Table 11 Significant iPSC-based cancer research case studies
From: Exploring the promising potential of induced pluripotent stem cells in cancer research and therapy
Study name | Results | Impact on understanding of tumorigenesis | References |
|---|---|---|---|
iPSCs as a tool for modeling cancer development and progression | Generated iPSCs from cancer cells and analyzed their behavior in vitro and in vivo, providing a new platform for studying cancer biology and identifying potential therapeutic targets | Demonstrated that iPSCs can be used to model cancer development and progression, enabling researchers to study the disease in a more controlled and reproducible manner | |
Characterization of oncogenic mutations in iPSC-derived cancer cells | Used CRISPR-Cas9 gene editing to introduce specific oncogenic mutations into iPSCs and analyzed their effect on cancer development and progression | Revealed the specific genetic mutations that can lead to cancer development and provided a new platform for testing potential cancer therapies | |
iPSC-based drug screening for cancer therapy | Screened a library of compounds using iPSC-derived cancer cells and identified several novel drug candidates with anti-cancer activity | Provided a new approach to drug screening for cancer therapy that can improve the efficiency and efficacy of drug discovery | |
Comparison of iPSC-derived cancer cells to primary tumor samples | Analyzed the similarities and differences between iPSC-derived cancer cells and primary tumor samples, providing insights into the limitations and potential of iPSC-based cancer research | Highlighted the importance of validating iPSC-derived cancer models against primary tumor samples to ensure their relevance and accuracy | [24] |
iPSC-based modeling of cancer metastasis | Generated iPSCs from metastatic cancer cells and analyzed their behavior in vitro and in vivo, providing new insights into the mechanisms underlying cancer metastasis | Revealed the specific genetic and cellular changes that enable cancer cells to metastasize, providing potential targets for developing therapies to prevent cancer spread | |
iPSC-based modeling of cancer immunotherapy | Generated iPSCs from patient-derived cancer cells and engineered them to express immune checkpoint inhibitors, providing a new platform for studying the effectiveness of immunotherapy in treating cancer | Demonstrated the potential of iPSC-based models to improve the development and optimization of cancer immunotherapies | |
iPSC-based modeling of cancer heterogeneity | Generated iPSCs from different types of cancer cells and analyzed their behavior in vitro and in vivo, providing insights into the heterogeneity of cancer and the importance of personalized medicine | Highlighted the need for personalized medicine approaches that take into account the heterogeneity of cancer and the individual characteristics of each patient's disease | |
iPSC-based modeling of drug resistance in cancer | Generated iPSCs from drug-resistant cancer cells and investigated the underlying mechanisms of resistance, identifying potential strategies to overcome it | Provided insights into the molecular mechanisms of drug resistance in cancer, leading to the development of more effective treatment approaches | |
Investigation of epigenetic modifications in iPSC-derived cancer cells | Analyzed epigenetic changes in iPSC-derived cancer cells compared to normal cells, revealing alterations in gene expression and potential epigenetic targets for therapy | Shed light on the role of epigenetic modifications in cancer development and progression, opening avenues for targeted epigenetic therapies | |
iPSC-based modeling of cancer stem cells | Generated iPSCs from cancer stem cells and characterized their properties, including self-renewal and differentiation capabilities, providing insights into their role in tumor initiation and treatment resistance | Enhanced understanding of cancer stem cells' contribution to tumor development, recurrence, and resistance to therapy, guiding the development of therapies targeting these cells | |
iPSC-based modeling of tumor microenvironment interactions | Co-cultured iPSC-derived cancer cells with stromal cells to mimic the tumor microenvironment and studied the reciprocal interactions, uncovering the role of stromal cells in tumor growth and progression | Improved understanding of the dynamic interactions between cancer cells and the surrounding microenvironment, leading to the identification of potential therapeutic targets in the tumor microenvironment | |
iPSC-based modeling of inherited cancer predisposition syndromes | Generated iPSCs from patients with inherited cancer predisposition syndromes and investigated the molecular mechanisms underlying their increased cancer risk, aiding in the development of targeted prevention and early detection strategies | Provided insights into the genetic factors contributing to inherited cancer predisposition syndromes, facilitating personalized risk assessment and management strategies | [670] |
iPSC-based modeling of tumor heterogeneity and clonal evolution | Generated iPSCs from different tumor subclones within a patient and tracked their evolution over time, revealing insights into tumor heterogeneity and clonal dynamics | Advanced our understanding of tumor evolution and the development of resistance, informing the design of combination therapies targeting multiple tumor subclones | |
iPSC-based modeling of cancer dormancy and recurrence | Induced dormancy in iPSC-derived cancer cells and investigated the factors contributing to their reactivation, providing insights into mechanisms of cancer recurrence | Enhanced understanding of cancer dormancy and the potential drivers of tumor relapse, aiding in the development of strategies to prevent or target dormant cancer cells | [674] |
