Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance.

The power of language to modify the reader's perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be "almost significant." The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being "marginally significant" (in 7,735 RCTs), "all but significant" (7,015), "a nonsignificant trend" (3,442), "failed to reach statistical significance" (2,578), and "a strong trend" (1,700). The strongest evidence for an increased temporal prevalence was found for "a numerical trend," "a positive trend," "an increasing trend," and "nominally significant." In contrast, the phrases "all but significant," "approaches statistical significance," "did not quite reach statistical significance," "difference was apparent," "failed to reach statistical significance," and "not quite significant" decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

Psammomatoid Ossifying Fibroma Is Defined by SATB2 Rearrangement.

Psammomatoid ossifying fibroma (PsOF), also known as juvenile PsOF, is a benign fibro-osseous neoplasm predominantly affecting the extragnathic bones, particularly the frontal and ethmoid bones, with a preference for adolescents and young adults. The clinical and morphologic features of PsOF may overlap with those of other fibro-osseous lesions, and additional molecular markers would help increase diagnostic accuracy. Because identical chromosomal breakpoints at bands Xq26 and 2q33 have been described in 3 cases of PsOF located in the orbita, we aimed to identify the exact genes involved in these chromosomal breakpoints and determine their frequency in PsOF using transcriptome sequencing and fluorescence in situ hybridization (FISH). We performed whole RNA transcriptome sequencing on frozen tissue in 2 PsOF index cases and identified a fusion transcript involving SATB2, located on chromosome 2q33.1, and AL513487.1, located on chromosome Xq26, in one of the cases. The fusion was validated using reverse transcription (RT)-PCR and SATB2 FISH. The fusion lead to a truncated protein product losing most of the functional domains. Subsequently, we analyzed an additional 24 juvenile PsOFs, 8 juvenile trabecular ossifying fibromas (JTOFs), and 11 cemento-ossifying fibromas (COFs) for SATB2 using FISH and found evidence of SATB2 gene rearrangements in 58% (7 of 12) of the evaluable PsOF cases but not in any of the evaluable JTOF (n = 7) and COF (n = 7) cases. A combination of SATB2 immunofluorescence and a 2-color SATB2 FISH in our index case revealed that most tumor cells harboring the rearrangement lacked SATB2 expression. Using immunohistochemistry, 65% of PsOF, 100% of JTOF, and 100% of COF cases showed moderate or strong staining for SATB2. In these cases, we observed a mosaic pattern of expression with >25% of the spindle cells in between the bone matrix, with osteoblasts and osteocytes being positive for SATB2. Interestingly, 35% (8 of 23) of PsOFs, in contrast to JTOFs and COFs, showed SATB2 expression in <5% of cells. To our knowledge, this is the first report that shows the involvement of SATB2 in the development of a neoplastic lesion. In this study, we have showed that SATB2 rearrangement is a recurrent molecular alteration that appears to be highly specific for PsOF. Our findings support that PsOF is not only morphologically and clinically but also genetically distinct from JTOF and COF.

Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas.

Based on morphology it is often challenging to distinguish between the many different soft tissue sarcoma subtypes. Moreover, outcome of disease is highly variable even between patients with the same disease. Machine learning on transcriptome sequencing data could be a valuable new tool to understand differences between and within entities. Here we used machine learning analysis to identify novel diagnostic and prognostic markers and therapeutic targets for soft tissue sarcomas. Gene expression data was used from the Cancer Genome Atlas, the Genotype-Tissue Expression project and the French Sarcoma Group. We identified three groups of tumors that overlap in their molecular profiles as seen with unsupervised t-Distributed Stochastic Neighbor Embedding clustering and a deep neural network. The three groups corresponded to subtypes that are morphologically overlapping. Using a random forest algorithm, we identified novel diagnostic markers for soft tissue sarcoma that distinguished between synovial sarcoma and MPNST, and that we validated using qRT-PCR in an independent series. Next, we identified prognostic genes that are strong predictors of disease outcome when used in a k-nearest neighbor algorithm. The prognostic genes were further validated in expression data from the French Sarcoma Group. One of these, HMMR, was validated in an independent series of leiomyosarcomas using immunohistochemistry on tissue micro array as a prognostic gene for disease-free interval. Furthermore, reconstruction of regulatory networks combined with data from the Connectivity Map showed, amongst others, that HDAC inhibitors could be a potential effective therapy for multiple soft tissue sarcoma subtypes. A viability assay with two HDAC inhibitors confirmed that both leiomyosarcoma and synovial sarcoma are sensitive to HDAC inhibition. In this study we identified novel diagnostic markers, prognostic markers and therapeutic leads from multiple soft tissue sarcoma gene expression datasets. Thus, machine learning algorithms are powerful new tools to improve our understanding of rare tumor entities.

