Methionine-producing tumor micro(be) environment fuels growth of solid tumors
Bibliographic record
Abstract
Abstract Background Recent studies have uncovered the near-ubiquitous presence of microbes in solid tumors of diverse origins. Previous literature has shown the impact of specific bacterial species on the progression of cancer. We propose that local microbial dysbiosis enables certain cancer phenotypes through provisioning of essential metabolites directly to tumor cells. Methods 16S rDNA sequencing of 75 patient lung samples revealed the lung tumor microbiome specifically enriched for bacteria capable of producing methionine. Wild-type (WT) and methionine auxotrophic (metA mutant) E. coli cells were used to condition cell culture media and the proliferation of lung adenocarcinoma (LUAD) cells were measured using SYTO60 staining. Further, colony forming assay, Annexin V Staining, BrdU, AlamarBlue, western blot, qPCR, LINE microarray and subcutaneous injection with methionine modulated feed were used to analyze cellular proliferation, cell-cycle, cell death, methylation potential, and xenograft formation under methionine restriction. Moreover, C14-labeled glucose was used to illustrate the interplay between tumor cells and bacteria. Results/Discussion Our results show bacteria found locally within the tumor microenvironment are enriched for methionine synthetic pathways, while having reduced S-adenosylmethionine metabolizing pathways. As methionine is one of nine essential amino acids that mammals are unable to synthesize de novo, we investigated a potentially novel function for the microbiome, supplying essential nutrients, such as methionine, to cancer cells. We demonstrate that LUAD cells can utilize methionine generated by bacteria to rescue phenotypes that would otherwise be inhibited due to nutrient restriction. In addition to this, with WT and metA mutant E. coli, we saw a selective advantage for bacteria with an intact methionine synthetic pathway to survive under the conditions induced by LUAD cells. These results would suggest that there is a potential bi-directional cross-talk between the local microbiome and adjacent tumor cells. In this study, we focused on methionine as one of the critical molecules, but we also hypothesize that additional bacterial metabolites may also be utilized by LUAD. Indeed, our radiolabeling data suggest that other biomolecules are shared between cancer cells and bacteria. Thus, modulating the local microbiome may have an indirect effect on tumor development, progression, and metastasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".