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Torisawa, Yu-suke, Yuta Mishima, and Shin Kaneko. "Developing thymus-on-a-chip and cancer-on-a-chip for cancer immunotherapy." Impact 2019, no. 2 (2019): 33–35. http://dx.doi.org/10.21820/23987073.2019.2.33.
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Zhang, Xiaojun, Mazharul Karim, Md Mahedi Hasan, et al. "Cancer-on-a-Chip: Models for Studying Metastasis." Cancers 14, no. 3 (2022): 648. http://dx.doi.org/10.3390/cancers14030648.
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The microfluidic-based cancer-on-a-chip models work as a powerful tool to study the tumor microenvironment and its role in metastasis. The models recapitulate and systematically simplify the in vitro tumor microenvironment. This enables the study of a metastatic process in unprecedented detail. This review examines the development of cancer-on-a-chip microfluidic platforms at the invasion/intravasation, extravasation, and angiogenesis steps over the last three years. The on-chip modeling of mechanical cues involved in the metastasis cascade are also discussed. Finally, the popular design of microfluidic chip models for each step are discussed along with the challenges and perspectives of cancer-on-a-chip models.
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Lee, I.-Chi. "Cancer-on-a-chip for Drug Screening." Current Pharmaceutical Design 24, no. 45 (2019): 5407–18. http://dx.doi.org/10.2174/1381612825666190206235233.
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: The oncology pharmaceutical research spent a shocking amount of money on target validation and drug optimization in preclinical models because many oncology drugs fail during clinical trial phase III. One of the most important reasons for oncology drug failures in clinical trials may due to the poor predictive tool of existing preclinical models. Therefore, in cancer research and personalized medicine field, it is critical to improve the effectiveness of preclinical predictions of the drug response of patients to therapies and to reduce costly failures in clinical trials. Three dimensional (3D) tumor models combine micro-manufacturing technologies mimic critical physiologic parameters present in vivo, including complex multicellular architecture with multicellular arrangement and extracellular matrix deposition, packed 3D structures with cell–cell interactions, such as tight junctions, barriers to mass transport of drugs, nutrients and other factors, which are similar to in vivo tumor tissues. These systems provide a solution to mimic the physiological environment for improving predictive accuracy in oncology drug discovery. : his review gives an overview of the innovations, development and limitations of different types of tumor-like construction techniques such as self-assemble spheroid formation, spheroids formation by micro-manufacturing technologies, micro-dissected tumor tissues and tumor organoid. Combination of 3D tumor-like construction and microfluidic techniques to achieve tumor on a chip for in vitro tumor environment modeling and drug screening were all included. Eventually, developmental directions and technical challenges in the research field are also discussed. We believe tumor on chip models have provided better sufficient clinical predictive power and will bridge the gap between proof-of-concept studies and a wider implementation within the oncology drug development for pathophysiological applications.
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Hao, Hsu-Chao, and Da-Jeng Yao. "Detection of Cancer Cells on a Chip." Current Topics in Medicinal Chemistry 15, no. 15 (2015): 1543–50. http://dx.doi.org/10.2174/1568026615666150414150950.
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Elmusrati, Mohammed, and Nureddin Ashammakhi. "Cancer-on-a-Chip and Artificial Intelligence." Journal of Craniofacial Surgery 29, no. 7 (2018): 1682–83. http://dx.doi.org/10.1097/scs.0000000000004703.
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Komen, Job, Sanne M. van Neerven, Elsbeth G. B. M. Bossink, et al. "The Effect of Dynamic, In Vivo-like Oxaliplatin on HCT116 Spheroids in a Cancer-on-Chip Model Is Representative of the Response in Xenografts." Micromachines 13, no. 5 (2022): 739. http://dx.doi.org/10.3390/mi13050739.
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The cancer xenograft model in which human cancer cells are implanted in a mouse is one of the most used preclinical models to test the efficacy of novel cancer drugs. However, the model is imperfect; animal models are ethically burdened, and the imperfect efficacy predictions contribute to high clinical attrition of novel drugs. If microfluidic cancer-on-chip models could recapitulate key elements of the xenograft model, then these models could substitute the xenograft model and subsequently surpass the xenograft model by reducing variation, increasing sensitivity and scale, and adding human factors. Here, we exposed HCT116 colorectal cancer spheroids to dynamic, in vivo-like, concentrations of oxaliplatin, including a 5 day drug-free period, on-chip. Growth inhibition on-chip was comparable to existing xenograft studies. Furthermore, immunohistochemistry showed a similar response in proliferation and apoptosis markers. While small volume changes in xenografts are hard to detect, in the chip-system, we could observe a temporary growth delay. Lastly, histopathology and a pharmacodynamic model showed that the cancer spheroid-on-chip was representative of the proliferating outer part of a HCT116 xenograft, thereby capturing the major driver of the drug response of the xenograft. Hence, the cancer-on-chip model recapitulated the response of HCT116 xenografts to oxaliplatin and provided additional drug efficacy information.
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Zuchowska, Agnieszka, and Sandra Skorupska. "Multi-organ-on-chip approach in cancer research." Organs-on-a-Chip 4 (December 2022): 100014. http://dx.doi.org/10.1016/j.ooc.2021.100014.
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Fey, M. F. "The impact of chip technology on cancer medicine." Annals of Oncology 13 (October 2002): 109–13. http://dx.doi.org/10.1093/annonc/mdf647.
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Sabour, Andrew F., Seung-min Park, Jun Ho Son, and Luke P. Lee. "An On-Chip Pcr Approach Enabling Cancer Diagnosis." Biophysical Journal 106, no. 2 (2014): 618a. http://dx.doi.org/10.1016/j.bpj.2013.11.3420.
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MASUDA, Taisuke, Miyako NIIMI, Hayao NAKANISHI, and Fumihito ARAI. "7B21 On-chip Cancer Diagnosis for Early Recognition of Gastric Cancer." Proceedings of the Bioengineering Conference Annual Meeting of BED/JSME 2012.24 (2012): _7B21–1_—_7B21–2_. http://dx.doi.org/10.1299/jsmebio.2012.24._7b21-1_.
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Liu, Qiang, Tian Zhao, Xianning Wang, Zhongyao Chen, Yawei Hu, and Xiaofang Chen. "In Situ Vitrification of Lung Cancer Organoids on a Microwell Array." Micromachines 12, no. 6 (2021): 624. http://dx.doi.org/10.3390/mi12060624.
