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1132 citation(s) found for "Yu, Yan".

Preliminary results from the randomized phase 2 study (1801 part 3B) of elraglusib in combination with gemcitabine/nab-paclitaxel (GnP) versus GnP alone in patients (pts) with previously untreated metastatic pancreatic ductal adenocarcinoma (mPDAC).
Shroff, Rachna T. , Carneiro, Benedito A. , Sahai, Vaibhav , Ploquin, Anne , Hiret, Sandrine , Percent, Ivor , Pernot, Simon , Kavan, Petr , Mulcahy, Mary F. , Mazar, Andrew P. , Fine, Gil D., Sahai, Vaibhav , Mahalingam, Devalingam , Ji, Yan , Coveler, Andrew L. , Cervantes, Andrés , LoConte, Noelle K. , Lopez, Charles D. , Carr, Ryan M , Giles, Francis Joseph , Bekaii‐Saab, Tanios

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 4006-4006

10.1200/jco.2025.43.16_suppl.4006 Get It

4006 Background: Elraglusib (9-ING-41) is a first-in-class inhibitor of GSK-3ß, which may mediate drug resistance, EMT, and damaged DNA and tumor immune response in advanced cancer. In pancreatic cancer models in mice, elraglusib combined with chemotherapy enhanced anti-tumor effects and survival. In a single-arm clinical study, elraglusib/GnP showed antitumor activity and prolonged survival in pts with mPDAC. Methods: Pts with previously untreated mPDAC were randomized 2:1 to GnP plus elraglusib 9.3 mg/kg IV once weekly or GnP in an open-label phase 2 study. The primary endpoint was 1-yr OS in the primary analysis set. Upon study completion, mOS will be the primary endpoint once survival distributions are compared after the 12-month follow-up using log-rank analysis. Secondary endpoints included DCR, ORR, mPFS, and TEAEs/TRAEs. The planned sample size was 207 evaluable pts (130 for elraglusib/GnP and 77 for GnP), assuming 1-yr OS of 55% with elraglusib/GnP and 35% with GnP to achieve 80% power with a chi-square test at a 2-sided 5% α. For OS, nonparametric log-rank test was used with statistical significance at p-value < 0.048. Cytokine/chemokine correlative biomarker assays were performed. The study completed enrollment in February 2024. Results: As of November 15, 2024 (preliminary data cut-off date), the primary analysis set included 155 pts in the elraglusib/GnP arm and 78 pts in the GnP arm, with 52.8% males and 57.5% ECOG PS 1. Median (range) CA 19-9 levels were 1568 U/mL (1 to 381,904 U/mL) in the elraglusib/GnP arm and 1590 U/mL (2 to 501,000 IU/mL) in the GnP arm. The 1-yr OS rate was 43.6% with elraglusib/GnP vs 22.5% with GnP (z-test p = 0.002); the mOS was 9.3 mo with elraglusib/GnP vs 7.2 mo with GnP (HR, 0.63; log rank p = 0.016; see Table). 38.1% of pts on elraglusib/GnP and 19.2% on GnP are censored, with the majority at > 10 months OS. Several biomarkers appear to be predictive for OS including IFNβ and PD-L1. The most common TRAE with elraglusib/GnP was grade 1-2 transient visual impairment in > 60% of patients (vs 9% with GnP). Grade ≥3 TEAEs occurred in 89.7% of pts on elraglusib/GnP and 80.8% on GnP. Most common grade ≥3 TEAEs with elraglusib/GnP (vs GnP) were neutropenia 51.6% (vs 29.5%), anemia 24.5% (vs 29.5%), and fatigue 16.1% (vs 5.1%). Conclusions: The preliminary results showed a statistically significant benefit for 1-yr OS and mOS and favorable trends for ORR and DCR with elraglusib/GnP over GnP, with manageable safety profile. The mOS for GnP is lower relative to MPACT and NAPOLI-3 but comparable to recent real-world meta-analyses, explained by advanced disease burden and higher mortality rate in the first 4 months in our study. Topline analysis (April 2025) and correlative biomarker analysis predictive for OS will be presented. Clinical trial information: NCT03678883 . Preliminary efficacy results. Elraglusib/GnPn=155 GnPn=78 1-year OS, %z-test p=0.002 43.6 22.5 mOS, moHR=0.63; log-rank p=0.016 9.3 7.2 Events, n (%) 96 (61.9) 63 (80.8) mPFS, moHR=0.91; p=NS 5.6 4.9 Events, n (%) 128 (82.6) 70 (89.7) DCR, % 42.6 33.3 ORR, n (%) 43 (27.7) 16 (20.5)
Retifanlimab with bevacizumab and hypofractionated radiotherapy to treat recurrent glioblastoma.
Karbhari, Nishika , Geyer, Susan M. , Chheda, Milan G. , Ruff, Michael W. , Kizilbash, Sani H. , Uhm, Joon H. , Neth, Bryan J. , Lehrer, Eric J. , Breen, William G. , Yan, Elizabeth , Mahajan, Anita , Brown, Paul D. , Campian, Jian , Neth, Byran J. , Kizilbash, Sani H , Karbhari, Nishika , Ulrich, Angela, Sherman, Wendy , Ensign, Shannon P. Fortin , Strowd, Roy E. , Sener, Uğur , Galanis, Evanthia

