Cancer immunotherapy has revolutionized the treatment of some malignancies. Yet, many tumors do not unfortunately respond to immune‐based therapies. Deeper insights into the biology of the immune ...response to cancer are required to identify novel therapeutic targets and advance immuno‐oncology. To do so, we need to study cancer in patient‐derived models that can faithfully recapitulate and capture the complexity and heterogeneity of the tumor immune ecosystem. Platforms facilitating the analysis of the human tumor immune microenvironment of individual patients are crucial. Patient‐derived models are fundamental not only to better understand the biology of the cancer immune system but also to discern the mechanism of action of therapeutic compounds and perform preclinical studies toward improving the success of subsequent clinical testing. In this viewpoint, I present a brief review of patient‐derived models for cancer immunotherapy.
Deeper insights into the biology of the immune response to cancer are required to identify novel therapeutic targets and advance immuno‐oncology. To do so, we need to study cancer in patient‐derived models that can faithfully recapitulate and capture the complexity and heterogeneity of the tumor immune ecosystem. Platforms facilitating the analysis of the human tumor immune microenvironment of individual patients are crucial. In this viewpoint, I present a brief review of patient‐derived models for cancer immunotherapy.
Smad transcription factors lie at the core of one of the most versatile cytokine signaling pathways in metazoan biology-the transforming growth factor-beta (TGFbeta) pathway. Recent progress has shed ...light into the processes of Smad activation and deactivation, nucleocytoplasmic dynamics, and assembly of transcriptional complexes. A rich repertoire of regulatory devices exerts control over each step of the Smad pathway. This knowledge is enabling work on more complex questions about the organization, integration, and modulation of Smad-dependent transcriptional programs. We are beginning to uncover self-enabled gene response cascades, graded Smad response mechanisms, and Smad-dependent synexpression groups. Our growing understanding of TGFbeta signaling through the Smad pathway provides general principles for how animal cells translate complex inputs into concrete behavior.
BMP is highly expressed in glioblastoma and promotes differentiation of cancer stem cells (CSCs). Recently, Yan and colleagues found the explanation to this apparent paradox by showing that the ...antagonist of BMP, Gremlin1, is secreted by CSCs to protect them against the BMP-induced differentiation.
The Warburg effect, characterized by the preferential conversion of glucose to lactate even in the presence of oxygen and functional mitochondria, is a prominent metabolic hallmark of cancer cells ...and has emerged as a promising therapeutic target for cancer therapy. Elevated lactate levels and acidic pH within the tumor microenvironment (TME) resulting from glycolytic profoundly impact various cellular populations, including macrophage reprogramming and impairment of T-cell functionality. Altogether, the Warburg effect has been shown to promote tumor progression and immunosuppression through multiple mechanisms. This review provides an overview of the current understanding of the Warburg effect in cancer and its implications. We summarize recent pharmacological strategies aimed at targeting glycolytic enzymes, highlighting the challenges encountered in achieving therapeutic efficacy. Additionally, we examine the utility of the Warburg effect as an early diagnostic tool. Finally, we discuss the multifaceted roles of lactate within the TME, emphasizing its potential as a therapeutic target to disrupt metabolic interactions between tumor and immune cells, thereby enhancing anti-tumor immunity.
Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal ...histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models.
PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field.
Heterogeneity is a hallmark of tumors and has a crucial role in the outcome of the malignancy, because it not only confounds diagnosis, but also challenges the design of effective therapies. There ...are two types of heterogeneity: inter-tumor and intra-tumor heterogeneity. While inter-tumor heterogeneity has been studied widely, intra-tumor heterogeneity has been neglected even though numerous studies support this aspect of tumor pathobiology. The main reason has been the technical difficulties, but with new advances in single-cell technology, intra-tumor heterogeneity is becoming a key area in the study of cancer. Several models try to explain the origin and maintenance of intra-tumor heterogeneity, however, one prominent model compares cancer with a tree where the ubiquitous mutations compose the trunk and mutations present in subpopulations of cells are represented by the branches. In this review we will focus on the intra-tumor heterogeneity of glioblastoma multiforme (GBM), the most common brain tumor in adults that is characterized by a marked heterogeneity at the cellular and molecular levels. Better understanding of this heterogeneity will be essential to design effective therapies against this devastating disease to avoid tumor escape.
