Open Access

Modeling tumor cell adaptations to hypoxia in multicellular tumor spheroids

Journal of Experimental & Clinical Cancer Research201736:102

https://doi.org/10.1186/s13046-017-0570-9

Received: 13 June 2017

Accepted: 18 July 2017

Published: 3 August 2017

Abstract

Under hypoxic conditions, tumor cells undergo a series of adaptations that promote evolution of a more aggressive tumor phenotype including the activation of DNA damage repair proteins, altered metabolism, and decreased proliferation. Together these changes mitigate the negative impact of oxygen deprivation and allow preservation of genomic integrity and proliferative capacity, thus contributing to tumor growth and metastasis. As a result the presence of a hypoxic microenvironment is considered a negative clinical feature of many solid tumors. Hypoxic niches in tumors also represent a therapeutically privileged environment in which chemo- and radiation therapy is less effective. Although the negative impact of tumor hypoxia has been well established, the precise effect of oxygen deprivation on tumor cell behavior, and the molecular signals that allow a tumor cell to survive in vivo are poorly understood. Multicellular tumor spheroids (MCTS) have been used as an in vitro model for the avascular tumor niche, capable of more accurately recreating tumor genomic profiles and predicting therapeutic response. However, relatively few studies have used MCTS to study the molecular mechanisms driving tumor cell adaptations within the hypoxic tumor environment. Here we will review what is known about cell proliferation, DNA damage repair, and metabolic pathways as modeled in MCTS in comparison to observations made in solid tumors. A more precise definition of the cell populations present within 3D tumor models in vitro could better inform our understanding of the heterogeneity within tumors as well as provide a more representative platform for the testing of therapeutic strategies.

Keywords

Hypoxia Multicellular Tumor Spheroids Metabolism DNA Damage Repair Proliferation Cancer

Background

The majority of solid tumors will develop hypoxia to some degree and tumor hypoxia is a significant prognostic factor that predicts poor patient outcome [1, 2]. It is clear from decades of research that hypoxia induces metastasis and invasion, imparts chemo- and radiation resistance, and provides a selective pressure to abrogate pro-apoptotic signaling [3]. The clinically relevant nature of hypoxia has prompted investigations into how the tumor microenvironment directs tumor cell biology and function. Although the literature on this topic is extensive [17], many aspects of tumor cell biology and survival in the context of a 3-dimensional (3D) environment remain poorly understood. For decades the Multicellular Tumor Spheroid (MCTS) model has been used to study clinically relevant aspects of tumor biology, including hypoxia [8], protein expression patterns within tumors [911], and responses to therapeutics [9, 10, 1223]. However, relatively few experiments have attempted to use MCTS to further our understanding of tumor cell adaptations within a hypoxic microenvironment. This review aims to describe ways in which MCTS can be used to better simulate solid tumors by detailing key features of MCTS that resemble the in vivo context.

The development of tumor hypoxia

While the term hypoxia is used to describe a wide variety of oxygen concentrations [2, 7], it most often refers to the point at which oxygen concentrations have decreased beyond the threshold required for normal cell function. The majority of solid tumors will develop hypoxic regions due to a combination of rapid oxygen depletion, insufficient vascularization, and suboptimal tumor blood flow [2, 7]. For example, the consumption of oxygen by rapidly proliferating perivascular tumor cells can deplete the limited supply of available oxygen and prevent sufficient oxygenation of subsequent cell layers [8, 2426]. While intracellular oxygen is utilized in a variety of reactions, the majority of oxygen consumption is devoted to ATP production through glucose metabolism [26, 27] where oxygen serves as a terminal electron receptor during oxidative phosphorylation. In addition to consumption through intracellular processes, the physical distance between tumor cells and blood vessels also influences the development of hypoxia. Oxygen diffusion through tissue is limited to approximately 200 μm based on evidence from experimental and mathematical models [3, 28]. Hypoxia can be further exacerbated by the destruction of angiogenic vessels following cytotoxic or anti-angiogenic therapy [8, 2931]. Accumulating evidence now suggests that antiangiogenic therapy induces tumor hypoxia which provides a selective pressure for tumors to acquire a more aggressive phenotype leading to therapeutic resistance and tumor progression [2931]. Whether developed as a result of rapid tumor growth or in response to therapeutics, hypoxia is ultimately the result of an imbalance between oxygen availability, consumption, and the physical boundaries to oxygen diffusion inherent to a 3D tissue mass.

Spheroid models for studying hypoxia

The effect of hypoxia on cells has traditionally been studied in monolayer culture. 2D (monolayer) hypoxia experiments are most typically performed by placing tumor cells in a gas-controlled chamber [2]. While experimentally straightforward, this method is unable to recreate clinically relevant aspects of tumor biology that can impact on tumor cell behavior and therapeutic response [13, 32]. For example, monolayer cells experience polarized cell adhesion and two dimensional contact with neighboring cells which results in abnormal cell spreading, alterations in the distribution of cell surface receptors, and selection for specific sub-populations of cells best adapted to in vitro growth [32]. It is also well established that the genomic profiles and therapeutic responses of tumor cells grown in 2D differ from those seen in solid tumors [913, 33]. Studying hypoxia in vivo is challenging due to the high degree of variation in oxygen tensions within and amongst tumors, and limited ability to definitively identify regions of chronic versus acute hypoxia [2, 34]. For these reasons, there can be a disconnect between in vitro studies and the complex 3D environment of a tumor. MCTS may contribute to bridging this gap.

Several methods are used for generating spherical 3D cultures and are reviewed extensively elsewhere [8, 32, 3537]. Common techniques include the liquid overlay technique in which 3D culture is attained by incubating cell suspensions in plates coated with an inert substrate, and the “hanging drop” method wherein cell suspensions are cultured in suspended droplets such that gravity prevents cell attachment and favors cell-cell adhesion [8, 36, 38]. Several factors, including the size of the spheroids, can influence the behavior of MCTS [39]. Spheroid size and media composition dictate the viability and growth kinetics of 3D cultures due to the development of gradients in oxygen and metabolites (discussed below); therefore 3D culture requires careful design of growth conditions and analytical endpoints [39]. Excellent discussions on the practical considerations needed when designing and interpreting data with 3D culture models have been published elsewhere [12, 39].

There are four types of 3D spherical culture models that differ in some important ways (recently reviewed in [36]): MCTS, Tumor Spheres (TS), Tumor Derived Tumor Spheres (TDTS), and Organotypic Multicellular Spheres (OMS). MCTS are formed from established tumor cell lines and grown in standard culture media. MCTS can be composed of mono- or heterotypic cell populations, the latter being the co-culture of tumor cells with other cell types such as macrophages, endothelial cells, and fibroblasts (discussed later in this review). A variation on MCTS culture is the TS model which has been used as a method for growing tumor stem cells in 3D. These spheres are formed from clonal expansion of single cells suspended in non-adherent conditions supplemented with a specific compliment of growth factors in the culture media [36]. Unlike MCTS derived from established cell lines, TS culture represents a selective population of cells known to be aggressive and likely to contribute to tumor regrowth [36, 40]. Accordingly, TS may differ in drug response and growth kinetics relative to MCTS owing to the enrichment of the cancer stem cell population [40]. TDTS are similar to TS however they are formed from partially dissociated tumor tissues [36, 40, 41]. In the TDTS model, primary tumor cells are separated from non-tumor cell types and grown in non-adherent conditions. Relative to MCTS and TS, TDTS have been shown to more accurately recreate tumor growth and gene expression profiles. For example, in breast and colon cancer, TDTS mimic differentiation properties and growth kinetics of the parent tumors more accurately than MCTS from the same tumor background [36, 42]. TDTS therefore provide a suitable model for studying properties of individual tumors. The OMS model utilizes primary, non-dissociated, tumor tissue comprised of all cell types residing within the tissue at the time of excision which provides additional complexity. The presence of stromal cells can adversely affect tumor therapeutic response; therefor the OMS culture method provides a suitable model in which an individual tumor’s therapeutic response can be studied to predict an in vivo response [36, 43, 44].

Each model has distinct advantages and disadvantages (discussed elsewhere [12, 15, 32, 36]) but for maximal control and reproducibility of cell behavior, the MCTS model provides the best coupling of speed with which spheres can be generated, the ability to eliminate influence from non-tumor cell types, and the heterogeneous phenotype of tumor cells incorporated into the sphere. The properties of 3D culture discussed in this review however are applicable to most 3D systems because critical physical properties, such as the development of hypoxia, within the 3D environment are consistent amongst models [12, 32, 39, 45].

