Optical Imaging of Glucose Uptake and Mitochondrial Membrane Potential to Characterize Her2 Breast Tumor Metabolic Phenotypes

Optical imaging reveals chemotherapy-induced metabolic reprogramming of residual disease and recurrence

Fewer than 20% of triple-negative breast cancer patients experience long-term responses to mainstay chemotherapy. Resistant tumor subpopulations use alternative metabolic pathways to escape therapy, survive, and eventually recur. Here, we show in vivo, longitudinal metabolic reprogramming in residual disease and recurrence of triple-negative breast cancer xenografts with varying sensitivities to the chemotherapeutic drug paclitaxel. Optical imaging coupled with metabolomics reported an increase in non-glucose-driven mitochondrial metabolism and an increase in intratumoral metabolic heterogeneity during regression and residual disease in resistant MDA-MB-231 tumors. Conversely, sensitive HCC-1806 tumors were primarily reliant on glucose uptake and minimal changes in metabolism or heterogeneity were observed over the tumors' therapeutic life cycles. Further, day-matched resistant HCC-1806 tumors revealed a higher reliance on mitochondrial metabolism and elevated metabolic heterogeneity compared to sensitive HCC-1806 tumors. Together, metabolic flexibility, increased reliance on mitochondrial metabolism, and increased metabolic heterogeneity are defining characteristics of persistent residual disease, features that will inform the appropriate type and timing of therapies.

Portable optical spectroscopic assay for non-destructive measurement of key metabolic parameters on in vitro cancer cells and organotypic fresh tumor slices

To enable non-destructive metabolic characterizations on in vitro cancer cells and organotypic tumor models for therapeutic studies in an easy-to-access way, we report a highly portable optical spectroscopic assay for simultaneous measurement of glucose uptake and mitochondrial function on various cancer models with high sensitivity. Well-established breast cancer cell lines (MCF-7 and MDA-MB-231) were used to validate the optical spectroscopic assay for metabolic characterizations, while fresh tumor samples harvested from both animals and human cancer patients were used to test the feasibility of our optical metabolic assay for non-destructive measurement of key metabolic parameters on organotypic tumor slices. Our optical metabolic assay captured that MCF-7 cells had higher mitochondrial metabolism, but lower glucose uptake compared to the MDA-MB-231 cells, which is consistent with our microscopy imaging and flow cytometry data, as well as the published Seahorse Assay data. Moreover, we demonstrated that our optical assay could non-destructively measure both glucose uptake and mitochondrial metabolism on the same cancer cell samples at one time, which remains challenging by existing metabolic tools. Our pilot tests on thin fresh tumor slices showed that our optical assay captured increased metabolic activities in tumors compared to normal tissues. Our non-destructive optical metabolic assay provides a cost-effective way for future longitudinal therapeutic studies using patient-derived organotypic fresh tumor slices through the lens of tumor energetics, which will significantly advance translational cancer research.

S100A9 promotes glycolytic activity in HER2-positive breast cancer to induce immunosuppression in the tumour microenvironment

Purpose

The purpose of this study was to investigate the correlation between S100 calcium binding protein A9 (S100A9), tumour glycolysis and tumour infiltrating lymphocytes (TIL) in human epidermal growth factor receptor 2 (HER2) - positive breast cancer (BRCA).

Materials and methods

A total of 667 BRCA patients in Xiangya Hospital of Central South University were enrolled in this study. Haematoxylin and eosin (H&E) staining were used to count TIN in tissues. Human breast cancer cell lines (SK-BR-3 cells and BT474 cells) were transfected with S100A9 specific small interfering RNA (siRNA). The expressions of S100A9, glycolytic enzymes and lymphocyte markers were detected by immunohistochemistry (IHC) staining, Western blot and immunofluorescence. Lactate production, glucose consumption and the extracellular acidification rate (ECAR) were detected to assess glycolysis activity.

Results

S100A9 was significantly overexpressed in HER2+ cases. The expressions of phosphoglycerol kinase 1 (PGK1), lactate dehydrogenase A (LDHA) and enolase α (ENO1) were significantly up-regulated in S100A9 dominant tissues. The expressions of PGK1, LDHA and ENO1 detected in S100A9 silenced cell lines were significantly down-regulated. Moreover, S100A9 silencing significantly altered lactate production, glucose uptake and ECAR levels in HER2+ cell lines. Co-expression of S100A9 and c-Myc was detected in HER2+ tissues. The absence of S100A9 greatly hindered β-catenin expression in cell lines, which later induced the phosphorylation of c-Myc.The amount of TILs in cases with abundant S100A9 and LDHA was much greater than in cases with low S100A9 levels and poorer LDHA. TIL deficiency and elevated S100A9 intensity are factors affecting the survival rate of HER2+ BRCA cases.

