Advances in Multi-Omics Study of Prognostic Biomarkers of Diffuse Large B-Cell Lymphoma

Liang, Xiaojie; Song, Xinyu; Wu, Jialin; Liú, Dan; Lin, Bing-yu; Zhou, Hongsheng; Wang, Liang

doi:10.7150/ijbs.67892

Cited by 6 publications

(3 citation statements)

References 115 publications

(130 reference statements)

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“…However, some DLBCL patients do not respond to immunotherapy. Therefore, identifying biomarkers that predict immunotherapy response and selecting the most sensitive patients is critical to improving response rates [ 21 , 22 ]. Co-stimulatory molecules play an important role in the progression of various cancers, and their role in DLBCL remains to be explored [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features

Sheng,

Li,

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features

Sheng,

Li,

et al. 2023

Heliyon

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“… 153 Integration of various omics information is expected to be valuable in guiding targeted cancer therapy. 156 Moreover, there have been many successful examples in finding cancer biomarkers by multi‐omics, for example, diffuse large B‐cell lymphoma, 157 ovarian cancer, 158 and pancreatic cancer. 159 In addition to the application in the discovery of tumor or cancer‐related disease biomarkers, multi‐omics is also applied to find biomarkers for other diseases, such as stroke, 160 obesity, 161 cardiovascular diseases, 162 , 163 severe COVID‐19, 164 , 165 , 166 Alzheimer's disease, 167 diabetes, 168 obstructive sleep apnea, 169 and so on.…”

Section: Applications Of Multi‐omics In Human Diseasesmentioning

confidence: 99%

Applications of multi‐omics analysis in human diseases

Chen

Wang

Pan

et al. 2023

MedComm

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Multi‐omics usually refers to the crossover application of multiple high‐throughput screening technologies represented by genomics, transcriptomics, single‐cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi‐omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi‐omics. This review outlines the existing technical categories of multi‐omics, cautions for experimental design, focuses on the integrated analysis methods of multi‐omics, especially the approach of machine learning and deep learning in multi‐omics data integration and the corresponding tools, and the application of multi‐omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open‐source analysis tools and databases, and finally, discusses the challenges and future directions of multi‐omics integration and application in precision medicine. With the development of high‐throughput technologies and data integration algorithms, as important directions of multi‐omics for future disease research, single‐cell multi‐omics and spatial multi‐omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi‐omics medical research.

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“…Recently, genetic and lymphoma microenvironment (LME) subtypes of DLBCL demonstrated prognostic significance and therapeutic implications [ 8 ]. Whole exome and genome sequencing were screened in 223 patients, including 124 FINE, 70 RES and 29 RET subtypes.…”

mentioning

confidence: 99%

Dynamic change of soluble interleukin-2 receptor distinguished molecular heterogeneity and microenvironment alterations in diffuse large B-cell lymphoma

Huo

Wang

et al. 2022

Biomark Res

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Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoma with variable clinical outcomes and prediction of prognosis remains important for long-term remission. We performed serial serum soluble interleukin-2 receptor (sIL-2R) measurement pretreatment and before each cycle of the treatment in 599 patients with de novo DLBCL. Genomic and transcriptomic features were analyzed by 223 DNA- and 227 RNA-sequencing, respectively. Applying the cut-off value to sIL-2R pretreatment and cycle 2 (C2) level, patients were classified into FINE subtype (pretreatment low level) with good prognosis, RES subtype (pretreatment high level and C2 low level) with intermediate prognosis, and RET subtype (pretreatment high level and C2 high level) with poor prognosis, independent of International Prognostic Index. In “others” genetic subtype, dynamic change of sIL-2R showed prognostic significance and genetic features. Compared with FINE subtype, RES subtype had increased ARID1A and MYD88 mutations, and RET subtype had increased KMT2D, LYN and SOCS1 mutations. RES and RET subtypes showed significant enrichment in oncogenic pathways, such as ERK, NF-κB, JAK-STAT, and immune-associated pathways. As for tumor microenvironment, RES subtype exhibited increased recruiting activity of CD8 + T, T helper 1, and natural killer cells, and RET subtype with increased recruiting activity of CD4 + T and regulatory T cells in silico. There was a positive correlation between transcripts of IL-2R and immune checkpoint expressions including PD-1 and CTLA-4. Our findings identified that dynamic change of sIL-2R, with this simple and easy detection method in peripheral blood, had long-term prognostic effect and specific relation to microenvironment alterations in DLBCL.

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Advances in Multi-Omics Study of Prognostic Biomarkers of Diffuse Large B-Cell Lymphoma

Cited by 6 publications

References 115 publications

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features

Prognostic and immunological characterization of diffuse large B-cell lymphoma evaluated by co-stimulatory molecular-related features

Applications of multi‐omics analysis in human diseases

Dynamic change of soluble interleukin-2 receptor distinguished molecular heterogeneity and microenvironment alterations in diffuse large B-cell lymphoma

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