Biology subjects

Moore, A. L.

Publications and source records attributed to Moore, A. L..

4 recordsLinked to original sources

bioRxiv2021

A statistical test for clonal exclusivity in tumour evolution

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Pairs of mutations that are overrepresented in a clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical test, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our test for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 6 clonally exclusive and 2 clonally co-occurring gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

cancer biology↗

bioRxiv2021

Dynamic changes of genomic and transcriptomic tumor diversity during melanoma progression

Metastatic melanoma is an aggressive disease that is notoriously difficult to treat. Here, we used a BRAFV600E-driven mouse model to study melanoma progression and metastasis in the absence of extrinsic mutagenic factors such as UV radiation. The tumors were grown for different time periods in seven different mice such that disease progression was tracked over time. We sequenced the whole exome and whole transcriptome of 16 melanoma samples from these mice. The timed samples revealed that many genes are increasingly upregulated during progression, such as genes involved in extracellular matrix organization, and Vegfc, a factor that induces lymphatic vessel growth and metastases to lymph nodes, which was identified as an important signaling hub in our analysis. The Vegfc gene interaction network highlighted multiple genes from the MAPK pathway that are increasingly deregulated during tumor evolution. The genomic diversity of primary and metastatic tumors showed an increase over time. Additionally, our integrative multi-omics analysis adds further evidence that Rock1 is a crucial player driving metastasis formation, and may be upregulated due to mutations in the PI3K/AKT pathway. In summary, our study contributes towards an improved understanding of melanoma which may eventually lead to improved treatment strategies.

cancer biology↗

bioRxiv2020

Proteogenomic heterogeneity of localized human prostate cancer progression

BackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

systems biology↗

bioRxiv2018

Intra-tumor heterogeneity and clonal exclusivity in renal cell carcinoma

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction, and might explain clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

cancer biology↗