iPSC-based modeling of cancer metabolism | Analyzed metabolic alterations in iPSC-derived cancer cells compared to normal cells, identifying metabolic vulnerabilities and potential targets for therapeutic intervention | Provided insights into the rewiring of cancer cell metabolism and the potential for targeting specific metabolic pathways in cancer treatment | |
iPSC-based modeling of immune evasion mechanisms in cancer | Generated iPSCs from cancer cells and examined their interaction with immune cells, uncovering mechanisms of immune evasion and resistance to immunotherapy | Improved understanding of the complex interplay between cancer cells and the immune system, guiding the development of novel immunotherapeutic strategies | [677] |
iPSC-based modeling of cancer-associated fibroblasts | Derived iPSCs from cancer-associated fibroblasts and investigated their role in tumor growth and metastasis, revealing the influence of the tumor microenvironment on cancer progression | Enhanced understanding of the interactions between cancer cells and cancer-associated fibroblasts, providing potential targets for therapeutic intervention | |
iPSC-based modeling of DNA repair defects in cancer | Generated iPSCs from patients with DNA repair deficiencies and examined their susceptibility to genomic instability and cancer development, highlighting the role of DNA repair mechanisms in tumor suppression | Provided insights into the link between DNA repair defects and cancer susceptibility, contributing to the development of personalized therapies for patients with specific DNA repair deficiencies | |
iPSC-based modeling of cancer cell dormancy and reactivation | Investigated the mechanisms underlying cancer cell dormancy and reactivation using iPSC-derived models, uncovering factors that control the switch between dormant and active states | Improved understanding of the processes involved in cancer cell dormancy and reactivation, providing potential targets for preventing tumor recurrence | |
iPSC-based modeling of cancer-associated inflammation | Generated iPSCs from cancer cells and studied their interaction with inflammatory cells, elucidating the role of inflammation in cancer development and progression | Enhanced understanding of the crosstalk between cancer cells and the inflammatory microenvironment, paving the way for the development of anti-inflammatory strategies for cancer treatment | |
iPSC-based modeling of therapeutic resistance in cancer | Created iPSCs from cancer cells resistant to specific therapies and investigated the molecular mechanisms underlying the resistance, identifying potential strategies to overcome treatment resistance | Provided insights into the mechanisms of therapeutic resistance in cancer, guiding the development of combination therapies and personalized treatment approaches | |
iPSC-based modeling of cancer-induced immunosuppression | Derived iPSCs from cancer cells and immune cells and studied their interactions, revealing the immunosuppressive mechanisms employed by cancer cells to evade immune surveillance | Improved understanding of the mechanisms of cancer-induced immunosuppression, facilitating the development of immunotherapeutic approaches to enhance anti-tumor immune responses | |
iPSC-based modeling of cancer cell plasticity and lineage reprogramming | Induced lineage reprogramming in iPSC-derived cancer cells and investigated their potential to acquire different cell fates, providing insights into cancer cell plasticity and transdifferentiation | Advanced our understanding of the phenotypic plasticity of cancer cells and their ability to switch between different cell types, contributing to the development of targeted therapies | |
iPSC-based modeling of cancer metastatic niche formation | Generated iPSCs from metastatic cancer cells and investigated their interactions with the microenvironment at metastatic sites, uncovering the processes involved in the formation of premetastatic niches | Enhanced understanding of the interactions between metastatic cancer cells and the microenvironment, opening up new avenues for the prevention and treatment of cancer metastasis | |
iPSC-based modeling of cancer cell invasion and migration | Generated iPSCs from invasive cancer cells and investigated their migratory behavior, revealing the molecular mechanisms involved in cancer cell invasion and migration | Improved understanding of the processes driving cancer cell invasion and migration, providing potential targets for inhibiting metastasis | |
iPSC-based modeling of tumor angiogenesis | Derived iPSCs from cancer cells and endothelial cells to study the process of tumor angiogenesis, uncovering the factors and signaling pathways involved in promoting blood vessel formation in tumors | Enhanced understanding of the mechanisms underlying tumor angiogenesis, facilitating the development of anti-angiogenic therapies for cancer treatment | |
iPSC-based modeling of immune cell interactions in the tumor microenvironment | Generated iPSCs from immune cells and cancer cells to study their interactions within the tumor microenvironment, elucidating the dynamics of immune cell infiltration, activation, and suppression | Advanced our understanding of the complex interplay between immune cells and cancer cells in the tumor microenvironment, guiding the development of immunotherapeutic strategies | |
iPSC-based modeling of cancer cell metabolism rewiring | Analyzed the metabolic profile of iPSC-derived cancer cells and identified metabolic alterations and rewiring associated with cancer development and progression | Provided insights into the metabolic adaptations of cancer cells, offering potential targets for metabolic therapies in cancer treatment | [700] |
