Lysophosphatidylcholine acyltransferase 1 promotes epithelial-mesenchymal transition of hepatocellular carcinoma via the Wnt/β-catenin signaling pathway

MIR4435-2HG: A novel biomarker for triple-negative breast cancer diagnosis and prognosis, activating cancer-associated fibroblasts and driving tumor invasion through EMT associated with JNK/c-Jun and p38 MAPK signaling pathway activation

BACKGROUND

Breast cancer has the highest incidence rate and causes the most fatalities among all female cancers worldwide. Triple-negative breast cancer (TNBC) is known for its strong invasiveness and higher rates of recurrence. In this research, we aimed to identify MIR4435-2HG as a promising long non-coding RNA (lncRNA) biomarker and therapeutic target for TNBC.

METHODS

Utilizing clinicopathological information and transcriptome data from The Cancer Genome Atlas (TCGA) database, we assessed the clinical relevance of MIR4435-2HG in breast cancer through univariate and multivariate COX regression, receiver operating characteristic (ROC) analysis, as well as Kaplan-Meier survival analysis. To investigate the biological role of MIR4435-2HG in TNBC, we conducted gene set enrichment analysis (GSEA), as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, we constructed and validated a nomogram to predict disease-free survival (DFS). Both the R package "pRRophetic" and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were employed to forecast the sensitivity to different therapeutics between the high- and low-MIR4435-2HG groups. We employed single-cell RNA sequencing analysis and tumor microenvironment infiltration analysis to investigate the potential involvement of MIR4435-2HG in the TNBC tumor microenvironment. Cellular biological behaviors were assessed utilizing CCK-8, transwell assays, and wound-healing assays. Furthermore, we performed RNA-seq, qRT-PCR, and western blotting analyses to elucidate and confirm the specific mechanisms underlying the role of MIR4435-2HG in TNBC.

RESULTS

In our study, we have identified MIR4435-2HG as a significant diagnostic and prognostic factor for TNBC. We observed that MIR4435-2HG is widely expressed and might have a significant impact on the reshaping of the TNBC tumor microenvironment. Patients with TNBC in the high-MIR4435-2HG group may show reduced sensitivity to cisplatin, doxorubicin, and gemcitabine and have an increased propensity for immune escape. Knockdown of MIR4435-2HG inhibits cancer-associated fibroblasts (CAFs) activation. Notably, MIR4435-2HG predominantly enhances the migratory and invasive capabilities of TNBC cells through the epithelial-mesenchymal transition (EMT) process. Mechanistically, we validated that MIR4435-2HG activates the JNK/c-Jun and p38 non-classical MAPK signaling pathway in TNBC cells.

CONCLUSIONS

Our findings highlight the significant potential of MIR4435-2HG as a highly promising biomarker for TNBC. Targeting MIR4435-2HG could represent an appealing therapeutic approach for TNBC.

Identification of LPCAT1 as a key biomarker for Crohn's disease based on bioinformatics and machine learnings and experimental verification

Epithelial-mesenchymal transition (EMT) plays a crucial role in regulating inflammatory responses and fibrosis formation. This study aims to explore the molecular mechanisms of EMT-related genes in Crohn's disease (CD) through bioinformatics methods and identify potential key biomarkers. In our research, we identified differentially expressed genes (DEGs) related to EMT based on the GSE52746 dataset and the gene set in the GeneCards database. Key genes were identified through Lasso-cox and Random Forest and validated using the external dataset GSE10616. Immune infiltration analysis showed that Lysophosphatidylcholine acyltransferase 1 (LPCAT1) was positively correlated with Neutrophils and Macrophages M1. The Gene Set Enrichment Analysis (GSEA) results for LPCAT1 showed associations with celladhesionmolecules and ECM receptor interaction. Additionally, a lncRNA-miRNA-mRNA ceRNA network was constructed. Finally, we validated that knocking down LPCAT1 could inhibit the release of inflammatory factors, EMT, and the elevation of fibrosis indices as well as the activation of NF-κB signaling pathway in LPS-induced HT-29 cells. LPCAT1 plays an important role in the occurrence and development of CD and may become a new biomarker.

