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1
Caskey, Thomas. "Precision Medicine: Functional Advancements." Annual Review of Medicine 69, no. 1 (January 29, 2018): 1–18. http://dx.doi.org/10.1146/annurev-med-041316-090905.
2
Letai, Anthony. "Functional precision cancer medicine—moving beyond pure genomics." Nature Medicine 23, no. 9 (September 2017): 1028–35. http://dx.doi.org/10.1038/nm.4389.
3
Mattson, David L., and Mingyu Liang. "From GWAS to functional genomics-based precision medicine." Nature Reviews Nephrology 13, no. 4 (March 6, 2017): 195–96. http://dx.doi.org/10.1038/nrneph.2017.21.
4
Friedman, Adam A., Anthony Letai, David E. Fisher, and Keith T. Flaherty. "Precision medicine for cancer with next-generation functional diagnostics." Nature Reviews Cancer 15, no. 12 (November 5, 2015): 747–56. http://dx.doi.org/10.1038/nrc4015.
5
van den Berg, Albert, Christine L. Mummery, Robert Passier, and Andries D. van der Meer. "Personalised organs-on-chips: functional testing for precision medicine." Lab on a Chip 19, no. 2 (2019): 198–205. http://dx.doi.org/10.1039/c8lc00827b.
6
Rusert, Jessica M., Edwin F. Juarez, Sebastian Brabetz, James Jensen, Alexandra Garancher, Lianne Q. Chau, Silvia K. Tacheva-Grigorova, et al. "Functional Precision Medicine Identifies New Therapeutic Candidates for Medulloblastoma." Cancer Research 80, no. 23 (October 12, 2020): 5393–407. http://dx.doi.org/10.1158/0008-5472.can-20-1655.
7
Papaccio, Federica, Manuel Cabeza-Segura, Blanca Garcia-Micò, Noelia Tarazona, Desamparados Roda, Josefa Castillo, and Andres Cervantes. "Will Organoids Fill the Gap towards Functional Precision Medicine?" Journal of Personalized Medicine 12, no. 11 (November 21, 2022): 1939. http://dx.doi.org/10.3390/jpm12111939.
Анотація:
Precision medicine approaches for solid tumors are mainly based on genomics. Its employment in clinical trials has led to somewhat underwhelming results, except for single responses. Moreover, several factors can influence the response, such as gene and protein expression, the coexistence of different genomic alterations or post-transcriptional/translational modifications, the impact of tumor microenvironment, etc., therefore making it insufficient to employ a genomics-only approach to predict response. Recently, the implementation of patient-derived organoids has shed light on the possibility to use them to predict patient response to drug treatment. This could offer for the first time the possibility to move precision medicine to a functional environment.
8
Shneider, Olga V., Tatyana A. Kamilova, Alexander S. Golota, Andrey M. Sarana, and Sergey G. Sсherbak. "Biomarkers and Target Therapy for Lung Cancer." Physical and rehabilitation medicine, medical rehabilitation 3, no. 1 (April 28, 2021): 74–94. http://dx.doi.org/10.36425/rehab63268.
Анотація:
Precision (target) medicine is proposed as a new strategy to identify and develop new highly selective drugs against specific targets for the disease and more precise tailoring of medicines to the target populations of patients. Precision medicine can be an important approach to create more novel and safer therapeutics (tyrosine kinase inhibitors, tumour specific monoclonal antibodies) for patients with gene mutation, aberrations, or protein over-expression. Precision medicine requires an understanding mutational processes, and heterogeneity between cancer cells during tumor evolution. The present review briefly define various heterogeneities and potential associations with drug efficacy and resistance, emphasize the importance to develop functional biomarkers to monitor drug efficacy and resistance, and define opportunities and challenges of precision medicine for clinical practice.
9
Her, Nam-Gu, Gi Ju Lee, Seung Yoon Hyun, San Ha Park, Jae Woo Ahn, Ji Soo Kang, Hong Boon Toh, and Do-Hyun Nam. "Abstract 3410: AVATASCAN®, a pioneer of functional precision medicine in guiding clinical decision-making." Cancer Research 83, no. 7_Supplement (April 4, 2023): 3410. http://dx.doi.org/10.1158/1538-7445.am2023-3410.
Анотація:
Abstract Precision medicine refers to the tailoring of individual therapeutics based on each patient’s genetic, phenotypic, and clinical characteristics, therefore seeking the most effective treatment for the patient. With recent advances in genome sequencing technology, it was anticipated that identifying specific genetic alterations would contribute greatly to the realization of precision medicine. However, most cancer patients do not benefit from genomic precision medicine, as shown in recent Next Generation Sequencing (NGS)-driven clinical trials. Functional precision medicine directly uses patient tumor cells to test their ex vivo responses to diverse drugs to predict the most effective drugs. Functional precision medicine is emerging because it provides immediate translatable information to select drugs among clinically available therapeutics. AVATASCAN®, developed by Samsung Medical Center and AimedBio Inc., is a robust and accurate high throughput functional precision medicine platform with more than 1,500 historical sample data. AVATASCAN® has tested more than 1,500 cancer patient samples across 14 different tumor types, including glioblastoma, lung, colorectal, stomach and breast cancers. We achieved a tissue culture success rate and a drug screening success rate of more than 90% in most tumor types. A retrospective analysis of the clinical outcomes of patients given matched drugs demonstrated actual complete/partial response in 85% of AVATASCAN® screening responders. Recognizing its potential for clinical application, AVATASCAN® was selected as one of the datasets referenced by the pediatric tumor board at Seoul National University Hospital for clinical decision-making. Furthermore, AVATASCAN® is now available in Singapore and Thailand as an early-access, premium precision medicine service. Overall, we present compelling evidence that AVATASCAN® is a valuable platform for personalized cancer therapy. Therefore, we are moving forward to adopt and expand this platform in clinical applications. Citation Format: Nam-Gu Her, Gi Ju Lee, Seung Yoon Hyun, San Ha Park, Jae Woo Ahn, Ji Soo Kang, Hong Boon Toh, Do-Hyun Nam. AVATASCAN®, a pioneer of functional precision medicine in guiding clinical decision-making [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3410.
10
Kropivsek, K., P. Kachel, S. Goetze, R. Wegmann, Y. Severin, B. D. Hale, Y. Festl, et al. "P856: A SINGLE-CELL FUNCTIONAL PRECISION MEDICINE LANDSCAPE OF MULTIPLE MYELOMA." HemaSphere 6 (June 2022): 749–50. http://dx.doi.org/10.1097/01.hs9.0000846304.52658.85.
11
Malani, Disha, Ashwini Kumar, Oscar Brück, Mika Kontro, Bhagwan Yadav, Monica Hellesøy, Heikki Kuusanmäki, et al. "Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid Leukemia." Cancer Discovery 12, no. 2 (November 17, 2021): 388–401. http://dx.doi.org/10.1158/2159-8290.cd-21-0410.
12
Saeed, K., P. Ojamies, T. Pellinen, V. Rahkama, S. Eldfors, L. Paavolainen, R. Turkki, et al. "Precision systems medicine in urological Tumors – Molecular profiling and functional testing." Annals of Oncology 28 (October 2017): vii2. http://dx.doi.org/10.1093/annonc/mdx508.
13
Shomorony, Ilan. "Data-driven precision medicine through the analysis of biological functional modules." Cell Reports Medicine 3, no. 12 (December 2022): 100876. http://dx.doi.org/10.1016/j.xcrm.2022.100876.
14
Berlow, Noah, Arlet M. Acanda de la Rocha, Maggie Eidson Fader, Ebony Coats, Cima Saghira, Paula Espinal, Jeanette Galano, et al. "Biomarker development from functional precision medicine datasets via explainable machine learning." Journal of Clinical Oncology 42, no. 16_suppl (June 1, 2024): 10061. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.10061.
