Upregulation of lipid metabolism genes in the breast prior to cancer diagnosis

Identification of the molecular subtypes and signatures to predict the prognosis, biological functions, and therapeutic response based on the anoikis-related genes in colorectal cancer

BACKGROUND

Tumors that resist anoikis, a programmed cell death triggered by detachment from the extracellular matrix, promote metastasis; however, the role of anoikis-related genes (ARGs) in colorectal cancer (CRC) stratification, prognosis, and biological functions remains unclear.

METHODS

We obtained transcriptomic profiles of CRC and 27 ARGs from The Cancer Genome Atlas, the Gene Expression Omnibus, and MSigDB databases, respectively. CRC tissue samples were classified into two clusters based on the expression pattern of ARGs, and their functional differences were explored. Hub genes were screened using weighted gene co-expression network analysis, univariate analysis, and least absolute selection and shrinkage operator analysis, and validated in cell lines, tissues, or the Human Protein Atlas database. We constructed an ARG-risk model and nomogram to predict prognosis in patients with CRC, which was validated using an external cohort. Multifaceted landscapes, including stemness, tumor microenvironment (TME), immune landscape, and drug sensitivity, between high- and low-risk groups were examined.

RESULTS

Patients with CRC were divided into C1 and C2 clusters. Cluster C1 exhibited higher TME scores, whereas cluster C2 had favorable outcomes and a higher stemness index. Eight upregulated hub ARGs (TIMP1, P3H1, SPP1, HAMP, IFI30, ADAM8, ITGAX, and APOC1) were utilized to construct the risk model. The qRT-PCR, Western blotting, and immunohistochemistry results were consistent with those of the bioinformatics analysis. Patients with high risk exhibited worse overall survival (p < 0.01), increased stemness, TME, immune checkpoint expression, immune infiltration, tumor mutation burden, and drug susceptibility compared with the patients with low risk.

CONCLUSION

Our results offer a novel CRC stratification based on ARGs and a risk-scoring system that could predict the prognosis, stemness, TME, immunophenotypes, and drug susceptibility of patients with CRC, thereby improving their prognosis. This stratification may facilitate personalized therapies.

Inference of differential gene regulatory networks using boosted differential trees

Summary

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We develop a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in four different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19, Crohn's disease, breast cancer, prostate adenocarcinoma, and stress response in Bacillus subtilis. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses.

Availability and implementation

BoostDiff is available at https://github.com/scibiome/boostdiff_inference.

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.

Towards Understanding the Development of Breast Cancer: The Role of RhoJ in the Obesity Microenvironment

Obesity is a growing pandemic with an increasing risk of inducing different cancer types, including breast cancer. Adipose tissue is proposed to be a major player in the initiation and progression of breast cancer in obese people. However, the mechanistic link between adipogenicity and tumorigenicity in breast tissues is poorly understood. We used in vitro and in vivo approaches to investigate the mechanistic relationship between obesity and the onset and progression of breast cancer. In obesity, adipose tissue expansion and remodeling are associated with increased inflammatory mediator's release and anti-inflammatory mediators' reduction.. In order to mimic the obesity micro-environment, we cultured cells in an enriched pro-inflammatory cytokine medium to which we added a low concentration of beneficial adipokines. Epithelial cells exposed to the obesity micro-environment were phenotypically transformed into mesenchymal-like cells, characterized by an increase in different mesenchymal markers and the acquisition of the major hallmarks of cancerous cells; these include sustained DNA damage, the activation of the ATR-Chk2 pathway, an increase in proliferation rate, cell invasion, and resistance to conventional chemotherapy. Transcriptomic analysis revealed that several genes, including RhoJ, CCL7, and MMP9, acted as potential major players in the observed phenomenon. The transcriptomics findings were confirmed in vitro using qRT-PCR and in vivo using high-fat-diet-fed mice. Our data suggests RhoJ as a potential novel molecular driver of tumor development in breast tissues and a mediator of cell resistance to conventional chemotherapy through PAK1 activation. These data propose that RhoJ is a potential target for therapeutic interventions in obese breast cancer patients.

LncRNA SOX9-AS1 triggers a transcriptional program involved in lipid metabolic reprogramming, cell migration and invasion in triple-negative breast cancer

At the molecular level, triple-negative breast cancer (TNBC) is frequently categorized as PAM50 basal-like subtype, but despite the advances in molecular analyses, the clinical outcome for these subtypes is uncertain. Long non-coding RNAs (lncRNAs) are master regulators of genes involved in hallmarks of cancer, which makes them suitable biomarkers for breast cancer (BRCA) diagnosis and prognosis. Here, we evaluated the regulatory role of lncRNA SOX9-AS1 in these subtypes. Using the BRCA-TCGA cohort, we observed that SOX9-AS1 was significantly overexpressed in basal-like and TNBC in comparison with other BRCA subtypes. Survival analyzes showed that SOX9-AS1 overexpression was associated with a favorable prognosis in TNBC and basal-like patients. To study the functions of SOX9-AS1, we determined the expression levels in a panel of nine BRCA cell lines finding increased levels in MDA-MB-468 and HCC1187 TNBC. Using subcellular fractionation in these cell lines, we ascertained that SOX9-AS1 was located in the cytoplasmic compartment. In addition, we performed SOX9-AS1 gene silencing using two short-harping constructs, which were transfected in both cell models and performed a genome-wide RNA-seq analysis. Data showed that 351 lncRNAs and 740 mRNAs were differentially expressed in MDA-MB-468 while 56 lncRNAs and 100 mRNAs were modulated in HCC1187 cells (Log2FC < - 1.5 and > 1.5, p.adj value < 0.05). Pathway analysis revealed that the protein-encoding genes potentially regulate lipid metabolic reprogramming, and epithelial-mesenchymal transition (EMT). Expression of lipid metabolic-related genes LIPE, REEP6, GABRE, FBP1, SCD1, UGT2B11, APOC1 was confirmed by RT-qPCR. Functional analysis demonstrated that the knockdown of SOX9-AS1 increases the triglyceride synthesis, cell migration and invasion in both two TNBC cell lines. In conclusion, high SOX9-AS1 expression predicts an improved clinical course in patients, while the loss of SOX9-AS1 expression enhances the aggressiveness of TNBC cells.

Endocrine-disrupting compounds and metabolomic reprogramming in breast cancer

Endocrine-disrupting chemicals pose a growing threat to human health through their increasing presence in the environment and their potential interactions with the mammalian endocrine systems. Due to their structural similarity to hormones like estrogen, these chemicals can interfere with endocrine signaling, leading to many deleterious effects. Exposure to estrogenic endocrine-disrupting compounds (EDC) is a suggested risk factor for the development of breast cancer, one of the most frequently diagnosed cancers in women. However, the mechanisms through which EDCs contribute to breast cancer development remain elusive. To rapidly proliferate, cancer cells undertake distinct metabolic programs to utilize existing nutrients in the tumor microenvironment and synthesize macromolecules de novo. EDCs are known to dysregulate cell signaling pathways related to cellular metabolism, which may be an important mechanism through which they exert their cancer-promoting effects. These altered pathways can be studied via metabolomic analysis, a new advancement in -omics technologies that can interrogate molecular pathways that favor cancer development and progression. This review will summarize recent discoveries regarding EDCs and the metabolic reprogramming that they may induce to facilitate the development of breast cancer.

