The road from Rous sarcoma virus to precision medicine.

In 1911, more than a century ago, Peyton Rous described a curious observation, later explained by a virus named for him that led to the discovery of oncogenes, the modern era of cancer research, and the emergent field of precision medicine (1911. J. Exp. Med. https://doi.org/10.1084/jem.13.4.397).

Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell.

Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. However, the precision/personalized medicine community has tended to underappreciate the third alphabet of life, the "sugar code" (i.e., the information stored in glycans, glycoproteins, and glycolipids). This article brings together experts in precision/personalized medicine science, pharmacoglycomics, emerging technology governance, cultural studies, contemporary art, and responsible innovation to critically comment on the sociomateriality of the three alphabets of life together. First, the current transformation of targeted therapies with personalized glycomedicine and glycan biomarkers is examined. Next, we discuss the reasons as to why unraveling of the sugar code might have lagged behind the DNA and protein codes. While social scientists have historically noted the importance of constructivism (e.g., how people interpret technology and build their values, hopes, and expectations into emerging technologies), life scientists relied on the material properties of technologies in explaining why some innovations emerge rapidly and are more popular than others. The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.

Combining Antimicrobial Peptides with Nanotechnology: An Emerging Field in Theranostics.

The emergence of multidrug-resistant pathogens and their rapid adaptation against new antibiotics is a major challenge for scientists and medical professionals. Different approaches have been taken to combat this problem, which includes rationally designed potent antimicrobial peptides (AMPs) and several nanoparticles and quantum dots. AMPs are considered as a new generation of super antibiotics that hold enormous potential to fight against bacterial resistance by the rapidly killing planktonic as well as their biofilm form while keeping low toxicity profile against eukaryotic cells. Various nanoparticles and quantum dots have proved their effectiveness against a vast array of infections and diseases. Conjugation and functionalization of nanoparticles with potentially active antimicrobial peptides have added advantages that widen their applications in the field of drug discovery as well as delivery system including imaging and diagnostics. This article reviews the current progress and implementation of different nanoparticles and quantum dots conjugated antimicrobial peptides in terms of bio-stability, drug delivery, and therapeutic applications.

Genomics and the History of Precision Oncology.

Progress toward the implementation of a molecular characterization paradigm in cancer drug development over the past 20 years has markedly enhanced our capability to select patients who are more likely to benefit from cancer therapy. Improvements in genomic and related diagnostic testing platforms have permitted evaluation of the efficacy of treatment assignment based on predefined biologic features of a patient's tumor or germline using master protocols that may include many malignancies and their molecularly characterized subsets. With this approach, a wide range of new targeted and immunologic treatment approaches have been defined for patients who, heretofore, lacked effective therapeutic options.

The history, current status, and possible future of precision mental health.

In evidence-based mental health practice, decisions must often be made for which there is little or no empirical basis. A common example of this is when there are multiple empirically supported interventions for a person with a given diagnosis, where the aim is to recommend the treatment most likely to be effective for that person. Data obtained from randomized clinical trials allow for the identification of patient characteristics that could be used to match patients to treatments. Historically, researchers have focused on individual moderators, single variables that interact statistically with treatment type, but these have rarely proved powerful enough to inform treatment decisions. Recently, researchers have begun to explore ways in which the use of multivariable algorithms might improve clinical decision-making. Common pitfalls have been identified, including the use of methods that provide overoptimistic estimates of the gains that can be expected from the applications of an algorithm in a clinical setting. It is too early to tell if these efforts will pay off and, if so, how much their use can increase the efficiency and effectiveness of mental health systems. It behooves the field to continue to learn and develop the most powerful methods that can produce generalizable knowledge that will advance the aims of precision mental health.

From the Broad Phase II Trial to Precision Oncology: A Perspective on the Origins of Basket and Umbrella Clinical Trial Designs in Cancer Drug Development.

Oncologic phase II trials that evaluate the activity of new therapeutic agents have evolved dramatically over the past 50 years. The standard approach beginning in the late 1960s focused on individual studies that evaluated new anticancer agents against a wide range of both solid and hematopoietic malignancies often in a single "broad phase II trial" that included hundreds of patients; such studies efficiently established the landscape for subsequent development of a specific drug with respect to likely disease focus, toxicity, dose, and schedule. In the 1980s and 1990s, emphasis on histological context drove an explosion in the number of individual phase II trials conducted; despite this increase in trial activity, investigations based on histology per se failed to improve the success rate of new agents brought to the clinic. Over the past 20 years, evolution toward a molecular drug development paradigm has demonstrably improved our ability to select patients more likely to benefit from systemic treatment; simultaneously, technological advances have permitted initial attempts at the rapid assignment of therapy based on predefined molecular characteristics of tumor or germline in broad-based master protocols that are inclusive of many diseases and molecularly characterized disease subsets, akin to but much more sophisticated scientifically than the broad phase II platforms of the past.

Post-Modern Epidemiology: When Methods Meet Matter.

In the last third of the 20th century, etiological epidemiology within academia in high-income countries shifted its primary concern from attempting to tackle the apparent epidemic of noncommunicable diseases to an increasing focus on developing statistical and causal inference methodologies. This move was mutually constitutive with the failure of applied epidemiology to make major progress, with many of the advances in understanding the causes of noncommunicable diseases coming from outside the discipline, while ironically revealing the infectious origins of several major conditions. Conversely, there were many examples of epidemiologic studies promoting ineffective interventions and little evident attempt to account for such failure. Major advances in concrete understanding of disease etiology have been driven by a willingness to learn about and incorporate into epidemiology developments in biology and cognate data science disciplines. If fundamental epidemiologic principles regarding the rooting of disease risk within populations are retained, recent methodological developments combined with increased biological understanding and data sciences capability should herald a fruitful post-Modern Epidemiology world.

Complexity of genome sequencing and reporting: Next generation sequencing (NGS) technologies and implementation of precision medicine in real life.

The finalization of the Human Genome Project in 2003 paved the way for a deeper understanding of cancer, favouring a faster progression towards "personalized" medicine. Research in oncology has progressively focused on the sequencing of cancer genomes, to better understand the genetic basis of tumorigenesis and identify actionable alterations to guide cancer therapy. Thanks to the development of next-generation-sequencing (NGS) techniques, sequencing of tumoral DNA is today technically easier, faster and cheaper. Commercially available NGS panels enable the detection of single or global genomic alterations, namely gene mutation and mutagenic burden, both on germline and somatic DNA, potentially predicting the response or resistance to cancer treatments. Profiling of tumor DNA is nowadays a standard in cancer research and treatment. In this review we discuss the history, techniques and applications of NGS in cancer care, under a "personalized tailored therapy" perspective.