Comprehensive Analysis of Immune-Related Prognosis of TK1 in Hepatocellular Carcinoma

Pan-cancer analysis reveals that TK1 promotes tumor progression by mediating cell proliferation and Th2 cell polarization

BACKGROUND

TK1 (Thymidine kinase 1) is a member of the thymidine kinase family and has been observed to be significantly upregulated in a variety of cancer types. However, the exact roles of TK1 in tumor progression and the tumor immune microenvironment are not fully understood. This study aims to investigate the comprehensive involvement of TK1 in pan-cancer through the utilization of bioinformatics analysis, validation of pathological tissue samples, and in vitro experimental investigations.

METHODS

The expression profiles together with diagnostic and prognostic role of TK1 in pan-cancer were investigated though TCGA, TARGET, GTEx, and CPTAC databases. The single-sample gene set enrichment analysis (ssGSEA) and single-cell sequencing datasets were used to examine the relationship between TK1 and immune infiltration. The expression of TK1 were verified in hepatocellular carcinoma (HCC) through qPCR, western blotting and immunohistochemical assays. The proliferative capacity of HCC cell lines was assessed through CCK-8 and colony formation assays, while cytokine levels were measured via ELISA. Furthermore, flow cytometry was utilized to analyze cell cycle distribution and the proportions of Th2 cells.

RESULTS

TK1 was overexpressed in most cancers and demonstrated significant diagnostic and prognostic value. Among the various immune cells in pan-cancer, Th2 cells exhibited the closest association with TK1. Furthermore, the single-cell atlas provided insights into the distribution and proportion of TK1 in immune cells of HCC. In vitro experiments revealed an elevated expression of TK1 in HCC tissue and cell lines, and its role in influencing HCC cell proliferation by regulating G0/G1 phase arrest. Additionally, TK1 in cancer cells was found to potentially modulate Th2 cell polarization through the chemokine CCL5.

CONCLUSION

TK1 holds immense potential as a biomarker for pan-cancer diagnosis and prognosis. Additionally, targeting the expression of TK1 represents a promising therapeutic approach that can enhance the efficacy of current anti-tumor immunotherapy by modulating Th2 cell polarization and multiple mechanisms.

Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC

BACKGROUND

Long noncoding RNAs (lncRNAs) are implicated in the tumor immunology of hepatocellular carcinoma (HCC).

METHODS

HCC mRNA and lncRNA expression profiles were used to extract immune-related genes with the ImmPort database, and immune-related lncRNAs with the ImmLnc algorithm. The MOVICS package was used to cluster immune-related mRNA, immune-related lncRNA, gene mutation and methylation data on HCC from the TCGA. GEO and ICGC datasets were used to validate the model. Data from single-cell sequencing was used to determine the expression of genes from the model in various immune cell types.

RESULTS

With this model, the area under the curve (AUC) for 1-, 3- and 5-year survival of HCC patients was 0.862, 0.869 and 0.912, respectively. Single-cell sequencing showed EREG was significantly expressed in a variety of immune cell types. Knockdown of the EREG target gene resulted in significant anti-apoptosis, pro-proliferation and pro-migration effects in HepG2 and HUH7 cells. Moreover, serum and liver tissue EREG levels in HCC patients were significantly higher than those of healthy control patients.

CONCLUSION

We built a prognostic model with good accuracy for predicting HCC patient survival. EREG is a potential immunotherapeutic target and a promising prognostic biomarker.

Thymidine kinase 1 appears to be a marker for the prognosis of hepatocellular carcinoma based on a large-scale, multicenter study

INTRODUCTION

The aim of this study was to investigate the role of thymidine kinase 1 (TK1) levels in hepatocellular carcinoma (HCC) prognosis and to develop a nomogram for predicting HCC prognosis.

METHOD

In this study, 1066 HCC patients were enrolled between August 2018 and April 2022. TK1 levels were measured within one week before enrollment, and the relationship with HCC prognosis was evaluated. Next, all patients were randomly assigned to the training set (70%, n = 746) and the validation set (30%, n = 320). We used multivariate Cox analysis to find independent prognostic factors in the training set to construct a nomogram. The predictive power of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The optimal critical value of TK1 was determined as 2.35 U/L using X-tile software.