Phospholipid Acyltransferases: Characterization and Involvement of the Enzymes in Metabolic and Cancer Diseases

This review delves into the enzymatic processes governing the initial stages of glycerophospholipid (phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine) and triacylglycerol synthesis. The key enzymes under scrutiny include GPAT and AGPAT. Additionally, as most AGPATs exhibit LPLAT activity, enzymes participating in the Lands cycle with similar functions are also covered. The review begins by discussing the properties of these enzymes, emphasizing their specificity in enzymatic reactions, notably the incorporation of polyunsaturated fatty acids (PUFAs) such as arachidonic acid and docosahexaenoic acid (DHA) into phospholipids. The paper sheds light on the intricate involvement of these enzymes in various diseases, including obesity, insulin resistance, and cancer. To underscore the relevance of these enzymes in cancer processes, a bioinformatics analysis was conducted. The expression levels of the described enzymes were correlated with the overall survival of patients across 33 different types of cancer using the GEPIA portal. This review further explores the potential therapeutic implications of inhibiting these enzymes in the treatment of metabolic diseases and cancer. By elucidating the intricate enzymatic pathways involved in lipid synthesis and their impact on various pathological conditions, this paper contributes to a comprehensive understanding of these processes and their potential as therapeutic targets.

Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer

Introduction

The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers.

Methods

We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions.

Results

Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95).

Discussion

In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.

Molecular cloning, tissue expression pattern, responses to different fatty acids and potential functions of lysophosphatidylcholine acyltransferase 1 (LPCAT1) in large yellow croaker (Larimichthys crocea)

In farmed fish, diets rich in palm oil have been observed to promote abnormal lipid build-up in the liver, subsequently leading to physiological harm and disease onset. Emerging research suggests that integrating phospholipids into the feed could serve as a potent countermeasure against hepatic impairments induced by vegetable oil consumption. Phosphatidylcholine is the most abundant type among phospholipids. In the metabolic processes of mammal, lysophosphatidylcholine acyltransferase 1 (LPCAT1), crucial for phosphatidylcholine remodeling, demonstrates a marked affinity towards palmitic acid (PA). Nonetheless, aspects concerning the cloning, tissue-specific distribution, and affinity of the LPCAT1 gene to diverse oil sources have yet to be elucidated in the large yellow croaker (Larimichthys crocea). Within the scope of this study, we successfully isolated and cloned the cDNA of the LPCAT1 gene from the large yellow croaker. Subsequent analysis revealed distinct gene expression patterns of LPCAT1 across ten different tissues of the species. The fully sequenced coding DNA sequence (CDS) of LPCAT1 spans 1503 bp and encodes a sequence of 500 amino acids. Comparative sequence alignment indicates that LPCAT1 shares a 69.75 % amino acid similarity with its counterparts in other species. Although LPCAT1 manifests across various tissues of the large yellow croaker, its predominance is markedly evident in the liver and gills. Furthermore, post exposure of the large yellow croaker's hepatocytes to varied fatty acids, PA has a strong response to LPCAT1. Upon the addition of appropriate lysolecithin to palm oil feed, the mRNA expression of LPCAT1 in the liver cells of the large yellow croaker showed significant variations compared to other subtypes. Concurrently, the mRNA expression of pro-inflammatory genes il-1β, il-6, il-8, tnf-α and ifn-γ in the liver tissue of the large yellow croaker decreased. Interestingly, they exhibit the same trend of change. In conclusion, we have cloned the LPCAT1 gene on fish successfully and find the augmented gene response of LPCAT1 in hepatocytes under PA treatment first. The results of this study suggest that LPCAT1 may be associated with liver inflammation in fish and offer new insights into mitigating liver diseases in fish caused by palm oil feed.

Integrated plasma metabolomics and lipidomics profiling highlights distinctive signature of hepatocellular carcinoma in HCV patients

BACKGROUND

Early diagnosis of hepatocellular carcinoma (HCC) is essential towards the improvement of prognosis and patient survival. Circulating markers such as α-fetoprotein (AFP) and micro-RNAs represent useful tools but still have limitations. Identifying new markers can be fundamental to improve both diagnosis and prognosis. In this approach, we harness the potential of metabolomics and lipidomics to uncover potential signatures of HCC.

METHODS

A combined untargeted metabolomics and lipidomics plasma profiling of 102 HCV-positive patients was performed by HILIC and RP-UHPLC coupled to Mass Spectrometry. Biochemical parameters of liver function (AST, ALT, GGT) and liver cancer biomarkers (AFP, CA19.9 e CEA) were evaluated by standard assays.

RESULTS

HCC was characterized by an elevation of short and long-chain acylcarnitines, asymmetric dimethylarginine, methylguanine, isoleucylproline and a global reduction of lysophosphatidylcholines. A supervised PLS-DA model showed that the predictive accuracy for HCC class of metabolomics and lipidomics was superior to AFP for the test set (100.00% and 94.40% vs 55.00%). Additionally, the model was applied to HCC patients with AFP values < 20 ng/mL, and, by using only the top 20 variables selected by VIP scores achieved an Area Under Curve (AUC) performance of 0.94.