Transforming growth factor‐β (TGF‐β) and programmed death ligand 1 (PD‐L1) initiate signaling pathways with complementary, nonredundant immunosuppressive functions in the tumor microenvironment ...(TME). In the TME, dysregulated TGF‐β signaling suppresses antitumor immunity and promotes cancer fibrosis, epithelial‐to‐mesenchymal transition, and angiogenesis. Meanwhile, PD‐L1 expression inactivates cytotoxic T cells and restricts immunosurveillance in the TME. Anti‐PD‐L1 therapies have been approved for the treatment of various cancers, but TGF‐β signaling in the TME is associated with resistance to these therapies. In this review, we discuss the importance of the TGF‐β and PD‐L1 pathways in cancer, as well as clinical strategies using combination therapies that block these pathways separately or approaches with dual‐targeting agents (bispecific and bifunctional immunotherapies) that may block them simultaneously. Currently, the furthest developed dual‐targeting agent is bintrafusp alfa. This drug is a first‐in‐class bifunctional fusion protein that consists of the extracellular domain of the TGF‐βRII receptor (a TGF‐β ‘trap’) fused to a human immunoglobulin G1 (IgG1) monoclonal antibody blocking PD‐L1. Given the immunosuppressive effects of the TGF‐β and PD‐L1 pathways within the TME, colocalized and simultaneous inhibition of these pathways may potentially improve clinical activity and reduce toxicity.
The TGF‐β and PD‐L1 signaling pathways have complementary, nonredundant functions in the tumor microenvironment. Dysregulated TGF‐β signaling suppresses antitumor immunity and promotes cancer fibrosis, epithelial–mesenchymal transition, and angiogenesis, while PD‐L1 restricts immunosurveillance. We review existing strategies for simultaneous inhibition of these pathways, highlighting dual‐targeting agents that may provide colocalized, simultaneous inhibition.
Cancer response to immunotherapy depends on the infiltration of CD8
T cells and the presence of tumor-associated macrophages within tumors. Still, little is known about the determinants of these ...factors. We show that LIF assumes a crucial role in the regulation of CD8
T cell tumor infiltration, while promoting the presence of protumoral tumor-associated macrophages. We observe that the blockade of LIF in tumors expressing high levels of LIF decreases CD206, CD163 and CCL2 and induces CXCL9 expression in tumor-associated macrophages. The blockade of LIF releases the epigenetic silencing of CXCL9 triggering CD8
T cell tumor infiltration. The combination of LIF neutralizing antibodies with the inhibition of the PD1 immune checkpoint promotes tumor regression, immunological memory and an increase in overall survival.
The correct characterisation of central nervous system (CNS) malignancies is crucial for accurate diagnosis and prognosis and also the identification of actionable genomic alterations that can guide ...the therapeutic strategy. Surgical biopsies are performed to characterise the tumour; however, these procedures are invasive and are not always feasible for all patients. Moreover, they only provide a static snapshot and can miss tumour heterogeneity. Currently, monitoring of CNS cancer is performed by conventional imaging techniques and, in some cases, cytology analysis of the cerebrospinal fluid (CSF); however, these techniques have limited sensitivity. To overcome these limitations, a liquid biopsy of the CSF can be used to obtain information about the tumour in a less invasive manner. The CSF is a source of cell-free circulating tumour DNA (ctDNA), and the analysis of this biomarker can characterise and monitor brain cancer. Recent studies have shown that ctDNA is more abundant in the CSF than plasma for CNS malignancies and that it can be sequenced to reveal tumour heterogeneity and provide diagnostic and prognostic information. Furthermore, analysis of longitudinal samples can aid patient monitoring by detecting residual disease or even tracking tumour evolution at relapse and, therefore, tailoring the therapeutic strategy. In this review, we provide an overview of the potential clinical applications of the analysis of CSF ctDNA and the challenges that need to be overcome in order to translate research findings into a tool for clinical practice.
The levels of cell free circulating tumor DNA (ctDNA) in plasma correlated with treatment response and outcome in systemic lymphomas. Notably, in brain tumors, the levels of ctDNA in the ...cerebrospinal fluid (CSF) are higher than in plasma. Nevertheless, their role in central nervous system (CNS) lymphomas remains elusive. We evaluated the CSF and plasma from 19 patients: 6 restricted CNS lymphomas, 1 systemic and CNS lymphoma, and 12 systemic lymphomas. We performed whole exome sequencing or targeted sequencing to identify somatic mutations of the primary tumor, then variant-specific droplet digital PCR was designed for each mutation. At time of enrolment, we found ctDNA in the CSF of all patients with restricted CNS lymphoma but not in patients with systemic lymphoma without CNS involvement. Conversely, plasma ctDNA was detected in only 2/6 patients with restricted CNS lymphoma with lower variant allele frequencies than CSF ctDNA. Moreover, we detected CSF ctDNA in 1 patient with CNS lymphoma in complete remission and in 1 patient with systemic lymphoma, 3 and 8 months before CNS relapse was confirmed; indicating CSF ctDNA might detect CNS relapse earlier than conventional methods. Finally, in 2 cases with CNS lymphoma, CSF ctDNA was still detected after treatment even though a complete decrease in CSF tumor cells was observed by flow cytometry (FC), indicating CSF ctDNA better detected residual disease than FC. In conclusion, CSF ctDNA can better detect CNS lesions than plasma ctDNA and FC. In addition, CSF ctDNA predicted CNS relapse in CNS and systemic lymphomas.
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