Controlled sulfur-based engineering confers mouldability to phosphorothioate antisense oligonucleotides

Phosphorothioates (PS) have proven their effectiveness in the area of therapeutic oligonucleotides with applications spanning from cancer treatment to neurodegenerative disorders. Initially, PS substitution was introduced for the antisense oligonucleotides (PS ASOs) because it confers an increased nuclease resistance meanwhile ameliorates cellular uptake and in-vivo bioavailability. Thus, PS oligonucleotides have been elevated to a fundamental asset in the realm of gene silencing therapeutic methodologies. But, despite their wide use, little is known on the possibly different structural changes PS-substitutions may provoke in DNA·RNA hybrids. Additionally, scarce information and significant controversy exists on the role of phosphorothioate chirality in modulating PS properties. Here, through comprehensive computational investigations and experimental measurements, we shed light on the impact of PS chirality in DNA-based antisense oligonucleotides; how the different phosphorothioate diastereomers impact DNA topology, stability and flexibility to ultimately disclose pro-Sp S and pro-Rp S roles at the catalytic core of DNA Exonuclease and Human Ribonuclease H; two major obstacles in ASOs-based therapies. Altogether, our results provide full-atom and mechanistic insights on the structural aberrations PS-substitutions provoke and explain the origin of nuclease resistance PS-linkages confer to DNA·RNA hybrids; crucial information to improve current ASOs-based therapies.© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research

A threshold level of NFATc1 activity facilitates thymocyte differentiation and opposes notch-driven leukaemia development.

International audienceNFATc1 plays a critical role in double-negative thymocyte survival and differentiation. However, the signals that regulate Nfatc1 expression are incompletely characterized. Here we show a developmental stage-specific differential expression pattern of Nfatc1 driven by the distal (P1) or proximal (P2) promoters in thymocytes. Whereas, preTCR-negative thymocytes exhibit only P2 promoter-derived Nfatc1beta expression, preTCR-positive thymocytes express both Nfatc1beta and P1 promoter-derived Nfatc1alpha transcripts. Inducing NFATc1alpha activity from P1 promoter in preTCR-negative thymocytes, in addition to the NFATc1beta from P2 promoter impairs thymocyte development resulting in severe T-cell lymphopenia. In addition, we show that NFATc1 activity suppresses the B-lineage potential of immature thymocytes, and consolidates their differentiation to T cells. Further, in the pTCR-positive DN3 cells, a threshold level of NFATc1 activity is vital in facilitating T-cell differentiation and to prevent Notch3-induced T-acute lymphoblastic leukaemia. Altogether, our results show NFATc1 activity is crucial in determining the T-cell fate of thymocytes

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis. Integrative analyses of ∼500 mice and ∼1,000 patients revealed a common MAPK-MYC genetic pathway that accelerated time to progression from precursor states across genetically heterogeneous MM. MYC-dependent time to progression conditioned immune evasion mechanisms that remodeled the BM microenvironment differently. Rapid MYC-driven progressors exhibited a high number of activated/exhausted CD8+ T cells with reduced immunosuppressive regulatory T (Treg) cells, while late MYC acquisition in slow progressors was associated with lower CD8+ T cell infiltration and more abundant Treg cells. Single-cell transcriptomics and functional assays defined a high ratio of CD8+ T cells versus Treg cells as a predictor of response to immune checkpoint blockade (ICB). In clinical series, high CD8+ T/Treg cell ratios underlie early progression in untreated smoldering MM, and correlated with early relapse in newly diagnosed patients with MM under Len/Dex therapy. In ICB-refractory MM models, increasing CD8+ T cell cytotoxicity or depleting Treg cells reversed immunotherapy resistance and yielded prolonged MM control. Our experimental models enable the correlation of MM genetic and immunological traits with preclinical therapy responses, which may inform the next-generation immunotherapy trials

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland

Pitfalls in machine learning‐based assessment of tumor‐infiltrating lymphocytes in breast cancer: a report of the international immuno‐oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer (BC) has been well established, and tumor-infiltrating lymphocytes (TILs) have emerged as a predictive and prognostic biomarker for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2 negative) breast cancer (TNBC) and HER2-positive breast cancer. How computational assessment of TILs can complement manual TIL-assessment in trial- and daily practices is currently debated and still unclear. Recent efforts to use machine learning (ML) for the automated evaluation of TILs show promising results. We review state-of-the-art approaches and identify pitfalls and challenges by studying the root cause of ML discordances in comparison to manual TILs quantification. We categorize our findings into four main topics; (i) technical slide issues, (ii) ML and image analysis aspects, (iii) data challenges, and (iv) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns, or design choices in the computational implementation. To aid the adoption of ML in TILs assessment, we provide an in-depth discussion of ML and image analysis including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial- and routine clinical management of patients with TNBC

Catalogo de especies vegetales espaNolas sensibles a la contaminacion atmosferica

Centro de Informacion y Documentacion Cientifica (CINDOC). C/Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai

Amebic monocyte locomotion inhibitory factor peptide ameliorates inflammation in CIA mouse model by downregulation of cell adhesion, inflammation/chemotaxis, and matrix metalloproteinases genes

Objective and design: Monocyte locomotion inhibitory factor (MLIF), an amebic peptide with antiinflammatory properties, was evaluated in collagen-induced arthritis (CIA) to test its effects on the onset and acute inflammatory response of arthritis. Material: DBA1/J mice at 8-10 weeks of age were divided into four groups (eight mice per group). Treatment: The adjuvant group received Freund adjuvant, the CIA group was immunized with collagen II, the MLIF/CIA group received collagen II and MLIF, and the MLIF group received MLIF and Freund adjuvant. Methods: All groups were evaluated clinically. Seven weeks after the collagen injection, at the peak of the clinical arthritis score, limb specimens were collected and histological studies and gene expression analysis using microarrays were performed. Results: MLIF administered weekly as a preventive scheme delayed and reduced the severity of acute arthritis. MLIF induced gene changes in functional categories including adhesion molecules, matrix metalloproteinases, and inflammatory cytokines. Conclusions: MLIF could be an interesting new molecule to investigate in the field of rheumatoid arthritis pathogenesis research for its potential to prevent inflammation. Zapotitlán Springer Basel AG 2010