Tumor cell adaptations under hypoxia

Spheroids are a useful in vitro model of avascular tumor spaces. Spheroids exceeding 400 μm in diameter develop a hypoxic core and activate known survival signaling pathways to maintain cell viability. Tumor cells grown as MCTS, TS, TDTS, and OMS display regional heterogeneity in tumor cell proliferation [44, 46, 47], metabolic activity [911, 32, 44, 48, 49], and DNA damage repair (DDR) signaling [9, 5053]. In addition to the influence of the 3D microenvironment, the genetic background of the tumor cells and stromal cell populations also contribute to the specifics of spheroid regionalization [39, 5456].

Hypoxia in the 3D environment of tumors and MCTS induces the stable expression of hypoxia inducible factors (HIF). In vivo, HIF proteins transcriptionally promote angiogenesis through VEGF-A, glycolysis, and pH control through CA-IX [57]. Expression of HIF target genes occurs in tumor regions distal to blood vessels and is commonly used to identify hypoxic conditions [2]. Similar patterns have been observed in MCTS wherein HIF target genes (CA-IX, Glut1, VEGF-A) are expressed in the inner, hypoxic cell layers [8, 5861]. Functionally HIF expression in both MCTS and in tumors has been linked to cell survival through the repression of pro-apoptotic signaling, repression of proliferation, and the regulation of metabolic reprograming [58, 62]. In this way, HIF signaling contributes to regionalization of MCTS cell layers and the formation of microenvironments as a function of cell distance from the MCTS surface: limited diffusion of oxygen into MCTS establishes gradients in HIF-α stabilization and subsequently tumor cell behavior. Similarly, rapid proliferation by well oxygenated cell layers and the formation of physical barriers, through tight cell-cell contacts and ECM deposition, generates gradients in glucose, catabolites, and therapeutics [32, 63]. The following sections will discuss the ways in which gradient development within the MCTS model reflects tumor cell adaptations in the avascular tumor space in vivo. These adaptations are schematized in Fig. 1.
Fig. 1

Hypoxia-induced adaptations in a spheroid. Oxygen gradients within tumor spheroids lead to conditions ranging between mild physiological hypoxia to anoxia (represented here by shades of gray). This results in regionalization of tumor cell populations [91, 127]. Hypoxia develops in the spheroid core due to a combination of oxygen diffusion limitations and rapid consumption from proliferating cells [24, 33, 127]. Oxygen deprivation induces glycogen storage to facilitate subsequent metabolism and continued proliferation under more severe hypoxia [49, 62, 71]. Cycling cells in hypoxic regions experience replication stress (stalled replication forks [77] and DNA damage [71]), inducing activation of DNA damage repair (DDR) signaling. DDR allows temporary tumor cell survival and proliferation upon re-oxygenation, but after prolonged periods of severe hypoxia the replisome will disassemble [65, 84]

Proliferation gradients within MCTS

Physiological hypoxia (5% > [O2] > 1%) [64] stimulates cell growth signaling through HIF-α to produce various cytokines and proteins necessary for carrying out cell division [20, 64]. Maintenance of proliferation of tumor and non-tumor cells requires an adequate supply of biomass (nucleotides, carbon sources, lipids) which is progressively diminished with decreasing oxygen levels resulting in a slowed and eventually halted replication cycle. Severe hypoxia defined as an [O2] < 0.13% [2] will result in replisome disassembly and exit from the cell cycle [2, 59, 65]. Spheroids larger than 400 μm in diameter develop oxygen gradients representing a range of hypoxic conditions including chronic-severe hypoxia in the spheroid core. Accordingly spheroid proliferation occurs in a regionally specified manner; there is a progressive decrease in the fraction of S-phase cells with the development of hypoxia in the MCTS core [17, 43, 46, 59, 60, 6671]. In this way, proliferation gradients develop in a size-dependent manner.

In a recent study we found that a population of cycling cells that retain proliferative status in a hypoxic environment can be identified in MCTS larger than 500 μm in diameter formed with A673 (Ewing Sarcoma) or Lewis Lung Carcinoma cells [71]. In human tumors, identification of a similar proliferative hypoxic cell population has been negatively correlated to outcome and it is hypothesized that these cells contribute to tumor recurrence and metastasis [7274]. The mechanisms underlying tumor cell survival and proliferation within the 3D hypoxic environment is not well studied, however the identification of such a population within the MCTS model indicates that MCTS can be used to advance our understanding of proliferation under hypoxia.

Hypoxia and the activation of DNA damage repair signaling

Hypoxia development drives the repression of several DDR proteins which contributes to an increased mutation rate amongst hypoxic cells [1, 4, 19, 5052, 75]. On the other hand, numerous studies have demonstrated hypoxia-dependent activation of DDR proteins leading to stabilization of otherwise damage prone replication forks [59, 60, 7680]. Although well described in vitro, there are still significant unknowns regarding hypoxia-induced DDR, including the clinical relevance of such signaling in vivo and the specific proteins involved in this signaling network.

There is extensive evidence showing down regulation of numerous proteins involved in homologous recombination, mismatch repair, base excision repair, and nucleotide excision repair under hypoxic conditions [1]. Homologous recombination genes RAD51 and BRCA1, and the mismatch repair protein MLH1 [53] were shown to be transcriptionally down regulated in a panel of established cell lines in response to severe hypoxia (<0.5% O2) [5052]. These results were validated in vivo by the finding that both RAD51 and BRCA1 were inversely correlated to markers of hypoxia in cervical and breast cancer patients [1, 5052]. Recent studies using MCTS reported a similar decrease in DDR proteins [9, 53]. The loss of DDR proteins correlates with a decreased ability to repair double stand breaks under oxygen deprivation [1, 19, 81, 82]. This impaired DDR response is being investigated as a potential therapeutic advantage through contextual synthetic lethality [82]. The concept proposes targeting the remaining DDR factors to induce catastrophic genomic instability. It is assumed that non-malignant cells, with an intact DDR signaling network, will be capable of repairing any therapy-induced damage. Promising results in preclinical experiments suggest that this strategy is effective when targeting PARP proteins in BRCA-deficient tumors [81, 83, 84]. This success has stimulated interest in the identification of DDR proteins operating under hypoxia as potential therapeutic targets. The ability of MCTS to recapitulate DDR protein loss validates the potential use of this model for future studies into contextual synthetic lethality.

Compelling evidence indicates that hypoxia drives replication stress, which in turn activates the DDR kinases Ataxia Telangiectasia (ATM) and ATM-and-Rad3 related (ATR) [76, 85]. These kinases were shown to then signal through phosphorylation of downstream targets including Kap1 (S824), Chk1 (S345), Chk2 (Thr68), and H2AX (Ser139), referred to as γ-H2AX [60, 7678]. Although ATM is activated, no DNA damage was originally reported in monolayer culture of the cell lines tested [77, 78]. However, recent studies using MCTS show increased DNA breaks under mild hypoxia using a Ewing Sarcoma cell line (A673) [71]. Together, these studies support a model where ATM and ATR activity leads to stabilization of stalled replication forks and prevention of catastrophic DNA damage, thus allowing continued cell survival and eventual restart of proliferation (Fig. 2). In vivo the consequences of hypoxia induced DDR have been difficult to study. Multiple recent papers reported correlations between γ-H2AX formation and the presence of hypoxia [8688]. For example, in carcinomas of the uterine cervix a 1.4 fold enrichment of γ-H2AX within hypoxic tumor regions (identified through carbonic anhydrase immunoreactivity) and a 2.8 fold enrichment in severely hypoxic (pimonidazole positive) regions has been reported [88].
Fig. 2

Hypoxia-induced DNA damage repair signaling. Cells attempting to proliferate under hypoxic conditions experience slowed replication due to decreased nucleotide pools [65, 85]. In the absence of oxygen, ribonucleotide reductase is impaired in its ability to produce deoxyribonucleotides required for efficient replication [65]. Replication forks stall under these conditions which can lead to DNA damage [71, 77, 78, 85]. Increased DNA damage and replication stress stimulate activation of the DNA damage repair kinases ATM and ATR [7678]. Together these kinases phosphorylate downstream targets resulting in the stabilization of stalled replication forks and preservation of cell viability [71, 78, 85]

Studies exploring DDR in MCTS typically used γ-H2AX staining of trypsin-dissociated spheres to identify the total levels of DNA damage via flow cytometry [46, 89]. More reliable assessment of regional expression can be done through immune labeling of spheroid sections or whole mount imaging. Expression of reporter constructs located downstream of a DDR protein promotor allows for live imaging of DDR response and is of particular interest for the purposes of high throughput screening [15, 39, 45, 90]. Using these techniques, DNA damage repair has largely been explored in the context of therapeutic response to DNA damaging treatments. We recently used MCTS to describe the spatial correlation between the activation or expression of specific DDR signaling proteins, hypoxia markers, and proliferation [71]. Using immunofluorescent labeling of spheroid sections, our findings showed a strong enrichment of γ-H2AX in the hypoxic (HIF-1α, pimonidazole positive), viable cell layers of MCTS. This enrichment and the spatial proximity to necrosis was similar to in vivo studies [8688]. Furthermore we were able to demonstrate for the first time in a 3D context that proliferating hypoxic cells activate DDR signaling which can be targeted by small molecule inhibitors. Interestingly the response to ATR inhibition differed between spheroids and monolayers, reinforcing the significant differences in cell signaling/response between 2D and 3D environments [71].