Fatty acid profiles and Delta9 desaturase (stearoyl-CoA desaturase; SCD 1) expression in adipose tissue surrounding benign and malignant breast tumors

The progression of tumors occurs through interactions between the tumor and the stroma. Understanding the role of adipose tissue (AT), as the main component of the breast tumor microenvironment (TME) in the development of cancer, is crucial for the early detection of breast cancer (BC). This study compared the FA profiles, desaturase index (DI), and stearoyl CoA desaturase 1 (SCD1) mRNA levels in the AT that surrounds tumors in women with BC and benign breast disease (BBD). Specimens were collected from 40 Iranian women who had undergone breast surgery. These women were age- and BMI-matched and were divided into two groups: BC (n = 20) and BBD (n = 20). Gas chromatography and quantitative real-time PCR were used to analyze the FA profiles and SCD1 mRNA levels, respectively. The DI was calculated by dividing the amounts of monounsaturated FAs by the amount of saturated FA. There were no significant differences in age and BMI between women with BC and BBD. The FA profiles and DI were also similar in both groups. However, mRNA levels of SCD1 were found to be 5 times higher in the breast AT of BC than in the breast AT of BBD (p < 0.0001). We showed that SCD1 was significantly upregulated in the AT surrounding BC tumors, even though the DI and FA profiles were unchanged compared to those in the AT of BBD patients. It is important to note that the breast AT of women with BBD has previously been overlooked and warrants further studies.

MALDI-MSI of lipids in a model of breast cancer brain metastasis provides a surrogate measure of ischemia/hypoxia

Breast cancer brain metastasis (BCBM) has an incidence of 10-30%. It is incurable and the biological mechanisms that promote its progression remain largely undefined. Consequently, to gain insights into BCBM processes, we have developed a spontaneous mouse model of BCBM and in this study found a 20% penetrance of macro-metastatic brain lesion formation. Considering that lipid metabolism is indispensable to metastatic progression, our goal was the mapping of lipid distributions throughout the metastatic regions of the brain. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) of lipids revealed that, relative to surrounding brain tissue, seven long-chain (13-21 carbons long) fatty acylcarnitines, as well as two phosphatidylcholines, two phosphatidylinositols two diacylglycerols, a long-chain phosphatidylethanolamine, and a long-chain sphingomyelin were highly concentrated in the metastatic brain lesion In broad terms, lipids known to be enriched in brain tissues, such as very long-chain (≥ 22 carbons in length) polyunsaturated fatty acid of phosphatidylcholines, phosphatidylethanolamine, sphingomyelins, sulfatides, phosphatidylinositol phosphates, and galactosylceramides, were not found or only found in trace amounts in the metastatic lesion and instead consistently detected in surrounding brain tissues. The data, from this mouse model, highlights an accumulation of fatty acylcarnitines as possible biological makers of a chaotic inefficient vasculature within the metastasis, resulting in relatively inadequate blood flow and disruption of fatty acid β-oxidation due to ischemia/hypoxia.

Genome-wide association analysis of plasma lipidome identifies 495 genetic associations

The human plasma lipidome captures risk for cardiometabolic diseases. To discover new lipid-associated variants and understand the link between lipid species and cardiometabolic disorders, we perform univariate and multivariate genome-wide analyses of 179 lipid species in 7174 Finnish individuals. We fine-map the associated loci, prioritize genes, and examine their disease links in 377,277 FinnGen participants. We identify 495 genome-trait associations in 56 genetic loci including 8 novel loci, with a considerable boost provided by the multivariate analysis. For 26 loci, fine-mapping identifies variants with a high causal probability, including 14 coding variants indicating likely causal genes. A phenome-wide analysis across 953 disease endpoints reveals disease associations for 40 lipid loci. For 11 coronary artery disease risk variants, we detect strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and lipid species beyond the standard lipids.

Comprehensive analysis of clinical prognostic features and tumor microenvironment landscape of CD11b+CD64+ patients with acute myeloid leukemia

BACKGROUND

Immunophenotyping surface molecules detected in the clinic are mainly applied in diagnostic confirmation and subtyping. However, the immunomodulatory molecules CD11b and CD64, are highly associated with leukemogenesis. Hence, the prognostic value of them and their potential biological functions merit further investigation.

METHODS

Flow cytometry was operated to detect immunophenotypic molecules from AML bone marrow samples. Multivariate cox regression, Kaplan-Meier analyses, and nomogram were conducted to predict survival. Transcriptomic data, lymphocyte subsets, and immunohistochemical staining were incorporated to identify potential biological functions of prognostic immunophenotype in acute myeloid leukemia (AML).

RESULTS

We classified 315 newly diagnosed AML patients of our center based on the expression of CD11b and CD64. The CD11b+CD64+ populations were identified as independent risk factors for overall survival and event-free survival of AML, exhibiting specific clinicopathological features. The predictive models based on CD11b+CD64+ showed high classification performance. In addition, the CD11b+CD64+ subset, characterized by high inhibitory immune checkpoints, M2-macrophage infiltration, low anti-tumor effector cells infiltration, as well as abnormal somatic mutation landscape, presented a distinctive tumor microenvironmental landscape. The CD11b+CD64+ population showd a higher expression of BCL2, and the drug sensitivity indicated that they presented a lower half-maximal inhibitory concentration value for BCL2 inhibitor, and could benefit more from the above medicine.

CONCLUSIONS

This work might be of benefit to enhanced understanding of CD11b+CD64+ in the prognosis and leukemogenesis, and yielded novel biomarkers to guide immunotherapy and targeted therapy for AML.

Mendelian randomization analysis revealed potential metabolic causal factors for breast cancer

Observational studies showed that metabolic phenotypes were associated with the risk of developing breast cancer (BC). However, those results are inconsistent regarding the magnitude of the association, particularly by subtypes of breast cancer. Furthermore, the mechanisms of the association remain unclear. We performed two-sample Mendelian randomization (MR) analyses to evaluate the causal effect of metabolic risk factors on breast cancer in the European population. Assessed individually using MR, body mass index (BMI) (odds ratio [OR] 0.94, 95% Confidence interval [CI] 0.90-0.98, P = 0.007), high-density lipoprotein cholesterol (HDL-C) (OR 1.10, 95% CI 1.07-1.13, P = 6.10 × 10-11) and triglycerides (TG) (OR 0.92, 95% CI 0.90-0.96, P = 1.58 × 10-6) were causally related to breast cancer risk. In multivariable MR, only HDL-C (OR 1.08; 95% CI 1.02-1.14; P = 0.02) retained a robust effect, suggesting that the genetic association between BMI, HDL-C and TG with breast cancer risk in univariable analysis was explained via HDL-C. These findings suggest a possible causal role of HDL-C in breast cancer etiology.

