Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression

Integration of pan-omics technologies and three-dimensional in vitro tumor models: an approach toward drug discovery and precision medicine

Despite advancements in treatment protocols, cancer is one of the leading cause of deaths worldwide. Therefore, there is a need to identify newer and personalized therapeutic targets along with screening technologies to combat cancer. With the advent of pan-omics technologies, such as genomics, transcriptomics, proteomics, metabolomics, and lipidomics, the scientific community has witnessed an improved molecular and metabolomic understanding of various diseases, including cancer. In addition, three-dimensional (3-D) disease models have been efficiently utilized for understanding disease pathophysiology and as screening tools in drug discovery. An integrated approach utilizing pan-omics technologies and 3-D in vitro tumor models has led to improved understanding of the intricate network encompassing various signalling pathways and molecular cross-talk in solid tumors. In the present review, we underscore the current trends in omics technologies and highlight their role in understanding genotypic-phenotypic co-relation in cancer with respect to 3-D in vitro tumor models. We further discuss the challenges associated with omics technologies and provide our outlook on the future applications of these technologies in drug discovery and precision medicine for improved management of cancer.

Mapping Spatiotemporal Heterogeneity in Multifocal Breast Tumor Progression by Noninvasive Ultrasound Elastography-Guided Mass Spectrometry Imaging Strategy

Spatiotemporal heterogeneity of tumors provides an escape mechanism for breast cancer cells, which can obstruct the investigation of tumor progression. While molecular profiling obtained from mass spectrometry imaging (MSI) is rich in biochemical information, it lacks the capacity for in vivo analysis. Ultrasound diagnosis has a high diagnostic accuracy but low chemical specificity. Here, we describe a noninvasive ultrasound elastography (UE)-guided MSI strategy (UEg-MSI) that integrates physical and biochemical characteristics of tumors acquired from both in vivo and in vitro imaging. Using UEg-MSI, both elasticity histopathology metabolism "fingerprints" and reciprocal crosstalk are revealed, indicating the intact, multifocal spatiotemporal heterogeneity of spontaneous tumorigenesis of the breast from early, middle, and late stages. Our results demonstrate a gradual increase in malignant degree of primary focus in cervical and thoracic mammary glands. This progression is characterized by increased stiffness according to elasticity scores, histopathological changes from hyperplasia to increased nests of neoplastic cells and necrotic areas, and regional metabolic heterogeneity and reprogramming at the spatiotemporal level. De novo fatty acid (FA) synthesis focused on independent (such as ω-9 FAs) and dependent (such as ω-6 FAs) dietary FA intake in the core cancerous nest areas in the middle and late stages of tumor or in the peripheral microareas in the early stage of the tumor. SM-Cer signaling pathway and GPs biosynthesis and degradation, as well as glycerophosphoinositol intensity, changed in multiple characteristic microareas. The UEg-MSI strategy holds the potential to expand MSI applications and enhance ultrasound-mediated cancer diagnosis. It offers new insight into early cancer discovery and the occurrence of metastasis.

Liquid chromatography-mass spectrometry-based metabolomics and fluxomics reveals the metabolic alterations in glioma U87MG multicellular tumor spheroids versus two-dimensional cell cultures

RATIONALE

Multicellular tumor spheroids (MCTSs) that reconstitute the metabolic characteristics of in vivo tumor tissue may facilitate the discovery of molecular biomarkers and effective anticancer therapies. However, little is known about how cancer cells adapt their metabolic changes in complex three-dimensional (3D) microenvironments. Here, using the two-dimensional (2D) cell model as control, the metabolic phenotypes of glioma U87MG multicellular tumor spheroids were systematically investigated based on static metabolomics and dynamic fluxomics analysis.

METHODS

A liquid chromatography-mass spectrometry-based global metabolomics and lipidomics approach was adopted to survey the cellular samples from 2D and 3D culture systems, revealing marked molecular differences between them. Then, by means of metabolomic pathway analysis, the metabolic pathways altered in glioma MCTSs were found using 13 C6 -glucose as a tracer to map the metabolic flux of glycolysis, the tricarboxylic acid (TCA) cycle, de novo nucleotide synthesis, and de novo lipid biosynthesis in the MCTS model.

RESULTS

We found nine metabolic pathways as well as glycerolipid, glycerophospholipid and sphingolipid metabolism to be predominantly altered in glioma MCTSs. The reduced nucleotide metabolism, amino acid metabolism and glutathione metabolism indicated an overall lower cellular activity in MCTSs. Through dynamic fluxomics analysis in the MCTS model, we found that cells cultured in MCTSs exhibited increased glycolysis activity and de novo lipid biosynthesis activity, and decreased the TCA cycle and de novo purine nucleotide biosynthesis activity.

