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Record W2991567593 · doi:10.1038/s41467-019-13460-3

Genomic and immune profiling of pre-invasive lung adenocarcinoma

2019· article· en· W2991567593 on OpenAlexfundno aff
Haiquan Chen, Jian Carrot‐Zhang, Yue Zhao, Haichuan Hu, Samuel S. Freeman, Su Jeong Yu, Gavin Ha, Alison M. Taylor, Ashton C. Berger, Lindsay Westlake, Yuanting Zheng, Jiyang Zhang, Aruna Ramachandran, Qiang Zheng, Yunjian Pan, Difan Zheng, Shanbo Zheng, Chao Cheng, Muyu Kuang, Xiaoyan Zhou, Yang Zhang, Hang Li, Ting Ye, Yuan Ma, Zhendong Gao, Xiaoting Tao, Han Han, Jun Shang, Ying Yu, Ding Bao, Yechao Huang, Xiangnan Li, Yawei Zhang, Jiaqing Xiang, Yihua Sun, Yuan Li, Andrew D. Cherniack, Joshua D. Campbell, Leming Shi, Matthew Meyerson

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
FundersNational Cancer InstituteNational Human Genome Research InstituteCanadian Institutes of Health ResearchNational Natural Science Foundation of ChinaShanghai Shen Kang Hospital Development CenterLUNGevity FoundationShanghai Municipal Health CommissionStand Up To CancerFudan University
KeywordsImmune systemProfiling (computer programming)AdenocarcinomaComputational biologyBiologyGene expression profilingGeneticsGeneComputer scienceGene expressionCancer

Abstract

fetched live from OpenAlex

Adenocarcinoma in situ and minimally invasive adenocarcinoma are the pre-invasive forms of lung adenocarcinoma. The genomic and immune profiles of these lesions are poorly understood. Here we report exome and transcriptome sequencing of 98 lung adenocarcinoma precursor lesions and 99 invasive adenocarcinomas. We have identified EGFR, RBM10, BRAF, ERBB2, TP53, KRAS, MAP2K1 and MET as significantly mutated genes in the pre/minimally invasive group. Classes of genome alterations that increase in frequency during the progression to malignancy are revealed. These include mutations in TP53, arm-level copy number alterations, and HLA loss of heterozygosity. Immune infiltration is correlated with copy number alterations of chromosome arm 6p, suggesting a link between arm-level events and the tumor immune environment.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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

Citations277
Published2019
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicCancer Genomics and DiagnosticsFrench-language works237,207