Atypical BCR-ABL1 transcript in mixed phenotype acute leukemia with bone marrow necrosis.

Mixed phenotype acute leukemia (MPAL) is a type of acute leukemia in which encompasses mixed features of myeloid, T-lymphoid, and/or B-lymphoid differentiation. Philadelphia chromosome-positive (Ph+) MPAL is a rare subgroup with a poor prognosis and accounts for ＜1% of adult acute leukemia. Until now, there is still no consensus on how to best treat Ph+ MPAL. Here, we report a 62-year-old male with Ph+ (atypical e13a2 BCR-ABL1 fusion protein) MPAL. This patient presented with recurrent and intense bone pain due to bone marrow necrosis (BMN). Besides, he did not achieve a complete remission for the first two chemotherapies, until he received flumatinib combined with hyper-CVAD (B) (a dose-intensive regimen include methotrexate and cytarabine). To our knowledge, this is the first report to describe the coexistence of BMN and atypical e13a2 BCR-ABL1 transcripts in patients with MPAL. This finding will bring new understandings in the diagnosis and treatment of Ph+ MPAL.

Gastrodin Liposomes Block Crosstalk between Astrocytes and Glioma Cells via Downregulating Cx43 to Improve Antiglioblastoma Efficacy of Temozolomide.

The crosstalk between glioma cells and astrocytes plays a crucial role in developing temozolomide (TMZ) resistance of glioblastomas, together with the existence of the BBB contributing to the unsatisfactory clinical treatment of glioblastomas. Herein, we developed a borneol-modified and gastrodin-loaded liposome (Bo-Gas-LP), with the intent of enhancing the efficacy of TMZ therapy after intranasal administration. The results showed that Bo-Gas-LP improved GL261 cells' sensitivity to TMZ and prolonged survival of GL261-bearing mice by blocking the crosstalk between astrocytes and glioblastoma cells with the decrease of Cx43. Our study showed that intranasal Bo-Gas-LP targeting the crosstalk in glioblastoma microenvironments proposed a promising targeted therapy idea to overcome the current therapeutic limitations of TMZ-resistant glioblastomas.

Characteristics of Molecular Genetic Mutations and Their Correlation with Prognosis in Adolescent and Adult Patients with Acute Lymphoblastic Leukemia.

INTRODUCTION: The prognosis of acute lymphoblastic leukemia (ALL) in adolescents and adults is poor, and recurrence is an important cause of their death. Changes of genetic information play a vital role in the pathogenesis and recurrence of ALL; however, the impact of molecular genetic mutations on disease diagnosis and prognosis remains unexplored. This study aimed to explore the frequency spectrum of gene mutations and their prognostic significance, along with the minimal residual disease (MRD) level and hematopoietic stem cell transplantation (HSCT), in adolescent and adult patients aged ≥15 years with ALL. METHODS: The basic characteristics, cytogenetics, molecular genetics, MRD level, treatment regimen, and survival outcome of patients with untreated ALL (≥15 years) were collected, and the correlation and survival analysis were performed using the SPSS 25.0 and R software. RESULTS: This study included 404 patients, of which 147 were selected for next-generation sequencing (NGS). NGS results revealed that 91.2% of the patients had at least one mutation, and 67.35% had multiple (≥2) mutations. NOTCH1, PHF6, RUNX1, PTEN, JAK3, TET2, and JAK1 were the most common mutations in T-ALL, whereas FAT1, TET2, NARS, KMT2D, FLT3, and RELN were the most common mutations in B-ALL. Correlation analysis revealed the mutation patterns, which were significantly different between T-ALL and B-ALL. In the prognostic analysis of 107 patients with B-ALL, multivariate analysis showed that the number of mutations ≥5 was an independent risk factor for overall survival and the RELN mutation was an independent poor prognostic factor for event-free survival. DISCUSSION: The distribution of gene mutations and the co-occurrence and repulsion of mutant genes in patients with ALL were closely related to the immunophenotype of the patients. The number of mutations ≥5 and the RELN mutation were significantly associated with poor prognosis in adolescent and adult patients with ALL.

From Detection to Cure - Emerging Roles for Urinary Tumor DNA (utDNA) in Bladder Cancer.