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Three-dimensional cultured patient-derived cancer organoids (PDOs) represent a powerful tool for anti-cancer drug development due to their similarity to the in vivo tumor tissues. However, the culture and manipulation of PDOs is more difficult than 2D cultured cell lines due to the presence of the culture matrix and the 3D feature of the organoids. In our other study, we established a method for lung cancer organoid (LCO)-based drug sensitivity tests on the superhydrophobic microwell array chip (SMAR-chip). Here, we describe a novel in situ cryopreservation technology on the SMAR-chip to preserve the viability of the organoids for future drug sensitivity tests. We compared two cryopreservation approaches (slow freezing and vitrification) and demonstrated that vitrification performed better at preserving the viability of LCOs. Next, we developed a simple procedure for in situ cryopreservation and thawing of the LCOs on the SMAR-chip. We proved that the on-chip cryopreserved organoids can be recovered successfully and, more importantly, showing similar responses to anti-cancer drugs as the unfrozen controls. This in situ vitrification technology eliminated the harvesting and centrifugation steps in conventional cryopreservation, making the whole freeze–thaw process easier to perform and the preserved LCOs ready to be used for the subsequent drug sensitivity test.
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Bērziņa, Santa, Alexandra Harrison, Valérie Taly, and Wenjin Xiao. "Technological Advances in Tumor-On-Chip Technology: From Bench to Bedside." Cancers 13, no. 16 (2021): 4192. http://dx.doi.org/10.3390/cancers13164192.
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Tumor-on-chip technology has cemented its importance as an in vitro tumor model for cancer research. Its ability to recapitulate different elements of the in vivo tumor microenvironment makes it promising for translational medicine, with potential application in enabling personalized anti-cancer therapies. Here, we provide an overview of the current technological advances for tumor-on-chip generation. To further elevate the functionalities of the technology, these approaches need to be coupled with effective analysis tools. This aspect of tumor-on-chip technology is often neglected in the current literature. We address this shortcoming by reviewing state-of-the-art on-chip analysis tools for microfluidic tumor models. Lastly, we focus on the current progress in tumor-on-chip devices using patient-derived samples and evaluate their potential for clinical research and personalized medicine applications.
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Gambari, Roberto, Monica Borgatti, Luigi Altomare, et al. "Applications to Cancer Research of “Lab-on-a-chip” Devices Based on Dielectrophoresis (DEP)." Technology in Cancer Research & Treatment 2, no. 1 (2003): 31–39. http://dx.doi.org/10.1177/153303460300200105.
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The recent development of advanced analytical and bioseparation methodologies based on microarrays and biosensors is one of the strategic objectives of the so-called post-genomic. In this field, the development of microfabricated devices could bring new opportunities in several application fields, such as predictive oncology, diagnostics and anti-tumor drug research. The so called “Laboratory-on-a-chip technology”, involving miniaturisation of analytical procedures, is expected to enable highly complex laboratory testing to move from the central laboratory into non-laboratory settings. The main advantages of Lab-on-a-chip devices are integration of multiple steps of different analytical procedures, large variety of applications, sub-microliter consumption of reagents and samples, and portability. One of the requirement for new generation Lab-on-a-chip devices is the possibility to be independent from additional preparative/analytical instruments. Ideally, Lab-on-a-chip devices should be able to perform with high efficiency and reproducibility both actuating and sensing procedures. In this review, we discuss applications of dielectrophoretic(DEP)-based Lab-on-a-chip devices to cancer research. The theory of dielectrophoresis as well as the description of several devices, based on spiral-shaped, parallel and arrayed electrodes are here presented. In addition, in this review we describe manipulation of cancer cells using advanced DEP-based Lab-on-a-chip devices in the absence of fluid flow and with the integration of both actuating and sensing procedures.
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Regmi, Sagar, Chetan Poudel, Rameshwar Adhikari, and Kathy Qian Luo. "Applications of Microfluidics and Organ-on-a-Chip in Cancer Research." Biosensors 12, no. 7 (2022): 459. http://dx.doi.org/10.3390/bios12070459.
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Taking the life of nearly 10 million people annually, cancer has become one of the major causes of mortality worldwide and a hot topic for researchers to find innovative approaches to demystify the disease and drug development. Having its root lying in microelectronics, microfluidics seems to hold great potential to explore our limited knowledge in the field of oncology. It offers numerous advantages such as a low sample volume, minimal cost, parallelization, and portability and has been advanced in the field of molecular biology and chemical synthesis. The platform has been proved to be valuable in cancer research, especially for diagnostics and prognosis purposes and has been successfully employed in recent years. Organ-on-a-chip, a biomimetic microfluidic platform, simulating the complexity of a human organ, has emerged as a breakthrough in cancer research as it provides a dynamic platform to simulate tumor growth and progression in a chip. This paper aims at giving an overview of microfluidics and organ-on-a-chip technology incorporating their historical development, physics of fluid flow and application in oncology. The current applications of microfluidics and organ-on-a-chip in the field of cancer research have been copiously discussed integrating the major application areas such as the isolation of CTCs, studying the cancer cell phenotype as well as metastasis, replicating TME in organ-on-a-chip and drug development. This technology’s significance and limitations are also addressed, giving readers a comprehensive picture of the ability of the microfluidic platform to advance the field of oncology.
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Liu, Yan, Qingzhen Yang, Hui Zhang, et al. "Construction of cancer-on-a-chip for drug screening." Drug Discovery Today 26, no. 8 (2021): 1875–90. http://dx.doi.org/10.1016/j.drudis.2021.03.006.
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Lin, Tianxiu. "Organ-on-a-Chip Models for Pancreatic Cancer Research." International Journal of Sciences 9, no. 02 (2020): 49–56. http://dx.doi.org/10.18483/ijsci.2253.
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He, J. H., J. Reboud, H. Ji, L. Zhang, Y. Long, and C. Lee. "Biomicrofluidic lab-on-chip device for cancer cell detection." Applied Physics Letters 93, no. 22 (2008): 223905. http://dx.doi.org/10.1063/1.3040313.
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Lee, Esak, H.-H. Greco Song, and Christopher S. Chen. "Biomimetic on-a-chip platforms for studying cancer metastasis." Current Opinion in Chemical Engineering 11 (February 2016): 20–27. http://dx.doi.org/10.1016/j.coche.2015.12.001.
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Özyurt, Canan, İnci Uludağ, Bahar İnce, and Mustafa Kemal Sezgintürk. "Lab-on-a-chip systems for cancer biomarker diagnosis." Journal of Pharmaceutical and Biomedical Analysis 226 (March 2023): 115266. http://dx.doi.org/10.1016/j.jpba.2023.115266.
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S. Rao, Roopa, Shankargouda Patil, and B. S. Ganavi. "Oral cancer-on-a-chip: A biomimicry to transform oral cancer research?" Journal of Medicine, Radiology, Pathology & Surgery 1, no. 2 (2015): 1–2. http://dx.doi.org/10.15713/ins.jmrps.7.
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Ustun, Merve, Sajjad Rahmani Dabbagh, Irem Ilci, Tugba Bagci-Onder, and Savas Tasoglu. "Glioma-on-a-Chip Models." Micromachines 12, no. 5 (2021): 490. http://dx.doi.org/10.3390/mi12050490.