Elucidating the roles of the mammary and gut microbiomes in breast cancer development

The mammary microbiome is a newly characterized bacterial niche that might offer biological insight into the development of breast cancer. Together with in-depth analysis of the gut microbiome in breast cancer, current evidence using next-generation sequencing and metabolic profiling suggests compositional and functional shifts in microbial consortia are associated with breast cancer. In this review, we discuss the fundamental studies that have progressed this important area of research, focusing on the roles of both the mammary tissue microbiome and the gut microbiome. From the literature, we identified the following major conclusions, (I) There are unique breast and gut microbial signatures (both compositional and functional) that are associated with breast cancer, (II) breast and gut microbiome compositional and breast functional dysbiosis represent potential early events of breast tumor development, (III) specific breast and gut microbes confer host immune responses that can combat breast tumor development and progression, and (IV) chemotherapies alter the microbiome and thus maintenance of a eubiotic microbiome may be key in breast cancer treatment. As the field expectantly advances, it is necessary for the role of the microbiome to continue to be elucidated using multi-omic approaches and translational animal models in order to improve predictive, preventive, and therapeutic strategies for breast cancer.

Exploring breast tissue microbial composition and the association with breast cancer risk factors

BACKGROUND

Microbial dysbiosis has emerged as an important element in the development and progression of various cancers, including breast cancer. However, the microbial composition of the breast from healthy individuals, even relative to risk of developing breast cancer, remains unclear. Here, we performed a comprehensive analysis of the microbiota of the normal breast tissue, which was analyzed in relation to the microbial composition of the tumor and adjacent normal tissue.

METHODS

The study cohorts included 403 cancer-free women (who donated normal breast tissue cores) and 76 breast cancer patients (who donated tumor and/or adjacent normal tissue samples). Microbiome profiling was obtained by sequencing the nine hypervariable regions of the 16S rRNA gene (V1V2, V2V3, V3V4, V4V5, V5V7, and V7V9). Transcriptome analysis was also performed on 190 normal breast tissue samples. Breast cancer risk score was assessed using the Tyrer-Cuzick risk model.

RESULTS

The V1V2 amplicon sequencing resulted more suitable for the analysis of the normal breast microbiome and identified Lactobacillaceae (Firmicutes phylum), Acetobacterraceae, and Xanthomonadaceae (both Proteobacteria phylum) as the most abundant families in the normal breast. However, Ralstonia (Proteobacteria phylum) was more abundant in both breast tumors and histologically normal tissues adjacent to malignant tumors. We also conducted a correlation analysis between the microbiome and known breast cancer risk factors. Abundances of the bacterial taxa Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp. were associated with age (p < 0.0001), racial background (p < 0.0001), and parity (p < 0.0001). Finally, transcriptome analysis of normal breast tissues showed an enrichment in metabolism- and immune-related genes in the tissues with abundant Acetotobacter aceti, Lactobacillus vini, Lactobacillus paracasei, and Xanthonomas sp., whereas the presence of Ralstonia in the normal tissue was linked to dysregulation of genes involved in the carbohydrate metabolic pathway.

CONCLUSIONS

This study defines the microbial features of normal breast tissue, thus providing a basis to understand cancer-related dysbiosis. Moreover, the findings reveal that lifestyle factors can significantly affect the normal breast microbial composition.

The Ratio of Monocyte to Apolipoprotein A1 is an Independent Predictor of Breast Cancer: A Retrospective Study

Objective

To explore the predictive value of the ratio of monocyte to apolipoprotein A1 (MAR) (a new index related to inflammation and lipid in breast cancer (BC)) and its relationship with clinicopathological staging.

Methods

The hematological test results of 394 patients with breast diseases, including 276 cases of BC, 118 cases of benign breast disease (BBD), and 219 healthy volunteers (HV), were retrospectively collected. The clinical value of MAR was analyzed with binary logistic regression.

Results

Using statistical software analysis, the results showed that MAR level (P<0.001) was the largest in the BC group, followed by BBD, and the lowest in the HV group, and it was found to be an indicator to distinguish BC from BBD, also an independent risk factor for BC. The increase in MAR level showed that the risk of BC was 3.733 times higher than that of HV (P<0.001). In addition, there was a notable difference in MAR between early, middle and late stages of BC patients (P=0.047), with the highest MAR level in late stage (0.510±0.078) and the lowest MAR level in early stage (0.392±0.011); the MAR level of those with tumor invasion depth of Phase 4 was the highest (0.484±0.072), and that of Phase 1/2 was the lowest (0.379±0.010), with a statistically significant difference (P<0.001). MAR was positively correlated with tumor invasion depth (P<0.001, r=0.210), that's, the size of MAR increased when there was more deeper tumor invasion.

Conclusion

MAR is a new indicator for the auxiliary differential diagnosis of benign and malignant breast diseases, and is also an independent risk factor for BC. High-level MAR is closely related to late staging and tumor invasion depth of BC. It can be seen that MAR is a potentially valuable predictor of BC, and this is the first study to explore the clinical value of MAR in BC.

Mass Spectrometry Imaging of Lumpectomy Specimens Deciphers Diacylglycerols as Potent Biomarkers for the Diagnosis of Breast Cancer

Detecting breast tumor markers with a fast turnaround time from frozen sections should foster intraoperative histopathology in breast-conserving surgery, reducing the need for a second operation. Hence, rapid label-free discrimination of the spatially resolved molecular makeup between cancer and adjacent normal breast tissue is of growing importance. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) of fresh-frozen excision specimens, including cancer and paired adjacent normal sections, obtained from the lumpectomy of 73 breast cancer patients. The results demonstrate that breast cancer tissue posits sharp metabolic upregulation of diacylglycerol, a lipid second messenger that activates protein kinase C for promoting tumor growth. We identified four specific sn-1,2-diacylglycerols that outperformed all other lipids simultaneously mapped by the positive ion mode DESI-MSI for distinguishing cancers from adjacent normal specimens. This result contrasts with several previous DESI-MSI studies that probed metabolic dysregulation of glycerophospholipids, sphingolipids, and free fatty acids for cancer diagnoses. A random forest-based supervised machine learning considering all detected ion signals also deciphered the highest diagnostic potential of these four diacylglycerols with the top four importance scores. This led us to construct a classifier with 100% overall prediction accuracy of breast cancer by using the parsimonious set of four diacylglycerol biomarkers only. The metabolic pathway analysis suggested that increased catabolism of phosphatidylcholine in breast cancer contributes to diacylglycerol overexpression. These results open up opportunities for mapping diacylglycerol signaling in breast cancer in the context of novel therapeutic and diagnostic developments, including the intraoperative assessment of breast cancer margin status.

