Stemness and reprogramming in liver cancer

StemSC: a cross-dataset human stemness index for single-cell samples

Background

Stemness is defined as the potential of cells for self-renewal and differentiation. Many transcriptome-based methods for stemness evaluation have been proposed. However, all these methods showed low negative correlations with differentiation time and can’t leverage the existing experimentally validated stem cells to recognize the stem-like cells.

Methods

Here, we constructed a stemness index for single-cell samples (StemSC) based on relative expression orderings (REO) of gene pairs. Firstly, we identified the stemness-related genes by selecting the genes significantly related to differentiation time. Then, we used 13 RNA-seq datasets from both the bulk and single-cell embryonic stem cell (ESC) samples to construct the reference REOs. Finally, the StemSC value of a given sample was calculated as the percentage of gene pairs with the same REOs as the ESC samples.

Results

We validated the StemSC by its higher negative correlations with differentiation time in eight normal datasets and its higher positive correlations with tumor dedifferentiation in three colorectal cancer datasets and four glioma datasets. Besides, the robust of StemSC to batch effect enabled us to leverage the existing experimentally validated cancer stem cells to recognize the stem-like cells in other independent tumor datasets. And the recognized stem-like tumor cells had fewer interactions with anti-tumor immune cells. Further survival analysis showed the immunotherapy-treated patients with high stemness had worse survival than those with low stemness.

Conclusions

StemSC is a better stemness index to calculate the stemness across datasets, which can help researchers explore the effect of stemness on other biological processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02803-5.

N1-methyladenosine methylation in tRNA drives liver tumourigenesis by regulating cholesterol metabolism

Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancers and is characterized by high recurrence and heterogeneity, yet its mechanism is not well understood. Here we show that N1-methyladenosine methylation (m1A) in tRNA is remarkably elevated in hepatocellular carcinoma (HCC) patient tumour tissues. Moreover, m1A methylation signals are increased in liver cancer stem cells (CSCs) and are negatively correlated with HCC patient survival. TRMT6 and TRMT61A, forming m1A methyltransferase complex, are highly expressed in advanced HCC tumours and are negatively correlated with HCC survival. TRMT6/TRMT61A-mediated m1A methylation is required for liver tumourigenesis. Mechanistically, TRMT6/TRMT61A elevates the m1A methylation in a subset of tRNA to increase PPARδ translation, which in turn triggers cholesterol synthesis to activate Hedgehog signaling, eventually driving self-renewal of liver CSCs and tumourigenesis. Finally, we identify a potent inhibitor against TRMT6/TRMT61A complex that exerts effective therapeutic effect on liver cancer.

Co-Expression of CD34, CD90, OV-6 and Cell-Surface Vimentin Defines Cancer Stem Cells of Hepatoblastoma, Which Are Affected by Hsp90 Inhibitor 17-AAG

Cancer stem cells (CSCs) are nowadays one of the major focuses in tumor research since this subpopulation was revealed to be a great obstacle for successful treatment. The identification of CSCs in pediatric solid tumors harbors major challenges because of the immature character of these tumors. Here, we present CD34, CD90, OV-6 and cell-surface vimentin (csVimentin) as reliable markers to identify CSCs in hepatoblastoma cell lines. We were able to identify CSC characteristics for the subset of CD34⁺CD90⁺OV-6⁺csVimentin⁺-co-expressing cells, such as pluripotency, self-renewal, increased expression of EMT markers and migration. Treatment with Cisplatin as the standard chemotherapeutic drug in hepatoblastoma therapy further revealed the chemo-resistance of this subset, which is a main characteristic of CSCs. When we treated the cells with the Hsp90 inhibitor 17-AAG, we observed a significant reduction in the CSC subset. With our study, we identified CSCs of hepatoblastoma using CD34, CD90, OV-6 and csVimentin. This set of markers could be helpful to estimate the success of novel therapeutic approaches, as resistant CSCs are responsible for tumor relapses.

