Integrating the Tumor Microenvironment into Cancer Therapy

cancers Review Integrating the Tumor Microenvironment into Cancer Therapy Sabina Sanegre 1,†, Federico Lucantoni 1,†, Rebeca Burgos-Panadero 1,2, Luis de La Cruz-Merino 3, Rosa Noguera 1,2,* and TomásÁlvaro Naranjo 2,4,5,* 1Department of Pathology, Medical School, University of Valencia—INCLIVA Biomedical Health Research Institute, 46010 Valencia, Spain; ssanegr[email protected] (S.S.); [email protected] (F.L.); [email protected].es (R.B.-P.) 2Low Prevalence Tumors, Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto de Salud Carlos III, 28029 Madrid, Spain 3Department of Oncology, Hospital Universitario Virgen Macarena, 41009 Seville, Spain; [email protected] 4Department of Pathology, Hospital de Tortosa Verge de la Cinta, Catalan Institute of Health, Institut d’InvestigacióSanitària Pere Virgili (IISPV), 43500 Tortosa, Spain 5Department of Morphological Science, Medical School, Rovira i Virgili University, 43201 Reus, Spain *Correspondence: [email protected] (R.N.); talvaro.ebr[email protected] (T.Á.N.); Tel.: +34-2304-977519104 (T.Á.N.) †These authors contributed equally to this work. Received: 18 May 2020; Accepted: 18 June 2020; Published: 24 June 2020   Abstract: Tumor progression is mediated by reciprocal interaction between tumor cells and their surrounding tumor microenvironment (TME), which among other factors encompasses the extracellular milieu, immune cells, fibroblasts, and the vascular system. However, the complexity of cancer goes beyond the local interaction of tumor cells with their microenvironment. We are on the path to understanding cancer from a systemic viewpoint where the host macroenvironment also plays a crucial role in determining tumor progression. Indeed, growing evidence is emerging on the impact of the gut microbiota, metabolism, biomechanics, and the neuroimmunological axis on cancer. Thus, external factors capable of influencing the entire body system, such as emotional stress, surgery, or psychosocial factors, must be taken into consideration for enhanced management and treatment of cancer patients. In this article, we review prognostic and predictive biomarkers, as well as their potential evaluation and quantitative analysis. Our overarching aim is to open up new fields of study and intervention possibilities, within the framework of an integral vision of cancer as a functional tissue with the capacity to respond to different non-cytotoxic factors, hormonal, immunological, and mechanical forces, and others inducing stroma and tumor reprogramming. Keywords: immune therapy; metabolism; microbiota; biomarker discovery; prognostic tools; vitamin D3; stromal reprogramming; mitochondria; mechanotransduction; metformin 1. Introduction Since the 1980s, cancer research has focused on developing new therapeutic agents targeting DNA alterations and the search for a suitable cure, rather than understanding cancer as an integrated system composed of several modules. To date, the ability of cancer cells to survive for a prolonged time is still incompletely understood. In this context, we are beginning to include the role of stem cells in the tumor evolution process and to point out cellular pathways as a physiological adaptive process like a “wound that never heals” [ 1 ]. The idea that cancer originates as a consequence of a malignant Cancers 2020,12, 1677; doi:10.3390/cancers12061677 www.mdpi.com/journal/cancers Cancers 2020,12, 1677 2 of 24 cellular development can be considered in a multi-level framework where different processes such as senescence, regeneration, wound healing and proliferation play a key role. The majority of tumors have a heterogeneous cellular population, and the vision that cancer originates from clonogenic expansion from a single mutated cell could be classed as simplistic and inexact. Microscopic observation of tumors reveals a multicellular 3-dimensional complex tissue underlying developmental alterations and a variable degree of morphological, immunophenotypic, and genomic heterogeneity. Indeed, the strategy used until recently of targeting one gene/protein/process at a time has proved unsuccessful. The Cancer Genome Atlas (TCGA), a public repertoire of genomic, epigenomic, transcriptomic and proteomic data, available to anyone in the research community, that leads to improvements in the ability to diagnose, treat and prevent cancer, represents a remarkable feat [ 2 ]; however, every tumor shows several