Анотація:
10061 Background: Genomics precision medicine, deployed via tumor panel sequencing, now assists in deploying targeted therapies to cancer patients. Numerous clinical trials have investigated the utility and benefit of genomics precision medicine in multiple cancer indications. Current large-scale studies report actionability rates from ~35% to ~60%, although clinical benefit rates have been shown to be closer to 10%. While this has positively impacted patients in need, the gap between actionability and benefit remains a clinical challenge attributed to multiple factors including the complex, multi-factorial relationship between molecular status and response to therapy. These differences go beyond simple disease states and may be reflective of multiple clinically relevant features including age, sex, and race/ethnicity. Methods: We implemented a functional precision medicine (FPM) program where patients with advanced pediatric cancers were prospectively profiled via high-throughput drug sensitivity testing (DST) of FDA-approved agents on patient-derived tumor cells as well as genomics testing. The objective was to investigate the clinical utility and benefit of FPM guidance in the treatment of pediatric cancer and elucidate the relationship between molecular status of patients’ diseases and treatment responses. We generated DST data (n = 21 patients) and genomic profiling data (n = 20 patients) on pediatric cancer patients in Miami, FL, as well as post-hoc whole exome and transcriptome sequencing data (n = 13 patients) and investigated three specific relationships. Results: We analyzed the relationship between racial/ethnic background and functional response to anti-cancer agents, determining potential differences in response to therapeutic classes. Next, we examined relationships between functional response and cancer type, identifying an unanticipated lack of clustering between disease indications in patients with advanced pediatric cancers. Finally, we applied an explainable machine learning (xML) framework to the functional genomic dataset to develop multi-omics biomarker hypotheses for the chemotherapy agent idarubicin, pinpointing a potential multi-cancer relationship between response to idarubicin and known disease mechanisms in acute myeloid leukemia (AML), the sole indication where idarubicin is approved. We further present additional proof-of-concept studies generating biomarker hypotheses via xML, demonstrating a framework for development of multi-omics biomarkers. Conclusions: We are now expanding our pan-pediatric cancer functional genomics dataset through an NIMHD-funded expansion cohort (NCT05857969, n = 65 patients) to further investigate multi-omics relationships between functional and molecular characteristics and understand the role of race/ethnicity in the complex relationship.
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Dixon, Ken, Jared James Barrott, and David Booker. "Abstract 4960: PIONEER initiative: Providing patient access to functional precision medicine." Cancer Research 84, no. 6_Supplement (March 22, 2024): 4960. http://dx.doi.org/10.1158/1538-7445.am2024-4960.
Анотація:
Abstract Eighty-five percent of patients receive medical care in cancer centers without National Cancer Institute (NCI) designation or significant ongoing research. The ability to access fresh tumor tissue for immediate functional testing is now available with appropriate logistical coordination. Cryopreservation of these tissues also allows testing to be done at a later date. We hypothesize that patient access to and ownership of each individual's tissues will facilitate personalized testing, thus bridging the chasm between research and the clinical cancer care for the individual patient. The PIONEER Initiative stands for Precision Insights On N-of-1 Ex vivo Effectiveness Research. In this Initiative we save cancerous tissue for any patient at any location, with subsequent cryopreservation and functional testing as needed and as able within an environment in which neither are standard. Our endpoint was to determine if this process serves to alter care for individual patients, and to what degree. The SpeciCare PIONEER Initiative: Precision Insights On N-of-1 Ex Vivo Effectiveness Research Based on Individual Tumor Ownership Trial (MYCT001) received human subjects IRB approval (Approval Number: 33943/1) from Quorum Review. The PIONEER Initiative is our lead clinical trial designed to provide the foundation for subsequent adaptive trials. Our mission with this trial was to demonstrate the utility of carrying out functional precision medicine in that cohort of patients who receive local cancer care at institutions that do not have significant research capabilities or are not NCI-designated cancer centers. Most cancer patients (~85%) are in this category. It is imperative to open the possibility of the best-in-class functional precision medicine testing to these patients. Core aspects of the PIONEER Initiative involve scaling up this process to approximately 200 patients, showing that our proof of concept in a more limited set of patients can ultimately scale to arbitrarily large numbers of patients. We see this capacity filling an important unmet need within the cancer community. The primary endpoint was the return of actionable information to positively impact care as assessed by the patient's clinical team and the patient. The underlying basic assumption of the PIONEER Initiative is that the ability to receive the best in cancer care should not come with restriction as to location, age, or medical condition. The PIONEER Initiative design facilitates inclusion of subjects across all these divides, thus providing beneficence to all participants. Among the 60 patients whose tumors had ex vivo drug testing performed, none of the data was included in the clinical decision making of the healthcare team. We conclude that physicians are not adequately prepared to use ex vivo drug testing data and the more likely acceptance of molecular characterization is primarily driven by genomic sequencing. Citation Format: Ken Dixon, Jared James Barrott, David Booker. PIONEER initiative: Providing patient access to functional precision medicine [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 4960.
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Hervella, Pablo, Ana Sampedro-Viana, Sabela Fernández-Rodicio, Manuel Rodríguez-Yáñez, Iria López-Dequidt, José M. Pumar, Antonio J. Mosqueira, et al. "Precision Medicine for Blood Glutamate Grabbing in Ischemic Stroke." International Journal of Molecular Sciences 25, no. 12 (June 14, 2024): 6554. http://dx.doi.org/10.3390/ijms25126554.
Анотація:
Glutamate grabbers, such as glutamate oxaloacetate transaminase (GOT), have been proposed to prevent excitotoxicity secondary to high glutamate levels in stroke patients. However, the efficacy of blood glutamate grabbing by GOT could be dependent on the extent and severity of the disruption of the blood–brain barrier (BBB). Our purpose was to analyze the relationship between GOT and glutamate concentration with the patient’s functional status differentially according to BBB serum markers (soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) and leukoaraiosis based on neuroimaging). This retrospective observational study includes 906 ischemic stroke patients. We studied the presence of leukoaraiosis and the serum levels of glutamate, GOT, and sTWEAK in blood samples. Functional outcome was assessed using the modified Rankin Scale (mRS) at 3 months. A significant negative correlation between GOT and glutamate levels at admission was shown in those patients with sTWEAK levels > 2900 pg/mL (Pearson’s correlation coefficient: −0.249; p < 0.0001). This correlation was also observed in patients with and without leukoaraiosis (Pearson’s correlation coefficients: −0.299; p < 0.001 vs. −0.116; p = 0.024). The logistic regression model confirmed the association of higher levels of GOT with lower odds of poor outcome at 3 months when sTWEAK levels were >2900 pg/mL (OR: 0.41; CI 95%: 0.28–0.68; p < 0.0001) or with leukoaraiosis (OR: 0.75; CI 95%: 0.69–0.82; p < 0.0001). GOT levels are associated with glutamate levels and functional outcomes at 3 months, but only in those patients with leukoaraiosis and elevated sTWEAK levels. Consequently, therapies targeting glutamate grabbing might be more effective in patients with BBB dysfunction.
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Lipsa, A., A. Hau, L. Ermini, R. Toth, A. Oudin, B. Klink, F. Hertel, M. Mittelbronn, A. Golebiewska, and S. Niclou. "P10.21.B Pharmacogenomics profiling of gliomas for precision medicine." Neuro-Oncology 24, Supplement_2 (September 1, 2022): ii53—ii54. http://dx.doi.org/10.1093/neuonc/noac174.186.
