Sarcomas are driven by diverse pathogenic mechanisms, including gene rearrangements in a subset of cases. Rare soft tissue sarcomas containing KMT2A fusions have recently been reported, characterized by a predilection for young adults, sclerosing epithelioid fibrosarcoma-like morphology, and an often aggressive course. Nonetheless, clinicopathologic and molecular descriptions of KMT2A-rearranged sarcomas remain limited. In this study, we identified by targeted next-generation RNA sequencing an index patient with KMT2A fusion-positive soft tissue sarcoma. In addition, we systematically searched for KMT2A structural variants in a comprehensive genomic profiling database of 14,680 sarcomas interrogated by targeted next-generation DNA and/or RNA sequencing. We characterized the clinicopathologic and molecular features of KMT2A fusion-positive sarcomas, including KMT2A breakpoints, rearrangement partners, and concurrent genetic alterations. Collectively, we identified a cohort of 34 sarcomas with KMT2A fusions (0.2%), and YAP1 was the predominant partner (n = 16 [47%]). Notably, a complex rearrangement with YAP1 consistent with YAP1–KMT2A–YAP1 fusion was detected in most cases, with preservation of KMT2A CxxC-binding domain in the YAP1–KMT2A–YAP1 fusion and concurrent deletions of corresponding exons in KMT2A. The tumors often affected younger adults (age 20–66 [median 40] years) and histologically showed variably monomorphic epithelioid-to-spindle shaped cells embedded in a dense collagenous stroma. Ultrastructural evidence of fibroblastic differentiation was noted in one tumor examined. Our cohort also included two sarcomas with VIM–KMT2A fusions, each harboring concurrent mutations in CTNNB1, SMARCB1, and ARID1A and characterized histologically by sheets of spindle-to-round blue cells. The remaining 16 KMT2A-rearranged sarcomas in our cohort exhibited diverse histologic subtypes, each with unique novel fusion partners. In summary, KMT2A-fusion-positive sarcomas most commonly exhibit sclerosing epithelioid fibrosarcoma-like morphology and complex YAP1–KMT2A–YAP1 fusions. Cases also include rare spindle-to-round cell sarcomas with VIM–KMT2A fusions and tumors of diverse histologic subtypes with unique KMT2A fusions to non-YAP1 non-VIM partners.

We use broadband coherent anti-Stokes Raman scattering (BCARS) microscopy to characterize lineage commitment of individual human mesenchymal stem cells cultured in adipogenic, osteogenic, and basal culture media. We treat hyperspectral images obtained by BCARS in two independent ways, obtaining robust metrics for differentiation. In one approach, pixel counts corresponding to functional markers, lipids, and minerals, are used to classify individual cells as belonging to one of the three lineage groups: adipocytes, osteoblasts, and undifferentiated stem cells. In the second approach, we use multivariate analysis of Raman spectra averaged exclusively over cytosol regions of individual cells to classify the cells into the same three groups, with consistent results. The exceptionally high speed of spectral imaging with BCARS allows us to chemically map a large number of cells with high spatial resolution, revealing not only the phenotype of individual cells, but also population heterogeneity in the degree of phenotype commitment.

Effective screening methodologies for cells are challenged by the divergent and heterogeneous nature of phenotypes inherent to stem cell cultures, particularly on engineered biomaterial surfaces. In this study, we showcase a high-content, confocal imaging-based methodology to parse single-cell phenotypes by quantifying organizational signatures of specific subcellular reporter proteins and applied this profiling approach to three human stem cell types (embryonic–human embryonic stem cell [hESC], induced pluripotent–induced pluripotent stem cell [iPSC], and mesenchymal–human mesenchymal stem cell [hMSC]). We demonstrate that this method could distinguish self-renewing subpopulations of hESCs and iPSCs from heterogeneous populations. This technique can also provide insights into how incremental changes in biomaterial properties, both physiochemical and mechanical, influence stem cell fates by parsing the organization of stem cell proteins. For example, hMSCs cultured on polymeric films with varying degrees of poly(ethylene glycol) to modulate osteogenic differentiation were parsed using high-content organization of the cytoskeletal protein F-actin. In addition, hMSCs cultured on a self-assembled monolayer platform featuring compositional gradients were screened and descriptors obtained to correlate substrate variations with adipogenic lineage commitment. Taken together, high-content imaging of structurally sensitive proteins can be used as a tool to identify stem cell phenotypes at the single-cell level across a diverse range of culture conditions and microenvironments.

Stem cell fates on biomaterials are influenced by the complex confluence of microenvironmental cues emanating from soluble growth factors, cell-to-cell contacts, and biomaterial properties. Cell-microenvironment interactions influence the cell fate by initiating a series of outside-in signaling events that traverse from the focal adhesions to the nucleus via the cytoskeleton and modulate the sub-nuclear protein organization and gene expression. Here, we report a novel imaging-based framework that highlights the spatial organization of sub-nuclear proteins, specifically the splicing factor SC-35 in the nucleoplasm, as an integrative marker to distinguish between minute differences of stem cell lineage pathways in response to stimulatory soluble factors, surface topologies, and microscale topographies. This framework involves the high resolution image acquisition of SC-35 domains and imaging-based feature extraction to obtain quantitative nuclear metrics in tandem with machine learning approaches to generate a predictive cell state classification model. The acquired SC-35 metrics led to > 90% correct classification of emergent human mesenchymal stem cell (hMSC) phenotypes in populations of hMSCs exposed for merely 3 days to basal, adipogenic, or osteogenic soluble cues, as well as varying levels of dexamethasone-induced alkaline phosphatase (ALP) expression. Early osteogenic cellular responses across a series of surface patterns, fibrous scaffolds, and micropillars were also detected and classified using this imaging-based methodology. Complex cell states resulting from inhibition of RhoGTPase, β-catenin, and FAK could be classified with > 90% sensitivity on the basis of differences in the SC-35 organizational metrics. This indicates that SC-35 organization is sensitively impacted by adhesion-related signaling molecules that regulate osteogenic differentiation. Our results show that diverse microenvironment cues affect different attributes of the SC-35 organizational metrics and lead to distinct emergent organizational patterns. Taken together, these studies demonstrate that the early organization of SC-35 domains could serve as a “fingerprint” of the intracellular mechanotransductive signaling that governs growth factor- and topography-responsive stem cell states.