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3 citation(s) found for "Yue, Wei".

Incorporation of Genomic Determinants Improves Diagnostic Accuracy of Oligomonocytic Chronic Myelomonocytic Leukemia
Montalban-Bravo, Guillermo, Wu, Chong , Rodríguez‐Sevilla, Juan José , Wei, Yue , Chien, K., Bouligny, Ian , Kanagal‐Shamanna, Rashmi , Li, Ziyi , Natu, Anuya , Bazinet, Alexandre , Hammond, Danielle E., Bataller, Alex, Borthakur, Gautam, Short, Nicholas J., DiNardo, Courtney D., Kadia, Tapan M., Ravandi, Farhad, Daver, Naval, Pemmaraju, Naveen, Jabbour, Elias, Issa, Ghayas C., Wang, Sa A., Patel, Keyur P. , Tang, Guilin, Medeiros, L. Jeffrey, Finke, Christy M. , Al‐Kali, Aref , Alkhateeb, Hassan, Gangat, Naseema, Mangaonkar, Abhishek A., Román, David , Arenillas, Leonor , Tefferi, Ayalew, Kantarjian, Hagop M., Garcia-Manero, Guillermo, Calvo, Xavier , Patnaik, Mrinal M. , Loghavi, Sanam, Kantarjian, Hagop M. , Bravo, Guillermo Montalban , Chien, Kelly , Gurney, Mark , Bazinet, Alexandre , Hammond, Danielle , Bataller, Alex , Borthakur, Gautam , Short, Nicholas , DiNardo, Courtney , Kadia, Tapan M , Ravandi, Farhad , Daver, Naval , Pemmaraju, Naveen , Jabbour, Elias , Issa, Ghayas , Wang, Sa A , Patel, Keyur P , Tang, Guilin , Medeiros, L Jeffrey , Lasho, Terra L , Finke, Christy M , Al-Kali, Aref , Csizmar, Clifford , Alkhateeb, Hassan B , Gangat, Naseema , Mangaonkar, Abhishek A. , Roman-Bravo, David , Arenillas, Leonor , Tefferi, Ayalew , Kantarjian, Hagop , Garcia-Manero, Guillermo , Calvo, Xavier , Patnaik, Mrinal , Loghavi, Sanam , Kanagal-Shamanna, Rashmi , Rodríguez-Sevilla, Juan José , Montalban‐Bravo, Guillermo , Chien, Kelly S. , Gurney, Mark E. , Hammond, Danielle , Borthakur, Gautam , Short, Nicholas J. , DiNardo, Courtney D. , Kadia, Tapan M. , Daver, Naval , Pemmaraju, Naveen , Jabbour, Elias , Wang, Sa A. , Tang, Guilin , Medeiros, L. Jeffrey , Lasho, Terra L. , Csizmar, Clifford M. , Alkhateeb, Hassan B. , Gangat, Naseema , Mangaonkar, Abhishek A. , Tefferi, Ayalew , Garcia‐Manero, Guillermo , Loghavi, Sanam

Blood Cancer Discovery | January 26, 2026 | Volume: 7 | Issue: 3 | Pages: 414-430

10.1158/2643-3230.bcd-25-0264 | PMID 41587375 Get It

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.
Consideration of genomic determinants improves the diagnostic accuracy of oligomonocytic chronic myelomonocytic leukemia
Montalban‐Bravo, Guillermo , Wei, Yue , Chien, Kelly S. , Kanagal‐Shamanna, Rashmi , Bazinet, Alexandre , Kadia, Tapan M. , Pemmaraju, Naveen , Issa, Ghayas C., Wang, Sa , Patel, Keyur P. , Lasho, Terra, Finke, Christy M. , Al‐Kali, Aref , Gangat, Naseema , Mangaonkar, Abhishek A. , Román, David , Tefferi, Ayalew , Kantarjian, Hagop, Garcia‐Manero, Guillermo , Patnaik, Mrinal M. , Kanagal-Shamanna, Rashmi , Wu, Chong , Rodríguez‐Sevilla, Juan José , Bouligny, Ian , Natu, Anuya , Gurney, Mark E. , Hammond, Danielle , Bataller, Alex , Borthakur, Gautam , Short, Nicholas J. , DiNardo, Courtney D. , Ravandi, Farhad , Daver, Naval , Jabbour, Elias , Issa, Ghayas , Tang, Guilin , Medeiros, L. Jeffrey , Lasho, Terra, Csizmar, Clifford M. , Alkhateeb, Hassan B. , Arenillas, Leonor , Calvo, Xavier , Loghavi, Sanam