Анотація:
Abstract Background Molecular characterization based on genomic, transcriptomic and epigenetic profiling has led to a better delineation of various glioma subtypes and highlighted the individual paths of glioma evolution upon treatment and recurrence. However, due to cellular and molecular diversity of these tumors, the pharmacological treatment of gliomas, in particular of its most malignant subtype Glioblastoma (GBM), remains a major challenge. To address this challenge, we here apply a pharmacogenomics approach, modelling the disease in matched patient-derived preclinical models and profiling the differential drug response among individual patients and glioma subtypes Material and Methods We generated a cohort of 45 Patient-Derived Orthotopic Xenografts (PDOX) from a collection of over 400 glioma patients. We used a multi-parametric approach based on genetic, transcriptomic and longitudinal profiling of patients and their matched xenografts for a comprehensive subgrouping of our glioma cohort. Based on PDOX-derived 3D tumor organoids we carried out a targeted drug screen focused on epigenetic regulators. A high throughput drug screening using an unbiased large chemical library containing a unique collection of FDA approved compounds with high pharmacological diversity is currently ongoing. Results Our glioma cohort with matched PDOX and 3D tumor organoids represents diverse subgroups of glioma patients, including a unique collection of primary and relapsed tumors from the same patient. Our preliminary drug screen analysis on 3D organoids highlights selective susceptibility to certain epigenetic inhibitors in primary disease but not in the same patient’s relapse. Results of matching genomics and functional data will be presented. Conclusion An integrated personalized approach to profile gliomas at multiple genomic and functional levels allows for pharmacogenomic subgrouping of patients for personalized treatment strategies. This analysis will allow to link genotypes to functional phenotypes and hopefully identify therapeutic options for selected glioma sub-populations.
18
Ahmed, Sagheer. "Welcome to Precision Medicine Communications!" Precision Medicine Communications 1, no. 1 (December 30, 2021): 01. http://dx.doi.org/10.55627/pmc.001.01.0057.
Анотація:
Welcome to the inaugural issue of Precision Medicine Communications -a biannual, open access, and peer-reviewed journal aiming to publish high-quality research articles in the field of precision medicine. Precision Medicine Communications accept studies that conduct basic and translational research to investigate the role of genetics and gene-environment interactions that influence human health disorders. The Journal publishes research in all areas of precision medicine. Precision Medicine Communications especially invites studies that are innovative in genomic medicine and add scientific insights that can be translated into improved patient care. It especially considers studies investigating the effects of genetic variability on drug toxicity and efficacy, identification and functional characterization of polymorphisms relevant to the pharmacological action and adverse effects of a drug, integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics, clinical implementation of pharmacogenomics, identification of novel genomic targets for drug development, the economics of genome-guided interventions, clinical implementation of pharmacogenomics, pharmacogenomics in developing countries, companion diagnostics and drug development. The journal provides an integrated forum for all players involved - academic and clinical researchers, pharmaceutical companies, regulatory authorities, healthcare management organizations, patient organizations, and others in the healthcare community. Precision Medicine Communications assists these parties to shape the future of medicine by providing a platform for expert commentary and analysis. In the last two decades, rapid advances in technology have enabled researchers to investigate arcane biological phenomena and ask deeper questions at the cellular, molecular and atomic levels. Several cellular processes involved in health and disease are being unraveled at a rapid pace, high resolution, and with unprecedented details. Authors carrying out investigations leveraging these technologies such as next genome sequencing, CRISPR-Cas9, digital medicine, 3-D printing, bioinformatics, and stem cell technologies, are encouraged to submit their findings to Precision Medicine Communications. An important objective of this journal is to provide a platform to the scientific fraternity, especially to the regional and national academics, where they could get their studies published after a rapid, transparent, and high-quality peer review. All the articles published in Precision Medicine Communications will be freely available to readers immediately after their publication. The open-access policy of our journal is likely to increase the readership of articles and will enhance their visibility and citation potential. Therefore, I invite you to submit your work to Precision Medicine Communications.
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Lopes-Júnior, Luís Carlos. "Personalized Nursing Care in Precision-Medicine Era." SAGE Open Nursing 7 (January 2021): 237796082110647. http://dx.doi.org/10.1177/23779608211064713.
Анотація:
The extensive investment and development of research in molecular biology in the last decades, mainly after the completion of the Human Genome Project, has raised many expectations regarding its impact on Precision-Medicine Era. To meet the new demands for care, it is necessary that the omics sciences be integrated into nursing practice, especially in nursing care. Based on knowledge of structural genomics, it has been improved techniques that enabled the advancement of research related to functional genomics, which together comprising the “omics” sciences including the transcriptomics, proteomics, the epigenomics and metabolomics. The current challenge is to transform this expanded set of information into clinical benefits for patients, through more accurate diagnoses, treatments, and personalized care to the particularities of individuals and communities. For Nursing, the main challenge is the incorporation of the omics sciences in training and professional practice, so that nurses can safely, scientifically, and autonomously empower themselves to provide personalized care to individuals and families based on Precision-Medicine Era. In this paper, a debate on the impacts and challenges for Nursing to incorporate the Precision-Medicine into clinical practice is described.
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JOHANSSON, BENTE B., AISHWARYA PAVITHRAM, HAICHEN ZHANG, KRISTIN A. MALONEY, MONIKA RINGDAL, ALBA KACI, JORN V. SAGEN, et al. "1638-P: Functional Characterization of HNF1B Variants Can Enhance Diabetes Precision Medicine." Diabetes 69, Supplement 1 (June 2020): 1638—P. http://dx.doi.org/10.2337/db20-1638-p.
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McConnon, Aili. "A review of functional nanotechnology: Its use and potential in precision medicine." Scilight 2020, no. 52 (December 25, 2020): 521107. http://dx.doi.org/10.1063/10.0003198.
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Fieuws, Charlotte, Jan Willem Bek, Bram Parton, Elyne De Neef, Olivier De Wever, Milena Hoorne, Marta F. Estrada, et al. "Zebrafish Avatars: Toward Functional Precision Medicine in Low-Grade Serous Ovarian Cancer." Cancers 16, no. 10 (May 9, 2024): 1812. http://dx.doi.org/10.3390/cancers16101812.
Анотація:
Ovarian cancer (OC) is an umbrella term for cancerous malignancies affecting the ovaries, yet treatment options for all subtypes are predominantly derived from high-grade serous ovarian cancer, the largest subgroup. The concept of "functional precision medicine" involves gaining personalized insights on therapy choice, based on direct exposure of patient tissues to drugs. This especially holds promise for rare subtypes like low-grade serous ovarian cancer (LGSOC). This study aims to establish an in vivo model for LGSOC using zebrafish embryos, comparing treatment responses previously observed in mouse PDX models, cell lines and 3D tumor models. To address this goal, a well-characterized patient-derived LGSOC cell line with the KRAS mutation c.35 G > T (p.(Gly12Val)) was used. Fluorescently labeled tumor cells were injected into the perivitelline space of 2 days’ post-fertilization zebrafish embryos. At 1 day post-injection, xenografts were assessed for tumor size, followed by random allocation into treatment groups with trametinib, luminespib and trametinib + luminespib. Subsequently, xenografts were euthanized and analyzed for apoptosis and proliferation by confocal microscopy. Tumor cells formed compact tumor masses (n = 84) in vivo, with clear Ki67 staining, indicating proliferation. Zebrafish xenografts exhibited sensitivity to trametinib and luminespib, individually or combined, within a two-week period, establishing them as a rapid and complementary tool to existing in vitro and in vivo models for evaluating targeted therapies in LGSOC.
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Rashid, Masturah Mohd Abdul, Jhin Jieh Lim, Lisa Chow, and Edward Kai-Hua Chow. "Abstract A128: Analytical and clinical evaluation of a functional combinatorial precision medicine platform." Molecular Cancer Therapeutics 22, no. 12_Supplement (December 1, 2023): A128. http://dx.doi.org/10.1158/1535-7163.targ-23-a128.