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: No page available

10.1200/jco.2025.43.16_suppl.tps2092 Get It

TPS2092 Background: Glioblastoma (GBM) is the most common primary brain malignancy in adults. GBM is universally recurrent and associated with dismal outcomes. Re-irradiation (reRT) is ideal for evaluating combination therapy for recurrent GBM (rGBM) due to its multifactorial mechanism of action, including downstream immunomodulatory activity. RT (especially multi-fraction) increases immunogenicity in preclinical models by promoting immune activation, immune migration, and antigen uptake. Additionally, a recent study demonstrated enhanced PD-L1 expression in the glioma tumor microenvironment (TME) following RT, and combining stereotactic RT with a PD-1 inhibitor improved survival in murine models. Retifanlimab is a humanized monoclonal anti-PD1 IgG4 antibody that received FDA approval for adults with metastatic or recurrent locally advanced Merkel cell carcinoma. Bevacizumab, an anti-VEGF antibody, is a treatment for radiation necrosis/cerebral edema with less immune suppression than corticosteroids. In a previous Phase 2 study, hypofractionated RT (HFRT), retifanlimab, and bevacizumab was associated with a 9-month overall survival (OS) rate of 71.4%. To demonstrate the efficacy of this regimen compared to HFRT and bevacizumab, we have designed a new randomized controlled Phase 2 trial. We hypothesize that combination reRT with retifanlimab will produce a more robust anti-tumor immune response and improve OS compared to reRT without retifanlimab. Methods: This is a multicenter, open-label, randomized, controlled Phase 2 study of retifanlimab, bevacizumab, and HFRT for adult patients with rGBM. Patients are randomized 1:1 to the experimental (bevacizumab + retifanlimab + HFRT) or control cohort (bevacizumab + HFRT). Key eligibility criteria include age ≥ 18 years, Karnofsky performance status ≥ 60, ≥ 4 months since administration of any prior bevacizumab, and dexamethasone dose ≤ 4 mg at the time of randomization. The primary endpoint is 9-month OS. Secondary endpoints include OS, progression-free survival, objective response rate, neurologic assessment by NANO criteria, and adverse events profile. Protocol treatment will continue up to two years, or until progression or intolerable toxicity. Survival follow up will continue every two months, up to four years. Seven of the planned 94 patients have been enrolled as of submission on 1/28/25. Clinical trial #: NCT06160206. Funding provided by Incyte. Clinical trial information: NCT06160206 .
Trends and outcomes by inpatient and outpatient infusion of axicabtagene ciloleucel (axi-cel) in the US for patients (pts) with relapsed/refractory large B-cell lymphoma (R/R LBCL).
Hemmer, Michael, Tees, Michael, Baird, John H. , McClune, Brian , Jacobson, Caron A. , Dahiya, Saurabh , Yan, Jiali , Kim, Jenny , Pizzi, E, Bonneh‐Barkay, Dafna, Pérez, Waleska S., Feng, Zhongyu, Pasquini, Marcelo C. , Furqan, Fateeha , Holter‐Chakrabarty, Jennifer , Locke, Frederick L. , Hsu, Hil , Lin, Yi

