Our understanding of hereditary breast and ovarian cancer has significantly improved over the past two decades. In addition to BRCA1/2, pathogenic variants in several other DNA-repair genes have been shown to increase the risks of breast and ovarian cancer. The magnitude of cancer risk is impacted not only by the gene involved, but also by family history of cancer, polygenic risk scores, and, in certain genes, pathogenic variant type or location. While estimates of breast and ovarian cancer risk associated with pathogenic variants are available, these are predominantly based on studies of high-risk populations with young age at diagnosis of cancer, multiple primary cancers, or family history of cancer. More recently, breast cancer risk for germline pathogenic variant carriers has been estimated from population-based studies. Here, we provide a review of the field of germline genetic testing and risk evaluation for hereditary breast and ovarian cancers in high-risk and population-based settings.
Metastasis is the ultimate and often lethal stage of cancer. Metastasis occurs in three phases that may vary across individuals: First, dissemination from the primary tumor. Second, tumor dormancy at the metastatic site where micrometastatic cancer cells remain quiescent or, in dynamic cycles of proliferation and elimination, remaining clinically undetectable. Finally, cancer cells are able to overcome microenvironmental constraints for outgrowth, or the formation of clinically detectable macrometastases that colonize distant organs and are largely incurable. A variety of approaches have been used to model metastasis to elucidate molecular mechanisms and identify putative therapeutic targets. In particular, metastatic dormancy has been challenging to model in vivo due to the sparse numbers of cancer cells in micrometastasis nodules and the long latency times required for tumor outgrowth. Here, we review state-of-the art genetically engineered mouse, syngeneic, and patient-derived xenograft approaches for modeling metastasis and dormancy. We describe the advantages and limitations of various metastasis models, novel findings enabled by such approaches, and highlight opportunities for future improvement.
Dementia is a significant public health crisis; the most common underlying cause of age-related cognitive decline and dementia is Alzheimer's disease neuropathologic change (ADNC). As such, there is an urgent need to identify novel therapeutic targets for the treatment and prevention of the underlying pathologic processes that contribute to the development of AD dementia. Although age is the top risk factor for dementia in general and AD specifically, these are not inevitable consequences of advanced age. Some individuals are able to live to advanced age without accumulating significant pathology (resistance to ADNC), whereas others are able to maintain cognitive function despite the presence of significant pathology (resilience to ADNC). Understanding mechanisms of resistance and resilience will inform therapeutic strategies to promote these processes to prevent or delay AD dementia. This article will highlight what is currently known about resistance and resilience to AD, including our current understanding of possible underlying mechanisms that may lead to candidate preventive and treatment interventions for this devastating neurodegenerative disease.
Optogenetics has emerged over the past 20 years as a powerful tool to investigate the various circuits underlying numerous functions, especially in neuroscience. The ability to control by light the activity of neurons has enabled the development of therapeutic strategies aimed at restoring some level of vision in blinding retinal conditions. Promising preclinical and initial clinical data support such expectations. Numerous challenges remain to be tackled (e.g., confirmation of safety, cell and circuit specificity, patterns, intensity and mode of stimulation, rehabilitation programs) on the path toward useful vision restoration.
The use of patient-derived xenografts (PDXs) has dramatically improved drug development programs. PDXs (1) reproduce the pathological features and the genomic profile of the parental tumors more precisely than other preclinical models, and (2) more faithfully predict therapy response. However, PDXs have limitations. These include the inability to completely capture tumor heterogeneity and the role of the immune system, the low engraftment efficiency of certain tumor types, and the consequences of the human-host interactions. Recently, the use of novel mouse strains and specialized engraftment techniques has enabled the generation of "humanized" PDXs, partially overcoming such limitations. Importantly, establishing, characterizing, and maintaining PDXs is costly and requires a significant regulatory, administrative, clinical, and laboratory infrastructure. In this review, we will retrace the historical milestones that led to the implementation of PDXs for cancer research, review the most recent innovations in the field, and discuss future avenues to tackle deficiencies that still exist.
With the rapid expansion of methods encompassed by the term gene therapy, new trials exploring the safety and efficacy of these methods are initiated more frequently. As a result, important questions arise pertaining the design of these trials and patient participation. One of the most important aspects of any clinical trial is the ability to measure the trial's outcome in a manner that will reflect the effect of the treatment and allow its quantification, whether the trial is aimed at preservation or restoration of retinal cells (photoreceptors and others), vision, or both. Here we will review the existing methods for quantification of trial outcomes, stressing the importance of assessing the participant's visual function and not just visual acuity. We will also describe the key considerations in trial design. Finally, as patient safety remains the primary concern in any trial participation, we will outline the key principles in that regard.

