Whole genome sequencing revealed microbiome in lung adenocarcinomas presented as ground-glass nodules
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Emerging evidence has suggested that dysbiosis of the microbiota may play vital roles in tumorigenesis. However, the interplay between the microbiome and lung cancer remains undetermined. In this study, we characterize the microbiome in the early stage of lung cancer, which presented as ground-glass nodules (GGNs). METHODS: We sequenced the whole genomes from 10 GGN lesions and 5 adjacent normal lung tissue samples. After being filtered with human genome sequences, the sequence reads were mapped to prokaryotic genomes refSeq and non-redundant protein database for taxa and gene functions profiling, respectively. RESULTS: Mycobacterium, Corynebacterium, and Negativicoccus were the core microbiota found in all GGNs and the normal tissue samples. The microbiota composition did not show significant difference between GGNs and normal tissues except the adenocarcinoma (AD) (P=0.047). A significant β diversity in microbiome gene functions was found among different patients. Two individual gene functions, the Secondary Metabolism (1.32 fold with P=0.01) and the Serine Threonine protein kinase (4.23 fold, P<0.001), were significantly increased in GGNs over normal tissue samples. CONCLUSIONS: This study helps shed light on the implication of the microbiome in early stage lung cancer, which encourages the further study and development of innovative strategies for early prevention and treatment of lung cancer.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it