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 3849-3849

10.1182/blood-2025-3849 Get It

Abstract Recent updates to the monocyte count thresholds for diagnosing chronic myelomonocytic leukemia (CMML) have recognized oligomonocytic CMML (OM-CMML) as an early stage within the CMML spectrum. However, the clinical validity of these revised criteria remains uncertain without considering biological factors and might misclassify myelodysplastic syndromes (MDS) with mild monocytosis as CMML. To characterize the genomic landscape of OM-CMML, we evaluated OM-CMML (n=249), MDS (n=304) and myelodysplastic CMML (MD-CMML, n=358) patients (pts) treated at three academic institutions. Targeted next-generation sequencing was performed on bone marrow (BM) at initial diagnosis or first referral. OM-CMML was characterized by lower frequencies of biallelic TET2 (biTET2) and RAS pathway (RASp) gene mutations (BRAF, CBL, KRAS, NF1, NRAS and PTPN11) compared to MD-CMML (p<0.001) but higher frequencies than MDS (p<0.001). BM monocyte frequencies, assessed morphologically, were higher in OM-CMML than in MDS (p<0.001) but lower than in MD-CMML (p<0.001), indicating that OM-CMML is a heterogenous group including true CMML and distinct MDS subsets. Unsupervised hierarchical clustering based on genomic alterations across all cases (n=911) identified three distinct clusters: 1) TP53 alterations (predominantly multihit TP53) and complex karyotype (TP53-complex); 2) biTET2 or TET2-SRSF2 co-mutation (biTET2/SRSF2); 3) a heterogenous group lacking these features (not otherwise specifiable [NOS]). Among OM-CMML pts, 11%, 34% and 55% belonged to these clusters, respectively. Model-based unsupervised clustering further identified 9 unique clusters that could be consolidated into 6 groups: 1) TP53-complex; 2) biTET2/SRSF2; 3) SF3B1 (without biTET2 or SRSF2); 4) SRSF2 without TET2 and frequent IDH2 mutations (SRSF2-IDH2); 5) ASXL1 and U2AF1 mutations and copy number alterations (CNA-ASXL1/U2AF1); 6) no somatic mutations (No mutation). biTET2/SRSF2 group exhibited monocytic bias with higher AMC, PB and BM monocyte % even among OM-CMML cases. This bias was not attributed to higher RAS pathway mutation frequencies, as biTET2/SRSF2 cases had similar RASp mutation frequencies but lower median variant allele frequencies for RASp mutations compared to NOS cases (9% vs. 21%, p=0.029). PB monocyte partitioning using flow cytometry (FC) in a subset of OM-CMML pts (n=50) demonstrated higher frequency of classical monocytosis (>94% CD14+/CD16- monocytes) in biTET2/SRSF2 vs other OM-CMML. To further determine if biTET2/SRSF2 genotype defines a distinct biological subgroup, we performed RNA-sequencing of BM CD34+ cells from healthy donors (n=15) and pts with OM-CMML (n=12), MD-CMML (n=14) and MDS (n=55). Unsupervised clustering based on gene expression profiles revealed that biTET2/SRSF2 clustered irrespective of their diagnostic group with greater dispersion being observed based on diagnosis. MDS and CMML with biTET2/SRSF2 had less differentially expressed genes compared to MDS and CMML with biTET2/SRSF2 relative to other MDS and CMML genotypes. Among 138 OM-CMML pts in whom progression to overt CMML was evaluable, 37 (27%) progressed to overt CMML of which 26 (70%) belonged to the biTET2/SRSF2 group. Competing risk analysis confirmed higher cumulative incidence and shorter time to CMML progression among biTET2/SRSF2 OM-CMML. Using ElasticNet regression we identified BM monocytosis and 14 genomic variables (including biTET2 and TET2-SRSF2) as predictors of overt CMML progression among OM-CMML. We developed a score-based model able to predict progression with high reliability (AUC 0.805, sensitivity 0.70, specificity 0.76). Model accuracy was confirmed by optimism-corrected bootstrap internal validation (AUC 0.668). Monocytic bias, BM classical monocytosis (>94% CD16- monocytes) and higher overt CMML progression in biTET2/SRSF2 was confirmed in a validation cohort (28, 66 and 22 pts with OM-CMML, MDS and MD-CMML, respectively). BM monocytosis of biTET2/SRSF2 was confirmed in this cohort with morphologic and FC monocyte frequency quantification having high concordance (r=0.737, p<0.001). Genomic subgroup analysis discriminated survival outcomes more reliably than diagnostic categories alone. Our findings suggest that the presence of biTET2 or TET2-SRSF2 co-mutations, combined with BM monocytosis, can more reliably identify true CMML cases within the OM-CMML spectrum. Integrating genomic determinants into the CMML diagnostic framework enhances diagnostic accuracy.
Remyelination-Promoting DNA Aptamer Conjugate Myaptavin-3064 Binds to Adult Oligodendrocytes In Vitro
Fereidan‐Esfahani, Mahboubeh, Yue, Wei , Wilbanks, Brandon , Johnson, Aaron J. , Warrington, Arthur E. , Howe, Charles L. , Rodriguez, Moses , Maher, L. James, Yue, Wei Ying, Maher, Louis J, Rodriguez, Moses , Howe, Charles L , Warrington, Arthur E , Wilbanks, Brandon A , Johnson, Aaron J.