CONCLUSION

These exploratory findings highlight how metabo-lipidomics enables the distinction of HCC from chronic HCV conditions. The identified biomarkers have high diagnostic potential and could represent a viable tool to support and assist in HCC diagnosis, including AFP-negative patients.

Deep dissection of stemness-related hierarchies in hepatocellular carcinoma

BACKGROUND

Increasing evidence suggests that hepatocellular carcinoma (HCC) stem cells (LCSCs) play an essential part in HCC recurrence, metastasis, and chemotherapy and radiotherapy resistance. Multiple studies have demonstrated that stemness-related genes facilitate the progression of tumors. However, the mechanism by which stemness-related genes contribute to HCC is not well understood. Here, we aim to construct a stemness-related score (SRscores) model for deeper analysis of stemness-related genes, assisting with the prognosis and individualized treatment of HCC patients.Further, we found that the gene LPCAT1 was highly expressed in tumor tissues by immunohistochemistry, and sphere-forming assay revealed that knockdown of LPCAT1 inhibited the sphere-forming ability of hepatocellular carcinoma cells.

METHODS

We used the TCGA-LIHC dataset to screen stemness-related genes of HCC from the MSigDB database. Prognosis, tumor microenvironment, immunological checkpoints, tumor immune dysfunction, rejection, treatment sensitivity, and putative biological pathways were examined. Random forest created the SRscores model. The anti-PD-1/anti-CTLA4 immunotherapy, tumor mutational burden, medication sensitivity, and cancer stem cell index were compared between the high- and low-risk score groups. We also examined risk scores for different cell types using single-cell RNA sequencing data and correlated transcription factor activity in cancer stem cells with SRscores genes. Finally, we tested core marker expression and biological functions.

RESULTS

Patients can be divided into two subtypes (Cluster1 and Cluster2) based on the TCGA-LIHC dataset's identification of 11 stemness-related genes. Additionally, a SRscores was developed based on subtypes. Cluster2 and the group with the lowest SRscores had superior survival and immunotherapy response than Cluster1 and the group with the highest SRscores. The group with a high SRscores was significantly more enriched in classical tumor pathways than the group with a low SRscores. Multiple transcription factors and SRscores genes are correlated. The core gene LPCAT1 is highly expressed in rat liver cancer tissues and promotes tumor cell sphere formation.

CONCLUSION

A SRscores model can be utilized to predict the prognosis of HCC patients as well as their response to immunotherapy.

LncRNA AC012360.1 facilitates growth and metastasis by regulating the miR-139-5p/LPCAT1 axis in hepatocellular carcinoma

Long noncoding RNAs (lncRNAs) participate in tumorigenesis and tumor progression. However, whether lncRNA AC012360.1 contributes to hepatocellular carcinoma (HCC) is unknown. In HCC tissues, differentially expressed lncRNAs were identified by bioinformatics. AC012360.1 level was validated and its role in HCC progression was investigated. Among the top 10 upregulated lncRNAs, AC012360.1 exhibited the greatest increase in HCC tissues. Additionally, AC012360.1 was upregulated in HCC tissues/cells. Moreover, AC012360.1 knockdown refrained cell proliferation/metastasis and tumor growth. Conversely, AC012360.1 overexpression showed an oncogenic role. AC012360.1 and lysophosphatidylcholine acyltransferase 1 (LPCAT1) contained miR-139-5p binding sites. Furthermore, miR-139-5p silencing partially mitigated the role of AC012360.1 knockdown, while LPCAT1 knockdown partially abolished the tumor-promoting effect of AC012360.1 overexpression. In conclusion, AC012360.1 exhibited its oncogenic function in HCC through sponging miR-139-5p and upregulating LPCAT1 expression.

The validation and clinical significance of LPCAT1 down-regulation in acute myeloid leukemia

BACKGROUND

Overexpression of lysophosphatidylcholine acyltransferase 1 (LPCAT1) has been found in various solid cancers and is associated with disease progression, metastasis, and recurrence. However, the expression pattern of LPCAT1 in acute myeloid leukemia (AML) bone marrow remains unknown. The present study aimed to compare LPCAT1 expression differences in bone marrow samples from AML patients and healthy controls and assess the clinical relevance of LPCAT1 in AML.