RESULT

Before and after propensity score matching (PSM), the median overall survival (mOS) of the low-TK1 group (< 2.35 U/L) remained significantly longer than that of the high-TK1 group (≥ 2.35 U/L) (48.1 vs 16.5 months, p < 0.001; 75.7 vs 19.8 months, p = 0.001). Moreover, multivariate Cox analysis showed that the low TK1 level was an independent positive prognostic indicator. Additionally, the area under the ROC curve for predicting the 1-year, 2-year, and 3-year survival rates was 0.770, 0.758, and 0.805, respectively.

CONCLUSIONS

TK1 could serve as a prognostic marker for HCC. In addition, the nomogram showed good predictive capability for HCC prognosis.

Construction and validation of a immune-related prognostic gene DHRS1 in hepatocellular carcinoma based on bioinformatic analysis

A member of the short-chain dehydrogenase/reductase superfamily (DHRS1, SDR19C1) is a member of the short-chain dehydrogenase/reductase superfamily and a potential predictor of hepatocellular carcinoma (HCC). However, the role of DHRS1 in HCC immunity remains unclear. We systematically analyzed the association between DHRS1 and HCC immunity with transcriptional and clinical data from the Tumor Immune Estimation Resource, an integrated repository portal for tumor immune system interactions, and cBioPortal databases. Six DHRS1-associated immunomodulators strongly correlated with survival and were uncovered by exploiting univariate and multivariate Cox analyses. We created a risk score for each patient by adding the points from each immunomodulator and then classified them into high and low risk categories. Survival analysis were used to compare the overall survival between the 2 groups, and the receiver operating characteristic curve was applied to assess the accuracy of the risk score. Data from our center were adopted as the external validation set, the risk score was calculated using the risk coefficient of the 6 genes in the training cohort, and survival analysis were executed to verify the experimental group results. A nomogram was ultimately constructed with the R package. Our data revealed a correlation between the levels of immune cell infiltration and either the DHRS1 gene copy numbers or mRNA levels in HCC. Second, we generated a signature based on the 6 DHRS1-related immunomodulators (KDR, TNFRSF4, CD276, TNFSF4, SLAMF6, and SIGLEC9). We postulate that the generated risk scores would serve as an independent indicator of HCC prognosis, with an area under the receiver operating characteristic curve for the risk score of 0.743. We further established external validation sets to reconfirm the predictive validity of the risk score. Finally, a prognostic nomogram and calibration curve were created. The DHRS1 gene may exert an impact on HCC immunity. We posit that the nominated immune signature based on DHRS1-associated immunomodulators could constitute a promising prognostic biomarker in HCC.

Trial watch: immunotherapeutic strategies on the horizon for hepatocellular carcinoma

The use of immune checkpoint inhibitors (ICIs) targeting PD-L1/PD-1 and CTLA-4 has transformed the oncology practice of hepatocellular carcinoma. However, only 25-30% of the patients with advanced HCC treated with atezolizumab-bevacizumab or tremelimumab-durvalumab (STRIDE) respond initially, and mechanistic biomarkers and novel treatment strategies are urgently needed for patients who present with or acquire resistance to first-line ICI-based therapies. The recent approval of the STRIDE regimen has also engendered new questions, such as patient selection factors (e.g. portal hypertension and history of variceal bleed) and biomarkers, and the optimal combination and sequencing of ICI-based regimens. Triumphs in the setting of advanced HCC have also galvanized considerable interest in the broader application of ICIs to early- and intermediate-stage diseases, including clinical combination of ICIs with locoregional therapies. Among these clinical contexts, the role of ICIs in liver transplantation - which is a potentially curative strategy unique to HCC management - as a bridge to liver transplant in potential candidates or in the setting of post-transplant recurrence, warrants investigation in view of the notable theoretical risk of allograft rejection. In this review, we summarize and chart the landscape of seminal immuno-oncology trials in HCC and envision future clinical developments.

The critical role of serum thymidine kinase 1(STK1) in predicting prognosis for immunotherapy in T4 stage lung squamous cell carcinoma

Purpose

The role of serum thymidine kinase 1 (STK1) in predicting the prognosis of T4-stage lung squamous cell carcinoma (LUSC) with immunotherapy is the focus of our work.

