In silico signaling modeling to understand cancer pathways and treatment responses

2019 ◽  
Vol 21 (3) ◽  
pp. 1115-1117 ◽  
Author(s):  
Meik Kunz ◽  
Julian Jeromin ◽  
Maximilian Fuchs ◽  
Jan Christoph ◽  
Giulia Veronesi ◽  
...  
Keyword(s):  
Precision Medicine ◽  
In Silico ◽  
Treatment Strategies ◽  
Therapy Response ◽  
Cancer Pathways ◽  
In Silico Modeling ◽  
Treatment Responses ◽  
The Individual ◽  
In Silico Models ◽  
Pan Cancer

Abstract Precision medicine has changed thinking in cancer therapy, highlighting a better understanding of the individual clinical interventions. But what role do the drivers and pathways identified from pan-cancer genome analysis play in the tumor? In this letter, we will highlight the importance of in silico modeling in precision medicine. In the current era of big data, tumor engines and pathways derived from pan-cancer analysis should be integrated into in silico models to understand the mutational tumor status and individual molecular pathway mechanism at a deeper level. This allows to pre-evaluate the potential therapy response and develop optimal patient-tailored treatment strategies which pave the way to support precision medicine in the clinic of the future.

scholarly journals Robust Detection of DNA Hypermethylation of ZNF154 as a Pan-Cancer Locus with in Silico Modeling for Blood-Based Diagnostic Development

2016 ◽  
Vol 18 (2) ◽  
pp. 283-298 ◽  
Author(s):  
Gennady Margolin ◽  
Hanna M. Petrykowska ◽  
Nader Jameel ◽  
Daphne W. Bell ◽  
Alice C. Young ◽  
...  
Keyword(s):  
In Silico ◽  
Dna Hypermethylation ◽  
Robust Detection ◽  
In Silico Modeling ◽  
Pan Cancer

scholarly journals Considering religion and spirituality in precision medicine

2019 ◽  
Vol 10 (1) ◽  
pp. 195-203
Author(s):  
Karen H K Yeary ◽  
Kassandra I Alcaraz ◽  
Kimlin Tam Ashing ◽  
Chungyi Chiu ◽  
Shannon M Christy ◽  
...  
Keyword(s):  
Precision Medicine ◽  
Health Beliefs ◽  
Treatment Strategies ◽  
Great Promise ◽  
Religion And Spirituality ◽  
Clinical Practices ◽  
Patient Centered ◽  
Treatment Context ◽  
The Individual ◽  
High Level

Abstract The emerging era of precision medicine (PM) holds great promise for patient care by considering individual, environmental, and lifestyle factors to optimize treatment. Context is centrally important to PM, yet, to date, little attention has been given to the unique context of religion and spirituality (R/S) and their applicability to PM. R/S can support and reinforce health beliefs and behaviors that affect health outcomes. The purpose of this article is to discuss how R/S can be considered in PM at multiple levels of context and recommend strategies for integrating R/S in PM. We conducted a descriptive, integrative literature review of R/S at the individual, institutional, and societal levels, with the aim of focusing on R/S factors with a high level of salience to PM. We discuss the utility of considering R/S in the suitability and uptake of PM prevention and treatment strategies by providing specific examples of how R/S influences health beliefs and practices at each level. We also propose future directions in research and practice to foster greater understanding and integration of R/S to enhance the acceptability and patient responsiveness of PM research approaches and clinical practices. Elucidating the context of R/S and its value to PM can advance efforts toward a more whole-person and patient-centered approach to improve individual and population health.

scholarly journals Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models

Cancers ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 28 ◽  
Author(s):  
Florentin Baur ◽  
Sarah L. Nietzer ◽  
Meik Kunz ◽  
Fabian Saal ◽  
Julian Jeromin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Treatment Options ◽  
Braf Inhibitor ◽  
3D Models ◽  
Cancer Pathways ◽  
In Silico Models ◽  
Tissue Matrix ◽  
Tissue Models

To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.

scholarly journals A Two-Stage Purkinje Network for More Accurate ECG Representations

2020 ◽  
Author(s):  
Noha Shalaby ◽  
Heba Aguib ◽  
Mohamed Badran ◽  
Khalil Elkhodary
Keyword(s):  
In Silico ◽  
Electrical Activation ◽  
Activation Patterns ◽  
Early Activation ◽  
In Silico Modeling ◽  
Ventricular Activation ◽  
Endocardial Surface ◽  
In Silico Models ◽  
Purkinje Network

