Identification of TP53 mutation associated-immunotype and prediction of survival in patients with hepatocellular carcinoma

Identification and Validation of a Novel Immune Infiltration-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma by Machine-Learning Strategies

Objective

To investigate the diagnostic gene biomarkers for hepatocellular carcinoma (HCC) and identify the immune cell infiltration characteristics in this pathology.

Methods

Five gene expression datasets were obtained through Gene Expression Omnibus (GEO) portal. After batch effect removal, differentially expressed genes (DEGs) were conducted between 209 HCC and 146 control tissues and functional correlation analyses were performed. Two machine learning algorithms were used to develop diagnostic signatures. The discriminatory ability of the gene signature was measured by AUC. The expression levels and diagnostic value of the identified biomarkers in HCC were further validated in three independent external cohorts. CIBERSORT algorithm was adopted to explore the immune infiltration of HCC. A correlation analysis was carried out between these diagnostic signatures and immune cells.

Results

A total of 375 DEGs were identified. GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 were identified as the early diagnostic signatures of HCC and were all validated in external cohorts. The corresponding results of AUC presented excellent discriminatory ability of these feature genes. The immune cell infiltration analysis showed that multiple immune cells associated with these biomarkers may be involved in the development of HCC.

Conclusion

This study indicates that GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 are potential biomarkers associated with immune infiltration in HCC. Combining these genes can be used for early detection of HCC and evaluating immune cell infiltration. Further studies are needed to explore their roles underlying the occurrence of HCC.

The component with abundant immune-related cells in combined hepatocellular cholangiocarcinoma identified by cluster analysis

Combined hepatocellular cholangiocarcinoma (cHCC‐CCA) is a heterogeneous tumor sharing histological features with hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). The tumor immune microenvironment (TIME) of cHCC‐CCA is unclear. We compared the TIME of cHCC‐CCA with that of HCC and iCCA. Twenty‐three patients with cHCC‐CCA after hepatectomy were evaluated in this study. Twenty‐three patients with iCCA and HCC were also included. iCCA was matched for size, and HCC was matched for size and hepatitis virus infection with cHCC‐CCA. Immune‐related cells among the iCCA‐component of cHCC‐CCA (C‐com), HCC‐component of cHCC‐CCA (H‐com), iCCA, and HCC were assessed using multiplex fluorescence immunohistochemistry. Among C‐com, H‐com, iCCA, and HCC, multiple comparisons and cluster analysis with k‐nearest neighbor algorithms were performed using immunological variables. Although HCC had more T lymphocytes and lower PD‐L1 expression than iCCA (P < 0.05), there were no significant differences in immunological variables between C‐com and H‐com. C‐com tended to have more T lymphocytes than iCCA (P = 0.09), and C‐com and H‐com had fewer macrophages than HCC (P < 0.05). In cluster analysis, all samples were classified into two clusters: one cluster had more immune‐related cells than the other, and 12 of 23 H‐com and eight of 23 C‐com were identified in this cluster. The TIME of C‐com and H‐com may be similar, and some immunological features in these components were different from those in HCC and some iCCA. Cluster analysis identified components with abundant immune‐related cells in cHCC‐iCCA.

Nrf2 Promotes Inflammation in Early Myocardial Ischemia-Reperfusion via Recruitment and Activation of Macrophages

Cardiomyocyte apoptosis in response to inflammation is a primary cause of myocardial ischemia-reperfusion injury (IRI). Nuclear factor erythroid 2 like 2 (Nrf2) reportedly plays an important role in myocardial IRI, but the underlying mechanism remains obscure. Expression data from the normal heart tissues of mice or heart tissues treated with reperfusion for 6 h after ischemia (IR6h) were acquired from the GEO database; changes in biological function and infiltrating immune cells were analyzed. The binding between the molecules was verified by chromatin immunoprecipitation sequencing. Based on confirmation that early myocardial ischemia-reperfusion (myocardial ischemia/reperfusion for 6 hours, IR6h) promoted myocardial apoptosis and inflammatory response, we found that Nrf2, cooperating with Programmed Cell Death 4, promoted transcription initiation of C-C Motif Chemokine Ligand 3 (Ccl3) in myocardial tissues of mice treated with IR6h. Moreover, Ccl3 contributed to the high signature score of C-C motif chemokine receptor 1 (Ccr1)-positive macrophages. The high signature score of Ccr1-positive macrophages leads to the release of pro-inflammatory factors interleukin 1 beta and interleukin 6. This study is the first to elucidate the damaging effect of Nrf2 via remodeling of the immune microenvironment in early myocardial ischemia-reperfusion, which provides us with new perspectives and treatment strategies for myocardial ischemia-reperfusion.

