Biology subjects

Goode, D. L.

Publications and source records attributed to Goode, D. L..

5 recordsLinked to original sources

bioRxiv2024

Defining focal neuroendocrine differentiation as a transcriptionally distinct form of prostate cancer pathology characterized by the expression of androgen receptors

BackgroundMen with neuroendocrine prostate cancer (NEPC) have a poor prognosis. NEPC is commonly diagnosed by immunohistochemical markers (CHGA, SYP and NCAM1) and genomic features (mutations in RB1, PTEN, TP53). But by pathology, NEPC tumours are variable, leading to a classification of NE subtypes such as small cell and large cell neuroendocrine carcinomas, focal neuroendocrine differentiation (Focal NED), and Amphicrine. We postulated the diversity observed in NEPC pathologies might arise from differences in transcriptional profiles and the aim of this study is to utilize single-cell RNA sequencing to define the transcriptional differences between NEPC subtype pathologies. MethodsGene expression profiles were obtained for 18,632 individual tumour cells from 9 patient-derived xenograft (PDX) models representing five distinct neuroendocrine pathologies of prostate cancer. Integration and clustering of cell-level data demarked transcriptionally distinct sub-populations of cells. Differential gene expression, gene set enrichment and transcriptional factor regulon analysis identified expression signatures unique to specific neuroendocrine pathologies. Copy-number estimated from expression data revealed the clonal structure of PDXs with mixed adenocarcinoma and neuroendocrine pathologies. ResultsSignificant differences were observed in the transcriptional profiles of NEPC pathology subtypes. Focal NED cells maintain AR signaling, similar to the amphicrine subtype but different from small and large cell carcinomas. Cellular sub-populations enriched for expression of KRAS, IL2-STAT5 and TNF-signaling genes were found in focal NED and amphicrine pathologies, but not in small or large cell carcinomas. In contrast, sub-populations enriched for the YAP, Myc and E2F pathways were detected in small cell, large cell and amphicrine tumours, but not in focal NED cells. Each pathology showed unique patterns of master regulator activity as well, further implicating focal NED as a transcriptionally distinct entity. Based on copy number alterations within PDXs of mixed pathology, focal NED cells showed little clonal divergence from neighboring adenocarcinoma cells, whereas cells with small cell neuroendocrine pathology were clonally distinct. ConclusionsNeuroendocrine prostate cancer subtypes can be identified by pathology and our study shows that transcriptional features identified by single-cell RNA-sequencing also distinguish neuroendocrine subtypes pathologies from each other. In particular, our data redefine focal neuroendocrine differentiation as a pathology expressing androgen receptors (AR), exhibiting its distinctive composition of transcriptionally unique sub-populations. These findings advocate for differences in the treatment of NEPC tumors, particularly those displaying focal NED.

cancer biology↗

bioRxiv2023

Disruption of metazoan gene regulatory networks in cancer alters the balance of co-expression between genes of unicellular and multicellular origins

Metazoans inherited genes from unicellular ancestors that perform essential biological processes such as cell division, metabolism and protein translation. Functioning multicellularity requires careful control and coordination of these unicellular genes to maintain tissue integrity and homeostasis. Gene regulatory networks (GRNs) formed during metazoan evolution to regulate conserved biological processes are frequently altered in cancer, resulting in over-expression of unicellular genes. We propose an imbalance in co-expression of unicellular (UC) and multicellular (MC) genes is a driving force in cancer. To investigate, we combined gene co-expression analysis to infer changes to GRNs in cancer with protein sequence conservation data to distinguish genes with UC and MC origins. Co-expression networks created using RNA sequencing data from 31 tumour types and normal tissue samples were divided into modules enriched for UC genes, MC genes or a mix of both (Mixed UC-MC modules). The greatest differences between tumour and normal tissue co-expression networks occurred within Mixed UC-MC modules. In particular, MC and UC genes not commonly co-expressed in normal tissues formed distinct co-expression modules seen only in tumours. The degree of rewiring of genes within Mixed UC-MC modules increased with both tumour grade and stage. Mixed UC-MC modules were enriched for somatic mutations in cancer genes, particularly copy-number amplifications, suggesting an important driver of the rewiring observed in tumours are copy-number changes. Overall, our study shows the greatest changes to gene co-expression patterns during tumour progression occur between genes of MC and UC origins, implicating the breakdown and rewiring of metazoan gene regulatory networks in cancer development and progression. Author summaryMulticellular organism cells follow certain rules that control and coordinate their growth and behavior. This happens because gene regulatory networks formed during the evolution of multicellularity to control the activity of genes inherited from unicellular ancestors. Cancer cells disobey these rules, growing and dividing in a competitive fashion analogous to that of colonial unicellular organisms. Here, we test the hypothesis that breakdown of gene regulatory networks enforcing multicellularity drives cancer progression by investigating 31 tumour types. Based on sequence similarity, genes were categorized as having origins in either unicellular or multicellular species. We found that the balance of expression unicellular and multicellular genes changes dramatically in cancer. Genes expressed together in normal tissues stop being co-expressed in tumors, while unicellular and multicellular genes that would not normally be expressed together in normal tissues become highly co-expressed. This phenomenon is more pronounced in cancers at more advanced stages, and sometimes occurs in association with gain or loss of parts of certain chromosomes. Our work indicates disruption and rewiring of gene regulatory networks that evolved to enforce multicellularity drives cancer progression by upsetting the carefully coordinated balance in the activity of unicellular and multicellular genes.