CONCLUSIONS

Our study highlights specific, altered biochemical pathways in MCTSs, emphasizing dysregulation of energy metabolism and lipid metabolism, and offering novel insight into metabolic events in glioma MCTSs.

The combination of the low immunohistochemical expression of peroxiredoxin 4 and perilipin 2 predicts longer survival in pancreatic ductal adenocarcinoma with peroxiredoxin 4 possibly playing a main role

Pancreatic ductal adenocarcinoma (PDAC) is a fatal disease with poor prognosis. Therefore, indicators that can be used for the early prediction of the prognosis of PDAC are needed. Peroxiredoxin (PRDX) 4 is a secretion-type antioxidant enzyme located in the cytoplasmic endoplasmic reticulum. Recent studies have reported that it is closely related to the development and prognosis of many types of cancer. Perilipin (PLIN) 2 is a lipid droplet coating protein. The high expression of PLIN2 is known to be an indicator of some types of cancer and oxidative stress management. It is highly suggestive of the interplay between PRDX4 and PLIN2 to some degree. In this study, we collected 101 patients' clinical data and paraffin-embedded specimens with PDAC and analyzed them with immunohistochemical staining of PRDX4 and PLIN2. We found that the low expression of PRDX4 predicts longer survival and a better clinical condition in PDAC patients. Moreover, when the low expression of PRDX4 is combined with the low expression of PLIN2, the 3-year survival is significantly improved. Univariate and multivariate Cox proportional hazard analyses showed that the PRDX4 expression in PDAC was an independent prognostic factor for survival. Taken together, between PRDX4 and PLIN2, PRDX4 plays a main role in prognosis and has the potential to become a clinical prognostic indicator of PDAC.

Spatial -omics technologies: the new enterprise in 3D breast cancer models

The fields of tissue bioengineering, -omics, and spatial biology are advancing rapidly, each offering the opportunity for a paradigm shift in breast cancer research. However, to date, collaboration between these fields has not reached its full potential. In this review, we describe the most recently generated 3D breast cancer models regarding the biomaterials and technological platforms employed. Additionally, their biological evaluation is reported, highlighting their advantages and limitations. Specifically, we focus on the most up-to-date -omics and spatial biology techniques, which can generate a deeper understanding of the biological relevance of bioengineered 3D breast cancer in vitro models, thus paving the way towards truly clinically relevant microphysiological systems, improved drug development success rates, and personalised medicine approaches.

Multicellular spheroids containing synthetic mineral particles: an advanced 3D tumor model system to investigate breast precancer malignancy potential according to the mineral type

Mineral particles that form in soft tissues in association with disease conditions are heterogeneous in their composition and physiochemical properties. Hence, it is challenging to study the effect of mineral type on disease progression in a high-throughput and realistic manner. For example, most early breast precancer lesions, termed ductal carcinoma in situ (DCIS), contain microcalcifications (MCs), calcium-containing pathological minerals. The most common type of MCs is calcium phosphate crystals, mainly carbonated apatite; it is associated with either benign or malignant lesions. In vitro studies indicate that the crystal properties of apatite MCs can affect breast cancer progression. A less common type of MCs is calcium oxalate dihydrate (COD), which is almost always found in benign lesions. We developed a 3D tumor model of multicellular spheroids of human precancer cells containing synthetic MC analogs that link the crystal properties of MCs with the progression of breast precancer to invasive cancer. Using this 3D model, we show that apatite crystals induce Her2 overexpression in DCIS cells. This tumor-triggering effect is increased when the carbonate fraction in the MCs decreases. COD crystals, in contrast, decrease Her2 expression in the spheroids, even compared with a control group with no added MC analogs. Furthermore, COD decreases cell proliferation and migration in DCIS monolayers compared to untreated cells and cells incubated with apatite crystals. This finding suggests that COD is not randomly located only in benign lesions-it may actively contribute to suppressing precancer progression in its surroundings. Our model provides an easy-to-manipulate platform to better understand the interactions between mineral particles and their biological microenvironment. A better understanding of the effect of the crystal properties of MCs on precancer progression will potentially provide new directions for better precancer prognosis and treatment.

DISC-3D: dual-hydrogel system enhances optical imaging and enables correlative mass spectrometry imaging of invading multicellular tumor spheroids

Multicellular tumor spheroids embedded in collagen I matrices are common in vitro systems for the study of solid tumors that reflect the physiological environment and complexities of the in vivo environment. While collagen I environments are physiologically relevant and permissive of cell invasion, studying spheroids in such hydrogels presents challenges to key analytical assays and to a wide array of imaging modalities. While this is largely due to the thickness of the 3D hydrogels that in other samples can typically be overcome by sectioning, because of their highly porous nature, collagen I hydrogels are very challenging to section, especially in a manner that preserves the hydrogel network including cell invasion patterns. Here, we describe a novel method for preparing and cryosectioning invasive spheroids in a two-component (collagen I and gelatin) matrix, a technique we term dual-hydrogel in vitro spheroid cryosectioning of three-dimensional samples (DISC-3D). DISC-3D does not require cell fixation, preserves the architecture of invasive spheroids and their surroundings, eliminates imaging challenges, and allows for use of techniques that have infrequently been applied in three-dimensional spheroid analysis, including super-resolution microscopy and mass spectrometry imaging.

