The role of metabolic ecosystem in cancer progression — metabolic plasticity and mTOR hyperactivity in tumor tissues

Tumor cell proliferation, survival, and migration are crucial elements in cancer progression. These processes have energy demands fueled by nutrients and metabolites sourced from additional bioenergetic mechanisms. The main metabolic pathways are connected to glycolysis and OXPHOS, preferentially using glucose as their energy source. Other properties that affect tumor survival and adaptation mechanisms include surrounding tissue microenvironment, biochemical factors, starvation, alternative nutrient utilization, and shifts in cellular metabolism. Healthy and nonmalignant cells usually produce pyruvate to fuel OXPHOS predominantly. During starvation, especially at low O₂ concentrations, anaerobic glucose utilization is preferred, and alternative substrates are directed to fuel the TCA cycle. Tumor cells have metabolic plasticity and switch dynamically between lactate-producing Warburg glycolysis and OXPHOS. Tumor cells during significant proliferation use Warburg glycolysis preferentially due to metabolic reprogramming caused by several oncogenic mutations of the signaling network. The metabolic characteristics of cells are determined by the distribution of glucose, carboxylate, or amino acid transporters and the carbon utilization of the tissue. The expression patterns of specific transporters such as GLUT1, MCT1/MCT4, CAIX, and amino acid transporters (e.g., ASCT2 — alanine/serine/cysteine transporter 2, LAT1 — large neutral amino acid transporter 1) help characterize the supplementary nutrient processes within an in situ tumor mass. GLUT1 overexpression is characteristic for several cancers in correlation with their glucose utilization. This feature is useful to detect several relapsed and metastatic tumors with in vivo imaging diagnostic tools (e.g., FDG-PET-CT) depending on the tumor type. MCTs facilitate the lactic acid exchange between the cytoplasm and extracellular space. MCT1 is expressed in all cells and assists with the transportation of lactate and pyruvate. In contrast, MCT4 expression is inducible and responsible for the exportation of lactate under hypoxic conditions, e.g., in glycolytic tissues, especially in many cancer cells.

Experimental and imaging studies have extensively analyzed the expressions of GLUT receptors, MCTs, carbonic anhydrases (CAs), and other proteins (e.g., amino acid transporters). Accordingly, tumors are classified based on their levels of protein expression (high or low levels) [134]. However, the tissue distribution of transporters in various cancers is not yet well characterized. The available results focus on scoring total protein expression (staining intensity) using only high or low categories for GLUT1, MCT1/4, and CAIX. In certain studies, the staining level and pattern were described in correlation with hypoxia, HIF1α expression, and FDG-PET-CT images in various tumor types [135]. IHC documentations demonstrate intratumoral heterogeneity; however, this phenomenon was not evaluated/scored in pathology studies and Protein Atlas documentations.

A vast literature exists about oncogene-driven alterations and the prognostic role of GLUT1 expression. These findings suggest that, in general, difference in GLUT1 expression might be a significant predictor for overall survival (OS), disease-free survival (DFS), PFS, and disease-specific survival (DSS). Poor OS correlation is associated with several cancer types, e.g., in gastric, urinary, ovarian, oral squamous cell, pancreatic, colorectal, lung, gallbladder, and esophageal carcinoma [135]. Multi-tracer characterization studies with FDG-PET-CT have resulted in the ability to show a complete representation of glucose uptake, heterogeneity, and therapy-induced metabolic adaptation of cancers. CT- and MRI-driven imaging technologies can facilitate the mapping of metabolic phenotypes and guide metabolic treatments, e.g., lung cancer [136]. GLUT inhibitors have gained attention in correlation with the growing knowledge of the glucose dependency of cancer, inflammation, and other diseases [137]. Targeting GLUT receptors or glycolysis could be an alternative option in cancer treatment, but several clinical trials were discontinued because of the reported high toxicity and severe side effects (Table 1).

Overexpression of MCT1/4 is a poor prognostic factor for various cancers, including breast, bone, colon, and renal cancers [138]. MCT1 overexpression is associated with a worse prognosis in bladder, endometrial, and clear cell renal cell cancers [139‐141] and with MCT4 in oral, colorectal, prostate, lung, and clear cell renal cell cancers (ccRCCs) [141‐146], respectively. MCT4 expression is regulated by AMPK and protein kinase C (PKC), and these signals influence metabolic adaptations via lactate shuttle under specific conditions [147].

CAs — which have 16 different isoforms — are involved in the regulation of intra- and extracellular pH; their overexpression and different localization were described in various tumors. CAIX requires special attention based on its predicted diagnostic, prognostic, and therapeutic biomarker potential in solid tumor pathology [148]. Diffuse CAIX expression, similarly to high GLUT1 and HIF1α expression, is characteristic for ccRCCs (in contrast with papillary renal clear cell carcinoma — RCC). This can help in differential diagnosis; ccRCC has lower CAIX expression [149]. On the contrary, higher expression of CAIX is correlated with poorer prognosis in the majority of breast, lung, ovarian, oral squamous, liver, and bladder cancer cells and glioblastomas [150‐156]. Considering this, CAIX could be therapeutically targeted [148]. In addition, IHC evaluation of MCT1/4 and CAIX — mainly focused on detecting higher or lower expression levels in tissues [66] — showed a correlation with hypoxia. Further research should be done to investigate tissue heterogeneity of CAIX and MCT4 expression, and its impact on the progression of solid tumors requires further analysis [157]. It was described that knockout (KO) or drug targeting of MCT1/4 inhibits the proliferation capacity both in vitro and in vivo [66]. Furthermore, these combined with metformin or phenformin [158] lead to synthetic lethality in tumor models [159]. Some effective small-molecule MCT1-specific inhibitors are in clinical trials (e.g., AZD3965), monoclonal antibodies, and small-molecule inhibitors of CAIX (SLC-0111) showing promising results. Some of these MCT1 inhibitors have entered phase II clinical trials, but the lack of isoform selectivity and potential associated toxicity necessitates designing additional, more selective drugs. Combining these with traditional chemotherapy or other metabolic targeting drugs during anticancer therapy is also being investigated [148, 149, 160] (Table 1).

