MET and FASN as Prognostic Biomarkers of Triple Negative Breast Cancer: A Systematic Evidence Landscape of Clinical Study

HE2Gene: image-to-RNA translation via multi-task learning for spatial transcriptomics data

MOTIVATION

Tissue context and molecular profiling are commonly used measures in understanding normal development and disease pathology. In recent years, the development of spatial molecular profiling technologies (e.g. spatial resolved transcriptomics) has enabled the exploration of quantitative links between tissue morphology and gene expression. However, these technologies remain expensive and time-consuming, with subsequent analyses necessitating high-throughput pathological annotations. On the other hand, existing computational tools are limited to predicting only a few dozen to several hundred genes, and the majority of the methods are designed for bulk RNA-seq.

RESULTS

In this context, we propose HE2Gene, the first multi-task learning-based method capable of predicting tens of thousands of spot-level gene expressions along with pathological annotations from H&E-stained images. Experimental results demonstrate that HE2Gene is comparable to state-of-the-art methods and generalizes well on an external dataset without the need for re-training. Moreover, HE2Gene preserves the annotated spatial domains and has the potential to identify biomarkers. This capability facilitates cancer diagnosis and broadens its applicability to investigate gene-disease associations.

AVAILABILITY AND IMPLEMENTATION

The source code and data information has been deposited at https://github.com/Microbiods/HE2Gene.

Single-Cell Unsaturated Lipid Profiling for Studying Chemoresistance Heterogeneity of Triple-Negative Breast Cancer Cells

Chemoresistance to triple-negative breast cancer (TNBC) is a critical issue in clinical practice. Lipid metabolism takes a unique role in breast cancer cells; especially, unsaturated lipids involving cell membrane fluidity and peroxidation are highly remarked. At present, for the lack of a high-resolution molecular recognition platform at the single-cell level, it is still hard to systematically study chemoresistance heterogeneity based on lipid unsaturation proportion. By designing a single-cell mass spectrometry workflow based on CyESI-MS, we profiled the unsaturated lipids of TNBC cells to evaluate lipidomic remodeling under platinum stress. Profiling revealed the heterogeneity of the polyunsaturated lipid proportion of TNBC cells under cisplatin treatment. A cluster of cells identified by polyunsaturated lipid accumulation was found to be involved in platinum sensitivity. Furthermore, we found that the chemoresistance of TNBC cells could be regulated by fatty acid supplementation, which determinates the composition of unsaturated lipids. These discoveries provide insights for monitoring and controlling cellular unsaturated lipid proportions to overcome chemoresistance in breast cancer.

Circadian clock and lipid metabolism disorders: a potential therapeutic strategy for cancer

Recent research has emphasized the interaction between the circadian clock and lipid metabolism, particularly in relation to tumors. This review aims to explore how the circadian clock regulates lipid metabolism and its impact on carcinogenesis. Specifically, targeting key enzymes involved in fatty acid synthesis (SREBP, ACLY, ACC, FASN, and SCD) has been identified as a potential strategy for cancer therapy. By disrupting these enzymes, it may be possible to inhibit tumor growth by interfering with lipid metabolism. Transcription factors, like SREBP play a significant role in regulating fatty acid synthesis which is influenced by circadian clock genes such as BMAL1, REV-ERB and DEC. This suggests a strong connection between fatty acid synthesis and the circadian clock. Therefore, successful combination therapy should target fatty acid synthesis in addition to considering the timing and duration of drug use. Ultimately, personalized chronotherapy can enhance drug efficacy in cancer treatment and achieve treatment goals.

Role of EGFR and FASN in breast cancer progression

Breast cancer (BC) emerged as one of the life-threatening diseases among females. Despite notable improvements made in cancer detection and treatment worldwide, according to GLOBACAN 2020, BC is the fifth leading cancer, with an estimated 1 in 6 cancer deaths, in a majority of countries. However, the exact cause that leads to BC progression still needs to be determined. Here, we reviewed the role of two novel biomarkers responsible for 50-70% of BC progression. The first one is epidermal growth factor receptor (EGFR) which belongs to the ErbB tyrosine kinases family, signalling pathways associated with it play a significant role in regulating cell proliferation and division. Another one is fatty acid synthase (FASN), a key enzyme responsible for the de novo lipid synthesis required for cancer cell development. This review presents a rationale for the EGFR-mediated pathways, their interaction with FASN, communion of these two biomarkers with BC, and improvements to overcome drug resistance caused by them.