Development of fish liver PLHC-1 spheroids and its applicability to investigate the toxicity of plastic additives

Fish liver cell lines are valuable tools to understand the toxicity of chemicals in aquatic vertebrates. While conventional 2D cell cultures grown in monolayers are well established, they fail to emulate toxic gradients and cellular functions as in in-vivo conditions. To overcome these limitations, this work focuses on the development of Poeciliopsis lucida (PLHC-1) spheroids as a testing platform to evaluate the toxicity of a mixture of plastic additives. The growth of spheroids was monitored over a period of 30 days, and spheroids 2-8 days old and sized between 150 and 250 µm were considered optimal for conducting toxicity tests due to their excellent viability and metabolic activity. Eight-day-old spheroids were selected for lipidomic characterization. Compared to 2D-cells, the lipidome of spheroids was relatively enriched in highly unsaturated phosphatidylcholines (PCs), sphingosines (SPBs), sphingomyelins (SMs) and cholesterol esters (CEs). When exposed to a mixture of plastic additives, spheroids were less responsive in terms of decreased cell viability and generation of reactive oxygen species (ROS), but were more sensitive than cells growing in monolayers for lipidomic responses. The lipid profile of 3D-spheroids was similar to a liver-like phenotype and it was strongly modulated by exposure to plastic additives. The development of PLHC-1 spheroids represents an important step towards the application of more realistic in-vitro methods in aquatic toxicity studies.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Characterization of the Metabolome of Breast Tissues from Non-Hispanic Black and Non-Hispanic White Women Reveals Correlations between Microbial Dysbiosis and Enhanced Lipid Metabolism Pathways in Triple-Negative Breast Tumors

Simple Summary

We previously showed that breast tumor tissues from women display an imbalance in abundance and composition of microbiota compared to normal healthy breast tissues. It is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The aim of our study was to conduct global metabolic profiling on normal and breast tumor tissues to identify differences in metabolite profiles and to determine whether breast microbial dysbiosis may be associated with enrichment of microbial metabolites in triple-negative breast cancer (TNBC) which disproportionately affects women of African ancestry. We observed significant correlations between elevated lipid metabolism pathways and microbial dysbiosis in TNBC tissues from both non-Hispanic black and white women. This is the first study to report an association between breast microbial dysbiosis and alterations in host metabolic pathways in breast tumors, including TNBC, of non-Hispanic black and non-Hispanic white women.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer that is non-responsive to hormonal therapies and disproportionately impact women of African ancestry. We previously showed that TN breast tumors have a distinct microbial signature that differs from less aggressive breast tumor subtypes and normal breast tissues. However, it is unknown whether these differences in breast tumor microbiota may be driven by alterations in microbial metabolites, leading to potentially protective or pathogenic consequences. The goal of this global metabolomic profiling study was to investigate alterations in microbial metabolism pathways in normal and breast tumor tissues, including TNBC, of non-Hispanic black (NHB) and non-Hispanic white (NHW) women. In this study, we profiled the microbiome (16S rRNA) from breast tumor tissues and analyzed 984 metabolites from a total of 51 NHB and NHW women. Breast tumor tissues were collected from 15 patients with TNBC, 12 patients with less aggressive luminal A-type (Luminal) breast cancer, and 24 healthy controls for comparison using UHPLC-tandem mass spectrometry. Principal component analysis and hierarchical clustering of the global metabolomic profiling data revealed separation between metabolic signatures of normal and breast tumor tissues. Random forest analysis revealed a unique biochemical signature associated with elevated lipid metabolites and lower levels of microbial-derived metabolites important in controlling inflammation and immune responses in breast tumor tissues. Significant relationships between the breast microbiome and the metabolome, particularly lipid metabolism, were observed in TNBC tissues. Further investigations to determine whether alterations in sphingolipid, phospholipid, ceramide, amino acid, and energy metabolism pathways modulate Fusobacterium and Tenericutes abundance and composition to alter host metabolism in TNBC are necessary to help us understand the risk and underlying mechanisms and to identify potential microbial-based targets.

