MétaCan
Menu
Back to cohort
Record W4365144168 · doi:10.1101/2023.04.10.23288365

The genomic and evolutionary landscapes of anaplastic thyroid carcinoma

2023· preprint· en· W4365144168 on OpenAlexafffund
Peter YF. Zeng, Stephenie D. Prokopec, Stephen Y. Lai, Nicole Pinto, Michelle Chan‐Seng‐Yue, Roderick Clifton‐Bligh, Michelle D. Williams, Christopher J. Howlett, Paul Plantinga, Matthew J. Cecchini, Alfred K. Lam, Iram Siddiqui, Jianxin Wang, Ren Sun, John D. Watson, Reju Korah, Tobias Carling, Nishant Agrawal, Nicole A. Cipriani, Douglas W. Ball, Barry D. Nelkin, Lisa M. Rooper, Justin A. Bishop, Cathie Garnis, Ken Berean, Norman G. Nicolson, Paul Weinberger, Ying C. Henderson, Christopher M. Lalansingh, Mao Tian, Takafumi N. Yamaguchi, Julie Livingstone, Adriana Salcedo, Krupal Patel, Frederick S. Vizeacoumar, Alessandro Datti, Xi Liu, Yuri E. Nikiforov, Robert C. Smallridge, John A. Copland, Laura A. Marlow, Martin Hyrcza, Leigh Delbridge, Stan B. Sidhu, Mark Sywak, Bruce Robinson, Kevin Fung, Farhad Ghasemi, Keith Kwan, S. Danielle MacNeil, Adrian Mendez, David A. Palma, Mohammed Imran Khan, Mushfiq Hassan Shaikh, Kara M. Ruicci, Bret Wehrli, Eric Winquist, John Yoo, Joe S. Mymryk, James W. Rocco, David A. Wheeler, Thomas J. Giordano, John W. Barrett, William C. Faquin, Anthony J. Gill, Gary L. Clayman, Paul C. Boutros, Anthony C. Nichols

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsMcMaster UniversityLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of SaskatchewanUniversity of TorontoHospital for Sick ChildrenBC Cancer AgencyOntario Institute for Cancer ResearchLawson Health Research InstituteWestern University
FundersNational Cancer InstituteCanadian Institutes of Health ResearchUniversity of Texas MD Anderson Cancer CenterOntario Genomics InstituteLondon Health Sciences FoundationGovernment of OntarioFlorida Department of HealthInstituto Tecnológico de Costa RicaNational Institutes of HealthOntario GenomicsGenome CanadaGovernment of CanadaOntario Institute for Cancer ResearchMayo Clinic
KeywordsAnaplastic thyroid cancerThyroid carcinomaThyroidThyroid cancerMalignancyCancer researchBiologyAnaplastic carcinomaCancerPathologyMedicineGenetics

Abstract

fetched live from OpenAlex

Abstract Anaplastic thyroid carcinoma is arguably the most lethal human malignancy. It often co-occurs with differentiated thyroid cancers, yet the molecular origins of its aggressivity are unknown. We sequenced tumor DNA from 329 regions of thyroid cancer, including 213 from patients with primary anaplastic thyroid carcinomas and multi-region whole-genome sequencing. Anaplastic thyroid carcinomas have a higher burden of mutations than other thyroid cancers, with distinct mutational signatures and molecular subtypes. Specific cancer driver genes are mutated in anaplastic and differentiated thyroid carcinomas, even those arising in a single patient. We unambiguously demonstrate that anaplastic thyroid carcinomas share a genomic origin with co-occurring differentiated carcinomas, and emerge from a common malignant field through acquisition of characteristic clonal driver mutations.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.259
Teacher spread0.238 · 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 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

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuemedRxivSame topicThyroid Cancer Diagnosis and TreatmentFrench-language works237,207