Identification of Metabolism-Related Proteins as Biomarkers of Insulin Resistance and Potential Mechanisms of m6A Modification

BACKGROUND

Insulin resistance (IR) is a major contributing factor to the pathogenesis of metabolic syndrome and type 2 diabetes mellitus (T2D). Adipocyte metabolism is known to play a crucial role in IR. Therefore, the aims of this study were to identify metabolism-related proteins that could be used as potential biomarkers of IR and to investigate the role of N⁶-methyladenosine (m⁶A) modification in the pathogenesis of this condition.

METHODS

RNA-seq data on human adipose tissue were retrieved from the Gene Expression Omnibus database. The differentially expressed genes of metabolism-related proteins (MP-DEGs) were screened using protein annotation databases. Biological function and pathway annotations of the MP-DEGs were performed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Key MP-DEGs were screened, and a protein-protein interaction (PPI) network was constructed using STRING, Cytoscape, MCODE, and CytoHubba. LASSO regression analysis was used to select primary hub genes, and their clinical performance was assessed using receiver operating characteristic (ROC) curves. The expression of key MP-DEGs and their relationship with m⁶A modification were further verified in adipose tissue samples collected from healthy individuals and patients with IR.

RESULTS

In total, 69 MP-DEGs were screened and annotated to be enriched in pathways related to hormone metabolism, low-density lipoprotein particle and carboxylic acid transmembrane transporter activity, insulin signaling, and AMPK signaling. The MP-DEG PPI network comprised 69 nodes and 72 edges, from which 10 hub genes (FASN, GCK, FGR, FBP1, GYS2, PNPLA3, MOGAT1, SLC27A2, PNPLA3, and ELOVL6) were identified. FASN was chosen as the key gene because it had the highest maximal clique centrality (MCC) score. GCK, FBP1, and FGR were selected as primary genes by LASSO analysis. According to the ROC curves, GCK, FBP1, FGR, and FASN could be used as potential biomarkers to detect IR with good sensitivity and accuracy (AUC = 0.80, 95% CI: 0.67-0.94; AUC = 0.86, 95% CI: 0.74-0.94; AUC = 0.83, 95% CI: 0.64-0.92; AUC = 0.78, 95% CI: 0.64-0.92). The expression of FASN, GCK, FBP1, and FGR was significantly correlated with that of IGF2BP3, FTO, EIF3A, WTAP, METTL16, and LRPPRC (p < 0.05). In validation clinical samples, the FASN was moderately effective for detecting IR (AUC = 0.78, 95% CI: 0.69-0.80), and its expression was positively correlated with the methylation levels of FASN (r = 0.359, p = 0.001).

CONCLUSION

Metabolism-related proteins play critical roles in IR. Moreover, FASN and GCK are potential biomarkers of IR and may be involved in the development of T2D via their m⁶A modification. These findings offer reliable biomarkers for the early detection of T2D and promising therapeutic targets.

Prognostic and clinicopathological significance of fatty acid synthase in breast cancer: A systematic review and meta-analysis

Background

Aberrant expression of fatty acid synthase (FASN) was demonstrated in various tumors including breast cancer. A meta-analysis was conducted to investigate the role of FASN in breast cancer development and its potential prognostic significance.

Methods

The Web of Science, PubMed, Embase, and Cochrane Library databases were searched to identify studies that evaluated the relationship between FASN expression and overall survival (OS), relapse-free survival (RFS), and disease-free survival (DFS) of breast cancer patients. To analyze the clinicopathological and prognostic values of FASN expression in breast cancer, pooled hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) were clustered based on random-effects models. To confirm whether the findings were stable and impartial, a sensitivity analysis was performed, and publication bias was estimated. Data were analyzed using Engauge Digitizer version 5.4 and Stata version 15.0.