Lipidomic comparison of 2D and 3D colon cancer cell culture models

Altered lipid metabolism is one of the hallmarks of cancer. Cellular proliferation and de novo synthesis of lipids are related to cancer progression. In this study, we evaluated the lipidomic profile of two-dimensional (2D) monolayer and multicellular tumor spheroids from the HCT 116 colon carcinoma cell line. We utilized serial trypsinization on the spheroid samples to generate three cellular populations representing the proliferative, quiescent, and necrotic regions of the spheroid. This analysis enabled a comprehensive identification and quantification of lipids produced in each of the spheroid layer and 2D cultures. We show that lipid subclasses associated with lipid droplets form in oxygen-restricted and acidic regions of spheroids and are produced at higher levels than in 2D cultures. Additionally, sphingolipid production, which is implicated in cell death and survival pathways, is higher in spheroids relative to 2D cells. Finally, we show that increased numbers of lipids composed of polyunsaturated fatty acids (PUFAs) are produced in the quiescent and necrotic regions of the spheroid. The lipidomic signature for each region and cell culture type highlights the importance of understanding the spatial aspects of cancer biology. These results provide additional lipid biomarkers in colon cancer cells that can be further studied to target pivotal lipid production pathways.

Lipid droplets and perilipins in canine osteosarcoma. Investigations on tumor tissue, 2D and 3D cell culture models

Lipid droplets were identified as important players in biological processes of various tumor types. With emphasis on lipid droplet-coating proteins (perilipins, PLINs), this study intended to shed light on the presence and formation of lipid droplets in canine osteosarcoma. For this purpose, canine osteosarcoma tissue samples (n = 11) were analyzed via immunohistochemistry and electron microscopy for lipid droplets and lipid droplet-coating proteins (PLINs). Additionally, we used the canine osteosarcoma cell lines D-17 and COS4288 in 2D monolayer and 3D spheroid (cultivated for 7, 14, and 21 days) in vitro models, and further analyzed the samples by means of histochemistry, immunofluorescence, molecular biological techniques (RT-qPCR, Western Blot) and electron microscopical imaging. Lipid droplets, PLIN2, and PLIN3 were detected in osteosarcoma tissue samples as well as in 2D and 3D cultivated D-17 and COS4288 cells. In spheroids, specific distribution patterns of lipid droplets and perilipins were identified, taking into consideration cell line specific zonal apportionment. Upon external lipid supplementation (oleic acid), a rise of lipid droplet amount accompanied with an increase of PLIN2 expression was observed. Detailed electron microscopical analyzes revealed that lipid droplet sizes in tumor tissue were comparable to that of 3D spheroid models. Moreover, the biggest lipid droplets were found in the central zone of the spheroids at all sampling time-points, reaching their maximum size at 21 days. Thus, the 3D spheroids can be considered as a relevant in vitro model for further studies focusing on lipid droplets biology and function in osteosarcoma.

Surface cholesterol-enriched domains specifically promote invasion of breast cancer cell lines by controlling invadopodia and extracellular matrix degradation

Tumor cells exhibit altered cholesterol content. However, cholesterol structural subcellular distribution and implication in cancer cell invasion are poorly understood mainly due to difficulties to investigate cholesterol both quantitatively and qualitatively and to compare isogenic cell models. Here, using the MCF10A cell line series (non-tumorigenic MCF10A, pre-malignant MCF10AT and malignant MCF10CAIa cells) as a model of breast cancer progression and the highly invasive MDA-MB-231 cell line which exhibits the common TP53 mutation, we investigated if cholesterol contributes to cancer cell invasion, whether the effects are specific to cancer cells and the underlying mechanism. We found that partial membrane cholesterol depletion specifically and reversibly decreased invasion of the malignant cell lines. Those cells exhibited dorsal surface cholesterol-enriched submicrometric domains and narrow ER-plasma membrane and ER-intracellular organelles contact sites. Dorsal cholesterol-enriched domains can be endocytosed and reach the cell ventral face where they were involved in invadopodia formation and extracellular matrix degradation. In contrast, non-malignant cells showed low cell invasion, low surface cholesterol exposure and cholesterol-dependent focal adhesions. The differential cholesterol distribution and role in breast cancer cell invasion provide new clues for the understanding of the molecular events underlying cellular mechanisms in breast cancer.

Advances in Analyzing the Breast Cancer Lipidome and Its Relevance to Disease Progression and Treatment

Abnormal lipid metabolism is common in breast cancer with the three main subtypes, hormone receptor (HR) positive, human epidermal growth factor 2 (HER2) positive, and triple negative, showing common and distinct lipid dependencies. A growing body of studies identify altered lipid metabolism as impacting breast cancer cell growth and survival, plasticity, drug resistance, and metastasis. Lipids are a class of nonpolar or polar (amphipathic) biomolecules that can be produced in cells via de novo synthesis or acquired from the microenvironment. The three main functions of cellular lipids are as essential components of membranes, signaling molecules, and nutrient storage. The use of mass spectrometry-based lipidomics to analyze the global cellular lipidome has become more prevalent in breast cancer research. In this review, we discuss current lipidomic methodologies, highlight recent breast cancer lipidomic studies and how these findings connect to disease progression and therapeutic development, and the potential use of lipidomics as a diagnostic tool in breast cancer. A better understanding of the breast cancer lipidome and how it changes during drug resistance and tumor progression will allow informed development of diagnostics and novel targeted therapies.