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Glioma, as an aggressive type of cancer, accounts for virtually 80% of malignant brain tumors. Despite advances in therapeutic approaches, the long-term survival of glioma patients is poor (it is usually fatal within 12–14 months). Glioma-on-chip platforms, with continuous perfusion, mimic in vivo metabolic functions of cancer cells for analytical purposes. This offers an unprecedented opportunity for understanding the underlying reasons that arise glioma, determining the most effective radiotherapy approach, testing different drug combinations, and screening conceivable side effects of drugs on other organs. Glioma-on-chip technologies can ultimately enhance the efficacy of treatments, promote the survival rate of patients, and pave a path for personalized medicine. In this perspective paper, we briefly review the latest developments of glioma-on-chip technologies, such as therapy applications, drug screening, and cell behavior studies, and discuss the current challenges as well as future research directions in this field.
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Tsai, Hsieh-Fu, Alen Trubelja, Amy Q. Shen, and Gang Bao. "Tumour-on-a-chip: microfluidic models of tumour morphology, growth and microenvironment." Journal of The Royal Society Interface 14, no. 131 (2017): 20170137. http://dx.doi.org/10.1098/rsif.2017.0137.
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Cancer remains one of the leading causes of death, albeit enormous efforts to cure the disease. To overcome the major challenges in cancer therapy, we need to have a better understanding of the tumour microenvironment (TME), as well as a more effective means to screen anti-cancer drug leads; both can be achieved using advanced technologies, including the emerging tumour-on-a-chip technology. Here, we review the recent development of the tumour-on-a-chip technology, which integrates microfluidics, microfabrication, tissue engineering and biomaterials research, and offers new opportunities for building and applying functional three-dimensional in vitro human tumour models for oncology research, immunotherapy studies and drug screening. In particular, tumour-on-a-chip microdevices allow well-controlled microscopic studies of the interaction among tumour cells, immune cells and cells in the TME, of which simple tissue cultures and animal models are not amenable to do. The challenges in developing the next-generation tumour-on-a-chip technology are also discussed.
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Marturano-Kruik, Alessandro, Michele Maria Nava, Keith Yeager, et al. "Human bone perivascular niche-on-a-chip for studying metastatic colonization." Proceedings of the National Academy of Sciences 115, no. 6 (2018): 1256–61. http://dx.doi.org/10.1073/pnas.1714282115.
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Eight out of 10 breast cancer patients die within 5 years after the primary tumor has spread to the bones. Tumor cells disseminated from the breast roam the vasculature, colonizing perivascular niches around blood capillaries. Slow flows support the niche maintenance by driving the oxygen, nutrients, and signaling factors from the blood into the interstitial tissue, while extracellular matrix, endothelial cells, and mesenchymal stem cells regulate metastatic homing. Here, we show the feasibility of developing a perfused bone perivascular niche-on-a-chip to investigate the progression and drug resistance of breast cancer cells colonizing the bone. The model is a functional human triculture with stable vascular networks within a 3D native bone matrix cultured on a microfluidic chip. Providing the niche-on-a-chip with controlled flow velocities, shear stresses, and oxygen gradients, we established a long-lasting, self-assembled vascular network without supplementation of angiogenic factors. We further show that human bone marrow-derived mesenchymal stem cells, which have undergone phenotypical transition toward perivascular cell lineages, support the formation of capillary-like structures lining the vascular lumen. Finally, breast cancer cells exposed to interstitial flow within the bone perivascular niche-on-a-chip persist in a slow-proliferative state associated with increased drug resistance. We propose that the bone perivascular niche-on-a-chip with interstitial flow promotes the formation of stable vasculature and mediates cancer cell colonization.
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Lee, Jae-Sung, Sae-Wan Kim, Eun-Yoon Jang, et al. "Rapid and Sensitive Detection of Lung Cancer Biomarker Using Nanoporous Biosensor Based on Localized Surface Plasmon Resonance Coupled with Interferometry." Journal of Nanomaterials 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/183438.
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We propose a nanobiosensor to evaluate a lung cancer-specific biomarker. The nanobiosensor is based on an anodic aluminum oxide (AAO) chip and functions on the principles of localized surface plasmon resonance (LSPR) and interferometry. The pore-depth of the fabricated nanoporous AAO chip was 1 µm and was obtained using a two-step electrochemical anodization process. The sensor chip is sensitive to the refractive index (RI) changes of the surrounding medium and also provides simple and label-free detection when specific antibodies are immobilized on the gold-deposited surface of the AAO chip. In order to confirm the effectiveness of the sensor, the antibodies were immobilized on the surface of the AAO chip, and the lung cancer-specific biomarker was applied atop of the immobilized-antibody layer using the self-assembled monolayer method. The nanoporous AAO chip was used as a sensor system to detect serum amyloid A1, which is a lung cancer-specific biomarker. The specific reaction of the antigen-antibody contributes to the change in the RI. This in turn causes a shift in the resonance spectrum in the refractive interference pattern. The limit of detection (LOD) was found to be 100 ag/mL and the biosensor had high sensitivity over a wide concentration range.
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Desai, Pinkal, Samuel Handelman, Alan Wu, et al. "Antecedent Clonal Hematopoesis and Risk of and Mortality after Solid and Hematological Malignancies: Analyses from the Women's Health Initiative Study." Blood 134, Supplement_1 (2019): 1199. http://dx.doi.org/10.1182/blood-2019-131862.