Results

Five studies involving 855 participants were included. Patients with higher FASN expression did not have a shorter survival period compared to those with lower FASN expression (summary HR: OS, 0.73 [95% CI, 0.41-1.32; P=0.300]; DFS/RFS, 1.65 [95% CI, 0.61-4.43; P=0.323]). However, increased FASN expression was correlated with large tumor size (OR, 2.04; 95% CI, 1.04-4.00; P=0.038), higher human epidermal growth factor receptor 2 (HER2) positivity (OR, 1.53; 95% CI, 1.05-2.23; P=0.028). No significant associations were observed between FASN expression and histological grade (OR, 0.92; 95% CI, 0.41-2.04; P=0.832), Tumor Node Metastasis (TNM) stage (OR, 1.11; 95% CI, 0.49-2.53; P=0.795), nodal metastasis (OR, 1.42; 95% CI, 0.84-2.38; P=0.183), Ki-67 labelling index (OR, 0.64; 95% CI, 0.15-2.63; P=0.533), estrogen receptor (ER) status (OR, 0.90; 95% CI, 0.61-1.32; P=0.586), or progesterone receptor (PR) status (OR, 0.67; 95% CI, 0.29-1.56; P=0.354).

Conclusion

FASN is associated with HER2 expression and may contribute to tumor growth, but it has no significant impact on the overall prognosis of breast cancer.

Fatty acid metabolism is related to the immune microenvironment changes of gastric cancer and RGS2 is a new tumor biomarker

Background

Alterations in lipid metabolism promote tumor progression. However, the role of lipid metabolism in the occurrence and development of gastric cancer have not been fully clarified.

Method

Here, genes that are related to fatty acid metabolism and differentially-expressed between normal and gastric cancer tissues were identified in the TCGA-STAD cohort. The intersection of identified differentially-expressed genes with Geneset was determined to obtain 78 fatty acid metabolism-related genes. The ConsensusClusterPlus R package was used to perform differentially-expressed genes, which yielded divided two gastric cancer subtypes termed cluster 1 and cluster 2.

Results

Patients in cluster 2 was found to display poorer prognosis than patients in cluster 1. Using machine learning method to select 8 differentially expressed genes among subtypes to construct fatty acid prognostic risk score model (FARS), which was found to display good prognostic efficacy. We also identified that certain anticancer drugs, such as bortezomib, elesclomol, GW843682X, and nilotinib, showed significant sensitivity in the high FARS score group. RGS2 was selected as the core gene upon an analysis of the gastric cancer single-cell, and Western blotting and immunofluorescence staining results revealed high level of expression of this gene in gastric cancer cells. The results of immunohistochemical staining showed that a large amount of RGS2 was deposited in the stroma in gastric cancer. A pan-cancer analysis also revealed a significant association of RGS2 with TMB, TIDE, and CD8+ T-cell infiltration in other cancer types as well. RGS2 may thus be studied further as a new target for immunotherapy in future studies on gastric cancer.

Conclusion

In summary, the FARS model developed here enhances our understanding of lipid metabolism in the TME in gastric cancer, and provides a theoretical basis for predicting tumor prognosis and clinical treatment.

Proteomics-Based Identification of Dysregulated Proteins in Breast Cancer

Immunohistochemistry (IHC) is still widely used as a morphology-based assay for in situ analysis of target proteins as specific tumor antigens. However, as a very heterogeneous collection of neoplastic diseases, breast cancer (BC) requires an accurate identification and characterization of larger panels of candidate biomarkers, beyond ER, PR, and HER2 proteins, for diagnosis and personalized treatment, without the limited availability of antibodies that are required to identify specific proteins. Top-down, middle-down, and bottom-up mass spectrometry (MS)-based proteomics approaches complement traditional histopathological tissue analysis to examine expression, modification, and interaction of hundreds to thousands of proteins simultaneously. In this review, we discuss the proteomics-based identification of dysregulated proteins in BC that are essential for the following issues: discovery and validation of new biomarkers by analysis of solid and liquid/non-invasive biopsies, cell lines, organoids and xenograft models; identification of panels of biomarkers for early detection and accurate discrimination between cancer, benign and normal tissues; identification of subtype-specific and stage-specific protein expression profiles in BC grading and measurement of disease progression; characterization of new subtypes of BC; characterization and quantitation of post-translational modifications (PTMs) and aberrant protein-protein interactions (PPI) involved in tumor development; characterization of the global remodeling of BC tissue homeostasis, diagnosis and prognostic information; and deciphering of molecular functions, biological processes and mechanisms through which the dysregulated proteins cause tumor initiation, invasion, and treatment resistance.

