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Enregistrement W2316737215 · doi:10.1097/01.cot.0000291737.73063.d5

How Targeting Dendritic Cells Boosts Cancer Vaccine Research

2004· article· en· W2316737215 sur OpenAlexaboutno aff
Peggy Eastman

Notice bibliographique

RevueOncology Times · 2004
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueImmunotherapy and Immune Responses
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImmune systemAntigenCancerCancer vaccineCancer immunotherapyImmunologyCancer cellclone (Java method)VaccinationBiologyImmunotherapyCancer researchGeneGenetics

Résumé

récupéré en direct d'OpenAlex

BETHESDA, MD—An increased understanding of how dendritic cells can jump-start the immune response is making these cells an attractive, natural target for cancer vaccines, according to speakers here at the 18th Annual Meeting of the International Society for Biological Therapy of Cancer. Dendritic cells—rare white blood cells found in lymphoid tissue—are powerful immune activators that can initiate an immune response when they present antigens to T cells. Cancer vaccine research has shown that when normal cells turn into cancer cells, some of the antigens on their surface change, giving rise to the concept that the body's immune system could be stimulated to fight these altered antigens as non-self. But because tumor antigens are weak antigens that have already escaped immune surveillance, part of the challenge in cancer vaccine development is to make them more recognizable as foreign by the immune system. The work on dendritic cell vaccines owes a debt to a pioneering cadre of cancer vaccine researchers including Steven A. Rosenberg, MD, PhD, Chief of the Surgery Branch at the National Cancer Institute and Editor-in-Chief of the Society's Journal of Immunotherapy. Identifying tumor-associated antigens, as Dr. Rosenberg has done, had long been a major goal of cancer vaccine research, say NCI officials. Today, after years of work trying to clone genes that code for cancer antigens, many cancer-associated antigens have been identified and characterized. Making dendritic cell vaccines involves collecting precursors of the cells from the patient's blood, combining them with cancer antigens in the laboratory, and reinfusing them back into the patient. The patient numbers are still small, but early trials in humans have shown the safety of cancer antigen-loaded dendritic cells as well as some clinical and immune responses,” said Jacques Banchereau, PhD, Director of the Baylor Institute for Immunology Research. However, he added, since there are different subsets of dendritic cells, many issues remain to be addressed, including the choice of the dendritic cell subset to be administered as therapy and the way to generate it. Recent Melanoma Trial In a recent clinical trial, Dr. Banchereau and his colleagues vaccinated 18 Stage IV melanoma patients with dendritic cells loaded with six antigens: influenza matrix peptide (Flu-MP); KLH; and peptides derived from four known melanoma antigens—MART-1/Melan A, gp100, tyrosinase, and MAGE-3. A single vaccination with the multiple antigen-loaded dendritic cells produced the following immune responses: KLH-specific responses in six patients; Flu-MP-specific responses in eight patients; and tumor-specific reactions to one or more melanoma antigens in five patients. None of these five patients showed early disease progression. Analysis at 10 weeks (after four vaccinations) showed an immune response to control (non-melanoma) antigens in 16 of 18 patients. An enhanced immune response to one or more melanoma antigens was seen in these 16 patients. The two patients who failed to respond to vaccination had rapid progression of their tumors, Dr. Banchereau noted. Six of seven patients with immunity to two or fewer melanoma antigens had progressive disease 10 weeks after their entry into the study, in contrast to tumor progression in only one of 10 patients with immunity to more than two melanoma antigens. Overall tumor survival data from the time of entry into the study showed that 12 of 18 patients were alive at year one, and nine of 18 patients were alive at year two. Overall survival from the time of entry into the study as well as the time to disease progression were related to the level of vaccine-specific immune responses detected at 10 weeks (after the initial four injections), Dr. Banchereau reported. Critical in Antibody Response Based on his research experience with dendritic cell vaccines thus far, Dr. Banchereau said that dendritic cells appear to be critical in the antibody response, and should be targeted in the development of cancer vaccines. Dendritic cell cancer vaccines may clearly be of benefit to patients who cannot be cured by conventional chemotherapy, said David E. Spaner, MD, PhD, of the Advanced Therapeutics Program at the University of Toronto's Department of Medicine and Toronto-Sunnybrook Regional Cancer Center. But one problem with current vaccines—which use tumor antigens that are also self-antigens—is that vaccine-generated immune responses are generally too weak to be maintained long enough for efficacy. To get around this problem, Dr. Spaner and his colleagues administered the anti-viral cytokine interferon at high doses for one month to boost the immune response in seven high-risk melanoma patients who had previously been treated with a vaccine incorporating the melanoma antigen gp100. High-dose interferon recalled gp100-reactive T cells in the four patients who had shown transient immunological vaccine responses, but not in the remaining patients in whom a previous vaccine response was not detectable, Dr. Spaner said. In two of the patients who responded, treatment with high-dose interferon led to the disappearance of metastatic melanoma lesions, even though interferon had been used therapeutically before vaccination with the anti-melanoma vaccine. The vaccine-triggered immune response was highly specific; only the population of gp100-reactive T cells recalled by high-dose interferon was able to kill gp100-expressing tumor targets, he noted. From this research, Dr. Spaner has concluded that “high-dose interferon recalls previously activated tumor-reactive T cells that are able to become potent killers—possibly by regulating the expression of co-stimulatory molecules on residual tumor cells.” In addition, he said, using high-dose interferon suggests “a strategy to maintain anti-tumor responses initiated by cancer vaccines.” Theoretically, dendritic cell vaccines will be as powerful as the antigens which they present to T cells. The more potent the antigen, the more powerful the immune response; conversely, the weaker the antigen, the weaker the cancer patient's immune defense. Identification of 5 Genes Overexpressed in Invasive Breast Cancer Laszlo Radvanyi, PhD, a Cancer Vaccine Program scientist at Aventis Pasteur Ltd. in Toronto, and his colleagues are working to discover and characterize new and more powerful immune-stimulating antigens that might be used for vaccination against breast cancer. He reported on a successful cancer antigen discovery program that has identified five new genes that are overexpressed in invasive breast cancer. These new genes could potentially be used in the development of breast cancer vaccines, he noted. Dr. Radvanyi and his co-workers screened RNA from more than 54 fresh tumor biopsies using gene-chip based profiling, and compared the cancerous RNA to RNA isolated from more than 150 normal tissues and cells. From this analysis, the researchers discovered five novel genes that are specifically overexpressed in breast cancer, which they named BFA4, BFA, BCZ4, BFY3, and BCY1. Further laboratory research on BFA4 revealed that it was markedly immunoreactive. When activated T cells were generated, they were able to kill peptide-loaded target cells and breast cancer cell lines expressing BFA4. Similar results were also seen with peptides of the other four new target genes, said Dr. Radvanyi. From this work, he concluded that vaccines combining BFA4 and other tumor-associated antigens in multi-antigenic vectors may be “a useful immunization approach, inducing more potent T-cell responses targeting breast tumors in a wider range of patients than is attainable with antigens currently being used.”

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,475
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,330
Écart entre enseignants0,304 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2004
Routes d'admission1
Résumé présentoui

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