Cellular uptake, transport, and the role of amino acids (as supplementary mechanisms) are well known in differentiated and proliferating cells. The primary function of amino acid metabolism is to serve protein synthesis. However, the complex metabolic coupling also supports the source of building blocks and other molecular precursors such as nucleotide, glutathione, and polyamine synthesis [161]. Furthermore, the emerging roles of non-proteinogenic amino acid metabolism in cancer should be considered. Nonessential amino acids limit tumor proliferation; in this case, the stromal and extracellular amino acids are often consumed and recycled. Amino acid restriction can be compensated by autophagy, and it could be mentioned that amino acid availability (intracellular concentrations) regulates the growth potential and influences stress responses, e.g., via mTORC1 activity [161‐163]. Based on increased amino acid demand during intensive proliferation, some nonessential amino acids (e.g., glutamine, asparagine, arginine, and cysteine) become conditionally essential. Glutamine addiction, the importance of glutaminolysis (reversible glutamine-glutamate-αKG metabolic axis), and additional “by-products” provide building blocks for fast proliferating cells. It should be considered that glutamine can be nitrogen and carbon sources in amino acid, nucleic acid, and lipid synthesis. There are several glutamine exchangers (ASCTs and Na⁺-coupled neutral amino acid transporters (SNATs)) that are often overexpressed by tumor cells (e.g., ASCT2 — SLC1A5; SNAT1 — SLC38A1, SNAT2 — SLC38A, and SNAT5 — SLC38A5) [164]. There were promising results for inhibiting tumor growth with applying ASCT2 inhibitors in gastric, prostate, lung, and breast cancers [165, 166]. However, many compensatory mechanisms were detected (e.g., SNAT1 overexpression) negating the effect of these inhibitors [167].

Therefore, the generation of novel targeted therapies and new inhibitors is under development. Many other amino acid transport (symport, antiport) mechanisms have been reported and tested in the last few decades. Serine/glycine-linked metabolic network and the related transporters can be involved in different mechanisms in cancer progression. These transports are dysregulated via epigenetic alterations (e.g., methylation) or de novo ATP synthesis. In addition, the modifications in serine-glycine extracellular level could influence the proliferation and function of cells in the immune microenvironment (T cell expansion) [168]. The transport of leucine, isoleucine, and valine — essential branched-chain amino acids — can also be upregulated in common cancers (e.g., lung, breast, and prostate). They have a role in maintaining amino acid pools in tumors [169]. Recently, small-molecule inhibitors and their derivatives have been applied as actionable targets, e.g., LAT1 (SLC7A5). Additionally, LAT1 targeted inhibitors were tested in vitro and in vivo, where decreasing leucine level and inactivation of mTORC1 are correlated with reduced tumor growth. [170]. Some of these (e.g., JPH203) have recently been introduced to clinical trials in advanced solid malignancies [171]. The de novo biosynthesis of arginine occurs in the urea cycle during ammonia detoxification. Arginine is referred to as a conditionally essential amino acid that serves as a precursor for polyamines and generates NO, creatine, and other amino acids. Additionally, arginine can be taken up by cationic amino acid transporters. Overexpression of SLC7A1 cationic amino acid transporter and its role in tumor cell survival were described in arginine-dependent breast cancers and cases with multikinase inhibitor resistance. The characterization of amino acid transporter expression and their alterations have been described in different cancers at protein and tissue levels. Limited data are available about the heterogeneous staining of LAT1, ASCT2, or other transporters. Some recent studies have combined these with in vivo PET-CT images [172, 173]. This highlights that metabolic heterogeneity could be scored by in vivo analyses and by special pathomorphological studies of these transport mechanisms in the future.

More recent attention has focused on the provision of the FA, acetate, and citrate utilization processes which have renewed interest; FA and lipids contribute to new biological membrane synthesis during the intensive proliferation of doubling cells. FA can be served by exogenous uptake and de novo synthesis. During tumor development, lipid metabolism alterations occur such as FA transport, lipid storage (e.g., LD), de novo lipogenesis, and β-oxidation–mediated energy production [174]. FA translocases (FATs), CD36, FA transport proteins (SLC27 members — FATP1-6), and other FA-binding proteins in membranes (e.g., FABPpm) have been intensively studied. These transporters were described to be overexpressed in breast, gastric, pancreatic, hepatocellular, and prostate cancers [175‐177]. It was also suggested that CD36 plays an essential role in metabolite exchange and symbiosis of the tissue microenvironment, facilitating lipid uptake of tumor cells [72, 178]. The occurrence of metastasis in visceral adipose tissue could be correlated with FA uptake and utilization. During progression, the adipose tissue generates an immunogenic inflammatory microenvironment and modulates paracrine-endocrine signals [179]. Lipid storage elevates LD formation, which dynamically contributes to lipid homeostasis by preventing lipid toxicity and providing acetyl-CoA, ATP, and NADH through β-oxidation [174]. Acetyl-CoA produced by β-oxidation from LDs assists the ATP generation in high amount via TCA cycle and electron transport chain. This process is highly effective since it gives a much higher amount of bioenergy than other mechanisms from carbohydrates. In parallel, the generated NADH is also helpful for ROS detoxification [180]. Besides lipid uptake, de novo lipid synthesis is characteristic for cancer tissues using LDs or other lipid sources [181]. The primary source is cytoplasmic acetyl-CoA from carbohydrates (through acetate and citrate) and amino acids (including glutamine), converted to FAs. Under metabolic stress (e.g., hypoxia and lipid deficit), cancer cells convert acetate and citrate using ACSS and ACLY. Additionally, acetyl-CoA carboxylases (ACCs) and FA synthase (FASN) facilitate palmitate generation in lipid synthesis.

In correlation with the importance of balanced lipid homeostasis, the complex pan-cancer analyses of the prognostic role of CD36 overexpression have been published recently and highlighted the tumor type–dependent increase in CD36 expression. Unfortunately, intratumoral heterogeneity was not evaluated in these studies; therefore, further analyses are necessary by pathologists in different tumor types and their metastases [182].

