NAD(P)-dependent steroid dehydrogenase-like is involved in breast cancer cell growth and metastasis

Lipid Metabolism in Breast Cancer: From Basic Research to Clinical Application

Breast cancer remains the most prevalent cancer among women globally, with significant links to obesity and lipid metabolism abnormalities. This review examines the role of lipid metabolism in breast cancer progression, highlighting its multifaceted contributions to tumor biology. We discuss key metabolic processes, including fatty acid metabolism, triglyceride metabolism, phospholipid metabolism, and cholesterol metabolism, detailing the reprogramming that occurs in these pathways within breast cancer cells. Alterations in lipid metabolism are emphasized for their roles in supporting energy production, membrane biogenesis, and tumor aggressiveness. Furthermore, we examine how lipid metabolism influences immune responses in the tumor microenvironment, affecting immune cell function and therapeutic efficacy. The potential of lipid metabolism as a target for novel therapeutic strategies is also addressed, with a focus on inhibitors of key metabolic enzymes. By integrating lipid metabolism with breast cancer research, this review underscores the importance of lipid metabolism in understanding breast cancer biology and developing treatment approaches aimed at improving patient outcomes.

NSDHL contributes to breast cancer stem-like cell maintenance and tumor-initiating capacity through TGF-β/Smad signaling pathway in MCF-7 tumor spheroid

BACKGROUND

NAD(P)-dependent steroid dehydrogenase-like protein (NSDHL), which is involved in breast tumor growth and metastasis, has been implicated in the maintenance of cancer stem cells. However, its role in regulating breast cancer stem-like cells (BCSCs) remains unclear. We have previously reported the clinical significance of NSDHL in patients with estrogen receptor-positive (ER +) breast cancer. This study aimed to elucidate the molecular mechanisms by which NSDHL regulates the capacity of BCSCs in the ER + human breast cancer cell line, MCF-7.

METHODS

NSDHL knockdown suppressed tumor spheroid formation in MCF-7 human breast cancer cells grown on ultralow-attachment plates. RNA sequencing revealed that NSDHL knockdown induced widespread transcriptional changes in the MCF-7 spheroids. TGF-β signaling pathway was the most significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (fold change ≥ 2, P ≤ 0.05) identified in NSDHL-knockdown MCF-7 spheroids compared with the control. In orthotopic tumor models injected with NSDHL-knockdown MCF-7 spheroids, tumor initiation and growth were strongly suppressed compared with those in the control.

RESULTS

BCSC populations with CD44+/CD24- and CD49f+/EpCAM + phenotypes and high ALDH activity were decreased in NSDHL-knockdown MCF-7 spheroids and xenograft tumors relative to controls, along with decreased secretion of TGF-β1 and 3, phosphorylation of Smad2/3, and expression of SOX2. In RNA-sequencing data from The (TCGA) database, a positive correlation between the expression of NSDHL and SOX2 was found in luminal-type breast cancer specimens (n = 998). Our findings revealed that NSDHL plays an important role in maintaining the BCSC population and tumor-initiating capacity of ER-positive MCF-7 spheroids, suggesting that NSDHL is an attractive therapeutic target for eliminating BCSCs, thus preventing breast cancer initiation and progression.

CONCLUSIONS

Our findings suggest that NSDHL regulates the BCSC/tumor-initiating cell population in MCF-7 spheroids and xenograft tumors.

An association weight matrix identified biological pathways associated with bull fertility traits in a multi-breed population

Using seven indicator traits, we investigated the genetic basis of bull fertility and predicted gene interactions from SNP associations. We used percent normal sperm as the key phenotype for the association weight matrix-partial correlation information theory (AWM-PCIT) approach. Beyond a simple list of candidate genes, AWM-PCIT predicts significant gene interactions and associations for the selected traits. These interactions formed a network of 537 genes: 38 genes were transcription cofactors, and 41 genes were transcription factors. The network displayed two distinct clusters, one with 294 genes and another with 243 genes. The network is enriched in fertility-associated pathways: steroid biosynthesis, p53 signalling, and the pentose phosphate pathway. Enrichment analysis also highlighted gene ontology terms associated with 'regulation of neurotransmitter secretion' and 'chromatin formation'. Our network recapitulates some genes previously implicated in another network built with lower-density genotypes. Sequence-level data also highlights additional candidate genes relevant to bull fertility, such as FOXO4, FOXP3, GATA1, CYP27B1, and EBP. A trio of regulatory genes-KDM5C, LRRK2, and PME-was deemed core to the network because of their overarching connections. This trio probably influences bull fertility through their interaction with genes, both known and unknown as to their role in male fertility. Future studies may target the trio and their target genes to enrich our understanding of male fertility further.