mutations in the genome, and with current knowledge, the search for drug candidates for each mutation seems unfeasible. Indeed, even the most clinically-promising drugs, such as tyrosine kinase inhibitors, represent a small advancement in comparison to the diversity of processes and pathway interactions regulated by these enzymes [ 3 ]. The majority of breast, colon, and pancreatic cancers encompass between 50 and 80 mutated genes [ 2 ] and thousands of mutations in single cancer cells; in addition, this single tumor might exhibit a remarkable degree of morphological and genetic heterogeneity at different stages of its development. The tumor microenvironment (TME), which surrounds and interacts with tumor cells including the extracellular matrix (ECM) elements, stromal cells, blood and lymph vessels, nerve fibers and the signaling molecules, has been put forward to provide a more complex overview of how cancers develop and progress [ 4 , 5 ]. Researchers, oncologists, and pathologists must understand that the complexity and heterogeneity found at a cellular and molecular level are influenced by a pro-tumorigenic TME and systemic macroenvironment and vice versa. Thus, in this review, we discuss recent developments in cancer and its ecosystem biomarkers and technologies based on an advanced understanding of the pathophysiological nature of cancer and its environment. We analyze the TME as the modulator of the dynamic ecosystem and examine the intrinsic and extrinsic systems capable of inducing TME reprogramming. 2. Is the TME Potentially Reprogrammable? The concept of cancer as a disease based on tissues and not only on genetic alterations at the cellular level [ 6 ] opens the door to a new understanding of cancer and its treatment. Growing evidence shows that the stroma is decisively involved in carcinogenesis [ 7 ]. An emerging strategy for cancer treatment is to revert the malignant phenotype by targeting the TME instead of or additionally to the cancer cell population [ 8 ], to modify the relationship between the cells and the stromal compartment to obtain a response on the substrate where tumors grow. Breast carcinoma cells injected into the adipose tissue of syngeneic rats not exposed to the carcinogen, reverse their malignant phenotype and acquire benign features [ 9 ]. In addition, components of the ECM such as type I collagen, basement membrane components, and the presence of normal fibroblasts show the ability to reverse the tumor phenotype through interactions with a favorable TME [ 10 ]. These observations present cancer as a functional tissue with the capacity to respond to different local and distant non-cytotoxic factors, hormonal, immunological, mechanical, and other influences, capable of reprogramming their stroma and cells. 3. Emerging Systems of TME Reprogramming Several local factors that shape the immune response, the ECM, and the adaptive process of angiogenesis contribute to the TME and tumor evolution. Host factors such as intestinal dysbiosis, neurotransmitters/neurohormones implicated in stress response, host and tumor metabolism, infections, surgical and physico-chemical stimuli can also impact on treatment response, activate the hypothalamic–pituitary–adrenal (HPA) axis and increase the risk of metastasis [11,12]. Tumors cells become aggressive through different mechanisms, such as epithelial-mesenchymal transition (EMT), which provides cancer cells with invasion and motility properties. This suggests the Cancers 2020,12, 1677 3 of 24 utility of modulating EMT and the inverse process, the mesenchymal to epithelial transition (MET), at a clinical level [ 13 ] to revert the malignant phenotype. In fact, this reported EMT-MET cycle implies that changes in cell plasticity during tumor progression are temporary and could be reversed [ 14 ]. EMT-MET can lead to the acquisition of stem cell-like features, to modify physico-chemical immunoregulatory properties and genetic, epigenetic, and functional behavior at all levels [ 15 ]. EMT is characterized by remodeling of the ECM and factors secreted by the mesenchymal stem cells that actively modulate several oncogenic signaling pathways such as JAK/STAT, Hedgehog, Wnt, Notch, NFκβ among others, to help stem cells maintain their properties [16]. MET induces regrowth and re-establishment of cancer cells at secondary/metastatic sites. TME factors like Runx2 expression, loss of promoter methylation, and/or miRNAs, can contribute to MET at the