STAT3 as a mediator of oncogenic cellular metabolism: Pathogenic and therapeutic implications

The oncogenic transcription factor signal transducer and activator of transcription 3 (STAT3) is activated constitutively in a wide array of human cancers. It is an appealing molecular target for novel therapy as it directly regulates expression of genes involved in cell proliferation, survival, angiogenesis, chemoresistance and immune responsiveness. In addition to these well-established oncogenic roles, STAT3 has also been found to mediate a wide array of functions in modulating cellular behavior. The transcriptional function of STAT3 is canonically regulated through tyrosine phosphorylation. However, STAT3 phosphorylated at a single serine residue can allow incorporation of this protein into the inner mitochondrial membrane to support oxidative phosphorylation (OXPHOS) and maximize the utility of glucose sources. Conflictingly, its canonical transcriptional activity suppresses OXPHOS and favors aerobic glycolysis to promote oncogenic behavior. Apart from mediating the energy metabolism and controversial effects on ATP production, STAT3 signaling modulates lipid metabolism of cancer cells. By mediating fatty acid synthesis and beta oxidation, STAT3 promotes employment of available resources and supports survival in the conditions of metabolic stress. Thus, the functions of STAT3 extend beyond regulation of oncogenic genes expression to pleiotropic effects on a spectrum of essential cellular processes. In this review, we dissect the current knowledge on activity and mechanisms of STAT3 involvement in transcriptional regulation, mitochondrial function, energy production and lipid metabolism of malignant cells, and its implications to cancer pathogenesis and therapy.

Mass spectrometry imaging revealed alterations of lipid metabolites in multicellular tumor spheroids in response to hydroxychloroquine

Three-dimensional (3D) multicellular tumor spheroids (MCTS) that mimic the complex tumor microenvironment provide a good platform for in vitro study of drug and endogenous metabolites. Hydroxychloroquine (HCQ) has shown anti-tumor activity in a variety of tumor models. However, the effect of the drug on the alteration of lipid metabolism spatial composition and distribution in the MCTS model is not clear. Herein, we utilized matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) in the analysis of A549 lung cancer multicellular spheroids to investigate the in situ spatial distribution of HCQ and its effect on lipid metabolism. We have successfully observed the spatial variations of HCQ in the inner region of the spheroid at different drug-treated time points. The MSI results also demonstrated that HCQ treatment altered the spatial composition of lipids in the inner and outer regions of treated spheroids. Furthermore, the lipidomic results showed that the identified phosphatidylcholines (PC), lysophosphatidylcholines (LPC), phosphatidylethanolamines (PE), lysophosphatidylethanolamines (LPE), phosphatidylinositols (PI), ceramides (Cer), glucosylceramides (CerG), and diglycerides (DG) were significantly up-regulated, and phosphatidylglycerol (PG) and triglycerides (TG) were remarkable down-regulated. MSI method combined with LC-MS/MS profiling of endogenous metabolites can obtain more detailed information about how spheroids respond to drug and spatial distribution information, thus fostering a better understanding of the relationship between drug-altered lipid metabolism and cancer microenvironment.

Nanocomposite Scaffolds for Monitoring of Drug Diffusion in Three-Dimensional Cell Environments by Surface-Enhanced Raman Spectroscopy

Monitoring dynamic processes in complex cellular environments requires the integration of uniformly distributed detectors within such three-dimensional (3D) networks, to an extent that the sensor could provide real-time information on nearby perturbations in a non-invasive manner. In this context, the development of 3D-printed structures that can function as both sensors and cell culture platforms emerges as a promising strategy, not only for mimicking a specific cell niche but also toward identifying its characteristic physicochemical conditions, such as concentration gradients. We present herein a 3D cancer model that incorporates a hydrogel-based scaffold containing gold nanorods. In addition to sustaining cell growth, the printed nanocomposite inks display the ability to uncover drug diffusion profiles by surface-enhanced Raman scattering, with high spatiotemporal resolution. We additionally demonstrate that the acquired information could pave the way to designing novel strategies for drug discovery in cancer therapy, through correlation of drug diffusion with cell death.

