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Biology subjects

Alavi, S.

Publications and source records attributed to Alavi, S..

2 recordsLinked to original sources

Repurposing melanoma chemotherapy to activate inflammasomes in treatment of BRAF/MAPK inhibitor-resistant melanoma

The development of resistance to treatments of melanoma is commonly associated with upregulation of the MAPK pathway and development of an undifferentiated state. Prior studies have suggested that melanoma with these resistance characteristics may be susceptible to innate death mechanisms such as pyroptosis triggered by activation of inflammasomes. In the present studies we have taken cell lines from patients before and after development of resistance to BRAF V600 inhibitors and exposed the resistant melanoma to temozolomide (a commonly used chemotherapy) with and without chloroquine to inhibit autophagy. It was found that melanoma with an inflammatory undifferentiated state appeared susceptible to this combination when tested in vitro and in vivo against xenografts in NSG mice. Translation of the latter results into patients would promise durable responses in patients treated by the combination. The inflammasome and death mechanism involved appeared to vary between melanoma and involved either AIM2, NLRP3 or NLRC4 inflammasomes and gasdermin D or E. These preliminary studies have raised questions as to the selectivity for different inflammasomes in different melanoma and their selective targeting by chemotherapy. They also question whether the inflammatory state of melanoma may be used as biomarkers to select patients for inflammasome targeted therapy.

cancer biology↗

Population-level inference for home-range areas

O_LIHome-range estimates are a common product of animal tracking data, as each range informs on the area needed by a given individual. Population-level inference on home-range areas--where multiple individual home-ranges are considered to be sampled from a population--is also important to evaluate changes over time, space, or covariates, such as habitat quality or fragmentation, and for comparative analyses of species averages. Population-level home-range parameters have traditionally been estimated by first assuming that the input tracking data were sampled independently when calculating home ranges via conventional kernel density estimation (KDE) or minimal convex polygon (MCP) methods, and then assuming that those individual home ranges were measured exactly when calculating the population-level estimates. This conventional approach does not account for the temporal autocorrelation that is inherent in modern tracking data, nor for the uncertainties of each individual home-range estimate, which are often large and heterogeneous. C_LIO_LIHere, we introduce a statistically and computationally efficient framework for the population-level analysis of home-range areas, based on autocorrelated kernel density estimation (AKDE), that can account for variable temporal autocorrelation and estimation uncertainty. C_LIO_LIWe apply our method to empirical examples on lowland tapir (Tapirus terrestris), kinkajou (Potos flavus), white-nosed coati (Nasua narica), white-faced capuchin monkey (Cebus capucinus), and spider monkey (Ateles geoffroyi), and quantify differences between species, environments, and sexes. C_LIO_LIOur approach allows researchers to more accurately compare different populations with different movement behaviors or sampling schedules, while retaining statistical precision and power when individual home-range uncertainties vary. Finally, we emphasize the estimation of effect sizes when comparing populations, rather than mere significance tests. C_LI

ecology↗