Impact of De Novo Cholesterol Biosynthesis on the Initiation and Progression of Breast Cancer

Cholesterol (CHOL) is a multifaceted lipid molecule. It is an essential structural component of cell membranes, where it cooperates in regulating the intracellular trafficking and signaling pathways. Additionally, it serves as a precursor for vital biomolecules, including steroid hormones, isoprenoids, vitamin D, and bile acids. Although CHOL is normally uptaken from the bloodstream, cells can synthesize it de novo in response to an increased requirement due to physiological tissue remodeling or abnormal proliferation, such as in cancer. Cumulating evidence indicated that increased CHOL biosynthesis is a common feature of breast cancer and is associated with the neoplastic transformation of normal mammary epithelial cells. After an overview of the multiple biological activities of CHOL and its derivatives, this review will address the impact of de novo CHOL production on the promotion of breast cancer with a focus on mammary stem cells. The review will also discuss the effect of de novo CHOL production on in situ and invasive carcinoma and its impact on the response to adjuvant treatment. Finally, the review will discuss the present and future therapeutic strategies to normalize CHOL biosynthesis.

Identification of a cholesterol metabolism-related prognostic signature for multiple myeloma

Multiple myeloma (MM) is a prevalent hematological malignancy that poses significant challenges for treatment. Dysregulated cholesterol metabolism has been linked to tumorigenesis, disease progression, and therapy resistance. However, the correlation between cholesterol metabolism-related genes (CMGs) and the prognosis of MM remains unclear. Univariate Cox regression analysis and LASSO Cox regression analysis were applied to construct an overall survival-related signature based on the Gene Expression Omnibus database. The signature was validated using three external datasets. Enrichment analysis and immune analysis were performed between two risk groups. Furthermore, an optimal nomogram was established for clinical application, and its performance was assessed by the calibration curve and C-index. A total of 6 CMGs were selected to establish the prognostic signature, including ANXA2, CHKA, NSDHL, PMVK, SCAP and SQLE. The prognostic signature demonstrated good prognostic performance and correlated with several important clinical parameters, including number of transplants, International Staging System, albumin, beta2-Microglobulin and lactate dehydrogenase levels. The function analysis and immune analysis revealed that the metabolic pathways and immunologic status were associated with risk score. The nomogram incorporating the signature along with other clinical characteristics was constructed and the discrimination was verified by the calibration curve and C-index. Our findings indicated the potential prognostic connotation of cholesterol metabolism in MM. The development and validation of the prognostic signature is expected to aid in predicting prognosis and guiding precision treatment for MM.

A novel glycolysis-related gene signature for predicting the prognosis of multiple myeloma

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM's great heterogeneity and incurability, risk assessment and treatment choices are still difficult. Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes. Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study. Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients.

Immune environment and antigen specificity of the T cell receptor repertoire of malignant ascites in ovarian cancer

We evaluated the association of disease outcome with T cell immune-related characteristics and T cell receptor (TCR) repertoire in malignant ascites from patients with high-grade epithelial ovarian cancer. Ascitic fluid samples were collected from 47 high-grade epithelial ovarian cancer patients and analyzed using flow cytometry and TCR sequencing to characterize the complementarity determining region 3 TCR β-chain. TCR functions were analyzed using the McPAS-TCR and VDJ databases. TCR clustering was implemented using Grouping of Lymphocyte Interactions by Paratope Hotspots software. Patients with poor prognosis had ascites characterized by an increased ratio of CD8+ T cells to regulatory T cells, which correlated with an increased productive frequency of the top 100 clones and decreased productive entropy. TCRs enriched in patients with an excellent or good prognosis were more likely to recognize cancer antigens and contained more TCR reads predicted to recognize epithelial ovarian cancer antigens. In addition, a TCR motif that is predicted to bind the TP53 neoantigen was identified, and this motif was enriched in patients with an excellent or good prognosis. Ascitic fluid in high-grade epithelial ovarian cancer patients with an excellent or good prognosis is enriched with TCRs that may recognize ovarian cancer-specific neoantigens, including mutated TP53 and TEAD1. These results suggest that an effective antigen-specific immune response in ascites is vital for a good outcome in high-grade epithelial ovarian cancer.