[Mass spectrometry imaging technology and its application in breast cancer research]

乳腺癌是女性最常见的恶性肿瘤,其发病率在世界范围内呈现上升趋势,是威胁女性健康的重要疾病之一。随着现代医学技术的快速发展,早期有效的诊断和筛查方法能够改善乳腺癌患者生存率和提高其生活质量。由于乳腺癌肿瘤具有非常显著的异质性,这对于诊断和筛查带来了较大困难,亟须在肿瘤演进时间信息中,继续引入生物分子的空间信息,从而对其异质性、肿瘤微环境等进行准确的追踪。质谱成像技术,可在免标记的前提下利用离子质荷比的特性发现生物组织中的各种分子,并研究这些分子的时间和空间信息,对其进行准确的定性、定量和空间定位。目前,通过质谱成像技术可直接获取药物及其代谢物、内源性代谢物、脂质、多肽和蛋白质等在组织中的空间分布信息,为肿瘤分子分型诊断和确认以及相关抗肿瘤药物的筛选提供了新的思路和研究方向。该综述以乳腺癌相关的生物样品制备和研究进展为主要内容,从小分子样本、大分子样本、石蜡包埋样本、基质喷涂方式、常用离子源等方面阐述质谱成像中样本制备的重要性以及样品制备过程中存在的难点问题。同时,以细胞模型、动物模型和临床肿瘤标本为研究对象,汇总了质谱成像技术在乳腺癌方面的应用进展,并进行了展望,为开展癌症精准分型研究和药物药效的快速筛查提供了重要依据。

Phasor S-FLIM: a new paradigm for fast and robust spectral fluorescence lifetime imaging

Fluorescence lifetime imaging microscopy (FLIM) and spectral imaging are two broadly applied methods for increasing dimensionality in microscopy. However, their combination is typically inefficient and slow in terms of acquisition and processing. By integrating technological and computational advances, we developed a robust and unbiased spectral FLIM (S-FLIM) system. Our method, Phasor S-FLIM, combines true parallel multichannel digital frequency domain electronics with a multidimensional phasor approach to extract detailed and precise information about the photophysics of fluorescent specimens at optical resolution. To show the flexibility of the Phasor S-FLIM technology and its applications to the biological and biomedical field, we address four common, yet challenging, problems: the blind unmixing of spectral and lifetime signatures from multiple unknown species, the unbiased bleedthrough- and background-free Förster resonance energy transfer analysis of biosensors, the photophysical characterization of environment-sensitive probes in living cells and parallel four-color FLIM imaging in tumor spheroids.

Three dimensional engineered models to study hypoxia biology in breast cancer

Breast cancer is the second leading cause of mortality among women worldwide. Despite the available therapeutic regimes, variable treatment response is reported among different breast cancer subtypes. Recently, the effects of the tumor microenvironment on tumor progression as well as treatment responses have been widely recognized. Hypoxia and hypoxia inducible factors in the tumor microenvironment have long been known as major players in tumor progression and survival. However, the majority of our understanding of hypoxia biology has been derived from two dimensional (2D) models. Although many hypoxia-targeted therapies have elicited promising results in vitro and in vivo, these results have not been successfully translated into clinical trials. These limitations of 2D models underscore the need to develop and integrate three dimensional (3D) models that recapitulate the complex tumor-stroma interactions in vivo. This review summarizes role of hypoxia in various hallmarks of cancer progression. We then compare traditional 2D experimental systems with novel 3D tissue-engineered models giving accounts of different bioengineering platforms available to develop 3D models and how these 3D models are being exploited to understand the role of hypoxia in breast cancer progression.

Tumorigenesis-related key genes in adolescents and young adults with HR(+)/HER2(-) breast cancer

Breast cancer (BC) in adolescents and young adults (AYAs) accounts for 5.6% of BC in all women. BC in this population is often characterized as aggressive. Two-thirds of BC in AYAs belong to the hormone-receptor positive (HR(+))/human epidermal growth factor receptor 2 negative (HER2(-)) subtype. However, the underlying pathogenesis of this subtype has not been fully elucidated. To study HR(+)/HER2(-) BC in AYAs, we downloaded the available RNA-seq data from The Cancer Genome Atlas (TCGA) database and then performed differential expression gene screening and constructed a protein-protein interaction (PPI) network, identified the key genes, and did gene set enrichment analysis (GSEA). Based on the analyses, 32.26% of patients were in stage III. Additionally, we identified 1671 differentially expressed genes (DEGs) and 35 key genes. In addition, GSEA showed that ether lipid metabolism and complement and coagulation cascades were significantly enriched in the GNAI1 high expression phenotype. The key genes CXCL2, CXCL5, CXCL3, GPR37L1, NPY2R, OXGR1, NPW, CCL21, GNAI1, SAA1, GRM4, HCAR2, CX3CL1, GRM8, CCL28, SSTR1, PENK, P2RY12, NMUR1, NMU, ADCY5, TAS1R1, OXER1, GNG13, CCL16, CCR8, NPY5R, CXCL11, CXCL10, CXCL9, CXCL1, CXCL6, CCR4, and ANXA1 may be molecular markers of tumorigenesis of HR(+)/HER2(-) BC in AYAs. In addition, ether lipid metabolism and complement and coagulation cascades may be key pathways for GNAI1 regulation in HR(+)/HER2(-) BC in AYAs.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

