive analysis about TMC family members in RCCC. In this study, we analyzed the expression of TMC family members in RCCC from TCGA and investigated the prognosis values and immune infiltration of TMC family members in RCCC. We found that TMC2, TMC3, TMC5, TMC7 and TMC8 were significantly related with overall survival (OS) of RCCC patients. TMC3, TMC6, and TMC8 was positively correlated with the degree of immune infiltration in RCCC. TMC2, TMC6, TMC7, and TMC8 were positively correlated with immune checkpoint genes, whereas TMC4 was negative. According to KEGG and GO analysis, almost all TMCs except TMC4 were involved in the immune response. Thus, we may regard the TMC family members as novel biomarkers to predict potential prognosis and immunotherapeutic response in RCCC patients.

Fibulin-2 Facilitates Malignant Progression of Hepatocellular Carcinoma

BACKGROUND

Identification of biomarkers to assist in the clinical management of hepatocellular carcinoma represents an urgent requirement. Fibulin-2 is known to contribute to the development and progression of various cancer types. This research investigated the role of fibulin-2 in hepatocellular carcinoma and explored the possible mechanisms.

METHODS

The expression of fibulin-2 in hepatocellular carcinoma was measured by bioinformatic analysis and confirmed by western blot and immunohistochemical staining in cell lines or patients' samples. The clinicopathologic features of hepatocellular carcinoma patients was analyzed. Cell viability assays were used to explore the role of fibulin-2 on proliferation in hepatocellular carcinoma. Western blot was conducted to uncover changes of protein expression of Ras-MEK-ERK1/2 pathway when Fibulin-2 was overexpressed or silenced. Flow cytometry analyses were used to determine the roles of fibulin-2 in the function of apoptosis and cell cycle. Subcutaneous xenograft mouse models showed the tumor growth pattern after fibulin-2 silence in vivo.

RESULTS

We reported the upregulation of fibulin-2 in most hepatocellular carcinoma tissues and cells lines. Fibulin-2 promoted the proliferation of hepatocellular carcinoma cells in vitro by regulating Ras-MEK-ERK1/2 signaling pathway, whereas knockdown of fibulin-2 incurred the opposite effect on proliferation. Consistently, knockdown of fibulin-2 resulted in increased apoptosis and induced growth arrest during the G0/G1 phase transition. In vivo xenograft assessment confirmed that knockdown of fibulin-2 inhibited hepatocellular carcinoma tumor growth.

CONCLUSIONS

Fibulin-2 exhibited tumor promotor activities in malignant progression of hepatocellular carcinoma. The results of the study highlighted the potential of fibulin-2 to be utilized as a promising biomarker and therapeutic target for hepatocellular carcinoma.

Risk model based on minichromosome maintenance 2 using objective assessment for predicting survival of neuroblastoma

Aberrant minichromosome maintenance (MCM) expression is associated with tumorigenesis. Here, we performed immunohistochemistry integrated with digital pathology to identify MCM2/5/6 expression in 130 neuroblastoma patients. A risk score was established using least absolute shrinkage and selection operator that predicts outcomes according to MCM2 expression, age, and the International Neuroblastoma Staging System in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) dataset (n = 150), where the patients with high risk had significantly worse prognosis that was validated in a hospital-based cohort (n = 130). After multivariable adjustment, the risk model remained an independent factor for survival in the TARGET cohort (overall survival [OS]: hazard ratio [HR] 2.3, 95% confidence interval [CI] 1.4-4.0; event-free survival [EFS]: HR 1.8, 95% CI 1.1-3.1) and for OS in the validation cohort (HR 8.3, 95% CI 1.6-44.5). The ESTIMATE indicates that the risk model is negatively correlated with low ESTIMATE and stromal scores. These findings show the additive nature of this score, fostering its future implementation with new prognostic variables.