PURPOSE OF REVIEW: This review sought to define the emerging roles of urinary tumor DNA (utDNA) for diagnosis, monitoring, and treatment of bladder cancer. Building from early landmark studies the focus is on recent studies, highlighting how utDNA could aid personalized care. RECENT FINDINGS: Recent research underscores the potential for utDNA to be the premiere biomarker in bladder cancer due to the constant interface between urine and tumor. Many studies find utDNA to be more informative than other biomarkers in bladder cancer, especially in early stages of disease. Points of emphasis include superior sensitivity over traditional urine cytology, broad genomic and epigenetic insights, and the potential for non-invasive, real-time analysis of tumor biology. utDNA shows promise for improving all phases of bladder cancer care, paving the way for personalized treatment strategies. Building from current research, future comprehensive clinical trials will validate utDNA's clinical utility, potentially revolutionizing bladder cancer management.

Targeting N6-methyladenosine reader YTHDF1 with siRNA boosts antitumor immunity in NASH-HCC by inhibiting EZH2-IL-6 axis.

BACKGROUND & AIMS: RNA N6-methyladenosine (m6A) reader protein YTHDF1 has been implicated in cancer; however, its role in hepatocellular carcinoma (HCC), especially in non-alcoholic steatohepatitis-associated HCC (NASH-HCC), remains unknown. Here, we investigated the functional role of YTHDF1 in NASH-HCC and its interplay with the tumor immune microenvironment. METHODS: Hepatocyte-specific Ythdf1-overexpressing mice were subjected to a NASH-HCC-inducing diet. Tumor-infiltrating immune cells were profiled with single-cell RNA-sequencing, flow cytometry, and immunostaining. The molecular target of YTHDF1 was elucidated with RNA-sequencing, m6A-sequencing, YTHDF1 RNA immunoprecipitation-sequencing, proteomics, and ribosome-profiling. Ythdf1 in NASH-HCC models was targeted by lipid nanoparticle (LNP)-encapsulated small-interfering Ythdf1. RESULTS: YTHDF1 is overexpressed in tumor tissues compared to adjacent peri-tumor tissues from patients with NASH-HCC. Liver-specific Ythdf1 overexpression drives tumorigenesis in dietary models of spontaneous NASH-HCC. Single-cell RNA-sequencing and flow cytometry revealed that Ythdf1 induced accumulation of myeloid-derived suppressor cells (MDSCs) and suppressed cytotoxic CD8+ T-cell function. Mechanistically, Ythdf1 expression in NASH-HCC cells induced the secretion of IL-6, which mediated MDSC recruitment and activation, leading to CD8+ T-cell dysfunction. EZH2 mRNA was identified as a key YTHDF1 target. YTHDF1 binds to m6A-modified EZH2 mRNA and promotes EZH2 translation. EZH2 in turn increased expression and secretion of IL-6. Ythdf1 knockout synergized with anti-PD-1 treatment to suppress tumor growth in NASH-HCC allografts. Furthermore, therapeutic targeting of Ythdf1 using LNP-encapsulated small-interfering RNA significantly increased the efficacy of anti-PD-1 blockade in NASH-HCC allografts. CONCLUSIONS: We identified that YTHDF1 promotes NASH-HCC tumorigenesis via EZH2-IL-6 signaling, which recruits and activates MDSCs to cause cytotoxic CD8+ T-cell dysfunction. YTHDF1 may be a novel therapeutic target to improve responses to anti-PD-1 immunotherapy in NASH-HCC. IMPACT AND IMPLICATIONS: YTHDF1, a N6-methyladenosine reader, is upregulated in patients with non-alcoholic steatohepatitis (NASH)-associated hepatocellular carcinoma (HCC); however, its role in modulating the tumor immune microenvironment in NASH-HCC remains unclear. Here, we show that Ythdf1 mediates immunosuppression in NASH-HCC and that targeting YTHDF1 in combination with immune checkpoint blockade elicits robust antitumor immune responses. Our findings suggest novel therapeutic targets for potentiating the efficacy of immune checkpoint blockade in NASH-HCC and provide the rationale for developing YTHDF1 inhibitors for the treatment of NASH-HCC.

METTL3 Inhibits Antitumor Immunity by Targeting m6A-BHLHE41-CXCL1/CXCR2 Axis to Promote Colorectal Cancer.