CPSF1 positively regulates NSDHL by alternative polyadenylation and promotes gastric cancer progression

Gastric cancer (GC) is a common malignancies with unfavourable prognosis. As one of the most common RNA modifications in nature, alternative polyadenylation (APA) plays a critical role in the progression of carcinomas. CPSF1 is a critical APA-related factor and is involved in many cancers. Nevertheless, the roles and underlying mechanisms of CPSF1 remain unclear in GC. In this work, we identified that CPSF1 is significantly upregulated in GC and that high CPSF1 expression indicates an unfavourable prognosis in GC patients. Moreover, CPSF1 expression levels were closely associated with tumour size, TNM stage and lymph node metastasis. CPSF1 depletion dramatically weakened GC cell proliferation and metastasis. We then performed RNA sequencing and found numerous downstream genes involved the regulation of CPSF1 with remarkable changes in 3'UTR length, among which NSDHL was positively regulated by CPSF1 and promoted GC progression. In addition, rescue assays demonstrated that NSDHL mediated the carcinogenic effect of CPSF1, and this process potentially involved APA. Therefore, this study showed that CPSF1 promotes GC progression, at least in part, by enhancing NSDHL and offered new insights into therapeutic targets for GC.

Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis

Background

The early-stage lung adenocarcinoma (LUAD) rate has increased with heightened public awareness and lung cancer screening implementation. Lipid metabolism abnormalities are associated with lung cancer initiation and progression. However, the comprehensive features and clinical significance of the immunometabolism landscape and lipid metabolism-related genes (LMRGs) in cancer recurrence for early-stage LUAD remain obscure.

Methods

LMRGs were extracted from Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Samples from The Cancer Genome Atlas (TCGA) were used as training cohort, and samples from four Gene Expression Omnibus (GEO) datasets were used as validation cohorts. The LUAD recurrence-associated LMRG molecular pattern and signature was constructed through unsupervised consensus clustering, time-dependent receiver operating characteristic (ROC), and least absolute shrinkage and selection operator (LASSO) analyses. Kaplan-Meier, ROC, and multivariate Cox regression analyses and prognostic meta-analysis were used to test the suitability and stability of the signature. We used Gene Ontology (GO), KEGG pathway, immune cell infiltration, chemotherapy response analyses, gene set variation analysis (GSVA), and GSEA to explore molecular mechanisms and immune landscapes related to the signature and the potential of the signature to predict immunotherapy or chemotherapy response.

Results

First, two LMRG molecular patterns were established, which showed diverse prognoses and immune infiltration statuses. Then, a 12-gene signature was identified, and a risk model was built. The signature remained an independent prognostic parameter in multivariate Cox regression and prognostic meta-analysis. In addition, this signature stratified patients into high- and low-risk groups with significantly different recurrence rates and was well validated in different clinical subgroups and several independent validation cohorts. The results of GO and KEGG analyses and GSEA showed that there were differences in multiple lipid metabolism, immune response, and drug metabolism pathways between the high- and low-risk groups. Further analyses revealed that the signature-based risk model was related to distinct immune cell proportions, immune checkpoint parameters, and immunotherapy and chemotherapy response, consistent with the GO, KEGG, and GSEA results.

Conclusions

This is the first lipid metabolism-based signature for predicting recurrence, and it could provide vital guidance to achieve optimized antitumor for immunotherapy or chemotherapy for early-stage LUAD.