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Background: Whole genome analyses of peripheral blood has demonstrated that acquired somatic mutations in peripheral blood also known as clonal hematopoiesis of indeterminate potential (CHIP) is present in up to 10% of individuals older than 60 years and associated with increased risk of cardiovascular mortality and hematologic malignancies (Jaiswal et al, Genovese et al, NEJM 2014). We have demonstrated that CHIP is associated specifically with increased risk of leukemia (Desai et al, Nat. Medicine 2018). CHIP has also been detected in 25% of individuals with concomitant advanced solid malignancies using targeted deep sequencing (Coombs et al, 2017). However, the role of antecedent CHIP in risk of solid malignancies has not been established due to lack of non-cancer controls and absence of CHIP data before the diagnosis of cancer in the published literature. The role of antecedent CHIP in cancer specific and non-cancer specific mortality after diagnosis of cancer is also not known. Methods: We analyzed whole genome sequencing data (30X coverage) from 10,089 participants in the Women's Health Initiative (WHI) enrolled in the Trans-Omics for Precision Medicine (TOPMED) consortium to assess the relationship between antecedent CHIP measured at baseline entry into the study, and cancer risk and mortality after cancer. Cox proportional hazards regression models were used to evaluate the relationship between CHIP and cancer risk, all-cause mortality as well as mortality due to cancer, cardiovascular disease (CVD) and other causes. All statistical tests are two-sided with an alpha level of 0.05. Results: Of 10,089 eligible participants, the overall rate of CHIP mutations was 9.3 % and the most common CHIP mutations included DNMT3A (55%), TET2 (19%), and ASXL1 (7.1%). CHIP was associated with both current and past history of smoking and the best-fit model suggested a dose dependent relationship by pack years. Over 13±6 years of follow-up, there were 2,337 women diagnosed with at least one cancer including (at 7±5 years of follow-up) 774 with breast cancer, 319 with colon, 355 with lung and 282 with hematologic malignancies. Among patients with cancer, there were 813 cancer specific deaths and 3,946 non-cancer related deaths. Among participants with and without a previous history of cancer, CHIP was detected in 8.4% and 9.3% of participants respectively. PPM1D or TP53 (n=50, of whom 8 had a previous history of malignancy) mutations were detected in 3.6% and 1.7 % of total participants with CH. 29% of participants with TP53 or PPM1D CHIP developed a future cancer , compared to 26% in non TP53/PPM1D CHIP and 21% without CHIP. There was no significant difference in TP53 CHIP in patients with or without previous history of cancer. After excluding 697 participants with a previous history of malignancy, antecedent CHIP (prior to the diagnosis of cancer) was not significantly associated with risk of solid malignancy overall (Hazards Ratio (HR), 95% confidence interval (CI) 1.07, (0.94−1.23) p=0.31). However, there was a borderline increased risk of breast cancer (HR, 95% CI, 1.23, (1.003−1.25) P=0.04) and no association with lung (HR 1.23, P=0.15) or colon cancer (HR 0.96, P=0.86). Among participants with solid malignancies, CHIP was associated with an increased cancer specific mortality (HR, 95% CI, 1.24 (1.02−1.51), p=0.03) but no association with mortality due to CVD post diagnosis of solid malignancy (HR 0.63, P=0.51) was seen. Any antecedent CHIP mutation was associated with increased risk of hematological malignancies (HR, 95% CI, 1.76, (1.25−2.48), p<0.002) with a higher risk of hematological malignancy seen with increased clonal complexity. Among patients with hematological malignancies, antecedent CHIP was associated with increased mortality from hematological malignancy (HR, 95% CI 1.45, (1.10−1.92) p=0.007) and not associated with increased cardiovascular mortality post diagnosis of the hematological disorder (HR 0.63, p=0.51). Conclusion: This is the first report to relate antecedent CHIP with solid tumor risk and mortality in a multi-site study of post-menopausal women. Antecedent CHIP was associated with increased solid cancer specific mortality but not with risk of solid malignancy or CVD mortality post cancer diagnosis. It is possible that deeper, targeted sequencing may identify an association between antecedent CHIP and the incidence of solid tumors; further investigation is warranted. Disclosures Desai: Sanofi: Consultancy; Astellas: Honoraria; Astex: Research Funding; Cellerant: Consultancy; Celgene: Consultancy. Lee:Helsinn: Consultancy; Jazz Pharmaceuticals, Inc: Consultancy; Roche Molecular Systems: Consultancy; AstraZeneca Pharmaceuticals: Consultancy; Karyopharm Therapeutics: Consultancy; Ai Therapeutics: Research Funding. Ritchie:Celgene, Incyte, Novartis, Pfizer: Consultancy; Ariad, Celgene, Incyte, Novartis: Speakers Bureau; AStella, Bristol-Myers Squibb, Novartis, NS Pharma, Pfizer: Research Funding; Celgene, Novartis: Other: travel support; Jazz Pharmaceuticals: Research Funding; Celgene: Other: Advisory board; Pfizer: Other: Advisory board, travel support; agios: Other: Advisory board; Tolero: Other: Advisory board; Genentech: Other: Advisory board. Guzman:Samus Therapeutics: Patents & Royalties: intellectual rights to the PU-FITC assay; SeqRx: Consultancy; Cellectis: Research Funding. Roboz:AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Actinium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amphivena: Consultancy, Membership on an entity's Board of Directors or advisory committees; Argenx: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astex: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Eisai: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Orsenix: Consultancy, Membership on an entity's Board of Directors or advisory committees; Otsuka: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Trovagene: Consultancy, Membership on an entity's Board of Directors or advisory committees.
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Ngo, Huyen, Sarnai Amartumur, Van Thi Ai Tran, et al. "In Vitro Tumor Models on Chip and Integrated Microphysiological Analysis Platform (MAP) for Life Sciences and High-Throughput Drug Screening." Biosensors 13, no. 2 (2023): 231. http://dx.doi.org/10.3390/bios13020231.
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The evolution of preclinical in vitro cancer models has led to the emergence of human cancer-on-chip or microphysiological analysis platforms (MAPs). Although it has numerous advantages compared to other models, cancer-on-chip technology still faces several challenges such as the complexity of the tumor microenvironment and integrating multiple organs to be widely accepted in cancer research and therapeutics. In this review, we highlight the advancements in cancer-on-chip technology in recapitulating the vital biological features of various cancer types and their applications in life sciences and high-throughput drug screening. We present advances in reconstituting the tumor microenvironment and modeling cancer stages in breast, brain, and other types of cancer. We also discuss the relevance of MAPs in cancer modeling and precision medicine such as effect of flow on cancer growth and the short culture period compared to clinics. The advanced MAPs provide high-throughput platforms with integrated biosensors to monitor real-time cellular responses applied in drug development. We envision that the integrated cancer MAPs has a promising future with regard to cancer research, including cancer biology, drug discovery, and personalized medicine.
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Bretti, Gabriella, Adele De Ninno, Roberto Natalini, Daniele Peri, and Nicole Roselli. "Estimation Algorithm for a Hybrid PDE–ODE Model Inspired by Immunocompetent Cancer-on-Chip Experiment." Axioms 10, no. 4 (2021): 243. http://dx.doi.org/10.3390/axioms10040243.
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The present work is motivated by the development of a mathematical model mimicking the mechanisms observed in lab-on-chip experiments, made to reproduce on microfluidic chips the in vivo reality. Here we consider the Cancer-on-Chip experiment where tumor cells are treated with chemotherapy drug and secrete chemical signals in the environment attracting multiple immune cell species. The in silico model here proposed goes towards the construction of a “digital twin” of the experimental immune cells in the chip environment to better understand the complex mechanisms of immunosurveillance. To this aim, we develop a tumor-immune microfluidic hybrid PDE–ODE model to describe the concentration of chemicals in the Cancer-on-Chip environment and immune cells migration. The development of a trustable simulation algorithm, able to reproduce the immunocompetent dynamics observed in the chip, requires an efficient tool for the calibration of the model parameters. In this respect, the present paper represents a first methodological work to test the feasibility and the soundness of the calibration technique here proposed, based on a multidimensional spline interpolation technique for the time-varying velocity field surfaces obtained from cell trajectories.
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Zhu, Luyao, Changmin Shao, Hanxu Chen, Zhuoyue Chen, and Yuanjin Zhao. "Hierarchical Hydrogels with Ordered Micro-Nano Structures for Cancer-on-a-Chip Construction." Research 2021 (December 26, 2021): 1–9. http://dx.doi.org/10.34133/2021/9845679.