Анотація:
Abstract Non-Hodgkin’s lymphoma (NHL) is a heterogenous malignancy with many different subtypes. Although patients initially respond to treatments, approximately 40% of this cohort will subsequently relapse. After exhausting several lines of treatment, determining the next option is largely empirical. There is a need to develop approaches that are able to identify personalized therapies. There are existing ex vivo approaches that use single-drug sensitivity assays but lack the ability to truly evaluate drug combinations. In this clinical study, we aim to evaluate the potential of an ex vivo combinatorial drug sensitivity platform, Optim.AI™, to identify therapeutic options for relapsed/refractory (RR) NHL. Repeatability, between-run and intermediate precision parameters were used to evaluate the analytical precision of the approach. Optim.AI™ was carried out using K422 and SU-DHL-4 cell lines, either on same or different days by two operators. The cell viability was quantified post-drug treatment and used to calculate the standard deviation (SD) and coefficient of variation (CV) between runs. 98 patients with RR-NHL of both B-NHL and NK/T-NHL origin were analyzed. Single cell suspensions from tumor biopsies or blood aspirates were treated with a panel of drugs with known efficacy. Post-drug treatment cell viability was used as phenotypic input for Optim.AI™ analysis, mapping experimental data points to a second-order quadratic function to predict all other cell killing efficacies. Optim.AI™ results were shared with treating physicians and Optim.AI™-guided therapy was offered in the absence of standard options. For the analytical precision validation, the percentage of replicates with CV ≤ 30% followed the same trend for both cell lines, where 92.2%, 96.1% and 92.6% for repeatability, between-run and intermediate precision parameters respectively were observed for K422 cell line. Out of the 98 successfully generated reports from the processed samples, 35 patient results were evaluable upon analysis where 19 patients were given Optim.AI™ top ranked therapies while the rest were given non-top ranked options, as per physicians’ discretion. Approximately 67% of those with guided therapies achieved clinical benefit, with 7 patients observing complete response while 6 patients attained partial response. For the 35 patients analyzed, the sensitivity of the study was found to be 85% (95% CI, 64-94.8%) while the specificity was at 86.7% (95% CI, 62.1-96.3%). This prospective study demonstrated the precision utility of Optim.AI™, evident from the high percentage of replicates falling within the defined CV. More importantly, it highlights the clinical utility of Optim.AI™ in identifying patient-specific therapies that improved clinical outcomes. The high sensitivity and specificity scores provide confidence in the reliability of the approach to accurately predict efficacious options. The results of this study show the potential of functional precision medicine in identifying patient-specific therapy, while improving precision and personalized cancer treatment. Citation Format: Masturah Mohd Abdul Rashid, Jhin Jieh Lim, Lisa Chow, Edward Kai-Hua Chow. Analytical and clinical evaluation of a functional combinatorial precision medicine platform [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A128.
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Salgotra, Romesh K., and C. Neal Stewart. "Functional Markers for Precision Plant Breeding." International Journal of Molecular Sciences 21, no. 13 (July 6, 2020): 4792. http://dx.doi.org/10.3390/ijms21134792.
Анотація:
Advances in molecular biology including genomics, high-throughput sequencing, and genome editing enable increasingly faster and more precise cultivar development. Identifying genes and functional markers (FMs) that are highly associated with plant phenotypic variation is a grand challenge. Functional genomics approaches such as transcriptomics, targeting induced local lesions in genomes (TILLING), homologous recombinant (HR), association mapping, and allele mining are all strategies to identify FMs for breeding goals, such as agronomic traits and biotic and abiotic stress resistance. The advantage of FMs over other markers used in plant breeding is the close genomic association of an FM with a phenotype. Thereby, FMs may facilitate the direct selection of genes associated with phenotypic traits, which serves to increase selection efficiencies to develop varieties. Herein, we review the latest methods in FM development and how FMs are being used in precision breeding for agronomic and quality traits as well as in breeding for biotic and abiotic stress resistance using marker assisted selection (MAS) methods. In summary, this article describes the use of FMs in breeding for development of elite crop cultivars to enhance global food security goals.
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Agusti, Alvar, Elisabeth Bel, Mike Thomas, Claus Vogelmeier, Guy Brusselle, Stephen Holgate, Marc Humbert, et al. "Treatable traits: toward precision medicine of chronic airway diseases." European Respiratory Journal 47, no. 2 (January 31, 2016): 410–19. http://dx.doi.org/10.1183/13993003.01359-2015.
Анотація:
Asthma and chronic obstructive pulmonary disease (COPD) are two prevalent chronic airway diseases that have a high personal and social impact. They likely represent a continuum of different diseases that may share biological mechanisms (i.e. endotypes), and present similar clinical, functional, imaging and/or biological features that can be observed (i.e. phenotypes) which require individualised treatment. Precision medicine is defined as “treatments targeted to the needs of individual patients on the basis of genetic, biomarker, phenotypic, or psychosocial characteristics that distinguish a given patient from other patients with similar clinical presentations”. In this Perspective, we propose a precision medicine strategy for chronic airway diseases in general, and asthma and COPD in particular.
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Wildgruber, Moritz, and Michel Eisenblätter. "Molecular Imaging of Immunity and Inflammation and Its Impact on Precision Medicine." Biomedicines 9, no. 1 (January 11, 2021): 62. http://dx.doi.org/10.3390/biomedicines9010062.
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Wildgruber, Moritz, and Michel Eisenblätter. "Molecular Imaging of Immunity and Inflammation and Its Impact on Precision Medicine." Biomedicines 9, no. 1 (January 11, 2021): 62. http://dx.doi.org/10.3390/biomedicines9010062.
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Kokkinos, John, Anya Jensen, George Sharbeen, Joshua A. McCarroll, David Goldstein, Koroush S. Haghighi, and Phoebe A. Phillips. "Does the Microenvironment Hold the Hidden Key for Functional Precision Medicine in Pancreatic Cancer?" Cancers 13, no. 10 (May 17, 2021): 2427. http://dx.doi.org/10.3390/cancers13102427.
Анотація:
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and no significant improvement in patient survival has been seen in the past three decades. Treatment options are limited and selection of chemotherapy in the clinic is usually based on the performance status of a patient rather than the biology of their disease. In recent years, research has attempted to unlock a personalised treatment strategy by identifying actionable molecular targets in tumour cells or using preclinical models to predict the effectiveness of chemotherapy. However, these approaches rely on the biology of PDAC tumour cells only and ignore the importance of the microenvironment and fibrotic stroma. In this review, we highlight the importance of the microenvironment in driving the chemoresistant nature of PDAC and the need for preclinical models to mimic the complex multi-cellular microenvironment of PDAC in the precision medicine pipeline. We discuss the potential for ex vivo whole-tissue culture models to inform precision medicine and their role in developing novel therapeutic strategies that hit both tumour and stromal compartments in PDAC. Thus, we highlight the critical role of the tumour microenvironment that needs to be addressed before a precision medicine program for PDAC can be implemented.
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Siraj, Sami. "Precision Medicine Approaches for Psychosis Treatment." Precision Medicine Communications 3, no. 1 (July 17, 2023): 01–02. http://dx.doi.org/10.55627/pmc.003.01.0313.
