The high-grade brain malignancy, glioblastoma multiforme (GBM), is one of the most aggressive tumours in central nervous system. The developing resistance against recent therapies and the recurrence rate of GBMs are extremely high. In spite several new ongoing trials, GBM therapies could not significantly increase the survival rate of the patients as significantly. The presence of inter-and intra-tumoral heterogeneity of GBMs arise the problem to find both the pre-existing potential resistant clones and the cellular processes which promote the adaptation mechanisms such as multidrug resistance, stem cell-ness or metabolic alterations, etc. In our work, the in situ metabolic heterogeneity of high-grade human glioblastoma cases were analysed by immunohistochemistry using tissue-microarray. The potential importance of the detected metabolic heterogeneity was tested in three glioma cell lines (grade III-IV) using protein expression analyses (Western blot and WES Simple) and therapeutic drug (temozolomide), metabolic inhibitor treatments (including glutaminase inhibitor) to compare the effects of rapamycin (RAPA) and glutaminase inhibitor combinations in vitro (Alamar Blue and SRB tests). The importance of individual differences and metabolic alterations were observed in mono-therapeutic failures, especially the enhanced Rictor expressions after different monotreatments in correlation to lower sensitivity (temozolomide, doxycycline, etomoxir, BPTES). RAPA combinations with other metabolic inhibitors were the best strategies except for RAPA+glutaminase inhibitor. These observations underline the importance of multi-targeting metabolic pathways. Finally, our data suggest that the detected metabolic heterogeneity (the high mTORC2 complex activity, enhanced expression of Rictor, p-Akt, p-S6, CPT1A, and LDHA enzymes in glioma cases) and the microenvironmental or treatment induced metabolic shift can be potential targets in combination therapy. Therefore, it should be considered to map tissue heterogeneity and alterations with several cellular metabolism markers in biopsy materials after applying recently available or new treatments.

Despite advancements in cancer management, tumor relapse and metastasis are associated with poor outcomes in many cancers. Over the past decade, oncogene-driven carcinogenesis, dysregulated cellular signaling networks, dynamic changes in the tissue microenvironment, epithelial-mesenchymal transitions, protein expression within regulatory pathways, and their part in tumor progression are described in several studies. However, the complexity of metabolic enzyme expression is considerably under evaluated. Alterations in cellular metabolism determine the individual phenotype and behavior of cells, which is a well-recognized hallmark of cancer progression, especially in the adaptation mechanisms underlying therapy resistance. In metabolic symbiosis, cells compete, communicate, and even feed each other, supervised by tumor cells. Metabolic reprogramming forms a unique fingerprint for each tumor tissue, depending on the cellular content and genetic, epigenetic, and microenvironmental alterations of the developing cancer. Based on its sensing and effector functions, the mechanistic target of rapamycin (mTOR) kinase is considered the master regulator of metabolic adaptation. Moreover, mTOR kinase hyperactivity is associated with poor prognosis in various tumor types. In situ metabolic phenotyping in recent studies highlights the importance of metabolic plasticity, mTOR hyperactivity, and their role in tumor progression. In this review, we update recent developments in metabolic phenotyping of the cancer ecosystem, metabolic symbiosis, and plasticity which could provide new research directions in tumor biology. In addition, we suggest pathomorphological and analytical studies relating to metabolic alterations, mTOR activity, and their associations which are necessary to improve understanding of tumor heterogeneity and expand the therapeutic management of cancer.

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

BackgroundGlioma is the most common highly aggressive, primary adult brain tumour. Clinical data show that therapeutic approaches cannot reach the expectations in patients, thus gliomas are mainly incurable diseases. Tumour cells can adapt rapidly to alterations during therapeutic treatments related to their metabolic rewiring and profound heterogeneity in tissue environment. Renewed interests aim to develop effective treatments targeting angiogenesis, kinase activity and/or cellular metabolism. mTOR (mammalian target of rapamycin), whose hyper-activation is characteristic for many tumours, promotes metabolic alterations, macromolecule biosynthesis, cellular growth and survival. Unfortunately, mTOR inhibitors with their lower toxicity have not resulted in appreciable survival benefit. Analysing mTOR inhibitor sensitivity, other metabolism targeting treatments and their combinations could help to find potential agents and biomarkers for therapeutic development in glioma patients.MethodsIn vitro proliferation assays, protein expression and metabolite concentration analyses were used to study the effects of mTOR inhibitors, other metabolic treatments and their combinations in glioma cell lines. Furthermore, mTOR activity and cellular metabolism related protein expression patterns were also investigated by immunohistochemistry in human biopsies. Temozolomide and/or rapamycin treatments altered the expressions of enzymes related to lipid synthesis, glycolysis and mitochondrial functions as consequences of metabolic adaptation; therefore, other anti-metabolic drugs (chloroquine, etomoxir, doxycycline) were combined in vitro.ResultsOur results suggest that co-targeting metabolic pathways had tumour cell dependent additive/synergistic effects related to mTOR and metabolic protein expression patterns cell line dependently. Drug combinations, especially rapamycin + doxycycline may have promising anti-tumour effect in gliomas. Additionally, our immunohistochemistry results suggest that metabolic and mTOR activity alterations are not related to the recent glioma classification, and these protein expression profiles show individual differences in patients’ materials.ConclusionsBased on these, combinations of different new/old drugs targeting cellular metabolism could be promising to inhibit high adaptation capacity of tumour cells depending on their metabolic shifts. Relating to this, such a development of current therapy needs to find special biomarkers to characterise metabolic heterogeneity of gliomas.

Monolayer cultures, the less standard three-dimensional (3D) culturing systems, and xenografts are the main tools used in current basic and drug development studies of cancer research. The aim of biofabrication is to design and construct a more representative in vivo 3D environment, replacing two-dimensional (2D) cell cultures. Here, we aim to provide a complex comparative analysis of 2D and 3D spheroid culturing, and 3D bioprinted and xenografted breast cancer models. We established a protocol to produce alginate-based hydrogel bioink for 3D bioprinting and the long-term culturing of tumour cells in vitro. Cell proliferation and tumourigenicity were assessed with various tests. Additionally, the results of rapamycin, doxycycline and doxorubicin monotreatments and combinations were also compared. The sensitivity and protein expression profile of 3D bioprinted tissue-mimetic scaffolds showed the highest similarity to the less drug-sensitive xenograft models. Several metabolic protein expressions were examined, and the in situ tissue heterogeneity representing the characteristics of human breast cancers was also verified in 3D bioprinted and cultured tissue-mimetic structures. Our results provide additional steps in the direction of representing in vivo 3D situations in in vitro studies. Future use of these models could help to reduce the number of animal experiments and increase the success rate of clinical phase trials.