Fatty Acid Synthase Is the Key Regulator of Fatty Acid Metabolism and Is Related to Immunotherapy in Bladder Cancer

Fatty acid metabolism (FAM) genes are potentially useful for predicting prognosis and immunotherapy response in bladder cancer (BC). To examine this, we constructed a prognostic model and identified key FAM genes in BC. Using transcriptional expression profiles and clinical data of BC patients from public datasets and Changhai (CH) hospital, we built and validated a risk-score model based on 13 prognostic FAM genes. Differential gene expression identified fatty acid synthase (FASN) as central to fatty acid metabolism in BC. FASN was differentially expressed between normal and tumor tissue, and was related to survival. In the CH dataset, FASN independently predicted muscle-invasive BC. FASN differential expression was significantly related to immune-cell infiltration and patients with low FASN expression responded better to immune checkpoint inhibitor (ICI) treatment. SREBF1 was predicted as the most significant transcription factor for FASN. Competing endogenous RNA network analysis suggested that lncRNA AC107027.3 may upregulate FASN by competitively binding miR-27A-3p, thereby regulating the immunotherapy response in BC. Dasatinib and temsirolimus are potential FASN-targeting drugs. Our model efficiently predicted prognosis in BC. FASN is central to fatty acid metabolism, and a potential indicator and regulator of ICI treatment.

Metabolic profile of the Warburg effect as a tool for molecular prognosis and diagnosis of cancer

INTRODUCTION

Adaptations of eukaryotic cells to environmental changes are important for their survival. However, under some circumstances, microenvironmental changes promote that eukaryotic cells utilize a metabolic signature resembling a unicellular organism named the Warburg effect. Most cancer cells share the Warburg effect displaying lactic fermentation and high glucose uptake. The Warburg effect also induces a metabolic rewiring stimulating glutamine consumption and lipid synthesis, also considered cancer hallmarks. Amino acid metabolism alteration due to the Warburg effect increases plasma levels of proline and branched-chain amino acids in several cancer types. Proline and lipids are probably used as electron transfer molecules in carcinogenic cells. In addition, branched-chain amino acids fuel the Krebs cycle, protein synthesis, and signaling in cancer cells.

AREAS COVERED

This review covers how metabolomics studies describe changes in some metabolites and proteins associated with the Warburg effect and related metabolic pathways.

EXPERT OPINION

In this review, we analyze the metabolic signature of the Warburg effect and related phenotypes and propose some Warburg effect-related metabolites and proteins (lactate, glucose uptake, glucose transporters, glutamine, branched-chain amino acids, proline, and some lipogenic enzymes) as promising cancer biomarkers.

Association between fatty acid synthase and adipophilin expression in triple‑negative breast cancer

It is well known that cancer cells produce energy via anaerobic glycolysis. Lipid metabolism is often upregulated in numerous types of cancer. Our previous study demonstrated that adipophilin (ADP), a lipid-associated protein, was a poor prognostic indicator in patients with triple-negative breast cancer (TNBC). However, the mechanism of ADP expression in TNBC remains unclear. Fatty acid synthase (FASN) is a crucial enzyme in de novo fatty acid synthesis, and its upregulation has been reported in several types of carcinomas; however, to the best of our knowledge, the association of FASN and ADP in TNBC remains unclear. The present study analysed the association between FASN and ADP expression and the prognostic significance of FASN in TNBC. Using immunohistochemical methods and tissue microarrays, the present study examined FASN expression in 61 patients with TNBC. Overall and relapse-free survival and their risk factors were analysed for FASN expression and compared with ADP expression. A total of 40 (65.6%) patients were classified as FASN-high (score ≥120), and this was significantly associated with a lower Ki-67 labelling index (P=0.011). FASN expression was not associated with relapse-free survival and overall survival. FASN-high was negatively associated with ADP expression (P=0.041). The results of the present study revealed that FASN-high was associated with a lack of ADP expression and a lower Ki-67 labelling index. These results indicated that de novo fatty acid synthesis by FASN is not the main pathway of lipogenesis and the source of energy in cancer cells of ADP-positive highly proliferative TNBC.