Molecular breast cancer subtype identification using photoacoustic spectral analysis and machine learning at the biomacromolecular level

Breast cancer threatens the health of women worldwide, and its molecular subtypes largely determine the therapy and prognosis of patients. However, an uncomplicated and accurate method to identify subtypes is currently lacking. This study utilized photoacoustic spectral analysis (PASA) based on the partial least squares discriminant algorithm (PLS-DA) to identify molecular breast cancer subtypes at the biomacromolecular level in vivo. The area of power spectrum density (APSD) was extracted to semi-quantify the biomacromolecule content. The feature wavelengths were obtained via the variable importance in projection (VIP) score and the selectivity ratio (Sratio), to identify the biomarkers. The PASA achieved an accuracy of 84%. Most of the feature wavelengths fell into the collagen-dominated absorption waveband, which was consistent with the histopathological results. This paper proposes a successful method for identifying molecular breast cancer subtypes and proves that collagen can be treated as a biomarker for molecular breast cancer subtyping.

Obesity promotes breast epithelium DNA damage in women carrying a germline mutation in BRCA1 or BRCA2

Obesity, defined as a body mass index (BMI) ≥ 30, is an established risk factor for breast cancer among women in the general population after menopause. Whether elevated BMI is a risk factor for women with a germline mutation in BRCA1 or BRCA2 is less clear because of inconsistent findings from epidemiological studies and a lack of mechanistic studies in this population. Here, we show that DNA damage in normal breast epithelia of women carrying a BRCA mutation is positively correlated with BMI and with biomarkers of metabolic dysfunction. In addition, RNA sequencing showed obesity-associated alterations to the breast adipose microenvironment of BRCA mutation carriers, including activation of estrogen biosynthesis, which affected neighboring breast epithelial cells. In breast tissue explants cultured from women carrying a BRCA mutation, we found that blockade of estrogen biosynthesis or estrogen receptor activity decreased DNA damage. Additional obesity-associated factors, including leptin and insulin, increased DNA damage in human BRCA heterozygous epithelial cells, and inhibiting the signaling of these factors with a leptin-neutralizing antibody or PI3K inhibitor, respectively, decreased DNA damage. Furthermore, we show that increased adiposity was associated with mammary gland DNA damage and increased penetrance of mammary tumors in Brca1+/- mice. Overall, our results provide mechanistic evidence in support of a link between elevated BMI and breast cancer development in BRCA mutation carriers. This suggests that maintaining a lower body weight or pharmacologically targeting estrogen or metabolic dysfunction may reduce the risk of breast cancer in this population.

Effective breast cancer therapy based on palmitic acid-loaded PLGA nanoparticles

Although new strategies for breast cancer treatment have yielded promising results, most drugs can lead to serious side effects when applied systemically. Doxorubicin (DOX), currently the most effective chemotherapeutic drug to treat breast cancer, is poorly selective towards tumor cells and treatment often leads to the development of drug resistance. Recent studies have indicated that several fatty acids (FAs) have beneficial effects on inhibiting tumorigenesis. The saturated FA palmitic acid (PA) showed anti-tumor activities in several types of cancer, as well as effective repolarization of M2 macrophages towards the anti-tumorigenic M1 phenotype. However, water insolubility and cellular impermeability limit the use of PA in vivo. To overcome these limitations, here, we encapsulated PA into a poly(d,l-lactic co-glycolic acid) (PLGA) nanoparticle (NP) platform, alone and in combination with DOX, to explore PA's potential as mono or combinational breast cancer therapy. Our results showed that PLGA-PA-DOX NPs and PLGA-PA NPs significantly reduced the viability and migratory capacity of breast cancer cells in vitro. In vivo studies in mice bearing mammary tumors demonstrated that PLGA-PA-NPs were as effective in reducing primary tumor growth and metastasis as NPs loaded with DOX, PA and DOX, or free DOX. At the molecular level, PLGA-PA NPs reduced the expression of genes associated with multi-drug resistance and inhibition of apoptosis, and induced apoptosis via a caspase-3-independent pathway in breast cancer cells. In addition, immunohistochemical analysis of residual tumors showed a reduction in M2 macrophage content and infiltration of leukocytes after treatment of PLGA-PA NPs and PLGA-PA-DOX NPs, suggesting immunomodulatory properties of PA in the tumor microenvironment. In conclusion, the use of PA alone or in combination with DOX may represent a promising novel strategy for the treatment of breast cancer.

Emphasis on Adipocyte Transformation: Anti-Inflammatory Agents to Prevent the Development of Cancer-Associated Adipocytes

Of the various cell types in the tumor microenvironment (TME), adipocytes undergo a dynamic transformation when activated by neighboring cancer cells. Although these adipocytes, known as cancer-associated adipocytes (CAAs), have been reported to play a crucial role in tumor progression, the factors that mediate their transformation remain elusive. In this review, we discuss the hypothesis that inflammatory signals involving NF-ĸB activation can induce lipolysis and adipocyte dedifferentiation. This provides a mechanistic understanding of CAA formation and introduces the concept of preventing adipocyte transformation via anti-inflammatory agents. Indeed, epidemiological studies indicate a higher efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) in obese patients with cancer, suggesting that NSAIDs can modulate the TME. Inhibition of cyclooxygenase-2 (COX-2) and prostaglandin production leads to the suppression of inflammatory signals such as NF-ĸB. Thus, we suggest the use of NSAIDs in cancer patients with metabolic disorders to prevent the transformation of TME components. Moreover, throughout this review, we attempt to expand our knowledge of CAA transformation to improve the clinical feasibility of targeting CAAs.

C1QBP Mediates Breast Cancer Cell Proliferation and Growth via Multiple Potential Signalling Pathways

Breast carcinoma is the most prevalent cancer in women globally, with complex genetic and molecular mechanisms that underlie its development and progression. Several challenges such as metastasis and drug resistance limit the prognosis of breast cancer, and hence a constant search for better treatment regimes, including novel molecular therapeutic targets is necessary. Complement component 1, q subcomponent binding protein (C1QBP), a promising molecular target, has been implicated in breast carcinogenesis. In this study, the role of C1QBP in breast cancer progression, in particular cancer cell growth, was determined in triple negative MDA-MB-231 breast cancer cells. Depletion of C1QBP decreased cell proliferation, whereas the opposite effect was observed when C1QBP was overexpressed in MDA-MB-231 cells. Furthermore, gene expression profiling and pathway analysis in C1QBP depleted cells revealed that C1QBP regulates several signaling pathways crucial for cell growth and survival. Taken together, these findings provide a deeper comprehension of the role of C1QBP in triple negative breast cancer, and could possibly pave the way for future advancement of C1QBP-targeted breast cancer therapy.