Conclusions

S100A9 overexpression upregulated the glycolysis activity of tumour cells through the c-Myc-related pathway, suppressing lymphocyte infiltration in the tumour stroma, affecting the efficacy of immune regulation and long-term survival of patients.

Adaptive Design of Fluorescence Imaging Systems for Custom Resolution, Fields of View, and Geometries

Objective and Impact Statement: We developed a generalized computational approach to design uniform, high-intensity excitation light for low-cost, quantitative fluorescence imaging of in vitro, ex vivo, and in vivo samples with a single device. Introduction: Fluorescence imaging is a ubiquitous tool for biomedical applications. Researchers extensively modify existing systems for tissue imaging, increasing the time and effort needed for translational research and thick tissue imaging. These modifications are application-specific, requiring new designs to scale across sample types. Methods: We implemented a computational model to simulate light propagation from multiple sources. Using a global optimization algorithm and a custom cost function, we determined the spatial positioning of optical fibers to generate 2 illumination profiles. These results were implemented to image core needle biopsies, preclinical mammary tumors, or tumor-derived organoids. Samples were stained with molecular probes and imaged with uniform and nonuniform illumination. Results: Simulation results were faithfully translated to benchtop systems. We demonstrated that uniform illumination increased the reliability of intraimage analysis compared to nonuniform illumination and was concordant with traditional histological findings. The computational approach was used to optimize the illumination geometry for the purposes of imaging 3 different fluorophores through a mammary window chamber model. Illumination specifically designed for intravital tumor imaging generated higher image contrast compared to the case in which illumination originally optimized for biopsy images was used. Conclusion: We demonstrate the significance of using a computationally designed illumination for in vitro, ex vivo, and in vivo fluorescence imaging. Application-specific illumination increased the reliability of intraimage analysis and enhanced the local contrast of biological features. This approach is generalizable across light sources, biological applications, and detectors.

Single cell metabolism: current and future trends

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

In vivo metabolic imaging identifies lipid vulnerability in a preclinical model of Her2+/Neu breast cancer residual disease and recurrence

Recurrent cancer cells that evade therapy is a leading cause of death in breast cancer patients. This risk is high for women showing an overexpression of human epidermal growth factor receptor 2 (Her2). Cells that persist can rely on different substrates for energy production relative to their primary tumor counterpart. Here, we characterize metabolic reprogramming related to tumor dormancy and recurrence in a doxycycline-induced Her2+/Neu model of breast cancer with varying times to recurrence using longitudinal fluorescence microscopy. Glucose uptake (2-NBDG) and mitochondrial membrane potential (TMRE) imaging metabolically phenotype mammary tumors as they transition to regression, dormancy, and recurrence. “Fast-recurrence” tumors (time to recurrence ~55 days), transition from glycolysis to mitochondrial metabolism during regression and this persists upon recurrence. “Slow-recurrence” tumors (time to recurrence ~100 days) rely on both glycolysis and mitochondrial metabolism during recurrence. The increase in mitochondrial activity in fast-recurrence tumors is attributed to a switch from glucose to fatty acids as the primary energy source for mitochondrial metabolism. Consequently, when fast-recurrence tumors receive treatment with a fatty acid inhibitor, Etomoxir, tumors report an increase in glucose uptake and lipid synthesis during regression. Treatment with Etomoxir ultimately prolongs survival. We show that metabolic reprogramming reports on tumor recurrence characteristics, particularly at time points that are essential for actionable targets. The temporal characteristics of metabolic reprogramming will be critical in determining the use of an appropriate timing for potential therapies; namely, the notion that metabolic-targeted inhibition during regression reports long-term therapeutic benefit.

Analyzing cell-type-specific dynamics of metabolism in kidney repair

A common drawback of metabolic analyses of complex biological samples is the inability to consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this limitation, we present an advanced high-spatial-resolution metabolomics approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) combined with isotope tracing. This method allows mapping of cell-type-specific dynamic changes in central carbon metabolism in the context of a complex heterogeneous tissue architecture, such as the kidney. Combined with multiplexed immunofluorescence staining, this method can detect metabolic changes and nutrient partitioning in targeted cell types, as demonstrated in a bilateral renal ischemia-reperfusion injury (bIRI) experimental model. Our approach enables us to identify region-specific metabolic perturbations associated with the lesion and throughout recovery, including unexpected metabolic anomalies in cells with an apparently normal phenotype in the recovery phase. These findings may be relevant to an understanding of the homeostatic capacity of the kidney microenvironment. In sum, this method allows us to achieve resolution at the single-cell level in situ and hence to interpret cell-type-specific metabolic dynamics in the context of structure and metabolism of neighboring cells.

