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Chien, Kelly

0000-0001-6024-1613

Mayo Clinic

Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas.

Citations 3

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 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.
Landscape and clinicopathologic features of RAS pathway mutations in chronic myelomonocytic leukemia
Montalban‐Bravo, Guillermo , Loghavi, Sanam , Li, Ziyi , Chien, Kelly S. , Kanagal‐Shamanna, Rashmi , Natu, Anuya , Gurney, Mark E. , Bazinet, Alexandre , Sasaki, Koji , Kadia, Tapan M. , Ravandi, Farhad, Pemmaraju, Naveen , Finke, Christy M. , Al‐Kali, Aref , Gangat, Naseema , Mangaonkar, Abhishek A. , Bueso‐Ramos, Carlos E. , Tefferi, Ayalew, Kantarjian, H., Garcia‐Manero, Guillermo , Patnaik, Mrinal M. , Kantarjian, Hagop M. , Chien, Kelly , Gurney, Mark , Sasaki, Koji , DiNardo, Courtney , Daver, Naval , Short, Nicholas , Pemmaraju, Naveen , Issa, Ghayas , Al-Kali, Aref , Csizmar, Clifford , Gangat, Naseema , Patnaik, Mrinal , Loghavi, Sanam , Kanagal-Shamanna, Rashmi , Kantarjian, Hagop , Bataller, Alex , Hammond, Danielle , Borthakur, Gautam , Swaminathan, Mahesh , DiNardo, Courtney D. , Ravandi, Farhad , Daver, Naval , Short, Nicholas J. , Lasho, Terra L. , Csizmar, Clifford M. , Alkhateeb, Hassan B. , Tefferi, Ayalew

Blood Advances | July 11, 2025 | Volume: 9 | Issue: 19 | Pages: 5105-5117

10.1182/bloodadvances.2025016529 Get It

Abstract RAS pathway (RASp) mutations induce proliferative features, and promote transformation in chronic myelomonocytic leukemia (CMML). However, the unique clonal landscape and hierarchy of distinct RASp mutations remain unexplored. To characterize the landscape, architecture, and implications of unique RASp mutations in CMML, we evaluated a cohort of 814 patients with CMML. We identified 461 RASp mutations among 342 patients (42%). N/KRAS and CBL mutations were the most common, frequently involved the P-loop or RING domains, respectively, and frequently appeared as dominant events (63% and 65%, respectively). BRAF, NF1, and PTPN11 mutations spanned throughout the gene structure, and frequently appeared as subclonal events (75%, 64%, and 59%, respectively). CBL mutations frequently occurred in codominance with SRSF2 and multihit TET2, and were enriched for KIT mutations. PTPN11 mutations more frequently co-occurred with SETBP1 and DNMT3A mutations, and were infrequently codominant with TET2 or ASXL1. RASp mutations predicted for shorter overall survival (hazard ratio [HR], 1.55; 95% confidence interval [CI], 1.15-2.07; P = .0075) and leukemia-free survival (LFS; HR, 1.67; 95% CI, 1.26-2.20; P = .0011), influenced outcomes of myelodysplastic and TET2 mutant CMML, and cooperated with IDH2 and RUNX1 mutations to induce shorter LFS. These data set the bases for refined genomic classifications of CMML, and underscore the need to develop RAS-directed therapies for patients with CMML.
BLAST: A Globally Applicable and Molecularly Versatile Survival Model for Chronic Myelomonocytic Leukemia
Tefferi, Ayalew , Fathima, Saubia , Abdelmagid, Maymona, Alsugair, Ali, Aperna, Fnu, Rezasoltani, Mahsa , Yousuf, Muhammad , Natu, Anuya , Csizmar, Clifford M. , Gurney, Mark E. , Finke, Christy M. , Chien, Kelly S. , Bazinet, Alexandre , Kadia, Tapan M. , Mangaonkar, Abhishek A. , Pardanani, Animesh , Zepeda‐Mendoza, Cinthya , Reichard, Kaaren K. , He, Rong , Sasaki, Koji , Garcia‐Manero, Guillermo , Gangat, Naseema , Montalban‐Bravo, Guillermo , Patnaik, Mrinal M. , Alsugair, Ali Khalid A, Gurney, Mark , Kanagal-Shamanna, Rashmi , Hammond, Danielle , Chien, Kelly , DiNardo, Courtney , Daver, Naval , Zepeda-Mendoza, Cinthya, He, Rong , Loghavi, Sanam , Sasaki, Koji , Larson, Dirk , Onida, Francesco , Gangat, Naseema , Patnaik, Mrinal , Csizmar, Clifford , Fathima, Saubia , Lasho, Terra L. , Kanagal‐Shamanna, Rashmi , Hammond, Danielle , DiNardo, Courtney D. , Daver, Naval , Borthakur, Gautam , Loghavi, Sanam , Passamonti, Francesco , Ravandi, Farhad , Larson, Dirk R.

Blood Journal | May 7, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1182/blood.2024027170 Get It

We sought to develop a survival model in chronic myelomonocytic leukemia (CMML) that is primarily based on clinical variables and examine additional impact from mutations and karyotype. 457 molecularly-annotated patients were considered. Multivariable analysis identified circulating Blasts ≥2% (1 point), Leukocytes ≥13 x 109/L (1 point), and severe (2 points) or moderate (1 point) Anemia as preferred risk variables in developing a clinical risk Stratification Tool for overall survival (OS), acronymized to "BLAST": low-risk (0 points; median 63 months); intermediate-risk (1 point; median 28 months; HR 2.2, 95% CI 1.6-3.0), and high-risk (2-4 points; median 13 months; 5.4, 4.1-7.3); the corresponding 3/5 year OS rates were 68%/53%, 43%/18%, and 12%/1%. BLAST model performance (AUC 0.77/0.85 at 3/5-years) was shown to be comparable to that of the molecular CMML-specific prognostic scoring system (CMML-mol; AUC 0.73/0.75) and the international prognostic scoring system-molecular (IPSS-M; AUC 0.73/0.74). Multivariable analysis of mutations and karyotype identified PHF6MUT and TET2MUT as being "favorable" and DNMT3AMUT, U2AF1MUT, BCORMUT, SETBP1MUT, ASXL1MUT, NRASMUT, PTPN11MUT, RUNX1MUT, TP53MUT, and adverse karyotype, "unfavorable". Molecular information was subsequently encoded in a combined clinical-molecular risk model (BLAST-mol; AUC 0.80/0.86 at 3/5-years) that included the aforementioned BLAST clinical risk variables and a 3-tiered molecular risk score. BLAST and BLAST-mol were subsequently validated by two separate external cohorts. Independent risk factors for blast transformation included DNMT3AMUT, ASXL1MUT, PHF6WT, leukocytes ≥13 x 109/L, and ≥2% circulating or ≥10% bone marrow blasts. The current study proposes an easy to implement, globally applicable, and molecularly adaptive risk model for CMML.