Methods

A total of 180 LUSC patients were enrolled. In this study, according to the T stage, the patients were divided into two groups: the T1-T2 stage and the T3-T4 stage. Receiver operating characteristic (ROC) curves were used to determine the best cutoff value for predicting overall survival (OS) outcomes. The next step is to use this cutoff value to introduce univariate and multivariate Cox regression models to screen the prognostic factors in different T stages of LUSC. The association of STK1 with other clinicopathological factors was also determined. Finally, to further explore the link between STK1 and the staging of LUSC patients, we have further divided the staging into T1-3 and T4 stages. We identified factors influencing the prognosis of patients who received immunotherapy in T4 stage LUSC.

Results

First, we determined that the optimal cutoff for STK1 for predicting OS outcome was 1.165 pmol/L. Correlation analysis revealed that STK1 was over-expressed in LUSC patients at the T3-4 stage. Univariate and multivariate analysis showed that immunotherapy was an independent prognostic factor in patients with T4 stage LUSC. In the group of patients who received immunotherapy or not, the STK1 expression level was found to be an independent prognostic factor in T4 LUSC patients receiving PD-1/PD-L1 inhibitor treatment; patients with high levels of STK1 had an increased risk of death (95%CI = 1.028-2.04).

Conclusion

STK1 is associated with a higher T stage and may be an effective prognostic marker for advanced LUSC immunotherapy patients.

Multi-Omics Integration Analysis of TK1 in Glioma: A Potential Biomarker for Predictive, Preventive, and Personalized Medical Approaches

Multi-omics expression datasets obtained from multiple public databases were used to elucidate the biological function of TK1 and its effects on clinical outcomes. The Kaplan-Meier curve, a predictive nomogram mode, and the time-dependent receiver operating characteristic (ROC) curve were established to assess the role of TK1 expression in glioma prognosis. TK1 was overexpressed in glioma compared with normal samples, and patients with elevated expression of TK1 had poor overall survival. The ROC curves indicated a high diagnostic value of TK1 expression in patients of glioma; the areas under the ROC curve (AUC) were 0.682, 0.735, and 0.758 for 1 year, 3 years, and 5 years of glioma survival, respectively. For a model based on TK1 expression and other clinical characteristics, the values of AUC were 0.864, 0.896, and 0.898 for 1 year, 3 years, and 5 years, respectively. Additionally, the calibration curve indicated that the predicted and observed areas at 1 year, 3 years, and 5 years of survival were in excellent agreement. Three types of TK1 alterations-missense mutations, splice mutations, and amplifications-were identified in 25 of 2706 glioma samples. The TK1-altered group had better overall survival than the unaltered group. Single-cell function analysis showed that TK1 was positively associated with proliferation, the cell cycle, DNA repair, DNA damage, and epithelial-mesenchymal transition in glioma. Immunoinfiltration analysis indicated that TK1 expression might play different roles in low-grade glioma and glioblastoma multiforme tumor microenvironments, but TK1 expression was positively associated with activated CD4 and Th2, regardless of tumor grade. In summary, our findings identified TK1 as a novel marker for predicting clinical outcomes and a potential target for glioma.

Cuproptosis-related immune checkpoint gene signature: Prediction of prognosis and immune response for hepatocellular carcinoma

Immune checkpoint genes (ICGs), the foundation of immunotherapy, are involved in the incidence and progression of hepatocellular carcinoma (HCC). Cuproptosis is characterized by copper-induced cell death, and this novel cell death pathway has piqued the interest of researchers in recent years. It is worth noting that there is little information available in the literature to determine the relationship between cuproptosis and anti-tumor immunity. We identified 39 cuproptosis-related ICGs using ICGs co-expressed with cuproptosis-related genes. A prognostic risk signature was constructed using the Cox regression and the least absolute shrinkage and selection operator analysis methods. The signature was built using the Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma database. The TCGA and International Cancer Genome Consortium cohorts were classified into two groups; the low- and high-risk groups were determined using a prognostic signature comprised of five genes. The multivariate Cox regression analysis revealed that the signature could independently predict overall survival. Furthermore, the level of immune infiltration analysis revealed the robustness of the prognostic signature-immune cell infiltration relationship observed for Tregs, macrophages, helper T cells, and naive B cells. Both groups showed significant differences in immune checkpoint expression levels. The gene enrichment analysis was used for characterization, and the results revealed that enriching various pathways such as PI3K-AKT-mTOR signaling, glycolysis, Wnt/beta-catenin signaling, and unfolded protein response could potentially influence the prognosis of patients with HCC and the level of immune infiltration. The sensitivity of the two groups of patients to various drug-targeted therapy methods and immunotherapy was analyzed. In conclusion, the findings presented here lay the foundation for developing individualized treatment methods for HCC patients. The findings also revealed that studying the cuproptosis-based pathway can aid in the prognosis of HCC patients. It is also possible that cuproptosis contributes to developing anti-tumor immunity in patients.