metastatic site [16]. Analysis and insight into these processes could support stratifying tumoral heterogeneity at the morphological, immunophenotypic, and genetic level throughout the stroma thus allowing us to identify targetable features [ 17 ]. Beyond the dynamic and progressive genetic alterations of cancer cells, other factors show multiple connections on the tumoral tissue with functional response capacities, such as TME molecules, hormones, cytokines, and neurotransmitters, as well as the macroenvironment, where the intestinal microbiota and external factors ranging from stress to medication intake play a role. 3.1. Intrinsic Systems Capable of Inducing TME Reprogramming 3.1.1. Remodeling TME to Enhance Antitumor Immune Activity The immunological landscape of the TME plays a pivotal role in tumor progression. Cancer immunotherapy has gained growing importance in the last decade and several therapeutic strategies are based on the reactivation of the immune system. However, most immunotherapies employed to date are administered systemically, leading to toxicity [ 18 ]. Targeting the TME by intratumoral injection of immunomodulators has been studied widely as a method to overcome this limitation, as have combinatorial strategies, stimulatory cytokines administration, inhibitory cytokine blockade and inhibition of immune checkpoints to restore immunological capability at the tumor site [ 19 ]. Although immune checkpoint blockade (ICB) appears very effective in a subset of patients, non-responders still remain very high. Several mechanisms for ICB resistance have been proposed [ 20 ] but a deeper understanding of the immune landscape at the TME is required for better patient stratification so they can benefit from ICB therapy. Characterization of the immune cell subpopulations is currently assessed using methods such as fluorescence-activated cell sorting (FACS) or immunohistochemistry (IHC)-staining. Novel transcriptome-based cell-type quantification algorithms are being optimized to provide cell-type signatures for immuno-oncology [ 21 ]. However, increasing the spatio-temporal resolution of these techniques is still necessary to achieve a more comprehensive view of the immune TME milieu, predict response to ICB and encourage the discovery of new immunotherapeutics [22]. The reciprocal interaction between cancer cells and TME determines the recruitment, activation, and reprogramming of stromal, inflammatory, and immune cells [ 23 ] (Figure 1). We have found emerging evidence of the role of ECM remodeling, structural plasticity, and mechanical forces in regulating immune cell trafficking, activation, and immunological synapse formation [24]. Cancer cells can downregulate the expression of endothelial adhesion molecules secreted into the TME and required for the transendothelial migration of leucocytes to diminish exposure to cytotoxic effector cells and evade the immunological response [ 25 ]. In addition, activation and proliferation of leucocytes have been shown to be a mechanosensitive process relying on substrate stiffness [ 26 – 28 ]. Leucocytes are also able to exert a certain degree of mechanical force on the ECM and surface of interacting cells [29]. Several components of the TME have been shown to play a direct role in shaping the immune response. Cancer-associated fibroblast (CAF)-mediated ECM remodeling and fibrosis contribute towards an immunosuppressed and pro-tumorigenic TME by affecting the recruitment and function Cancers 2020,12, 1677 4 of 24 of various innate and adaptive immune cells [ 30 ]. A dense architecture barrier can be imposed by ECM elements such as collagen, hyaluronic acid (HA), and laminins. Whereas high molecular weight HA provides structural integrity and increases regulatory T (Tregs) cell activity to suppress the immune system [ 31 , 32 ], laminins prevent transmigration and polarize leucocytes [ 33 ]. In addition, ECM remodeling enzymes such as metalloproteinases and matrikines direct polarization and activation of immune cells, acting as cytokines and chemokines promoting IL expression and T cell chemoattractant [34–36]. Cancers 2020, 12, x 4 of 24 Cancers 2020, 12, x; doi: www.mdpi.com/journal/cancers ECM elements such as collagen, hyaluronic acid (HA), and laminins. Whereas high molecular weight HA provides structural integrity and increases regulatory T (Tregs) cell activity to suppress the immune system [31,32], laminins prevent transmigration and polarize leucocytes [33]. In