Functional analyses of a human vascular tumor FOS variant identify a novel degradation mechanism and a link to tumorigenesis.

Epithelioid hemangioma is a locally aggressive vascular neoplasm, found in bones and soft tissue, whose cause is currently unknown, but may involve oncogene activation. FOS is one of the earliest viral oncogenes to be characterized, and normal cellular FOS forms part of the activator protein 1 (AP-1) transcription factor complex, which plays a pivotal role in cell growth, differentiation, and survival as well as the DNA damage response. Despite this, a causal link between aberrant FOS function and naturally occurring tumors has not yet been established. Here, we describe a thorough molecular and biochemical analysis of a mutant FOS protein we identified in these vascular tumors. The mutant protein lacks a highly conserved helix consisting of the C-terminal four amino acids of FOS, which we show is indispensable for fast, ubiquitin-independent FOS degradation via the 20S proteasome. Our work reveals that FOS stimulates endothelial sprouting and that perturbation of normal FOS degradation could account for the abnormal vessel growth typical of epithelioid hemangioma. To the best of our knowledge, this is the first functional characterization of mutant FOS proteins found in tumors.

PyPanda: a Python package for gene regulatory network reconstruction.

PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of 'omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. AVAILABILITY AND IMPLEMENTATION: The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda CONTACT: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl.

Fusion events lead to truncation of FOS in epithelioid hemangioma of bone.

Epithelioid hemangioma of bone is a locally aggressive vascular neoplasm. It can be challenging to diagnose because of the wide histological spectrum, which can make it difficult to differentiate from other vascular neoplasms such as epithelioid hemangioendothelioma or epithelioid angiosarcoma. COBRA-FISH karyotyping identified a balanced t(3;14) translocation. Transcriptome sequencing of the index case and two other epithelioid hemangiomas revealed a recurrent translocation breakpoint involving the FOS gene, which was fused to different partners in all three cases. The break was observed in exon 4 of the FOS gene and the fusion event led to the introduction of a stop codon. In all instances, the truncation of the FOS gene would result in the loss of the transactivation domain (TAD). Using FISH probes we found a break in the FOS gene in two additional cases, in none of these cases a recurrent fusion partner could be identified. In total, FOS was split in 5/7 evaluable samples. We did not observe point mutations leading to early stop codons in any of the 10 cases where RNA was available. Detection of FOS rearrangement may be a useful diagnostic tool to assist in the often difficult differential diagnosis of vascular tumors of bone. Our data suggest that the translocation causes truncation of the FOS protein, with loss of the TAD, which is thereby a novel mechanism involved in tumorigenesis.

Single Cell Expression Analysis of Ductal Carcinoma in Situ Identifies Complex Genotypic-Phenotypic Relationships Altering Epithelial Composition.

To identify mechanisms underlying the growth of ductal carcinoma in situ (DCIS) and properties that lead to progression to invasive cancer, we performed single-cell RNA-sequencing (scRNA-seq) on DCIS lesions and matched synchronous normal breast tissue. Using inferred copy number variations (CNV), we identified neoplastic epithelial cells from the clinical specimens which contained a mixture of DCIS and normal ducts. Phylogenetic analysis based on the CNVs demonstrated intratumoral clonal heterogeneity was associated with significant gene expression differences. We also classified epithelial cells into mammary cell states and found that individual genetic clones contained a mixture of cell states suggesting an ongoing pattern of differentiation after neoplastic transformation. Cell state proportions were significantly different based on estrogen receptor (ER) expression with ER-DCIS more closely resembling the distribution in the normal breast, particularly with respect to cells with basal characteristics. Using deconvolution from bulk RNA-seq in archival DCIS specimens, we show that specific alterations in cell state proportions are associated with progression to invasive cancer. Loss of an intact basement membrane (BM) is the functional definition of invasive breast cancer (IBC) and scRNA-seq data demonstrated that ongoing transcription of key BM genes occurs in specific subsets of epithelial cell states. Examining BM in archival microinvasive breast cancers and an in vitro model of invasion, we found that passive loss of BM gene expression due to cell state proportion alterations is associated with loss of the structural integrity of the duct leading to an invasive phenotype. Our analyses provide detailed insight into DCIS biology. SIGNIFICANCE: Single cell analysis reveals that preinvasive breast cancer is comprised of multiple genetic clones and there is substantial phenotypic diversity both within and between these clones. Ductal carcinoma in situ (DCIS) of the breast is a non-invasive condition commonly identified through mammographic screening. A primary diagnosis of DCIS carries little mortality risk on its own, but its presence is a risk factor for subsequent clonally related invasive breast cancer (IBC) (1-5).

Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancer.

