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Record W3041665519 · doi:10.1080/2162402x.2020.1792058

Complete and long-lasting clinical responses in immune checkpoint inhibitor-resistant, metastasized melanoma treated with adoptive T cell transfer combined with DC vaccination

2020· article· en· W3041665519 on OpenAlexaff
Tanja Lövgren, Maria Wolodarski, Stina L. Wickström, Ulrika Edbäck, Mette Wallin, Eva Martell, Katrin Markland, Pontus Blomberg, Maria Nyström, Andreas Lundqvist, Hans Jacobsson, Gustav Ullenhag, Per Ljungman, Johan Hansson, Giuseppe Masucci, Roger Tell, Isabel Poschke, Lars Adamson, Jonas Mattsson, Rolf Kiessling

Bibliographic record

VenueOncoImmunology · 2020
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersCancerföreningen i StockholmMedicinska ForskningsrådetKnut och Alice Wallenbergs StiftelseKommunfullmäktige, Stockholms StadStiftelsen för Strategisk Forskning
KeywordsMedicineImmunotherapyMelanomaCohortT cellInternal medicineAdoptive cell transferVaccinationOncologyImmune systemImmunologySurgeryCancer research

Abstract

fetched live from OpenAlex

F]-FDG PET/CT radiology was performed to evaluate clinical response, according to RECIST 1.1 (on the CT part). Immunological monitoring was performed by flow cytometry and T-cell receptor (TCR) sequencing. In the safety/optimization cohort, all patients had a mixed response or stable disease, but none durable. In the combination cohort, two patients experienced complete responses (CR) that are still ongoing (>36 and >18 months, respectively). In addition, two patients had partial responses (PR), one still ongoing (>42 months) with only a small bone-lesion remaining, and one of short duration (<4 months). One patient died early during treatment and did not receive DC. Long-lasting persistency of the injected TILs was demonstrated in blood. In summary, we report clinical responses by TIL therapy combined with DC vaccination in 4 out of 4 treated MM patients who previously failed ICI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.317
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations50
Published2020
Admission routes1
Has abstractyes

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