LIPH promotes metastasis by enriching stem-like cells in triple-negative breast cancer

Genomic analysis and filtration of novel prognostic biomarkers based on metabolic and immune subtypes in pancreatic cancer

PURPOSE

Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer METHODS: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC RESULTS: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids CONCLUSION: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC.

Circular RNA eukaryotic translation initiation factor 6 facilitates TPC-1 cell proliferation and invasion through the microRNA-138-5p/lipase H axis

Both circular RNA eukaryotic translation initiation factor 6 (circEIF6) and microRNA (miR)-138-5p participate in thyroid cancer (TC) progression. Nevertheless, the relationship between them remains under-explored. Hence, this research ascertained the mechanism of circEIF6 in TC via miR-138-5p. After TC tissues and cells were harvested, circEIF6, miR-138-5p, and lipase H (LIPH) levels were assessed. The binding relationships among circEIF6, miR-138-5p, and LIPH were analyzed. The impacts of circEIF6, miR-138-5p, and LIPH on the invasive and proliferative abilities of TPC-1 cells were examined by Transwell and EdU assays. Tumor xenograft in nude mice was established for in vivo validation of the impact of circEIF6. CircEIF6 expression was high in TC cells and tissues. Additionally, miR-138-5p was poor and LIPH level was high in TC tissues. Mechanistically, circEIF6 competitively bound to miR-138-5p to elevate LIPH via a competitive endogenous RNA mechanism. Silencing of circEIF6 reduced TPC-1 cell proliferative and invasive properties, which was annulled by further inhibiting miR-138-5p or overexpressing LIPH. Likewise, circEIF6 silencing repressed the growth of transplanted tumors, augmented miR-138-5p expression, and diminished LIPH expression in nude mice. Conclusively, circEIF6 silencing reduced LIPH level by competitive binding to miR-138-5p, thus subduing the proliferation and invasion of TPC-1 cells.

Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients' microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy. Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan-Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment. Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils. Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options.

Potential role of LPAR5 gene in prognosis and immunity of thyroid papillary carcinoma and pan-cancer

Papillary carcinomas account for the largest proportion of thyroid cancers, with papillary thyroid carcinoma (PTC) being prone to early lymph node metastasis. Some studies have confirmed that LPAR5 can promote the progression of PTC, but immune-related analyses of LPAR5 and PTC have not been widely discussed. This study aimed to determine the role of LPAR5 in PTC prognosis and immunity. We will further explore the role of LPAR5 in 33 different tumor types. Regarding PTC, we analyzed the effect of LPAR5 expression on overall survival (OS). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Immune-related analyses of immune checkpoints (ICPs) and immune cell infiltration were also performed. For pan-cancer, R packages were used to analyze prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), and immune cell infiltration. Analysis of tumor microenvironment (TME) and ICPs was performed using Sangerbox ( http://vip.sangerbox.com/home.html ). The TISIDB database ( http://cis.hku.hk/TISIDB/index.php ) was used to identify immune and molecular subtypes. LPAR5 expression is associated with PTC prognosis and immunity as well as various human tumors. LPAR5 may be a potential biomarker for multiple malignancies and may provide a new target for cancer immunotherapy.

Proteomic profiling and ROC analysis identify CD151 and ELAVL1 as potential therapy response markers for the antiviral drug in resistant TNBC

Triple-negative breast cancer is high heterogeneous, aggressive, and metastatic with poor prognosis. Despite of advances in targeted therapies, TNBC has been reported to cause high morbidity and mortality. A rare subpopulation within the tumor microenvironment organized into a hierarchy of cancer stem cells is responsible for therapy resistance and tumor recurrence. Repurposing of antiviral drugs for cancer treatment is gaining momentum due to reduced cost, labour, and research time, but limited due to lack of prognostic, and predictive markers. The present study investigates proteomic profiling and ROC analysis to identify CD151 and ELAVL1 as potential therapy response markers for the antiviral drug 2-thio-6-azauridine (TAU) in resistant TNBC. The stemness of MDA-MB 231 and MDA-MD 468 adherent cells was enriched by culturing them under non-adherent and non-differentiation conditions. Then, CD151⁺ subpopulation was isolated and characterized for the enrichment of stemness. This study found that CD151 has overexpressed in stemness enriched subpopulations, and also showed CD44 high and CD24 low expression along with stem cell-related transcription factors octamer-binding transcription factor 4 (OCT4) and Sex determining Y-box 2 (SOX2). This study also found that TAU induced significant cytotoxicity and genotoxicity in the CD151⁺TNBC subpopulation and inhibited their proliferation by inducing DNA damage, cell cycle arrest at the G₂M phase, and apoptosis. Further, a proteomic profiling study showed that the expression of CD151 along with ELAVL1, an RNA-binding protein, was significantly reduced with TAU treatment. KM plotter showed correlation of CD151 and ELAVL1 gene expression with a poor prognosis of TNBC. ROC analysis predicted and validated CD151 and ELAVL1 as best therapy response marker for TAU in TNBC. These findings provide new insight into repurposing antiviral drug TAU for treatment of metastatic and drug resistant TNBC.