HCC: RNA-Sequencing in Cirrhosis

Hepatocellular carcinoma (HCC) ranks the most common types of cancer worldwide. As the fourth leading cause of cancer-related deaths, its prognosis remains poor. Most patients developed HCC on the basis of chronic liver disease. Cirrhosis is an important precancerous lesion for HCC. However, the molecular mechanisms in HCC development are still unclear. To explore the changes at the level of transcriptome in this process, we performed RNA-sequencing on cirrhosis, HCC and paracancerous tissues. Continuously changing mRNA was identified using Mfuzz cluster analysis, then their functions were explored by enrichment analyses. Data of cirrhotic HCC patients were obtained from TCGA, and a fatty acid metabolism (FAM)-related prognostic signature was then established. The performance and immunity relevance of the signature were verified in internal and external datasets. Finally, we validated the expression and function of ADH1C by experiments. As a result, 2012 differently expressed mRNA were identified by RNA-sequencing and bioinformatics analyses. Fatty acid metabolism was identified as a critical pathway by enrichment analyses of the DEGs. A FAM-related prognostic model and nomogram based on it were efficient in predicting the prognosis of cirrhotic HCC patients, as patients with higher risk scores had shorter survival time. Risk scores calculated by the signature were then proved to be associated with a tumor immune environment. ADH1C were downregulated in HCC, while silence of ADH1C could significantly promote proliferation and motility of the HCC cell line.

CD5L-associated gene analyses highlight the dysregulations, prognostic effects, immune associations, and drug-sensitivity predicative potentials of LCAT and CDC20 in hepatocellular carcinoma

BACKGROUND

The dysregulation of CD5L has been reported in hepatocellular carcinoma (HCC). However, its functions in HCC were controversial. In this study, we aimed to identify CD5L-associated pathways and markers and explore their values in HCC diagnosis, prognosis and treatment.

METHODS

HCC datasets with gene expression profiles and clinical data in TCGA and ICGC were downloaded. The immune/stroma cell infiltrations were estimated with xCell. CD5L-associated pathways and CD5L-associated genes (CD5L-AGs) were identified with gene expression comparisons and gene set enrichment analysis (GSEA). Cox regression, Kaplan-Meier survival analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were performed. The correlations of the key genes with immune/stroma infiltrations, immunoregulators, and anti-cancer drug sensitivities in HCC were investigated. At protein level, the key genes dysregulations, their correlations and prognostic values were validated in clinical proteomic tumor analysis consortium (CPTAC) database. Serum CD5L and LCAT activity in 50 HCC and 30 normal samples were evaluated and compared. The correlations of serum LCAT activity with alpha-fetoprotein (AFP), albumin (ALB) and high-density lipoprotein (HDL) in HCC were also investigated.

RESULTS

Through systemic analyses, 14 CD5L-associated biological pathways, 256 CD5L-AGs and 28 CD5L-associated prognostic and diagnostic genes (CD5L-APDGs) were identified. A risk model consisting of LCAT and CDC20 was constructed for HCC overall survival (OS), which could discriminate HCC OS status effectively in both the training and the validation sets. CD5L, LCAT and CDC20 were shown to be significantly correlated with immune/stroma cell infiltrations, immunoregulators and 31 anti-cancer drug sensitivities in HCC. At protein level, the dysregulations of CD5L, LCAT and CDC20 were confirmed. LCAT and CDC20 were shown to be significantly correlated with proliferation marker MKI67. In serum, no significance of CD5L was shown. However, the lower activity of LCAT in HCC serum was obvious, as well as its significant positive correlations ALB and HDL concentrations.

CONCLUSIONS

CD5L, LCAT and CDC20 were dysregulated in HCC both at mRNA and protein levels. The LCAT-CDC20 signature might be new predicator for HCC OS. The associations of the three genes with HCC microenvironment and anti-cancer drug sensitivities would provide new clues for HCC immunotherapy and chemotherapy.

Role of Up-Regulated Transmembrane Channel-Like Protein 5 in Pancreatic Adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a malignant tumor responsible for a heavy disease burden. Previously, only one pan-cancer study of Transmembrane channel-like protein 5 (TMC5) showed that TMC5 was highly expressed in PAAD, but the results lacked comprehensive verification, and the mechanism of TMC5 in PAAD was still unclear.

METHODS

For exploring the expression and clinical value of TMC5 in PAAD better, we adopted a comprehensive evaluation method, using internal immunohistochemistry (IHC) data combined with microarray and RNA-sequencing data collected from public databases. The single cell RNA-sequencing (scRNA-seq) data were exploited to explore the TMC5 expression in cell populations and intercellular communication. The potential mechanism of TMC5 in PAAD was analyzed from the aspects of immune infiltration, transcriptional regulation, function and pathway enrichment.