Pharmaceuticals | November 19, 2020 | Volume: 13 | Issue: 11 | Pages: 403

10.3390/ph13110403 | PMID 33228043 Get It

We previously applied Systematic Evolution of Ligands by EXponential enrichment (SELEX) technology to identify myelin-specific DNA aptamers, using crude mouse central nervous system myelin as bait. This selection identified a 40-nucleotide aptamer (LJM-3064). Multiple biotinylated LJM-3064 molecules were conjugated to a streptavidin core to mimic a multimeric immunoglobulin M (IgM) antibody, generating 3064-BS-streptavidin (Myaptavin-3064). We previously showed that Myaptavin-3064 induces remyelination in the Theiler’s murine encephalomyelitis virus (TMEV) model of chronic spinal cord demyelination. While details of target binding and the mechanism of action remain unclear, we hypothesized that Myaptavin-3064 induces remyelination by binding to oligodendrocytes (OLs). We now report the results of binding assays using the human oligodendroglioma (HOG) cell line, applying both flow cytometry and immunocytochemistry (IC) to assay aptamer conjugate binding to cells. IC assays were applied to compare aptamer conjugate binding to primary embryonic mouse mixed cortical cultures and primary adult rat mixed glial cultures. We show that Myaptavin-3064 binds to HOG cells, with increased binding upon differentiation. In contrast, a negative control aptamer conjugate, 3060-BS, which did not promote central nervous system (CNS) remyelination, does not bind to HOG cells. Myaptavin-3064 did not bind to lung (L2) or kidney (BHK) cell lines. Total internal reflection fluorescence (TIRF) imaging indicates that Myaptavin-3064 binds at the cell membrane of live cells. In addition to HOG cells, Myaptavin-3064 binds to adult rat OLs, but not to embryonic mouse mixed cortical cultures. These data support the hypothesis that Myaptavin-3064 binds to a surface molecule on both rodent and human OLs in a manner that triggers a remyelination signal pathway.