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 7023-7023

10.1200/jco.2025.43.16_suppl.7023 Get It

7023 Background: Axi-cel is an autologous chimeric antigen receptor (CAR) T-cell therapy approved for adults with R/R LBCL after ≥ 1 prior line of therapy (LoT). Adverse events, such as cytokine release syndrome (CRS) and neurologic events (NEs), may deter centers from using axi-cel in an outpatient (OPT) setting, though individual centers have observed comparable safety and effectiveness in OPT and inpatient (IPT) care (Furqan et al. Blood Adv . 2024). Here, we present safety and effectiveness outcomes of axi-cel by intention to treat in OPT and IPT settings in a multicenter real-world dataset. Methods: Pts receiving axi-cel for R/R LBCL in the US from 01/2021-07/2023 with data in the Center for International Blood and Marrow Transplant Research (CIBMTR) registry were eligible for analysis. Pts with prior allogeneic transplant or unknown intended care setting were excluded. Of potential pts, 119 OPT pts were identified from 29 centers where an increasing trend was seen (9.6% of pts in 2021 were OPT, 13.5% in 2022, 22.8% in 2023). Pts were matched to 119 IPT pts by propensity score matching on age, sex, comorbidities, lactate dehydrogenase (LDH), bulky disease, prior LoT, chemosensitivity, and infusion year (see table). Results: OPT pts had median age of 63 y (25% ≥ 70), 66% were male, and 67% had ≥ 1 comorbidity. Half (50%) had elevated LDH and 73% had 1 prior LoT. Bulky disease was reported in 3%, and 60% had chemo-resistant disease. Outcomes were analyzed at median follow-up of 12 mo. Safety and effectiveness outcomes were similar between OPT and IPT pts (see table). In multivariate analyses, no differences were found between intended care setting and CRS (odds ratio [OR] 1.09 [95% CI 0.51-2.35]), CRS Gr ≥ 3 (OR 0.57 [0.12-2.60]), NEs (OR 1.14 [0.65-2.00]), or NEs Gr ≥ 3 (OR 0.98 [0.48-2.00]). Among OPT pts, 24% and 50% did not require hospital admission within 30 d and 3 d, respectively. In pts aged ≥ 70 y, only any Gr NEs were higher in the OPT group. Conclusions: After matching on key factors that may be used to select pts for OPT infusion, outcomes were comparable between intended care settings. These findings corroborate prior results and support the consideration of axi-cel in appropriate OPT care settings. Outcomes between matched pts with R/R LBCL receiving axi-cel intended for OPT or IPT. OPT (n=119) a IPT (n=119) a CRS any Gr / Gr ≥ 3 83 (75−89) / 3 (<1−7) 83 (74−89) / 4 (1−10) NE any Gr / Gr ≥ 3 47 (38−57) / 19 (12−27) 46 (37−56) / 21 (14−30) Overall / complete response rates 78 (69−85) / 68 (59−76) 76 (67−83) / 62 (52-70) Duration of response @ 12 mo 64 (52−74) 69 (58−78) Progression-free survival @ 12 mo 53 (43−62) 53 (43−61) Overall survival @ 12 mo 71 (61−78) 72 (62−79) Non-relapse mortality @ 12 mo 6 (2−11) 4 (1−8) Hospital admission within 30 days of infusion / median duration (range), d 76 (67−83) / 9 (2−53) Not Applicable a Percent (95% CI) unless otherwise specified.
Protein N-Glycosylation Traits Combined With CA19-9 Accurately Distinguish Pancreatic Cancer Cases From Healthy Controls and Benign Pancreatic Diseases
Bogdański, Aleksander , Ballieux, Bart E.P.B. , Mesker, Wilma E. , Bi, Yan , Burgt, Yuri E. M. van der , Bogdanski, Aleksander M , Klatte, Derk C.F. , Leerdam, Monique E. van , Cobbaert, Christa M. , Hooft, Jeanin E. van , Clift, Kristin , Wuhrer, Manfred , Wallace, Michael B.