Altered metabolic activity in MCTS

Hypoxia within the MCTS model is tightly correlated with glucose deprivation. It has long been known that glucose starvation significantly decreases spheroid growth and viability [54, 91, 92]. Studies using radiolabeled glucose and mathematical modeling revealed a critical threshold for glucose and oxygen diffusion into the MCTS core, beyond which chronic starvation results in cell death [56, 93]. Recent findings detailing protein expression and metabolic adaptations within MCTS resemble metabolic profiles described in vivo [9, 11, 49, 54, 94, 95]. The accumulation of glycogen stores under mild hypoxia and subsequent breakdown of these stores into glucose under severe hypoxia represents one such adaptation [49]. Our studies using MCTS demonstrated regional increases in glycogen storage in the perinecrotic/hypoxic core of MCTS, correlating hypoxia development with glycogen accumulation [71]. These observations correlate well with studies showing enrichment of glycogen in perinecrotic/hypoxic zones of tumor xenografts where hypoxia altered the expression of glycogenic (GYS1) and glycolytic (PYGL) enzymes which are known to regulate MCTS glycogen storage [49]. Further glycogen accumulation within hypoxic regions of spheroids and tumor xenografts has been shown in real-time via positron emission tomography [95].

In addition to regulation of energy production, metabolic adaptations facilitate the production of reducing equivalents as a means of controlling reactive oxygen species (ROS) [96]. It is well established that hypoxia reduces oxidative phosphorylation efficiency which generates increased levels of ROS [97]. These highly reactive species oxidize lipids, proteins, and nucleic acids which disrupts cellular homeostasis and induces potentially catastrophic DNA damage [98, 99]. To counteract such effects, tumor cells upregulate metabolic pathways that generate NADPH, a powerful reducing equivalent that helps to restore glutathione levels and mitigate the negative impact of ROS [96, 98]. Some such pathways involve glucose metabolism. It was recently shown that detachment of tumor cells from the ECM disrupts glucose metabolism and induces increased ROS species [100]. In agreement with this data, the formation and growth of MCTS is dependent on sufficient glucose availability and activation of antioxidant pathways [49, 100, 101]. To facilitate growth in MCTS and within hypoxic microenvironments, tumor cells activate signaling through HIF proteins [57]. The HIF transcriptional unit is a heterodimeric complex composed of a constitutively expressed HIF-β subunit and a labile HIF-α subunit. In well oxygenated tumor regions, HIF-α proteins are degraded following proline hydroxylation by Prolyl Hydroxylase (PHD) proteins [57]. In the absence of oxygen, PHD protein function is diminished resulting in HIF-α stabilization, dimerization with HIF-β, and subsequent transcriptional regulation of numerous proteins. The majority of proteins involved in glycolysis are regulated by the HIF transcriptional complex leading to increased glycolysis under hypoxic conditions [57, 62, 102]. In addition to oxygen deprivation, ROS production impairs PHD function leading to HIF-α stabilization, further contributing to metabolic reprograming under hypoxic stress [98].

HIF-α stabilization, metabolic reprograming, and ROS production have all been observed in MCTS with patterns similar to those reported in vivo [8, 22, 49, 71, 103, 104], reflecting recent reports of increased glycogen storage under hypoxic conditions facilitating continued cell proliferation and survival by increasing NADPH production [49, 62]. Similarly, metabolic reprograming under hypoxia includes increased activity from the Isocitrate Dehydrogenase proteins (IDH) which play a significant role in ROS homeostasis and proliferation under hypoxia [105107]. IDH proteins reductively carboxylate α-ketoglutarate to form citrate and NADPH [106, 107]. This process has become increasingly appreciated as critical for cell viability under hypoxia by promoting de novo lipogenesis, restoration of cellular glutathione, and production of carbon equivalents for cell signaling [104107]. Not surprisingly, the loss of IDH proteins leads to the suppression of MCTS growth concomitant with increased ROS production [104]. IDH appears to be involved in MCTS formation as evidenced by the inability to reproducibly form MCTS from glioma cells containing IDH mutations which alter substrate specificity [108]. Similar mutations in vivo are associated with increased patient survival due to an impaired HIF response within hypoxic tumor regions [109]. These adaptations to neutralize ROS have been schematized in Fig. 3.
Fig. 3

Hypoxia induces metabolic adaptations to prevent ROS related damage and maintain proliferation. Under hypoxic conditions tumor cells experience elevated levels of ROS. To mitigate the negative impact of ROS, tumor cells have been shown to increase glycogen stores which are later broken down into glucose-6-phosphate (Glucose-6-P) [49, 62]. Hypoxic cells increase flux through the pentose phosphate pathway which produces NADPH and Ribose-5-phosphate (Ribose-5-P). Ribose-5-P serves as a precursor for DNA nucleotides thus facilitating proliferation [143]. NADPH provides reducing equivalents that restore glutathione levels and neutralize ROS. NADPH is also generated through reductive carboxylation of α-ketoglutarate by Isocitrate Dehydrogenase proteins [104, 106]. Following oxygen deprivation, glutamine is metabolized to form glutamate and subsequently α-ketoglutarate [106]. The formation of citrate by IDH proteins has been shown to increase lipogenesis and facilitate proliferation [105]

The activation of glycolytic pathways is clearly replicated in MCTS as well. Numerous studies have identified increased lactic acid production within hypoxic spheroids which correlates with increased production and activity from glycolytic enzymes [94, 110, 111]. Increased glycolytic activity is indicative of an adaptive shift from oxidative phosphorylation to glycolysis as the primary source of ATP, referred to as the Warburg effect [5, 112, 113]. The ability of MCTS to mimic metabolic adaptations observed in vivo could provide a relevant model system for targeting metabolic pathways in cancer therapy.

Together these studies indicate that hypoxia development within the MCTS model generates metabolic reprograming leading to increased synthesis of glycogen, IDH reductive carboxylation, and glycolytic activity with similar distributions to that observed in vivo. Comprehensive reviews of metabolic adaptations under hypoxic conditions and the interplay of ROS with this process are available [96, 98, 114].

MCTS in co-culture studies

The MCTS discussed thus far were composed exclusively of tumor cells. However, tumors are diverse in terms of their micro-environmental composition as well as their cellular composition. The adaptation of tumor cells to a hypoxic environment is influenced by the activity of stromal cells including endothelial cells, fibroblasts, adipocytes, macrophages, monocytes, and other cell types [115]. As in the case of tumor cells, the hypoxic environment can affect stromal cell behavior [116]. Endothelial cells are known to increase proliferation in response to a hypoxic environment and to activate a DDR signaling cascade similar to that described for tumor cells [117119]. Accumulating evidence suggests that immune cell infiltration into the hypoxic tumor microenvironment increases angiogenesis and tumor metastasis [6, 120]. Both adipocytes and fibroblasts contribute significantly to tumor progression through the production of pro-proliferative cytokines and through production of extracellular matrix (ECM) proteins which confer chemo-resistance [6, 16, 56, 121124].

Towards accurately recreating the tumor microenvironment in vitro, various co-culture models have been developed wherein MCTS are composed of both tumor and stromal cells. The OMS model is perhaps the most representative form of co-culture system due to the inclusion of all resident stromal cell types within the excised tissue [36, 125]. OMS have been used as a model for multiple tumor types and accurately reflect tumor growth kinetics [36, 43, 44]. In glioblastoma for example, the OMS model was found to be superior to MCTS in its ability to recreate the immuno-histochemical profile of in vivo tissues including the expression of many proteins previously correlated to hypoxia-induced aggression (CD31, CD133, P-glycoprotein, and TIMP-1) [44]. However, the inclusion of multiple cell types in the OMS model makes it difficult to determine the influence of a specific stromal cell population on the adaptive tumor cell response [36, 125].