BACKGROUND & AIMS: N6-Methyladenosine (m6A) is the most prevalent RNA modification and recognized as an important epitranscriptomic mechanism in colorectal cancer (CRC). We aimed to exploit whether and how tumor-intrinsic m6A modification driven by methyltransferase like 3 (METTL3) can dictate the immune landscape of CRC. METHODS: Mettl3 knockout mice, CD34+ humanized mice, and different syngeneic mice models were used. Immune cell composition and cytokine level were analyzed by flow cytometry and Cytokine 23-Plex immunoassay, respectively. M6A sequencing and RNA sequencing were performed to identify downstream targets and pathways of METTL3. Human CRC specimens (n = 176) were used to evaluate correlation between METTL3 expression and myeloid-derived suppressor cell (MDSC) infiltration. RESULTS: We demonstrated that silencing of METTL3 in CRC cells reduced MDSC accumulation to sustain activation and proliferation of CD4+ and CD8+ T cells, and eventually suppressed CRC in ApcMin/+Mettl3+/- mice, CD34+ humanized mice, and syngeneic mice models. Mechanistically, METTL3 activated the m6A-BHLHE41-CXCL1 axis by analysis of m6A sequencing, RNA sequencing, and cytokine arrays. METTL3 promoted BHLHE41 expression in an m6A-dependent manner, which subsequently induced CXCL1 transcription to enhance MDSC migration in vitro. However, the effect was negligible on BHLHE41 depletion, CXCL1 protein or CXCR2 inhibitor SB265610 administration, inferring that METTL3 promotes MDSC migration via BHLHE41-CXCL1/CXCR2. Consistently, depletion of MDSCs by anti-Gr1 antibody or SB265610 blocked the tumor-promoting effect of METTL3 in vivo. Importantly, targeting METTL3 by METTL3-single guide RNA or specific inhibitor potentiated the effect of anti-programmed cell death protein 1 (anti-PD1) treatment. CONCLUSIONS: Our study identifies METTL3 as a potential therapeutic target for CRC immunotherapy whose inhibition reverses immune suppression through the m6A-BHLHE41-CXCL1 axis. METTL3 inhibition plus anti-PD1 treatment shows promising antitumor efficacy against CRC.

Artificial Intelligence-Assisted Colonoscopy for Colorectal Cancer Screening: A Multicenter Randomized Controlled Trial.

BACKGROUND AND AIMS: Artificial intelligence (AI)-assisted colonoscopy improves polyp detection and characterization in colonoscopy. However, data from large-scale multicenter randomized controlled trials (RCT) in an asymptomatic population are lacking. METHODS: This multicenter RCT aimed to compare AI-assisted colonoscopy with conventional colonoscopy for adenoma detection in an asymptomatic population. Asymptomatic subjects 45-75 years of age undergoing colorectal cancer screening by direct colonoscopy or fecal immunochemical test were recruited in 6 referral centers in Hong Kong, Jilin, Inner Mongolia, Xiamen, and Beijing. In the AI-assisted colonoscopy, an AI polyp detection system (Eagle-Eye) with real-time notification on the same monitor of the endoscopy system was used. The primary outcome was overall adenoma detection rate (ADR). Secondary outcomes were mean number of adenomas per colonoscopy, ADR according to endoscopist's experience, and colonoscopy withdrawal time. This study received Institutional Review Board approval (CRE-2019.393). RESULTS: From November 2019 to August 2021, 3059 subjects were randomized to AI-assisted colonoscopy (n = 1519) and conventional colonoscopy (n = 1540). Baseline characteristics and bowel preparation quality between the 2 groups were similar. The overall ADR (39.9% vs 32.4%; P < .001), advanced ADR (6.6% vs 4.9%; P = .041), ADR of expert (42.3% vs 32.8%; P < .001) and nonexpert endoscopists (37.5% vs 32.1%; P = .023), and adenomas per colonoscopy (0.59 ± 0.97 vs 0.45 ± 0.81; P < .001) were all significantly higher in the AI-assisted colonoscopy. The median withdrawal time (8.3 minutes vs 7.8 minutes; P = .004) was slightly longer in the AI-assisted colonoscopy group. CONCLUSIONS: In this multicenter RCT in asymptomatic patients, AI-assisted colonoscopy improved overall ADR, advanced ADR, and ADR of both expert and nonexpert attending endoscopists. (ClinicalTrials.gov, Number: NCT04422548).

Identification of ORM1, vWF, SPARC, and PPBP as immune-related proteins involved in immune thrombocytopenia by quantitative LC-MS/MS.