Clinical Potential of lncRNA PPP1R26-AS1 in Breast Cancer and Its Contribution to Cancer Progression

Breast cancer has become the most leading diagnosed tumor worldwide in 2020. In this study, the biomarker potential and influence on the cellular function of lncRNA PPP1R26-AS1 was investigated in breast cancer. Expression levels of lncRNA PPP1R26-AS1 in breast tissues and cells were detected by RT-qPCR. Association between lncRNA PPP1R26-AS1 level and clinical parameters was investigated by Chi-square analysis. The prognostic potential was assessed by Kaplan-Meier and multivariate Cox regression analysis. Knockdown of lncRNA PPP1R26-AS1 was subjected to study the effect on cell proliferation, invasion, and migration by CCK-8 and transwell assay. The bind between PPP1R26-AS1 and miR-1226-3p was investigated. LncRNA PPP1R26-AS1 was highly expressed in breast tissues and cell lines. This upregulation was correlated with pTNM, positive ER status, luminal B subtype, positive nodal status, and shorter overall survival in breast cancer patients. Significant decreases in proliferation, migration, and invasion activity were observed upon knockdown of lncRNA PPP1R26-AS1. lncRNA PPP1R26-AS1 could act as ceRNA to bind with miR-1226-3p in breast cancer. LncRNA PPP1R26-AS1, as oncogenic lncRNA, could provide a new perspective on the development of prognostic biomarkers and a new approach in tailoring the treatment personalized in breast cancer.

Molecular Mechanism of Malignant Transformation of Balb/c-3T3 Cells Induced by Long-Term Exposure to 1800 MHz Radiofrequency Electromagnetic Radiation (RF-EMR)

Purpose: We aimed to investigate RF-EMR-induced cell malignant transformation. Methods: We divided Balb/c-3T3 cells into sham and expo groups. The expo groups were exposed to a 1800 MHz RF continuous wave for 40 and 60 days, for 4 h per day. The sham group was sham-exposed. Cells were harvested for a cell transformation assay, transplantation in severe combined immune deficient (SCID) mice, soft agar clone formation detection, and a transwell assay. The mRNA microarray assay was used to declare key genes and pathways. Results: The exposed Balb/c-3T3 cells showed a strong increase in cell proliferation and migration. Malignant transformation was observed in expo Balb/c-3T3 cells exposed for 40 days and 60 days, which was symbolized with visible foci and clone formation. Expo Balb/c-3T3 cells that were exposed for 40 days and 60 days produced visible tumors in the SCID mice. Lipid metabolism was the key biological process and pathway involved. The mevalonate (MVA) pathway was the key metabolic pathway. The interacted miRNAs could be further research targets to examine the molecular mechanism of the carcinogenic effects of long-term exposure. Conclusion: Exposure for 40 and 60 days to 1800 MHz RF-EMR induced malignant transformation in Balb/c-3T3 cells at the SAR of 8.0 W/kg. We declared that lipid metabolism was the pivotal biological process and pathway. The MVA pathway was the key metabolic pathway.

Enzymes in the Cholesterol Synthesis Pathway: Interactomics in the Cancer Context

A global protein interactome ensures the maintenance of regulatory, signaling and structural processes in cells, but at the same time, aberrations in the repertoire of protein-protein interactions usually cause a disease onset. Many metabolic enzymes catalyze multistage transformation of cholesterol precursors in the cholesterol biosynthesis pathway. Cancer-associated deregulation of these enzymes through various molecular mechanisms results in pathological cholesterol accumulation (its precursors) which can be disease risk factors. This work is aimed at systematization and bioinformatic analysis of the available interactomics data on seventeen enzymes in the cholesterol pathway, encoded by HMGCR, MVK, PMVK, MVD, FDPS, FDFT1, SQLE, LSS, DHCR24, CYP51A1, TM7SF2, MSMO1, NSDHL, HSD17B7, EBP, SC5D, DHCR7 genes. The spectrum of 165 unique and 21 common protein partners that physically interact with target enzymes was selected from several interatomic resources. Among them there were 47 modifying proteins from different protein kinases/phosphatases and ubiquitin-protein ligases/deubiquitinases families. A literature search, enrichment and gene co-expression analysis showed that about a quarter of the identified protein partners was associated with cancer hallmarks and over-represented in cancer pathways. Our results allow to update the current fundamental view on protein-protein interactions and regulatory aspects of the cholesterol synthesis enzymes and annotate of their sub-interactomes in term of possible involvement in cancers that will contribute to prioritization of protein targets for future drug development.