Pancreas | May 22, 2025 | Volume: 54 | Issue: 9 | Pages: e823-e830

10.1097/mpa.0000000000002517 | PMID 40403287 Get It

Objectives: New methods are needed to detect pancreatic ductal adenocarcinoma (PDAC) earlier to improve outcomes. We previously reported that a panel of protein N-glycosylation traits (NGTs) discriminated PDAC from healthy controls with an area under the curve (AUC) of 0.81–0.88. However, it remained unclear whether this panel accurately differentiates PDAC from other benign pancreatic disorders. Our study aims to evaluate the performance of the NGT panel in combination with CA19-9 in a diverse cohort, including PDAC cases, healthy controls, and controls with benign pancreatic disorders. Methods: Protein N-glycosylation profiles were determined in plasma samples using an in-house developed mass spectrometry assay. CA19-9 levels were measured using a routine immunoassay test. Results of total plasma NGTs and CA19-9 were evaluated separately as well as in combination. Logistic regression was performed to calculate odds ratios (ORs), AUC, sensitivity, and specificity to determine the performance of NGTs and CA19-9 in distinguishing PDAC from controls. Results: In total, 221 individuals were included: 45 (20.4%) with PDAC, and 176 (79.6%) controls (53 healthy and 123 with benign pancreatic disease). The AUC for differentiating PDAC from the total control cohort based on the combination of the NGT panel and CA19-9 was 0.94 (95% CI, 0.90–0.97), with a sensitivity of 0.89 (95% CI, 0.78–0.98) and specificity of 0.86 (95% CI, 0.81–0.91). Comparison of PDAC cases with healthy controls only resulted in an AUC of 0.96 (95% CI, 0.93–0.99), with a sensitivity of 0.84 (95% CI, 0.73–0.93) and specificity of 0.98 (95% CI, 0.94–1.00). Conclusions: Both plasma NGTs and CA19-9 distinguish PDAC from a diverse control cohort. The accuracy further improves when these readouts are combined, showing promise for future early detection methods.
Immunopipe: a comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline
Wang, Panwen , Yu, Yue , Zhang, Shuwen , Kocher, Jean‐Pierre , Wang, Junwen , Asmann, Yan W. , Lin, Yi, Li, Ying , Kocher, Jean-Pierre A , Wang, Junwen , Yu, Yue, Dong, Haidong , Sun, Zhifu , Zeng, Hu , Mondello, Patrizia

NAR Genomics and Bioinformatics | May 8, 2025 | Volume: 7 | Issue: 2 | Pages: No page available

10.1093/nargab/lqaf063 | PMID 40391086 Get It

Abstract Single-cell sequencing technologies provide us with information at the level of individual cells. Combining single-cell RNA-seq and single-cell TCR-seq profiling enables the exploration of cell heterogeneity and T-cell receptor repertoires simultaneously. Integrating both types of data can play a crucial role in enhancing our understanding of T-cell-mediated immunity and, in turn, facilitate the advancement of immunotherapy. Here, we present immunopipe, a comprehensive and flexible pipeline to perform integrated analysis of scRNA-seq and scTCR-seq data. In addition to the command line tool, we provide a user-friendly web interface for pipeline configuration and execution monitoring, benefiting researchers without extensive programming experience. With its comprehensive functionality and ease of use, immunopipe empowers researchers to uncover valuable insights from scRNA-seq and scTCR-seq data, ultimately advancing the understanding of immune responses and immunotherapy development.
JAB-3312, a Potent Allosteric SHP2 Inhibitor That Enhances the Efficacy of RTK/RAS/MAPK and PD-1 Blockade Therapies
Kang, Di , Wang, Yanping , Lin, Yiwei , Wee, Wen , Morgensztern, Daniel , Leventakos, Konstantinos , Bi, Chao , Ding, Yuli , Xiong, Jing , Yan, Man , Sun, Xin , Wang, Peng George , Ma, Cunbo , Wang, Yinxiang , Ma, Wen Wee , Wang, Peng , Ding, Yuli

Clinical Cancer Research | May 7, 2025 | Volume: 31 | Issue: 14 | Pages: 3019-3032