Tumor-associated macrophages are transcriptionally heterogeneous, but the spatial distribution and cell interactions that shape macrophage tissue roles remain poorly characterized. Here, we spatially resolve five distinct human macrophage populations in normal and malignant human breast and colon tissue and reveal their cellular associations. This spatial map reveals that distinct macrophage populations reside in spatially segregated micro-environmental niches with conserved cellular compositions that are repeated across healthy and diseased tissue. We show that IL4I1+ macrophages phagocytose dying cells in areas with high cell turnover and predict good outcome in colon cancer. In contrast, SPP1+ macrophages are enriched in hypoxic and necrotic tumor regions and portend worse outcome in colon cancer. A subset of FOLR2+ macrophages is embedded in plasma cell niches. NLRP3+ macrophages co-localize with neutrophils and activate an inflammasome in tumors. Our findings indicate that a limited number of unique human macrophage niches function as fundamental building blocks in tissue. Significance: This work broadens our understanding of the distinct roles different macrophage populations may exert on cancer growth and reveals potential predictive markers and macrophage population-specific therapy targets.

Sarcoma microenvironment cell states and ecosystems are associated with prognosis and predict response to immunotherapy.

Characterization of the diverse malignant and stromal cell states that make up soft tissue sarcomas and their correlation with patient outcomes has proven difficult using fixed clinical specimens. Here, we employed EcoTyper, a machine-learning framework, to identify the fundamental cell states and cellular ecosystems that make up sarcomas on a large scale using bulk transcriptomes with clinical annotations. We identified and validated 23 sarcoma-specific, transcriptionally defined cell states, many of which were highly prognostic of patient outcomes across independent datasets. We discovered three conserved cellular communities or ecotypes associated with underlying genomic alterations and distinct clinical outcomes. We show that one ecotype defined by tumor-associated macrophages and epithelial-like malignant cells predicts response to immune-checkpoint inhibition but not chemotherapy and validate our findings in an independent cohort. Our results may enable identification of patients with soft tissue sarcomas who could benefit from immunotherapy and help develop new therapeutic strategies.

The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks.

Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods.

Identification of stable housekeeping genes for induced pluripotent stem cells and -derived endothelial cells for drug testing.

There are no validated housekeeping genes in induced pluripotent stem cells (iPSC) and derived endothelial iPSC (iPSC-EC). Thus a comparison of gene expression levels is less reliable, especially during drug treatments. Here, we utilized transcriptome sequencing data of iPSC and iPSC-EC with or without CRISPR-Cas9 induced translocation to identify a panel of 15 candidate housekeeping genes. For comparison, five commonly used housekeeping genes (B2M, GAPDH, GUSB, HMBS, and HPRT1) were included in the study. The panel of 20 candidate genes were investigated for their stability as reference genes. This panel was analyzed and ranked based on stability using five algorithms, delta-Ct, bestkeeper, geNorm, Normfinder, and Reffinder. Based on the comprehensive ranking of Reffinder, the stability of the top two genes-RPL36AL and TMBIM6, and the bottom two genes-UBA1 and B2M, were further studied in iPSC-EC with and without genetic manipulation, and after treatment with telatinib. Using quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR), it was shown that gene expression of the top two housekeeping genes, RPL36AL and TMBIM6, remained stable during drug treatment. We identified a panel of housekeeping genes that could be utilized in various conditions using iPSC and iPSC-derived endothelial cells as well as genetically modified iPSC for drug treatment.

Interactions in CSF1-Driven Tenosynovial Giant Cell Tumors.

PURPOSE: A major component of cells in tenosynovial giant cell tumor (TGCT) consists of bystander macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. An autocrine loop was postulated where the neoplastic cells would be stimulated through CSF1R expressed on their surface. Here, we use single-cell RNA sequencing (scRNA-seq) to investigate cellular interactions in TGCT. EXPERIMENTAL DESIGN: A total of 18,788 single cells from three TGCT and two giant cell tumor of bone (GCTB) samples underwent scRNA-seq. The three TGCTs were additionally analyzed using long-read RNA sequencing. Immunofluorescence and IHC for a range of markers were used to validate and extend the scRNA-seq findings. RESULTS: Two recurrent neoplastic cell populations were identified in TGCT that are highly similar to nonneoplastic synoviocytes. We identified GFPT2 as a marker that highlights the neoplastic cells in TCGT. We show that the neoplastic cells themselves do not express CSF1R. We identified overlapping MAB features between the giant cells in TGCT and GCTB. CONCLUSIONS: The neoplastic cells in TGCT are highly similar to nonneoplastic synoviocytes. The lack of CSF1R on the neoplastic cells indicates they may be unaffected by current therapies. High expression of GFPT2 in the neoplastic cells is associated with activation of the YAP1/TAZ pathway. In addition, we identified expression of the platelet-derived growth factor receptor in the neoplastic cells. These findings suggest two additional pathways to target in this tumor.