An immune-related gene prognostic risk index for pancreatic adenocarcinoma

Objective

Our goal is to construct an immune-related gene prognostic risk index (IRGPRI) for pancreatic adenocarcinoma (PAAD), and to clarify the immune and molecular features in IRGPRI-defined PAAD subgroups and the benefit of immune checkpoint inhibitors (ICIs) therapy.

Method

Through differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), and univariate Cox regression analysis, 16 immune-related hub genes were identified using the Cancer Genome Atlas (TCGA) PAAD dataset (n = 182) and immune gene set. From these genes, we constructed an IRGPRI with the Cox regression method and the IRGPRI was verified based on the Gene Expression Omnibus (GEO) dataset (n = 45). Then, we analyzed the immune and molecular features and the benefit of ICI therapy in IRGPRI-defined subgroups.

Results

Five genes, including S100A16, CD40, VCAM1, TNFRSF4 and TRAF1 were used to construct IRGPRI. As with the results of the GEO cohort, the overall survival (OS) was more favorable in low IRGPRI patients versus high IRGPRI patients. The composite results pointed out that low IRGPRI was associated with immune response-related pathways, high level of CTLA4, low KRAS and TP53 mutation rate, more infiltration of activated memory CD4⁺ T cells, CD8⁺ T cells, and more benefits from ICIs therapy. In comparison, high IRGPRI was associated with cancer-related pathways, low expression of CTLA4, high KRAS and TP53 mutation rate, more infiltration of M2 macrophages, and less benefit from ICIs therapies.

Conclusion

This IRGPRI is an encouraging biomarker to define the prognosis, immune and molecular features, and benefits from ICIs treatments in PAAD.

SOCS3 Acts as an Onco-immunological Biomarker With Value in Assessing the Tumor Microenvironment, Pathological Staging, Histological Subtypes, Therapeutic Effect, and Prognoses of Several Types of Cancer

The suppressor of cytokine signaling (SOCS) family contains eight members, including SOCS1–7 and CIS, and SOCS3 has been shown to inhibit cytokine signal transduction in various signaling pathways. Although several studies have currently shown the correlations between SOCS3 and several types of cancer, no pan-cancer analysis is available to date. We used various computational tools to explore the expression and pathogenic roles of SOCS3 in several types of cancer, assessing its potential role in the pathogenesis of cancer, in tumor immune infiltration, tumor progression, immune evasion, therapeutic response, and prognostic. The results showed that SOCS3 was downregulated in most The Cancer Genome Atlas (TCGA) cancer datasets but was highly expressed in brain tumors, breast cancer, esophageal cancer, colorectal cancer, and lymphoma. High SOCS3 expression in glioblastoma multiforme (GBM) and brain lower-grade glioma (LGG) were verified through immunohistochemical experiments. GEPIA and Kaplan–Meier Plotter were used, and this bioinformatics analysis showed that high SOCS3 expression was associated with a poor prognosis in the majority of cancers, including LGG and GBM. Our analysis also indicated that SOCS3 may be involved in tumor immune evasion via immune cell infiltration or T-cell exclusion across different types of cancer. In addition, SOCS3 methylation was negatively correlated with mRNA expression levels, worse prognoses, and dysfunctional T-cell phenotypes in various types of cancer. Next, different analytical methods were used to select genes related to SOCS3 gene alterations and carcinogenic characteristics, such as STAT3, SNAI1, NFKBIA, BCL10, TK1, PGS1, BIRC5, TMC8, and AFMID, and several biological functions were identified between them. We found that SOCS3 was involved in cancer development primarily through the JAK/STAT signaling pathway and cytokine receptor activity. Furthermore, SOCS3 expression levels were associated with immunotherapy or chemotherapy for numerous types of cancer. In conclusion, this study showed that SOCS3 is an immune-oncogenic molecule that may possess value as a biomarker for diagnosis, treatment, and prognosis of several types of cancer in the future.