Single-cell transcriptomics reveal the heterogeneity and dynamic of cancer stem-like cells during breast tumor progression

Breast cancer stem-like cells (BCSCs) play vital roles in tumorigenesis and progression. However, the origin and dynamic changes of BCSCs are still to be elucidated. Using the breast cancer mouse model MMTV-PyMT, we constructed a single-cell atlas of 31,778 cells from four distinct stages of tumor progression (hyperplasia, adenoma/MIN, early carcinoma and late carcinoma), during which malignant transition occurs. We identified that the precise cell type of ER^low epithelial cell lineage gave rise to the tumors, and the differentiation of ER^high epithelial cell lineage was blocked. Furthermore, we discovered a specific signature with a continuum of gene expression profiles along the tumor progression and significantly correlated with clinical outcomes, and we also found a stem-like cell cluster existed among ER^low epithelial cells. Further clustering on this stem-like cluster showed several sub-clusters indicating heterogeneity of stem-like epithelial cells. Moreover, we distinguished normal and cancer stem-like cells in this stem-like epithelial cell cluster and profiled the molecular portraits from normal stem-like cell to cancer stem-like cells during the malignant transition. Finally, we found the diverse immune cell infiltration displayed immunosuppressive characteristics along tumor progression. We also found the specific expression pattern of cytokines and their corresponding cytokine receptors in BCSCs and immune cells, suggesting the possible cross-talk between BCSCs and the immune cells. These data provide a useful resource for illuminating BCSC heterogeneity and the immune cell remodeling during breast tumor progression, and shed new light on transcriptomic dynamics during the progression at the single-cell level.

N6-methyladenosine (m6A) regulatory gene divides hepatocellular carcinoma into three subtypes

Background

The N6-methyladenosine (m6A) plays an important role in epigenetic modification and tumor progression, but the modulations of m6A in hepatocellular carcinoma (HCC) have not been determined while the relationship between m6A regulation and immune cell infiltration remains unclear.

Methods

This study investigated the modification patterns of m6A by analyzing HCC samples from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset, and performed molecular typing based on the characteristics of immune cell infiltration. The m6Ascore was also constructed to quantify m6A modifications and predict the immunotherapy response and prognosis of HCC patients.

Results

Of the 364 samples, 31 (8.52%) were genetically altered in the m6A regulatory gene, with the highest frequency of mutations in HNRNPC, ZC3H13, and LRPPRC. Three distinct molecular subtypes of m6A were identified in 590 HCC samples, which were associated with different immune cell infiltrates: immunodepletion type, immune activation type, and immune immunity type. According to the construction of the m6Ascore system in the m6A genotype, HCC patients could be divided into high and low groups. The m6A modified pattern, characterized by immune immunity and immune failure, showed a lower score and a better prognosis. However, the immune-activated type of m6A had a higher score and a poorer prognosis. Further analysis showed that the m6Ascore was correlated with tumor mutation burden (TMB), and the higher the TMB, the worse the prognosis. m6Ascore was also correlated with the expression of cytotoxic T-lymphocyte-associated protein 4 (CTAL-4), and the higher the score, the higher the expression of HCC in patients.

Conclusions

HCC has a unique m6A modification pattern, and 3 different m6A subtypes help to classify HCC, provide knowledge of drug regimens for immunotherapy, and can be used to predict treatment response and prognosis.

Loss of IL-34 Expression Indicates Poor Prognosis in Patients With Lung Adenocarcinoma

Interleukin 34 (IL-34), an additional ligand of the colony-stimulating factor-1 receptor (CSF-1R), promotes the secretion of pro-inflammatory cytokines and stimulates NF-κB and JNK-related signaling pathways. However, the potential mechanism and prognostic value of IL-34 in lung adenocarcinoma (LUAD) remain obscure. In this study, IL-34 was found to be downregulated in LUAD tissues compared with para-carcinoma tissues, and loss of IL-34 expression was correlated with shorter overall survival (OS), which was validated by bioinformatics\ analysis in TCGA (The Cancer Genome Atlas) cohort and immunohistochemical analysis in the NTU (Nantong University) cohort, respectively. Subsequently, loss of IL-34 promotes negative regulation of the immune system and inhibits the infiltration of immune cells. Moreover, IL-34 deficiency was shown to be an independent adverse prognostic factor for patients with LUAD, and subgroup analysis indicated that IL-34 might contribute to the stratified management of patients with LUAD. IL-34-based nomogram model significantly improved the accuracy of prognostic predictions for OS of patients with LUAD, both in the TCGA cohort and the NTU cohort. Taken together, our data suggested that loss of IL-34 expression is associated with poor prognosis and negative regulation of the immune system of patients with LUAD, contributing to the stratified management of patients with LUAD.

Significance of TP53 mutation in treatment and prognosis in head and neck squamous cell carcinoma

Background: TP53 is ranked as the most common mutated gene in head and neck squamous cell carcinoma (HNSCC). Results: The status of TP53 mutation was investigated on International Cancer Genome Consortium and The Cancer Genome Atlas database and TP53-related differentially expressed genes were screened out from transcriptome data and mutation information. A TP53-related prognostic gene signature (TIMP4, ONECUT2, CGNL1, DMRTA2 and NKX2.3) was constructed based on Cox regression analysis and LASSO algorithm. Univariate and multivariate analyses were carried out to identify promising prognosticators for HNSCC. Conclusion: Our findings provide a well-rounded landscape of TP53 mutation in HNSCC and pave the groundwork for developing innovative and effective cancer treatment methods for HNSCC.