Immunotherapy against programmed death-1/programmed death ligand 1 in hepatocellular carcinoma: Importance of molecular variations, cellular heterogeneity, and cancer stem cells

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy related to diverse etiological factors. Different oncogenic mechanisms and genetic variations lead to multiple HCC molecular classifications. Recently, an immune-based strategy using immune checkpoint inhibitors (ICIs) was presented in HCC therapy, especially with ICIs against the programmed death-1 (PD-1) and its ligand PD-L1. However, despite the success of anti-PD-1/PD-L1 in other cancers, a substantial proportion of HCC patients fail to respond. In this review, we gather current information on biomarkers of anti-PD-1/PD-L1 treatment and the contribution of HCC heterogeneity and hepatic cancer stem cells (CSCs). Genetic variations of PD-1 and PD-L1 are associated with chronic liver disease and progression to cancer. PD-L1 expression in tumoral tissues is differentially expressed in CSCs, particularly in those with a close association with the tumor microenvironment. This information will be beneficial for the selection of patients and the management of the ICIs against PD-1/PD-L1.

A stemness-based eleven-gene signature correlates with the clinical outcome of hepatocellular carcinoma

Background

Cumulative evidences have been implicated cancer stem cells in the tumor environment of hepatocellular carcinoma (HCC) cells, whereas the biological functions and prognostic significance of stemness related genes (SRGs) in HCC is still unclear.

Methods

Molecular subtypes were identified by cumulative distribution function (CDF) clustering on 207 prognostic SRGs. The overall survival (OS) predictive gene signature was developed, internally and externally validated based on HCC datasets including The Cancer Genome Atlas (TCGA), GEO and ICGC datasets. Hub genes were identified in molecular subtypes by protein-protein interaction (PPI) network analysis, and then enrolled for determination of prognostic genes. Univariate, LASSO and multivariate Cox regression analyses were performed to assess prognostic genes and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC) curve, Kaplan-Meier curve and nomogram were used to assess the performance of the gene signature.

Results

We identified four molecular subtypes, among which the C2 subtype showed the highest SRGs expression levels and proportions of immune cells, whereas the worst OS; the C1 subtype showed the lowest SRGs expression levels and was associated with most favorable OS. Next, we identified 11 prognostic genes (CDX2, PON1, ADH4, RBP2, LCAT, GAL, LPA, CYP19A1, GAST, SST and UGT1A8) and then constructed a prognostic 11-gene module and validated its robustness in all three datasets. Moreover, by univariate and multivariate Cox regression, we confirmed the independent prognostic ability of the 11-gene module for patients with HCC. In addition, calibration analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the 11-gene signature.

Conclusions

Findings in the present study shed new light on the role of stemness related genes within HCC, and the established 11-SRG signature can be utilized as a novel prognostic marker for survival prognostication in patients with HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08351-0.

Microvesicles - promising tiny players' of cancer stem cells targeted liver cancer treatments: The interesting interactions and therapeutic aspects

Liver cancer is one of the most malignant cancers worldwide with poor prognosis. Intracellular mediators like microvesicles (MVs) and cancer stem cells (CSCs) are considered as potential candidates in liver cancer progression. CSCs receive stimuli from the tumor microenvironment to initiate tumor formation in which it's secreted MVs play a noteworthy role. The phenotypic conversion of tumor cells during epithelial-to-mesenchymal transition (EMT) is a key step in tumor invasion and metastasis which indicates that the diverse cell populations within the primary tumor are in a dynamic balance and can be regulated by cell to cell communication via secreted microvesicles. Thus, in this review, we aim to highlight the evidences that suggest CSCs are crucial for liver cancer development where the microvesicles plays an important part in the maintenance of its stemness properties. In addition, we summarize the existing evidences that support the concept of microvesicles, the tiny particles have a big role behind the rare immortal CSCs which controls the tumor initiation, propagation and metastasis in liver cancer. Identifying interactions between CSCs and microvesicles may offer new insights into precise anti-cancer therapies in the future.