10.1158/1078-0432.ccr-24-3691 | PMID 40333694 Get It

Abstract Purpose: Recent advances have seen the development of targeted therapeutics against the receptor tyrosine kinase (RTK)/RAS/MAPK pathway, which, when aberrantly activated, drives the malignant transformation of many cancer indications. However, the efficacy of inhibitors targeting single molecules is dampened by pathway feedback activation and acquired drug resistance. We seek to evaluate the application of JAB-3312 (sitneprotafib), a potent inhibitor of SHP2, in RTK/RAS/MAPK pathway–targeted combination therapies. Furthermore, SHP2 plays a vital role in PD-1–mediated immunosuppression. The rational combination of JAB-3312 with PD-1 blocking therapies is also explored. Experimental Design: Biochemical and cellular assays were applied to evaluate the potency of JAB-3312 in SHP2 inhibition. Tumor cell lines and cell line– and patient-derived xenografts were used to test different combinations of JAB-3312 with KRASG12C, MEK, EGFR, and PD-1 inhibitors. Results: JAB-3312 produced potent in vitro inhibition of SHP2 activity and downstream ERK phosphorylation, with IC50 values of 1.44 nmol/L and 0.68 to 4.84 nmol/L, respectively. When used in combination, JAB-3312 significantly increased the antitumor activity of the KRASG12C inhibitor glecirasib in naïve and resistant models. The combination of JAB-3312 with MEK inhibitors significantly delayed RTK signaling reactivation and enhanced tumor growth inhibition in KRAS-mutated cancer models. The JAB-3312–osimertinib combination exhibited great efficacy in osimertinib-resistant non–small cell lung cancer models. Additionally, JAB-3312 enhanced the efficacy of PD-1 blockade therapies by promoting an antitumor microenvironment. Representative cases of patients who responded to the combination therapies from two ongoing clinical trials (NCT05288205 and NCT04720976) were reported. Conclusions: JAB-3312 in combination with RTK/RAS/MAPK or PD-1 blockade therapies is a promising strategy that warrants further clinical investigation.
3D‐Printed Microfluidic Platform for Creating Porous Nanofibrous Microspheres to Regulate Cell Response and Enhance Tissue Regeneration
Lee, Dong-Hee , Tran, Huy Quang , Sharma, Navatha Shree , Yan, Zishuo , Killeen, Amy C., Reinhardt, Richard A., Zhu, Wuqiang , Xie, Jingwei , Zhu, Wuqiang , Andrabi, Syed Muntazir , Xie, Jingwei