Recent Advances on the Role of ATGL in Cancer

The hypoxic state of the tumor microenvironment leads to reprogramming lipid metabolism in tumor cells. Adipose triglyceride lipase, also known as patatin-like phospholipase= domain-containing protein 2 and Adipose triglyceride lipase (ATGL), as an essential lipid metabolism-regulating enzyme in cells, is regulated accordingly under hypoxia induction. However, studies revealed that ATGL exhibits both tumor-promoting and tumor-suppressing effects, which depend on the cancer cell type and the site of tumorigenesis. For example, elevated ATGL expression in breast cancer is accompanied by enhanced fatty acid oxidation (FAO), enhancing cancer cells’ metastatic ability. In prostate cancer, on the other hand, tumor activity tends to be negatively correlated with ATGL expression. This review outlined the regulation of ATGL-mediated lipid metabolism pathways in tumor cells, emphasizing the Hypoxia-inducible factors 1 (HIF-1)/Hypoxia-inducible lipid droplet-associated (HIG-2)/ATGL axis, peroxisome proliferator-activated receptor (PPAR)/G0/G1 switch gene 2 (G0S2)/ATGL axis, and fat-specific protein 27 (FSP-27)/Early growth response protein 1 (EGR-1)/ATGL axis. In the light of recent research on different cancer types, the role of ATGL on tumorigenesis, tumor proliferation, and tumor metastasis was systemically reviewed.

Identification of a novel Calpain-2-SRC feed-back loop as necessity for β-Catenin accumulation and signaling activation in hepatocellular carcinoma

Rapid progression is the major cause of the poor prognosis of hepatocellular carcinoma (HCC); however, the underlying mechanism remained unclear. Here, we found Calpain-2 (CAPN2), a well-established protease that accelerates tumor progression in several malignancies, is overexpressed in HCC and acts as an independent predictor for poor outcomes. Furthermore, CAPN2 promoted the proliferation and invasion of HCC, and showed a positive correlation with the levels of invasion-related markers. Mechanistically, a novel CAPN2-SRC positive regulatory loop was identified upstream of β-catenin to prevent its ubiquitination and degradation, and subsequently promoted HCC progression: CAPN2 could proteolyze PTP1B to form a truncation of approximately 42 kDa with increased phosphatase activity, resulting in reduced SRC Y530 phosphorylation and increased SRC kinase activity; meanwhile, CAPN2 itself was a bone fide substrate of SRC that was primarily phosphorylated at Y625 by SRC and exhibited increased proteolysis activity upon phosphorylation. Interestingly, the CAPN2-SRC loop could not only restrain most of cytoplasmic β-catenin degradation by inhibiting GSK3β pathway, but also prevented TRIM33-induced nuclear β-catenin degradation even in β-catenin-mutant cells. Present study identified a CAPN2-SRC positive loop responsible for intracellular β-catenin accumulation and signaling activation, and targeting CAPN2 protease activity might be a promising approach for preventing HCC progression.

