Abstract B020: A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness

Abstract Introduction: The standard clinical assessment for treatment response of lymphoma currently relies on periodic functional imaging examinations. In this prospective study, we utilized a blood-based multi-omics test, SeekInClarity, to evaluate treatment response and predict patient outcomes in the major types of lymphoma. Methods: 116 patients with various lymphoma subtypes were recruited from two clinical centers: The First Affiliated Hospital of Zhengzhou University and Sun Yat-sen University Cancer Center. Blood samples were collected at pre- treatment (baseline) and after two cycles of treatment (landmark) for SeekInClarity analysis, which integrated shallow whole-genome sequencing (sWGS) data of circulating-free DNA (cfDNA), including copy number aberrations (CNA) and fragment size (FS), with seven protein markers. The molecular tumor burden (MTB) score was calculated with SeekInClarity to assess the therapeutic efficacy of patients. Results: At 95.2% specificity, cancer signals were detected in 74.1% (86/116) of patients at baseline. Higher MTB scores were associated with advanced tumor stages, with MTB+ ratios of 31.8%, 63.6%, 84.6%, and 91.2% for stage I, II, III, and IV, respectively. After two cycles of treatment, patients with MTB+ status exhibited significantly poorer progression-free survival (PFS) (HR: 0.13, 95% CI, 0.05-0.33, P < 0.001) and overall survival (OS) (HR: 0.24, 95% CI, 0.06-0.97, P < 0.05) compared to MTB- patients. These trends were consistent across stages, subtypes, and treatment regimens. Traditional biomarkers, lactate dehydrogenase (LDH) and β2-microglobulin (B2M), showed no OS difference between high and low expression groups. The disease progression (PD) rate was 5.2 times higher in the MTB+ group (41.5%) than in the MTB- group (8.0%, P < 0.001), outperforming LDH (1.1 times, 20.7% vs 18.1%, P = 0.15) and B2M (3.1 times, 43.8% vs 14.0%, P = 0.02). All 116 patients, except four with stable disease, were classified as partial or complete response based on imaging at the landmark analysis. However, 13 patients experienced disease progression within six months after treatment. Notably, six (46.2%) were identified earlier through MTB reduction at the landmark. Greater MTB reduction at landmark associated with better OS (P<0.05). Multivariate Cox regression analysis confirmed MTB reduction at landmark as an independent prognostic indicator for PFS, with low reduction indicating a significant increase in disease progression (HR: 0.11, 95% CI: 0.03-0.42, P < 0.001), while other clinical parameters were not significant. Conclusions: This study confirms the clinical utility of SeekInClarity in evaluating lymphoma treatment responses. Reductions in MTB during treatment are associated with patient survival and can predict therapeutic outcomes. Furthermore, post-treatment MTB status after two cycles is an independent prognostic indicator for both PFS and OS. Citation Format: Mao Mao, Wang Xin hua, Li Zhi ming, Chang Yu, Li Shi yong, Wu Wei, Chang Fang yuan, Chang Yin yin, Zhu Dan dan, Zhang Ming zhi. A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B020.

Authors

Institutions

Publication Details

Journal
Clinical Cancer Research
Published
2024-11-13
DOI
https://doi.org/10.1158/1557-3265.liqbiop24-b020
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract B020: A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness

Wei Wu, Li Zhi ming, Zhang Zhi, Yuan Cheng et al.
1 links
Clinical Cancer Research
Lymphoma Diagnosis and Treatment
article

Abstract B020: A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness

Wei Wu, Li Zhi ming, Zhang Zhi, Yuan Cheng, Yong Li, Hua Wang, Chong Yin, Dan Zhang, Yu Chang, Mao Mao
article en

Abstract

Abstract Introduction: The standard clinical assessment for treatment response of lymphoma currently relies on periodic functional imaging examinations. In this prospective study, we utilized a blood-based multi-omics test, SeekInClarity, to evaluate treatment response and predict patient outcomes in the major types of lymphoma. Methods: 116 patients with various lymphoma subtypes were recruited from two clinical centers: The First Affiliated Hospital of Zhengzhou University and Sun Yat-sen University Cancer Center. Blood samples were collected at pre- treatment (baseline) and after two cycles of treatment (landmark) for SeekInClarity analysis, which integrated shallow whole-genome sequencing (sWGS) data of circulating-free DNA (cfDNA), including copy number aberrations (CNA) and fragment size (FS), with seven protein markers. The molecular tumor burden (MTB) score was calculated with SeekInClarity to assess the therapeutic efficacy of patients. Results: At 95.2% specificity, cancer signals were detected in 74.1% (86/116) of patients at baseline. Higher MTB scores were associated with advanced tumor stages, with MTB+ ratios of 31.8%, 63.6%, 84.6%, and 91.2% for stage I, II, III, and IV, respectively. After two cycles of treatment, patients with MTB+ status exhibited significantly poorer progression-free survival (PFS) (HR: 0.13, 95% CI, 0.05-0.33, P < 0.001) and overall survival (OS) (HR: 0.24, 95% CI, 0.06-0.97, P < 0.05) compared to MTB- patients. These trends were consistent across stages, subtypes, and treatment regimens. Traditional biomarkers, lactate dehydrogenase (LDH) and β2-microglobulin (B2M), showed no OS difference between high and low expression groups. The disease progression (PD) rate was 5.2 times higher in the MTB+ group (41.5%) than in the MTB- group (8.0%, P < 0.001), outperforming LDH (1.1 times, 20.7% vs 18.1%, P = 0.15) and B2M (3.1 times, 43.8% vs 14.0%, P = 0.02). All 116 patients, except four with stable disease, were classified as partial or complete response based on imaging at the landmark analysis. However, 13 patients experienced disease progression within six months after treatment. Notably, six (46.2%) were identified earlier through MTB reduction at the landmark. Greater MTB reduction at landmark associated with better OS (P<0.05). Multivariate Cox regression analysis confirmed MTB reduction at landmark as an independent prognostic indicator for PFS, with low reduction indicating a significant increase in disease progression (HR: 0.11, 95% CI: 0.03-0.42, P < 0.001), while other clinical parameters were not significant. Conclusions: This study confirms the clinical utility of SeekInClarity in evaluating lymphoma treatment responses. Reductions in MTB during treatment are associated with patient survival and can predict therapeutic outcomes. Furthermore, post-treatment MTB status after two cycles is an independent prognostic indicator for both PFS and OS. Citation Format: Mao Mao, Wang Xin hua, Li Zhi ming, Chang Yu, Li Shi yong, Wu Wei, Chang Fang yuan, Chang Yin yin, Zhu Dan dan, Zhang Ming zhi. A blood-based multi-omics test for early evaluation of lymphoma treatment effectiveness [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B020.

Clinical Cancer ResearchVol. 30(21_Supplement)
Sun Yat-sen University (CN), Yonsei University (KR), Sun Yat-sen University Cancer Center (CN), First Affiliated Hospital of Zhengzhou University (CN)
No poverty
Openalex Percentile: Top 67%
Lymphoma Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.