Heterologous spheroid culture in which tumor cells are combined with one or more stromal cell types has provided unique insights into stromal and tumor cell responses to hypoxia [15, 36, 126]. The most commonly used methods of heterologous culture can be broadly described as: 1) Spheroid confrontation culture: individual spheroids are formed from stromal cells and separately from tumor cells followed by joint culture in suspension or embedded within an ECM, 2) Spheroid-monolayer culture: pre-formed MCTS are placed atop confluent monolayers, 3) Heterologous spheroid co-culture: tumor and stromal cell suspensions are combined during the sphere forming process, 4) Spheroid co-cultures in vivo: pre-formed MCTS containing stromal cells are implanted in vivo [125].

MCTS in co-culture with endothelial cells mimic several processes during hypoxia-induced angiogenesis: oxygen deprivation within the MCTS core stimulates production and accumulation of vascular endothelial growth factors (VEGF) [61, 127] which provides a stimulus for endothelial cell recruitment. In vivo, endothelial cell invasion into tumors facilitates metastasis and release of tumor cells from the growth inhibitory effects of a hypoxic environment [6]. Other MCTS co-culture models recreate a similar process and have been used to improve our understanding of the relationship between endothelial cells and tumor cells [125, 128]. For example, placement of tumor spheroids atop confluent endothelial monolayers can result in infiltration by endothelial cells expressing tumor complimentary adhesion molecules or can result in tumor-mediated destruction of endothelial vessels, reminiscent of cell death observed in vivo following vessel cooption [125, 128]. Use of confrontation or heterologous co-culture models can successfully produce vascular networks within spheroids with an increase in tumor cell viability and drug resistance [22, 129]. The invasive potential of tumor cells following vascularization is also replicated through the use of heterologous sphere culture systems [56, 122, 130]. A recent study highlighted this by showing the formation of MCTS with both endothelial and tumor cells could lead to the formation of luminal vessels in which migrating tumor cells can be seen [130], mimicking the process of tumor intravasation.

Fibroblasts are also a critical stromal cell population that contribute to tumor progression through the release of proliferative and pro-metastatic growth factors and foster the creation of a drug resistant environment by depositing ECM which hinders drug diffusion [122, 125, 126]. Each of these characteristics are replicated in heterologous sphere culture [16, 56, 122, 124126]. Within a pro-angiogenic environment, fibroblasts take on a mural cell phenotype and augment angiogenesis through the release of VEGF, matrix metalloproteinases (MMP), and other growth factors [16, 56, 122, 124, 126]. In vitro this process can be studied through the “mini-tumor model” in which endothelial cells, fibroblasts, and tumor cells are co-cultured in 3D [122]. This tri-culture model replicated pathological formation of luminal vascular structures bordered by fibroblasts and tumor cells which are both dependent on angiogenic growth factors and responsive to anti-angiogenic therapeutics [122]. This mini-tumor model has significant potential for studying the refractory response of tumor and stromal cells following anti-angiogenic therapy and the specific mechanisms used to circumvent these treatments.

Immune cells are a major regulatory factor during tumor progression [5]. Within the hypoxic tumor environment, there are indications that immune cells facilitate tumor aggression through increased angiogenesis and immunosuppression [115, 131]. In vivo immune cells aggregate within hypoxic, peri-necrotic regions [131]. These observations have been mirrored in MCTS co-cultures and indicate potential utility for MCTS as an investigational tool to replicate in vivo conditions [56, 132]. In support of this, immune cell influence over angiogenesis has been described by a series of studies through the inclusion of monocytes in co-culture with tumor spheroids to show immune-dependent increases in production of VEGF, ECM degrading proteins, and in vivo angiogenesis through MCTS co-culture in skinfold window chambers [56, 131133]. A particular advantage to MCTS co-culture in modelling the hypoxic microenvironment is the accumulation of immunomodulatory metabolites and cytokines.

Levels of lactic acid are commonly high in hypoxic tumor regions due to increased glycolytic activity and HIF mediated production of lactic acid transporters [134]. In vitro studies show that hypoxia-induced increases in lactic acid and VEGF can decrease dendritic cell differentiation and maturation while increasing monocyte conversion to M2 macrophages, ultimately resulting in immunosuppression [56, 131, 135137]. The MCTS co-culture models are well suited to model a hypoxic microenvironment with high metabolite and growth factor levels. Hypoxic spheroids show higher levels of lactic acid which correlates with decreased immune cell invasion, reduced production of colony stimulating factor [131, 136] and decreased dendritic cell maturation in hypoxic conditions [131, 138].

MCTS as a model to determine therapeutic efficacy in heterogeneous environments

Aside from instigating an aggressive phenotype, tumor hypoxia presents several challenges to therapeutic intervention [3, 139]. Hypoxia has been appreciated for its ability to reduce radiation effectiveness for many decades [24, 84, 140]. Since this phenomenon was described, a significant amount of evidence has amassed demonstrating the ways a hypoxic environment renders tumor cells privileged, or resistant, to multiple therapeutic modalities [3, 13, 22, 23, 44, 63, 88, 139, 141, 142]. Several studies have detailed the contribution of stromal cells to chemo-resistance in the MCTS model [14, 16, 122, 124] and technological advances are allowing more complex co-culture systems to be developed [15, 45]. The use of MCTS for screening of therapeutics has been extensively reviewed elsewhere [39].

Conclusions

The negative impact of hypoxia on tumor prognosis warrants a significant effort to better understand and target hypoxic tumor cell adaptations. The MCTS model is an established technique with untapped potential to improve our understanding of subpopulations within a tumor. With growing therapeutic interest in targeting metabolic pathways, DDR proteins, and contextual synthetic lethality, the MCTS model could be used to great effect.

Abbreviations

2D: 

Two dimensional cell culture monolayer culture

3D: 

Three dimensional

A673: 

Human Ewing Sarcoma cell line (CRL-1598; ATCC)

ATM: 

Ataxia Telangiectasia

ATR: 

ATM and Rad3-related

BRCA1: 

Breast Cancer 1

CD133: 

Prominin-1

CD31: 

Platelet Endothelial Cell Adhesion Molecule

Chk1/2: 

Checkpoint kinase 1 and 2

DDR: 

DNA damage repair

ECM: 

Extracellular matrix

GYS1: 

Glycogen synthase 1

H2AX: 

Histone variant 2A.X

HIF-α: 

Hypoxia Inducible Factor α subunit

IDH: 

Isocitrate Dehydrogenase

Kap1: 

KRAB-associated protein-1

MCTS: 

Multicellular Tumor Spheroids

MLH1: 

MutL homolog 1

MMP: 

Matrix metallopeptidase

OMS: 

Organotypic Multicellular Sphere

PARP: 

Poly (ADP-ribose) polymerase

PYGL: 

Glycogen phosphorylase L (Liver)

RAD51: 

RAD51 recombinase

TDTS: 

Tumor Derived Tumor Sphere

TIMP-1: 

TIMP metallopeptidase inhibitor 1

TS: 

Tumor Sphere

VEGF: 

Vascular Endothelial Growth Factor

γ-H2AX: 

H2AX phosphorylated on serine-139

Declarations

Authors' contributions

SR wrote an initial draft of this review. It was extensively edited and modified by RSH. Both authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine

