Publications by authors named "J G Kretz"

It is estimated that only 0.02% of disseminated tumour cells are able to seed overt metastases. While this suggests the presence of environmental constraints to metastatic seeding, the landscape of host factors controlling this process remains largely unclear.

View Article and Find Full Text PDF

The tumour evolution model posits that malignant transformation is preceded by randomly distributed driver mutations in cancer genes, which cause clonal expansions in phenotypically normal tissues. Although clonal expansions can remodel entire tissues, the mechanisms that result in only a small number of clones transforming into malignant tumours remain unknown. Here we develop an in vivo single-cell CRISPR strategy to systematically investigate tissue-wide clonal dynamics of the 150 most frequently mutated squamous cell carcinoma genes.

View Article and Find Full Text PDF
Article Synopsis
  • Screening for gene mutations in melanoma has become standard practice, with identified mutations impacting prognosis in metastatic uveal melanoma, while their significance in non-uveal melanoma is still unclear.
  • A study analyzing 2,650 melanoma cases found mutations in 129 samples, highlighting differences in the prevalence and types of mutations between uveal and non-uveal melanomas.
  • Unlike uveal melanomas, where mutations are linked to worse outcomes, mutations in non-uveal melanomas are mostly seen as "passenger mutations" with little impact on prognosis or treatment effectiveness.
View Article and Find Full Text PDF

Bacteria use CRISPR Cas systems to defend against invading foreign nucleic acids, e.g., phage genomes, plasmids or mobile genetic elements.

View Article and Find Full Text PDF

Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots.

View Article and Find Full Text PDF