Анотація:
Precision The precision medicine approach takes into account individual variability in genes, environment, and lifestyle and holds great promise in revolutionizing the treatment of various disorders, including psychosis. Psychosis is a mental health condition characterized by a loss of contact with reality, and it can occur in disorders such as schizophrenia and bipolar disorder. By integrating psychiatry and neurology, precision medicine aims to provide personalized and targeted interventions for individuals with psychosis. Several approaches are used for improved treatment outcomes in psychosis patients. Genetic biomarkers: Advances in genomic research have identified genetic variations associated with an increased risk of developing psychosis. Understanding these genetic biomarkers can help identify individuals at risk early and tailor treatment strategies based on their genetic profile. Genetic testing can assist in determining the optimal medication selection, dosage, and potential side effects. Pharmacogenomics: Psychiatric medications, including antipsychotics, can have varying efficacy and side effect profiles among different individuals. Pharmacogenomics studies the influence of genetic variations on drug response, metabolism, and side effects. By analyzing an individual's genetic makeup, clinicians can predict their response to specific medications and adjust treatment plans accordingly, improving treatment outcomes and reducing adverse effects. Neuroimaging and biomarkers: Neuroimaging techniques, such as magnetic resonance imaging (MRI) and functional MRI (fMRI), can provide insights into brain structure, function, and connectivity. These imaging methods, combined with other biomarkers like blood-based markers or cerebrospinal fluid analysis, can help identify subtypes within the broad category of psychosis. These subtypes can inform treatment selection and predict treatment response, leading to more targeted interventions. Digital phenotyping and wearables: The use of digital tools, such as smartphones and wearable devices, allows continuous monitoring of various parameters like sleep patterns, physical activity, social interactions, and cognitive function. These data, combined with machine learning algorithms, can help in detecting early signs of psychosis relapse, predicting treatment response, and personalizing interventions based on individual patterns and needs. Integrated care models: Precision medicine in psychosis involves collaborative approaches between psychiatrists, neurologists, geneticists, and other healthcare providers. By integrating diverse expertise, clinicians can develop comprehensive treatment plans that address both the psychiatric and neurological aspects of the disorder. This interdisciplinary approach enables personalized interventions and a more holistic understanding of the underlying mechanisms of psychosis. Patient-centered care: Precision medicine emphasizes a patient-centered approach, recognizing the unique experiences and needs of individuals with psychosis. It encourages shared decision-making between healthcare providers and patients, considering their preferences, values, and goals in treatment planning. This approach improves treatment adherence, engagement, and overall satisfaction with care. While precision medicine in psychosis holds immense potential, further research and integration of these approaches into routine clinical practice are needed. Large-scale studies, data sharing, and collaborative efforts are crucial for advancing the field and harnessing the benefits of precision medicine for individuals with psychosis.
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Zou, Jinfeng, and Edwin Wang. "Cancer Biomarker Discovery for Precision Medicine: New Progress." Current Medicinal Chemistry 26, no. 42 (January 8, 2020): 7655–71. http://dx.doi.org/10.2174/0929867325666180718164712.
Анотація:
Background: Precision medicine puts forward customized healthcare for cancer patients. An important way to accomplish this task is to stratify patients into those who may respond to a treatment and those who may not. For this purpose, diagnostic and prognostic biomarkers have been pursued. Objective: This review focuses on novel approaches and concepts of exploring biomarker discovery under the circumstances that technologies are developed, and data are accumulated for precision medicine. Results: The traditional mechanism-driven functional biomarkers have the advantage of actionable insights, while data-driven computational biomarkers can fulfill more needs, especially with tremendous data on the molecules of different layers (e.g. genetic mutation, mRNA, protein etc.) which are accumulated based on a plenty of technologies. Besides, the technology-driven liquid biopsy biomarker is very promising to improve patients’ survival. The developments of biomarker discovery on these aspects are promoting the understanding of cancer, helping the stratification of patients and improving patients’ survival. Conclusion: Current developments on mechanisms-, data- and technology-driven biomarker discovery are achieving the aim of precision medicine and promoting the clinical application of biomarkers. Meanwhile, the complexity of cancer requires more effective biomarkers, which could be accomplished by a comprehensive integration of multiple types of biomarkers together with a deep understanding of cancer.
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Achenbach, Stephan, Friedrich Fuchs, Alexandra Goncalves, Claudia Kaiser-Albers, Ziad A. Ali, Frank M. Bengel, Stefanie Dimmeler, et al. "Non-invasive imaging as the cornerstone of cardiovascular precision medicine." European Heart Journal - Cardiovascular Imaging 23, no. 4 (January 20, 2022): 465–75. http://dx.doi.org/10.1093/ehjci/jeab287.
Анотація:
Abstract Aims To provide an overview of the role of cardiovascular (CV) imaging in facilitating and advancing the field of precision medicine in CV disease. Methods and results Non-invasive CV imaging is essential to accurately and efficiently phenotype patients with heart disease, including coronary artery disease (CAD) and heart failure (HF). Various modalities, such as echocardiography, nuclear cardiology, cardiac computed tomography (CT), cardiovascular magnetic resonance (CMR), and invasive coronary angiography, and in some cases a combination, can be required to provide sufficient information for diagnosis and management. Taking CAD as an example, imaging is essential for the detection and functional assessment of coronary stenoses, as well as for the quantification of cardiac function and ischaemic myocardial damage. Furthermore, imaging may detect and quantify coronary atherosclerosis, potentially identify plaques at increased risk of rupture, and guide coronary interventions. In patients with HF, imaging helps identify specific aetiologies, quantify damage, and assess its impact on cardiac function. Imaging plays a central role in individualizing diagnosis and management and to determine the optimal treatment for each patient to increase the likelihood of response and improve patient outcomes. Conclusions Advances in all imaging techniques continue to improve accuracy, sensitivity, and standardization of functional and prognostic assessments, and identify established and novel therapeutic targets. Combining imaging with artificial intelligence, machine learning and computer algorithms, as well as with genomic, transcriptomic, proteomic, and metabolomic approaches, will become state of the art in the future to understand pathologies of CAD and HF, and in the development of new, targeted therapies.
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Bhatt, Shruti, Vineeth Kumar Murali, Holly Zhu, Sophia Adamia, Amanda L. Christie, David M. Weinstock, Jackie S. Garcia, and Anthony Letai. "A Functional Approach to Precision Medicine Identifies Targeted Therapies for Acute Myeloid Leukemia." Blood 130, Suppl_1 (December 7, 2017): 853. http://dx.doi.org/10.1182/blood.v130.suppl_1.853.853.
Анотація:
Abstract Identification of genetic heterogeneity in acute myeloid leukemia (AML) has provided a unique opportunity for the greater individualization of therapy. However the implementation of new therapies has lagged far behind the ability to initially recognize operationally important genetic lesions. Until we have further bridged this gap between the identification of genetic lesions and the resultant knowledge of effective therapies, alternative strategies for rapidly identifying candidate therapies can become an important tool for precision medicine. Since most agents, regardless of whether "cytotoxic" or "targeted" ultimately function by activating the mitochondrial apoptotic pathway, we hypothesized that a tool that measures mitochondrial sensitivity may serve as a broadly predictable biomarker. We developed a dynamic BH3 profiling (DBP) technique that measures early death signaling within 8-16 hours after exposure to drugs. Increased cell death signaling is reflected by increased mitochondrial sensitivity (i.e. increased priming) to standardized BH3 peptides mimicking pro-apoptotic proteins. To develop a personalized therapy for AML using DBP, we utilized 20 independent patient derived xenograft (PDX) models, established from de novo, primary refractory or relapsed (R/R) patients (available at http://www.PRoXe.org). Human myeloblasts from spleen and bone marrow of xenotransplanted NSG mice were exposed to 30 targeted and 3 standard of care drugs to determine mitochondrial responses. Unsupervised hierarchical clustering of ex-vivo DBP measurements across AML PDXs revealed several distinct clusters. Majority of targeted agents with an ability to induce priming in selective PDXs were enriched within a cluster, including kinase inhibitors, epigenetic modifiers, SMAC mimetic and chemotherapy drugs. In contrast, a discrete subcluster of drugs showed sensitivity across majority of PDXs, including BH3 mimetics, CDK9 inhibitors and HDAC inhibitors. Drugs with identical mechanism of action showed similar priming patterns across PDXs. Of note, 3 non-myeloid PDXs clustered distinctly from AML, an indication of differential priming responses owing to their cells of origin. AML PDXs developed from treatment naïve patients clustered adjacently and showed greater priming responses to a large number of drugs as opposed to PDXs from R/R patients that formed a discrete cluster. These data reveal that mitochondrial priming can stratify AML PDXs according to its predicted sensitivity to targeted agents. Next, we validated ability of DBP to predict in-vivo responses of single agent birinapant (SMAC mimetic), JQ-1 (BRD-4 inhibitor), quizartinib (FLT-3 inhibitor), and venetoclax (BCL-2 inhibitor) across 6 AML PDX models, prioritized based on their greatest range of priming responses. We found that birinapant was most efficacious nonetheless as expected from ex-vivo DBP studies, responses varied between different PDX models. Myeloblasts of those PDXs that showed the greatest drug-induced changes in apoptotic priming were indeed the PDXs with the highest in-vivo responses. When we compared the ability of DBP to identify sensitive PDXs with additional precision medicine tools such as genomics, we found that DBP was able to accurately predict quizartinib activity in PDXs expressing WT FLT-3, which would have been predicted to be unresponsive based on genomic analysis. Collectively, priming responses obtained from ex-vivo DBP was able to rank different PDX models according to their sensitivities to targeted agents (AUC of ROC curve 0.8731, p<0.005). To investigate if DBP can predict combination therapies in relapsed settings, we first developed resistant models of single agents and then repeated DBP. Myeloblasts from relapsing clone showed reduced overall mitochondrial priming and lacked acquisition of a new chemical dependency compared to initial clone. This suggests that targeting of pre-existing dependencies might be more crucial than therapy induced dependency for AML. In summary, our findings highlight that mitochondria-based measurements could identifying individualized therapy for a heterogeneous population and may serve as a as a powerful biomarker to identify the best responders to patient therapies. Disclosures Letai: AbbVie, AstraZeneca, Novartis: Consultancy, Research Funding.