Evaluation of Melanoma (SK-MEL-2) Cell Growth between Three-Dimensional (3D) and Two-Dimensional (2D) Cell Cultures with Fourier Transform Infrared (FTIR) Microspectroscopy

Fourier transform infrared (FTIR) microspectroscopy was used to evaluate the growth of human melanoma cells (SK-MEL-2) in two-dimensional (2D) versus three-dimensional (3D) spheroid culture systems. FTIR microspectroscopy, coupled with multivariate analysis, could be used to monitor the variability of spheroid morphologies prepared from different cell densities. The characteristic shift in absorbance bands of the 2D cells were different from the spectra of cells from 3D spheroids. FTIR microspectroscopy can also be used to monitor cell death similar to fluorescence cell staining in 3D spheroids. A change in the secondary structure of protein was observed in cells from the 3D spheroid versus the 2D culture system. FTIR microspectroscopy can detect specific alterations in the biological components inside the spheroid, which cannot be detected using fluorescence cell death staining. In the cells from 3D spheroids, the respective lipid, DNA, and RNA region content represent specific markers directly proportional to the spheroid size and central area of necrotic cell death, which can be confirmed using unsupervised PCA and hierarchical cluster analysis. FTIR microspectroscopy could be used as an alternative tool for spheroid cell culture discrimination, and validation of the usual biochemical technique.

Environmental lipidomics: understanding the response of organisms and ecosystems to a changing world

BACKGROUND

Understanding the interaction between organisms and the environment is important for predicting and mitigating the effects of global phenomena such as climate change, and the fate, transport, and health effects of anthropogenic pollutants. By understanding organism and ecosystem responses to environmental stressors at the molecular level, mechanisms of toxicity and adaptation can be determined. This information has important implications in human and environmental health, engineering biotechnologies, and understanding the interaction between anthropogenic induced changes and the biosphere. One class of molecules with unique promise for environmental science are lipids; lipids are highly abundant and ubiquitous across nearly all organisms, and lipid profiles often change drastically in response to external stimuli. These changes allow organisms to maintain essential biological functions, for example, membrane fluidity, as they adapt to a changing climate and chemical environment. Lipidomics can help scientists understand the historical and present biofeedback processes in climate change and the biogeochemical processes affecting nutrient cycles. Lipids can also be used to understand how ecosystems respond to historical environmental changes with lipid signatures dating back to hundreds of millions of years, which can help predict similar changes in the future. In addition, lipids are direct targets of environmental stressors, for example, lipids are easily prone to oxidative damage, which occurs during exposure to most toxins.

AIM OF REVIEW

This is the first review to summarize the current efforts to comprehensively measure lipids to better understand the interaction between organisms and their environment. This review focuses on lipidomic applications in the arenas of environmental toxicology and exposure assessment, xenobiotic exposures and health (e.g., obesity), global climate change, and nutrient cycles. Moreover, this review summarizes the use of and the potential for lipidomics in engineering biotechnologies for the remediation of persistent compounds and biofuel production.

KEY SCIENTIFIC CONCEPT

With the preservation of certain lipids across millions of years and our ever-increasing understanding of their diverse biological roles, lipidomic-based approaches provide a unique utility to increase our understanding of the contemporary and historical interactions between organisms, ecosystems, and anthropogenically-induced environmental changes.

Lipidomic study of cell lines reveals differences between breast cancer subtypes

Breast cancer (BC) is the most prevalent type of cancer in women in western countries. BC mortality has not declined despite early detection by screening, indicating the need for better informed treatment decisions. Therefore, a novel noninvasive diagnostic tool for BC would give the opportunity of subtype-specific treatment and improved prospects for the patients. Heterogeneity of BC tumor subtypes is reflected in the expression levels of enzymes in lipid metabolism. The aim of the study was to investigate whether the subtype defined by the transcriptome is reflected in the lipidome of BC cell lines. A liquid chromatography mass spectrometry (LC-MS) platform was applied to analyze the lipidome of six cell lines derived from human BC cell lines representing different BC subtypes. We identified an increased abundance of triacylglycerols (TG) ≥ C-48 with moderate or multiple unsaturation in fatty acyl chains and down-regulated ether-phosphatidylethanolamines (PE) (C-34 to C-38) in cell lines representing estrogen receptor and progesterone receptor positive tumor subtypes. In a cell line representing HER2-overexpressing tumor subtype an elevated expression of TG (≤ C-46), phosphatidylcholines (PC) and PE containing short-chained (≤ C-16) saturated or monounsaturated fatty acids were observed. Increased abundance of PC ≥ C-40 was found in cell lines of triple negative BC subtype. In addition, differences were detected in lipidomes within these previously defined subtypes. We conclude that subtypes defined by the transcriptome are indeed reflected in differences in the lipidome and, furthermore, potentially biologically relevant differences may exist within these defined subtypes.

