Proteomic Changes in Cancer Cell Lines as a Result of Bacterial Infection
Bibliographic record
Abstract
Bacterial infections have been implicated in shaping the tumor microenvironment (TME), but their effects on cancer cell proteomes remain unexplored. In this study, we analyzed proteomic changes in melanoma (A375) and ovarian cancer (OVCAR3) cell line models following infection with Staphylococcus aureus strain USA300 or Salmonella enterica strain SL1344 using mass spectrometry-based label-free quantitative proteomics. Bacterial infection leads to widespread changes in host protein expression in the cancer cells, with levels of proteins involved in mitochondrial metabolism, RNA processing, and cellular stress response all increasing in relative abundance. In contrast, proteins involved in DNA repair, cytoskeletal structure, vesicle trafficking, and cell cycle regulation were consistently downregulated. The magnitude of the observed changes varied by the cancer cell type. Understanding these interactions may provide new directions for the role of bacteria in tumor progression and therapeutic resistance.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".