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Lee, Sohyon, Tobias Weiss, Marcel Bühler, Rebekka Wegmann, Julien Mena, Michel Bihl, Sandra Goetze, et al. "Abstract 5325: Image-based functional precision medicine for repurposing neuroactive drugs in glioblastoma." Cancer Research 82, no. 12_Supplement (June 15, 2022): 5325. http://dx.doi.org/10.1158/1538-7445.am2022-5325.
Анотація:
Abstract Treatment of glioblastoma multiforme (GBM), the most aggressive form of primary brain cancer, has essentially not advanced over the past few decades. Numerous challenges hinder the successful development of new therapies, including drug delivery across the blood-brain barrier (BBB), the complexity of the tumor microenvironment (TME), and the lack of clinically predictive cancer models. Here, we present the results of an image-based ex vivo drug-testing platform that addresses these therapeutic roadblocks. To demonstrate the clinical utility of our platform, in a retrospective cohort of 14 GBM patients, we show that ex vivo sensitivity to Temozolomide (TMZ, 1st-line GBM chemotherapy), is associated with longer progression free survival (PFS) and overall survival (OS). Next, by screening 150 clinically approved drugs across 27 GBM surgical patient samples, we identify a set of BBB-permeable neuroactive drugs with anti-glioma activity. These neurological drugs display remarkably consistent on-target killing of cancer cells with minimal toxicity to non-malignant TME cells across both primary and recurrent GBM samples. Single-cell transcriptional profiling of GBM patient samples and functional genetics reveals novel glioma-dependencies on neurological drug-target expression. Furthermore, a drug-target network enrichment analysis uncovers an AP1/BTG/TP53 gene signature associated with the anti-glioma activity of neurological drugs. In silico screening of over 1 million compounds for this common gene signature identified additional drug hits that could be validated in patient samples with 90% accuracy. Multiplexed transcriptomics revealed AP-1 transcription factor family activation to be the common underlying feature of neurological drugs with anti-glioma activity. Among the most promising candidate drugs, we identify the atypical antidepressant Vortioxetine as the strongest inducer of this gene signature, and confirm its efficacy in vivo across multiple mouse models. Vortioxetine in combination with Temozolomide or Lomustine further increased median survival in vivo compared to single agents alone. This study thus provides a clinically predictive and personalized drug-testing platform that identifies new treatment opportunities for GBM, warranting further investigation. Citation Format: Sohyon Lee, Tobias Weiss, Marcel Bühler, Rebekka Wegmann, Julien Mena, Michel Bihl, Sandra Goetze, Audrey van Drogen, Elisabeth J. Rushing, Bernd Wollscheid, Michael Weller, Berend Snijder. Image-based functional precision medicine for repurposing neuroactive drugs in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5325.
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Ledford, Aubrey, Ashley Smith, Tessa DesRochers, and Cecile Rose Vibat. "CLRM-19 USING FUNCTIONAL PRECISION MEDICINE TO GUIDE CLINICAL TRIAL ENROLLMENT IN GBM." Neuro-Oncology Advances 4, Supplement_1 (August 1, 2022): i10. http://dx.doi.org/10.1093/noajnl/vdac078.039.
Анотація:
Abstract Interventional clinical trials in glioblastoma (GBM) have been consistently disappointing, attributable to various factors such as ineffective therapies, inadequate trial designs including lack of control arms, or enrollment criteria that do not represent real-world practice. Novel paradigms for clinical trial design(s) in GBM are desperately needed to produce clinically useful patient outcomes. KIYATEC has developed a patient- and tumor-specific technology platform to evaluate cellular response(s) to therapeutics using 3D cell culture methods that provide functional, patient-specific response predictions. Employing KIYATEC’s technology to screen compounds against both primary patient-, and PDX-derived specimens, enables clinical prioritization of early-stage assets most likely to have therapeutic response in vivo. In addition, KIYATEC’s 3D Predict™ Glioma test has shown clinical correlation of test-predicted response(s) and clinical outcomes in GBM patients. Incorporating KIYATEC’s 3D ex vivo technology into GBM therapeutic development is positioned to accelerate more successful trial results by 1) identifying early-stage compounds likely to possess clinical effects in vivo, and 2) prospectively identifying patients expected to have a clinical response to therapeutics in development. 3D Predict Glioma provides patient-specific responses within 7-10 days of tissue acquisition, providing an avenue for test integration into adaptive clinical trials, whereby functional characterization could provide gating information relating to trial execution. Specifically, functional response prediction may play a pivotal role in identifying newly diagnosed patients who might derive greater benefit from clinical trials compared to standard of care and by optimizing effective therapeutic selection in the recurrent setting. Therefore, a priori knowledge of an early-stage assets’ potential, combined with therapeutic sensitivity of individual patient tissue, may facilitate a new era for adaptive clinical trial design by assimilating KIYATEC’s analytically and clinically validated test into various steps of clinical trial execution such as randomization, stratification, therapy-switching, or compound addition/discontinuation.
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Letai, Anthony. "Functional Precision Medicine: Putting Drugs on Patient Cancer Cells and Seeing What Happens." Cancer Discovery 12, no. 2 (February 2022): 290–92. http://dx.doi.org/10.1158/2159-8290.cd-21-1498.
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Mina, M., F. Raynaud, D. Tavernari, E. Battistello, S. Sungalee, S. Saghafinia, T. Laessle, et al. "Interrogating functional dependencies between genomic alterations can facilitate precision medicine approaches in cancer." Annals of Oncology 28 (October 2017): vii2. http://dx.doi.org/10.1093/annonc/mdx508.001.
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Wright, Chadwick L., Katherine Binzel, Jun Zhang, and Michael V. Knopp. "Advanced Functional Tumor Imaging and Precision Nuclear Medicine Enabled by Digital PET Technologies." Contrast Media & Molecular Imaging 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/5260305.
Анотація:
The purpose of this article is to provide a brief overview of the background, basic principles, technological evolution, clinical capabilities, and future directions for functional tumor imaging as PET evolves from the conventional photomultiplier tube-based platform into a fully digital detector acquisition platform. The recent introduction of solid-state digital photon counting PET detector is the latest evolution of clinical PET which enables faster time-of-flight timing resolution that leads to more precise localization of the annihilation events and further contributes to reduction in partial volume and thus makes high definition and ultrahigh definition PET imaging feasible with current standard acquisition procedures. The technological advances of digital PET can be further leveraged by optimizing many of the acquisition and reconstruction methodologies to achieve faster image acquisition to improve cancer patient throughput, lower patient dose in accordance with ALARA, and improved quantitative accuracy to enable biomarker capability. Digital PET technology will advance molecular imaging capabilities beyond oncology and enable Precision Nuclear Medicine.
