An integrated single-cell analysis of human adrenal cortex development

The adrenal glands synthesize and release essential steroid hormones such as cortisol and aldosterone, but many aspects of human adrenal gland development are not well understood. Here, we combined single-cell and bulk RNA sequencing, spatial transcriptomics, IHC, and micro-focus computed tomography to investigate key aspects of adrenal development in the first 20 weeks of gestation. We demonstrate rapid adrenal growth and vascularization, with more cell division in the outer definitive zone (DZ). Steroidogenic pathways favored androgen synthesis in the central fetal zone, but DZ capacity to synthesize cortisol and aldosterone developed with time. Core transcriptional regulators were identified, with localized expression of HOPX (also known as Hop homeobox/homeobox-only protein) in the DZ. Potential ligand-receptor interactions between mesenchyme and adrenal cortex were seen (e.g., RSPO3/LGR4). Growth-promoting imprinted genes were enriched in the developing cortex (e.g., IGF2, PEG3). These findings reveal aspects of human adrenal development and have clinical implications for understanding primary adrenal insufficiency and related postnatal adrenal disorders, such as adrenal tumor development, steroid disorders, and neonatal stress

Single cell derived mRNA signals across human kidney tumors.

Funder: Department of HealthTumor cells may share some patterns of gene expression with their cell of origin, providing clues into the differentiation state and origin of cancer. Here, we study the differentiation state and cellular origin of 1300 childhood and adult kidney tumors. Using single cell mRNA reference maps of normal tissues, we quantify reference "cellular signals" in each tumor. Quantifying global differentiation, we find that childhood tumors exhibit fetal cellular signals, replacing the presumption of "fetalness" with a quantitative measure of immaturity. By contrast, in adult cancers our assessment refutes the suggestion of dedifferentiation towards a fetal state in most cases. We find an intimate connection between developmental mesenchymal populations and childhood renal tumors. We demonstrate the diagnostic potential of our approach with a case study of a cryptic renal tumor. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer

Normal cell signals in human cancer transcriptomes

Cancer cells arise from normal cells, and may retain transcriptional patterns present in the cell of origin. Recent advances in single-cell transcriptomics have allowed us to profile both normal and cancer cells at a single cell resolution, enabling direct comparisons between the two. Such comparisons can reveal information about which cells cancers originate from, transcriptional programs that underpin carcinogenesis, and differentiation states in cancer. The work presented in this thesis aims to study normal cell signals in human cancer, utilising single-cell transcriptomics. Chapter 1 provides an overview of transcriptomics as a whole, as well as in the context of cancer, with a focus on single-cell transcriptomics. In Chapter 2, I construct a single-cell normal reference of the fetal adrenal gland, and explore the development of the fetal adrenal medulla, from which the childhood cancer, neuroblastoma, arises. I then compare that reference to neuroblastoma single-cell and bulk transcriptomes in chapter 3. This comparison reveals sympathoblasts as the normal correlate of neuroblastoma cancer cells, and allows identification of transcripts present in both neuroblastoma and fetal adrenal medulla, but not adult tissues, making these transcripts an attractive therapeutic target. Chapter 4 presents a comparison of fetal and adult references across three different organs (gut, lung and liver) to bulk and single-cell transcriptomes of adult cancers originating in these organs. This analysis assesses the contribution of fetal and adult cell type signals to cancer transcriptomes. Overall, my work delineates the transcriptional relationship between cancer and normal cells

Additional file 17: Figure S13. of The protein subunit of telomerase displays patterns of dynamic evolution and conservation across different metazoan taxa