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In the drug therapy of tumor, efficient and stable drug screening platforms are required since the drug efficacy varies individually. Here, inspired by the microstructures of hepatic lobules, in which hepatocytes obtain nutrients from both capillary vessel and the central vein, we present a novel hierarchical hydrogel system with ordered micro-nano structure for liver cancer-on-a-chip construction and drug screening. The hierarchical hydrogel system was fabricated by using pregel to fill and replicate self-assembled colloidal crystal arrays and microcolumn array template. Due to the synergistic effect of its interconnected micro-nano structures, the resultant system could not only precisely control the size of cell spheroids but also realize adequate nutrient supply of cell spheroids. We have demonstrated that by integrating the hierarchical hydrogel system into a multichannel concentration gradients microfluidic chip, a functional liver cancer-on-a-chip could be constructed for high-throughput drug screening with good repeatability and high accuracy. These results indicated that the hierarchical hydrogel system and its derived liver cancer-on-a-chip are ideal platforms for drug screening and have great application potential in the field of personalized medicine.
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Holler, Albert E., Lukasz Gondek, Hua-Ling Tsai, et al. "Clonal hematopoiesis of indeterminate potential (CHIP) and association with response to bipolar androgen therapy (BAT)." Journal of Clinical Oncology 41, no. 16_suppl (2023): e17048-e17048. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.e17048.
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e17048 Background: CHIP, the expansion of hematopoietic cells carrying acquired somatic alterations associated with hematologic malignancies, is associated with increased inflammation, risk of heart disease, and poor outcomes. BAT, where testosterone levels are therapeutically manipulated between castrate levels to supraphysiologic levels, has been shown to be an effective therapy for some men with castration resistant prostate cancer. Clinical predictors of response are not established. We hypothesized that CHIP, would be negatively associated with clinical outcomes. Methods: Baseline peripheral blood from participants on the RESTORE Cohort C (NCT02090114) were analyzed for the presence of CHIP. Patients in this cohort had castration resistant prostate cancer with progressive disease after treatment with ADT alone. All participants were treated with 400mg of intramuscular testosterone cypionate every 28 days. Peripheral blood mononuclear cells were analyzed for the presence of CHIP using targeted next generation sequencing focused on 49 genes most commonly mutated in CHIP and myeloid malignancies. Given patients had metastatic and non-metastatic CRPC, progression free survival was determined based on the time to the start of the next therapy. Results: CHIP was present in 6 of 29 patients at baseline (21%) with one patient having 2 clones (Table). Median age of patients CHIP+ was 73 compared to age of 68 in the CHIP- group (p = 0.16). Median PSA was higher in the CHIP+ group (median 15, IQR 1-56) compared to the CHIP- group (median 3.5, IQR 1-57). 67% of the CHIP+ group and 57% of the CHIP- group had baseline Gleason scores of > = 8. The CHIP+ group had a median PFS of 8.8 months compared to 13.3 months in the CHIP- group (HR 3.3 95%CI 1.2, 9.1; p = 0.02). This remained significant after adjusting for age. There was no difference in overall survival (HR = 2.5 95% CI 0.5,2.9; p = 0.3). Conclusions: Among men treated with BAT as first line treatment for CRPC after ADT alone, CHIP was associated with a decreased progression free survival. Larger studies are needed to understand the impact of CHIP in larger cohorts of men treated with BAT and other therapies for prostate cancer.[Table: see text]
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Yu, Xiaolei, Bingrui Wang, Nangang Zhang, et al. "Capture and Release of Cancer Cells by Combining On-Chip Purification and Off-Chip Enzymatic Treatment." ACS Applied Materials & Interfaces 7, no. 43 (2015): 24001–7. http://dx.doi.org/10.1021/acsami.5b06791.
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Caballero, D., S. Kaushik, V. M. Correlo, J. M. Oliveira, R. L. Reis, and S. C. Kundu. "Organ-on-chip models of cancer metastasis for future personalized medicine: From chip to the patient." Biomaterials 149 (December 2017): 98–115. http://dx.doi.org/10.1016/j.biomaterials.2017.10.005.
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LI, CHIYU, WANG LI, CHUNYANG GENG, HAIJUN REN, XIAOHUI YU, and BO LIU. "MICROFLUIDIC CHIP FOR CANCER CELL DETECTION AND DIAGNOSIS." Journal of Mechanics in Medicine and Biology 18, no. 01 (2018): 1830001. http://dx.doi.org/10.1142/s0219519418300016.
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Since cancer becomes the most deadly disease to our health, research on early detection on cancer cells is necessary for clinical treatment. The combination of microfluidic device with cell biology has shown a unique method for cancer cell research. In the present review, recent development on microfluidic chip for cancer cell detection and diagnosis will be addressed. Some typical microfluidic chips focussed on cancer cells and their advantages for different kinds of cancer cell detection and diagnosis will be listed, and the cell capture methods within the microfluidics will be simultaneously mentioned. Then the potential direction of microfluidic chip on cancer cell detection and diagnosis in the future is also discussed.
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Duzagac, Fahriye, Gloria Saorin, Lorenzo Memeo, Vincenzo Canzonieri, and Flavio Rizzolio. "Microfluidic Organoids-on-a-Chip: Quantum Leap in Cancer Research." Cancers 13, no. 4 (2021): 737. http://dx.doi.org/10.3390/cancers13040737.
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Organ-like cell clusters, so-called organoids, which exhibit self-organized and similar organ functionality as the tissue of origin, have provided a whole new level of bioinspiration for ex vivo systems. Microfluidic organoid or organs-on-a-chip platforms are a new group of micro-engineered promising models that recapitulate 3D tissue structure and physiology and combines several advantages of current in vivo and in vitro models. Microfluidics technology is used in numerous applications since it allows us to control and manipulate fluid flows with a high degree of accuracy. This system is an emerging tool for understanding disease development and progression, especially for personalized therapeutic strategies for cancer treatment, which provide well-grounded, cost-effective, powerful, fast, and reproducible results. In this review, we highlight how the organoid-on-a-chip models have improved the potential of efficiency and reproducibility of organoid cultures. More widely, we discuss current challenges and development on organoid culture systems together with microfluidic approaches and their limitations. Finally, we describe the recent progress and potential utilization in the organs-on-a-chip practice.
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Ngan Ngo, Thi Kim, Cheng-Hsiang Kuo, and Ting-Yuan Tu. "Recent advances in microfluidic-based cancer immunotherapy-on-a-chip strategies." Biomicrofluidics 17, no. 1 (2023): 011501. http://dx.doi.org/10.1063/5.0108792.
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Despite several extraordinary improvements in cancer immunotherapy, its therapeutic effectiveness against many distinct cancer types remains mostly limited and requires further study. Different microfluidic-based cancer immunotherapy-on-a-chip (ITOC) systems have been developed to help researchers replicate the tumor microenvironment and immune system. Numerous microfluidic platforms can potentially be used to perform various on-chip activities related to early clinical cancer immunotherapy processes, such as improving immune checkpoint blockade therapy, studying immune cell dynamics, evaluating cytotoxicity, and creating vaccines or organoid models from patient samples. In this review, we summarize the most recent advancements in the development of various microfluidic-based ITOC devices for cancer treatment niches and present future perspectives on microfluidic devices for immunotherapy research.