RESULTS

Our IHC data includes 148 PAAD samples and 19 non-PAAD samples, along with the available microarray and RNA-sequencing data (1166 PAAD samples, 704 non-PAAD samples). The comprehensive evaluation results showed that TMC5 was evidently up-regulated in PAAD (SMD = 1.17). Further analysis showed that TMC5 was over-expressed in cancerous epithelial cells. Furthermore, TMC5 was up-regulated in more advanced tumor T and N stages. Interestingly, we found that STAT3 as an immune marker of Th17 cells was not only positively correlated with TMC5 and up-regulated in PAAD tissues, but also the major predicted TMC5 transcription regulator. Moreover, STAT3 was involved in cancer pathway of PAAD.

CONCLUSION

Up-regulated TMC5 indicates advanced tumor stage in PAAD patients, and its role in promoting PAAD development may be regulated by STAT3.

Negative regulator NLRC3: Its potential role and regulatory mechanism in immune response and immune-related diseases

NLRC3 is a member of the pattern recognition receptors nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) family, and plays a pivotal regulatory role in modulating the activation of immune cells. In macrophages, NLRC3 inhibits the activation of the NF-κB signaling pathway, the STING/TBK1 signaling pathway, and the formation of the inflammasome. In the context of T cells immune response, NLRC3 prevents the activation of T cells by regulating the function of dendritic cells and directly influencing the function of T cells. Different from other pattern recognition receptors, NLRC3 is more closely associated with regulatory activity than pathogens recognition, it influences the fates of cells, for example, prevents proliferation, promotes apoptosis and inhibits pyroptosis. These cellular functions regulated by NLRC3 are involved in the development processes of a variety of diseases, such as infectious disease, sterile inflammatory diseases, and cancer. However, its characteristics, function and regulatory mechanism in immune response and immune-related diseases have not been addressed fully. In this review, we elaborate the potential roles of NLRC3 from several different levels, include molecular mechanism, cellular functions in the immune-related diseases.

Glycometabolism-related gene signature of hepatocellular carcinoma predicts prognosis and guides immunotherapy

Hepatocellular carcinoma (HCC) is a severe cancer endangering human health. We constructed a novel glycometabolism-related risk score to predict prognosis and immunotherapy strategies in HCC patients. The HCC data sets were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, and the glycometabolism-related gene sets were obtained from the Molecular Signature Database. The least absolute contraction and selection operator (LASSO) regression model was used to construct a risk score based on glycometabolism-related genes. A simple visual nomogram model with clinical indicators was constructed and its effectiveness in calibration, accuracy, and clinical value was evaluated. We also explored the correlation between glycometabolism-related risk scores and molecular pathways, immune cells, and functions. Patients in the low-risk group responded better to anti-CTLA-4 immune checkpoint treatment and benefited from immune checkpoint inhibitor (ICI) therapy. The study found that glycometabolism-related risk score can effectively distinguish the prognosis, molecular and immune-related characteristics of HCC patients, and may provide a new strategy for individualized treatment.

Immune Checkpoint Inhibitors for Advanced Hepatocellular Carcinoma: Monotherapies and Combined Therapies

Hepatocellular carcinoma (HCC) is an important cause of cancer death and is considered the 3rd most lethal around the world. Hepatectomy, liver transplantation, and ablation therapy are considered curative treatments for early-stage HCC. Transarterial chemoembolization is the preferred therapy for intermediate stage HCC. Ssystemic therapy is recommended for advanced HCC. For more than a decade, sorafenib and lenvatinib were used as the first-line treatment for the advanced HCC. For the great success of immunotherapy in melanoma and lung cancer, some immune-based treatments, such as immune checkpoint inhibitors (ICIs), have been applied in the treatment of HCC. The anti-programmed cell death protein 1 (PD1) antibodies, including nivolumab and pembrolizumab, have been approved by the Food and Drug Administration for sorafenib-pretreated patients. Moreover, due to the results of durable antitumor responses attained from the phase 3 trials, atezolizumab in combination with bevacizumab is now the standard therapy for advanced HCC. Recently, there are a lot of clinical trials involving the ICIs, as monotherapy or combination therapy, with tyrosine kinase inhibitors, antiangiogenic drugs, cytotoxic agents, and locoregional treatments, providing a promising outcome for advanced HCC. Thus, this review summarized the role of ICIs for HCC patients with monotherapy or combination therapy. The success and failures of monotherapy and combination therapy involving ICIs have provided advanced insights into HCC treatment and led to novel avenues to improve therapy efficacy in HCC.