Regulation of cancer stem cells in triple negative breast cancer

Triple Negative Breast Cancer (TNBC) is the most lethal subtype of breast cancer. Despite the successes of emerging targeted therapies, relapse, recurrence, and therapy failure rates in TNBC significantly outpace other subtypes of breast cancer. Mounting evidence suggests accumulation of therapy resistant Cancer Stem Cell (CSC) populations within TNBCs contributes to poor clinical outcomes. These CSCs are enriched in TNBC compared to non-TNBC breast cancers. The mechanisms underlying CSC accumulation have been well-characterized and discussed in other reviews. In this review, we focus on TNBC-specific mechanisms that allow the expansion and activity of self-renewing CSCs. We highlight cellular signaling pathways and transcription factors, specifically enriched in TNBC over non-TNBC breast cancer, contributing to stemness. We also analyze publicly available single-cell RNA-seq data from basal breast cancer tumors to highlight the potential of emerging bioinformatic approaches in identifying novel drivers of stemness in TNBC and other cancers.

Biglycan Promotes Cancer Stem Cell Properties, NFκB Signaling and Metastatic Potential in Breast Cancer Cells

Simple Summary

Breast cancer stem cells (BCSCs) are a small sub-population of cells within tumors with high metastatic potential. We identified biglycan (BGN) as a prospective molecular target in BCSCs that regulates the aggressive phenotypes of these cells. These findings establish a foundation for the development of therapeutics against BGN to eliminate BCSCs and prevent metastatic breast cancer.

Abstract

It is a major challenge to treat metastasis due to the presence of heterogenous BCSCs. Therefore, it is important to identify new molecular targets and their underlying molecular mechanisms in various BCSCs to improve treatment of breast cancer metastasis. Here, we performed RNA sequencing on two distinct co-existing BCSC populations, ALDH⁺ and CD29^hi CD61⁺ from PyMT mammary tumor cells and detected upregulation of biglycan (BGN) in these BCSCs. Genetic depletion of BGN reduced BCSC proportions and tumorsphere formation. Furthermore, BCSC associated aggressive traits such as migration and invasion were significantly reduced by depletion of BGN. Glycolytic and mitochondrial metabolic assays also revealed that BCSCs exhibited decreased metabolism upon loss of BGN. BCSCs showed decreased activation of the NFκB transcription factor, p65, and phospho-IκB levels upon BGN ablation, indicating regulation of NFκB pathway by BGN. To further support our data, we also characterized CD24⁻/CD44⁺ BCSCs from human luminal MCF-7 breast cancer cells. These CD24⁻/CD44⁺ BCSCs similarly exhibited reduced tumorigenic phenotypes, metabolism and attenuation of NFκB pathway after knockdown of BGN. Finally, loss of BGN in ALDH⁺ and CD29^hi CD61⁺ BCSCs showed decreased metastatic potential, suggesting BGN serves as an important therapeutic target in BCSCs for treating metastasis of breast cancer.

The Epithelial-Mesenchymal Transition at the Crossroads between Metabolism and Tumor Progression

The transition between epithelial and mesenchymal phenotype is emerging as a key determinant of tumor cell invasion and metastasis. It is a plastic process in which epithelial cells first acquire the ability to invade the extracellular matrix and migrate into the bloodstream via transdifferentiation into mesenchymal cells, a phenomenon known as epithelial–mesenchymal transition (EMT), and then reacquire the epithelial phenotype, the reverse process called mesenchymal–epithelial transition (MET), to colonize a new organ. During all metastatic stages, metabolic changes, which give cancer cells the ability to adapt to increased energy demand and to withstand a hostile new environment, are also important determinants of successful cancer progression. In this review, we describe the complex interaction between EMT and metabolism during tumor progression. First, we outline the main connections between the two processes, with particular emphasis on the role of cancer stem cells and LncRNAs. Then, we focus on some specific cancers, such as breast, lung, and thyroid cancer.

Prognostic Value and Clinical Significance of LIPH in Breast Cancer

Background

Lipase member H (LIPH), a novel member of the mammalian triglyceride lipase family, is localized on human chromosome 3q27-q28. Exploration of the importance of the new cancer-related gene LIPH in several carcinomas has been reported in previous studies. Our study aims to systematically assess the expression pattern of LIPH in breast cancer.

Methods

Our study explored 2994 breast cancer samples with transcriptome data from the Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. We systematically evaluated the mRNA expression of LIPH in breast cancer and the overall survival (OS) of patients. The protein expression of LIPH in breast cancer was evaluated with the Human Protein Atlas. We also explored the relationship between LIPH and the immune microenvironment in pan-cancer.