References

  1. Scanlon SE, Glazer PM. Multifaceted control of DNA repair pathways by the hypoxic tumor microenvironment. DNA Repair (Amst). 2015;32:180–9.View ArticleGoogle Scholar
  2. Hammond EM, Asselin MC, Forster D, O'Connor JP, Senra JM, Williams KJ. The meaning, measurement and modification of hypoxia in the laboratory and the clinic. Clin Oncol (R Coll Radiol). 2014;26(5):277–88.View ArticleGoogle Scholar
  3. Wilson WR, Hay MP. Targeting hypoxia in cancer therapy. Nat Rev Cancer. 2011;11(6):393–410.PubMedView ArticleGoogle Scholar
  4. Bristow RG, Hill RP. Hypoxia and metabolism. Hypoxia, DNA repair and genetic instability. Nat Rev Cancer. 2008;8(3):180–92.PubMedView ArticleGoogle Scholar
  5. Hanahan D, Weinberg RA. Hallmarks of cancer: The next generation. Cell. 2011;144(5):646–74.PubMedView ArticleGoogle Scholar
  6. Wang M, Zhao J, Zhang L, et al. Role of tumor microenvironment in tumorigenesis. J Cancer. 2017;8(5):761–73.PubMedPubMed CentralView ArticleGoogle Scholar
  7. Hockel M, Vaupel P. Tumor hypoxia: Definitions and current clinical, biologic, and molecular aspects. J Natl Cancer Inst. 2001;93(4):266–76.PubMedView ArticleGoogle Scholar
  8. Leek R, Grimes DR, Harris AL, McIntyre A. Methods: Using three-dimensional culture (spheroids) as an in vitro model of tumour hypoxia. Adv Exp Med Biol. 2016;899:167–96.PubMedView ArticleGoogle Scholar
  9. Ghosh S, Spagnoli GC, Martin I, et al. Three-dimensional culture of melanoma cells profoundly affects gene expression profile: A high density oligonucleotide array study. J Cell Physiol. 2005;204(2):522–31.PubMedView ArticleGoogle Scholar
  10. Daster S, Amatruda N, Calabrese D, et al. Induction of hypoxia and necrosis in multicellular tumor spheroids is associated with resistance to chemotherapy treatment. Oncotarget. 2017;8(1):1725–36.PubMedGoogle Scholar
  11. Pacheco-Marin R, Melendez-Zajgla J, Castillo-Rojas G, et al. Transcriptome profile of the early stages of breast cancer tumoral spheroids. Sci Rep. 2016;6:23373.PubMedPubMed CentralView ArticleGoogle Scholar
  12. Hirschhaeuser F, Menne H, Dittfeld C, West J, Mueller-Klieser W, Kunz-Schughart LA. Multicellular tumor spheroids: An underestimated tool is catching up again. J Biotechnol. 2010;148(1):3–15.PubMedView ArticleGoogle Scholar
  13. Mehta G, Hsiao AY, Ingram M, Luker GD, Takayama S. Opportunities and challenges for use of tumor spheroids as models to test drug delivery and efficacy. J Control Release. 2012;164(2):192–204.PubMedPubMed CentralView ArticleGoogle Scholar
  14. Song Y, Kim SH, Kim KM, Choi EK, Kim J, Seo HR. Activated hepatic stellate cells play pivotal roles in hepatocellular carcinoma cell chemoresistance and migration in multicellular tumor spheroids. Sci Rep. 2016;6:36750.PubMedPubMed CentralView ArticleGoogle Scholar
  15. Lovitt CJ, Shelper TB, Avery VM. Advanced cell culture techniques for cancer drug discovery. Biology (Basel). 2014;3(2):345–67.Google Scholar
  16. Yip D, Cho CH. A multicellular 3d heterospheroid model of liver tumor and stromal cells in collagen gel for anti-cancer drug testing. Biochem Biophys Res Commun. 2013;433(3):327–32.PubMedView ArticleGoogle Scholar
  17. Dufau I, Frongia C, Sicard F, et al. Multicellular tumor spheroid model to evaluate spatio-temporal dynamics effect of chemotherapeutics: Application to the gemcitabine/chk1 inhibitor combination in pancreatic cancer. BMC Cancer. 2012;12:15.PubMedPubMed CentralView ArticleGoogle Scholar
  18. Fedrigo CA, Grivicich I, Schunemann DP, et al. Radioresistance of human glioma spheroids and expression of hsp70, p53 and egfr. Radiat Oncol. 2011;6:156.PubMedPubMed CentralView ArticleGoogle Scholar
  19. Chan N, Koritzinsky M, Zhao H, et al. Chronic hypoxia decreases synthesis of homologous recombination proteins to offset chemoresistance and radioresistance. Cancer Res. 2008;68(2):605–14.PubMedView ArticleGoogle Scholar
  20. Kilic M, Kasperczyk H, Fulda S, Debatin KM. Role of hypoxia inducible factor-1 alpha in modulation of apoptosis resistance. Oncogene. 2007;26(14):2027–38.PubMedView ArticleGoogle Scholar
  21. Francia G, Man S, Teicher B, Grasso L, Kerbel RS. Gene expression analysis of tumor spheroids reveals a role for suppressed DNA mismatch repair in multicellular resistance to alkylating agents. Mol Cell Biol. 2004;24(15):6837–49.PubMedPubMed CentralView ArticleGoogle Scholar
  22. Wartenberg M, Ling FC, Muschen M, et al. Regulation of the multidrug resistance transporter p-glycoprotein in multicellular tumor spheroids by hypoxia-inducible factor (hif-1) and reactive oxygen species. FASEB J. 2003;17(3):503–5.PubMedGoogle Scholar
  23. Olive PL, Durand RE. Drug and radiation resistance in spheroids: Cell contact and kinetics. Cancer Metastasis Rev. 1994;13(2):121–38.PubMedView ArticleGoogle Scholar
  24. Durand RE, Biaglow JE. Radiosensitization of hypoxic cells of an in vitro tumor model by respiratory inhibitors. Radiat Res. 1977;69(2):359–66.PubMedView ArticleGoogle Scholar
  25. Groebe K, Mueller-Klieser W. On the relation between size of necrosis and diameter of tumor spheroids. Int J Radiat Oncol Biol Phys. 1996;34(2):395–401.PubMedView ArticleGoogle Scholar
  26. Wagner BA, Venkataraman S, Buettner GR. The rate of oxygen utilization by cells. Free Radic Biol Med. 2011;51(3):700–12.PubMedPubMed CentralView ArticleGoogle Scholar
  27. Herst PM, Berridge MV. Cell surface oxygen consumption: A major contributor to cellular oxygen consumption in glycolytic cancer cell lines. Biochim Biophys Acta. 2007;1767(2):170–7.PubMedView ArticleGoogle Scholar
  28. Grimes R, Kelly C, Bloch K, Partridge M. A method for estimating the oxygen consumption rate in multicellular tumour spheroids. J R Soc Interface. 2014;11:20131124. doi:https://doi.org/10.1098/rsif.2013.1124.
  29. Al-Husein B, Abdalla M, Trepte M, Deremer DL, Somanath PR. Antiangiogenic therapy for cancer: An update. Pharmacotherapy. 2012;32(12):1095–111.PubMedPubMed CentralView ArticleGoogle Scholar
  30. Paez-Ribes M, Allen E, Hudock J, et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell. 2009;15(3):220–31.PubMedPubMed CentralView ArticleGoogle Scholar
  31. Pinto MP, Sotomayor P, Carrasco¬Avino G, Corvalan AH, Owen GI. Escaping antiangiogenic therapy: Strategies employed by cancer cells. Int J Mol Sci. 2016;17(9). doi:https://doi.org/10.3390/ijms17091489.
  32. Baker BM, Chen CS. Deconstructing the third dimension: How 3d culture microenvironments alter cellular cues. J Cell Sci. 2012;125(Pt 13):3015–24.PubMedPubMed CentralView ArticleGoogle Scholar
  33. Zhou Y, Arai T, Horiguchi Y, Ino K, Matsue T, Shiku H. Multiparameter analyses of three-dimensionally cultured tumor spheroids based on respiratory activity and comprehensive gene expression profiles. Anal Biochem. 2013;439(2):187–93.PubMedView ArticleGoogle Scholar
  34. Dewhirst MW, Birer SR. Oxygen-enhanced mri is a major advance in tumor hypoxia imaging. Cancer Res. 2016;76(4):769–72.PubMedView ArticleGoogle Scholar
  35. Vinci M, Gowan S, Boxall F, et al. Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. BMC Biol. 2012;10:29.PubMedPubMed CentralView ArticleGoogle Scholar
  36. Weiswald LB, Bellet D, Dangles-Marie V. Spherical cancer models in tumor biology. Neoplasia. 2015;17(1):1–15.PubMedPubMed CentralView ArticleGoogle Scholar
  37. Achilli TM, Meyer J, Morgan JR. Advances in the formation, use and understanding of multi-cellular spheroids. Expert Opin Biol Ther. 2012;12(10):1347–60.PubMedPubMed CentralView ArticleGoogle Scholar