addition, ECM remodeling enzymes such as metalloproteinases and matrikines direct polarization and activation of immune cells, acting as cytokines and chemokines promoting IL expression and T cell chemoattractant [34–36]. Figure 1. Hodgkin lymphoma is a clear example of a neoplasm where the components of the TME largely exceed the number of tumor cells. The differential staining of the histological sections corresponds to the same field of the tumor, showing overlapping layers that reveal a heterogeneous composition of the TME. (a) H&E staining of Hodgkin lymphoma. (b) little proportion of CD30 positive lymphoma tumoral cells. (c) Masson’s trichrome stain of abundant type I collagen (blue) and (d) representation of the host innate immune response via macrophage infiltrate (CD68) and the adaptive cellular response mediated by T cells (CD3) and B cells secreting antibodies against the tumor (CD138). Among others, this example constitutes the complex immune and stromal response that determines the histology, response to treatment, and tumor prognosis. Given these findings, we suggest adding a systematic study of the relationship between ECM remodeling and the inflamed stromal components of the TME to the current characterization of the immune TME. In an attempt to methodize evaluation of the host immune response in regarding the TME, the Immunoscore assay quantifies immune cell density to predict patient prognosis and suggest clinical treatment [37]. This takes into account tumoral/TME heterogeneity and from a spatial point of view considers the core of the tumor and its invasive margin, with the contribution of T-cell subpopulations (CD3, CD8, and CD45RO); this could be included in the anatomopathological report Figure 1. Hodgkin lymphoma is a clear example of a neoplasm where the components of the TME largely exceed the number of tumor cells. The differential staining of the histological sections corresponds to the same field of the tumor, showing overlapping layers that reveal a heterogeneous composition of the TME. ( a ) H&E staining of Hodgkin lymphoma. ( b ) little proportion of CD30 positive lymphoma tumoral cells. ( c ) Masson’s trichrome stain of abundant type I collagen (blue) and ( d ) representation of the host innate immune response via macrophage infiltrate (CD68) and the adaptive cellular response mediated by T cells (CD3) and B cells secreting antibodies against the tumor (CD138). Among others, this example constitutes the complex immune and stromal response that determines the histology, response to treatment, and tumor prognosis. Given these findings, we suggest adding a systematic study of the relationship between ECM remodeling and the inflamed stromal components of the TME to the current characterization of the immune TME. In an attempt to methodize evaluation of the host immune response in regarding the TME, the Immunoscore assay quantifies immune cell density to predict patient prognosis and Cancers 2020,12, 1677 5 of 24 suggest clinical treatment [ 37 ]. This takes into account tumoral/TME heterogeneity and from a spatial point of view considers the core of the tumor and its invasive margin, with the contribution of T-cell subpopulations (CD3, CD8, and CD45RO); this could be included in the anatomopathological report as a classification in five levels (0–4), giving more information regarding the treatment options for decision making in a personalized medicine approach [ 38 ]. Production of IFNγ induces PD-L1 (programmed death-ligand 1, also termed B7–H1) tumoral expression correlating with the presence of tumor-infiltrating lymphocytes (TIL), which in turn produce IFNγ (Figure 2a). The presence or absence of PD-L1 and TIL determines the classification into 4 subtypes listed as TIME (Tumor Immune MicroEnvironment): T1 (PD-L1 − , TIL − ), T2 (PD-L1+, TIL+), T3 (PD-L1 − , TIL+) and T4 (PD-L1+, TI − ) (Figure 2(b1–b4)) although the existence of the latter is under debate because, in the absence of TIL, PD-L1 is not expected [ 39 ]. T2 tumors have been shown to correlate with better response to anti-PD-1 therapy [ 40 ]. Although T3 tumors have TIL, they do not express PD-L1, most likely due to a cellular dysfunction where T effector cells are not able to produce IFNγ [ 41 ]. Co-stimulation of T3 tumors with OX-40 or 4-1BB agonists could disrupt the T-cell tolerance [ 42 ] and reprogram the TME into a more treatable tumor. However, the majority of tumors are classified as T1 and T4, both lacking