Many transport proteins and different channels are necessary to connect mitochondrial and cytosolic metabolism, providing the integrity, metabolic cargo, and maintenance of mitochondrial homeostasis. Most of the 53 mitochondrial carriers are localized in the inner mitochondrial membrane. Mitochondrial carrier family (SLC25) members are the most critical transporters; however, others such as pyruvate carriers and ABC transporters also have essential functions [183]. These amino acids, nucleotides/dinucleotides, carboxylates, ketoacids, and additional carriers use several exchange mechanisms. Pi carriers (PiC) are used for phosphorylation of ADP by ATP synthase. The overexpression of SLC25A1, mitochondrial citrate transporter, was described in primary lung cancers and their metastases, contributing to therapy resistance. SLC25A10 transports malate and succinate, which is linked to NADPH synthesis and the maintenance of redox homeostasis [184, 185]. For example, aspartate and glutamate mitochondrial carrier (SLC25A12) overexpression (via unlimited amino acid shuttle) supports aspartate utilization in hepatocellular carcinoma (HCC) [186]. Changes in mitochondrial metabolite transporter expression and their role in cancer progression correlated with ROS accumulation in central nerve system (CNS) neoplasms (overexpression of SLC25A30). On the contrary, SLC25A43 loss was detected in HER2 + breast cancers [187]. Based on these results, the alterations in mitochondrial carrier expression (see below), their potential impact on tumor growth, and inhibitor therapy are under investigation (e.g., SLC25A10 inhibitors, which disturb redox homeostasis).

Different metabolite transporters and their role in cancer progression are a current topic of interest. The expression patterns of the above-discussed transporters could expand therapeutic targets concerning the dynamic and complex adaptation mechanisms in cellular stress, altered extracellular nutrient concentration, and growing/survival demands.

There are many networks, data analysis, and IHC studies focusing on the changes in metabolic enzyme expressions, at tissue level. Most of these studies analyzed the changes (increase, decrease, or loss of some central metabolic enzymes) in various catabolic and anabolic processes (glycolysis, TCA enzymes, lipid synthesis or oxidation, amino acids, electron transport chain proteins, etc.). However, the description of staining heterogeneity in correlation with the clinical data are usually not evaluated.

Several studies describe the alterations of enzyme expression in correlation with hypoxia, increased HIF1α, and related altered tissue distribution of prolyl hydroxylases (PHDs) [188]. This highlights the role of the tissue microenvironment and its influence on metabolic alterations in various cancers and cancer progression. In situ HK2, LDHA, PKM2, PDKs, PDHs, factor inhibiting hypoxia (FIH), and different PHDs were studied in tissues over the last few decades. The upregulation of PKM2 expression, which is often associated with increased glycolytic enzymes or glucose transporters (e.g., HK2, GLUT), was described at tissue level in various cancers (e.g., in breast, lung, ovarian, bladder, colon cancers). The unfavorable prognosis (lower OS and DFS) was correlated with higher PKM2 expression, e.g., in breast, hepatocellular cancer, as well as in tongue and esophagus squamous cell carcinoma [189‐192]. In correlation with glucose utilization, elevated HK2 was recently described in patients’ biopsies of esophageal, renal, lung, cervical, colon, and breast cancers [193‐195]. The analyses of LDHA and PDK1 in situ protein expression also showed association with poor survival and therapy resistance in many malignancies (colon, breast, uterine, pancreas, lung, renal, gastric cancers, CNS malignancies, etc.). Considering the increasing serum lactate level of end-stage cachexia patients, these observations are not surprising [196‐201].

Glutamine and glutamate utilization are essential supporters of TCA fulfilling mechanisms and redox homeostasis. GLS expression and tissue distribution were also intensively examined. These studies highlight that GLS expression is often increased during metabolic adaptation in malignant progression of prostate, breast, colon, ovarian, pancreatic cancers, gliomas, rhabdomyosarcomas, etc. These could be potential targets in rare malignant cancers (e.g., sarcoma, lymphangioleiomyomatosis, or pheochromocytoma) [202‐207]. Other amino acids and their roles in metabolic network regulation are also crucial. Amino acid (e.g., leucine and arginine) sensing, transporters, carriers, and their cytoplasmic or lysosomal levels influence the intracellular anabolic and catabolic balance. This will be discussed below among mTOR activity regulation and its metabolic functions.

TCA cycle, OXPHOS, the mitochondrial electron transport chain enzymes, and their activity are also under investigation. However, their functional alterations are more common than changes in expression level. It was found that COX enzymes are overexpressed in many cancers; e.g., overexpression of COX2 is characteristic for breast, gastric, and prostate cancer; COX4/COX5B can be detected in glioma and renal and breast cancers. Additionally, increased COX2 level was described to correlate with worse prognosis in cholangiocarcinoma, gynecologic, and gastric cancers. However, there were contradictory COX expression results in other cancers (e.g., breast and cervical cancers) [208‐212] regarding the differences in metabolic rewiring (tissue-specific). The ATP synthases level in various tumor tissues suggests that lowered ATP synthase expression and the reduced mitochondrial electron transport chain activity may have a predictive role in progression and prognosis (worse outcome in ccRCC, NSCLC, and colon cancer patients) [213‐215]. An increased need for substrates places stress on the dynamic network, in which a back flux of protons can attenuate into the mitochondrial matrix (uncoupling). Mitochondrial uncoupling proteins (UCP1-5) have a role in nucleotide and FA cycling. As important mitochondrial transport mechanisms, these link mitochondrial respiration and ATP synthesis and decrease superoxide formation. UCP2-mediated metabolite antiport (aspartate, oxaloacetate, and malate) could cause special metabolism-rewiring in cancer cells which confer chemoresistance as well [216, 217]. Induction of UCP2 has been related to metabolic switch leading to accelerated glycolysis and reduced mitochondrial activity, e.g., in colon, pancreas, lung, breast, prostate, and head and neck cancers [218].