bioinformatics↗

bioRxiv2020

SPIAT: An R package for the Spatial Image Analysis of Cells in Tissues

Spatial technologies that query the location of cells in tissues at single-cell resolution are gaining popularity and are likely to become commonplace. The resulting data includes the X, Y coordinates of millions of cells, cell phenotypes and marker or gene expression levels. However, to date, the tools for the analysis of this data are largely underdeveloped, making us severely underpowered in our ability to extract quantifiable information. We have developed SPIAT (Spatial Image Analysis of Tissues), an R package with a suite of data processing, quality control, visualization, data handling and data analysis tools. SPIAT includes our novel algorithms for the identification of cell clusters, cell margins and cell gradients, the calculation of neighbourhood proportions, and algorithms for the prediction of cell phenotypes. SPIAT also includes speedy implementations of the calculation of cell distances and detection of cell communities. This version of SPIAT is directly compatible with Opal multiplex immunohistochemistry images analysed through the HALO and InForm analysis software, but its intuitive implementation allows use with a diversity of platforms. We expect SPIAT to become a user-friendly and speedy go-to package for the spatial analysis of cells in tissues. SPIAT is available on Github: https://github.com/cancer-evolution/SPIAT

bioinformatics↗

bioRxiv2019

Reprogrammed mRNA translation drives metabolic response to therapeutic targeting of ribosome biogenesis

Elevated ribosome biogenesis in oncogene-driven cancers is commonly targeted by DNA-damaging cytotoxic drugs. Our first-in-human trial of CX-5461, a novel, less genotoxic agent that specifically inhibits ribosome biogenesis via suppression of RNA Polymerase I (Pol I) transcription, revealed single agent efficacy in refractory blood cancers. Despite this clinical response, patients were not cured. In parallel, we demonstrated a marked improvement in the in vivo efficacy of CX-5461 in combination with PI3K/AKT/mTORC1 pathway inhibitors. Here we show that this improved efficacy is associated with specific suppression of translation of mRNAs encoding regulators of cellular metabolism. Importantly, acquired resistance to this co-treatment is driven by translational re-wiring that results in dysregulated cellular metabolism and induction of a cAMP-dependent pathway critical for the survival of blood cancers including lymphoma and acute myeloid leukemia. Our studies identify the molecular mechanisms underpinning the response of blood cancers to selective ribosome biogenesis inhibitors and identify metabolic vulnerabilities that will facilitate the rational design of more effective regimens for Pol I-directed therapies.

cancer biology↗

bioRxiv2018

Somatic mutations in early metazoan genes disrupt regulatory links between unicellular and multicellular genes in cancer

Extensive transcriptional alterations are observed in cancer, many of which activate core biological processes established in unicellular organisms or suppress differentiation pathways formed in metazoans. Through rigorous, integrative analysis of genomics data from a range of solid tumours, we show many transcriptional changes in tumours are tied to mutations disrupting regulatory interactions between unicellular and multicellular genes within human gene regulatory networks (GRNs). Recurrent point mutations were enriched in regulator genes linking unicellular and multicellular subnetworks, while copy-number alterations affected downstream target genes in distinctly unicellular and multicellular regions of the GRN. Our results depict drivers of tumourigenesis as genes that created key regulatory links during the evolution of early multicellular life, whose dysfunction creates widespread dysregulation of primitive elements of the GRN. Several genes we identified as important in this process were associated with drug response, demonstrating the potential clinical value of our approach.

cancer biology↗