Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy
Abstract Precision medicine in less‐defined subtype diffuse large B‐cell lymphoma (DLBCL) remains a challenge due to the heterogeneous nature of the disease. Programmed cell death (PCD) pathways are crucial in the advancement of lymphoma and serve as significant prognostic markers for individuals af...
Saved in:
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | Clinical and Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ctm2.70150 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832586832725934080 |
|---|---|
| author | Wei Hua Jie Liu Yue Li Hua Yin Hao‐Rui Shen Jia‐Zhu Wu Yi‐Lin Kong Bi‐Hui Pan Jun‐Heng Liang Li Wang Jian‐Yong Li Rui Gao Jin‐Hua Liang Wei Xu |
| author_facet | Wei Hua Jie Liu Yue Li Hua Yin Hao‐Rui Shen Jia‐Zhu Wu Yi‐Lin Kong Bi‐Hui Pan Jun‐Heng Liang Li Wang Jian‐Yong Li Rui Gao Jin‐Hua Liang Wei Xu |
| author_sort | Wei Hua |
| collection | DOAJ |
| description | Abstract Precision medicine in less‐defined subtype diffuse large B‐cell lymphoma (DLBCL) remains a challenge due to the heterogeneous nature of the disease. Programmed cell death (PCD) pathways are crucial in the advancement of lymphoma and serve as significant prognostic markers for individuals afflicted with lymphoid cancers. To identify robust prognostic biomarkers that can guide personalized management for less‐defined subtype DLBCL patients, we integrated multi‐omics data derived from 339 standard R‐CHOP‐treated patients diagnosed with less‐defined subtype DLBCL from three independent cohorts. By employing various machine learning algorithms, we pinpointed eight pivotal genes linked to PCD, specifically FLT3, SORL1, CD8A, BCL2L1, COL13A1, MPG, DYRK2 and CAMK2B. Following this, we established a Programmed Cell Death Index (PCDI) utilizing the aforementioned genes and amalgamated it with pertinent clinical characteristics to formulate a predictive nomogram model for prognosis. We observed a significant correlation between the PCDI, pre‐treatment circulating tumour DNA (ctDNA) burden, minimal residual disease (MRD) status and immune features. Furthermore, our research indicated that patients with elevated PCDI scores could potentially show resistance to conventional chemotherapy treatments, yet they might derive an advantage from alternative inhibitors targeting specific signalling pathways. Conclusively, leveraging these results, we have created an online analytical tool (https://xulymphoma.shinyapps.io/PCDI_pred/) designed for the prognostic prediction of patients with less‐defined subtype DLBCL. This tool facilitates the forecasting of outcomes for these patients, enhancing the precision of their clinical management. Key points Developing the Programmed Cell Death Index (PCDI) utilizing multiple machine learning algorithms for patients with less‐defined subtype diffuse large B‐cell lymphoma. The difference in clinical characteristics, circulating tumour DNA burden and immune profiling between patients with distinct PCDI groups. A potentially effective regimen was speculated for patients with high PCDI scores who tend to exhibit worse progression‐free survival. |
| format | Article |
| id | doaj-art-fca6c35468614d8aa3f736007ca9a8c1 |
| institution | Kabale University |
| issn | 2001-1326 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Clinical and Translational Medicine |
| spelling | doaj-art-fca6c35468614d8aa3f736007ca9a8c12025-01-25T04:00:38ZengWileyClinical and Translational Medicine2001-13262025-01-01151n/an/a10.1002/ctm2.70150Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsyWei Hua0Jie Liu1Yue Li2Hua Yin3Hao‐Rui Shen4Jia‐Zhu Wu5Yi‐Lin Kong6Bi‐Hui Pan7Jun‐Heng Liang8Li Wang9Jian‐Yong Li10Rui Gao11Jin‐Hua Liang12Wei Xu13Department of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe Third Affiliated Hospital of Nanjing Medical UniversityNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of Medical AffairsNanjing Geneseeq Technology IncNanjing ChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of EndocrinologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaDepartment of HematologyThe First Affiliated Hospital of Nanjing Medical University, Jiangsu Province HospitalNanjingChinaAbstract Precision medicine in less‐defined subtype diffuse large B‐cell lymphoma (DLBCL) remains a challenge due to the heterogeneous nature of the disease. Programmed cell death (PCD) pathways are crucial in the advancement of lymphoma and serve as significant prognostic markers for individuals afflicted with lymphoid cancers. To identify robust prognostic biomarkers that can guide personalized management for less‐defined subtype DLBCL patients, we integrated multi‐omics data derived from 339 standard R‐CHOP‐treated patients diagnosed with less‐defined subtype DLBCL from three independent cohorts. By employing various machine learning algorithms, we pinpointed eight pivotal genes linked to PCD, specifically FLT3, SORL1, CD8A, BCL2L1, COL13A1, MPG, DYRK2 and CAMK2B. Following this, we established a Programmed Cell Death Index (PCDI) utilizing the aforementioned genes and amalgamated it with pertinent clinical characteristics to formulate a predictive nomogram model for prognosis. We observed a significant correlation between the PCDI, pre‐treatment circulating tumour DNA (ctDNA) burden, minimal residual disease (MRD) status and immune features. Furthermore, our research indicated that patients with elevated PCDI scores could potentially show resistance to conventional chemotherapy treatments, yet they might derive an advantage from alternative inhibitors targeting specific signalling pathways. Conclusively, leveraging these results, we have created an online analytical tool (https://xulymphoma.shinyapps.io/PCDI_pred/) designed for the prognostic prediction of patients with less‐defined subtype DLBCL. This tool facilitates the forecasting of outcomes for these patients, enhancing the precision of their clinical management. Key points Developing the Programmed Cell Death Index (PCDI) utilizing multiple machine learning algorithms for patients with less‐defined subtype diffuse large B‐cell lymphoma. The difference in clinical characteristics, circulating tumour DNA burden and immune profiling between patients with distinct PCDI groups. A potentially effective regimen was speculated for patients with high PCDI scores who tend to exhibit worse progression‐free survival.https://doi.org/10.1002/ctm2.70150ctDNADLBCLliquid biopsylymphoma microenvironmentmachine learningprognostic nomogram |
| spellingShingle | Wei Hua Jie Liu Yue Li Hua Yin Hao‐Rui Shen Jia‐Zhu Wu Yi‐Lin Kong Bi‐Hui Pan Jun‐Heng Liang Li Wang Jian‐Yong Li Rui Gao Jin‐Hua Liang Wei Xu Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy Clinical and Translational Medicine ctDNA DLBCL liquid biopsy lymphoma microenvironment machine learning prognostic nomogram |
| title | Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| title_full | Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| title_fullStr | Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| title_full_unstemmed | Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| title_short | Revealing the heterogeneity of treatment resistance in less‐defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| title_sort | revealing the heterogeneity of treatment resistance in less defined subtype diffuse large b cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy |
| topic | ctDNA DLBCL liquid biopsy lymphoma microenvironment machine learning prognostic nomogram |
| url | https://doi.org/10.1002/ctm2.70150 |
| work_keys_str_mv | AT weihua revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT jieliu revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT yueli revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT huayin revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT haoruishen revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT jiazhuwu revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT yilinkong revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT bihuipan revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT junhengliang revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT liwang revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT jianyongli revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT ruigao revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT jinhualiang revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy AT weixu revealingtheheterogeneityoftreatmentresistanceinlessdefinedsubtypediffuselargebcelllymphomapatientsbyintegratingprogrammedcelldeathpatternsandliquidbiopsy |