Evidence for hypoxia increasing the tempo of evolution in glioblastoma

Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation

Computational models are not just appealing because they can simulate and predict the development of biological phenomena across multiple spatial and temporal scales, but also because they can integrate information from well-established in vitro and in vivo models and test new hypotheses in cancer biomedicine. Agent-based models and simulations are especially interesting candidates among computational modeling procedures in cancer research due to the capability to, for instance, recapitulate the dynamics of neoplasia and tumor - host interactions. Yet, the absence of methods to validate the consistency of the results across scales can hinder adoption by turning fine-tuned models into black boxes. This review compiles relevant literature that explores strategies to leverage high-fidelity simulations of multi-scale, or multi-level, cancer models with a focus on verification approached as simulation calibration. We consolidate our review with an outline of modern approaches for agent-based models' validation and provide an ambitious outlook toward rigorous and reliable calibration.

Morphological and molecular-biological features of glioblastoma progression in tolerant and susceptible to hypoxia Wistar rats

Hypoxia is a major pathogenetic factor in many cancers. Individual resistance to suboptimal oxygen availability is subject to broad variation and its possible role in tumorigenesis remains underexplored. This study aimed at specific characterization of glioblastoma progression in male tolerant and susceptible to hypoxia Wistar rats. Hypoxia resistance was assessed by gasping time measurement in an 11,500 m altitude-equivalent hypobaric decompression chamber. Based on the outcome, the animals were assigned to three groups termed 'tolerant to hypoxia' (n = 13), 'normal', and 'susceptible to hypoxia' (n = 24). The 'normal' group was excluded from subsequent experiments. One month later, the animals underwent inoculation with rat glioblastoma 101.8 followed by monitoring of survival, body weight dynamics and neurological symptoms. The animals were sacrificed on post-inoculation days 11 (subgroup 1) and 15 (subgroup 2). Relative vessels number, necrosis areas and Ki-67 index were assessed microscopically; tumor volumes were determined by 3D reconstruction from histological images; serum levels of HIF-1α, IL-1β, and TNFα were determined by ELISA. None of the tolerant to hypoxia animals died of the disease during observation period, cf. 85% survival on day 11 and 55% survival on day 15 in the susceptible group. On day 11, proliferative activity of the tumors in the tolerant animals was higher compared with the susceptible group. On day 15, proliferative activity, necrosis area and volume of the tumors in the tolerant to hypoxia animals were higher compared with the susceptible group. ELISA revealed no dynamics in TNFα levels, elevated levels of IL-1β in the susceptible animals on day 15 in comparison with day 11 and tolerant ones. Moreover, there were elevated levels of HIF-1α in the tolerant animals on day 15 in comparison with day 11. Thus, the proliferative activity of glioblastoma cells and the content of HIF-1α were higher in tolerant to hypoxia rats, but the mortality associated with the tumor process and IL-1β level in them were lower than in susceptible animals. Specific features of glioblastoma 101.8 progression in tolerant and susceptible to hypoxia rats, including survival, tumor growth rates and IL-1β level, can become the basis of new personalized approaches for cancer diseases treatment in accordance to individual hypoxia resistance.

Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative "omics" approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of a few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. Despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on revealing the general picture of GBM heterogeneity. Hence, in this mini-review, we summarized the current state of knowledge on GBM heterogeneity revealed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

Integration of single-cell RNA sequencing and spatial transcriptomics to reveal the glioblastoma heterogeneity

Glioblastoma (GBM), a deadly brain tumor, is still one of the few lasting challenges of contemporary oncology. Current therapies fail to significantly improve patient survival due to GBM's tremendous genetic, transcriptomic, immunological, and sex-dependent heterogeneity. Over the years, clinical differences between males and females were characterized. For instance, higher incidence of GBM in males or distinct responses to cancer chemotherapy and immunotherapy between males and females have been noted. However, despite the introduction of single-cell RNA sequencing and spatial transcriptomics, these differences were not further investigated as studies were focused only on exposing the general picture of GBM heterogeneity. Hence, in this study, we summarized the current state of knowledge on GBM heterogeneity exposed by single-cell RNA sequencing and spatial transcriptomics with regard to genetics, immunology, and sex-dependent differences. Additionally, we highlighted future research directions which would fill the gap of knowledge on the impact of patient's sex on the disease outcome.

Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus efficacy

Oncolytic viruses (OVs) are emerging cancer immunotherapy. Despite notable successes in the treatment of some tumors, OV therapy for central nervous system cancers has failed to show efficacy. We used an ex vivo tumor model developed from human glioblastoma tissue to evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into glioblastoma tumors. We next leveraged our data to develop a computational, model of glioblastoma dynamics that accounts for cellular interactions within the tumor. Using our computational model, we found that low stromal density was highly predictive of oHSV-1 therapeutic success, suggesting that the efficacy of oHSV-1 in glioblastoma may be determined by stromal-to-tumor cell regional density. We validated these findings in heterogenous patient samples from brain metastatic adenocarcinoma. Our integrated modeling strategy can be applied to suggest mechanisms of therapeutic responses for central nervous system cancers and to facilitate the successful translation of OVs into the clinic.

Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.

(Dis)similarities between the Decidual and Tumor Microenvironment

Placenta-specific trophoblast and tumor cells exhibit many common characteristics. Trophoblast cells invade maternal tissues while being tolerated by the maternal immune system. Similarly, tumor cells can invade surrounding tissues and escape the immune system. Importantly, both trophoblast and tumor cells are supported by an abetting microenvironment, which influences invasion, angiogenesis, and immune tolerance/evasion, among others. However, in contrast to tumor cells, the metabolic, proliferative, migrative, and invasive states of trophoblast cells are under tight regulatory control. In this review, we provide an overview of similarities and dissimilarities in regulatory processes that drive trophoblast and tumor cell fate, particularly focusing on the role of the abetting microenvironments.

Detection of Hypoxia in Cancer Models: Significance, Challenges, and Advances

The rapid proliferation of cancer cells combined with deficient vessels cause regions of nutrient and O₂ deprivation in solid tumors. Some cancer cells can adapt to these extreme hypoxic conditions and persist to promote cancer progression. Intratumoral hypoxia has been consistently associated with a worse patient prognosis. In vitro, 3D models of spheroids or organoids can recapitulate spontaneous O₂ gradients in solid tumors. Likewise, in vivo murine models of cancer reproduce the physiological levels of hypoxia that have been measured in human tumors. Given the potential clinical importance of hypoxia in cancer progression, there is an increasing need to design methods to measure O₂ concentrations. O₂ levels can be directly measured with needle-type probes, both optical and electrochemical. Alternatively, indirect, noninvasive approaches have been optimized, and include immunolabeling endogenous or exogenous markers. Fluorescent, phosphorescent, and luminescent reporters have also been employed experimentally to provide dynamic measurements of O₂ in live cells or tumors. In medical imaging, modalities such as MRI and PET are often the method of choice. This review provides a comparative overview of the main methods utilized to detect hypoxia in cell culture and preclinical models of cancer.

Immunohistochemical expression of HIF-1α, IDH1 and TP53: Prognostic profile of Moroccan patients with diffuse glioma

Diffuse gliomas are growing brain tumors that occur in adult life. This study was designed to determine whether the immunohistochemical analysis of IDH1, HIF-1alpha, or TP53 can provide useful biomarkers of clinical severity and progression of diffuse gliomas. Also, it is hypothesized that the expression of IDH1 mutant induces HIF-1alpha. Immunohistochemical staining for HIF-1alpha, IDH1, and TP 53 was performed in biopsy or resection (sub-total or gross-total) tissue from diffuse gliomas in a clinical series of 32 patients. Associations of the HIF-1alpha, IDH1, and TP53 with clinical characteristics were evaluated and the co-expression of two biomarkers (HIF-1alpha and IDH1) was tested. Our data revealed that each biomarker is expressed in a subset of gliomas (IDH1 was positive in 56% cases, HIF-1alpha was positive in 50% cases and TP53 was positive in 44% cases). While no associations were found between clinical characteristics and the expression of HIF-1alpha, and TP53, IDH1 expression was associated with less severe clinical presentation (Karnofsky Performance Status) and disease progression and was more often expressed in females than males. In addition, there was no clear association between IDH1 and HIF-1alpha expression (21.9% of patients co-expressed IDH1 and HIF-1alpha). The current series provides clinical and immunohistochemical findings that can be useful for the clinical management of patients with diffused gliomas.