PI3K/AKT/mTOR Pathway-Associated Genes Reveal a Putative Prognostic Signature Correlated with Immune Infiltration in Hepatocellular Carcinoma

Background

The dysregulated PI3K/AKT/mTOR pathway acts as the main regulator of tumorigenesis in hepatocellular carcinoma (HCC).

Aim

Here, we identify the prognostic significance of PI3K/AKT/mTOR pathway-associated genes (PAGs) as well as their putative signature based on PAGs in an HCC patient's cohort.

Methods

The transcriptomic data and clinical feature sets were queried to extract the putative prognostic signature.

Results

We identified nine PAGs with different expressions. GO and KEGG indicated that these differentially expressed genes were associated with various carcinogenic pathways. Based on the signature-computed median risk score, we categorized the patients into groups of low risk and high risk. The survival time for the low-risk group is longer than that of the high-risk group in Kaplan-Meier (KM) curves. The prognostic value of risk score (ROC = 0.736) of receiver operating characteristic (ROC) curves performed better in comparison to that of other clinicopathological features. In both the GEO database and ICGC database, these outcomes were verified. The predictions of the overall survival rates in HCC patients of 1 year, 3 years, and 5 years can be obtained separately from the nomogram. The risk score was associated with the immune infiltrations of CD8 T cells, activated CD4 memory T cells, and follicular helper T cells, and the expression of immune checkpoints (PD-1, TIGIT, TIM-3, BTLA, LAG-3, and CTLA4) was positively relevant to the risk score. The sensitivity to several chemotherapeutic drugs can also be revealed by the signature. CDK1, PITX2, PRKAA2, and SFN were all upregulated in the tumor tissue of clinical samples.

Conclusion

A putative and differential dataset-validated prognostic signature on the basis of integrated bioinformatic analysis was established in our study, providing the immunotherapeutic targets as well as the personalized treatment in HCC with neoteric insight.

Comprehensive analysis of DOK family genes expression, immune characteristics, and drug sensitivity in human tumors

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The expression of DOK family genes is related to overall survival (OS), clinical stage, tumor mutation, methylation, CNV, and SNV.

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DOK family genes are significantly associated with poor prognosis of UVM.

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DOK1-DOK3 has obvious correlation with tumor immunity and tumor microenvironment.

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DOK family gene is significantly related to tumor stemness and drug sensitivity.

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The expression of DOK family genes is related to the activation of EMT and hormone ER pathways, and is related to the inhibition of DNA damage response, cell cycle, and hormone AR pathways.

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DOK1 and DOK3, DOK2 and DOK3 have the significant correlation.

Introduction

Objectives

Methods

Results

Conclusions

Systematic Pan-Cancer Analysis of KLRB1 with Prognostic Value and Immunological Activity across Human Tumors

Introduction

KLRB1 is a gene encoding CD161 expressed in NK cells and some T cell subsets. At present, KLRB1 is believed to affect tumorigenesis and development by regulating the cytotoxicity of NK cells in several cancers. However, there is a lack of systematic reviews of KLRB1 in a variety of malignancies.

Objectives

Hence, our research is aimed at providing a relatively comprehensive understanding of the role of KLRB1 in different types of cancer, paving the way for further research on the molecular mechanism and immunotherapy potential of KLRB1.

Methods

In this study, we used relevant public databases, including TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus), CCLE (Cancer Cell Line Encyclopedia), GTEx (Genotype Tissue-Expression), and HPA (Human Protein Atlas), to perform a pan-cancer analysis of KLRB1 across 33 types of cancer. We explored the potential molecular mechanism of KLRB1 in clinical prognosis and tumor immunity from the aspects of gene expression, survival status, clinical phenotype, immune infiltration, immunotherapy response, and chemotherapeutic drug sensitivity.