iPSC-based modeling of cancer cell senescence and aging | Induced cellular senescence in iPSC-derived cancer cells and studied the effects of senescence on cancer cell behavior and response to therapy, revealing the impact of cellular aging on tumor progression and treatment outcomes | Enhanced understanding of the role of senescence in cancer cell biology and its implications for therapeutic interventions | |
iPSC-based modeling of cancer-associated pain | Generated iPSCs from patients with cancer-associated pain and investigated the mechanisms underlying pain perception in cancer, identifying potential targets for pain management and relief | Provided insights into the molecular and cellular basis of cancer-associated pain, contributing to the development of personalized pain management strategies | |
iPSC-based modeling of immune cell therapies for cancer | Generated iPSCs from patient-derived immune cells and engineered them to express chimeric antigen receptors (CARs) or T cell receptors (TCRs), providing a platform for studying the efficacy and safety of immune cell therapies | Advanced our understanding of immune cell therapies for cancer, facilitating the development of improved strategies for enhancing anti-tumor immune responses | |
iPSC-based modeling of cancer-associated fibrosis | Derived iPSCs from fibroblasts within tumor tissues and studied their role in promoting cancer-associated fibrosis, revealing the mechanisms underlying fibrotic changes in the tumor microenvironment | Improved understanding of the role of cancer-associated fibrosis in tumor progression and resistance to therapy, suggesting potential targets for intervention | |
iPSC-based modeling of cancer metabolism heterogeneity | Analyzed metabolic variations among iPSC-derived cancer cells from different patients and tumor types, uncovering metabolic heterogeneity in cancer and its implications for personalized treatment approaches | Enhanced understanding of the metabolic diversity of cancer cells, guiding the development of tailored metabolic therapies | |
iPSC-based modeling of cancer cell dormancy in bone marrow niches | Co-cultured iPSC-derived cancer cells with bone marrow stromal cells to mimic the bone marrow microenvironment and investigated the mechanisms underlying cancer cell dormancy in bone metastases | Provided insights into the factors contributing to cancer cell dormancy in the bone marrow and potential strategies to target dormant cells for improved treatment outcomes | |
iPSC-based modeling of tumor immunosurveillance escape mechanisms | Derived iPSCs from tumor cells and investigated the mechanisms by which cancer cells evade immune recognition and destruction, revealing the strategies employed by tumors to evade immunosurveillance | Advanced our understanding of immune evasion mechanisms in cancer, informing the development of immunotherapies to overcome immune escape | |
iPSC-based modeling of tumor suppressor gene mutations in cancer | Generated iPSCs from patients with inherited or acquired tumor suppressor gene mutations and studied the consequences of these mutations on cancer development and progression | Provided insights into the role of tumor suppressor genes in cancer pathogenesis, aiding in the identification of potential therapeutic targets | |
iPSC-based modeling of cancer cell immune evasion through immune checkpoint pathways | Generated iPSCs from cancer cells and investigated the expression and regulation of immune checkpoint molecules, providing insights into the mechanisms of immune evasion in cancer | Enhanced understanding of the role of immune checkpoint pathways in cancer immune evasion, informing the development of targeted immunotherapies | [715] |
iPSC-based modeling of cancer cell metabolism and microenvironment interactions | Co-cultured iPSC-derived cancer cells with different cell types representing the tumor microenvironment and studied their metabolic interactions, revealing the metabolic crosstalk between cancer cells and surrounding cells | Improved understanding of the metabolic interplay within the tumor microenvironment, suggesting potential metabolic targets for cancer therapy | |
iPSC-based modeling of cancer cell resistance to radiation therapy | Induced iPSC-derived cancer cells to undergo radiation treatment and investigated the mechanisms of radioresistance, uncovering factors contributing to cancer cell survival and resistance to radiation therapy | Provided insights into the mechanisms underlying resistance to radiation therapy, guiding the development of strategies to overcome radioresistance | |
iPSC-based modeling of tumor dormancy and recurrence after therapy | Generated iPSCs from residual tumor cells following treatment and studied their ability to reinitiate tumor growth, providing insights into the mechanisms of tumor dormancy and recurrence | Advanced our understanding of tumor dormancy and recurrence, facilitating the development of strategies to prevent tumor relapse after therapy | |
iPSC-based modeling of cancer cell metabolism and therapeutic response | Analyzed the metabolic profile of iPSC-derived cancer cells and correlated it with their response to different therapies, identifying metabolic markers predictive of therapeutic outcomes | Provided insights into the relationship between cancer cell metabolism and treatment response, guiding the development of personalized treatment strategies | |
iPSC-based modeling of cancer cell heterogeneity and clonal evolution during therapy | Generated iPSCs from multiple tumor subclones within a patient and studied their response to therapy, revealing the dynamics of clonal evolution and the emergence of resistant subclones | Improved understanding of tumor heterogeneity and clonal evolution during therapy, informing the design of combination therapies and strategies to prevent therapy resistance |