Precision Medicine and Cancer Systems Biology: From Drug Screening to Therapeutics

Dear Colleagues,

Cancer is a highly complex, heterogeneous, and robust disease and depending on the organs affected, it may be classified as leukemia, lymphoma, sarcoma, carcinoma, melanoma, or glioma. Multi-level unwanted alterations (such as (epi)genetic alterations, transcriptional level change, and abnormal signaling) are the main reason behind the conversion of normal cells into tumor cells and such heterogenous levels of complexity are considered as the greatest barrier in the development of therapeutic approaches or in the resistance to existing therapeutic approaches. In other words, we can say that intra-tumor cell population variability and complexity are potential reasons for the poor efficacy of biomarker-based targeted cancer therapy. In a simplified way, it can also be said that cancer arises due to failure at multiple levels in multicellular organisms (due to genetic lesions, abnormal signaling, and metabolic disorders). After such changes, the cell appears different from a normal cell and is called a cancer cell. This cell is clearly different in physiological behavior and in morphology compared to a normal cell. The (epi)genetic alterations and transcriptional-level change have a potential impact on cellular signaling pathways and networks. The expression level of signaling molecules (SMs) and the types of interactions (feedforward and feedback loops (both positive and negative) and crosstalk between signaling pathways) control the temporal dynamics of SMs and temporal dynamics (transient, sustained, and oscillatory) are associated with cell-fate decisions (apoptosis, proliferation, differentiation, growth). In this Special Issue, we aim to publish research/reviews/reports/perspectives within the computational and/or experimental field that could act as a milestone in achieving the goal of successful application of precision medicine or personalized therapeutics.

The program's overarching goal is to determine the genetic markers and mechanisms that cause resistance in individual cells, as well as the degree of intratumor heterogeneity and how this affects cancer treatment. The program's goal is to create instruments with a wider range of applications across several indications.

Specific goals:

The overall goal of this project is to develop a novel theoretical approach in the context of various cancer types in conjunction with bioinformatics (data analysis), systems biology (mathematical modeling of biological pathways and networks), and computational chemistry (docking and MDS). These approaches will aid in the analysis and comprehension of changes at the transcriptional and translational levels, enriched (inferred) pathways, and (epi)genetic modification and determine the subsets of SMs that are most likely to be the cause of changes by forecasting the dominantly impacted pathways and the crosstalk between them from the sets of inferred pathways.

Dr. Mohammad Mobashir
Guest Editor

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• bioinformatics
• data analysis
• systems biology
• computational chemistry
• genetic marker
• precision medicine