Editorial: Thymic Epithelial Cells: New Insights Into the Essential Driving Force of T-Cell Differentiation

M.B. is supported by the Intramural Research Program of the NIH. I.O. is supported by grant from the MEXT-JSPS 17K08884 and Takeda Science Foundation. The laboratory of N.L.A. is supported by a starting grant from the European Research Council (ERC) under the project 637843 and by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT - Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the project POCI-01-0145-FEDER-029129 (PTDC/MED-IMU/29129/2017) and PTDC/ MED-IMU/1416/2020

Smelling the dark proteome: Functional characterization of PITH domain-containing protein 1 (C1orf128) in olfactory metabolism

The Human Proteome Project (HPP) consortium aims to functionally characterize the dark proteome. On the basis of the relevance of olfaction in early neurodegeneration, we have analyzed the dark proteome using data mining in public resources and omics data sets derived from the human olfactory system. Multiple dark proteins localize at synaptic terminals and may be involved in amyloidopathies such as Alzheimer’s disease (AD). We have characterized the dark PITH domain-containing protein 1 (PITHD1) in olfactory metabolism using bioinformatics, proteomics, in vitro and in vivo studies, and neuropathology. PITHD1–/– mice exhibit olfactory bulb (OB) proteome changes related to synaptic transmission, cognition, and memory. OB PITHD1 expression increases with age in wild-type (WT) mice and decreases in Tg2576 AD mice at late stages. The analysis across 6 neurological disorders reveals that olfactory tract (OT) PITHD1 is specifically upregulated in human AD. Stimulation of olfactory neuroepithelial (ON) cells with PITHD1 alters the ON phosphoproteome, modifies the proliferation rate, and induces a pro-inflammatory phenotype. This workflow applied by the Spanish C-HPP and Human Brain Proteome Project (HBPP) teams across the ON-OB-OT axis can be adapted as a guidance to decipher functional features of dark proteins. Data are available via ProteomeXchange with identifiers PXD018784 and PXD021634

Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

The crucial capability of T cells for discrimination between self and non-self peptides is based on negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). Although the autoimmune regulator (AIRE) protein is known to promote the expression of a subset of TRAs, its mechanism of action is still not fully understood. The expression of TRAs that are not under the control of AIRE also needs further characterization. Furthermore, expression patterns of TRA genes have been suggested to change over the course of mTEC development. Herein we have used single-cell RNA-sequencing to resolve patterns of TRA expression during mTEC development. Our data indicated that mTEC development consists of three distinct stages, correlating with previously described jTEC, mTEChi and mTEClo phenotypes. For each subpopulation, we have identified marker genes useful in future studies. Aire-induced TRAs were switched on during jTEC-mTEC transition and were expressed in genomic clusters, while otherwise the subsets expressed largely overlapping sets of TRAs. Moreover, population-level analysis of TRA expression frequencies suggested that such differences might not be necessary to achieve efficient thymocyte selection.RM is supported by a PhD Fellowship from the Fundação para a Ciência e Tecnologia, Portugal (SFRH/ BD/51950/2012). XZ is supported by an Advanced Postdoc Mobility Fellowship from the Swiss National Science Foundation (SNSF, grant number P300P2_151352). Part of the work was performed during XZ’s visit to the Simons Institute for the Theory of Computing. TL is supported by the Academy of Finland (Decision 311081). The authors would like to thank Bee Ling Ng and the staff of the Cytometry Core Facility, and Stephan Lorenz and the staff of the Single Cell Genomics Core Facility for their contribution. Mark Lynch is acknowledged for technical assistance with the Fluidigm C1 platform. Mike Stubbington and Kylie James are acknowledged for revising the language of the manuscript. We thank Sarah Teichmann for help and discussions regarding the manuscript.info:eu-repo/semantics/publishedVersio

A Distinct Subset of Fibroblastic Stromal Cells Constitutes the Cortex-Medulla Boundary Subcompartment of the Lymph Node

The spatiotemporal regulation of immune responses in the lymph node (LN) depends on its sophisticated tissue architecture, consisting of several subcompartments supported by distinct fibroblastic stromal cells (FSCs). However, the intricate details of stomal structures and associated FSC subsets are not fully understood. Using several gene reporter mice, we sought to discover unrecognized stromal structures and FSCs in the LN. The four previously identified FSC subsets in the cortex are clearly distinguished by the expression pattern of reporters including PDGFR beta, CCL21-ser, and CXCL12. Herein, we identified a unique FSC subset expressing both CCL21-ser and CXCL12 in the deep cortex periphery (DCP) that is characterized by preferential B cell localization. This subset was clearly different from CXCL12(high) LepR(high) FSCs in the medullary cord, which harbors plasma cells. B cell localization in the DCP was controlled chiefly by CCL21-ser and, to a lesser extent, CXCL12. Moreover, the optimal development of the DCP as well as medulla requires B cells. Together, our findings suggest the presence of a unique microenvironment in the cortex-medulla boundary and offer an advanced view of the multi-layered stromal framework constructed by distinct FSC subsets in the LN