Aquaporins in Tumor

Recent researches have demonstrated that aquaporins (AQPs), including water-selective channels, aquaglyceroporins and superaquaporins, are generally expressed in various tumors, such as lung, colorectal, liver, brain, breast tumors, etc. Therefore, it is imperative to study the accurate relationship between AQPs and tumor, which may provide innovative approaches to treat and prevent tumor development. In this chapter, we mainly reviewed the expression and pathophysiological function of AQPs in tumor, and summarize recent work on AQPs in tumor. Although, the underlying mechanism of AQP in tumor is not very clear, growing evidences suggest that cell migration, adhesion, angiogenesis, and division contribute to tumor development, in which AQPs might be involved. Therefore, it is still necessary to conduct further studies to determine the specific roles of AQPs in the tumor.

Bidirectional Mendelian randomization study of insulin-related traits and risk of ovarian cancer

BACKGROUND

It is well known that the occurrence and development of ovarian cancer are closely related to the patient's weight and various endocrine factors in the body.

AIM

Mendelian randomization (MR) was used to analyze the bidirectional relationship between insulin related characteristics and ovarian cancer.

METHODS

The data on insulin related characteristics are from up to 5567 diabetes free patients from 10 studies, mainly including fasting insulin level, insulin secretion rate, peak insulin response, etc. For ovarian cancer, UK Biobank data just updated in 2021 was selected, of which the relevant gene data was from 199741 Europeans. Mendelian randomization method was selected, with inverse variance weighting (IVW) as the main estimation, while MR Pleiotropy, MR Egger, weighted median and other methods were used to detect the heterogeneity of data and whether there was multi validity affecting conclusions.

RESULTS

Among all insulin related indicators (fasting insulin level, insulin secretion rate, peak insulin response), the insulin secretion rate was selected to have a causal relationship with the occurrence of ovarian cancer (IVW, P < 0.05), that is, the risk of ovarian cancer increased with the decrease of insulin secretion rate. At the same time, we tested the heterogeneity and polymorphism of this indicator, and the results were non-existent, which ensured the accuracy of the analysis results. Reverse causal analysis showed that there was no causal effect between the two (P>0.05).

CONCLUSION

The impairment of the insulin secretion rate has a causal effect on the risk of ovarian cancer, which was confirmed by Mendel randomization. This suggests that the human glucose metabolism cycle represented by insulin secretion plays an important role in the pathogenesis of ovarian cancer, which provides a new idea for preventing the release of ovarian cancer.

Fatty acid metabolism and radiation-induced anti-tumor immunity

Fatty acid metabolic reprogramming has emerged as a major regulator of anti-tumor immune responses with large body of evidence that demonstrate its ability to impact the differentiation and function of immune cells. Therefore, depending on the metabolic cues that stem in the tumor microenvironment, the tumor fatty acid metabolism can tilt the balance of inflammatory signals to either promote or impair anti-tumor immune responses. Oxidative stressors such as reactive oxygen species generated from radiation therapy can rewire the tumor energy supply, suggesting that radiation therapy can further perturb the energy metabolism of a tumor by promoting fatty acid production. In this review, we critically discuss the network of fatty acid metabolism and how it regulates immune response especially in the context of radiation therapy.

Phytochemical Targeting of Mitochondria for Breast Cancer Chemoprevention, Therapy, and Sensitization

Breast cancer is a common and deadly disease that causes tremendous physical, emotional, and financial burden on patients and society. Early-stage breast cancer and less aggressive subtypes have promising prognosis for patients, but in aggressive subtypes, and as cancers progress, treatment options and responses diminish, dramatically decreasing survival. Plants are nutritionally rich and biologically diverse organisms containing thousands of metabolites, some of which have chemopreventive, therapeutic, and sensitizing properties, providing a rich source for drug discovery. In this study we review the current landscape of breast cancer with a central focus on the potential role of phytochemicals for treatment, management, and disease prevention. We discuss the relevance of phytochemical targeting of mitochondria for improved anti-breast cancer efficacy. We highlight current applications of phytochemicals and derivative structures that display anti-cancer properties and modulate cancer mitochondria, while describing future applicability and identifying areas of promise.

The role of lipids in cancer progression and metastasis

Lipids have essential biological functions in the body (e.g., providing energy storage, acting as a signaling molecule, and being a structural component of membranes); however, an excess of lipids can promote tumorigenesis, colonization, and metastatic capacity of tumor cells. To metastasize, a tumor cell goes through different stages that require lipid-related metabolic and structural adaptations. These adaptations include altering the lipid membrane composition for invading other niches and overcoming cell death mechanisms and promoting lipid catabolism and anabolism for energy and oxidative stress protective purposes. Cancer cells also harness lipid metabolism to modulate the activity of stromal and immune cells to their advantage and to resist therapy and promote relapse. All this is especially worrying given the high fat intake in Western diets. Thus, metabolic interventions aiming to reduce lipid availability to cancer cells or to exacerbate their metabolic vulnerabilities provide promising therapeutic opportunities to prevent cancer progression and treat metastasis.

Developing dietary interventions as therapy for cancer

Cancer cells acquire distinct metabolic preferences based on their tissue of origin, genetic alterations and degree of interaction with systemic hormones and metabolites. These adaptations support the increased nutrient demand required for increased growth and proliferation. Diet is the major source of nutrients for tumours, yet dietary interventions lack robust evidence and are rarely prescribed by clinicians for the treatment of cancer. Well-controlled diet studies in patients with cancer are rare, and existing studies have been limited by nonspecific enrolment criteria that inappropriately grouped together subjects with disparate tumour and host metabolic profiles. This imprecision may have masked the efficacy of the intervention for appropriate candidates. Here, we review the metabolic alterations and key vulnerabilities that occur across multiple types of cancer. We describe how these vulnerabilities could potentially be targeted using dietary therapies including energy or macronutrient restriction and intermittent fasting regimens. We also discuss recent trials that highlight how dietary strategies may be combined with pharmacological therapies to treat some cancers, potentially ushering a path towards precision nutrition for cancer.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

Composition and Functional Potential of the Human Mammary Microbiota Prior to and Following Breast Tumor Diagnosis

Microbiota studies have reported changes in the microbial composition of the breast upon cancer development. However, results are inconsistent and limited to the later phases of cancer development (after diagnosis). We analyzed and compared the resident bacterial taxa of histologically normal breast tissue (healthy, H, n = 49) with those of tissues donated prior to (prediagnostic, PD, n = 15) and after (adjacent normal, AN, n = 49, and tumor, T, n = 46) breast cancer diagnosis (n total = 159). DNA was isolated from tissue samples and submitted for Illumina MiSeq paired-end sequencing of the V3-V4 region of the 16S gene. To infer bacterial function in breast cancer, we predicted the functional bacteriome from the 16S sequencing data using PICRUSt2. Bacterial compositional analysis revealed an intermediary taxonomic signature in the PD tissue relative to that of the H tissue, represented by shifts in Bacillaceae, Burkholderiaceae, Corynebacteriaceae, Streptococcaceae, and Staphylococcaceae. This compositional signature was enhanced in the AN and T tissues. We also identified significant metabolic reprogramming of the microbiota of the PD, AN, and T tissue compared with the H tissue. Further, preliminary correlation analysis between host transcriptome profiling and microbial taxa and genes in H and PD tissues identified altered associations between the human host and mammary microbiota in PD tissue compared with H tissue. These findings suggest that compositional shifts in bacterial abundance and metabolic reprogramming of the breast tissue microbiota are early events in breast cancer development that are potentially linked with cancer susceptibility.