Results

KLRB1 was downregulated in 13 cancers while upregulated in kidney cancer. Patients with high expression of KLRB1 have a better prognosis in most types of cancer. Moreover, the KLRB1 expression level is related to TMB and MSI and related to various immune signatures of tumor. The expression of KLRB1 can affect tumor immune cell infiltration. KLRB1 expression level can also affect the sensitivity of chemotherapy drugs.

Conclusions

KLRB1 may be a prognostic and immunological biomarker across tumors. At the same time, KLRB1 expression can reflect the sensitivity of cancer patients to chemotherapy drugs. KLRB1 may become a new target for immunotherapy.

TMC5 is Highly Expressed in Human Cancers and Corelates to Prognosis and Immune Cell Infiltration: A Comprehensive Bioinformatics Analysis

Background: The oncological role of TMC5 in human cancers has only been revealed partially. We performed integrated bioinformatics analysis to provide a thorough and detailed insight of associations between TMC5 and tumorigenesis, cancer progression, and prognosis.

Methods: With reference to the accessible online databases, the TMC5 expressions in tumor tissues and corresponding normal tissues, different pathological stages, and various cancer cells were analyzed, while the protein levels of TMC5 in different cancers were also inspected. Meanwhile, the prognostic value of TMC5 expression in multiple cancers as well as in advanced-stage patients was investigated. Furthermore, the mutational data of TMC5 and its correlation with cancer prognosis were assessed. Moreover, the association between the TMC5 level and immune cell infiltration was evaluated. Next, TMC5-related pathway alterations and drug responses were summarized. Finally, the TMC5 based protein network was generated, and relevant enrichment was performed.

Results: In our study, the expression level of TMC5 was significantly higher in the tumor tissue than that of the normal tissues in most cancer types. Fluctuations of TMC5 levels were also observed among different pathological stages. In the meantime, the protein level elevated in the tumor tissue in the cancers enrolled. Moreover, the expression of TMC5 was not only prognostic for overall survival (OS) or recurrence free survival (RFS) in various types of cancers but also correlated to OS in patients with more advanced cancers. Additionally, the mutational status of TMC5 is also associated with prognosis in cancer patients. It is worth noting that the TMC5 level was closely related to immune cell infiltrations, especially in ESCA, TGCT, and USC. The TMC5 expression was also identified as an activator for pathways including PI3K/AKT, RAS/MAPK, and TSC/mTOR, proved to be associated with multiple drug responses and assessed to be interactive with the TMEM family.

Conclusion: TMC5 might function as a potential marker for cancer survival and immune responses.

DOK5 as a Prognostic Biomarker of Gastric Cancer Immunoinvasion: A Bioinformatics Analysis

Background

Docking protein 5 (DOK5) is a member of the docking protein group of membrane proteins and is an adapter protein involved in signal transduction. Nevertheless, the role of DOK5 expression in the prognosis of gastric cancer (GC) remains unclear.

Methods

In this study, clinical prognostic parameters and survival data related to DOK5, in patients with GC, were analyzed using bioinformatics analysis comprising Oncomine and TIMER, UALCAN database, Kaplan-Meier plotter, GEPIA, GSEA, DAVID, and cBioPortal websites.

Results

In our study, GC contained various DOK5 expressions, which forecasted poor survival outcomes. Moreover, our research showed that high DOK5 could predict high-level infiltration of several GC immune cells, as evidenced by M1, TAM, M2, B cell, and T cell failure. Hence, DOK5 might become a new gastric cancer biomarker and therapeutic target. In the following analysis, in order to explore the prognostic value of DOK5 in GC, more clinical trials are needed to validate our results.

Conclusions

Through multiple database verifications, DOK5 was found to be part of the pathogenic genes for GC. Thus, it can change the formation and progression of tumors by acting on human immunity.