TILs possibly owing to an active suppression of inflammatory infiltration or failure of tumor antigen presentation. The TIME that shows abundant immune cells in the periphery, but is empty of cytotoxic lymphocytes (CTL) in the tumor core, is called TIME infiltrated-excluded (I-E). It possesses a high number of CTLs with low expression of activation markers and low CTL infiltration in the tumor core, meaning that adaptive immunity is unable to recognize malignant cells. On the other hand, infiltrated-inflamed (I-I) TIME is characterized by abundant CTLs that express programmed cell death protein 1 (PD-1) with an antitumoral cytotoxic capacity, therefore considered highly immunogenic tumors. Several strategies could induce the TME reprogramming by promoting an inflammatory infiltration, from focal radiation, locally administered oncolytic viruses, and cryotherapy to the use of anti-cytotoxic T-lymphocyte-associated protein–4 antibody, cancer vaccines, and adoptive T-cell therapy. Costimulatory targeting of 4-1BB or OX40 could also potentially increase tumor infiltration in T1 and T4 tumors [ 42 , 43 ]. A pan-cancer combined quantitative analysis of genomics and proteomics of the tumor matrisome (ECM and its related components) not only relates the tumor matrisome index to mutational load and tumor pathology but also predicts survival rates. Worthy of note, high tumor matrisome index tumors revealed enrichment of specific tumor-infiltrating immune cell populations, along with signatures predictive of resistance to ICB, and clinically targetable immune checkpoints [ 44 ]. 3.1.2. The Nervous System (NS), Adrenaline and Glucocorticoids, and Their Role in Metastases In cancer both the protective mechanisms of the immune system and the protective influence of the NS are lost [ 45 ], leaving the peripheral nervous system (PNS) as a critical part of the tumor stroma, its function, and its structure [ 46 ]. While there is increased insight into the function and significance of nervous components of TME, the neurobiology of cancer is an emerging discipline in oncology. It provides growing evidence on the master regulatory effect on immunity of neurotransmitters and psychosocial factors [ 47 ] and shows that tumors are not isolated structures, but interact with different systems, directly cell to cell, through electromagnetic signals, as well as through neuronal signaling molecules [48]. TME components such as nerve fibers are important tissue elements in defining the intraand peritumoral neural milieu [ 49 – 51 ]. Clinical and in vitro experiments have shown that tumor innervation release neurotransmitters, neuropeptides, and neurotrophins, acting directly on receptors expressed by cancer cells and modulating signaling, apoptosis, angiogenesis, metastases, and progression [ 52 , 53 ]. In fact, in gastric cancer patients, tumor stage has been correlated with neural density whereas vagotomy reduced the risk of gastric cancer [ 54 ]. The tumor cells emit humoral and nervous signals that not only reach the brain, which uses the information to modulate the neuroendocrine and immune system [ 55 ] but can spread via perineural invasion of surrounding nerves and related structures. Notably, perineural Cancers 2020,12, 1677 6 of 24 invasion relates to poor prognosis, correlating with decreased overall and disease-free survival time in colon, pancreatic, gastric, and head and neck carcinoma [56–59]. Cancers 2020, 12, x 6 of 24 Cancers 2020, 12, x; doi: www.mdpi.com/journal/cancers Figure 2. Schematic representation of TIME (Tumor Immune MicroEnvironment) classification. (a) The PD-1/PD-L1 pathway represents an adaptive immune resistance mechanism exerted by tumor cells in response to endogenous immune anti-tumor activity. Engagement of PD-L1 expressed on the tumor cells to PD-1 receptors on the activated T cells leads to inhibition of cytotoxic T cells. (b1–b4) Classification into 4 subtypes listed as TIME. (b1) PD-L1₋, TIL⁻ is classified into type 1 (T1). (b2) PDL1+, TIL+, belongs to type 2 (T2). (b3) PD-L1−, TIL+ belongs to type 3 (T3) and (b4) PD-L1+, TIL−, classified as type 4 (T4) although its existence is under debate. MHC: major histocompatibility complex. TCR: T cell receptor. TAAs: tumor-associated antigens. TSAs: tumor-specific antigens. Legends at the top right. Most human tumors express surface adrenergic receptors, which when activated by stress catecholamines play a role in facilitating tumorigenesis and tumor progression [60]. In lung and breast in vitro cancer models, stimulation of β-adrenergic receptors resulted in the increased metastatic potential of cancer cells, among others via natural killer (NK)-cell, macrophage signaling, or osteoblast stimulation [61]. In vitro, in vivo, and clinical studies show that stress-related processes can affect the pathways involved in cancer progression, including immune regulation, angiogenesis, and invasion. It has been shown that chronic use of beta-blocking drugs (antagonizing norepinephrine and adrenaline (Table 1), is associated with lower recurrence and mortality of breast cancer and malignant melanoma and could to decrease prostate cancer risk [62]. Moreover, low-dose glucocorticoids can suppress ovarian cancer progression and metastasis, probably through upregulation of metastasis suppressor microRNAs, but also via modulation of tumor-associated macrophages and myeloid-derived suppressor cells (MDSCs) in the TME [63]. In addition, the sympathetic nervous system (SNS) regulates pathological gene expression in human tumors, leading to DNA damage repair inhibition, oncogene activation, apoptosis, and anoikis suppression [64]. Figure 2. Schematic representation of TIME (Tumor Immune MicroEnvironment) classification. ( a ) The PD-1/PD-L1 pathway represents an adaptive immune resistance mechanism exerted by tumor cells in response to endogenous immune anti-tumor activity. Engagement of PD-L1 expressed on the tumor cells to PD-1 receptors on the activated T cells leads to inhibition of cytotoxic T cells. ( b1 – b4 ) Classification into 4 subtypes listed as TIME. ( b1 ) PD-L1-, TIL − is classified into type 1 (T1). ( b2 ) PD-L1+, TIL+, belongs to type 2 (T2). ( b3 ) PD-L1 − , TIL+belongs to type 3 (T3) and ( b4 ) PD-L1+, TIL − , classified as type 4 (T4) although its existence is under debate. MHC: major histocompatibility complex. TCR: T cell receptor. TAAs: tumor-associated antigens. TSAs: tumor-specific antigens. Legends at the top right. Most human tumors express surface adrenergic receptors, which when activated by stress catecholamines play a role in facilitating tumorigenesis and tumor progression [ 60 ]. In lung and breast in vitro cancer models, stimulation of β -adrenergic receptors resulted in the increased metastatic potential of cancer cells, among others via natural killer (NK)-cell, macrophage signaling, or osteoblast stimulation [ 61 ]. In vitro , in vivo , and clinical studies show that stress-related processes can affect the pathways involved in cancer progression, including immune regulation, angiogenesis, and invasion. It has been shown that chronic use of beta-blocking drugs (antagonizing norepinephrine and adrenaline (Table 1), is associated with lower recurrence and mortality of breast cancer and malignant melanoma and could to decrease prostate cancer risk [ 62 ]. Moreover, low-dose glucocorticoids can suppress Cancers 2020,12, 1677 7 of 24 ovarian cancer progression and metastasis, probably through upregulation of metastasis suppressor microRNAs, but also via modulation of tumor-associated macrophages and myeloid-derived suppressor cells (MDSCs) in the TME [ 63 ]. In addition, the sympathetic nervous system (SNS) regulates pathological gene expression in human tumors, leading to DNA damage repair inhibition, oncogene activation, apoptosis, and anoikis suppression [ 64 ]. Other neurotransmitters such as endorphins influence tumor proliferation and electrical stimulation of the hypothalamus, increasing the cytotoxicity of NK cells, while pinealectomy affects the course of breast cancer, an effect reversed by the administration of melatonin [48]. Understanding the interaction between cancer cells and NS is becoming indispensable for the development of new targeted therapeutic intervention. 3.1.3. Intestinal Microbiota as TME Regulator In cancer, the intestinal microbiota (IMB), the complex and dynamic population of microorganisms that live in the digestive tracts, is of two-fold importance: on the one hand, for its etiopathogenic role [ 65 ] and on the other for its effect on cancer treatment efficacy, both through an impact on TME [ 66 ]. Several studies link the IMB to the maturation of the immune system, the structure of the TME, metabolism modulation, response to chemical and immunotherapeutic treatment, and most hallmarks of cancer [ 66 – 69 ]. The existence of a tumor microbiota, found in situ in the TME, could, therefore, have major physiopathological and