Results

Both mRNA and protein expression LIPH were found to be upregulated in breast cancer tumors. The overall survival rate of patients with high LIPH expression was lower than those of patients with low LIPH expression in both the TCGA dataset (p=0.0067) and METABRIC dataset (p<0.0001). Outcomes of the multivariate analysis found that the level of LIPH expression was an independent prognostic factor in both TCGA (p=0.001) and METABRIC (p=0.019) databases. The outcomes of the univariate analysis showed that LIPH was an important prognostic factor (p=0.01 in TCGA dataset, p=0.001 in METABRIC dataset). In the TCGA dataset, outcomes showed that LIPH expression was negatively correlated with the AJCC (American Joint Committee on Cancer) stage (p=2.3e-05) and triple-negative breast cancer (TNBC) tissues (p=3.1e-10). High LIPH expression showed lower OS in the TNBC subtype (P=0.011).

Conclusion

Compared to normal tissues, the expression of LIPH was higher in breast cancer tissues in both mRNA and protein levels. This study showed that the high level of LIPH expression might be related to the worse prognosis of breast cancer.

Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

Background

The incidence and mortality of pancreatic cancer (PC) has gradually increased. The aim of this study was to identify survival-related DNA methylation (DNAm)-driven genes and establish a nomogram to predict outcomes in patients with PC.

Methods

The gene expression, DNA methylation database, and PC clinical samples were downloaded from TCGA. DNAm-driven genes were identified by integrating analyses of gene expression and DNA methylation data. Survival-related DNAm-driven genes were screened via univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to develop a risk score model for prognosis. Based on analyses of clinical parameters and risk score, a nomogram was built and validated. The independent cohort from GEO database were used for external validation.

Results

A total of 16 differentially expressed methylation-driven genes were identified. Based on LASSO Cox regression and multivariate Cox regression analysis, six genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) were chosen to develop the risk score model. In the Kaplan–Meier analysis, age, T stage, N stage, AJCC stage, radiation therapy history, tumor size, surgery type performed, pathological type, chemotherapy history, and risk score were potential prognostic factors in PC (P < 0.1). In the multivariate analysis, stage, chemotherapy, and risk score were significantly correlated to overall survival (P < 0.05). The nomogram was constructed with the three variables (stage, chemotherapy, and risk score) for predicting the 1-year, 2-year, and 3-year survival rates of PC patients. Nomogram performance was assessed by receiver operating characteristic (ROC) curves and calibration curves. 1-year, 2-year and 3-year AUC of nomogram model was 0.899, 0.765 and 0.776, respectively.

Conclusions

In our study, we successfully identified the six DNAm-driven genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) with a relationship to the outcomes of PC patients. The nomogram including stage, chemotherapy, and risk score could be used to predict survival in PC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08097-w.

LIPH promotes metastasis by enriching stem-like cells in triple-negative breast cancer

Lipase member H (LIPH), a novel member of the triglyceride lipase family. The clinical implications of its expression in breast cancer are still unclear. Therefore, in this study, we investigated the associations between LIPH and the tumorigenic behaviours of 144 triple-negative breast cancer (TNBC) patients. The ratio and mammosphere-forming ability of CD44+/CD24- stem-like cells were tested. The role of LIPH in breast cancer cell migration and invasion was also evaluated. In addition, the effect of LIPH silencing on mitochondrial respiration was determined using the Seahorse assay. Finally, the effect of LIPH silencing on protein expression was determined via tandem mass tag-based spectrometry and Western blotting. We found that LIPH expression was associated with metastasis in lymph nodes and distant organs (P = 0.025), resulting in poor survival among breast cancer patients (P = 0.027). LIPH knockdown significantly decreased both the ratio of CD44+ /CD24- stem-like cells and their mammosphere-forming ability. LIPH silencing promoted apoptosis, arrested cell cycle in the G2/M phase, mitigated the oxidation-related oxygen consumption rate in the mitochondria, and reduced metabolism. LIPH inhibited adhesion between tumour cells and enhanced the epithelial-mesenchymal transition. Tandem mass spectrometric analysis presented 68 proteins were differentially expressed in LIPH-silenced cells and LIPH-mediated modulation of tumour cell adhesion depended on integrin-related CAPN2 and paxillin signalling. Overall, our findings provided strong evidence that LIPH up-regulation promoted metastasis and the stemness of TNBC cells. Therefore, targeting LIPH is a potentially viable strategy for preventing metastasis in TNBC.