Small | May 2, 2025 | Volume: 21 | Issue: 41 | Pages: No page available

10.1002/smll.202502033 | PMID 40318101 Get It

Abstract Porous nanofibrous microspheres (PNMs) present a versatile and minimally invasive strategy for tissue regeneration, combining biomimetic morphology, tunable structure, and injectability. While self‐assembly and co‐axial electrospray are explored for PNM fabrication, these methods are limited in compositional versatility and production scalability. Here, a 3D‐printed microfluidic platform is presented that enables large‐scale fabrication of PNMs with precise control over size, pore architecture, and morphology. PNMs can be functionalized with bioactive molecules through UV crosslinking, enhancing their regenerative potential by promoting osteogenesis in human bone marrow stromal cells (hBMSCs), angiogenesis in human umbilical vein endothelial cells (HUVECs), and exerting anti‐inflammatory effects on macrophages. Subcutaneous implantation in rats demonstrates that PNMs support cell infiltration, minimize fibrosis, and facilitate tissue integration, achieving complete cell penetration and tissue incorporation within 14 days. These findings establish PNMs as versatile, scalable, and customizable platforms, ideal for applications as injectable drugs or cell carriers, as well as powders, offering promising solutions for wound healing and tissue regeneration.
Acalabrutinib Plus Bendamustine-Rituximab in Untreated Mantle Cell Lymphoma
Wang, Michael , Song, Yuqin, Jurczak, Wojciech, Kahl, Brad S. , Chu, Michael P., Kryachok, Iryna, Fogliatto, Laura, Cheah, Chan Y. , Morawska, Marta , Li, Yufu, Patti, Caterina , Forsyth, Cecily , Lesley, Robin, Ramadan, Safaa, Rule, Simon, Dreyling, Martin , investigators, for the ECHO, Cazap, Nicolás, Foncuberta, María Cecilia, Garate, Gonzalo, Gustavo, Jarchum, Pavlovsky, Miguel Arturo , Riveros, Dardo, Baker, Ross, Butler, Jason, Cannell, Paul , Cheah, Chan, Forsyth, Cecily, Giri, Pratyush, Johnston, Amanda, Lee, Denise , Lee, Hui‐Peng, Mapp, Sally, Roncolato, Fernando , Thant, Aung , Walker, Patricia, Doo, Nicole Wong, Demuynck, Hilde, Offner, Fritz , Hende, Vanessa Van, Vergote, Vibeke, Wu, Ka Lung , Chiattone, Carlos, Azevedo, Sergio de, Fogliatto, Laura, Fonseca, Ana, Hamerschlak, Nelson, Lazaretti, Nicolas, Rocha, Vanderson, Salvino, Marco, Santucci, Rodrigo, Schaan, Mariza, Scheliga, Adriana, Vieira, Garles Miller, Berinstein, Neil, Boutin, Mélina , Chu, Michael, Keating, Mary‐Margaret, Schattner, Ariah, Restrepo, Diego Villa, Cen, Xinan, Du, Xin, Feng, Ru, Gao, Sujun, Huang, Haiwen, Ji, Jie, Jin, Jie, Ke, Xiaoyan, Li, Dengju, Li, Fei, Li, Jianyong, Li, Junmin, Li, Yan, Li, Yufu, Li, Zhenyu, Lin, Li'e, Liu, Tingbo, Lv, Fangfang , Shuang, Yuerong, Sun, Lan, Sun, Xiuhua, Wang, Zhao, Wu, Huijing, Xi, Yaming, Xia, Ruixiang, Xue, Hongwei, Yang, Haiyan, Yi, Shuhua, Zhang, Cheng, Zhang, Huilai, Zhang, Mingzhi, Zhang, Qingyuan, Zhao, Xielan, Zhou, Hui, Hajek, Roman, Jindra, Pavel , Mayer, Jiri, Novak, Jan, Abraham, Julie, Bijou, Fontanet, Bouabdallah, Kamal , Cymbalista, Florence, Guilbert, Sophie, Laribi, Kamel, Rodon, Philippe, Decker, Thomas, Dreger, Peter, Dreyling, Martin, Hess, Georg, Lenz, Georg, Stilgenbauer, Stephan, Tummes, Dirk, Anargyrou, Konstantinos , Dimopoulos, Meletios-Athanassios, Kapsali, Eleni, Kyriakou, Despoina, Panayiotidis, Panayiotis, Pappa, Vasiliki , Stavroyianni, Niki, Cheng, Hoi Ching, Kwong, Yok-Lam, Lee, Harold, Ng, Ting Ying, Wong, Raymond, Borbényi, Zita , Illés, Árpád, Lázár, Zsolt, Nagy, Ágnes , Nagy, Zsolt, Schneider, Tamas, Avivi, Irit, Gurion, Ronit, Horowitz, Netanel, Ronson, Aaron, Arcaini, Luca, Boccomini, Carola, Ghia, Paolo, Luminari, Stefano, Plenteda, Caterina, Santoro, Armando, Zilioli, Vittorio Ruggero, Zinzani, Pier Luigi, Choi, Ilseung , Ennishi, Daisuke , Ichikawa, Satoshi, Ishikawa, Takayuki, Izutsu, Koji, Kato, Koji, Maruyama, Dai, Nagai, Hirokazu, Ota, Shuichi, Saito, Toko, Sakai, Rika, Suzuki, Ritsuro, Uoshima, Nobuhiko , Yano, Takahiro, Yoshida, Isao, Eom, Ki-Seong, Kim, Jin Seok, Kim, Seok Jin, Lee, Jung-Hee, Mun, Yeung Chul, Yoon, Sung Soo , Arreguin, Elsa Veronica Avila, Andrade, Adriana Dominguez, Almaguer, David Gómez, Vera, Maria Silvia Rivas, Anaya, Luis Solís, Berkahn, Leanne, Pemberton, Lucy, Simpson, David, Beltrán, Brady, Quintana, Shirely, Revilla, Jose Carlos, Vargas, Ernesto, Grosicki, Sebastian , Hałka, Janusz , Jedrzejczak, Wieslaw, Knopińska-Posłuszny, Wanda, Krzanowski, Jacek, Lech-Maranda, Ewa, Robak, Tadeusz, Rzepecki, Piotr , Wróbel, Tomasz, Borsaru, Gabriela, Ciuleanu, Tudor Eliade, Danaı̈la, Catalin, Lazaroiu, Mihaela, Alexeeva, Julia, Chistyakov, Valeriy, Manikhas, Georgy, Mikhailova, Natalia, Proydakov, Andrey, Volodicheva, Elena , Voloshin, Sergey, Bastos, Mariana, Cordoba, Raul, Codina, José , Gonzalez, Eva Maria, Marin, Ana, Panizo, Carlos, Rodriguez, Guillermo, Salar, Antonio, Sancho, Juan-Manuel, Velo, Jose A, Chiu, Chang-Fang, Hsiao, Liang-Tsai, Kuo, Ching-Yuan, Lin, Tung-Liang, Lysa, Tamila, Maslyak, Zvenyslava, Nogaieva, Larysa, Polenkov, Sergey, Usenko, Ganna, Agajanian, Richie, Anz, Bertrand, Chaudhry, Arvind, Chiu, Alden , Cultrera, Jennifer, D’Olimpio, James, Dunleavy, Kieron, Fanning, Suzanne, Flinn, Ian, Gabrail, Nashat, Gallinson, David, Goldenberg, Alec, Graf, Solomon, Grover, N., Hess, Brian, Hoffman, Marc, Isufi, Iris, Kahl, Brad, Kambhampati, Suman , Kirkel, Dean, Diaz, Guillermo Lazo, Levy, Moshe, Liu, Delong, Mead, Monica , Paludo, Jonas, Patel, Anjan, Peles, Shachar, Persky, Daniel, Portell, Craig, Rosenthal, Allison, Sano, Dahlia , Smith, Sonali , Smith, Stephen, Spurgeon, Stephen, Tache, Jason, Tsai, Michaela, Veltri, Lauren, Wang, Michael, Yimer, Habte, Bach, Quoc Khanh, Đỗ, Huyền Nga, Luu, Hung Vu, Khoa, Trọng, Phạm, Như Hiệp, Panizo, Carlos , Kriachok, Iryna , Kahl, Brad S , Paludo, Jonas , Cheah, Chan Yoon , Morawska, Marta , Sancho, Juan-Manuel , Forsyth, Cecily , Dreyling, Martin , Belada, David , Song, Yuqin , Paludo, Jonas , Fogliatto, Laura , Zhang, Jingyang , Lesley, Robin, Ramadan, Safaa Mahmoud , Garate, Gonzalo, Riveros, Dardo Alberto, Cannell, Paul , Cochrane, Tara , Giri, Pratyush, Mapp, Sally , Doo, Nicole Wong , Demuynck, H, Hende, Vanessa Van, Vergote, Vibeke K. J. , CHIATTONE, CARLOS SÉRGIO , Farias, João Samuel de Holanda , Fonseca, Ana Rita Da , Rocha, Vanderson , Oliveira, José Salvador Rodrigues de , Scheinberg, Phillip , Scheliga, Adriana , Vieira, Garles Miller Matias , Berinstein, Neil Lorne , Shuang, Yuerong , Hájek, Roman , Mayer, Jiřı́ , Bijou, Fontanet , Cymbalista, Florence, Delwail, Vincent , Genet, Philippe , Dreger, Peter , Heß, Georg , Lenz, Georg , Stilgenbauer, Stephan , Kapsali, Eleni , Katodritou, Eirini , Kyriakou, Despoina S, Panayiotidis, Panayiotis G. , Symeonidis, Argiris , Schneider, Tamas J., Avivi, Irit, Gurion, Ronit , Horowitz, Netanel A. , Arcaini, Luca , Boccomini, Carola , Luminari, Stefano , Santoro, Armando, Zilioli, Vittorio Ruggero , Zinzani, Pier Luigi , Fukushima, Kentaro , Izutsu, Koji , Maruyama, Dai , Tatetsu, Hiro , Kim, Sang‐A , Oh, Sung Yong , Arreguin, Elsa Ávila, Gómez‐Almaguer, David , Issa, Samar , Revilla, Jose C., Vargas, Ernesto, Lech-Maranda, Ewa, Robak, Tadeusz , Borsaru, Gabriela, Ciuleanu, Tudor–Eliade , Danaila, Catalin-Doru , Alexeeva, Julia, Briones, Javier , Salar, Antonio , Yuste, Victor Jimenez, Chen, Chien‐Yuan , Kuo, Ching‐Yuan, Anz, Bertrand, Cultrera, Jennifer L. , D’Olimpio, James, Dunleavy, Kieron , Gabrail, Nashat , Gallinson, David, Goldenberg, Alec S., Goy, Andre Henri , Graf, Solomon A. , Hess, Brian, Kirkel, Dean, Portell, Craig A. , Rosenthal, Allison , Stevens, Don, Veltri, Lauren Westfall , Yimer, Habte, Tran, Thanh Tung