Lipids (triglycerides, phospholipids, sphingolipids, and cholesterol) can be used as an energy sources, building blocks of membrane components, and precursors for steroid hormone, bile acids, vitamins, etc. Based on these, cancer cells can completely rewire their lipid metabolism with increased de novo lipid synthesis, FA uptake, and FA oxidation and finally alter cancer-associated adipose tissues [174]. These central changes influence FA, cholesterol, arachidonic metabolism, and peroxisome proliferator–activated receptor (PPAR) signals. Elevated CD36 expression facilitates free FA uptake that supplies new membrane building and influences signaling events via activating, e.g., Wnt and TGFβ pathways [175, 176]. De novo lipid synthesis can be supported by acetyl-CoA production from glucose and glutamine via glycolysis or the truncated TCA cycle, respectively. Furthermore, hyperactivated FA synthesis is in correlation with an increased amount of crucial lipogenic enzymes (ACLY, ACC, CoA carboxylase — ACACA, FA synthase — FASN, and stearoyl-CoA — SCD). ACC and FASN are generally upregulated in growing tumors (breast, renal, gastric, colon, esophagus, lung, ovarian, prostate cancers, melanoma, gastrointestinal stromal tumors — GISTs, gliomas, etc.) [176, 219, 220]. Additionally, SREBPs activate the transcription of several enzymes participating in FA, cholesterol, and phospholipid synthesis in cancers (e.g., in NSCLC, pancreas, colon, endometrial, and breast cancers). The levels of many previously mentioned enzymes (ACLY, FASN, ACC) are increasing after SREBP1 activation propagated by PI3K/Akt/mTOR or Ras/Raf/Mek/Erk signaling pathways [221‐224]. Furthermore, some studies indicate that a high level of SREBP1 protein expression was detected in specific tumor types by IHC, which could be an independent prognostic marker in breast, thyroid, and pancreatic cancers. Carnitine palmitoyltransferases (CPTs), localized in either the inner or outer mitochondrial membranes, and carnitine-acyl transferase (CAT) support the rate-limiting steps of FA β-oxidation via FAO, which can produce a high amount of ATP. Shifts among switching on or off, the oxidation of newly synthesized FAs, or their accumulation in LDs are regulated by extracellular tissue environment and local conditions. Moreover, starving conditions can provoke autophagy both in tumors and neighboring cells [225]. PPARγ participates in storing FAs as triglycerides in lipid droplets; therefore, this mechanism could rescue the cells from the toxic increase of endogenous palmitate [226]. LDH cholesterols are also essential components for membrane building in lipid rafts. Cholesterol homeostasis is balanced by de novo synthesis, uptake, and removal; the upregulated cholesterol synthesis is influenced by SREBP2 and orchestrated by oncogenic signals (PI3K/Akt, RAS/MAPK) [227]. The prognostic value of dysregulated FA acid oxidation, synthesis, lipid homeostasis, and expression alterations of contributing metabolic enzymes are known from several IHC studies. This highlights that lipid metabolism–related enzyme expression changes could be targeted (e.g., ACC, CPT1A, ACLY, or FASN) since these alterations could correlate with patients’ prognosis [128, 202, 205, 228‐231]. Recent in situ human tumor tissue studies have investigated only some elements of these networks; therefore, its complexity is not well examined, and a deeper characterization is necessary.

In case of lipid metabolism regulation, the role of altered oncogene-addicted metabolic rewiring was described in many details. The consequences of activation and frequent mutations of RAS and other cellular signaling network elements (e.g., growth factor receptor kinases, TSC1/2, PTEN, PI3KCA in colon and breast cancers, and NSCLCs) contribute to the Erk1/2 and mTORC1/C2 hyperactivity by many steps (regulation of mitochondrial biosynthesis and lipogenesis, SREBP1 maturation) [232, 233]. Additionally, mTOR phosphorylates and inactivates lipin1 to liberate SREBP1. It is well-known that mTOR inhibitor therapies or Raptor KO decrease the expression of lipogenic enzymes FASN, ACLY, and ACC [234, 235]. Moreover, mTORC1 activation has translational effects by activating ribosomal S6K and ribosome genesis and influencing spliceosome formation [236]. The recent publications and ongoing studies suggest that mTORC2 can also affect lipogenesis. mTORC2 phosphorylates PKC isoforms, SGK1, and ACLY, therefore increasing activity of ChREBP, histone acetylation, and lipogenic gene expression in adipocytes [237]. These underline the specific regulatory role of mTOR signal activity in lipid metabolism.

Metastasis-driven cellular alterations (EMT-invasion-intravasation-extravasation-MET-metastatic growing) are cooperating in a complex manner during metastatic progression. Various molecular mechanisms influence these programs; these related cellular processes reprogram metabolic signals and regulate the expression of related enzymes. Additionally, metabolites produced by cancer cells/tissues stimulate migration, survival of circulating cells, colonization, and regrowth of tumor cells in a specific new microenvironment. Several experimental and clinical data underline the role of glycolysis (Warburg glycolytic process) in metastatic progression. In animal models, c-Src tyrosine kinase–mediated HK1/2 increase was documented in lung metastasis of colon cancers [238]. In other experiments, the silencing of HK2 reduced lung metastasis in several cancer models [239].

Moreover, the accumulation of glycolytic methylglyoxal and the glycated proteins activate EMT and migration in breast and colon cancer metastasis [240]. Increased amount and nuclear localization of PKM2 are correlated with the metastatic properties and behavior of many epithelial cancers [241]. Glycolytic lactate has additional critical regulatory functions in metastasis formation and progression (e.g., β-integrin, MCT expression alterations, or increasing MMPs). As a part of glucose usage, PPP is a primary source of NADPH that can neutralize ROS in detached and regrowing cells. In contrast, cells with lost anchorage have reduced proliferation, glucose uptake, and PPP pathway activity, increasing the ROS level. In this context, it was described that metabolic rewiring could be microenvironment-dependent in breast cancer metastasis; G6PDH and glutathione reductase levels can be increased in brain metastasis. However, in bone metastasis, the opposite is observed [242]. It was published that PPP can be upregulated in metastatic versus primary tumors in melanoma, renal, and pancreatic cancers [243]. Oxidation of glutamine, FAs, and glucose in TCA is also linked to cancer cell progression and metastasis formation [244, 245]. Glutamine and FA oxidation were described as characteristic features of specific metastatic cancer cells, e.g., melanoma, prostate, and breast cancer [246‐249].

PGC1a could have tumor type–dependent effect in mitochondrial oxidation processes: PGC1a was described as a metastatic promoter expressed in circulating breast cancer cells [250]; however, its KO could increase the invasiveness of melanoma cells through focal adhesion kinase signaling, modulating cell–cell, cell–matrix connection, and support dissemination [251]. Even in starving conditions, the low amount of ATP (bioenergy) liberated from nutrients can serve migration and invasion, protect the cells from apoptosis and immune system attacks, and promote survival in a new organ. In correlation with these, some TCA intermediates could alter epigenetic regulation. For example, it was suggested that increased αKG could play an essential role in maintaining stemness [252]. Regarding this, ketoglutarate dehydrogenase inhibition can reduce metastasis in various models [253]. These examples underline that glycolytic and mitochondrial alterations can have anti- or pro-metastatic effects, depending on the tumor type and cellular microenvironment. These strongly emphasize the role of altered metabolism during metastasis [254]. Defining the metabolic profile in various cellular states (during the metastatic cascade) could expand therapeutic targets and precision-based therapy. Based on this growing evidence, metabolic enzyme inhibitors have been tested in many preclinical and clinical studies. These ongoing studies focus on conventional treatments where metabolic adaptation could have a role in developing resistance (Fig. 5). Based on the results from these trials, therapeutic options can be successfully tailored to each patient individually using metabolic inhibitors in combination with conventional therapies. However, undesirable side effects from combined treatment require special care by clinicians.