Molecular sensors for detection of tumor-stroma crosstalk

In most solid tumors, malignant cells coexist with non-cancerous host tissue comprised of a variety of extracellular matrix components and cell types, notably fibroblasts, immune cells, and endothelial cells. It is becoming increasingly evident that the non-cancerous host tissue, often referred to as the tumor stroma or the tumor microenvironment, wields tremendous influence in the proliferation, survival, and metastatic ability of cancer cells. The tumor stroma has an active biological role in the transmission of signals, such as growth factors and chemokines that activate oncogenic signaling pathways by autocrine and paracrine mechanisms. Moreover, the constituents of the stroma define the mechanical properties and the physical features of solid tumors, which influence cancer progression and response to therapy. Inspired by the emerging importance of tumor-stroma crosstalk and oncogenic physical forces, numerous biosensors, or advanced imaging and analysis techniques have been developed and applied to investigate complex and challenging questions in cancer research. These techniques facilitate measurements and biological readouts at scales ranging from subcellular to tissue-level with unprecedented level of spatial and temporal precision. Here we examine the application of biosensor technology for studying the complex and dynamic multiscale interactions of the tumor-host system.

A Spectroscopic Technique to Simultaneously Characterize Fatty Acid Uptake, Mitochondrial Activity, Vascularity, and Oxygen Saturation for Longitudinal Studies In Vivo

Aggressive breast cancer has been shown to shift its metabolism towards increased lipid catabolism as the primary carbon source for oxidative phosphorylation. In this study, we present a technique to longitudinally monitor lipid metabolism and oxidative phosphorylation in pre-clinical tumor models to investigate the metabolic changes with mammary tissue development and characterize metabolic differences between primary murine breast cancer and normal mammary tissue. We used optical spectroscopy to measure the signal of two simultaneously injected exogenous fluorescent metabolic reporters: TMRE (oxidative phosphorylation surrogate) and Bodipy FL C16 (lipid catabolism surrogate). We leverage an inverse Monte Carlo algorithm to correct for aberrations resulting from tissue optical properties and to extract vascular endpoints relevant to oxidative metabolism, specifically oxygen saturation (SO2) and hemoglobin concentration ([Hb]). We extensively validated our optical method to demonstrate that our two fluorescent metabolic endpoints can be measured without chemical or optical crosstalk and that dual measurements of both fluorophores in vivo faithfully recapitulate the measurements of each fluorophore independently. We then applied our method to track the metabolism of growing 4T1 and 67NR breast tumors and aging mammary tissue, all highly metabolic tissue types. Our results show the changes in metabolism as a function of mammary age and tumor growth, and these changes can be best distinguished through the combination of endpoints measured with our system. Clustering analysis incorporating both Bodipy FL C16 and TMRE endpoints combined with either SO2 or [Hb] proved to be the most effective in minimizing intra-group variance and maximizing inter-group differences. Our platform can be extended to applications in which long-term metabolic flexibility is important to study, for example in tumor regression, recurrence following dormancy, and responses to cancer treatment.

HER2-PI9 and HER2-I12: two novel and functionally active splice variants of the oncogene HER2 in breast cancer

In this study, two novel alternative splice variants of HER2, named HER2-PI9 and HER2-I12, were identified in breast cancer cell lines and breast tumour tissues. Whilst HER2-P19 arises from the inclusion of an 117 bp cassette-exon of intron 9 of HER2, HER2-I12 results from intron 12 inclusion. In silico analyses were performed to predict the amino acid sequences of these two HER2 novel variants. To confirm their protein expression, plasmid vectors were generated and transfected into the HER2 negative breast cancer cell line, MCF-7. Additionally, their functional properties in oncogenic signalling were confirmed. Expression of HER2-PI9 and HER2-I12 was successful and matched the in silico predictions. Importantly, these splice variants can modulate the phosphorylation levels of extracellular signal-related kinase 1/2 (ERK1/2) and Akt/protein kinase B (Akt) signalling in MCF-7 breast cancer cells. Enhanced cellular proliferation, migration and invasion were observed in the case of the HER2-I12 expressing model. In human tissues and breast carcinoma tumours both variants were present. This study reveals two novel splice variants of HER2. Additionally, the potential biological activity for HER2-PI9 and HER2-I12 in breast cancer cells is also reported..