Journal of Clinical Oncology | May 1, 2025 | Volume: 43 | Issue: 20 | Pages: 2276-2284

10.1200/jco-25-00690 | PMID 40311141 Get It

PURPOSE The combination of the Bruton tyrosine kinase inhibitor ibrutinib with bendamustine-rituximab for first-line treatment of mantle cell lymphoma (MCL) prolonged progression-free survival (PFS), but without improvement in overall survival (OS), likely because of toxicity. Acalabrutinib was shown to be efficacious and less toxic than ibrutinib in a head-to-head trial in chronic lymphocytic leukemia and therefore might lead to better outcomes in MCL. METHODS Patients 65 years and older with previously untreated MCL received acalabrutinib (100 mg twice daily) or placebo (until disease progression or unacceptable toxicity), plus six cycles of bendamustine (90 mg/m 2 once daily; days 1 and 2) and rituximab (375 mg/m 2 as a single dose; day 1) followed by rituximab maintenance in responding patients for 2 years. Crossover to acalabrutinib at disease progression was permitted. The primary end point was PFS per the independent review committee; overall response rate and OS were secondary end points. RESULTS In total, 598 patients were randomly assigned, with 299 in each arm. At a median follow-up of 49.8 months using the reverse Kaplan-Meier method, the median PFS was 66.4 months in the acalabrutinib arm and 49.6 months in the placebo arm (hazard ratio [HR], 0.73 [95% CI, 0.57 to 0.94]; P = .0160). Benefit was seen across all subgroups, including those with high-risk features. Overall response/complete response rates were 91.0%/66.6% and 88.0%/53.5% in the acalabrutinib and placebo arms, respectively. OS was not significantly different (HR, 0.86 [95% CI, 0.65 to 1.13]; P = .27). Grade 3 or greater adverse events were reported in 88.9% and 88.2% in the acalabrutinib and placebo arms, respectively. CONCLUSION The combination of acalabrutinib with bendamustine-rituximab significantly improved PFS. Clinical benefit of acalabrutinib with bendamustine-rituximab was achieved with manageable toxicity.
UNISOM: Unified Somatic Calling and Machine Learning-based Classification Enhance the Discovery of CHIP
Tian, Shulan , Jenkinson, Garrett , Ferrer, Alejandro Tiana, Yan, Huihuang , Morales‐Rosado, Joel A. , Wang, Kevin L. , Lasho, Terra L. , Yan, Benjamin B. , Baheti, Saurabh , Olson, Janet E. , Patnaik, Mrinal M. , Klee, Eric W. , Ferrer, Alejandro , Ferrer, Alejandro , Baughn, Linda B , Ding, Wei , Slager, Susan L , Patnaik, Mrinal , Lazaridis, Konstantinos N , Klee, Eric W , Olson, Janet E , Lasho, Terra L , Tian, Shulan , Morales-Rosado, Joel A , Baughn, Linda B. , Slager, Susan L. , Lazaridis, Konstantinos N.

Genomics, Proteomics & Bioinformatics | April 29, 2025 | Volume: 23 | Issue: 2 | Pages: No page available

10.1093/gpbjnl/qzaf040 | PMID 40300108 Get It

Abstract Clonal hematopoiesis (CH) of indeterminate potential (CHIP), driven by somatic mutations in leukemia-associated genes, confers increased risk of hematologic malignancies, cardiovascular disease, and all-cause mortality. In blood of healthy individuals, small CH clones can expand over time to reach 2% variant allele frequency (VAF), the current threshold for CHIP. Nevertheless, reliable detection of low-VAF CHIP mutations is challenging, often relying on deep targeted sequencing. Here, we present UNISOM, a streamlined workflow for enhancing CHIP detection from whole-genome and whole-exome sequencing data that are underpowered, especially for low VAFs. UNISOM utilizes a meta-caller for variant detection, in couple with machine learning models which classify variants into CHIP, germline, and artifact. In whole-exome sequencing data, UNISOM recovered nearly 80% of the CHIP mutations identified via deep targeted sequencing in the same cohort. Applied to whole-genome sequencing data from Mayo Clinic Biobank, it recapitulated the patterns previously established in much larger cohorts, including the most frequently mutated CHIP genes and predominant mutation types and signatures, as well as strong associations of CHIP with age and smoking status. Notably, 30% of the identified CHIP mutations had &lt; 5% VAFs, demonstrating its high sensitivity toward small mutant clones. This workflow is applicable to CHIP screening in population genomic studies. The UNISOM pipeline is freely available at https://github.com/shulanmayo/UNISOM and https://ngdc.cncb.ac.cn/biocode/tool/7816.