MétaCan
Menu
← Retour à la cohorte
Enregistrement W4415273737 · doi:10.3389/fimmu.2025.1719075

Editorial: Community series in immune responses against tumors - from the bench to the bedside, volume II

2025· editorial· en· W4415273737 sur OpenAlexaff
Chun Jing Wang, Shisan Bao

Notice bibliographique

RevueFrontiers in Immunology · 2025
Typeeditorial
Langueen
DomaineMedicine
ThématiqueCancer Immunotherapy and Biomarkers
Établissements canadiensInstitute of Infection and Immunity
Organismes subventionnairesnon disponible
Mots-clésImmune systemCancerImmune checkpointImmunotherapyAutoantibodyLung cancerBreast cancerAntibodyIpilimumab

Résumé

récupéré en direct d'OpenAlex

Reliable biomarkers continue to be pivotal in cancer management. Zhou et al. (2024a) analysed serum total immunoglobulin E (IgE) levels and lung cancer risk in a retrospective cohort of 675 patients and 1,193 healthy controls. Patients with lung cancer had significantly elevated IgE levels, with 47.9% above 100 IU/ml, which was associated with more advanced tumour stages, although progression-free and overall survival were not significantly different. This study identifies IgE as a possible diagnostic marker and draws attention to allergic immune pathways as therapeutic opportunities, particularly in older patients with smoking histories and altered monocyte counts [https://doi.org/10.3389/fimmu.2024.1637803 ].In a complementary study, Zhou et al. (2024b) examined a panel of seven tumour-associated autoantibodies (7-TAABs) in oesophageal squamous cell carcinoma (ESCC). The combined 7-TAAB assay improved sensitivity and diagnostic accuracy compared with single-antibody tests and was associated with clinical features such as tumour location, size, and TNM stage. These findings highlight how multi-antibody panels could support earlier detection and refined clinical risk assessment in ESCC [https://doi.org/10.3389/fimmu.2024.1518431 IF: 5.9 Q1 B2].A detailed characterisation of the tumour immune microenvironment (TIME) is essential for progress in immunotherapy. Guo et al. (2024) reviewed T cell subsets in cervical cancer, emphasising their functional diversity, spatial distribution, and interactions with other immune cells. Variations in T cell subsets across histological subtypes and disease stages influence anti-tumour responses and affect outcomes of therapies such as immune checkpoint blockade and HPV-directed vaccination [https://doi.org/10.3389/fimmu.2024.1612032 ]. Miranda et al. (2024) showed that local tumour ablation can trigger systemic immune effects, with cryoablation of primary breast cancers inducing an abscopal effect on distant lesions. These results suggest that combining local interventions with systemic immunomodulation can enhance anti-tumour responses, offering a promising route for combined therapeutic strategies [https://doi.org/10.3389/fimmu.2024.1498942 IF: 5.9 Q1 B2].Adding molecular depth, Zhou et al. ( 2025) investigated the CXCR7-TAGLN2 protein complex in papillary thyroid carcinoma (PTC), using an integrated approach that combined clinical tissue analysis, in vitro studies, and mechanistic experiments. Immunohistochemistry of 64 PTC and 24 benign thyroid tissues demonstrated markedly elevated CXCR7 and TAGLN2 expression, both of which were significantly linked to lymph node metastasis and positively correlated with each other. Co-localisation and co-immunoprecipitation assays confirmed their physical interaction. Functionally, silencing TAGLN2 suppressed PTC cell migration, while CXCR7 overexpression reversed this effect. Mechanistic studies revealed that TAGLN2 knockdown reduced phosphorylated Smad2 (p-Smad2) levels, implicating TAGLN2 in TGF-β/Smad2 pathway activity, while re-introduction of CXCR7 restored p-Smad2 expression. Together, these findings indicate that CXCR7 promotes invasion and metastasis through TAGLN2-mediated activation of TGF-β/Smad2 signalling. Identification of the CXCR7-TAGLN2 complex as a regulator of metastatic progression highlights a potential therapeutic target in PTC [https://doi.org/10.3389/fimmu.2025.1627419 ].Managing rare or complex cancers frequently requires personalised and multimodal approaches. Zeng et al. ( 2024) described a patient with synchronous lung adenocarcinoma and oesophageal squamous cell carcinoma who achieved survival beyond three years following chemotherapy, definitive chemoradiotherapy, stereotactic body radiation therapy (SBRT), and anti-PD-1 immunotherapy. This case illustrates the feasibility of integrating systemic and local therapies in patients with multiple primary malignancies while maintaining acceptable safety [https://doi.org/10.3389/fimmu.2024.1548176 ].Similarly, Xiong et al. ( 2024) reported a patient with advanced pulmonary large-cell neuroendocrine carcinoma (LCNEC) who received first-line chemotherapy followed by sovantinib and toripalimab. The patient achieved a partial response and a progression-free survival of 15.1 months, highlighting the promise of combining immune checkpoint inhibition with targeted agents in rare and aggressive cancers. Both cases reinforce the importance of tailoring therapeutic strategies to tumour biology and immune context [https://doi.org/10.3389/fimmu.2024.1527719 ].Vaccination approaches represent a growing frontier in cancer prevention and treatment. Asadollahi et al. ( 2024) designed a multi-neoepitope vaccine (MNEV) against non-small cell lung cancer (NSCLC) using reverse vaccinology and bioinformatics. In murine models, The studies in this volume reflect the breadth and depth of contemporary cancer immunology. From biomarker identification to mechanistic investigations, and from immune microenvironment analysis to innovative therapies and vaccines, these contributions demonstrate how molecular, cellular, and clinical perspectives converge to advance patient care. Mechanistic studies such as the CXCR7-TAGLN2 investigation show how dissecting specific molecular interactions can guide the rational development of targeted therapies and immune-based strategies. By linking molecular targets with immune-focused interventions and vaccine approaches, these works move experimental discoveries closer to clinical application and advance the goals of precision oncology.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,019
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,104

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,019
Méta-épidémiologie (sens strict)0,0050,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0040,002
Études des sciences et des technologies0,0020,003
Communication savante0,0070,006
Science ouverte0,0040,002
Intégrité de la recherche0,0120,016
Charge utile insuffisante (le modèle a refusé de juger)0,0310,020

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 Opus0,007
Tête enseignante GPT0,257
Écart entre enseignants0,249 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueFrontiers in Immunology→Même sujetCancer Immunotherapy and Biomarkers→Travaux en français237 207→