Real-time monitoring of single circulating tumor cells with a fluorescently labeled deoxy-glucose by in vivo flow cytometry

Circulating tumor cells (CTCs) play an essential role in metastasis and serve as an important prognostic biomarker. The technology of CTC labeling and detection in vivo can greatly improve the research of cancer metastasis and therapy. However, there is no in vivo technology to detect CTCs in clinic. In this study, we demonstrate that 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxy-d-glucose (2-NBDG), a 2-deoxy-glucose analog, can work in vivo to indicate CTCs and metastases fluorescently by direct intravenous injection. During the development of an implanted tumor in mice, the spontaneous CTCs released from the primary tumor into blood vessels can be labeled by 2-NBDG due to the abnormal metabolism of CTCs. The green fluorescence of 2-NBDG from CTCs is then noninvasively detected by an in vivo flow cytometry system. Due to the high uptake of glucose by tumor cells, the CTCs in mice can maintain a high 2-NBDG level and thus be distinguished by 2-NBDG fluorescence in vivo efficiently, enabling tumor detection in vivo like positron emission tomography (PET) but at the single-cell resolution. Our results suggest 2-NBDG, a glucose analog with high biosafety, holds promising potential in clinical applications, similar to the widely-used contrast medium 2-F¹⁸ -fluorodeoxyglucose in PET.

In Vivo Optical Metabolic Imaging of Long-Chain Fatty Acid Uptake in Orthotopic Models of Triple-Negative Breast Cancer

Simple Summary

A dysregulated metabolism is a hallmark of cancer. Once understood, tumor metabolic reprogramming can lead to targetable vulnerabilities, spurring the development of novel treatment strategies. Beyond the common observation that tumors rely heavily on glucose, building evidence indicates that a subset of tumors use lipids to maintain their proliferative or metastatic phenotype. This study developed an intra-vital microscopy method to quantify lipid uptake in breast cancer murine models using a fluorescently labeled palmitate molecule, Bodipy FL c16. This work highlights optical imaging’s ability to both measure metabolic endpoints non-destructively and repeatedly, as well as inform small animal metabolic phenotyping beyond in vivo optical imaging of breast cancer alone.

Abstract

Targeting a tumor’s metabolic dependencies is a clinically actionable therapeutic approach; however, identifying subtypes of tumors likely to respond remains difficult. The use of lipids as a nutrient source is of particular importance, especially in breast cancer. Imaging techniques offer the opportunity to quantify nutrient use in preclinical tumor models to guide development of new drugs that restrict uptake or utilization of these nutrients. We describe a fast and dynamic approach to image fatty acid uptake in vivo and demonstrate its relevance to study both tumor metabolic reprogramming directly, as well as the effectiveness of drugs targeting lipid metabolism. Specifically, we developed a quantitative optical approach to spatially and longitudinally map the kinetics of long-chain fatty acid uptake in in vivo murine models of breast cancer using a fluorescently labeled palmitate molecule, Bodipy FL c16. We chose intra-vital microscopy of mammary tumor windows to validate our approach in two orthotopic breast cancer models: a MYC-overexpressing, transgenic, triple-negative breast cancer (TNBC) model and a murine model of the 4T1 family. Following injection, Bodipy FL c16 fluorescence increased and reached its maximum after approximately 30 min, with the signal remaining stable during the 30–80 min post-injection period. We used the fluorescence at 60 min (Bodipy₆₀), the mid-point in the plateau region, as a summary parameter to quantify Bodipy FL c16 fluorescence in subsequent experiments. Using our imaging platform, we observed a two- to four-fold decrease in fatty acid uptake in response to the downregulation of the MYC oncogene, consistent with findings from in vitro metabolic assays. In contrast, our imaging studies report an increase in fatty acid uptake with tumor aggressiveness (6NR, 4T07, and 4T1), and uptake was significantly decreased after treatment with a fatty acid transport inhibitor, perphenazine, in both normal mammary pads and in the most aggressive 4T1 tumor model. Our approach fills an important gap between in vitro assays providing rich metabolic information at static time points and imaging approaches visualizing metabolism in whole organs at a reduced resolution.