Vascular Tumor Recapitulated in Endothelial Cells from hiPSCs Engineered to Express the SERPINE1-FOSB Translocation.

Chromosomal translocations are prevalent among soft tissue tumors, including those of the vasculature such as pseudomyogenic hemangioendothelioma (PHE). PHE shows endothelial cell (EC) features and has a tumor-specific t(7;19)(q22;q13) SERPINE1-FOSB translocation, but is difficult to study as no primary tumor cell lines have yet been derived. Here, we engineer the PHE chromosomal translocation into human induced pluripotent stem cells (hiPSCs) using CRISPR/Cas9 and differentiate these into ECs (hiPSC-ECs) to address this. Comparison of parental with PHE hiPSC-ECs shows (1) elevated expression of FOSB, (2) higher proliferation and more tube formation but lower endothelial barrier function, (3) invasive growth and abnormal vessel formation in mice after transplantation, and (4) specific transcriptome alterations reflecting PHE and indicating PI3K-Akt and MAPK signaling pathways as possible therapeutic targets. The modified hiPSC-ECs thus recapitulate functional features of PHE and demonstrate how these translocation models can be used to understand tumorigenic mechanisms and identify therapeutic targets.

Molecular Pathology of Bone Tumors.

Although classic histomorphology is the cornerstone of bone tumor diagnostics, this field has rapidly evolved since the advancement of new molecular techniques. The identification of novel genetic alterations in bone tumors has led to more insight into the genetic background of these tumors, which has resulted in a more prominent role of molecular pathology in daily practice. Numerous studies have been conducted in the past few decades and illustrated that based on molecular alterations, bone tumors can be roughly classified as tumors with simple karyotypes and those with complex karyotypes. The first group can be subclassified as tumors that carry specific translocations, somatic gene mutations, or more or less specific amplifications. On the other hand, sarcomas with complex karyotypes usually lack specific alterations. Many techniques are available for the detection of recurrent genetic alterations, now also including IHC analysis, and this review focuses on assays routinely performed in molecular diagnostics. Subsequently, tumor classes with distinct genetic abnormalities are discussed and illustrated by more specific examples, and the usefulness of molecular pathology in routine diagnostics is highlighted.

Telatinib Is an Effective Targeted Therapy for Pseudomyogenic Hemangioendothelioma.

Purpose: Pseudomyogenic hemangioendothelioma (PHE) is an extremely rare locally aggressive neoplasm with endothelial differentiation, which often presents with multiple lesions. These tumors have characteristic SERPINE1-FOSB fusions. We report a 17 years old patient with advanced unresectable PHE with a durable complete remission to the multi-tyrosine kinase inhibitor telatinib. The aim of this study was to generate an in vitro model for PHE, to study the functional consequences of SERPINE1-FOSB in endothelial cells, and its interaction with telatinib, to biologically substantiate the complete response to telatinib.Experimental Design: As the fusion results in overexpression of a truncated form of FOSB, we overexpressed truncated FOSB in normal endothelial cells.Results: Truncated FOSB significantly affected tumor growth in three-dimensional (3D) on matrigel with increased and sustained sprouting. Moreover, truncated FOSB acted as an active transcription factor capable to regulate its own transcription, as well as to upregulate PDGFRA and FLT1 expression (four-fold). Telatinib decreased proliferation and tumor growth in 3D and induced apoptosis. As expected, telatinib blocked VEGF signaling as phosphorylation of ERK was abolished. Interestingly, in FOSB overexpressing cells, telatinib specifically affected PDGFRA, FLT1, and FLT4 signaling and downregulated SERPINE1, thereby affecting the self-regulation of the fusion gene.Conclusions: We provide a biological substantiation of a complete clinical remission that was seen in a patient with PHE, showing that telatinib indirectly interferes with the self-regulated expression of the fusion product. Thus, telatinib or any other currently available VEGFR1-4/PDGFRA inhibitor could be a highly specific treatment option for patients with multifocal unresectable PHE. Clin Cancer Res; 24(11); 2678-87. ©2018 AACR.

Vascular Tumors of Bone: The Evolvement of a Classification Based on Molecular Developments.

The classification of vascular tumors of bone has been under debate over time. Vascular tumors in bone are rare, display highly overlapping morphology, and, therefore, are considered difficult by pathologists. Compared with their soft tissue counterparts, they are more often multifocal and sometimes behave more aggressively. Over the past decade, with the advent of next-generation sequencing, recurrent molecular alterations have been found in some of the entities. The integration of morphology and molecular changes has led to a better characterization of these separate entities.