Malignant teratoid tumor of the thyroid gland: an aggressive primitive multiphenotypic malignancy showing organotypical elements and frequent DICER1 alterations—is the term “thyroblastoma” more appropriate?

Primary thyroid teratomas are exceedingly rare. Mature and immature variants recapitulate their gonadal counterparts (predilection for infants/children, triphasic germ layer differentiation, and favorable outcome). On the other hand, the so-called malignant teratomas affect predominantly adults and elderly, are highly aggressive, and, according to a few published cases, harbor DICER1 mutations. We describe three highly aggressive sporadic malignant teratoid thyroid tumors in 2 females (17 and 45 years) and one male (17 years). Histology showed triphasic neoplasms composed of solid nests of small primitive monomorphic cells embedded in a cellular stroma with primitive immature rhabdomyosarcoma-like (2) or pleomorphic sarcoma-like (1) phenotype. The third component was represented by TTF1+/PAX8+ primitive teratoid epithelial tubules reminiscent of primitive thyroid follicles and/or Wilms tumor, admixed with scattered respiratory- or enteric-type tubules, neuroepithelial rosettes, and fetal-type squamoid nests. Foci of cartilage were seen in two cases, but none contained mature organoid adult-type tissue or skin adnexa. SALL4 was expressed in the small cell (2) and stromal (1) component. Other germ cell markers were negative. Molecular testing revealed a known “hotspot” pathogenic DICER1 mutation in two cases. In addition, case 1 had a missense TP53 variant. This type of thyroid malignancy is distinct from genuine teratomas. The immunoprofile suggests primitive thyroid- or branchial cleft-like differentiation. Given that “blastoma” is a well-accepted terminology in the spectrum of DICER1-associated malignancies, the term “thyroblastoma” might be more convenient for these malignant teratoid tumors of the thyroid gland. Relationship of thyroblastoma to the DICER1 syndrome remains to be addressed.

Gatekeeper transcription factors regulate switch between lineage preservation and cell plasticity

SummaryReprogramming somatic cells to pluripotency by repressing lineage-instructive transcription factors (TFs) alone has not been pursued because lineage specification is thought to be regulated by transcriptional regulatory networks (TRNs) comprising of multiple TFs rather than by single pivotal “gatekeeper” TFs. Utilizing an intra-species somatic cell hybrid model, we identified Snai2 and Prrx1 as the most critical determinants of mesenchymal commitment in rat embryonic fibroblasts (REFs) and demonstrate that siRNA-mediated knockdown of either of these master regulators is adequate to convert REFs into functional adipocytes, chondrocytes or osteocytes without requiring exogenous TFs or small molecule cocktails. Furthermore, knockdown of Snai2 alone proved sufficient to transform REFs to dedifferentiated pluripotent stem-like cells (dPSCs) that formed embryoid bodies capable of triple germ-layer differentiation. These findings suggest that inhibition of a single gatekeeper TF in a lineage committed cell is adequate for acquisition of cell plasticity and reprogramming without requiring permanent genetic modification.Graphical AbstractSchematic diagram depicting transdifferentiation of REFs into adipocytes, osteocytes, chondrocytes and dedifferentiation into MSCs on individual treatment with siSnai2 or siPrrx1. dPSCs were generated only in the siSnai2 group.

Visualizing Structure and Transitions for Biological Data Exploration

With the advent of high-throughput technologies measuring high-dimensional biological data, there is a pressing need for visualization tools that reveal the structure and emergent patterns of data in an intuitive form. We present PHATE, a visualization method that captures both local and global nonlinear structure in data by an information-geometric distance between datapoints. We perform extensive comparison between PHATE and other tools on a variety of artificial and biological datasets, and find that it consistently preserves a range of patterns in data including continual progressions, branches, and clusters. We define a manifold preservation metric DEMaP to show that PHATE produces quantitatively better denoised embeddings than existing visualization methods. We show that PHATE is able to gain unique insight from a newly generated scRNA-seq dataset of human germ layer differentiation. Here, PHATE reveals a dynamic picture of the main developmental branches in unparalleled detail, including the identification of three novel subpopulations. Finally, we show that PHATE is applicable to a wide variety of datatypes including mass cytometry, single-cell RNA-sequencing, Hi-C, and gut microbiome data, where it can generate interpretable insights into the underlying systems.