giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration

We introduce giotto-tda, a Python library that integrates high-performance topological data analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ implementations. The library's ability to handle various types of data is rooted in a wide range of preprocessing techniques, and its strong focus on data exploration and interpretability is aided by an intuitive plotting API. Source code, binaries, examples, and documentation can be found at https://github.com/giotto-ai/giotto-tda.Comment: 7 pages, 2 figure

JAK2-mutant hematopoietic cells display metabolic alterations that can be targeted to treat myeloproliferative neoplasms

Increased energy requirement and metabolic reprogramming are hallmarks of cancer cells. We show that metabolic alterations in hematopoietic cells are fundamental to the pathogenesis of mutant JAK2-driven myeloproliferative neoplasms (MPNs). We found that expression of mutant JAK2 augmented and subverted metabolic activity of MPN cells, resulting in systemic metabolic changes in vivo, including hypoglycemia, adipose tissue atrophy, and early mortality. Hypoglycemia in MPN mouse models correlated with hyperactive erythropoiesis and was due to a combination of elevated glycolysis and increased oxidative phosphorylation. Modulating nutrient supply through high-fat diet improved survival, whereas high-glucose diet augmented the MPN phenotype. Transcriptomic and metabolomic analyses identified numerous metabolic nodes in JAK2-mutant hematopoietic stem and progenitor cells that were altered in comparison with wild-type controls. We studied the consequences of elevated levels of Pfkfb3, a key regulatory enzyme of glycolysis, and found that pharmacological inhibition of Pfkfb3 with the small molecule 3PO reversed hypoglycemia and reduced hematopoietic manifestations of MPNs. These effects were additive with the JAK1/2 inhibitor ruxolitinib in vivo and in vitro. Inhibition of glycolysis by 3PO altered the redox homeostasis, leading to accumulation of reactive oxygen species and augmented apoptosis rate. Our findings reveal the contribution of metabolic alterations to the pathogenesis of MPNs and suggest that metabolic dependencies of mutant cells represent vulnerabilities that can be targeted for treating MPNs

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Effects of crystallographic anisotropy on fracture development and acoustic emission in quartz

Transgranular microcracking is fundamental for the initiation and propagation of all fractures in rocks. The geometry of these microcracks is primarily controlled by the interaction of the imposed stress field with the mineral elastic properties. However, the effects of anisotropic elastic properties of minerals on brittle fracture are not well understood. This study examines the effects of elastic anisotropy of quartz on the geometry of brittle fracture and related acoustic emissions (AE) developed during indentation experiments on single crystals at ambient pressure and temperature. A Hertzian cone crack developed during blunt indentation of a single crystal of flawless Brazilian quartz parallel to the c axis shows geometric deviation away from predictions based on the isotropic case, consistent with trigonal symmetry. The visible cone crack penetration depth varies from 3 to 5 mm and apical angle from 53 to 40. Electron backscatter diffraction (EBSD) mapping of the crack tip shows that fracturing initiates along a ~40 μm wide process zone, comprising damage along overlapping en echelon high-index crystallographic planes, shown by discrete bands of reduced electron backscatter pattern (EBSP) quality (band contrast).Coalescence of these surfaces results in a stepped fracture morphology. Monitoring of AE during indentation reveals that the elastic anisotropy of quartz has a significant effect on AE location and focal mechanisms. Ninety-four AE events were recorded during indentation and show an increasing frequency with increasing load. They correspond to the development of subsidiary concentric cracks peripheral to the main cone crack. The strong and complex anisotropy in seismic velocity (~28% Vp, ~43% Vs with trigonal symmetry) resulted in inaccurate and high uncertainty in AE locations using Geiger location routine with an isotropic velocity model. This problem was overcome by using a relative (master event) location algorithm that only requires a priori knowledge of the velocity structure within the source volume. The AE location results correlate reasonably well to the extent of the observed cone crack. Decomposition of AE source mechanisms of the Geiger relocated events shows dominantly end-member behavior between tensile and compressive vector dipole events, with some double-couple-dominated events and no purely tensile or compressive events. The same events located by the master event algorithm yield greater percentage of vector dipole components and no double-couple events, indicating that AE source mechanism solutions can depend on AE location accuracy, and therefore, relocation routine that is utilized. Calculations show that the crystallographic anisotropy of quartz causes apparent deviation of the moment tensors away from double-couple and pure tensile/compressive sources consistent with the observations. Preliminary modeling of calcite anisotropy shows a response distinct from quartz, indicating that the effects of anisotropy on interpreting AE are complex and require detailed further study

Functional genomic analysis of drug sensitivity pathways to guide adjuvant strategies in breast cancer

The widespread introduction of high throughput RNA interference screening technology has revealed tumour drug sensitivity pathways to common cytotoxics such as paclitaxel, doxorubicin and 5-fluorouracil, targeted agents such as trastuzumab and inhibitors of AKT and Poly(ADP-ribose) polymerase (PARP) as well as endocrine therapies such as tamoxifen. Given the limited power of microarray signatures to predict therapeutic response in associative studies of small clinical trial cohorts, the use of functional genomic data combined with expression or sequence analysis of genes and microRNAs implicated in drug response in human tumours may provide a more robust method to guide adjuvant treatment strategies in breast cancer that are transferable across different expression platforms and patient cohorts