Biology subjects

Ansari-Pour, N.

Publications and source records attributed to Ansari-Pour, N..

7 recordsLinked to original sources

bioRxiv2026

Sequential acquisition of 1p31.1-p12 LOH and 1q Gain is a common double-hit event in relapsed/refractory myeloma

Therapy-driven genomic changes in multiple myeloma (MM) remain poorly defined. We analyzed whole-genome sequencing (WGS) data from relapsed/refractory MM (rrMM, N=386) and identified regional 1p31.1-p12 (hereafter 1pCEN, a region proximal to the centromere) loss-of-heterozygosity (LOH) as the only enriched aberration showing strong therapy-associated clonal selection (clonal timing rank fold-change = 3.7, P<2.2x10-16). This event showed enriched co-occurrence with 1qGain (OR = 2.3 (1.5-3.8), P=2x10-4) forming a recurrent "double-hit" in rrMM. To validate the clonal selection process, we examined three longitudinal cohorts (180 patients, 390 samples) and confirmed clonal expansion of 1pCEN and consistent prevalence of the 1pCEN+1q double-hit (20-24%). Survival analyses demonstrated significantly reduced progression-free survival in rrMM patients with this double-hit compared with those without. Comparison with a large newly diagnosed MM (ndMM) cohort confirmed previously-described 1p32 LOH is the prognostic locus at baseline, whereas 1pCEN is therapy-selected and largely independent of the 1p32 locus. Thus, 1pCEN+1q represents a recurrent double-hit event that clonally emerges in rrMM, conferring selective advantage under drug exposure and is distinct from the ndMM high-risk markers defined by current consensus guidelines. These findings nominate 1pCEN as a new genomic biomarker in rrMM and 1pCEN+1q may help patient stratification for therapeutic monitoring. Key PointsA therapy-driven common genomic double-hit (1p31.1-p12 LOH with 1q gain) clonally emerges in relapsed/refractory myeloma.

cancer biology↗

bioRxiv2022

Clonal diversification and histogenesis of malignant germ cell tumours

Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells. They are uniquely able to recapitulate embryonic and extraembryonic tissues, which carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the relationship of histogenesis and clonal diversification in GCTs by analysing the genome and transcriptome of 547 microdissected histological units. We found that the extensive diversification of tissues and genetic subclones were not correlated. However, we identified unifying features including the retention of fetal developmental transcripts across tissues, expression changes on chromosome 12p, and a conserved somatic evolutionary sequence of whole genome duplication followed by clonal diversification. Whilst this pattern was preserved across all GCTs, the developmental timing of the duplication varied between prepubertal and postpubertal cases. In addition, tumours of younger children exhibited distinct substitution signatures, including a novel one, which may lend themselves as potential biomarkers for risk stratification. Our findings portray the extensive diversification of GCT tissues and genetic subclones as randomly distributed, whilst identifying overarching tissue and tumour transcriptional and genomic features.

cancer biology↗

bioRxiv2021

A simple and direct method to define clonal selection in somatic mosaicism

As DNA variants accumulate in somatic stem cells, become selected or evolve neutrally, they may ultimately alter tissue function. When, and how, selection occurs in homeostatic tissues is incompletely understood. Here, we introduce SCIFER, a scalable method that identifies selection in an individual tissue, without requiring knowledge of the underlying driver event. Moreover, SCIFER infers the self-renewal and mutation dynamics of the tissues stem cells, and, if selection is present, the size and growth rate of the largest selected clone. We benchmark SCIFER with published data and then probe bone marrow of 22 non-leukemic individuals for clonal hematopoiesis (CH), identifying CH with known and unknown driver events. Unexpectedly, we find accelerated division of all stem cells in CH, compared to age-matched non-CH individuals, suggesting that the bone marrow environment alters stem cell dynamics in individuals with CH. SCIFER is broadly applicable to renewing somatic tissues to detect and quantify selection.

