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Molecular, cellular and systemic aspects of epithelial ovarian cancer and its tumor microenvironment

2022· review· en· W4223430921 on OpenAlexaff
Esther Schoutrop, Lidia Moyano‐Galceran, Stéphanie Lheureux, Jonas Mattsson, Kaisa Lehti, Hanna Dahlstrand, Isabelle Magalhaes

Bibliographic record

VenueSeminars in Cancer Biology · 2022
Typereview
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersRadiumhemmets ForskningsfonderCancerfondenVetenskapsrådetKreftforeningen
KeywordsDebulkingOvarian cancerTumor microenvironmentMedicineDiseaseCancerChemotherapyOncologyCancer researchInternal medicine

Abstract

fetched live from OpenAlex

Ovarian cancer encompasses a heterogeneous group of malignancies that involve the ovaries, fallopian tubes and the peritoneal cavity. Despite major advances made within the field of cancer, the majority of patients with ovarian cancer are still being diagnosed at an advanced stage of the disease due to lack of effective screening tools. The overall survival of these patients has, therefore, not substantially improved over the past decades. Most patients undergo debulking surgery and treatment with chemotherapy, but often micrometastases remain and acquire resistance to the therapy, eventually leading to disease recurrence. Here, we summarize the current knowledge in epithelial ovarian cancer development and metastatic progression. For the most common subtypes, we focus further on the properties and functions of the immunosuppressive tumor microenvironment, including the extracellular matrix. Current and future treatment modalities are discussed and finally we provide an overview of the different experimental models used to develop novel therapies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.313
Teacher spread0.288 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations169
Published2022
Admission routes1
Has abstractyes

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