The two functionally and structurally different mTOR complexes (mTORC1 and mTORC2) consist of two common proteins, mTOR serine/threonine kinase, and mLST8. The specific subunits are composed of unique scaffold proteins, Raptor in mTORC1 and Rictor in mTORC2, respectively. The mTORC2 complex has additional elements such as mSIN1, MAPK-interacting protein 1, which determine the subcellular localization of the complex and help in substrate recruitment. Additionally, the endogenous common inhibitory protein (DEPTOR) can bind and inhibit mTOR kinase in both complexes, while PROTOR1/2 can associate with Rictor and inhibit mTORC2 specifically [267]. Crystallographic analysis revealed that dimerized protein complexes have different structures in different cellular localizations (membrane, lysosomes, endoplasmic reticulum — ER, etc.). These offer binding sites for several other regulators (Rheb GTPase), substrates, and protein complexes [268]. mTOR complexes integrate different external and internal information (signals) based on monitoring cellular stress conditions; these influence “cellular decisions” (proliferation/differentiation or growth/survival). These decisions are assisted by mTOR-related signaling crosstalk, networking with many pathways, cellular state sensing, feedback, and feed-forward regulatory mechanisms [269].

The environment and the actual condition of cells influence the cellular programs and functions. mTORC1 and mTORC2 complexes integrate several signals, including growth factors, nutrients, starving conditions, energy, and stress levels, to regulate their activity. mTORC1 should “turn on and off” in correlation with cellular bioenergetics, genome integrity status, energy, O₂, and growth factor levels [264]. To monitor bioenergetics and the activity of growth signals, two small G protein families, the Rheb and Rag GTPases, alter mTOR kinase phosphorylation status, activity, and the cytoplasmic/lysosomal localization of mTORC1 complex [270]. Signals of cytokines and endocrine hormones maintain Rheb in active GTP-bounded forms and determine the lysosomal localization of Rheb. The translocation of the mTORC1 complex to lysosomes mainly depends on the presence of amino acids and glucose. Their appropriate concentrations activate Rag GTPases and induce lysosomal localization of the mTORC1 complex [271]. Adequate levels of lysosomal cholesterol and arginine influence the lysosomal sensor (SLC38A9) and generate the activity of Rag GTPases [272]. GATOR1 usually shifts to mTORC1-Rag-GDPs; therefore, inhibited GATOR1 serves the RagA/B-GTP isoform and localization of mTORC1 to the lysosome [273, 274]. Additionally, GATOR1 functions can be inhibited by the folliculin sensor (high total amino acids level) and GATOR2 amino acid sensors (high level of arginine and leucine). Low levels of leucine, arginine, and their metabolites can activate Sestrin1/2/3, SAMTOR (S-adenosyl methionine regulator), and SARB1, leading to the inhibition of GATOR2. Therefore, active GATOR1 shifts RagC/D to GDP-bound forms, and mTORC1 loses the lysosomal membrane localization [275‐277]. Moreover, lowering amino acids through Sestrin1/3 can alter the expressions of uncoupling proteins which switch off mTORC1 activity amino acid sensor pathways, independently [278]. This nutrient and growth factor sensor regulation provides the balance between anabolism and catabolism depending on nutrient conditions. Additionally, the mTOR activating function of lysosomal Rheb GTPases is negatively regulated by TSC1/2. The inhibitory effect of TSC1/2 can be maintained (reactivated) by hypoxia, energetic stress (e.g., low glucose and ATP level) — AMPK activation, DNA damage, or Wnt signaling. However, it can be suspended by several growth factors (e.g., IGFR, EGFR) [279‐281].

To date, the regulation of mTORC2 complex activity has been less described. Usually, the mTORC2 complex is positively regulated by growth factors mediated by PI3K pathway [282]. mSIN1 pleckstrin domain autoinhibits mTORC2 activity; this can be released by insulin- or serum-induced PI3K activation and increased PIP3. After these alterations, PIP3, mTORC2, and Akt are recruited into the cell membrane. mTORC2 is mainly active in the plasma membrane, but its active forms were also detected in the outer mitochondrial membrane and endosomes [283]. Evidence showed that growth factors regulate mTORC2; however, amino acids and other metabolites could also have some regulatory effects. Several new data highlighted that Rac1, Rap1, and Ras GTPases had potential roles in mTORC1 and mTORC2 activation and membrane localization processes in the last few years. These, especially oncogenic Ras, can directly induce mTORC2 kinase activation, promoting proliferation, and cell survival, which are associated with poor patient outcomes [284]. It was reported that lowered glutamine concentration can activate mTORC2 and modulate glutamine homeostasis by increasing glutamine-fructose 6 phosphate amidotransferase 1 and cellular catabolism [285]. mTORC2 complex activity can also be regulated through Rictor phosphorylation and acetylation. For example, GSK3 phosphorylates Rictor, initiating the FBXW7 ubiquitin–proteasome degradation of Rictor. It was also described that Rictor acetylation increases mTORC2 activity. Additionally, glucose stress and starvation activate AMPK, increasing mTORC2 activity in cells (instead of inhibiting mTORC1). These mechanisms underline the importance of mTORC2 functions in cell survival mechanisms under the conditions of starvation and acute bioenergetic stress (Fig. 6).

“mTOR controls almost everything” — this statement highlights that mTOR plays crucial roles as it not only promotes cellular growth by stimulating proteins and initiates the synthesis of building blocks (from various sources: nucleotides and lipids) but inhibits autophagy as well.