  38. Timmins NE, Nielsen LK. Generation of multicellular tumor spheroids by the hanging-drop method. Methods Mol Med. 2007;140:141–51.PubMedView ArticleGoogle Scholar
  39. Friedrich J, Seidel C, Ebner R, Kunz-Schughart LA. Spheroid-based drug screen: Considerations and practical approach. Nat Protoc. 2009;4(3):309–24.PubMedView ArticleGoogle Scholar
  40. Ishiguro T, Ohata H, Sato A, Yamawaki K, Enomoto T, Okamoto K. Tumor-derived spheroids: Relevance to cancer stem cells and clinical applications. Cancer Sci. 2017;108(3):283–9.PubMedPubMed CentralView ArticleGoogle Scholar
  41. Ham SL, Joshi R, Thakuri PS, Tavana H. Liquid-based three-dimensional tumor models for cancer research and drug discovery. Exp Biol Med (Maywood). 2016;241(9):939–54.View ArticleGoogle Scholar
  42. Theodoraki MA, Rezende CO Jr, Chantarasriwong O, Corben AD, Theodorakis EA, Alpaugh ML. Spontaneously-forming spheroids as an in vitro cancer cell model for anticancer drug screening. Oncotarget. 2015;6(25):21255–67.PubMedPubMed CentralView ArticleGoogle Scholar
  43. Bjerkvig R, Tonnesen A, Laerum OD, Backlund EO. Multicellular tumor spheroids from human gliomas maintained in organ culture. J Neurosurg. 1990;72(3):463–75.PubMedView ArticleGoogle Scholar
  44. Christensen K, Aaberg-Jessen C, Andersen C, Goplen D, Bjerkvig R, Kristensen BW. Immunohistochemical expression of stem cell, endothelial cell, and chemosensitivity markers in primary glioma spheroids cultured in serum-containing and serum-free medium. Neurosurgery. 2010;66(5):933–47.PubMedView ArticleGoogle Scholar
  45. Huh D, Hamilton GA, Ingber DE. From 3d cell culture to organs-on-chips. Trends Cell Biol. 2011;21(12):745–54.PubMedPubMed CentralView ArticleGoogle Scholar
  46. LaRue KE, Khalil M, Freyer JP. Microenvironmental regulation of proliferation in multicellular spheroids is mediated through differential expression of cyclin-dependent kinase inhibitors. Cancer Res. 2004;64(5):1621–31.PubMedView ArticleGoogle Scholar
  47. Lawlor ER, Scheel C, Irving J, Sorensen PH. Anchorage-independent multi-cellular spheroids as an in vitro model of growth signaling in ewing tumors. Oncogene. 2002;21(2):307–18.PubMedView ArticleGoogle Scholar
  48. Kumar HR, Zhong X, Hoelz DJ, et al. Three-dimensional neuroblastoma cell culture: Proteomic analysis between monolayer and multicellular tumor spheroids. Pediatr Surg Int. 2008;24(11):1229–34.PubMedPubMed CentralView ArticleGoogle Scholar
  49. Favaro E, Bensaad K, Chong MG, et al. Glucose utilization via glycogen phosphorylase sustains proliferation and prevents premature senescence in cancer cells. Cell Metab. 2012;16(6):751–64.PubMedView ArticleGoogle Scholar
  50. Bindra RS, Gibson SL, Meng A, et al. Hypoxia-induced down-regulation of brca1 expression by e2fs. Cancer Res. 2005;65(24):11597–604.PubMedView ArticleGoogle Scholar
  51. Bindra RS, Glazer PM. Repression of rad51 gene expression by e2f4/p130 complexes in hypoxia. Oncogene. 2007;26(14):2048–57.PubMedView ArticleGoogle Scholar
  52. Bindra RS, Schaffer PJ, Meng A, et al. Down-regulation of rad51 and decreased homologous recombination in hypoxic cancer cells. Mol Cell Biol. 2004;24(19):8504–18.PubMedPubMed CentralView ArticleGoogle Scholar
  53. Collins SL, Herve R, Keevil CW, Blaydes JP, Webb JS. Down-regulation of DNA mismatch repair enhances initiation and growth of neuroblastoma and brain tumour multicellular spheroids. PLoS One. 2011;6(12):e28123.PubMedPubMed CentralView ArticleGoogle Scholar
  54. Kunz-Schughart LA, Groebe K, Mueller-Klieser W. Three-dimensional cell culture induces novel proliferative and metabolic alterations associated with oncogenic transformation. Int J Cancer. 1996;66(4):578–86.PubMedView ArticleGoogle Scholar
  55. Stadler M, Walter S, Walzl A, et al. Increased complexity in carcinomas: Analyzing and modeling the interaction of human cancer cells with their microenvironment. Semin Cancer Biol. 2015;35:107–24.PubMedView ArticleGoogle Scholar
  56. Stock K, Estrada MF, Vidic S, et al. Capturing tumor complexity in vitro: Comparative analysis of 2d and 3d tumor models for drug discovery. Sci Rep. 2016;6:28951.PubMedPubMed CentralView ArticleGoogle Scholar
  57. Loboda A, Jozkowicz A, Dulak J. Hif-1 and hif-2 transcription factors--similar but not identical. Mol Cells. 2010;29(5):435–42.PubMedView ArticleGoogle Scholar
  58. Menrad H, Werno C, Schmid T, et al. Roles of hypoxia-inducible factor-1alpha (hif-1alpha) versus hif-2alpha in the survival of hepatocellular tumor spheroids. Hepatology. 2010;51(6):2183–92.PubMedView ArticleGoogle Scholar
  59. Pires IM, Bencokova Z, Milani M, et al. Effects of acute versus chronic hypoxia on DNA damage responses and genomic instability. Cancer Res. 2010;70(3):925–35.PubMedPubMed CentralView ArticleGoogle Scholar
  60. Pires IM, Olcina MM, Anbalagan S, et al. Targeting radiation-resistant hypoxic tumour cells through atr inhibition. Br J Cancer. 2012;107(2):291–9.PubMedPubMed CentralView ArticleGoogle Scholar
  61. Shweiki D, Neeman M, Itin A, Keshet E. Induction of vascular endothelial growth factor expression by hypoxia and by glucose deficiency in multicell spheroids: Implications for tumor angiogenesis. Proc Natl Acad Sci U S A. 1995;92(3):768–72.PubMedPubMed CentralView ArticleGoogle Scholar
  62. Pescador N, Villar D, Cifuentes D, et al. Hypoxia promotes glycogen accumulation through hypoxia inducible factor (hif)-mediated induction of glycogen synthase 1. PLoS One. 2010;5(3):e9644.PubMedPubMed CentralView ArticleGoogle Scholar
  63. Grantab RH, Tannock IF. Penetration of anticancer drugs through tumour tissue as a function of cellular packing density and interstitial fluid pressure and its modification by bortezomib. BMC Cancer. 2012;12:214.PubMedPubMed CentralView ArticleGoogle Scholar
  64. Carrera S, Senra J, Acosta MI, et al. The role of the hif-1alpha transcription factor in increased cell division at physiological oxygen tensions. PLoS One. 2014;9(5):e97938.PubMedPubMed CentralView ArticleGoogle Scholar
  65. Foskolou IP, Jorgensen C, Leszczynska KB, et al. Ribonucleotide reductase requires subunit switching in hypoxia to maintain DNA replication. Mol Cell. 2017;66(2):206–220 e209.PubMedPubMed CentralView ArticleGoogle Scholar
  66. Frongia C, Lorenzo C, Gianni F, Prevost GP, Ducommun B, Lobjois V. 3d imaging of the response to cdc25 inhibition in multicellular spheroids. Cancer Biol Ther. 2009;8(23):2230–6.PubMedView ArticleGoogle Scholar
  67. Khaitan D, Chandna S, Arya MB, Dwarakanath BS. Establishment and characterization of multicellular spheroids from a human glioma cell line; implications for tumor therapy. J Transl Med. 2006;4:12.PubMedPubMed CentralView ArticleGoogle Scholar
  68. Laurent J, Frongia C, Cazales M, Mondesert O, Ducommun B, Lobjois V. Multicellular tumor spheroid models to explore cell cycle checkpoints in 3d. BMC Cancer. 2013;13:73.PubMedPubMed CentralView ArticleGoogle Scholar
  69. Lobjois V, Frongia C, Jozan S, Truchet I, Valette A. Cell cycle and apoptotic effects of saha are regulated by the cellular microenvironment in hct116 multicellular tumour spheroids. Eur J Cancer. 2009;45(13):2402–11.PubMedView ArticleGoogle Scholar
  70. Magnussen GI, Emilsen E, Giller Fleten K, et al. Combined inhibition of the cell cycle related proteins wee1 and chk1/2 induces synergistic anti-cancer effect in melanoma. BMC Cancer. 2015;15:462.PubMedPubMed CentralView ArticleGoogle Scholar
  71. Riffle S, Pandey RN, Albert M, Hegde RS. Linking hypoxia, DNA damage and proliferation in multicellular tumor spheroids. BMC Cancer. 2017;17(1):338.PubMedPubMed CentralView ArticleGoogle Scholar
