Download Cancer Drug Resistance by Marta Baiocchi 2022 Easily In PDF Format For Free
Preface
Despite the recent advancement in cancer treatment, drug resistance still constitutes a major
cause of death in patients, affecting not only first-generation chemotherapies but also
new-concept, pathway-directed drugs. Thus, it represents a continuous challenge for both
clinical and basic research efforts. The enormous amount of research conducted on this
topic keeps disclosing a complex interplay of different biological mechanisms, interacting
and cooperating in the development of drug resistance.
To the aim of improving the overall clinical outcome of cancer patients, dissecting this wide web of molecular and biological
events is a task of the utmost importance, which imperatively requires solid methodologies,
both for basic research and for reliable preclinical studies.
The growing knowledge of gene alterations associated with drug resistance is now being
progressively integrated by an increased capability to analyze nongenetic events such as
epigenetic and metabolic changes, tumor cell heterogeneity, and cellular interactions
between tumor and microenvironment.
The concept of cancer stem cells, in turn, is influencing the concept of cancer drug resistance, owing to their dynamic features that
make them capable of transitioning to quiescent or drug-resistant states.
Aimed to give a state-of-the-art practical guide, this book brings together a variety of
different protocols, all geared toward identifying cancer drug resistance determinants by
different approaches, at the molecular, cellular, and/or functional levels.
Protocols range from microfluidic cancer cell culture and tumor-microenvironment cell co-culture methods, to workflows for functional assessment of drug resistance in vitro and in vivo, to quantitative techniques for identifying quiescent blood-flow circulating cells, to single-cell characteriza- tion techniques, such as mass cytometry.
Updated approaches to genomic and epigenomic, transcriptomic, and metabolomic analyses are also described, importantly also including
advanced computational methods for large dataset sorting and analysis.
Given the diversity of techniques described, we believe this volume will provide readers not only with an updated how-to guide to the latest methods but also with an exciting overview of the wide variety of current, evolving approaches to understanding and over coming anticancer drug resistance.
