Editorial: Personalized Medicine for Urological Cancers: Targeting Cancer Metabolism

Combined mechanistic modeling and machine-learning approaches in systems biology - A systematic literature review

BACKGROUND AND OBJECTIVE

Mechanistic-based Model simulations (MM) are an effective approach commonly employed, for research and learning purposes, to better investigate and understand the inherent behavior of biological systems. Recent advancements in modern technologies and the large availability of omics data allowed the application of Machine Learning (ML) techniques to different research fields, including systems biology. However, the availability of information regarding the analyzed biological context, sufficient experimental data, as well as the degree of computational complexity, represent some of the issues that both MMs and ML techniques could present individually. For this reason, recently, several studies suggest overcoming or significantly reducing these drawbacks by combining the above-mentioned two methods. In the wake of the growing interest in this hybrid analysis approach, with the present review, we want to systematically investigate the studies available in the scientific literature in which both MMs and ML have been combined to explain biological processes at genomics, proteomics, and metabolomics levels, or the behavior of entire cellular populations.

METHODS

Elsevier Scopus®, Clarivate Web of Science™ and National Library of Medicine PubMed® databases were enquired using the queries reported in Table 1, resulting in 350 scientific articles.

RESULTS

Only 14 of the 350 documents returned by the comprehensive search conducted on the three major online databases met our search criteria, i.e. present a hybrid approach consisting of the synergistic combination of MMs and ML to treat a particular aspect of systems biology.

CONCLUSIONS

Despite the recent interest in this methodology, from a careful analysis of the selected papers, it emerged how examples of integration between MMs and ML are already present in systems biology, highlighting the great potential of this hybrid approach to both at micro and macro biological scales.

Immunosuppressive Signaling Pathways as Targeted Cancer Therapies

Immune response has been shown to play an important role in defining patient prognosis and response to cancer treatment. Tumor-induced immunosuppression encouraged the recent development of new chemotherapeutic agents that assists in the augmentation of immune responses. Molecular mechanisms that tumors use to evade immunosurveillance are attributed to their ability to alter antigen processing/presentation pathways and the tumor microenvironment. Cancer cells take advantage of normal molecular and immunoregulatory machinery to survive and thrive. Cancer cells constantly adjust their genetic makeup using several mechanisms such as nucleotide excision repair as well as microsatellite and chromosomal instability, thus giving rise to new variants with reduced immunogenicity and the ability to continue to grow without restrictions. This review will focus on the central molecular signaling pathways involved in immunosuppressive cells and briefly discuss how cancer cells evade immunosurveillance by manipulating antigen processing cells and related proteins. Secondly, the review will discuss how these pathways can be utilized for the implementation of precision medicine and deciphering drug resistance.

Immunosuppressive Signaling Pathways as Targeted Cancer Therapies

Immune response has been shown to play an important role in defining patient prognosis and response to cancer treatment. Tumor-induced immunosuppression encouraged the recent development of new chemotherapeutic agents that assists in the augmentation of immune responses. Molecular mechanisms that tumors use to evade immunosurveillance are attributed to their ability to alter antigen processing/presentation pathways and the tumor microenvironment. Cancer cells take advantage of normal molecular and immunoregulatory machinery to survive and thrive. Cancer cells constantly adjust their genetic makeup using several mechanisms such as nucleotide excision repair as well as microsatellite and chromosomal instability, thus giving rise to new variants with reduced immunogenicity and the ability to continue to grow without restrictions. This review will focus on the central molecular signaling pathways involved in immunosuppressive cells and briefly discuss how cancer cells evade immunosurveillance by manipulating antigen processing cells and related proteins. Secondly, the review will discuss how these pathways can be utilized for the implementation of precision medicine and deciphering drug resistance.