  72. Evans SM, Du KL, Chalian AA, et al. Patterns and levels of hypoxia in head and neck squamous cell carcinomas and their relationship to patient outcome. Int J Radiat Oncol Biol Phys. 2007;69(4):1024–31.PubMedPubMed CentralView ArticleGoogle Scholar
  73. Evans SM, Hahn SM, Magarelli DP, Koch CJ. Hypoxic heterogeneity in human tumors: Ef5 binding, vasculature, necrosis, and proliferation. Am J Clin Oncol. 2001;24(5):467–72.PubMedView ArticleGoogle Scholar
  74. Evans SM, Jenkins KW, Chen HI, et al. The relationship among hypoxia, proliferation, and outcome in patients with de novo glioblastoma: A pilot study. Transl Oncol. 2010;3(3):160–9.PubMedPubMed CentralView ArticleGoogle Scholar
  75. Koshiji M, To KK, Hammer S, et al. Hif-1alpha induces genetic instability by transcriptionally downregulating mutsalpha expression. Mol Cell. 2005;17(6):793–803.PubMedView ArticleGoogle Scholar
  76. Bencokova Z, Kaufmann MR, Pires IM, Lecane PS, Giaccia AJ, Hammond EM. Atm activation and signaling under hypoxic conditions. Mol Cell Biol. 2009;29(2):526–37.PubMedView ArticleGoogle Scholar
  77. Hammond EM, Denko NC, Dorie MJ, Abraham RT, Giaccia AJ. Hypoxia links atr and p53 through replication arrest. Mol Cell Biol. 2002;22(6):1834–43.PubMedPubMed CentralView ArticleGoogle Scholar
  78. Hammond EM, Dorie MJ, Giaccia AJ. Atr/atm targets are phosphorylated by atr in response to hypoxia and atm in response to reoxygenation. J Biol Chem. 2003;278(14):12207–13.PubMedView ArticleGoogle Scholar
  79. Hammond EM, Dorie MJ, Giaccia AJ. Inhibition of atr leads to increased sensitivity to hypoxia/reoxygenation. Cancer Res. 2004;64(18):6556–62.PubMedView ArticleGoogle Scholar
  80. Olcina MM, Foskolou IP, Anbalagan S, et al. Replication stress and chromatin context link atm activation to a role in DNA replication. Mol Cell. 2013;52(5):758–66.PubMedPubMed CentralView ArticleGoogle Scholar
  81. Chan N, Pires IM, Bencokova Z, et al. Contextual synthetic lethality of cancer cell kill based on the tumor microenvironment. Cancer Res. 2010;70(20):8045–54.PubMedPubMed CentralView ArticleGoogle Scholar
  82. Chan N, Bristow RG. “Contextual” synthetic lethality and/or loss of heterozygosity: Tumor hypoxia and modification of DNA repair. Clin Cancer Res. 2010;16(18):4553–60.PubMedView ArticleGoogle Scholar
  83. Chan DA, Giaccia AJ. Harnessing synthetic lethal interactions in anticancer drug discovery. Nat Rev Drug Discov. 2011;10(5):351–64.PubMedPubMed CentralView ArticleGoogle Scholar
  84. Olcina M, Lecane PS, Hammond EM. Targeting hypoxic cells through the DNA damage response. Clin Cancer Res. 2010;16(23):5624–9.PubMedPubMed CentralView ArticleGoogle Scholar
  85. Olcina MM, Grand RJ, Hammond EM. Atm activation in hypoxia - causes and consequences. Mol Cell Oncol. 2014;1(1):–e29903.Google Scholar
  86. Banuelos CA, Banath JP, Kim JY, Aquino-Parsons C, Olive PL. Gammah2ax expression in tumors exposed to cisplatin and fractionated irradiation. Clin Cancer Res. 2009;15(10):3344–53.PubMedView ArticleGoogle Scholar
  87. Nagelkerke A, Span PN. Staining against phospho-h2ax (gamma-h2ax) as a marker for DNA damage and genomic instability in cancer tissues and cells. Adv Exp Med Biol. 2016;899:1–10.PubMedView ArticleGoogle Scholar
  88. Olive PL, Banuelos CA, Durand RE, Kim JY, Aquino-Parsons C. Endogenous and radiation-induced expression of gammah2ax in biopsies from patients treated for carcinoma of the uterine cervix. Radiother Oncol. 2010;94(1):82–9.PubMedView ArticleGoogle Scholar
  89. Olive PL, Banath JP, Sinnott LT. Phosphorylated histone h2ax in spheroids, tumors, and tissues of mice exposed to etoposide and 3-amino-1,2,4-benzotriazine-1,3-dioxide. Cancer Res. 2004;64(15):5363–9.PubMedView ArticleGoogle Scholar
  90. Mondesert O, Frongia C, Clayton O, Boizeau ML, Lobjois V, Ducommun B. Monitoring the activation of the DNA damage response pathway in a 3d spheroid model. PLoS One. 2015;10(7):e0134411.PubMedPubMed CentralView ArticleGoogle Scholar
  91. Freyer JP, Sutherland RM. Regulation of growth saturation and development of necrosis in emt6/ro multicellular spheroids by the glucose and oxygen supply. Cancer Res. 1986;46(7):3504–12.PubMedGoogle Scholar
  92. Tannock IF, Kopelyan I. Influence of glucose concentration on growth and formation of necrosis in spheroids derived from a human bladder cancer cell line. Cancer Res. 1986;46(6):3105–10.PubMedGoogle Scholar
  93. Owen MR, Byrne HM, Lewis CE. Mathematical modelling of the use of macrophages as vehicles for drug delivery to hypoxic tumour sites. J Theor Biol. 2004;226(4):377–91.PubMedView ArticleGoogle Scholar
  94. Bloch K, Smith H, van Hamel PV, et al. Metabolic alterations during the growth of tumour spheroids. Cell Biochem Biophys. 2014;68(3):615–28.PubMedView ArticleGoogle Scholar
  95. Witney TH, Carroll L, Alam IS, et al. A novel radiotracer to image glycogen metabolism in tumors by positron emission tomography. Cancer Res. 2014;74(5):1319–28.PubMedPubMed CentralView ArticleGoogle Scholar
  96. Kim J, Kim J, Bae JS. Ros homeostasis and metabolism: A critical liaison for cancer therapy. Exp Mol Med. 2016;48(11):e269.PubMedPubMed CentralView ArticleGoogle Scholar
  97. Dugan LL CD. Free radicals in hypoxia-ischemia. In: Siegel GJ AB, Albers RW, et al, ed. Basic Neurochemistry: Molecular, Cellular and Medical Aspects. Vol 6th. Philadelphia: Lippincott-Raven; 1999.Google Scholar
  98. Tafani M, Sansone L, Limana F, et al. The interplay of reactive oxygen species, hypoxia, inflammation, and sirtuins in cancer initiation and progression. Oxidative Med Cell Longev. 2016;2016:18.View ArticleGoogle Scholar
  99. Cadet J, Davies KJA, Medeiros MHG, Di Mascio P, Wagner JR. Formation and repair of oxidatively generated damage in cellular DNA. Free Radic Biol Med. 2017;107:13–34.PubMedView ArticleGoogle Scholar
  100. Schafer ZT, Grassian AR, Song L, et al. Antioxidant and oncogene rescue of metabolic defects caused by loss of matrix attachment. Nature. 2009;461(7260):109–13.PubMedPubMed CentralView ArticleGoogle Scholar
  101. Marín-Hernández Á, Gallardo-Pérez JC, Hernández-Reséndiz I, et al. Hypoglycemia enhances epithelial-mesenchymal transition and invasiveness, and restrains the warburg phenotype, in hypoxic hela cell cultures and microspheroids. J Cell Physiol. 2017;232(6):1346–59.PubMedView ArticleGoogle Scholar
  102. Parks SK, Cormerais Y, Pouyssegur J. Hypoxia and cellular metabolism in tumour pathophysiology. J Physiol. 2017;595(8):2439–50.PubMedView ArticleGoogle Scholar
  103. Wartenberg M, Fischer K, Hescheler J, Sauer H. Redox regulation of p-glycoprotein-mediated multidrug resistance in multicellular prostate tumor spheroids. Int J Cancer. 2000;85(2):267–74.PubMedView ArticleGoogle Scholar
  104. Jiang L, Shestov AA, Swain P, et al. Reductive carboxylation supports redox homeostasis during anchorage-independent growth. Nature. 2016;532(7598):255–8.PubMedPubMed CentralView ArticleGoogle Scholar
  105. Metallo CM, Gameiro PA, Bell EL, et al. Reductive glutamine metabolism by idh1 mediates lipogenesis under hypoxia. Nature. 2011;481(7381):380–4.Google Scholar
  106. Wise DR, Ward PS, Shay JES, et al. Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability. Proc Natl Acad Sci. 2011;108(49):19611–6.PubMedPubMed CentralView ArticleGoogle Scholar
  107. Yang H, Ye D, Guan KL, Xiong Y. Idh1 and idh2 mutations in tumorigenesis: Mechanistic insights and clinical perspectives. Clin Cancer Res. 2012;18(20):5562–71.PubMedPubMed CentralView ArticleGoogle Scholar
