Evidence map›Paper›PMID 40592237›Full record

ReviewNeoplasia (New York, N.Y.)2025

New horizons in B-cell lymphoma immunotherapy: From immune checkpoints to precision medicine.

RuiXin Zheng, YuXiao Li, KaiXin Shi, YuanYuan Pan, KaiYi Liu, JinCheng Song, Li Li

Abstract readReview
In one paragraph

Review in Neoplasia (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

RuiXin ZhengDepartment of Hematology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
YuXiao LiDepartment of Hematology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
KaiXin ShiDepartment of Hematology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
YuanYuan PanYiwu Central Hospital, Jinhua, People's Republic of China.
KaiYi LiuDepartment of Hematology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
JinCheng SongDepartment of Oncology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China.
Li LiDepartment of Hematology, The Second Hospital of Dalian Medical University, Dalian, People's Republic of China. Electronic address: lilydlmu@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

B-cell lymphoma, a malignancy in hematology with high heterogeneity, has its genesis and progression intricately associated with immune system regulation. Over the past three decades, transformative breakthroughs in B-cell malignancy investigations have emerged through paradigm-shifting molecular discoveries. Nevertheless, numerous hurdles persist in attaining a comprehensive understanding and effective treatment of this disease. Novel chemotherapeutic strategies demonstrate promising potential in B-cell lymphoma management, particularly through targeting immune checkpoints such as PD-1 (Programmed Cell Death Protein 1), LAG-3 (Lymphocyte-activation Gene 3), TIM-3 (T-cell Immunoglobulin and Mucin-domain containing-3), and TIGIT (T-cell Immunoreceptor with Ig and ITIM Domains) play pivotal regulatory roles within the immune system. These molecules critically orchestrate immune cell activation dynamics, proliferative capacity, and effector functions, thereby preserving immunological homeostasis. Deciphering the functional architecture of co-inhibitory checkpoints (e.g., PD-1/CTLA-4) in lymphomagenesis serves dual imperatives: deconstructing tumor immune evasion programs while establishing conceptual frameworks for precision immunotherapeutics development. PD-1 engagement with PD-L1/PD-L2 impairs T lymphocyte activation, facilitating tumor immune evasion. Deciphering these molecular processes enables therapeutic agents to employ targeted blockade strategies to restore antitumor immunity in lymphomas. Moreover, in-depth research on these checkpoints holds great promise for the discovery of novel biomarkers. These biomarkers may help predict responses to immunotherapy in lymphoma patients. This would enable clinicians to tailor personalized treatment plans for each patient, maximizing the therapeutic efficacy while minimizing unnecessary side-effects. Certain genetic signatures related to these immune checkpoints might be identified as predictors of a favorable response to PD-1 inhibitor-based immunotherapy. This analysis systematically deciphers the molecular interplay of PD-1/LAG-3/TIM-3/TIGIT immune checkpoint axes, delineating their regulatory dynamics in B-cell lymphomagenesis. It systematically summarizes the current research achievements, delves into the existing problems, and explores the future research directions. This approach seeks to advance dual contributions to fundamental science and clinical application in B-cell lymphoma immunotherapy, thereby facilitating therapeutic innovations while deepening mechanistic comprehension of disease pathogenesis. By doing so, it aims to provide valuable insights for both basic research and clinical translation in the field of B-cell lymphoma immunotherapy, ultimately enabling advancements in patient care and deeper insights into this multifaceted condition.

Indexed as

Immune Checkpoint InhibitorsImmunotherapyLymphoma, B-CellPrecision MedicineAnimalsBiomarkers, TumorHumansImmune Checkpoint ProteinsMolecular Targeted TherapyProgrammed Cell Death 1 ReceptorBiomarkers, TumorImmune Checkpoint InhibitorsImmune Checkpoint ProteinsProgrammed Cell Death 1 ReceptorB-Cell LymphomaImmunological CheckpointImmunosuppressantLAG-3PD-1TIGITTIM-3

Identifiers

PMID40592237
PMCPMC12271925

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.