Fatty acid synthetase expression in triple-negative breast cancer

Background

Triple-negative breast cancer (TNBC) has a relatively poor prognosis. Research has identified potential metabolic targets, including fatty acid metabolism, in TNBC. The absence of effective target therapies for TNBC led to exploration of the role of fatty acid synthetase (FASN) as a potential target for TNBC therapy. Here, we analyzed the expression of FASN, a representative lipid metabolism–related protein, and investigated the association between FASN expression and Ki-67 and the programmed death ligand 1 (PD-L1) biomarkers in TNBC.

Methods

Immunohistochemical expression of FASN was analyzed in 166 patients with TNBC. For analytical purposes, patients with 0–1+ FASN staining were grouped as low-grade FASN and patients with 2–3+ FASN staining as high-grade FASN.

Results

FASN expression was observed in 47.1% of TNBC patients. Low and high expression of FASN was identified in 75.9% and 24.1%, respectively, and no statistically significant difference was found in T category, N category, American Joint Committee on Cancer stage, or recurrence rate between the low and high-FASN expression groups. Ki-67 proliferation level was significantly different between the low and high-FASN expression groups. FASN expression was significantly related to Ki-67 as the level increased. There was no significant difference in PD-L1 positivity between the low- and high-FASN expression groups.

Conclusions

We identified FASN expression in 166 TNBC patients. The Ki-67 proliferation index was positively correlated with FASN level, indicating higher proliferation activity as FASN increases. However, there was no statistical association with PD-L1 SP142, the currently FDA-approved assay, or FASN expression level.

Recent advances of nanotechnology in the diagnosis and therapy of triple-negative breast cancer (TNBC)

BACKGROUND

The development of advanced treatment of triple-negative breast cancer (TNBC) is the utmost need of an era. TNBC is recognized as the most aggressive, metastatic cancer and the leading cause of mortality in females worldwide. The lack of expression of triple receptors namely, estrogen, progesterone, and human epidermal receptor2 defined TNBC.

OBJECTIVE

The current review introduced the novel biomarkers such as miRNA and family, PD1, EGFR, VEGF, TILs, P53, AR and PI3K, etc. contributed significantly to the prognosis and diagnosis of TNBC. Once diagnosed the utilization advanced approaches available for TNBC because of the limitations of chemotherapy. Novel approaches include lipid-based (liposomes, SLN, NLC, and SNEDDS), polymer-based (micelle, nanoparticles, dendrimers, and quantum dots), advanced nanocarriers such as (exosomes, antibody and peptide-drug conjugates), carbon-based nanocarriers (Carbon nanotubes, and graphene oxide). Lipid-based delivery is used for excellent carriers for hydrophobic drugs, biocompatibility, and lesser systemic toxicities than chemotherapeutic agents. Polymer-based approaches are preferred over lipids for providing longer circulation time, nanosize, high loading efficiency, high linking; avoiding the expulsion of drugs, targeted action, diagnostic and biosensing abilities. Advanced approaches like exosomes, conjugated moieties are preferred over polymeric for possessing potency, high penetrability, biomarkers, and avoiding the toxicity of tissues. Carbon-based gained wide applicability for their unique properties like a versatile carrier, prognostic, diagnostic, sensing, photodynamic, and photothermal characteristics.

CONCLUSION

The survival rate can be increased by utilizing several kinds of biomarkers. The advanced approaches can also be significantly useful in the prognosis and theranostic of triple-negative breast cancer. One of the biggest successes in treating with nanotechnology-based approaches is the marked reduction of systemic toxicity with high therapeutic effectiveness compared with chemotherapy, surgery, etc. The requirements such as prompt diagnosis, longer circulation time, high efficiency, and high potency, can be fulfilled with these nanocarriers.