  108. Lenting K, Verhaak R, ter Laan M, Wesseling P, Leenders W. Glioma: Experimental models and reality. Acta Neuropathol. 2017;133(2):263–82.PubMedPubMed CentralView ArticleGoogle Scholar
  109. Miroshnikova YA, Mouw JK, Barnes JM, et al. Tissue mechanics promote idh1-dependent hif1[alpha]-tenascin c feedback to regulate glioblastoma aggression. Nat Cell Biol. 2016;18(12):1336–45.PubMedView ArticleGoogle Scholar
  110. Longati P, Jia X, Eimer J, et al. 3d pancreatic carcinoma spheroids induce a matrix-rich, chemoresistant phenotype offering a better model for drug testing. BMC Cancer. 2013;13:95.PubMedPubMed CentralView ArticleGoogle Scholar
  111. Rodriguez-Enriquez S, Gallardo-Perez JC, Aviles-Salas A, et al. Energy metabolism transition in multi-cellular human tumor spheroids. J Cell Physiol. 2008;216(1):189–97.PubMedView ArticleGoogle Scholar
  112. Weinhouse S. On respiratory impairment in cancer cells. Science. 1956;124(3215):267–72.PubMedView ArticleGoogle Scholar
  113. Zu XL, Guppy M. Cancer metabolism: Facts, fantasy, and fiction. Biochem Biophys Res Commun. 2004;313(3):459–65.PubMedView ArticleGoogle Scholar
  114. Eales KL, Hollinshead KE, Tennant DA. Hypoxia and metabolic adaptation of cancer cells. Oncogene. 2016;5:e190.View ArticleGoogle Scholar
  115. Mao Y, Keller ET, Garfield DH, Shen K, Wang J. Stromal cells in tumor microenvironment and breast cancer. Cancer Metastasis Rev. 2013;32(1–2):303–15.PubMedPubMed CentralView ArticleGoogle Scholar
  116. Lau EY, Ho NP, Lee TK. Cancer stem cells and their microenvironment: Biology and therapeutic implications. Stem Cells Int. 2017;2017:3714190.PubMedPubMed CentralView ArticleGoogle Scholar
  117. Wang Y, Tadjuidje E, Pandey RN, et al. The eyes absent proteins in developmental and pathological angiogenesis. Am J Pathol. 2016;186(3):568–78.PubMedPubMed CentralView ArticleGoogle Scholar
  118. Economopoulou M, Langer HF, Celeste A, et al. Histone h2ax is integral to hypoxia-driven neovascularization. Nat Med. 2009;15(5):553–8.PubMedPubMed CentralView ArticleGoogle Scholar
  119. Okuno Y, Nakamura-Ishizu A, Otsu K, Suda T, Kubota Y. Pathological neoangiogenesis depends on oxidative stress regulation by atm. Nat Med. 2012;18(8):1208–16.PubMedView ArticleGoogle Scholar
  120. Guiet R, Van Goethem E, Cougoule C, et al. The process of macrophage migration promotes matrix metalloproteinase-independent invasion by tumor cells. J Immunol. 2011;187(7):3806–14.PubMedPubMed CentralView ArticleGoogle Scholar
  121. Wen YA, Xing X, Harris JW, et al. Adipocytes activate mitochondrial fatty acid oxidation and autophagy to promote tumor growth in colon cancer. Cell Death Dis. 2017;8(2):e2593.PubMedPubMed CentralView ArticleGoogle Scholar
  122. Correa de Sampaio P, Auslaender D, Krubasik D, et al. A heterogeneous in vitro three dimensional model of tumour-stroma interactions regulating sprouting angiogenesis. PLoS One. 2012;7(2):e30753.PubMedPubMed CentralView ArticleGoogle Scholar
  123. Moya M, Tran D, George SC. An integrated in vitro model of perfused tumor and cardiac tissue. Stem Cell Res Ther. 2013;4(Suppl 1):S15.PubMedPubMed CentralView ArticleGoogle Scholar
  124. Osterholm C, Lu N, Liden A, et al. Fibroblast ext1-levels influence tumor cell proliferation and migration in composite spheroids. PLoS One. 2012;7(7):e41334.PubMedPubMed CentralView ArticleGoogle Scholar
  125. Oudar O. Spheroids: Relation between tumour and endothelial cells. Crit Rev Oncol Hematol. 2000;36(2–3):99–106.PubMedView ArticleGoogle Scholar
  126. Kunz-Schughart LA, Heyder P, Schroeder J, Knuechel R. A heterologous 3-d coculture model of breast tumor cells and fibroblasts to study tumor-associated fibroblast differentiation. Exp Cell Res. 2001;266(1):74–86.PubMedView ArticleGoogle Scholar
  127. Sutherland RM. Cell and environment interactions in tumor microregions: The multicell spheroid model. Science. 1988;240(4849):177–84.PubMedView ArticleGoogle Scholar
  128. Ghosh S, Joshi MB, Ivanov D, et al. Use of multicellular tumor spheroids to dissect endothelial cell-tumor cell interactions: A role for t-cadherin in tumor angiogenesis. FEBS Lett. 2007;581(23):4523–8.PubMedView ArticleGoogle Scholar
  129. Wartenberg M, Donmez F, Ling FC, Acker H, Hescheler J, Sauer H. Tumor-induced angiogenesis studied in confrontation cultures of multicellular tumor spheroids and embryoid bodies grown from pluripotent embryonic stem cells. FASEB J. 2001;15(6):995–1005.PubMedView ArticleGoogle Scholar
  130. Ehsan SM, Welch-Reardon KM, Waterman ML, Hughes CC, George SC. A three-dimensional in vitro model of tumor cell intravasation. Integr Biol (Camb). 2014;6(6):603–10.View ArticleGoogle Scholar
  131. Gottfried E, Kunz-Schughart LA, Andreesen R, Kreutz M. Brave little world: Spheroids as an in vitro model to study tumor-immune-cell interactions. Cell Cycle. 2006;5(7):691–5.PubMedView ArticleGoogle Scholar
  132. Dangles V, Validire P, Wertheimer M, et al. Impact of human bladder cancer cell architecture on autologous t-lymphocyte activation. Int J Cancer. 2002;98(1):51–6.PubMedView ArticleGoogle Scholar
  133. Bingle L, Lewis CE, Corke KP, Reed MW, Brown NJ. Macrophages promote angiogenesis in human breast tumour spheroids in vivo. Br J Cancer. 2006;94(1):101–7.PubMedPubMed CentralView ArticleGoogle Scholar
  134. Perez de Heredia F, Wood IS, Trayhurn P. Hypoxia stimulates lactate release and modulates monocarboxylate transporter (mct1, mct2, and mct4) expression in human adipocytes. Pflugers Arch. 2010;459(3):509–18.PubMedView ArticleGoogle Scholar
  135. Dikov MM, Ohm JE, Ray N, et al. Differential roles of vascular endothelial growth factor receptors 1 and 2 in dendritic cell differentiation. J Immunol. 2005;174(1):215–22.PubMedView ArticleGoogle Scholar
  136. Gottfried E, Kunz-Schughart LA, Ebner S, et al. Tumor-derived lactic acid modulates dendritic cell activation and antigen expression. Blood. 2006;107(5):2013–21.PubMedView ArticleGoogle Scholar
  137. Tang X, Lucas JE, Chen JL, et al. Functional interaction between responses to lactic acidosis and hypoxia regulates genomic transcriptional outputs. Cancer Res. 2012;72(2):491–502.PubMedView ArticleGoogle Scholar
  138. Selleri S, Bifsha P, Civini S, et al. Human mesenchymal stromal cell-secreted lactate induces m2-macrophage differentiation by metabolic reprogramming. Oncotarget. 2016;7(21):30193–210.PubMedPubMed CentralView ArticleGoogle Scholar
  139. Minchinton AI, Tannock IF. Drug penetration in solid tumours. Nat Rev Cancer. 2006;6(8):583–92.PubMedView ArticleGoogle Scholar
  140. Hammond EM, Muschel RJ. Radiation and atm inhibition: The heart of the matter. J Clin Invest. 2014;124(8):3289–91.PubMedPubMed CentralView ArticleGoogle Scholar
  141. Harada H, Inoue M, Itasaka S, et al. Cancer cells that survive radiation therapy acquire hif-1 activity and translocate towards tumour blood vessels. Nat Commun. 2012;3:783.PubMedPubMed CentralView ArticleGoogle Scholar
  142. Casanovas O, Hicklin DJ, Bergers G, Hanahan D. Drug resistance by evasion of antiangiogenic targeting of vegf signaling in late-stage pancreatic islet tumors. Cancer Cell. 2005;8(4):299–309.PubMedView ArticleGoogle Scholar
  143. Riganti C, Gazzano E, Polimeni M, Aldieri E, Ghigo D. The pentose phosphate pathway: An antioxidant defense and a crossroad in tumor cell fate. Free Radic Biol Med. 2012;53(3):421–36.PubMedView ArticleGoogle Scholar

Copyright

© The Author(s). 2017

Advertisement