Mass spectrometry imaging of endogenous metabolites in response to doxorubicin in a novel 3D osteosarcoma cell culture model

Three-dimensional (3D) cell culture is a rapidly emerging field, which mimics some of the physiological conditions of human tissues. In cancer biology, it is considered a useful tool in predicting in vivo chemotherapy responses, compared with conventional two-dimensional (2D) cell culture. We have developed a novel 3D cell culture model of osteosarcoma composed of aggregated proliferative tumour spheroids, which shows regions of tumour heterogeneity formed by aggregated spheroids of polyclonal tumour cells. Aggregated spheroids show local necrotic and apoptotic regions and have sizes suitable for the study of spatial distribution of metabolites by mass spectrometry imaging (MSI). We have used this model to perform a proof-of-principle study showing a heterogeneous distribution of endogenous metabolites that colocalise with the necrotic core and apoptotic regions in this model. Cytotoxic chemotherapy (doxorubicin) responses were significantly attenuated in our 3D cell culture model compared with those of standard cell culture, as determined by resazurin assay, despite sufficient doxorubicin diffusion demonstrated by localisation throughout the 3D constructs. Finally, changes to the distribution of endogenous metabolites in response to doxorubicin were readily detected by MSI. Principal component analysis identified 50 metabolites which differed most in their abundance between treatment groups, and of these, 10 were identified by both in-software t test and mixed-effects analysis of variance (ANOVA). Subsequent independent MSIs of identified species were consistent with principle component analysis findings. This proof-of-principle study shows for the first time that chemotherapy-induced changes in metabolite abundance and distribution may be determined in 3D cell culture by MSI, highlighting this method as a potentially useful tool in the elucidation of chemotherapy responses as an alternative to in vivo testing.

Developing a Drug Screening Platform: MALDI-Mass Spectrometry Imaging of Paper-Based Cultures

Many potential chemotherapeutics fail to reach patients. One of the key reasons is that compounds are tested during the drug discovery stage in two-dimensional (2D) cell cultures, which are often unable to accurately model in vivo outcomes. Three-dimensional (3D) in vitro tumor models are more predictive of chemotherapeutic effectiveness than 2D cultures, and thus, their implementation during the drug screening stage has the potential to more accurately evaluate compounds earlier, saving both time and money. Paper-based cultures (PBCs) are an emerging 3D culture platform in which cells suspended in Matrigel are seeded into paper scaffolds and cultured to generate a tissue-like environment. In this study, we demonstrate the potential of matrix-assisted laser desorption/ionization-mass spectrometry imaging with PBCs (MALDI-MSI-PBC) as a drug screening platform. This method discriminated regions of the PBCs with and without cells and/or drugs, indicating that coupling PBCs with MALDI-MSI has the potential to develop rapid, large-scale, and parallel mass spectrometric drug screens.

Steroidomics for the Prevention, Assessment, and Management of Cancers: A Systematic Review and Functional Analysis

Steroidomics, an analytical technique for steroid biomarker mining, has received much attention in recent years. This systematic review and functional analysis, following the PRISMA statement, aims to provide a comprehensive review and an appraisal of the developments and fundamental issues in steroid high-throughput analysis, with a focus on cancer research. We also discuss potential pitfalls and proposed recommendations for steroidomics-based clinical research. Forty-five studies met our inclusion criteria, with a focus on 12 types of cancer. Most studies focused on cancer risk prediction, followed by diagnosis, prognosis, and therapy monitoring. Prostate cancer was the most frequently studied cancer. Estradiol, dehydroepiandrosterone, and cortisol were mostly reported and altered in at least four types of cancer. Estrogen and estrogen metabolites were highly reported to associate with women-related cancers. Pathway enrichment analysis revealed that steroidogenesis; androgen and estrogen metabolism; and androstenedione metabolism were significantly altered in cancers. Our findings indicated that estradiol, dehydroepiandrosterone, cortisol, and estrogen metabolites, among others, could be considered oncosteroids. Despite noble achievements, significant shortcomings among the investigated studies were small sample sizes, cross-sectional designs, potential confounding factors, and problematic statistical approaches. More efforts are required to establish standardized procedures regarding study design, analytical procedures, and statistical inference.