IMPORTANCE The goal of this study was to determine the role of resident breast tissue bacteria in breast cancer development. We analyzed breast tissue bacteria in healthy breast tissue and breast tissue donated prior to (precancerous) and after (postcancerous) breast cancer diagnosis. Compared to healthy tissue, the precancerous and postcancerous breast tissues demonstrated differences in the amounts of breast tissue bacteria. In addition, breast tissue bacteria exhibit different functions in pre-cancerous and post-cancerous breast tissues relative to healthy tissue. These differences in function are further emphasized by altered associations of the breast tissue bacteria with gene expression in the human host prior to cancer development. Collectively, these analyses identified shifts in bacterial abundance and metabolic function (dysbiosis) prior to breast tumor diagnosis. This dysbiosis may serve as a therapeutic target in breast cancer prevention.

A Review of Twenty Years of Research on the Regulation of Signaling Pathways by Natural Products in Breast Cancer

Breast cancer (BC) is the second leading cause of death among women, and it has become a global health issue due to the increasing number of cases. Different treatment options, including radiotherapy, surgery, chemotherapy and anti-estrogen therapy, aromatase inhibitors, anti-angiogenesis drugs, and anthracyclines, are available for BC treatment. However, due to its high occurrence and disease progression, effective therapeutic options for metastatic BC are still lacking. Considering this scenario, there is an urgent need for an effective therapeutic strategy to meet the current challenges of BC. Natural products have been screened as anticancer agents as they are cost-effective, possess low toxicity and fewer side effects, and are considered alternative therapeutic options for BC therapy. Natural products showed anticancer activities against BC through the inhibition of angiogenesis, cell migrations, proliferations, and tumor growth; cell cycle arrest by inducing apoptosis and cell death, the downstream regulation of signaling pathways (such as Notch, NF-κB, PI3K/Akt/mTOR, MAPK/ERK, and NFAT-MDM2), and the regulation of EMT processes. Natural products also acted synergistically to overcome the drug resistance issue, thus improving their efficacy as an emerging therapeutic option for BC therapy. This review focused on the emerging roles of novel natural products and derived bioactive compounds as therapeutic agents against BC. The present review also discussed the mechanism of action through signaling pathways and the synergistic approach of natural compounds to improve their efficacy. We discussed the recent in vivo and in vitro studies for exploring the overexpression of oncogenes in the case of BC and the current status of newly discovered natural products in clinical investigations.

Multifunctional Role of Lipids in Modulating the Tumorigenic Properties of 4T1 Breast Cancer Cells

Tumor growth and progression are linked to an altered lipid metabolism in the tumor microenvironment (TME), including tumor cells and tumor-associated macrophages (TAMs). A growing number of lipid metabolism targeting drugs have shown efficacy in anti-tumor therapy. In addition, exogenously applied lipids and lipid analogues have demonstrated anti-tumor activities in several cancers, including breast cancer. In this study, we investigated the anti-tumor efficacies of the natural lipids palmitic acid (PA), sphingomyelin (SM), ceramide (Cer) and docosahexaenoic acid (DHA) on breast cancer cells. All tested lipids reduced the malignancy of breast cancer cells in vitro by impairing cell proliferation, migration and invasiveness. PA showed superior anti-tumor properties, as it additionally impaired cancer cell viability by inducing apoptosis, without affecting healthy cells. Co-culture experiments further demonstrated that Cer and PA reduced the immunosuppressive phenotype of M2 macrophages and the M2 macrophage-promoted the epithelial–mesenchymal transition (EMT) and migration of breast cancer cells. At the molecular level, this coincided with the up-regulation of E-cadherin. Our results highlight a powerful role for exogenously applied PA and Cer in reducing breast cancer tumorigenicity by simultaneously targeting cancer cells and M2 macrophages. Our findings support the notion that lipids represent alternative biocompatible therapeutic agents for breast cancer.

Insulin and cancer: a tangled web

For a century, since the pioneering work of Otto Warburg, the interwoven relationship between metabolism and cancer has been appreciated. More recently, with obesity rates rising in the U.S. and worldwide, epidemiologic evidence has supported a link between obesity and cancer. A substantial body of work seeks to mechanistically unpack the association between obesity, altered metabolism, and cancer. Without question, these relationships are multifactorial and cannot be distilled to a single obesity- and metabolism-altering hormone, substrate, or factor. However, it is important to understand the hormone-specific associations between metabolism and cancer. Here, we review the links between obesity, metabolic dysregulation, insulin, and cancer, with an emphasis on current investigational metabolic adjuncts to standard-of-care cancer treatment.

FAM83A is a potential biomarker for breast cancer initiation

Background

Family with sequence similarity 83 member A (FAM83A) presents oncogenic properties in several cancers including breast cancer. Recently, we reported FAM83A overexpression in normal breast tissues from women at high risk of breast cancer. We now hypothesize that FAM83A is a key factor in breast cancer initiation.

Methods

Immunohistochemical staining was used to evaluate FAM83A protein levels in both a normal breast tissue microarray (TMA, N = 411) and a breast tumor TMA (N = 349). EGFR staining and its correlation with FAM83A expression were also assessed. Lentivirus-mediated manipulation of FAM83A expression in primary and hTERT-immortalized breast epithelial cells was employed. Biological and molecular alterations upon FAM83A overexpression/downregulation and FAM83A’s interaction partners were investigated.

Results

TMA analysis revealed a 1.5-fold increase in FAM83A expression level in breast cancer cases as compared with normal breast tissues (p < 0.0001). FAM83A protein expression was directly correlated with EGFR level in both normal and breast cancer tissues. In in vitro assays, exogenous expression of FAM83A in either primary or immortalized breast epithelial cells promoted cell viability and proliferation. Additionally, Ingenuity Pathway Analysis (IPA) revealed that FAM83A overexpression in primary cells affected the expression of genes involved in cellular morphology and metabolism. Mass spectrometry analysis identified DDX3X and LAMB3 as potential FAM83A interaction partners in primary cells, while we detected FAM83A interaction with cytoskeleton reorganization factors, including LIMA1, MYH10, PLEC, MYL6 in the immortalized cells.