METHODS AND RESULTS

LPCAT1 expression in bone marrow was significantly lower in AML than in healthy controls predicted by public databases. Furthermore, real-time quantitative PCR (RQ-PCR) validated that LPCAT1 expression in bone marrow was significantly down-regulated in AML compared to healthy controls [0.056 (0.000-0.846) vs 0.253 (0.031-1.000)]. The DiseaseMeth version 2.0 and The Cancer Genome Atlas analysis revealed that the LPCAT1 promoter was hypermethylated in AML, and there was a strong negative correlation between LPCAT1 expression and methylation (R = - 0.610, P < 0.001). RQ-PCR revealed that the frequency of LPCAT1 low expression was lower in the FAB-M4/M5 subtype than in the other subtypes (P = 0.018). The ROC curve revealed that LPCAT1 expression could serve as a potential diagnostic marker for differentiating AML from controls with an area under the ROC curve of 0.819 (95% CI 0.743-0.894, P < 0.001). In cytogenetically normal AML, patients with LPCAT1 low expression had significantly longer overall survival than those without LPCAT1 low expression (median 19 versus 5.5 months, P = 0.036).

CONCLUSIONS

LPCAT1 is down-regulated in AML bone marrow, and LPCAT1 down-regulation could be used as a potential biomarker for AML diagnosis and prognosis.

Spatial multiomics map of trophoblast development in early pregnancy

The relationship between the human placenta-the extraembryonic organ made by the fetus, and the decidua-the mucosal layer of the uterus, is essential to nurture and protect the fetus during pregnancy. Extravillous trophoblast cells (EVTs) derived from placental villi infiltrate the decidua, transforming the maternal arteries into high-conductance vessels1. Defects in trophoblast invasion and arterial transformation established during early pregnancy underlie common pregnancy disorders such as pre-eclampsia2. Here we have generated a spatially resolved multiomics single-cell atlas of the entire human maternal-fetal interface including the myometrium, which enables us to resolve the full trajectory of trophoblast differentiation. We have used this cellular map to infer the possible transcription factors mediating EVT invasion and show that they are preserved in in vitro models of EVT differentiation from primary trophoblast organoids3,4 and trophoblast stem cells5. We define the transcriptomes of the final cell states of trophoblast invasion: placental bed giant cells (fused multinucleated EVTs) and endovascular EVTs (which form plugs inside the maternal arteries). We predict the cell-cell communication events contributing to trophoblast invasion and placental bed giant cell formation, and model the dual role of interstitial EVTs and endovascular EVTs in mediating arterial transformation during early pregnancy. Together, our data provide a comprehensive analysis of postimplantation trophoblast differentiation that can be used to inform the design of experimental models of the human placenta in early pregnancy.

The prognostic value of the GPAT/AGPAT gene family in hepatocellular carcinoma and its role in the tumor immune microenvironment

Background

Liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer-related death worldwide. Hepatocellular carcinoma accounts for an estimated 90% of all liver cancers. Many enzymes of the GPAT/AGPAT family are required for the synthesis of triacylglycerol. Expression of AGPAT isoenzymes has been reported to be associated with an increased risk of tumorigenesis or development of aggressive phenotypes in a variety of cancers. However, whether members of the GPAT/AGPAT gene family also influence the pathophysiology of HCC is unknown.

Methods

Hepatocellular carcinoma datasets were obtained from the TCGA and ICGC databases. Predictive models related to the GPAT/AGPAT gene family were constructed based on LASSO-Cox regression using the ICGC-LIRI dataset as an external validation cohort. Seven immune cell infiltration algorithms were used to analyze immune cell infiltration patterns in different risk groups. IHC, CCK-8, Transwell assay, and Western blotting were used for in vitro validation.

Results

Compared with low-risk patients, high-risk patients had shorter survival and higher risk scores. Multivariate Cox regression analysis showed that risk score was a significant independent predictor of overall survival (OS) after adjustment for confounding clinical factors (p < 0.001). The established nomogram combined risk score and TNM staging to accurately predict survival at 1, 3, and 5 years in patients with HCC with AUC values of 0.807, 0.806, and 0.795, respectively. This risk score improved the reliability of the nomogram and guided clinical decision-making. In addition, we comprehensively analyzed immune cell infiltration (using seven algorithms), response to immune checkpoint blockade, clinical relevance, survival, mutations, mRNA expression-based stemness index, signaling pathways, and interacting proteins related to the three core genes of the prognostic model (AGPAT5, LCLAT1, and LPCAT1). We also performed preliminary validation of the differential expression, oncological phenotype, and potential downstream pathways of the three core genes by IHC, CCK-8, Transwell assay, and Western blotting.

Conclusion

These results improve our understanding of the function of GPAT/AGPAT gene family members and provide a reference for prognostic biomarker research and individualized treatment of HCC.