therapeutic implications [ 70 , 71 ]. All these functions perhaps partly owing to the privileged bidirectional communication between IMB and NS, through the so-called neurenteric axis, HPA regulator, and the accompanying homeostatic equilibrium triangle made up by the endocrine, immune and NS [72]. Importantly, IMB modulates the immunotherapeutic response of anti-PD-1 in patients with melanoma [ 73 ] and epithelial tumors [ 74 ], showing how IMB regulation is a key factor in the equilibrium between Treg cells, antigen processing/immunoglobulin-secreting cells and the TME structure [ 75 ]. On the other hand, dysbiosis develops a pro-inflammatory environment, deregulates the immune response, and diminishes the concentration of chemotherapeutic agents by increasing desmoplasia in the TME [ 75 ]. Metagenomic analyses have shown an enrichment of Fusobacterium nucleatum in colorectal carcinoma tissue (Table 1). Fusobacterium nucleatum causes immunosuppression and recruits tumor-infiltrating immune cells, thus yielding a pro-inflammatory microenvironment, which promotes colorectal neoplasia progression [ 76 ]. Antibiotics adversely affect overall and disease-free survival in cancer, regardless of other criteria, due to the destruction of IMB [ 74 ], required for chemotherapy to be effective. Overall survival of 20 months without and 11 months with antibiotics (15 and 8 months respectively in lung cancer) show how the IBM governs immune checkpoints and opens up new approaches for a decisive intestinal ecosystem in resistance to inhibitors of immune response control and modification of TME [77]. This opens a new field of research and clinical application and puts forward the IMB as an interesting biomarker that determines the efficacy of immunotherapy treatment [78] (Table 1). Cancers 2020,12, 1677 8 of 24 Table 1. Evaluation methods for emerging biomarkers. Evaluation Groups Parameters Indicators Detection Method References TME Inflammatory infiltrated cells TAM CD68, CD163 IHC [79] TAN CD15, CD32, CD35 [80] T helper CD4 [81] Cytotoxic T cells CD8 [82] Memory T cells CD8, CD4, CTLA-4 [83] Tregs FOXP3, CD4, CD25 [84] DC CD141, CLEC9, CD11c [85,86] NK CD16, CD56, PD-L1, PD-L2 [87] B lymphocytes CD20 [88] Stromal cells CAF αSAM, CD10, FSP1, AEBP1 [89,90] Schwann cells S100, GFAP, p75NTR [91] MSC SC Sox2, Oct4, CD133, Nestin, c-kit [92] Fibers Collagen type I T. Masson, van Gieson HC [93,94] Collagen type III [94] Elastic fibers Orcein, Gomori, Snook, Wilder, Verhoeff[94] Interstitial fluid Proteoglycans Alcian blue [95] Fibronectin Antifibronectin IHC [96] Laminin Antilaminin [97] Vitronectin Antivitronectin [98] Growth factor TGF-βAS [99] Cytokines Lymphokines ELISA [100] Proteases Metalloproteinases [100] Oxygen (ROS) GSH/GSSG [100] 3D structure Fibres and Cellular elements Topology Graph theory [101,102] Mechanical forces Focal adhesions (F-actin, myosin II, α-actin, fascin) IF [103] Stress fibres [103] Mechanotransduction Mechano-actuated shuttling proteins (β-catenin, zyxin) [103] LINC complex (SUN and nesprins) [103] Systemic factors Glycolic index ↑metabolic index 18FDG PET [104] pH Acidosis Electrolytes serum concentration Enzymatic [105] Oxygen saturation Hypoxia ↑HIF-1, ↑lactate IHC [106] Metabolism Inflammatory response ↓VEGF AS, ELISA [107] Intestinal microbiota Dysbiosis ↑Bacteroids MALDI-TOF MS [76,108–110] ↑Fusobacterium NGS [76,108–110] ↑Porphyromonas 16S rRNA [76,108–110] ↑Enterobacter [76,108–110] ↑Cybrobacter [76,108–110] Nervous system Deregulation ↑Norepinephrine, HPLC [62] ↑Dopamine [111] ↑substance P [112] ↓β-endorphins [113] AS: absorption spectrometry; DC: dendritic cells; CAF: cancer-associated fibroblasts; 18FDG: fluorodeoxyglucose; GSH: glutathione; GSSG: glutathione disulfide; HC: histochemistry; HPLC: high-performance liquid chromatography; IF: immunofluorescence; IHC: immunohistochemistry; LINC: linker of nucleoskeleton and cytoskeleton; MALDI-TOF MS: matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; MSC: mesenchymal stem cells; NGS: next-generation sequencing; NK: natural killer cells; PET: positron emission tomography; ROS: reactive oxygen species; 16S rRNA: ribosomal RNA 16S; SC: stem cells; TAM: tumor-associated macrophage; TAN: tumor-associated neutrophils; TME: tumor microenvironment; Tregs: regulatory T cells. Adapted from Noguera et at., 2019 [46]. Cancers 2020,12, 1677 9 of 24 3.1.4. Metabolic Regulation and Mitochondrial Dysfunction of Cancer Otto Warburg pioneered the study of