Single-Cell Analysis of the Multicellular Ecosystem in Viral Carcinogenesis by HTLV-1

成人T細胞白血病リンパ腫の多段階発がん分子メカニズムを解明 --難治性疾患の新規治療標的候補を複数同定--. 京都大学プレスリリース. 2021-09-07.Premalignant clonal expansion of human T-cell leukemia virus type-1 (HTLV-1)–infected cells occurs before viral carcinogenesis. Here we characterize premalignant cells and the multicellular ecosystem in HTLV-1 infection with and without adult T-cell leukemia/lymphoma (ATL) by genome sequencing and single-cell simultaneous transcriptome and T/B-cell receptor sequencing with surface protein analysis. We distinguish malignant phenotypes caused by HTLV-1 infection and leukemogenesis and dissect clonal evolution of malignant cells with different clinical behavior. Within HTLV-1–infected cells, a regulatory T-cell phenotype associates with premalignant clonal expansion. We also delineate differences between virus- and tumor-related changes in the nonmalignant hematopoietic pool, including tumor-specific myeloid propagation. In a newly generated conditional knockout mouse model recapitulating T-cell–restricted CD274 (encoding PD-L1) gene lesions found in ATL, we demonstrate that PD-L1 overexpressed by T cells is transferred to surrounding cells, leading to their PD-L1 upregulation. Our findings provide insights into clonal evolution and immune landscape of multistep virus carcinogenesis

Integrated genetic and clinical prognostic factors for aggressive adult T-cell leukemia/lymphoma

成人T細胞白血病リンパ腫（ATL）におけるゲノム情報と臨床情報を統合したリスクモデルを確立 --ATLの個別化医療を推進--. 京都大学プレスリリース. 2023-04-10.The prognosis of aggressive adult T-cell leukemia/lymphoma (ATL) is poor, and allogeneic hematopoietic stem-cell transplantation (allo-HSCT) is a curative treatment. To identify favorable prognostic patients after intensive chemotherapy, and who therefore might not require upfront allo-HSCT, we aimed to improve risk stratification of aggressive ATL patients aged <70 years. The clinical risk factors and genetic mutations were incorporated into risk modeling for overall survival (OS). We generated the m7-ATLPI, a clinicogenetic risk model for OS, that included the ATL prognostic index (PI) (ATL-PI) risk category, and non-silent mutations in seven genes, namely TP53, IRF4, RHOA, PRKCB, CARD11, CCR7, and GATA3. In the training cohort of 99 patients, the m7-ATLPI identified a low-, intermediate-, and high-risk group with 2-year OS of 100%, 43%, and 19%, respectively (hazard ratio [HR] 5.46, p < 0.0001). The m7-ATLPI achieved superior risk stratification compared to the current ATL-PI (C-index 0.92 vs. 0.85, respectively). In the validation cohort of 84 patients, the m7-ATLPI defined low-, intermediate-, and high-risk groups with a 2-year OS of 81%, 30%, and 0%, respectively (HR 2.33, p = 0.0094), and the model again outperformed the ATL-PI (C-index 0.72 vs. 0.70, respectively). The simplified m7-ATLPI, which is easier to use in clinical practice, achieved superior risk stratification compared to the ATL-PI, as did the original m7-ATLPI; the simplified version was calculated by summing the following: high-risk ATL-PI category (+10), low-risk ATL-PI category (−4), and non-silent mutations in TP53 (+4), IRF4 (+3), RHOA (+1), PRKCB (+1), CARD11 (+0.5), CCR7 (−2), and GATA3 (−3)

Machine Learning in Predicting Tooth Loss: A Systematic Review and Risk of Bias Assessment

Predicting tooth loss is a persistent clinical challenge in the 21st century. While an emerging field in dentistry, computational solutions that employ machine learning are promising for enhancing clinical outcomes, including the chairside prognostication of tooth loss. We aimed to evaluate the risk of bias in prognostic prediction models of tooth loss that use machine learning. To do this, literature was searched in two electronic databases (MEDLINE via PubMed; Google Scholar) for studies that reported the accuracy or area under the curve (AUC) of prediction models. AUC measures the entire two-dimensional area underneath the entire receiver operating characteristic (ROC) curves. AUC provides an aggregate measure of performance across all possible classification thresholds. Although both development and validation were included in this review, studies that did not assess the accuracy or validation of boosting models (AdaBoosting, Gradient-boosting decision tree, XGBoost, LightGBM, CatBoost) were excluded. Five studies met criteria for inclusion and revealed high accuracy; however, models displayed a high risk of bias. Importantly, patient-level assessments combined with socioeconomic predictors performed better than clinical predictors alone. While there are current limitations, machine-learning-assisted models for tooth loss may enhance prognostication accuracy in combination with clinical and patient metadata in the future

Drug-Coated Balloon versus Plain Balloon Angioplasty in the Treatment of Infrainguinal Vein Bypass Stenosis: A Systematic Review and Meta-Analysis

The optimal endovascular therapy for vein graft stenosis (VGS) following infrainguinal arterial bypass is yet to be established. Drug-coated balloons (DCB) have rapidly improved the inferior patency outcomes of angioplasty using a conventional plain balloon (PB). This study compares the efficacy of DCBs and PBs for the treatment of infrainguinal VGS. This systematic review and meta-analysis was performed according to the PRISMA statement. Multiple electronic searches were conducted in consultation with a health science librarian in September 2022. Studies describing the comparative outcomes of angioplasty using DCBs and PBs in the treatment of infrainguinal VGS were eligible. Datasets from one randomized controlled trial and two cohort studies with a total of 179 patients were identified. The results indicated no significant difference in target lesion revascularization between DCBs and PBs (OR, 0.64; 95% CI, 0.32–1.28; p = 0.21), with no significant heterogeneity between studies. Additionally, differences in primary patency, assisted primary patency, secondary patency, and graft occlusion were not significant. Subgroup analysis showed similar effects for different DCB devices. In conclusion, DCBs showed no significant benefit in the treatment of VGS compared to PBs. Given the small population size of this meta-analysis, future trials with a larger population are desired

Anomalous pH Effect of Blue Proteorhodopsin

Proteorhodopsin (PR) is a light-driven proton pump found in marine bacteria, and thousands of PRs are classified into blue-absorbing PR (B-PR; λ_max ≈ 490 nm) and green-absorbing PR (G-PR; λ_max ≈ 525 nm). In this report, we present conversion of B-PR into G-PR using anomalous pH effect. B-PR in LC1-200, marine γ-proteobacteria, absorbs 497 and 513 nm maximally at pH 7 and 4, respectively, whose pH titration was reversible (p<i>K</i>_a = 4.8). When pH was lowered from 4, the λ_max was further red-shifted (528 nm at pH 2). This is unusual because blue shift occurs by chloride binding in the case of bacteriorhodopsin. Surprisingly, when pH was increased from 2 to 7, the λ_max of this B-PR was further red-shifted to 540 nm, indicating that green-absorbing PR (PR₅₄₀) is created only by changing pH. The present study reports the conformational flexibility of microbial rhodopsins, leading to the switch of absorbing color by a simple pH change