The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma

Li, Lunxu; Xia, Shilin; Shi, Xueying; Xu, Chen; Shang, Dong

doi:10.1038/s41598-021-89747-7

Cited by 4 publications

(3 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Likewise, the peculiar contribution of long non-coding RNA (IARlncRNA) can also not be excluded. To date, several prognostic signatures involving autophagy-related (AR) and immune-related (IR) genes have been shown [ 24 , 25 , 26 ], and some have even attempted to combine them with lncRNAs [ 27 , 28 ]. However, to date, no combinatorial signature utilizing IR, AR and lncRNAs has been shown.…”

Section: Discussionmentioning

confidence: 99%

Immunoautophagy-Related Long Noncoding RNA (IAR-lncRNA) Signature Predicts Survival in Hepatocellular Carcinoma

Wang

Sharma

et al. 2021

Biology

View full text Add to dashboard Cite

Background: The dysregulation of autophagy and immunological processes has been linked to various pathophysiological conditions, including cancer. Most notably, their particular involvement in hepatocellular carcinoma (HCC) is becoming increasingly evident. This has led to the possibility of developing a prognostic signature based on immuno-autophagy-related (IAR) genes. Given that long non-coding RNAs (lncRNAs) also play a special role in HCC, a combined signature utilizing IAR genes and HCC-associated long noncoding RNAs (as IARlncRNA) may potentially help in the clinical scenario. Method: We used Pearson correlation analysis, Kaplan–Meier survival curves, univariate and multivariate Cox regression, and ROC curves to generate and validate a prognostic immuno-autophagy-related long non-coding RNA (IARlncRNA) signature. The Chi-squared test was utilized to investigate the correlation between the obtained signature and the clinical characteristics. CIBERSORT algorithms and the Wilcoxon rank sum test were applied to investigate the correlation between signature and infiltrating immune cells. GO and KEGG analyses were performed to derived signature-dependent pathways. Results: Herein, we build an IAR-lncRNA signature (as first in the literature) and demonstrate its prognostic ability in hepatocellular carcinoma. Primarily, we identified three IARlncRNAs (MIR210HG, AC099850.3 and CYTOR) as unfavorable prognostic determinants. The obtained signature predicted the high-risk HCC group with shorter overall survival, and was further associated with clinical characteristics such as tumor grade (t = 10.918, p = 0.001). Additionally, several infiltrating immune cells showed varied fractions between the low-risk group and the high-risk HCC groups in association with the obtained signature. In addition, pathways analysis described by the signature clearly distinguishes both risk groups in HCC. Conclusions: The immuno-autophagy-related long non-coding RNA (IARlncRNA) signature we established exhibits a prognostic ability in hepatocellular carcinoma. To our knowledge, this is the first attempt in the literature to combine three determinants (immune, autophagy and LnRNAs), thus requiring molecular validation of this obtained signature in clinical samples.

show abstract

Section: Discussionmentioning

confidence: 99%

Immunoautophagy-Related Long Noncoding RNA (IAR-lncRNA) Signature Predicts Survival in Hepatocellular Carcinoma

Wang

Sharma

et al. 2021

Biology

View full text Add to dashboard Cite

show abstract

“…Moreover, MAT2A can produce SAM, which trimethylates the promoter of ACSL3, leading to ACSL3 upregulation and ferroptosis resistance in gastric cancer [71]. Consistent with these insights, many bioinformatics analyses have reported that ACSL3 can be used to predict the prognosis of various cancers [129][130][131][132][133].…”

Section: Fatty Acidsmentioning

confidence: 94%

Metabolism-regulated ferroptosis in cancer progression and therapy

Ye,

Wen,

Qin

et al. 2024

Cell Death Dis

View full text Add to dashboard Cite

Cancer metabolism mainly includes carbohydrate, amino acid and lipid metabolism, each of which can be reprogrammed. These processes interact with each other to adapt to the complicated microenvironment. Ferroptosis is a regulated cell death induced by iron-dependent lipid peroxidation, which is morphologically different from apoptosis, necrosis, necroptosis, pyroptosis, autophagy-dependent cell death and cuprotosis. Cancer metabolism plays opposite roles in ferroptosis. On the one hand, carbohydrate metabolism can produce NADPH to maintain GPX4 and FSP1 function, and amino acid metabolism can provide substrates for synthesizing GPX4; on the other hand, lipid metabolism might synthesize PUFAs to trigger ferroptosis. The mechanisms through which cancer metabolism affects ferroptosis have been investigated extensively for a long time; however, some mechanisms have not yet been elucidated. In this review, we summarize the interaction between cancer metabolism and ferroptosis. Importantly, we were most concerned with how these targets can be utilized in cancer therapy.

show abstract

“…What's more, TDT was highly associated with tumor vascular invasion and recurrence [ 12 ] and could be regarded as a reliable predictor of sorafenib's therapeutic effect [ 7 ], suggesting that TDT might have a significant relationship with the cancer immune status. Furthermore, immunotherapy is becoming the new standard of treatment for advanced stages, considering its increasing use worldwide to treat HCC patients, although the inadequate immune response has been a growing concern [ 13 ]. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear.…”

Section: Introductionmentioning

confidence: 99%

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

Zhang

et al. 2021

Cancer Cell Int

View full text Add to dashboard Cite

Background Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs. Methods Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed. Results Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells. Conclusions In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies.

show abstract

The novel immune-related genes predict the prognosis of patients with hepatocellular carcinoma

Cited by 4 publications

References 75 publications

Immunoautophagy-Related Long Noncoding RNA (IAR-lncRNA) Signature Predicts Survival in Hepatocellular Carcinoma

Immunoautophagy-Related Long Noncoding RNA (IAR-lncRNA) Signature Predicts Survival in Hepatocellular Carcinoma

Metabolism-regulated ferroptosis in cancer progression and therapy

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

Contact Info

Product

Resources

About