Conclusions

This study shows that FAM83A promotes metabolic activation in primary breast epithelial cells and cell proliferation in both primary and immortalized cells. These findings support its role in early breast oncogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-022-00353-9.

Aberrant epigenetic and transcriptional events associated with breast cancer risk

BACKGROUND

Genome-wide association studies have identified several breast cancer susceptibility loci. However, biomarkers for risk assessment are still missing. Here, we investigated cancer-related molecular changes detected in tissues from women at high risk for breast cancer prior to disease manifestation. Disease-free breast tissue cores donated by healthy women (N = 146, median age = 39 years) were processed for both methylome (MethylCap) and transcriptome (Illumina's HiSeq4000) sequencing. Analysis of tissue microarray and primary breast epithelial cells was used to confirm gene expression dysregulation.

RESULTS

Transcriptomic analysis identified 69 differentially expressed genes between women at high and those at average risk of breast cancer (Tyrer-Cuzick model) at FDR < 0.05 and fold change ≥ 2. Majority of the identified genes were involved in DNA damage checkpoint, cell cycle, and cell adhesion. Two genes, FAM83A and NEK2, were overexpressed in tissue sections (FDR < 0.01) and primary epithelial cells (p < 0.05) from high-risk breasts. Moreover, 1698 DNA methylation changes were identified in high-risk breast tissues (FDR < 0.05), partially overlapped with cancer-related signatures, and correlated with transcriptional changes (p < 0.05, r ≤ 0.5). Finally, among the participants, 35 women donated breast biopsies at two time points, and age-related molecular alterations enhanced in high-risk subjects were identified.

CONCLUSIONS

Normal breast tissue from women at high risk of breast cancer bears molecular aberrations that may contribute to breast cancer susceptibility. This study is the first molecular characterization of the true normal breast tissues, and provides an opportunity to investigate molecular markers of breast cancer risk, which may lead to new preventive approaches.

MS4A1 as a Potential Independent Prognostic Factor of Breast Cancer Related to Lipid Metabolism and Immune Microenvironment Based on TCGA Database Analysis

Background

Lipid metabolism has been proved to be related to the prognosis of breast cancer patients in previous studies, and the tumor immune microenvironment (TIME) plays an important role in tumorigenesis and development, but the dynamic regulation of these is still a challenge.

Material/Methods

This study used lipid metabolism-related pathways to score the gene expression of 980 breast cancer patients in the TCGA database. We used 4 pathways in HALLMARK related to lipid metabolism to score the genes in the database. The differentially expressed genes (DEGs) were further analyzed through survival analysis and Cox regression analysis, and MS4A1, which is associated with better prognosis, was finally determined to be a predictor. In-depth analysis found that MS4A1 was negatively correlated with patient age, clinical stage, tumor size, and distant metastasis. In the MS4A1 high-expression group, most genes were enriched in immune-related pathways, and CIBERSORT analysis found that MS4A1 expression was positively correlated with the abundance of 10 kinds of immune cells, such as CD8⁺T cells, which are related to the active immune status.

Results

Our results suggest that MS4A1 expression can indicate the situation of lipid metabolism in breast cancer patients and reflect the status of the immune microenvironment.

Conclusions

MS4A1 has the potential to be an independent indicator of prognosis. Since the expression of MS4A1 is also related to the immune checkpoint mutation burden, detecting its expression level can also provide guidance for choosing treatment options.

Local Biomarkers Involved in the Interplay between Obesity and Breast Cancer

Simple Summary

Breast cancer is the second most common cancer in women worldwide. The risk of developing breast cancer depends on various mechanisms, such as age, heredity, reproductive factors, physical inactivity, and obesity. Obesity increases the risk of breast cancer and worsens outcomes for breast cancer patients. The rate of obesity is increasing worldwide, stressing the need for awareness of the association between obesity and breast cancer. In this review, we outline the biomarkers—including cellular and soluble factors—in the breast, associated with obesity, that affect the risk of breast cancer and breast cancer prognosis. Through these biomarkers, we aim to better identify patients with obesity with a higher risk of breast cancer and an inferior prognosis.

Abstract

Obesity is associated with an increased risk of breast cancer, which is the most common cancer in women worldwide (excluding non-melanoma skin cancer). Furthermore, breast cancer patients with obesity have an impaired prognosis. Adipose tissue is abundant in the breast. Therefore, breast cancer develops in an adipose-rich environment. During obesity, changes in the local environment in the breast occur which are associated with breast cancer. A shift towards a pro-inflammatory state is seen, resulting in altered levels of cytokines and immune cells. Levels of adipokines, such as leptin, adiponectin, and resistin, are changed. Aromatase activity rises, resulting in higher levels of potent estrogen in the breast. Lastly, remodeling of the extracellular matrix takes place. In this review, we address the current knowledge on the changes in the breast adipose tissue in obesity associated with breast cancer initiation and progression. We aim to identify obesity-associated biomarkers in the breast involved in the interplay between obesity and breast cancer. Hereby, we can improve identification of women with obesity with an increased risk of breast cancer and an impaired prognosis. Studies investigating mammary adipocytes and breast adipose tissue in women with obesity versus women without obesity are, however, sparse and further research is needed.

Early Detection and Investigation of Extracellular Vesicles Biomarkers in Breast Cancer

Breast cancer (BC) is the most commonly diagnosed malignant tumor in women worldwide, and the leading cause of cancer death in the female population. The percentage of patients experiencing poor prognosis along with the risk of developing metastasis remains high, also affecting the resistance to current main therapies. Cancer progression and metastatic development are no longer due entirely to their intrinsic characteristics, but also regulated by signals derived from cells of the tumor microenvironment. Extracellular vesicles (EVs) packed with DNA, RNA, and proteins, are the most attractive targets for both diagnostic and therapeutic applications, and represent a decisive challenge as liquid biopsy-based markers. Here we performed a study based on a multiplexed phenotyping flow cytometric approach to characterize BC-derived EVs from BC patients and cell lines, through the detection of multiple antigens. Our data reveal the expression of EVs-related biomarkers derived from BC patient plasma and cell line supernatants, suggesting that EVs could be exploited for characterizing and monitoring disease progression.

