216 research outputs found
Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set
BACKGROUND: While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements. METHODS: We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan–Meier method. RESULTS: PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R(2) = 0.73 and R(2) = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts). CONCLUSIONS: The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0705-4) contains supplementary material, which is available to authorized users
Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set
Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential
Evidence of positive selection associated with placental loss in tiger sharks
Background: All vertebrates initially feed their offspring using yolk reserves. In some live-bearing species these yolk
reserves may be supplemented with extra nutrition via a placenta. Sharks belonging to the Carcharhinidae family
are all live-bearing, and with the exception of the tiger shark (Galeocerdo cuvier), develop placental connections
after exhausting yolk reserves. Phylogenetic relationships suggest the lack of placenta in tiger sharks is due to
secondary loss. This represents a dramatic shift in reproductive strategy, and is likely to have left a molecular
footprint of positive selection within the genome.
Results: We sequenced the transcriptome of the tiger shark and eight other live-bearing shark species. From this
data we constructed a time-calibrated phylogenetic tree estimating the tiger shark lineage diverged from the
placental carcharhinids approximately 94 million years ago. Along the tiger shark lineage, we identified five genes
exhibiting a signature of positive selection. Four of these genes have functions likely associated with brain
development (YWHAE and ARL6IP5) and sexual reproduction (VAMP4 and TCTEX1D2).
Conclusions: Our results indicate the loss of placenta in tiger sharks may be associated with subsequent adaptive
changes in brain development and sperm production
Phylotranscriptomics suggests the jawed vertebrate ancestor could generate diverse helper and regulatory T cell subsets
This study was supported by The Royal Society Research Grant RG130789 awarded to HD, as well as by a University of Aberdeen Centre for Genome-Enabled Biology and Medicine PhD studentship and Marine Alliance for Science and Technology for Scotland (MASTS) research grant SG363 awarded to AKR.Peer reviewedPublisher PD
New developments in vertebrate cytotaxonomy II. the chromosomes of the cartilaginous fishes
- …