ReviewBioengineered
Production of recombinant immunotherapeutics for anticancer treatment: the role of bioengineering.
Review in Bioengineered. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 24 citations in OpenAlex.
- Recombinant L-asparaginase from Stenotrophomonas maltophilia: a promising low-immunogenic anticancer agent.Microbial cell factories · 2025Article
- Recent Findings on Therapeutic Cancer Vaccines: An Updated Review.Biomolecules · 2024Review
- Highly efficient CD4+ T cell targeting and genetic recombination using engineered CD4+ cell-homing mRNA-LNPs.Molecular therapy : the journal of the American Society of Gene Therapy · 2021Article
- Mechanisms of sterile inflammation after intravitreal injection of antiangiogenic drugs: a narrative review.International journal of retina and vitreous · 2021Review
- Comparative analytical profiling of bevacizumab biosimilars marketed in India: a national control laboratory study.3 Biotech · 2020Article
- Antimicrobial activities and mechanism of action of Cymbopogon khasianus (Munro ex Hackel) Bor essential oil.BMC complementary medicine and therapies · 2020Article
- Apoptin as a Tumor-Specific Therapeutic Agent: Current Perspective on Mechanism of Action and Delivery Systems.Frontiers in cell and developmental biology · 2020Review
- Recombinant Immunotoxin Therapy of Glioblastoma: Smart Design, Key Findings, and Specific Challenges.BioMed research international · 2017Review
- Bioengineered non-coding RNA agent (BERA) in action.Bioengineered · 2016Review
- Article
- Recombinant Immunotoxin Therapy of Solid Tumors: Challenges and Strategies.Journal of basic and clinical medicine · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is one of the most important health problems because many cases are difficult to prevent. Cancer still has unknown mechanisms of pathogenesis, and its capacity to produce temporary or permanent damage, besides death, is very high. Although many anticancer therapies are available, finding a cure for cancer continues to be a difficult task. Thus, many efforts have been made to develop more effective treatments, such as immunotherapy based on a new class of tumor-specific products that are produced using recombinant DNA technology. These recombinant products are used with the main objectives of killing the tumor and stimulating immune cells to respond to the cancer cells. The principal recombinant products in anticancer therapy are immunostimulants, vaccines, antibodies, immunotoxins and fusion proteins. This review focuses on the general aspects of these genetically engineered products, their clinical performance, current advances and future prospects for this type of anticancer therapy.
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.