The switch from anabolism to catabolism and vice versa is primarily regulated by mTORC1 activity. For example, in in vitro cell cultures, the growing cells are bathed in nutrients (growth factors, glucose, and proteins). In correlation with this, tumor cell lines have higher mTOR activity than their original in vivo tumor tissue counterparts (xenograft or human cancers in situ). However, in in vivo tumors, the fluctuation between fasting and feeding and the deregulated mTOR cause metabolic alterations under various environmental conditions [286, 287]. Several data confirm the importance of mTORC1-dependent metabolic regulatory functions in the whole organ and organism as well. After a 24-h fasting period in mouse models, it was observed that liver cell mass was reduced by 25% mTORC1 dependently (in case of Raptor KO mice, this reduction did not occur) [288]. Additional experiments described that mTORC1 activity delays autophagy under perinatal fasting conditions. The disturbance of these pathways results in uncompensated glucose reduction and mortality in animal models [289]. Moreover, hundreds of results underline the central role of mTORC1 in dysregulated metabolic signaling during overfeeding, obesity, and type II diabetes. It is not surprising that mTOR inhibitory treatments could decrease symptoms of obesity and diabetes [233]. mTORC1 activity is a well-known promoter of cellular protein, nucleotide, and lipid synthesis. These are in correlation with the already described effector mechanism of mTORC1: (a) phosphorylates eukaryotic initiation factor 4E–binding proteins (4EBP1) releasing eIF4E and enhances cap-dependent mRNA translation; (b) phosphorylates p70 S6 kinase 1 (S6K1) and subsequently ribosomal S6, which enhances the translational efficiency by influencing the expression and function of several ribosomal proteins (SKAR, RNA polymerases) and protein synthesis [290‐292]; (c) phosphorylates and inactivates lipin1 and induces the translocation of SREBP1 from ER to the nucleus in an S6K1-dependent manner, initiating the expression of enzymes in lipid and cholesterol syntheses [293]; (d) phosphorylates ATF4 (activating transcription factor 4) and consequently induces MTHFD2 (mitochondrial tetrahydrofolate dehydrogenase) enhancing purine biosynthesis [294]; (e) phosphorylates and activates carbamoyl phosphate synthase (CAD), the rate-limiting enzyme in pyrimidine synthesis [295]; (f) influences several further transcription factors regulating hypoxia, energetic stress responses, or lysosomal biogenesis (HIF1α, PGC1a, TFEB) [296]. In parallel, mTORC1 activity decreases the catabolism in tumor cells by inhibiting the phosphorylation of autophagosome proteins ULK1 kinase and Atg13 autophagosome compartments, arresting autophagosome functions, and inducing autophagosome accumulation. Furthermore, it inhibits autophagosome maturation through phosphorylating other proteins by reducing lysosome biogenesis (UVRAG, Rab7, TFEB, TF3) [297, 298].

mTORC2 complex has been less characterized. However, its effector mechanisms were described in correlation with kinase activity, phosphorylation of AGC kinases, Akt, PKC members, and SGK1. The best-characterized kinase activity of mTORC2 is Ser473-Akt phosphorylation which is complex and context-dependent. The Ser473-Akt phosphorylation is required to phosphorylate some additional Akt substrates, including PRAS40, FOXO1/3a, and TSC2. It was suggested that this Ser473 phosphorylation is more critical for maximal activity of Akt than substrate specificity. Other phospho-Akts (Ser477, Thr479) resulting from mTORC2 induce the degradation of IRS1 by stabilizing FBW8 ubiquitin ligase activity [299]. mTORC2 is also stated to promote ACLY phosphorylation which increases ChREBP activity and influences histone acetylation [237]. mTORC2-mediated Akt phosphorylation could further promote c-Myc expression and, in turn, increase glycolytic HK2 expression and glucose-6-phosphate level. PKC phosphorylation by mTORC2 was suggested to regulate actin polymerization, which could orchestrate EMT, migration, and metastatic events [300]. Moreover, TGFβ, Wnt, and YAP/Hippo can also activate mTORC2, which could influence EMT-associated migration and invasion [282]. In a mouse model study, the role of mTORC2 in lipid metabolism was also highlighted. This detailed analysis confirmed mTORC2-mediated promotion of FA and lipid metabolism (sphingolipid and cardiolipin biosyntheses), causing steatosis and tumor development in the liver. Regarding these results, elevated mTORC2 and correlated lipogenesis were detected in human HCC cases. Besides the well-known regulatory functions of mTORC1 in autophagy, mTORC2 activity influences SGK-1– and Akt-mediated alterations of autophagy-related proteins (Atg7, beclin-1, FOXO3, VDAC1, etc.). In correlation with this autophagy regulating function the inactivation of mTORC2 and lowered SGK-1 activity, disrupting the autophagy and the normal differentiation in an animal model (Caenorhabditis elegans) [301, 302] (Fig. 6).

mTOR hyperactivity has multifunctional tumor growth–promoting effects. High mTOR activity (both complexes) through a broad spectrum of mechanisms contributes to cellular adaptation. mTOR hyperactivity has a central regulatory role in integrating complex pathway networks, especially in adaptation to bioenergetic demands and survival of migrating cells which can metastasize and be reactivated at distant sites. Therefore, it is not surprising that mTORC1 and mTORC2 complex overexpression and hyperactivity were described in many cancers, especially in patients with unfavorable prognoses [303, 304].

Higher mTOR activity scores are associated with a worse prognosis in several tumor types (metastasis, leading to metastasis-related cancer mortality). During cancer progression, malignant cells lose their adherence capacity, gain invasive nature, survive under extreme conditions (e.g., in circulation), spread, and find new sites to form additional tumors. Tumor cells need to adapt to the new microenvironment and rearrange their resources, dependencies, and cellular connections during all these steps. Therefore, the mTOR activity–provided EMT-MET could contribute to the migratory and invasive potential of tumor cells in the metastatic cascade. Several publications confirmed that small GTPases support actin-cytoskeletal rearrangement, migration, and invasion. The contribution of mTOR signaling elements was described in correlation with TGFβ-mediated protein expression changes of EMT. Based on this observation, rapamycin can inhibit the TGFβ-dependent PI3K/Akt/mTOR activation and influence the migratory and invasive features of cancer cells. It was also described that mTORC2 complex–mediated functions are required in EMT, migration, and metastasis [305]. In prostate cancer, Rho and Rac1 GTPases were proposed to be regulated by mTOR [306]. Additionally, dual mTOR inhibitors were shown to arrest hypoxia- and TGFβ-mediated EMT in cancer cell lines. Besides these effects, mTOR activity–dependent alterations can induce protein expression (e.g., that of BMP2 and Sestrin2) and promote EMT and metastasis in different cancer models (ovarian, nasopharyngeal, pancreatic cancer, NSCLC, and HCC) [307]. Both mTORC1 and mTORC2 could contribute to modifying the metastatic properties of cells. It was described that IGF induces mTOR/Raptor/S6K1–dependent F-actin reorganization and phosphorylation of focal adhesion protein [308]. It was also published that the knockdown of mTOR/Rictor/mLST8 resulted in malformation of F-actin fibers and prevented paxillin phosphorylation, leading to the recruitment of focal adhesion complexes in starved fibroblasts [309‐311]. The dynamics of cytoskeleton reorganization were found to be mediated by mTOR, mTORC2 via the Rho family of small GTPases (Rho A, Cdc42, and Rac1) in RH30 and HeLa cells. It was also proposed that mTORC2 controls the migration of neutrophils via Rac/Cdc42 [312, 313]. Recently, it was confirmed that mTOR KO caused dis-morphogenesis (documented by morphology analyses) in correlation with actin synthesis and assembly (F-actin and Cdc42 expression) in tooth epithelia [313].

