Primary and Secondary Cone Cell Death Mechanisms in Inherited Retinal Diseases and Potential Treatment Options

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Abstract

Inherited retinal diseases (IRDs) are a leading cause of blindness. To date, 260 disease-causing genes have been identified, but there is currently a lack of available and effective treatment options. Cone photoreceptors are responsible for daylight vision but are highly susceptible to disease progression, the loss of cone-mediated vision having the highest impact on the quality of life of IRD patients. Cone degeneration can occur either directly via mutations in cone-specific genes (primary cone death), or indirectly via the primary degeneration of rods followed by subsequent degeneration of cones (secondary cone death). How cones degenerate as a result of pathological mutations remains unclear, hindering the development of effective therapies for IRDs. This review aims to highlight similarities and differences between primary and secondary cone cell death in inherited retinal diseases in order to better define cone death mechanisms and further identify potential treatment options.

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The term apoptosis is proposed for a hitherto little recognized mechanism of controlled cell deletion, which appears to play a complementary but opposite role to mitosis in the regulation of animal cell populations. Its morphological features suggest that it is an active, inherently programmed phenomenon, and it has been shown that it can be initiated or inhibited by a variety of environmental stimuli, both physiological and pathological. The structural changes take place in two discrete stages. The first comprises nuclear and cytoplasmic condensation and breaking up of the cell into a number of membrane-bound, ultrastructurally well-preserved fragments. In the second stage these apoptotic bodies are shed from epithelial-lined surfaces or are taken up by other cells, where they undergo a series of changes resembling in vitro autolysis within phagosomes, and are rapidly degraded by lysosomal enzymes derived from the ingesting cells. Apoptosis seems to be involved in cell turnover in many healthy adult tissues and is responsible for focal elimination of cells during normal embryonic development. It occurs spontaneously in untreated malignant neoplasms, and participates in at least some types of therapeutically induced tumour regression. It is implicated in both physiological involution and atrophy of various tissues and organs. It can also be triggered by noxious agents, both in the embryo and adult animal. Images Fig. 8-10 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 6 Fig. 7 Fig. 11-14 Fig. 15-18 Fig. 19 Fig. 20-22 Fig. 23 and 24

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Disturbances in the normal functions of the ER lead to an evolutionarily conserved cell stress response, the unfolded protein response, which is aimed initially at compensating for damage but can eventually trigger cell death if ER dysfunction is severe or prolonged. The mechanisms by which ER stress leads to cell death remain enigmatic, with multiple potential participants described but little clarity about which specific death effectors dominate in particular cellular contexts. Important roles for ER-initiated cell death pathways have been recognized for several diseases, including hypoxia, ischemia/reperfusion injury, neurodegeneration, heart disease, and diabetes.

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Estimation of clinical trial success rates and related parameters

Chi Heem Wong, Kien Wei Siah, Andrew Lo (2018)

SUMMARY Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial data for over 21 143 compounds from January 1, 2000 to October 31, 2015, we estimate aggregate clinical trial success rates and durations. We also compute disaggregated estimates across several trial features including disease type, clinical phase, industry or academic sponsor, biomarker presence, lead indication status, and time. In several cases, our results differ significantly in detail from widely cited statistics. For example, oncology has a 3.4% success rate in our sample vs. 5.1% in prior studies. However, after declining to 1.7% in 2012, this rate has improved to 2.5% and 8.3% in 2014 and 2015, respectively. In addition, trials that use biomarkers in patient-selection have higher overall success probabilities than trials without biomarkers.