Identification and Validation of Immune-Related Prognostic Genes in the Tumor Microenvironment of Colon Adenocarcinoma

The tumor microenvironment (TME) has been shown to be involved in angiogenesis, tumor metastasis, and immune response, thereby affecting the treatment and prognosis of patients. This study aims to identify genes that are dysregulated in the TME of patients with colon adenocarcinoma (COAD) and to evaluate their prognostic value based on RNA omics data. We obtained 512 COAD samples from the Cancer Genome Atlas (TCGA) database and 579 COAD patients from the independent dataset (GSE39582) in the Gene Expression Omnibus (GEO) database. The immune/stromal/ESTIMATE score of each patient based on their gene expression was calculated using the ESTIMATE algorithm. Kaplan-Meier survival analysis, Cox regression analysis, gene functional enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. We found that immune and stromal scores were significantly correlated with COAD patients' overall survival (log rank p < 0.05). By comparing the high immune/stromal score group with the low score group, we identified 688 intersection differentially expressed genes (DEGs) from the TCGA dataset (663 upregulated and 25 downregulated). The functional enrichment analysis of intersection DEGs showed that they were mainly enriched in the immune process, cell migration, cell motility, Toll-like receptor signaling pathway, and PI3K-Akt signaling pathway. The hub genes were revealed by PPI network analysis. Through Kaplan-Meier and Cox analysis, four TME-related genes that were significantly related to the prognosis of COAD patients were verified in GSE39582. In addition, we uncovered the relationship between the four prognostic genes and immune cells in COAD. In conclusion, based on the RNA expression profiles of 1091 COAD patients, we screened four genes that can predict prognosis from the TME, which may serve as candidate prognostic biomarkers for COAD.

Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.

Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).

Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.

Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

"Complimenting the Complement": Mechanistic Insights and Opportunities for Therapeutics in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and a leading cause of death in the US and worldwide. HCC remains a global health problem and is highly aggressive with unfavorable prognosis. Even with surgical interventions and newer medical treatment regimens, patients with HCC have poor survival rates. These limited therapeutic strategies and mechanistic understandings of HCC immunopathogenesis urgently warrant non-palliative treatment measures. Irrespective of the multitude etiologies, the liver microenvironment in HCC is intricately associated with chronic necroinflammation, progressive fibrosis, and cirrhosis as precedent events along with dysregulated innate and adaptive immune responses. Central to these immunological networks is the complement cascade (CC), a fundamental defense system inherent to the liver which tightly regulates humoral and cellular responses to noxious stimuli. Importantly, the liver is the primary source for biosynthesis of >80% of complement components and expresses a variety of complement receptors. Recent studies implicate the complement system in liver inflammation, abnormal regenerative responses, fibrosis, carcinogenesis, and development of HCC. Although complement activation differentially promotes immunosuppressive, stimulant, and angiogenic microenvironments conducive to HCC development, it remains under-investigated. Here, we review derangement of specific complement proteins in HCC in the context of altered complement regulatory factors, immune-activating components, and their implications in disease pathogenesis. We also summarize how complement molecules regulate cancer stem cells (CSCs), interact with complement-coagulation cascades, and provide therapeutic opportunities for targeted intervention in HCC.

An immune-related gene signature for predicting survival and immunotherapy efficacy in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients.

METHODS

The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquiring immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan-Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analyses on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of a nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy.

RESULTS

Analysis of 365 HCC samples identified 11 differentially expressed immune-related genes, which were selected to establish the IRGPI. Notably, it can predict the survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy.

CONCLUSION

Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

Novel nomograms based on immune and stromal scores for predicting the disease-free and overall survival of patients with hepatocellular carcinoma undergoing radical surgery

BACKGROUND

Stromal and immune cells play important roles in hepatocellular carcinoma (HCC) development and progression. However, tools for predicting the prognosis of patients with HCC based on stromal and immune scores are not well established. We aimed to develop nomograms that predicted the disease-free survival (DFS) and overall survival (OS) of patients after radical surgery.

METHODS

Basic information of 251 patients were retrieved from The Cancer Genome Atlas. Multivariate Cox analyses identified variables predicting the prognosis of patients. DFS and OS nomograms were constructed based on the stromal and immune scores of the training group and verified in the well-matched test group.

RESULTS

An intermediate stromal score (hazards ratio [HR] = 3.177; P < .001] was an independent risk factor for DFS. An intermediate immune score independently predicted a longer DFS (HR = 0.323; P = .002) and OS (HR = 0.305; P = .021); a high immune score predicted a longer DFS (HR = 0.289; P = .002). The concordance index (C-index) of nomograms was 0.729 for DFS and 0.696 for OS in the test group.

CONCLUSION

Nomograms based on the stromal and immune scores favorably predicted the DFS and OS of patients with HCC after radical surgery.