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Tan, Jianfeng, Xindi Sun, Jianhua Zhang, et al. "Exploratory Evaluation of EGFR-Targeted Anti-Tumor Drugs for Lung Cancer Based on Lung-on-a-Chip." Biosensors 12, no. 8 (2022): 618. http://dx.doi.org/10.3390/bios12080618.
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In this study, we used three-dimensional (3D) printing to prepare a template of a microfluidic chip from which a polydimethylsiloxane (PDMS)lung chip was successfully constructed. The upper and lower channels of the chip are separated by a microporous membrane. The upper channel is seeded with lung cancer cells, and the lower channel is seeded with vascular endothelial cells and continuously perfused with cell culture medium. This lung chip can simulate the microenvironment of lung tissue and realize the coculture of two kinds of cells at different levels. We used a two-dimensional (2D) well plate and a 3D lung chip to evaluate the effects of different EGFR-targeting drugs (gefitinib, afatinib, and osimertinib) on tumor cells. The 3D lung chip was superior to the 2D well plate at evaluating the effect of drugs on the NCI-H650, and the results were more consistent with existing clinical data. For primary tumor cells, 3D lung chips have more advantages because they simulate conditions that are more similar to the physiological cell microenvironment. The evaluation of EGFR-targeted drugs on lung chips is of great significance for personalized diagnosis and treatment and pharmacodynamic evaluation.
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Guo, Jia, Tuotuo Gong, Beina Hui, Xu Zhao, and Jing Li. "Screening Tumor-Related Genes of Gallbladder Cancer Based on AR-Based Tumor Expression Profile Gene Chip." Contrast Media & Molecular Imaging 2022 (September 26, 2022): 1–11. http://dx.doi.org/10.1155/2022/8579279.
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The rapid development of molecular biology and gene chip technology has produced a large amount of gene expression profile data. The main research in this article is to screen the tumor-related genes of gallbladder cancer based on AR-based tumor expression profile gene chip. First, convert the chip data into an expression matrix pattern that can be analyzed, and then standardize and normalize all the data. Run ReliefF, GA, and IReliefF-GA on the data set, record the size of the feature subset, and use the tenfold cross-validation method to obtain the classification accuracy, specificity, and sensitivity of each method on the classifier. The target genes used in the chip were amplified by PCR with the universal primers used in cDNA library construction, and the quality of PCR was monitored by agarose gel electrophoresis. The gene chip data of gallbladder cancer was processed with missing values, singular values, and so forth, and 22294 transcripts were obtained. After statistical testing, there were 9483 transcripts with statistically significant differences. The results show that as the number of clusters increases, the network can be better reconstructed through decomposition modeling.
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Flebbe, Hannah, Feda H. Hamdan, Vijayalakshmi Kari, et al. "Epigenome Mapping Identifies Tumor-Specific Gene Expression in Primary Rectal Cancer." Cancers 11, no. 8 (2019): 1142. http://dx.doi.org/10.3390/cancers11081142.
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Epigenetic alterations play a central role in cancer development and progression. The acetylation of histone 3 at lysine 27 (H3K27ac) specifically marks active genes. While chromatin immunoprecipitation (ChIP) followed by next-generation sequencing (ChIP-seq) analyses are commonly performed in cell lines, only limited data are available from primary tumors. We therefore examined whether cancer-specific alterations in H3K27ac occupancy can be identified in primary rectal cancer. Tissue samples from primary rectal cancer and matched mucosa were obtained. ChIP-seq for H3K27ac was performed and differentially occupied regions were identified. The expression of selected genes displaying differential occupancy between tumor and mucosa were examined in gene expression data from an independent patient cohort. Differential expression of four proteins was further examined by immunohistochemistry. ChIP-seq for H3K27ac in primary rectal cancer and matched mucosa was successfully performed and revealed differential binding on 44 regions. This led to the identification of genes with increased H3K27ac, i.e., RIPK2, FOXQ1, KRT23, and EPHX4, which were also highly upregulated in primary rectal cancer in an independent dataset. The increased expression of these four proteins was confirmed by immunohistochemistry. This study demonstrates the feasibility of ChIP-seq-based epigenome mapping of primary rectal cancer and confirms the value of H3K27ac occupancy to predict gene expression differences.
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Park, Jeongmin, GangPyo Ryu, Daniel Nachun, et al. "Abstract 2277: Understanding the impact of clonal hematopoiesis on multiple myeloma: Insights from exosomal RNA analysis and survival analysis." Cancer Research 84, no. 6_Supplement (2024): 2277. http://dx.doi.org/10.1158/1538-7445.am2024-2277.
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Abstract Clonal Hematopoiesis of Indeterminate Potential (CHIP) is a trait characterized by the accumulation of somatic mutations in hematopoietic stem cells in certain adults. It has been observed that the presence of CHIP can have significant implications for the development and prognosis of various blood cancers. Multiple myeloma (MM), a cancer involving the abnormal proliferation of malignant plasma cells in the bone marrow, is one such condition. Exosomes, a type of extracellular vesicles, play a role in cell communication by carrying information between cells. Analysis of UK Biobank data confirmed the poor prognosis of multiple myeloma patients with CHIP and identified a potential of paracrine effect on plasma cancer cells. To gain deeper insights into this paracrine effect on plasma cells, we attempted to analyze cell-to-cell interaction, such as the expression of miRNAs in exosomes, through exosome RNA sequencing. In our research, exosomes were extracted from bone marrow samples of 30 multiple myeloma patients, and exosome RNA sequencing was performed. Differential expression of miRNAs was identified. A total of 14 down-regulated miRNAs were identified based on adjusted p value &lt; 0.05, log2 fold change &lt; -1. We found that hsa-let-7f-5p, hsa-let-7a-5p, and hsa-miR-148a-3p, which are mainly miRNAs targeting MAP kinase, were significantly down-regulated in the CHIP cases. A computational tool was used to predict and integrate the target genes and pathways regulated by these DE miRNAs. The results suggested that certain inflammatory and oncogenic pathways including the MAPK signaling pathways, were not effectively suppressed in cases with CHIP (KEGG, p &lt; 0.005). In addition, the chemokine signaling pathway and cytokine-cytokine receptor interaction (KEGG, p &lt; 0.005) related to the paracrine effect, integrins in angiogenesis (PID, p &lt; 0.005) related to poor prognosis and metastasis of cancer were also not adequately inhibited in the CHIP cases. Using UK Biobank data, we called somatic CHIP variants excluding those with VAF &lt; 0.02 and analyzed them against ICD-10 codes. Hazard ratios (HR) were computed through Cox proportional regression with covariates. CHIP presence significantly correlated with MM diagnosis (HR: 1.64, CI: 1.35-2, p &lt; 0.001), notably in TET2 mutation carriers (HR: 2.35, CI: 1.63-3.4, p &lt; 0.001). TET2 mutations intensified MGUS to MM progression (HR: 5.0, CI: 2.27-11.0, p &lt; 0.001). CHIP in MM impacted EFS (HR: 1.61, CI: 1.25-2.1, p &lt; 0.001), with TET2 mutation carriers facing higher hazards (HR: 1.66, CI: 1.05-2.6, p = 0.031). CHIP, especially TET2 mutations, significantly contribute to adverse MM outcomes and MGUS to MM evolution. Our findings provide insight into how CHIP influences the tumorigenesis and cancer progression of MM. Citation Format: Jeongmin Park, GangPyo Ryu, Daniel Nachun, Maggie Maurer, Siddhartha Jaiswal, Dong-Yeop Shin, Ja Min Byun, Junshik Hong, Youngil Koh, Sung-Soo Yoon. Understanding the impact of clonal hematopoiesis on multiple myeloma: Insights from exosomal RNA analysis and survival analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2277.
