ReviewCurrent treatment options in oncology2023
Application of Engineered Dendritic Cell Vaccines in Cancer Immunotherapy: Challenges and Opportunities.
Review in Current treatment options in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Lentiviral Dendritic Cell Vaccine Targeting Claudin-18.2 Elicits Potent Antitumor Immunity Against Gastric Cancer.Cancers · 2026Article
- Immune cell-based therapies for solid tumors, current challenges and therapeutic advances.Cell communication and signaling : CCS · 2025Review
- SLC16A3 (MCT4) expression in tumor immunity and Metabolism: Insights from pan-cancer analysis.Biochemistry and biophysics reports · 2025Article
- Immunological Effects of Proton Radiotherapy: New Opportunities and Challenges in Cancer Therapy.Cancer innovation · 2025Review
- Hydrogel-Based Vaccines: A Promising Approach for Cancer Immunotherapy.International journal of nanomedicine · 2025Review
- Trial watch: anticancer vaccination with dendritic cells.Oncoimmunology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
opinion statementThe primary objective of this study is to evaluate the effectiveness of cancer vaccines containing genetically modified dendritic cells (DCs) in inducing transformational immune responses. This paper sheds considerable light on DCs' function in advancing treatment techniques. This objective is achieved by thoroughly analyzing the many facets of DCs and their strategic integration into cancer treatment. Due to their role as immune response regulators, DCs can potentially enhance cancer treatment strategies. DCs have the potential to revolutionize immunotherapy, as shown by a comprehensive analysis of their numerous characteristics. The review deftly transitions from examining the fundamentals of preclinical research to delving into the complexities of clinical implementation while acknowledging the inherent challenges in translating DC vaccine concepts into tangible progress. The analysis also emphasizes the potential synergistic outcomes that can be achieved by combining DC vaccines with established pharmaceuticals, thereby emphasizing the importance of employing a holistic approach to enhance treatment efficacy. Despite the existence of transformative opportunities, advancement is hindered by several obstacles. The exhaustive analysis of technical complexities, regulatory dynamics, and upcoming challenges provides valuable insights for overcoming obstacles requiring strategic navigation to incorporate DC vaccines successfully. This document provides a comprehensive analysis of the developments in DC-based immunotherapy, concentrating on its potential to transform cancer therapy radically.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.