Genetically modified Rictor expression influences the metastasis formation of HER2 overexpressing mouse breast cancers. The studied metastasis model system documented that mTORC2 can activate Rac1 into two ways, either via decreasing the expression of RhoGDI2 inhibitor by PKCa or via Akt-activated Rac-GEF Tiam1 [314]. Additionally, data obtained from mTOR/Rictor/PKCa silencing studies confirmed the role of mTORC2 in PKCa-mediated actin filament organization [315]. Following these results, mTOR inhibitor therapy decreases cell motility and metastatic potential in several preclinical and clinical studies (OS and DFS studies were performed).

Receptor tyrosine kinases (EGFR, HER2, PDGFRa, and FGFR in colorectal, breast, head and neck, gastric cancer, NSCLC, glioblastomas, GISTs, melanoma, etc.), PI3KCA and RAS mutation-mediated PI3K hyperactivity, as well as the loss of PTEN or TSC1/2, leading to mTOR hyperactivity in many cancers. Additionally, amplification and mutations of mTOR kinase and Rictor could also influence mTOR deregulation in cancers. PI3KCA, AKT1, PTEN, TSC1/2, or LKB1 modifications and PI3KCA alterations are frequently described in breast (> 20%), colon, and gynecologic cancers. PTEN mutations occur in colorectal cancers and about 10% of central nervous system malignancies. TSC1/2 loss can be detected in 4–6% of endometrial, urothelial, cervical, liver, and lung cancers. On the contrary, loss-of-function mutations occur less frequently in the prostate, endometrium, breast cancers, melanomas, glioblastomas, and renal cancers (in less aggressive hamartomas, rhabdomyoma, and angiofibroma). The deregulation of these growth signaling pathways correlates with mTOR hyperactivity. mTOR mutations and RICTOR amplification are among the most significant and frequent oncogenic mutations. Approximately, 5% of solid cancers carry disease-related mTOR kinase activating mutations (e.g., in melanomas, colon, renal, lung, endometrial, and gastric cancers) (Fig. 7). The importance of RICTOR amplification and overexpression was described in small cell lung (SCLC), breast, gastric, and head and neck cancers [316‐319]. As a result of cellular signaling network–related oncogenic alterations, increased mTOR activity can be detected in ~ 80% of human malignancies. Consequently, mTOR hyperactivity and its outcome on a cellular level can influence the therapeutic sensitivity and progression (in a tumor type–dependent manner). mTOR hyperactivity can overwrite the metabolic checkpoints, contributing to cancer growth nutrient and growth factors independently.

Studying the mTOR hyperactivity of malignancies at the protein level was initiated in 1998. Studies examined p-mTOR and p-p70S6K proteins in malignant cell lines were initially conducted by Western blot analyses [320]. The development of phospho-protein antibodies and further examination of mTORC1 and mTORC2 targets could be possible with in situ characterization of human biopsy materials (formalin-fixed tissues).

Experimental data found that the pattern of mTOR hyperactivity could be altered at the tissue level during therapy [321]. Additionally, the progression and metastatic potential and the preference of metastatic sites were analyzed in correlation with mTOR hyperactivity in different cancers [322]. However, higher mTOR activity was described in many various cancers; the in situ staining pattern (heterogeneity) and the mTORC1/C2 complex distribution were not studied in detail. More precise analyses of tissue and mTORC1/C2 complex–related mTOR activity distribution, special markers, the use of well-defined complex scoring systems, and excellent pathologists are required. Moreover, active (phosphorylated) forms of mTOR kinase, other mTORC1, and mTORC2-specific elements (e.g., Raptor and Rictor) and active forms of mTOR complex target proteins (p-S6K1, p-4EBP1, pS6, p-Ser473-Akt, p-SGK1, etc.) must be analyzed.

Many studies on mTOR hyperactivity and its correlation with prognosis have been published; however, mTORC1 and mTORC2 complex distribution and additional metabolic regulatory proteins and their correlation with tumor progression have been less studied [323]. In these studies, strict conclusions were not possible due to lower case numbers, a broad diversity of tumor subtypes (with higher incidence), and intertumoral differences. In the early 2010s, our and others’ results confirmed that elevated mTOR activity is characteristic for human lymphoma and leukemia cells. Based on IHC and flow cytometry data, higher mTOR activity, especially in the presence of a high amount of mTORC2 complex, was correlated with worse prognosis and lower OS in lymphoma/leukemia patients [324‐327].

In the case of solid tumors, similar observations were published in the last decade. For example, almost all of the published studies underline the role of mTOR hyperactivity in the progression and metastasis formation in hormone receptor–positive (HR +) or triple-negative (TN) breast cancers. Recent preclinical studies described that mTORC1 and mTORC2 inhibition could have significant growth inhibitory effects in these malignancies [328‐330]. Moreover, in some reports, it was also highlighted that high mTOR activity could be associated with the presence of metabolic plasticity (higher expression level of alternative metabolic enzymes at tissue level, e.g., simultaneously increased expressions of LDHA, GLS, and carnitine palmitoyltransferase 1A — CPT1A) in breast and other cancers [128, 202, 331‐333]. Our findings suggest that metabolic plasticity (high mTOR activity and the overexpression of at least two alternative metabolic pathway–related enzymes) could be a subtype-independent risk factor in breast cancers, certain lung tumors rhabdomyosarcomas, and pheochromocytomas [128, 207, 334, 335]. In general, mTOR hyperactivity and the expression of mTORC2 complex elements were analyzed and characterized in correlation with prognosis and metastasis of other malignancies. Most of these results confirm the significant role of mTOR hyperactivity in malignant progression.