BACKGROUND: Immune thrombocytopenia (ITP) is a common autoimmune disease characterized by loss of immune tolerance to platelet autoantigens leading to excessive destruction and insufficient production of platelets. METHOD: Quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS) was performed to detect the differentially expressed proteins in bone marrow samples from active ITP patients and normal controls. RESULT: Our bioinformatic analysis identified two upregulated proteins (ORM1 and vWF) and two downregulated proteins (PPBP and SPARC) related to immune function. The four proteins were all found to be related to the tumor necrosis factor (TNF) -α signalling pathway and involved in the pathogenesis of ITP in KEGG pathway analysis. CONCLUSION: Bioinformatics analysis identified differentially expressed proteins in bone marrow that are involved in the TNF-α signalling pathway and are related to the activation of immune function in ITP patients. These findings could provide new ideas for research on the loss of immune tolerance in ITP patients.

Comparison of the efficacy and safety of an oral sulfate solution and 3-L polyethylene glycol on bowel preparation before colonoscopy: a phase III multicenter randomized controlled trial.

BACKGROUND AND AIMS: Adequate bowel preparation is crucial for clear mucosal visualization during colonoscopy. We aimed to comprehensively compare oral sulfate solution (OSS) and 3-L split-dose polyethylene glycol (PEG) for bowel preparation before colonoscopy. METHODS: This randomized, active-controlled, noninferiority study was performed in 10 medical centers. Eligible subjects were enrolled to receive OSS or 3-L PEG in a split-dose regimen. The quality of bowel preparation, adverse reactions, and acceptability were evaluated. The quality of bowel preparation was evaluated using the Boston Bowel Preparation Scale. Safety was evaluated by adverse reactions. The study population was divided into the full analysis set (FAS), the safety set, the modified FAS (mFAS), and the per-protocol set (PPS). RESULTS: Three hundred forty-eight potentially eligible subjects were enrolled. Three hundred forty-four subjects were included in the FAS and safety set, 340 subjects were included in the mFAS, and 328 subjects were included in the PPS. Adequate bowel preparation of the OSS was not inferior to 3-L PEG in the mFAS (98.22% vs 97.66%) and the PPS (98.17% vs 98.78%). There was no significant difference in acceptability between the 2 groups (94.74% vs 94.80%, P = .9798). Overall adverse reactions were similar (50.88% vs 44.51%, P = .2370) between the 2 groups. CONCLUSIONS: The split-dose OSS regimen was not inferior to the split-dose 3-L PEG regimen for the quality of bowel preparation in a Chinese adult population. The safety and acceptability of the 2 groups were similar. (Clinical trial registration number: NCT05465889.).

Novel deep learning-based computer-aided diagnosis system for predicting inflammatory activity in ulcerative colitis.

BACKGROUND AND AIMS: Endoscopy is increasingly performed for evaluating patients with ulcerative colitis (UC). However, its diagnostic accuracy is largely affected by the subjectivity of endoscopists' experience and scoring methods, and scoring of selected endoscopic images cannot reflect the inflammation of the entire intestine. We aimed to develop an automatic scoring system using deep-learning technology for consistent and objective scoring of endoscopic images and full-length endoscopic videos of patients with UC. METHODS: We collected 5875 endoscopic images and 20 full-length videos from 332 patients with UC who underwent colonoscopy between January 2017 and March 2021. We trained the artificial intelligence (AI) scoring system using these images, which was then used for full-length video scoring. To more accurately assess and visualize the full-length intestinal inflammation, we divided the large intestine into a fixed number of "areas" (cecum, 20; transverse colon, 20; descending colon, 20; sigmoid colon, 15; rectum, 10). The scoring system automatically scored inflammatory severity of 85 areas from every video and generated a visualized result of full-length intestinal inflammatory activity. RESULTS: Compared with endoscopist scoring, the trained convolutional neural network achieved 86.54% accuracy in the Mayo-scored task, whereas the kappa coefficient was .813 (95% confidence interval [CI], .782-.844). The metrics of the Ulcerative Colitis Endoscopic Index of Severity-scored task were encouraging, with accuracies of 90.7%, 84.6%, and 77.7% and kappa coefficients of .822 (95% CI, .788-.855), .784 (95% CI, .744-.823), and .702 (95% CI, .612-.793) for vascular pattern, erosions and ulcers, and bleeding, respectively. The AI scoring system predicted each bowel segment's score and displayed distribution of inflammatory activity in the entire large intestine using a 2-dimensional colorized image. CONCLUSIONS: We established a novel deep learning-based scoring system to evaluate endoscopic images from patients with UC, which can also accurately describe the severity and distribution of inflammatory activity through full-length intestinal endoscopic videos.