Proteomic Characterization of Cytoplasmic Lipid Droplets in Human Metastatic Breast Cancer Cells

One of the characteristic features of metastatic breast cancer is increased cellular storage of neutral lipid in cytoplasmic lipid droplets (CLDs). CLD accumulation is associated with increased cancer aggressiveness, suggesting CLDs contribute to metastasis. However, how CLDs contribute to metastasis is not clear. CLDs are composed of a neutral lipid core, a phospholipid monolayer, and associated proteins. Proteins that associate with CLDs regulate both cellular and CLD metabolism; however, the proteome of CLDs in metastatic breast cancer and how these proteins may contribute to breast cancer progression is unknown. Therefore, the purpose of this study was to identify the proteome and assess the characteristics of CLDs in the MCF10CA1a human metastatic breast cancer cell line. Utilizing shotgun proteomics, we identified over 1500 proteins involved in a variety of cellular processes in the isolated CLD fraction. Interestingly, unlike other cell lines such as adipocytes or enterocytes, the most enriched protein categories were involved in cellular processes outside of lipid metabolism. For example, cell-cell adhesion was the most enriched category of proteins identified, and many of these proteins have been implicated in breast cancer metastasis. In addition, we characterized CLD size and area in MCF10CA1a cells using transmission electron microscopy. Our results provide a hypothesis-generating list of potential players in breast cancer progression and offers a new perspective on the role of CLDs in cancer.

Unearthing the Janus-face cholesterogenesis pathways in cancer

Cholesterol biosynthesis, primarily associated with eukaryotes, occurs as an essential component of human metabolism with biosynthetic deregulation a factor in cancer viability. The segment that partitions between squalene and the C₂₇-end cholesterol yields the main cholesterogenesis branch subdivided into the Bloch and Kandutsch-Russell pathways. Their importance in cell viability, in normal growth and development originates primarily from the amphipathic property and shape of the cholesterol molecule which makes it suitable as a membrane insert. Cholesterol can also convert to variant oxygenated product metabolites of distinct function producing a complex interplay between cholesterol synthesis and overall steroidogenesis. In this review, we disassociate the two sides of cholesterogenesisis affecting the type and amounts of systemic sterols-one which is beneficial to human welfare while the other dysfunctional leading to misery and disease that could result in premature death. Our focus here is first to examine the cholesterol biosynthetic genes, enzymes, and order of biosynthetic intermediates in human cholesterogenesis pathways, then compare the effect of proximal and distal inhibitors of cholesterol biosynthesis against normal and cancer cell growth and metabolism. Collectively, the inhibitor studies of druggable enzymes and specific biosynthetic steps, suggest a potential role of disrupted cholesterol biosynthesis, in coordination with imported cholesterol, as a factor in cancer development and as discussed some of these inhibitors have chemotherapeutic implications.

NSDHL promotes triple-negative breast cancer metastasis through the TGFβ signaling pathway and cholesterol biosynthesis

PURPOSE

Metastasis is the main cause of breast cancer mortality. Recent studies have proved that lipid metabolic reprogramming plays critical roles in breast cancer carcinogenesis and metastasis. We aim to identify critical lipid metabolism genes in breast cancer metastasis.

METHODS

We designed and cloned a CRISPR pooled library containing lipid metabolic gene guide RNAs and performed a genetic screen in vivo. Transwell assay and animal experiments were used to evaluate cell metastatic ability in vitro or in vivo, respectively. We performed immunohistochemistry with breast cancer tissue microarray to study the clinical significance of NSDHL.

FINDINGS

We identified a cholesterol metabolic enzyme, NSDHL, as a potential metastatic driver in triple-negative breast cancer. NSDHL was highly expressed in breast cancer tissues and predicted a poor prognosis. NSDHL knockdown significantly suppressed cell proliferation and migration. Mechanistically, NSDHL activated the TGFβ signaling pathway by inhibiting the endosomal degradation of TGFβR2. In addition, blocking the upstream metabolism of NSDHL with ketoconazole rescued cancer metastasis and TGFβR2 degradation. However, the inactivation of NSDHL (Y151X) did not rescue the migration ability and the TGFβR2 protein expression.

CONCLUSION

Taken together, our findings established that NSDHL serves as a metastatic driver, and its function depends on its enzyme activity in cholesterol biosynthesis and is mediated by the NSDHL-TGFβR2 signal pathway. Our study indicated that NSDHL and steroid biosynthesis may serve as new drug targets for patients with advanced breast cancer.