cancer biology↗

bioRxiv2020

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes

Black women of African ancestry experience more aggressive breast cancer with higher mortality rates than White women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast tumors, with RNA-seq in a subset, from indigenous African patients in Nigeria in comparison to The Cancer Genome Atlas (n=76) revealed a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations and a 10.5-year younger age at diagnosis. We also found evidence for non-coding mutations in two novel drivers (ZNF217 and SYPL1) and a novel INDEL signature strongly associated with African ancestry proportion. This comprehensive analysis of an understudied population underscores the need to incorporate diversity of genomes as a key parameter in fundamental research with potential to tailor clinical intervention and promote equity in precision oncology care.

genomics↗

bioRxiv2019

Multi-site clonality analyses uncovers pervasive subclonal heterogeneity and branching evolution across melanoma metastases

Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naive patient and by leveraging the analytical power of multi-sample analyses, we reveal that metastatic cells may depart the primary tumour very early in the disease course and follow a branched pattern of evolution. Truncal UV-induced mutations that often swamp downstream analyses of heterogeneity, were found to be replaced by APOBEC-associated mutations in the branches of the evolutionary tree. Multi-sample analyses from a further 7 patients confirmed that branched evolution was pervasive, representing an important mode of melanoma dissemination. Our analyses illustrate that combining cancer cell fraction estimates across multiple metastases provides higher resolution phylogenetic reconstructions relative to single sample analyses and highlights the limitations of accurately inferring inter-tumoural heterogeneity from a single biopsy.

genomics↗

bioRxiv2019

Do signaling networks and whole-transcriptome gene expression profiles orchestrate the same symphony?

Studying relationships among gene-products by gene expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed correlation of transcript and protein expression levels. All these efforts partook in the current understanding of signaling network models and expanded the signaling databases. In fact, due to the unavailability or high-cost of the experiments, most of the studies do not usually look for direct interactions, and some parts of these networks are contradictory. Besides, it is now a standard step to accomplish enrichment analysis on biological annotations, to make claims about the potentially implicated biological pathways in any perturbation. Explicitly, upon identifying differentially expressed genes, they are spontaneously presumed the corresponding dysregulated pathways. Then, molecular mechanistic insights are proposed for disease etiology and drug discovery based on statistically enriched biological processes. In this study, using four common and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level and the causal relationships among the gene pairs. We illustrated that the signaling network was not more consistent or coherent with the recorded expression profile compared to the random relationships. Finally, we provided the pieces of evidence and concluded that gene-product expression data, especially at the transcript level, are not reliable or at least insufficient to infer causal biological relationships among genes and in turn, describe cellular behavior.

systems biology↗

bioRxiv2017

The genetic legacy of Zoroastrianism in Iran and India: Insights into population structure, gene flow and selection.

Zoroastrianism is one of the oldest extant religions in the world, originating in Persia (present-day Iran) during the second millennium BCE. Historical records indicate that migrants from Persia brought Zoroastrianism to India, but there is debate over the timing of these migrations. Here we present novel genome-wide autosomal, Y-chromosome and mitochondrial data from Iranian and Indian Zoroastrians and neighbouring modern-day Indian and Iranian populations to conduct the first genome-wide genetic analysis in these groups. Using powerful haplotype-based techniques, we show that Zoroastrians in Iran and India show increased genetic homogeneity relative to other sampled groups in their respective countries, consistent with their current practices of endogamy. Despite this, we show that Indian Zoroastrians (Parsis) intermixed with local groups sometime after their arrival in India, dating this mixture to 690-1390 CE and providing strong evidence that the migrating group was largely comprised of Zoroastrian males. By exploiting the rich information in DNA from ancient human remains, we also highlight admixture in the ancestors of Iranian Zoroastrians dated to 570 BCE-746 CE, older than admixture seen in any other sampled Iranian group, consistent with a long-standing isolation of Zoroastrians from outside groups. Finally, we report genomic regions showing signatures of positive selection in present-day Zoroastrians that might correlate to the prevalence of particular diseases amongst these communities.

genomics↗