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Apfel, Christian, David Chen, Juliana Baratta, and Dhruva K. Mishra. "A functional precision medicine 3D microtumor platform to identify and personalize novel indications." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e15588-e15588. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e15588.
Анотація:
e15588 Background: We have previously validated our 3D microtumor platform that captures the tumor heterogeneity of a patient's primary tumor biopsy using a patient-derived xenograft model (Nikolov et al. ASCO 2019, e17076). Here we describe its utility to identify FDA approved therapies that may be effective for tumors previously not considered. Methods: A fresh tumor sample of a liver metastasis of a 45-year-old colorectal cancer patient was shipped overnight and processed to create hundreds of live 3D microtumors. These microtumors were treated with a panel of 12 commonly used drugs including chemotherapies and targeted therapies. Treatment effects were quantified and validated on fresh and cryopreserved/thawed samples using our metabolic and proprietary multiplexed fluorescent staining technologies to quantify the ratio of live and dead cells in those microtumors. Results: None of the conventional treatments in the 12-panel drug test suggested any efficacy as determined by the log of efficacy concentrations (in µmol/l): Oxaliplatin 2.59, 5-FU 3.00 (upper cut-off value), paclitaxel 1.72, topotecan 3.00, irinotecan (SN-38) 2.33, gemcitabine 2.44, and bevacizumab 3.00. The microtumors also appeared resistant to several targeted therapies that are not commonly given, ranging from 1.85 to 2.44. However, abemaciclib had an efficacy of 0.49, which was confirmed on thawed samples with all drug efficacy concentrations again suggesting resistance, except for abemaciclib at 0.67. Conclusions: Our 3D microtumor platform may be a useful tool a) to identify rescue treatment options for metastatic patients that have multi-resistant tumors and b) to identify novel indications to personalize FDA-approved cytotoxic or targeted therapies as a companion diagnostic.
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Her, Nam-Gu, Adelheid Woehrer, Gi Ju Lee, Seung Yoon Hyun, Jae Woo Ahn, Ji Soo Kang, Ryu I. Hwang, et al. "Abstract 2553: Functional precision medicine as a valid tool in glioblastoma clinical practice." Cancer Research 84, no. 6_Supplement (March 22, 2024): 2553. http://dx.doi.org/10.1158/1538-7445.am2024-2553.
Анотація:
Abstract Background: Glioblastoma remains a formidable therapeutic challenge, necessitating innovative strategies such as functional precision medicine (FPM). FPM offers personalized treatment by utilizing high-throughput screening of 10-100 compounds on patient-derived tumor cells (PDCs), assessing both efficacy and relative sensitivity, with results reported to the molecular tumor board within 2 weeks. The focus of this study is the cross-laboratory validity of this approach in glioblastoma, an essential step towards confirming FPM's consistency and potential as a game-changing tool in personalized cancer treatment. Methods: Patient-derived tumor cells from glioblastoma cases were cultured for 3-7 days followed by automated high-throughput screening. The drug library contained ~80 compounds, including specific numbers of cytotoxic and targeted drugs. Drug response curves informed the calculation of sensitivity scores, which were compared to the AimedBio reference library to identify potentially effective drug candidates for a given patient. Additionally, corresponding tumor tissues were analyzed through panel sequencing of 50 glioma-related genes. Results: A total of >50 patients with glioblastoma were included, with subgroups from CBmed, Austria, and AimedBio, South Korea. PDC cultures were successful in over 90% of cases, and informative high-throughput drug screening results were obtained. Integration of drug response with genetic tumor profiles yielded testable treatment candidates. Additionally, transcontinental shipping and re-screening of PDCs yielded comparable results, affirming the robustness of the method. Conclusion: This study establishes and validates high-throughput drug screening platforms specifically tailored for functional precision medicine, utilizing glioblastoma as a model. The findings reveal a high degree of validity in the drug screening results, reinforced by the excellent performance of both technical and biological replicates. Such success not only lays a solid foundation for further academic and pharmaceutical collaborations but also opens the path for regulatory approval, bringing the platforms one step closer to clinical implementation. Funding: K1 COMET Competence Centre CBmed, funded by the Federal Ministry of Transport, Innovation and Technology; the Federal Ministry of Science, Research and Economy, Land Steiermark (Dep. 12, Business and Innovation), the Styrian Business Promotion Agency (SFG), and the Vienna Business Agency. COMET is executed by the Austrian Research Promotion Agency (FFG). Citation Format: Nam-Gu Her, Adelheid Woehrer, Gi Ju Lee, Seung Yoon Hyun, Jae Woo Ahn, Ji Soo Kang, Ryu I Hwang, Amin El-Heliebi, Barbara Prietl, Stefanie Stanzer, Thomas R. Pieber, Do-Hyun Nam. Functional precision medicine as a valid tool in glioblastoma clinical practice [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 2553.
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Riedesser, Julian E., Matthias P. Ebert, and Johannes Betge. "Precision medicine for metastatic colorectal cancer in clinical practice." Therapeutic Advances in Medical Oncology 14 (January 2022): 175883592110727. http://dx.doi.org/10.1177/17588359211072703.
Анотація:
Globally, metastatic colorectal cancer is one of the leading causes for cancer-related death. Treatment limited to conventional chemotherapeutics extended life for only a few months. However, advances in surgical approaches and medical treatment regimens have greatly increased survival, even leading to long-term remission in selected patients. Advances in multiomics analysis of tumors have built a foundation for molecular-targeted therapies. Furthermore, immunotherapies are on the edge of revolutionizing oncological practice. This review summarizes recent advances in the growing toolbox of personalized treatment for patients with metastatic colorectal cancer. We provide an overview of current multimodal therapy and explain novel immunotherapy and targeted therapy approaches in detail. We emphasize clinically relevant therapies, such as inhibitors of MAPK signaling, and give recommendations for clinical practice. Finally, we describe the potential predictive impact of molecular subtypes and provide an outlook on novel concepts, such as functional precision medicine.
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Smith, Lacey A., Jeremy F. P. Ullmann, Heather E. Olson, Christelle M. El Achkar, Gessica Truglio, McKenna Kelly, Beth Rosen-Sheidley, and Annapurna Poduri. "A Model Program for Translational Medicine in Epilepsy Genetics." Journal of Child Neurology 32, no. 4 (January 6, 2017): 429–36. http://dx.doi.org/10.1177/0883073816685654.
Анотація:
Recent technological advances in gene sequencing have led to a rapid increase in gene discovery in epilepsy. However, the ability to assess pathogenicity of variants, provide functional analysis, and develop targeted therapies has not kept pace with rapid advances in sequencing technology. Thus, although clinical genetic testing may lead to a specific molecular diagnosis for some patients, test results often lead to more questions than answers. As the field begins to focus on therapeutic applications of genetic diagnoses using precision medicine, developing processes that offer more than equivocal test results is essential. The success of precision medicine in epilepsy relies on establishing a correct genetic diagnosis, analyzing functional consequences of genetic variants, screening potential therapeutics in the preclinical laboratory setting, and initiating targeted therapy trials for patients. The authors describe the structure of a comprehensive, pediatric Epilepsy Genetics Program that can serve as a model for translational medicine in epilepsy.
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Clasen, Kerstin, Cihan Gani, Christopher Schroeder, Olaf Riess, Daniel Zips, Oliver Schöffski, and Stephan Clasen. "Patient views on genetics and functional imaging for precision medicine: a willingness-to-pay analysis." Personalized Medicine 19, no. 2 (March 2022): 103–12. http://dx.doi.org/10.2217/pme-2021-0067.
Анотація:
Purpose: Willingness-to-pay (WTP) analyses can support allocation processes considering the patients preferences in personalized medicine. However, genetic testing especially might imply ethical concerns that have to be considered. Methods: A WTP questionnaire was designed to compare preferences for imaging and genetic testing in cancer patients and to evaluate potential ethical concerns. Results: Comparing the options of imaging and genetics showed comparable WTP values. Ethical concerns about genetic testing seemed to be minor. Treatment success was the top priority irrespective of the diagnostic modality. In general, the majority of patients considered personalized medicine to be beneficial. Conclusion: Most patients valued personalized approaches and rated the benefits of precision medicine of overriding importance irrespective of modality or ethical concerns.