TERT in Dugesiidae is alternatively spliced. Comparison of alternatively spliced (AS) variants in seven Dugesiidae species from the genera Schmidtea, Girardia and Dugesia. Structure of AS variants in S. mediterranea, S. lugubris, G. tigrina, D. japonica, D. ryukyuensis, D. benazzi and D. tahitientis. Full-length or wild-type TERT structure is shown at the top of each set of AS variants. Functional TERT domains (TRBD and RT) and positions of (putative) exons are indicated. Deletions (skipped exons) are denoted by triangles and insertions (retained introns or splice site mutations) are denoted by grey rectangles. ‘M’ abbreviations represent splice site mutations. Red triangles represent conserved alternatively spliced exons in all Dugesiidae species except S. mediterranea and D. tahitientis. Blue triangles represent conserved alternatively spliced exons in all Dugesiidae species except G. tigrina and D. japonica. Asterisks indicate stop codon positions caused by frame shift mutation or retained introns. The left margin shows TERT gene and AS variant names for each species and the right margin shows descriptive names of TERT AS sequences. Schematic diagrams on the far right illustrate the presence or absence of canonical motifs (QFP, T, 1, 2, A, B′, C, D and E) on TERT AS protein variants drawn to scale. (JPEG 1654 kb

Precise identification of cancer cells from allelic imbalances in single cell transcriptomes.

A fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data

Transcriptional signals of transformation in human cancer

Acknowledgements: Not applicable.Abstract Background As normal cells transform into cancers, their cell state changes, which may drive cancer cells into a stem-like or more primordial, foetal, or embryonic cell state. The transcriptomic profile of this final state may encode information about cancer’s origin and how cancers relate to their normal cell counterparts. Methods Here, we used single-cell atlases to study cancer transformation in transcriptional terms. We utilised bulk transcriptomes across a wide spectrum of adult and childhood cancers, using a previously established method to interrogate their relationship to normal cell states. We extend and validate these findings using single-cell cancer transcriptomes and organ-specific atlases of colorectal and liver cancer. Results Our bulk transcriptomic data reveals that adult cancers rarely return to an embryonic state, but that a foetal state is a near-universal feature of childhood cancers. This finding was confirmed with single-cell cancer transcriptomes. Conclusions Our findings provide a nuanced picture of transformation in human cancer, indicating cancer-specific rather than universal patterns of transformation pervade adult epithelial cancers. </jats:sec

Tumor to normal single-cell mRNA comparisons reveal a pan-neuroblastoma cancer cell

Neuroblastoma is a childhood cancer that resembles developmental stages of the neural crest. It is not established what developmental processes neuroblastoma cancer cells represent. Here, we sought to reveal the phenotype of neuroblastoma cancer cells by comparing cancer (n = 19,723) with normal fetal adrenal single-cell transcriptomes (n = 57,972). Our principal finding was that the neuroblastoma cancer cell resembled fetal sympathoblasts, but no other fetal adrenal cell type. The sympathoblastic state was a universal feature of neuroblastoma cells, transcending cell cluster diversity, individual patients, and clinical phenotypes. We substantiated our findings in 650 neuroblastoma bulk transcriptomes and by integrating canonical features of the neuroblastoma genome with transcriptional signals. Overall, our observations indicate that a pan-neuroblastoma cancer cell state exists, which may be attractive for novel immunotherapeutic and targeted avenues

Tumor to normal single-cell mRNA comparisons reveal a pan-neuroblastoma cancer cell

Neuroblastoma is a childhood cancer that resembles developmental stages of the neural crest. It is not established what developmental processes neuroblastoma cancer cells represent. Here, we sought to reveal the phenotype of neuroblastoma cancer cells by comparing cancer (n = 19,723) with normal fetal adrenal single-cell transcriptomes (n = 57,972). Our principal finding was that the neuroblastoma cancer cell resembled fetal sympathoblasts, but no other fetal adrenal cell type. The sympathoblastic state was a universal feature of neuroblastoma cells, transcending cell cluster diversity, individual patients, and clinical phenotypes. We substantiated our findings in 650 neuroblastoma bulk transcriptomes and by integrating canonical features of the neuroblastoma genome with transcriptional signals. Overall, our observations indicate that a pan-neuroblastoma cancer cell state exists, which may be attractive for novel immunotherapeutic and targeted avenues