In Situ Metabolic Characterisation of Breast Cancer and Its Potential Impact on Therapy

In spite of tremendous developments in breast cancer treatment, the relatively high incidence of relapsing cases indicates a great need to find new therapeutic strategies in recurrent, metastatic and advanced cases. The bioenergetic needs of growing tumours at the primary site or in metastases-accumulating genomic alterations and further heterogeneity-are supported by metabolic rewiring, an important hallmark of cancer. Adaptation mechanisms as well as altered anabolic and catabolic processes balance according to available nutrients, energy, oxygen demand and overgrowth or therapeutic resistance. Mammalian target of rapamycin (mTOR) hyperactivity may contribute to this metabolic plasticity and progression in breast carcinomas. We set out to assess the metabolic complexity in breast cancer cell lines and primary breast cancer cases. Cellular metabolism and mTOR-related protein expression were characterised in ten cell lines, along with their sensitivity to specific mTOR and other metabolic inhibitors. Selected immunohistochemical reactions were performed on ~100 surgically removed breast cancer specimens. The obtained protein expression scores were correlated with survival and other clinicopathological data. Metabolic and mTOR inhibitor mono-treatments had moderate antiproliferative effects in the studied cell lines in a subtype-independent manner, revealing their high adaptive capacity and survival/growth potential. Immunohistochemical analysis of p-S6, Rictor, lactate dehydrogenase A, glutaminase, fatty acid synthase and carnitine palmitoyltransferase 1A in human samples identified high mTOR activity and potential metabolic plasticity as negative prognostic factors for breast cancer patients, even in subtypes generally considered as low-risk. According to our results, breast cancer is characterised by considerable metabolic diversity, which can be targeted by combining antimetabolic treatments and recent therapies. Alterations in these pathways may provide novel targets for future drug development in breast cancer. We also propose a set of immunostainings for scoring metabolic heterogeneity in individual cases in order to select patients who may benefit from more accurate follow-up and specific therapies.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Consideration of Ketogenic Metabolic Therapy as a Complementary or Alternative Approach for Managing Breast Cancer

Breast cancer remains as a significant cause of morbidity and mortality in women. Ultrastructural and biochemical evidence from breast biopsy tissue and cancer cells shows mitochondrial abnormalities that are incompatible with energy production through oxidative phosphorylation (OxPhos). Consequently, breast cancer, like most cancers, will become more reliant on substrate level phosphorylation (fermentation) than on oxidative phosphorylation (OxPhos) for growth consistent with the mitochondrial metabolic theory of cancer. Glucose and glutamine are the prime fermentable fuels that underlie therapy resistance and drive breast cancer growth through substrate level phosphorylation (SLP) in both the cytoplasm (Warburg effect) and the mitochondria (Q-effect), respectively. Emerging evidence indicates that ketogenic metabolic therapy (KMT) can reduce glucose availability to tumor cells while simultaneously elevating ketone bodies, a non-fermentable metabolic fuel. It is suggested that KMT would be most effective when used together with glutamine targeting. Information is reviewed for suggesting how KMT could reduce systemic inflammation and target tumor cells without causing damage to normal cells. Implementation of KMT in the clinic could improve progression free and overall survival for patients with breast cancer.

Tracking Photodynamic- and Chemotherapy-Induced Redox-State Perturbations in 3D Culture Models of Pancreatic Cancer: A Tool for Identifying Therapy-Induced Metabolic Changes

The metabolic plasticity of cancer cells is considered a highly advantageous phenotype that is crucial for disease progression and acquisition of treatment resistance. A better understanding of cancer metabolism and its adaptability after treatments is vital to develop more effective therapies. To screen novel therapies and combination regimens, three-dimensional (3D) culture models of cancers are attractive platforms as they recapitulate key features of cancer. By applying non-perturbative intensity-based redox imaging combined with high-throughput image analysis, we demonstrated metabolic heterogeneity in various 3D culture models of pancreatic cancer. Photodynamic therapy and oxaliplatin chemotherapy, two cancer treatments with relevance to pancreatic cancer, induced perturbations in redox state in 3D microtumor cultures of pancreatic cancer. In an orthotopic mouse model of pancreatic cancer, a similar disruption in redox homeostasis was observed on ex vivo slices following photodynamic therapy in vivo. Taken together, redox imaging on cancer tissues combined with high-throughput analysis can elucidate dynamic spatiotemporal changes in metabolism following treatment, which will benefit the design of new metabolism-targeted therapeutic approaches.