Targeting Liver Cancer Stem Cells: An Alternative Therapeutic Approach for Liver Cancer

The first report of cancer stem cell (CSC) from Bruce et al. has demonstrated the relatively rare population of stem-like cells in acute myeloid leukemia (AML). The discovery of leukemic CSCs prompted further identification of CSCs in multiple types of solid tumor. Recently, extensive research has attempted to identity CSCs in multiple types of solid tumors in the brain, colon, head and neck, liver, and lung. Based on these studies, we hypothesize that the initiation and progression of most malignant tumors rely largely on the CSC population. Recent studies indicated that stem cell-related markers or signaling pathways, such as aldehyde dehydrogenase (ALDH), CD133, epithelial cell adhesion molecule (EpCAM), Wnt/β-catenin signaling, and Notch signaling, contribute to the initiation and progression of various liver cancer types. Importantly, CSCs are markedly resistant to conventional therapeutic approaches and current targeted therapeutics. Therefore, it is believed that selectively targeting specific markers and/or signaling pathways of hepatic CSCs is an effective therapeutic strategy for treating chemotherapy-resistant liver cancer. Here, we provide an overview of the current knowledge on the hepatic CSC hypothesis and discuss the specific surface markers and critical signaling pathways involved in the development and maintenance of hepatic CSC subpopulations.

An absolute human stemness index associated with oncogenic dedifferentiation

The progression of cancer is accompanied by the acquisition of stemness features. Many stemness evaluation methods based on transcriptional profiles have been presented to reveal the relationship between stemness and cancer. However, instead of absolute stemness index values-the values with certain range-these methods gave the values without range, which makes them unable to intuitively evaluate the stemness. Besides, these indices were based on the absolute expression values of genes, which were found to be seriously influenced by batch effects and the composition of samples in the dataset. Recently, we have showed that the signatures based on the relative expression orderings (REOs) of gene pairs within a sample were highly robust against these factors, which makes that the REO-based signatures have been stably applied in the evaluations of the continuous scores with certain range. Here, we provided an absolute REO-based stemness index to evaluate the stemness. We found that this stemness index had higher correlation with the culture time of the differentiated stem cells than the previous stemness index. When applied to the cancer and normal tissue samples, the stemness index showed its significant difference between cancers and normal tissues and its ability to reveal the intratumor heterogeneity at stemness level. Importantly, higher stemness index was associated with poorer prognosis and greater oncogenic dedifferentiation reflected by histological grade. All results showed the capability of the REO-based stemness index to assist the assignment of tumor grade and its potential therapeutic and diagnostic implications.

Look into hepatic progenitor cell associated trait: Histological heterogeneity of hepatitis B-related combined hepatocellular-cholangiocarcinoma

Combined hepatocellular-cholangiocarcinoma (CHC) is a mixed tumor containing elements of both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC). Its remarkable histological heterogeneity has been linked to putative hepatic progenitor cell (HPC) origin. However, detailed histological or phenotypic description is rarely documented. In the present study, we reassessed 68 cases previously diagnosed as hepatitis B-related CHCs by immunohistochemistry and double-fluorescence immunostaining, focusing on HPC associated phenotypic observation of intermediate area of the tumor. It was found that tumor cells showed remarkable heterogeneity in intermediate area. Tumor cells with intermediate morphology between hepatocytes and cholangiocytes were oval-shaped and small with scant cytoplasm and hyperchromatic nuclei, arranging in solid nests mostly. By Keratin 7 (K7) staining, it appeared that the nests of tumor cells represented a maturation process from the undifferentiated small cells to mature hepatocytes through the "transitional" cells. Then, these small cells were further confirmed with intermediate phenotype as HPC by exploring immature hepatocellular marker and HPC/biliary markers co-localization. In conclusion, the HPC associated trait in CHC can be interpreted by HPC origin or gain of "stemness" by dedifferentiation. It is still too soon to give a final word that it is innate or acquired signature of HPC associated trait in CHC.