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Maulana, Tengku Ibrahim, Elena Kromidas, Lars Wallstabe, et al. "Immunocompetent cancer-on-chip models to assess immuno-oncology therapy." Advanced Drug Delivery Reviews 173 (June 2021): 281–305. http://dx.doi.org/10.1016/j.addr.2021.03.015.
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Del Piccolo, Nuala, Venktesh S. Shirure, Ye Bi, et al. "Tumor-on-chip modeling of organ-specific cancer and metastasis." Advanced Drug Delivery Reviews 175 (August 2021): 113798. http://dx.doi.org/10.1016/j.addr.2021.05.008.
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Imparato, Giorgia, Francesco Urciuolo, and Paolo Antonio Netti. "Organ on Chip Technology to Model Cancer Growth and Metastasis." Bioengineering 9, no. 1 (2022): 28. http://dx.doi.org/10.3390/bioengineering9010028.
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Organ on chip (OOC) has emerged as a major technological breakthrough and distinct model system revolutionizing biomedical research and drug discovery by recapitulating the crucial structural and functional complexity of human organs in vitro. OOC are rapidly emerging as powerful tools for oncology research. Indeed, Cancer on chip (COC) can ideally reproduce certain key aspects of the tumor microenvironment (TME), such as biochemical gradients and niche factors, dynamic cell–cell and cell–matrix interactions, and complex tissue structures composed of tumor and stromal cells. Here, we review the state of the art in COC models with a focus on the microphysiological systems that host multicellular 3D tissue engineering models and can help elucidate the complex biology of TME and cancer growth and progression. Finally, some examples of microengineered tumor models integrated with multi-organ microdevices to study disease progression in different tissues will be presented.
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Selvathi, D., and R. Deiva Nayagam. "FPGA implementation of on-chip ANN for breast cancer diagnosis." Intelligent Decision Technologies 10, no. 4 (2016): 341–52. http://dx.doi.org/10.3233/idt-160261.
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Prakash, Somashekar Bangalore, and Pamela Abshire. "Tracking cancer cell proliferation on a CMOS capacitance sensor chip." Biosensors and Bioelectronics 23, no. 10 (2008): 1449–57. http://dx.doi.org/10.1016/j.bios.2007.12.015.
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Ziober, Barry L., Michael G. Mauk, Erica M. Falls, Zongyuan Chen, Amy F. Ziober, and Haim H. Bau. "Lab-on-a-chip for oral cancer screening and diagnosis." Head & Neck 30, no. 1 (2007): 111–21. http://dx.doi.org/10.1002/hed.20680.
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Zhang, Yu Shrike, Yi-Nan Zhang, and Weijia Zhang. "Cancer-on-a-chip systems at the frontier of nanomedicine." Drug Discovery Today 22, no. 9 (2017): 1392–99. http://dx.doi.org/10.1016/j.drudis.2017.03.011.
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Sun, Wujin, Zhimin Luo, Junmin Lee, et al. "Organ‐on‐a‐Chip for Cancer and Immune Organs Modeling." Advanced Healthcare Materials 8, no. 15 (2019): 1900754. http://dx.doi.org/10.1002/adhm.201900754.
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Fetah, Kirsten Lee, Benjamin J. DiPardo, Eve‐Mary Kongadzem, et al. "Cancer Modeling‐on‐a‐Chip with Future Artificial Intelligence Integration." Small 15, no. 50 (2019): 1901985. http://dx.doi.org/10.1002/smll.201901985.
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García-Hernández, Luis Abraham, Eduardo Martínez-Martínez, Denni Pazos-Solís, et al. "Optical Detection of Cancer Cells Using Lab-on-a-Chip." Biosensors 13, no. 4 (2023): 439. http://dx.doi.org/10.3390/bios13040439.
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The global need for accurate and efficient cancer cell detection in biomedicine and clinical diagnosis has driven extensive research and technological development in the field. Precision, high-throughput, non-invasive separation, detection, and classification of individual cells are critical requirements for successful technology. Lab-on-a-chip devices offer enormous potential for solving biological and medical problems and have become a priority research area for microanalysis and manipulating cells. This paper reviews recent developments in the detection of cancer cells using the microfluidics-based lab-on-a-chip method, focusing on describing and explaining techniques that use optical phenomena and a plethora of probes for sensing, amplification, and immobilization. The paper describes how optics are applied in each experimental method, highlighting their advantages and disadvantages. The discussion includes a summary of current challenges and prospects for cancer diagnosis.
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Marshall, Catherine Handy, Lukasz Gondek, Elizabeth Mauer, Calvin Y. Chao, Jun Luo, and Emmanuel S. Antonarakis. "Germline mutations and the presence of clonal hematopoiesis of indeterminate potential (CHIP) in 20,963 patients with BRCA-associated cancers." Journal of Clinical Oncology 41, no. 16_suppl (2023): 10522. http://dx.doi.org/10.1200/jco.2023.41.16_suppl.10522.