Overview of human 20 alpha-hydroxysteroid dehydrogenase (AKR1C1): Functions, regulation, and structural insights of inhibitors

Human aldo-keto reductase family 1C1 (AKR1C1) is an important enzyme involved in human hormone metabolism, which is mainly responsible for the metabolism of progesterone in the human body. AKR1C1 is highly expressed and has an important relationship with the occurrence and development of various diseases, especially some cancers related to hormone metabolism. Nowadays, many inhibitors against AKR1C1 have been discovered, including some synthetic compounds and natural products, which have certain inhibitory activity against AKR1C1 at the target level. Here we briefly reviewed the physiological and pathological functions of AKR1C1 and the relationship with the disease, and then summarized the development of AKR1C1 inhibitors, elucidated the interaction between inhibitors and AKR1C1 through molecular docking results and existing co-crystal structures. Finally, we discussed the design ideals of selective AKR1C1 inhibitors from the perspective of AKR1C1 structure, discussed the prospects of AKR1C1 in the treatment of human diseases in terms of biomarkers, pre-receptor regulation and single nucleotide polymorphisms, aiming to provide new ideas for drug research targeting AKR1C1.

Role of the CTRP family in tumor development and progression

C1q tumor necrosis factor-related proteins (CTRPs), which are members of the adipokine superfamily, have gained significant interest in the recent years. CTRPs are homologs of adiponectin with numerous functions and are closely associated with metabolic diseases, such as abnormal glucose and lipid metabolism and diabetes. Previous studies have demonstrated that CTRPs are highly involved in the regulation of numerous physiological and pathological processes, including glycolipid metabolism, protein kinase pathways, cell proliferation, cell apoptosis and inflammation. CTRPs also play important roles in the development and progression of numerous types of tumor, including liver, colon and lung cancers. This observation can be attributed to the fact that diabetes, obesity and insulin resistance are independent risk factors for tumorigenesis. Numerous CTRPs, including CTRP3, CTRP4, CTRP6 and CTRP8, have been reported to be associated with tumor progression by activating multiple signal pathways. CTRPs could therefore be considered as diagnostic markers and therapeutic targets in some cancers. However, the underlying mechanisms of CTRPs in tumorigenesis remain unknown. The present review aimed to determine the roles and underlying mechanisms of CTRPs in tumorigenesis, which may help the development of novel cancer treatments in the future.

Towards More Predictive, Physiological and Animal-free In Vitro Models: Advances in Cell and Tissue Culture 2020 Conference Proceedings

Experimental systems that faithfully replicate human physiology at cellular, tissue and organ level are crucial to the development of efficacious and safe therapies with high success rates and low cost. The development of such systems is challenging and requires skills, expertise and inputs from a diverse range of experts, such as biologists, physicists, engineers, clinicians and regulatory bodies. Kirkstall Limited, a biotechnology company based in York, UK, organised the annual conference, Advances in Cell and Tissue Culture (ACTC), which brought together people having a variety of expertise and interests, to present and discuss the latest developments in the field of cell and tissue culture and in vitro modelling. The conference has also been influential in engaging animal welfare organisations in the promotion of research, collaborative projects and funding opportunities. This report describes the proceedings of the latest ACTC conference, which was held virtually on 30th September and 1st October 2020, and included sessions on in vitro models in the following areas: advanced skin and respiratory models, neurological disease, cancer research, advanced models including 3-D, fluid flow and co-cultures, diabetes and other age-related disorders, and animal-free research. The roundtable session on the second day was very interactive and drew huge interest, with intriguing discussion taking place among all participants on the theme of replacement of animal models of disease.

Meta-Analysis of Microdissected Breast Tumors Reveals Genes Regulated in the Stroma but Hidden in Bulk Analysis

Transcriptome data provide a valuable resource for the study of cancer molecular mechanisms, but technical biases, sample heterogeneity, and small sample sizes result in poorly reproducible lists of regulated genes. Additionally, the presence of multiple cellular components contributing to cancer development complicates the interpretation of bulk transcriptomic profiles. To address these issues, we collected 48 microarray datasets derived from laser capture microdissected stroma or epithelium in breast tumors and performed a meta-analysis identifying robust lists of differentially expressed genes. This was used to create a database with carefully harmonized metadata that we make freely available to the research community. As predicted, combining the results of multiple datasets improved statistical power. Moreover, the separate analysis of stroma and epithelium allowed the identification of genes with different contributions in each compartment, which would not be detected by bulk analysis due to their distinct regulation in the two compartments. Our method can be profitably used to help in the discovery of biomarkers and the identification of functionally relevant genes in both the stroma and the epithelium. This database was made to be readily accessible through a user-friendly web interface.

Metabolic Reprogramming: A Friend or Foe to Cancer Therapy?

Drug resistance is a major cause of cancer treatment failure, effectively driven by processes that promote escape from therapy-induced cell death. The mechanisms driving evasion of apoptosis have been widely studied across multiple cancer types, and have facilitated new and exciting therapeutic discoveries with the potential to improve cancer patient care. However, an increasing understanding of the crosstalk between cancer hallmarks has highlighted the complexity of the mechanisms of drug resistance, co-opting pathways outside of the canonical "cell death" machinery to facilitate cell survival in the face of cytotoxic stress. Rewiring of cellular metabolism is vital to drive and support increased proliferative demands in cancer cells, and recent discoveries in the field of cancer metabolism have uncovered a novel role for these programs in facilitating drug resistance. As a key organelle in both metabolic and apoptotic homeostasis, the mitochondria are at the forefront of these mechanisms of resistance, coordinating crosstalk in the event of cellular stress, and promoting cellular survival. Importantly, the appreciation of this role metabolism plays in the cytotoxic response to therapy, and the ability to profile metabolic adaptions in response to treatment, has encouraged new avenues of investigation into the potential of exploiting metabolic addictions to improve therapeutic efficacy and overcome drug resistance in cancer. Here, we review the role cancer metabolism can play in mediating drug resistance, and the exciting opportunities presented by imposed metabolic vulnerabilities.

Obese Adipose Tissue as a Driver of Breast Cancer Growth and Development: Update and Emerging Evidence

Obesity is an established risk factor for breast cancer growth and progression. A number of advances have been made in recent years revealing new insights into this link. Early events in breast cancer development involve the neoplastic transformation of breast epithelial cells to cancer cells. In obesity, breast adipose tissue undergoes significant hormonal and inflammatory changes that create a mitogenic microenvironment. Many factors that are produced in obesity have also been shown to promote tumorigenesis. Given that breast epithelial cells are surrounded by adipose tissue, the crosstalk between the adipose compartment and breast epithelial cells is hypothesized to be a significant player in the initiation and progression of breast cancer in individuals with excess adiposity. The present review examines this crosstalk with a focus on obese breast adipose-derived estrogen, inflammatory mediators and adipokines, and how they are mechanistically linked to breast cancer risk and growth through stimulation of oxidative stress, DNA damage, and pro-oncogenic transcriptional programs. Pharmacological and lifestyle strategies targeting these factors and their downstream effects are evaluated for feasibility and efficacy in decreasing the risk of obesity-induced breast epithelial cell transformation and consequently, breast cancer development.