Identification and Analysis of the Active Phytochemicals from the Anti-Cancer Botanical Extract Bezielle

Bezielle is a botanical extract that has selective anti-tumor activity, and has shown a promising efficacy in the early phases of clinical testing. Bezielle inhibits mitochondrial respiration and induces reactive oxygen species (ROS) in mitochondria of tumor cells but not in non-transformed cells. The generation of high ROS in tumor cells leads to heavy DNA damage and hyper-activation of PARP, followed by the inhibition of glycolysis. Bezielle therefore belongs to a group of drugs that target tumor cell mitochondria, but its cytotoxicity involves inhibition of both cellular energy producing pathways. We found that the cytotoxic activity of the Bezielle extract in vitro co-purified with a defined fraction containing multiple flavonoids. We have isolated several of these Bezielle flavonoids, and examined their possible roles in the selective anti-tumor cytotoxicity of Bezielle. Our results support the hypothesis that a major Scutellaria flavonoid, scutellarein, possesses many if not all of the biologically relevant properties of the total extract. Like Bezielle, scutellarein induced increasing levels of ROS of mitochondrial origin, progressive DNA damage, protein oxidation, depletion of reduced glutathione and ATP, and suppression of both OXPHOS and glycolysis. Like Bezielle, scutellarein was selectively cytotoxic towards cancer cells. Carthamidin, a flavonone found in Bezielle, also induced DNA damage and oxidative cell death. Two well known plant flavonoids, apigenin and luteolin, had limited and not selective cytotoxicity that did not depend on their pro-oxidant activities. We also provide evidence that the cytotoxicity of scutellarein was increased when other Bezielle flavonoids, not necessarily highly cytotoxic or selective on their own, were present. This indicates that the activity of total Bezielle extract might depend on a combination of several different compounds present within it

Modelling prognostic factors in advanced pancreatic cancer

Pancreatic cancer is the fifth most common cause of cancer death. Identification of defined patient groups based on a prognostic index may improve the prediction of survival and selection of therapy. Many prognostic factors have been identified often based on retrospective, underpowered studies with unclear analyses. Data from 653 patients were analysed. Continuous variables are often simplified assuming a linear relationship with log hazard or introducing a step function (dichotomising). Misspecification may lead to inappropriate conclusions but has not been previously investigated in pancreatic cancer studies. Models based on standard assumptions were compared with a novel approach using nonlinear fractional polynomial (FP) transformations. The model based on FP-transformed covariates was most appropriate and confirmed five previously reported prognostic factors: albumin, CA19-9, alkaline phosphatase, LDH and metastases, and identified three additional factors not previously reported: WBC, AST and BUN. The effects of CA19-9, alkaline phosphatase, AST and BUN may go unrecognised due to simplistic assumptions made in statistical modelling. We advocate a multivariable approach that uses information contained within continuous variables appropriately. The functional form of the relationship between continuous covariates and survival should always be assessed. Our model should aid individual patient risk stratification and the design and analysis of future trials in pancreatic cancer

FISH analysis of 107 prostate cancers shows that PTEN genomic deletion is associated with poor clinical outcome

This study examines the clinical impact of PTEN genomic deletions using fluorescence in situ hybridisation (FISH) analysis of 107 prostate cancers, with follow-up information covering a period of up to 10 years. Tissue microarray analysis using interphase FISH indicated that hemizygous PTEN losses were present in 42/107 (39%) of prostatic adenocarcinomas, with a homozygous PTEN deletion observed in 5/107 (5%) tumours. FISH analysis using closely linked probes centromeric and telomeric to the PTEN indicated that subband microdeletions accounted for ∼70% genomic losses. Kaplan–Meier survival analysis of PTEN genomic losses (hemizygous and homozygous deletion vs not deleted) identified subgroups with different prognosis based on their time to biochemical relapse after surgery, and demonstrated significant association between PTEN deletion and an earlier onset of disease recurrence (as determined by prostate-specific antigen levels). Homozygous PTEN deletion was associated with a much earlier onset of biochemical recurrence (P=0.002). Furthermore, PTEN loss at the time of prostatectomy correlated with clinical parameters of more advanced disease, such as extraprostatic extension and seminal vesicle invasion. Collectively, our data indicates that haploinsufficiency or PTEN genomic loss is an indicator of more advanced disease at surgery, and is predictive of a shorter time to biochemical recurrence of disease