Genomic–transcriptomic evolution in lung cancer and metastasis

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic–transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary–metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis

Exposure assessment of heavy metals pollution enriched in core sediment samples of river Nile, Aswan, Egypt

The river Nile is a dominating physical feature of the north- eastern part of the African continent, covering areas exhibiting varieties and contrasts in topography, climate vegetation and people. So, in this study, we estimated the contamination of the Nile sediment with some major and trace heavy metals in core samples which can cause some undesirable health effects. Concentrations of all elements shows that the maximum enrichment is found in the top subsamples, while the most elements shows low contents in the lower layer reflecting the impact of human activity on the sediment contents. Different normalizing methods were used, i.e. geoaccumulation (Igeo) and enrichment factor (EF), for the influence of the natural variability in sediment mineralogy and to assess whether the concentrations observed in surface sediment represent background or contaminated levels. The study has also shown the importance of different sediment characteristics in spatial distribution of heavy metals in the sediments of river Nile. To protect the ecological system of river Nile watershed, industrial mining and agricultural activities along river stream should to be strictly regulated