Abstract In this manuscript we propose a method to generate Purkinje networks that are anatomically and physiologically plausible, for use with in-silico modeling. Purkinje networks play a fundamental role in shaping cardiac electrical activation patterns and their corresponding clinical electrocardiograms (ECGs). Despite a known variability in ventricular activation sequences, certain sites of early activation within the left and right ventricles have been identified in the literature for normal electrical excitation patterns. Nevertheless, in-vivo imaging of Purkinje networks cannot at present yield detailed information on their structure, so there is a genuine need for in-silico models that can construct Purkinje networks that are both anatomically and physiologically plausible, in particular networks that can exhibit correctly situated early activation sites in the ventricles. Of special interest to this manuscript is the method of representation of Purkinje networks by line-like electrical elements that are generated by means of a fractal-tree algorithm (1–3) to overlay the irregular endocardial surfaces. A known drawback to a direct implementation of this approach in complex geometries relates to its incorrect modeling of clinically observed ECGs and electrical activation sequences for a human heart (4). Our aim was thus to correct this deficiency by generating Purkinje networks that leverage a pre-knowledge of the location of early activation sites. At every such site we first generate a Purkinje sub-network. These sub-networks are linked together and to the bundle of His, setting up our first stage of the Purkinje network. Subsequently, we spawn a second stage to the Purkinje network from one or more tips of any given sub-network, to cover the full endocardial surface with Purkinje elements. Our resulting activation sequences and ECGs compare favorably to those of a population of 39 healthy male individuals (the PTB diagnostic database), and our corresponding mechanical markers of cardiac function also match well with the literature.

‘Precision psychiatry’ needs to become part of ‘personalized psychiatry’

2020 ◽  
Vol 88 (12) ◽  
pp. 767-772
Author(s):  
Giulia Maria Giordano ◽  
Pasquale Pezzella ◽  
Andrea Perrottelli ◽  
Silvana Galderisi
Keyword(s):  
Precision Medicine ◽  
Treatment Strategies ◽  
Personalized Care ◽  
Treatment And Prevention ◽  
Technological Advances ◽  
Choice Of Treatment ◽  
Treatment Plans ◽  
The Individual ◽  
Personalized Psychiatry ◽  
Current Potential

Abstract‘Precision medicine’ is defined as ‘an emerging approach for treatment and prevention that takes into account each person’s variability in genes, environment, and lifestyle’. Sometimes the term ‘personalized medicine’ is also used, either as a synonym or in a broader sense. In psychiatry, the term ‘personalized’ applies to different levels of health-care provision, such as the service organization and the choice of treatment plans based on the characterization of the individual patient. This approach is already feasible but, currently, it is often hampered by the shortage of human and financial resources. Recently, the terminology of ‘precision medicine’ has been extended to psychiatry: the term ‘precision psychiatry’ refers to the full exploitation of recent scientific and technological advances to achieve a close match between individual biosignature and prevention / treatment strategies. This article provides an overview of recent advances in neuroimaging, multi-omics and computational neuroscience, which have contributed to foster our understanding of the neurobiology of major mental disorders, and led to the implementation of a precision medicine-oriented approach in psychiatry.We argue that, while ‘precision psychiatry’ represents an important step to further advance the effectiveness of the ‘personalized psychiatry’, the distinction between the two terms is important to avoid dangerous neglect of the current potential of personalized care in psychiatry and to underscore the need for disseminating good existing practices aimed at organizing mental health services and providing care according to person’s psychopathological characteristics, illness trajectory, needs, environment and preferences.In conclusion, ‘precision psychiatry’ will contribute to advance ‘personalized psychiatry’, but for the time being keeping the distinction between the two terms will contribute to fully exploit the current potential of personalized care.

In silico modeling of cellular probabilistic nanoparticle radiosensitization in head and neck cancers

Nanomedicine ◽  
2020 ◽  
Vol 15 (29) ◽  
pp. 2837-2850
Author(s):  
Myxuan Huynh ◽  
Ivan Kempson ◽  
Eva Bezak ◽  
Wendy Phillips
Keyword(s):  
Head And Neck ◽  
Patient Outcomes ◽  
Head And Neck Cancers ◽  
New Approach ◽  
Treatment Regimens ◽  
Therapeutic Benefits ◽  
In Silico Modeling ◽  
The Individual ◽  
Dose Deposition ◽  
Therapy Treatment

Background: The use of gold nanoparticles (AuNPs) as radiosensitizers may offer a new approach in the treatment of head and neck cancers; minimizing treatment-associated toxicities and improving patient outcomes. AuNPs promote localized dose deposition; permitting improved local control and/or dose reduction. Aim: This work aimed to address the theoretical optimization of radiation doses, fractionation and nanoparticle injection schedules to maximize therapeutic benefits. Materials & methods: Probabilistic nanoparticle sensitization factors were incorporated into the individual cell-based HYP-RT computer model of tumor growth and radiotherapy. Results: Total dose outcomes across all radiation therapy treatment regimens were found to be significantly reduced with the presence of AuNPs, with bi-weekly injections showing the most decrease. Conclusion: Outcomes suggest the need for regular AuNP administration to permit effective radiosensitization.

Sign in / Sign up

Export Citation Format

Share Document