The site-specific metastatic progression was suggested to be influenced by mTORC1 and mTORC2 activity in liver, lung, bone, brain, colon, breast, and pancreatic cancers or melanomas. The incidence of PIK3CA mutations, the activation of PI3K/Akt/mTOR signaling axis, and, in correlation with these, the increased mTORC2 activity (p-Ser473-Akt)–related HER2 expression were found to be involved in the liver metastases of breast cancers, which are occurring more frequently [336]. However, another study emphasized the potential role of PI3K/Akt/mTOR axis hyperactivity in brain metastases of melanomas. mTOR-related hyperactivity correlated with metastases of other cancers was reported in a few lower case number studies (e.g., breast, lung, and renal carcinomas) [334, 337]. There is a strong correlation between high mTOR activity and poor prognosis, significantly increasing mTORC2 complex expression analyzed by IHC follow-up studies.

Regarding these observations, Rictor overexpression results and RICTOR amplification were found to negatively influence the progression of different cancers [304]. This could help in patient selection for mTORC1 and mTORC2 or dual inhibitor therapies (Table 2). Several experimental studies described that dual inhibitors could reduce brain metastasis formation and growth of PI3KCA-mutated cancers [338]. Additionally, in colon carcinomas and highly aggressive pancreatic cancers, dual mTOR inhibitors could reduce the occurrence of liver and lung/liver metastases, respectively [339].

Based on these results and the detected high mTOR activity in many cancers, mTOR inhibitor therapies have been tested in highly metastatic and aggressive cancer types characterized by high mTOR activity (e.g., pancreas, relapsed HER2 + , and TN breast cancers, EGFRI-resistant or cisplatin-, radiotherapy-resistant cancers). mTORIs have been approved in the therapy of renal cancers; mantle cell lymphomas; advanced breast cancers (hormone receptor–positive); pancreatic, gastrointestinal, and pulmonary neuroendocrine cancers; and sporadic lymphangioleiomyomatosis. Despite the correlation between high mTOR activity and worse prognosis, it might be surprising that clinical phase trials usually have lower beneficial therapeutic outcomes; mTORIs also have a lower success rate in monotherapy. Therefore, better mTOR and more specific mTORC1 and mTORC2 inhibitors are needed to be developed. Next-generation mTOR inhibitors include dual mTOR and ATP competitive mTOR kinase inhibitors (2nd generation) [340]. The 3rd-generation new synthetic mTOR (e.g., JR-AB2-011, RapaLinks) and specific mTORC2 complex inhibitors (Rictor si-NPs: nanoparticles harboring Rictor siRNA sequences) are under preclinical and clinical investigations [330, 340]. Additionally, more and more mTOR and PI3K/Akt/mTOR pathways inhibiting natural compounds have been discovered and tested in clinical trials. For example, indole-3-carbinol (an alkaloid from Brassica genus — NCT00579332), berberine (an alkaloid from European barberry — NCT03281096, NCT02226185), curcumin (diarylheptanoid from Curcuma genus — NCT03769766), epicatechin and other catechins (flavonoids from green tea — NCT02029352), and genistein (isoflavone from soybean — NCT00584532) are in phase III trials, and these have favorable results and are available as dietary supplements. Many different PI3K/Akt/mTOR inhibitors have been under development in clinical trials. These all have promising effects in preclinical studies (Table 3). Unfortunately, the application of mTORI monotherapy has often lower final survival advantages than expected, as is the unfortunate case of targeted monotherapies in general. Therefore, the selection of optimal partner drugs needs to be considered for achieving more effective combination therapies. The combination of mTORIs with targeted or traditional chemotherapeutics/radiotherapy could be applied and initiated in clinical trials (Table 4). However, the possible higher toxicity could limit the success of these combined treatments. Based on the highlighted role of metabolic profiles, other antimetabolic drugs with traditional therapies or mTORIs should be considered to find additional therapeutic options. Some new preclinical studies highlight that mTORIs combined with metabolic (e.g., GLS, OXPHOS, lipid metabolism) inhibitors could have additive or synergistic effects on tumor growth in advanced cancer, in in vitro and in vivo models [341‐343].

Such combined antimetabolic treatments can induce synthetic lethality [389]. For example, inhibiting both OXPHOS and glycolysis (e.g., with metformin + 2-deoxy-D-glucose/GLUT/MCTI) can effectively induce the collapse of balanced energy metabolism, which was detected to be effective in many different cell line and xenograft models (e.g., breast, prostate, ovarian, and hepatocellular cancers) [159, 390, 391]. In the case tumors depend on glutamine utilization and anaplerosis, this metabolic rewiring provides a potential opportunity for rational dual targeting of glutaminolysis and glycolysis. Simultaneous glutaminolysis blockade with CB-839 and 3-bromopyruvate (3BP) could also induce tumor regression in the renal cancer model [392]. These preclinical combination studies initiated a phase I study using ritonavir and metformin in the management of multiple myeloma and chronic lymphocytic leukemia (CLL) (NCT02948283). Further preclinical data and key clinical trials using metabolic inhibitors are available; including mTORIs combined with conventional tumor type–dependent and targeted therapy (including immune checkpoint inhibitor therapy) [393]. There are several promising preclinical observations regarding the potential use of antimetabolic (OXPHOS or glutamine metabolism inhibitors) and targeted kinase inhibitory therapy in various cancer types (e.g., melanoma, GIST, etc.) (NCT03026517, NCT03831932) [394‐396]. These have propagated further clinical studies (lung RCC NCT03158324, NCT03071705, and NCT02071862). According to this promising preclinical data, early-phase trials of rapalog and metformin combinations were set off. These suggest that further examinations of temsirolimus and metformin is necessary since this combination reported good tolerance and promising effects in advanced cancers (NCT01529593, NCT03163667, and NCT00659568). Moreover, immune checkpoint inhibitors or other monoclonal antibody therapies promoted the attempts of glutamine utilization inhibitor (including mTORIs) combinations with pembrolizumab, nivolumab, or daratumumab in advanced solid cancers (NCT04265534 and NCT02771626) [397]. Other agents and drugs (e.g., antibiotics, cardiovascular drugs, antidepressants) [398] with antimetabolic (off-target) properties can be applied in an off-label use in these combinations in future studies [399‐401].

All these data suggest that there is an urgent need to clarify the role of metabolic adaptations in tumor resistance, with respect to recently used therapies (metabolic rewiring at tissue level). Future implications in this field of research are to expand the clinically available metabolic targets (drugs) to improve the response rate and patient survival in recently used treatments.