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Rezayi, Sorayya, Sharareh R Niakan Kalhori, and Soheila Saeedi. "Effectiveness of Artificial Intelligence for Personalized Medicine in Neoplasms: A Systematic Review." BioMed Research International 2022 (April 7, 2022): 1–34. http://dx.doi.org/10.1155/2022/7842566.
Анотація:
Purpose. Artificial intelligence (AI) techniques are used in precision medicine to explore novel genotypes and phenotypes data. The main aims of precision medicine include early diagnosis, screening, and personalized treatment regime for a patient based on genetic-oriented features and characteristics. The main objective of this study was to review AI techniques and their effectiveness in neoplasm precision medicine. Materials and Methods. A comprehensive search was performed in Medline (through PubMed), Scopus, ISI Web of Science, IEEE Xplore, Embase, and Cochrane databases from inception to December 29, 2021, in order to identify the studies that used AI methods for cancer precision medicine and evaluate outcomes of the models. Results. Sixty-three studies were included in this systematic review. The main AI approaches in 17 papers (26.9%) were linear and nonlinear categories (random forest or decision trees), and in 21 citations, rule-based systems and deep learning models were used. Notably, 62% of the articles were done in the United States and China. R package was the most frequent software, and breast and lung cancer were the most selected neoplasms in the papers. Out of 63 papers, in 34 articles, genomic data like gene expression, somatic mutation data, phenotype data, and proteomics with drug-response which is functional data was used as input in AI methods; in 16 papers’ (25.3%) drug response, functional data was utilized in personalization of treatment. The maximum values of the assessment indicators such as accuracy, sensitivity, specificity, precision, recall, and area under the curve (AUC) in included studies were 0.99, 1.00, 0.96, 0.98, 0.99, and 0.9929, respectively. Conclusion. The findings showed that in many cases, the use of artificial intelligence methods had effective application in personalized medicine.
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Clegg, John R., Afshan S. Irani, Eric W. Ander, Catherine M. Ludolph, Abhijeet K. Venkataraman, Justin X. Zhong, and Nicholas A. Peppas. "Synthetic networks with tunable responsiveness, biodegradation, and molecular recognition for precision medicine applications." Science Advances 5, no. 9 (September 2019): eaax7946. http://dx.doi.org/10.1126/sciadv.aax7946.
Анотація:
Formulations and devices for precision medicine applications must be tunable and multiresponsive to treat heterogeneous patient populations in a calibrated and individual manner. We engineered modular poly(acrylamide-co-methacrylic acid) copolymers, cross-linked into multiresponsive nanogels with either a nondegradable or degradable disulfide cross-linker, that were customized via orthogonal chemistries to target biomarkers of an individual patient’s disease or deliver multiple therapeutic modalities. Upon modification with functional small molecules, peptides, or proteins, these nanomaterials delivered methylene blue with environmental responsiveness, transduced visible light for photothermal therapy, acted as a functional enzyme, or promoted uptake by cells. In addition to quantifying the nanogels’ composition, physicochemical characteristics, and cytotoxicity, we used a QCM-D method for characterizing nanomaterial degradation and a high-throughput assay for cellular uptake. In conclusion, we generated a tunable nanogel composition for precision medicine applications and new quantitative protocols for assessing the bioactivity of similar platforms.
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Galderisi, S. "Precision medicine in psychosis: Translating findings from research into clinical practice." European Psychiatry 64, S1 (April 2021): S70. http://dx.doi.org/10.1192/j.eurpsy.2021.218.
Анотація:
Abstract Body Precision medicine is “an emerging approach for treatment and prevention that takes into account each person’s variability in genes, environment, and lifestyle” [1]. The terminology is increasingly used in psychiatry, and especially in research relevant to the prediction of psychosis onset, response to treatment and functional outcome. While this is an important step-forward for the discipline, at this stage it is very important to promote the translation of research findings into clinical practice, as much as possible. Nowadays the availability of machine learning and artificial intelligence tools, together with advances in data storage and data security, enable the integration of neuroimaging, biological, clinical and cognitive data. By overcoming current limitations in multiple domain data analysis these tools may lead to the identification of reliable diagnostic, prognostic and therapeutic markers in routine clinical care, as well as to the prediction of clinically meaningful outcomes (e.g., psychosis onset, symptomatic and functional outcome, and treatment response). Precision medicine in psychiatry is a developing science, deserving further large-scale research, translational approaches and refinement that, hopefully, will soon be an integral part of every-day clinical practice. However, challenges in pursuing this strategy should not be underestimated, and efforts should be made to constantly advocate for more investments in human and financial resources in psychiatry, and to concentrate on the use of widely available and not too expensive and time-consuming methods.1 Toward Precision Medicine. Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Washington, DC: National Academies Press; 2011.DisclosureNo significant relationships.
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Post, Nicholas, and George T. C. Chiu. "Precision Deposition of Functional Layers for Microcantilever Sensor Generation." NIP & Digital Fabrication Conference 23, no. 1 (January 1, 2007): 846–51. http://dx.doi.org/10.2352/issn.2169-4451.2007.23.1.art00082_2.
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García-Giménez, José Luis, Salvador Mena-Molla, Francisco José Tarazona-Santabalbina, Jose Viña, Mari Carmen Gomez-Cabrera, and Federico V. Pallardó. "Implementing Precision Medicine in Human Frailty through Epigenetic Biomarkers." International Journal of Environmental Research and Public Health 18, no. 4 (February 15, 2021): 1883. http://dx.doi.org/10.3390/ijerph18041883.
Анотація:
The main epigenetic features in aging are: reduced bulk levels of core histones, altered pattern of histone post-translational modifications, changes in the pattern of DNA methylation, replacement of canonical histones with histone variants, and altered expression of non-coding RNA. The identification of epigenetic mechanisms may contribute to the early detection of age-associated subclinical changes or deficits at the molecular and/or cellular level, to predict the development of frailty, or even more interestingly, to improve health trajectories in older adults. Frailty reflects a state of increased vulnerability to stressors as a result of decreased physiologic reserves, and even dysregulation of multiple physiologic systems leading to adverse health outcomes for individuals of the same chronological age. A key approach to overcome the challenges of frailty is the development of biomarkers to improve early diagnostic accuracy and to predict trajectories in older individuals. The identification of epigenetic biomarkers of frailty could provide important support for the clinical diagnosis of frailty, or more specifically, to the evaluation of its associated risks. Interventional studies aimed at delaying the onset of frailty and the functional alterations associated with it, would also undoubtedly benefit from the identification of frailty biomarkers. Specific to the article yet reasonably common within the subject discipline.
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Acanda De La Rocha, Arlet M., Maggie Fader, Ebony R. Coats, Paula S. Espinal, Vanessa Berrios, Cima Saghira, Ileana Sotto, et al. "Clinical Utility of Functional Precision Medicine in the Management of Recurrent/Relapsed Childhood Rhabdomyosarcoma." JCO Precision Oncology, no. 5 (October 2021): 1659–65. http://dx.doi.org/10.1200/po.20.00438.
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Hamilton, Gerhard, Barbara Rath, Adelina Plangger, and Maximilian Hochmair. "Implementation of functional precision medicine for anaplastic lymphoma kinase-rearranged non-small lung cancer." Precision Cancer Medicine 2 (June 2019): 19. http://dx.doi.org/10.21037/pcm.2019.05.03.
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Falligant, John Michael, and Louis P. Hagopian. "Further extensions of precision medicine to behavior analysis: A demonstration using functional communication training." Journal of Applied Behavior Analysis 53, no. 4 (July 21, 2020): 1961–81. http://dx.doi.org/10.1002/jaba.739.