Hypoxia: The Cornerstone of Glioblastoma

Glioblastoma is the most aggressive form of brain tumor in adults and is characterized by the presence of hypervascularization and necrosis, both caused by a hypoxic microenvironment. In this review, we highlight that hypoxia-induced factor 1 (HIF-1), the main factor activated by hypoxia, is an important driver of tumor progression in GB patients. HIF-1α is a transcription factor regulated by the presence or absence of O2. The expression of HIF-1 has been related to high-grade gliomas and aggressive tumor behavior. HIF-1 promotes tumor progression via the activation of angiogenesis, immunosuppression, and metabolic reprogramming, promoting cell invasion and survival. Moreover, in GB, HIF-1 is not solely modulated by oxygen but also by oncogenic signaling pathways, such as MAPK/ERK, p53, and PI3K/PTEN. Therefore, the inhibition of the hypoxia pathway could represent an important treatment alternative in a disease with very few therapy options. Here, we review the roles of HIF-1 in GB progression and the inhibitors that have been studied thus far, with the aim of shedding light on this devastating disease.

Effects of hypoxia and nanocarrier size on pH-responsive nano-delivery system to solid tumors

One of the special features of solid tumors is the acidity of the tumor microenvironment, which is mainly due to the presence of hypoxic regions. Therefore, pH-responsive drug delivery systems have recently been highly welcomed. In the present study, a comprehensive mathematical model is presented based on extravascular drug release paradigm. Accordingly, drug delivery system using pH-responsive nanocarriers is taken into account to examine the impacts of hypoxic regions as well as the size of nanocarriers for cancerous cell-death. The extent of hypoxic regions is controlled by vascular density. This means that regions with very low vascular density represent regions of hypoxia. Using this mathematical model, it is possible to simulate the extracellular and intracellular concentrations of drug by considering the association/disassociation of the free drug to the cell-surface receptors and cellular uptake. Results show that nanocarriers with smaller sizes are more effective due to higher accumulation in the tumor tissue interstitium. The small size of the nanocarriers also allows them to penetrate deeper, so they can expose a larger portion of the tumor to the drug. Additionally, the presence of hypoxic regions in tumor reduces the fraction of killed cancer cells due to reduced penetration depth. The proposed model can be considered for optimizing and developing pH-sensitive delivery systems to reduce both cost and time of the process.

A phase Ib/IIa trial of 9 repurposed drugs combined with temozolomide for the treatment of recurrent glioblastoma: CUSP9v3

Background

The dismal prognosis of glioblastoma (GBM) may be related to the ability of GBM cells to develop mechanisms of treatment resistance. We designed a protocol called Coordinated Undermining of Survival Paths combining 9 repurposed non-oncological drugs with metronomic temozolomide—version 3—(CUSP9v3) to address this issue. The aim of this phase Ib/IIa trial was to assess the safety of CUSP9v3.

Methods

Ten adults with histologically confirmed GBM and recurrent or progressive disease were included. Treatment consisted of aprepitant, auranofin, celecoxib, captopril, disulfiram, itraconazole, minocycline, ritonavir, and sertraline added to metronomic low-dose temozolomide. Treatment was continued until toxicity or progression. Primary endpoint was dose-limiting toxicity defined as either any unmanageable grade 3–4 toxicity or inability to receive at least 7 of the 10 drugs at ≥ 50% of the per-protocol doses at the end of the second treatment cycle.

Results

One patient was not evaluable for the primary endpoint (safety). All 9 evaluable patients met the primary endpoint. Ritonavir, temozolomide, captopril, and itraconazole were the drugs most frequently requiring dose modification or pausing. The most common adverse events were nausea, headache, fatigue, diarrhea, and ataxia. Progression-free survival at 12 months was 50%.

Conclusions

CUSP9v3 can be safely administered in patients with recurrent GBM under careful monitoring. A randomized phase II trial is in preparation to assess the efficacy of the CUSP9v3 regimen in GBM.