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10522 Background: The contribution of germline genetics on the emergence of CHIP in patients with solid tumor malignancies is not well understood. We hypothesized that those with germline (g) alterations in homologous recombination repair genes (gHRR) and BRCA-associated cancers (breast, ovarian, prostate, pancreas) would have different rates of CHIP than those without. Methods: We analyzed a large real-world Tempus multimodal database of paired germline and somatic DNA sequencing results. CHIP was calculated based on the presence of pathogenic or likely pathogenic alterations in any one of 16 CHIP-associated genes ( ASXL1, BCOR, BCORL1, CBL, CREBBP, CUX1, DNMT3A, GNB1, JAK2, PPM1D, PRPF8, SETDB1, SF3B1, SRSF2, TET2, U2AF1) with a variant allele frequency of at least 2%. Patients with g alterations in BRCA1, BRCA2, ATM, CHEK2, and PALB2 were compared to those without gHRR alterations (sporadic). Results: In breast cancer, patients with g BRCA1 (n = 104) mutations were younger (med 43 yrs) at diagnosis compared to sporadic cases (n = 6,546 med 56yrs) but had similar rates of CHIP (3% vs 5%). Those with gPALB2 (n = 42 med age 55) had the highest rate of CHIP (14%). gBRCA2 (n = 148; med age 52), gATM (n = 57 med age 52), and gCHEK2 (n = 57 med age 53) and similar rates of CHIP (3%, 4%, 7%). In ovarian cancer, patients with gBRCA1 (n = 137 med age 53) were younger at diagnosis than sporadic cases (n = 3,979 med age 63) with similar rates of CHIP (4% vs 3%). Those with gBRCA2 (n = 83 med age 61) were similar (4%) and gPALB2 (n = 11 med age 68) had the highest rate of 9%. CHIP was not detected among patients with g ATM (n = 23 med age 61) or g CHEK2 mutations (n = 9, med age 59). In prostate cancer, 4% of patients with sporadic cases had CHIP (n = 4,183 med age 66) compared to 4% in gBRCA2 (n = 109 med age 63) and 5% in gATM (n = 44 med age 66). gCHEK2 had 17% prevalence of CHIP (n = 12 med age 66) followed by gPALB2 (n = 12 med age 69). There were no CHIP mutations found among those with g BRCA1 (n = 16 med age 64). In pancreatic cancer, patients with g BRCA2 (n = 89 med age 64) and PALB2 (n = 20 med age 62) were younger at diagnosis, compared to sporadic cases (n = 5,176 med age 67) with lower rates of CHIP (1% gBRCA2, 0 PALB2, 5% sporadic). The highest proportion was in gBRCA1 patients (n = 20 med age 63) with 10%, gCHEK2 (n = 16 med age 68) with 6% and gATM (n = 60 med age 66) with 5%. Conclusions: Despite younger age at diagnosis, patients with g BRCA1 had similar or higher rates of CHIP within breast and ovarian cancer. Women with g PALB2 alterations and breast and ovarian cancer, as well as men with g CHEK2 mutations and prostate cancer, had higher rates of CHIP. These data suggest that gHRR mutations may influence the prevalence of CHIP among patients with BRCA-associated cancers and more research is needed.
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Pérez González, Ana, Clàudia Pellín Jou, Laura Palomo, et al. "Prevalence, Dynamics and Clinical Significance of Clonal Hematopoiesis of Indeterminate Potential (CHIP) in Newly Diagnosed Cancer Patients." Blood 142, Supplement 1 (2023): 5593. http://dx.doi.org/10.1182/blood-2023-189503.
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INTRODUCTION Prevalence of CHIP in cancer patients (pts) is estimated at about 25%, its presence being associated with inferior outcomes and with increased risk of development of therapy-related myeloid neoplasms (TRMN). Despite the increased body of knowledge on cancer and CHIP, processes driving the selection of clones and their latter malignant transformation have not been fully elucidated. We hypothesized that CHIP in cancer pts might not only lead to TRMN but also affect the prognosis of the primary neoplasm and its treatment-related toxicity. Our study aims to describe the prevalence and dynamics of CHIP in treatment-naïve pts with cancer and to analyze its impact on clinical outcomes. METHODS This study included 103 pts with a first cancer diagnosis at age ≥ 60 years and eligible for anticancer treatment without prior exposure to cytostatic agents. Peripheral blood (PB) samples were collected at diagnosis and 6 months after treatment. A customized NGS panel covering common CHIP genes ( DNMT3A, TET2, ASXL1, JAK2, PPM1D, TP53, SF3B1, GNB1, SRSF2, CHEK2, CBL, GNAS, and NRAS) was used to identify CHIP-positive (VAF≥ 1%) and CHIP-negative cases. Clonal dynamics were assessed through NGS at 6 months after treatment, categorized as ‘growing’ when their VAF increased by more than 25% compared to the baseline, ‘shrinking’ when VAF decreased by more than 25% compared to the baseline and ‘stable’ if it remains unaltered. RESULTS Baseline characteristics are shown in table 1.The prevalence of CHIP in our cohort was 35%, with an average of 1.5 somatic variants per patient and 54 identified variants, and a median VAF of 4.7% (IQR 2.5-11.0%). Notably, mutations in DNMT3A (33%), TET2 (28%), and PPM1D (13%) were the most prevailing gene aberrations, accounting for nearly 75% of all variants, while other common CHIP genes such as ASXL1 (9%) or JAK2 (0%) were less frequent. TP53 variants represented 9% of all mutations, whereas SF3B1, GNB1, SRSF2, and CBL each accounted for 2%. Breast cancer pts displayed a significantly higher prevalence of CHIP compared to other primary neoplasms (66% vs. 36%, p=0.01) whereas no patient with bladder neoplasm presented CHIP at diagnosis (p=0.04). These observations were not warranted only by differences in the age or smoking habit of these subgroup of neoplasms. The mutational spectrum of CHIP across different cancer categories was comparable. Among 20 paired samples sequenced (baseline and post-genotoxic exposure), 41% of all variants exhibited a growing pattern, 31% a shrinking pattern, and 28% remained static (Figure 1). Platinum-based therapy exposition promoted clonal expansion in DNMT3A mutations (p=0.03), while this effect was not observed in PPM1D or other genes, likely due to the low sample size. Age, tobacco use, and type of primary neoplasm did not appear to influence clonal fitness. There were no significant differences in the incidence of infectious complications or chemotherapy-induced hematologic toxicity between CHIP-positive and CHIP-negative cohorts. With the current follow-up time (16.8 months), the overall response (ORR) and complete response rates (CR) appeared comparable (ORR: 94% in CHIP-positive vs. 85% in CHIP-negative; CR: 79% vs. 70%, respectively). A patient with diffuse large B-cell lymphoma and CHIP ( ASXL1, PPM1D, and TP53 variants) developed a TRMN (MDS-MD) 7 months after completing R-CHOP treatment. CONCLUSION The prevalence of CHIP in our cancer pts cohort is 35%, with breast cancer cases displaying a CHIP occurrence around 62% not previously reported. Our study highlights an enrichment of mutations in PPM1D in treatment-naïve cancer pts, surpassing the frequency of ASXL1 in contrast to prior literature. Genotoxic therapy promotes clonal expansion in 41% of variants in our cohort; although factors influencing CHIP fitness remain poorly understood, DNMT3A showed heightened susceptibility to platinum therapy. Finally, and in contrast contrast with our initial hypothesis, we found no evidence of impaired outcomes in the CHIP population. These results emphasize the need for further longitudinal follow-up. Acknowledgements: This work was supported by two grants from the Instituto de Salud Carlos III (PI20/00881 and PI 20/00531)(Co-funded by European Regional Development Fund. ERDF, a way to build Europe). 2021 SGR 00560 (GRC) Generalitat de Catalunya; economical support from CERCA Programme.