tumor metabolism [ 114 ], which established hypoxia and acidosis as characteristics of cancer. This specific metabolic pattern is based on aerobic glycolysis of tumor cells (Warburg effect), which is a necessary source of substrates for uncontrolled tumor cell growth considering that tumor suppressor oncogenes and genes might be carriers of bioenergetic alterations [ 115 ]. Metabolic reprogramming is an essential mechanism by which cancer cells switch to different pathways to obtain the energy necessary to survive and proliferate. This metabolic and bioenergetic shift sustains high proliferation rates, as carbon sources are rapidly diverted to produce lipids, nucleic acids, and proteins [ 116 ]. This process is also essential to regulate the interaction between cancer and immune cells, as well as to recruit a variety of immune cells [ 117 ]. Cancer metabolism has led to a scientific focus on tumor cell reprogramming of glucose consumption [ 118 ] to correct the dysfunctional behavior of tumors. Indeed, it is well accepted that aberrant cancer metabolism is linked to treatment resistance [ 119 ]. Glutamine levels, which are decreased in the hypoxic core of the tumor, drive histone methylation, and tumor de-differentiation to lead drug resistance [ 120 ]. Glutamine also affects the stroma by changing it to a tumor-promoting environment through increased glutamine-induced autophagy in fibroblasts [ 121 ]. Lipid metabolism also supports TME reprogramming; indeed, it has been found that Tregs accumulate lipids and combine glycolysis and fatty acid synthesis and oxidation to survive [ 122 ]. In addition, recent studies show that the metabolic state of TME, oxygen levels, acidity, and nutrient availability affect T-cell infiltration, survival, and effector function [ 123 , 124 ]. Furthermore, gradients of extracellular metabolites, levels of ischemia, hypoxia, and lactate act as morphogens and increase stromal stiffness. Among other findings, metabolic alterations of the stroma impact tumor heterogeneity, affecting both morpho-immunophenotypic and genetic features [ 17 ]; they contribute to identifying sampling error as a cause of lack of correlation between biomarker research and response to immunotherapeutic treatment; shed light on the spatial structure of the TME depending on the Warburg effect [ 125 ] and finally show the ability of tumor cells to reprogram their metabolism and survive the harsh conditions of TME [126]. Furthermore, mitochondrial lesions not only affect tumor metabolism but also alter apoptosis and present cancer as mitochondrial dysfunction [ 127 ]. The cells act as if there is oxygen shortage, even if there is abundance as HIF-1a maintains the expression of normally inactive genes that make the cell immortal, unable to activate programmed cell death and keep its reproduction program activated [ 128 ] (Table 1) through the concatenation of hypoxia, lactate levels, malignancy, and metastatic capacity. While the highly glycolytic tumor cell is very aggressive and invasive, cells without mitochondrial DNA cannot form tumors [ 129 ], unless they acquire it from adjacent cells, as occurs through mitochondria donation from stromal cells to tumor-deficient tumor cells. Tumor cells recover respiratory capacity and biological aggressiveness when they take up mitochondrial DNA from TME cells [ 130 ]. A promising perspective could be based around the ability of the mitochondria to suppress the malignant phenotype [127]. 3.1.5. Mechanotransduction and Biotensegrity as Properties of the TME The mechanical properties of the tumor stroma are determinants of cell biology and clinical behavior [131]. A recurrent tumor feature is the stiffness of the stroma, through which tumors can be detected by palpation or radiological examination. The main mechanical perturbations of the TME are stiffness of the ECM, elevated interstitial fluid pressure, and/or an increase in solid tension caused by tumor growth [ 132 ]. These mechanical properties are difficult to study and evaluate with conventional histological techniques, and advances in the field now stem from a new knowledge area called mechanobiology, an interdisciplinary science branch combining biology, physics and engineering. The tumor tissue biotensegrity mechanism is based on tension forces on cells and various elements of the ECM, which receive mechanical impact through specifically designed elements [ 102 ]. 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