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Record W4318707292 · doi:10.3389/fonc.2023.1126924

Editorial: Revisiting seed and soil: A new approach to target hibernating dormant tumor cells

2023· editorial· en· W4318707292 on OpenAlexafffund
Angélica Santiago-Gómez, Dalit Barkan, Ann F. Chambers

Bibliographic record

VenueFrontiers in Oncology · 2023
Typeeditorial
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsWestern University
FundersIsrael Cancer AssociationUnited States-Israel Binational Science FoundationQueen's University BelfastQueen's UniversityChristie CharityIsrael Cancer Research Fund
KeywordsCancer researchMedicineOncologyInternal medicine

Abstract

fetched live from OpenAlex

Over hundred and thirty years have passed since Stephen Paget proposed his ‘Seed and Soil’ hypothesis about metastatic spreading (1). Since then, we have gained a better insight into the complexities of this multistep dispersal, but we are yet to fully comprehend the interactions governing the metastatic ecosystems to enable us to clinically prevent disease recurrence and, ultimately, cancer-related deaths. Despite the high inefficiency of the metastatic process (2), cancer patients often suffer late recurrences following five to thirty years of undetectable disease (3, 4). This clinical observation is due to the presence of disseminated tumour cells (DTCs) that escape early from the primary tumour and spread to distant organs. Once there, DTCs may initially lie in a dormant or hibernating state to later reawaken, resulting in incurable metastatic outgrowths (5, 6). Dormant DTCs persist in a non-proliferative but reversible arrest, and consequently are resistant to conventional therapies directed towards rapidly dividing cancer cells. Moreover, they adapt to the metastatic niche they reside in, evading the immune system and reactivating tumour-initiating abilities when the opportunity arises (7, Weidenfeld and Barkan) (see (7) for concept definitions to avoid terminology misconceptions). Therefore, metastatic dormancy represents a major clinical problem, as well as a novel window of opportunity to hamper metastatic relapse by interfering with the dormant cancer cell life cycle [key steps to control dormancy in (7)]. In this Research Topic, we revisited Paget’s hypothesis focusing on the dormant phase of metastatic progression. This 10-article collection provides an overview on recent advances in the dormancy field, including original research on organ-specific mechanisms driving the reawakening of DTCs; and comprehensive and exhaustive reviews about the microenvironmental regulation of dormancy and reawakening, cutting-edge technologies to study interactions with the metastatic microenvironment and innovative therapeutic strategies to clinically monitor and target this undetectable stage of metastatic disease.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.014
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0050.005
Open science0.0040.001
Research integrity0.0140.019
Insufficient payload (model declined to judge)0.0120.011

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 head0.013
GPT teacher head0.294
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations4
Published2023
Admission routes2
Has abstractyes

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