Abstract 978: The potential role of microbiome in metastatic HNSCC
Bibliographic record
Abstract
Abstract HNSCC is 6th most common malignancy in the world. Most of HNSCC patients present with metastatic disease for which the survival rates for which remain low. Hypoxia serves as a bad prognostic factor in HNSCC correlating with worse survival and resistance to radiotherapy. We aimed to discover novel targets in metastatic HNSCC utilizing a unique collection of matched sets of cell lines derived from primary tumors and their respective metastatic sites. We carried out expression profiling across the lines to reveal potential common changes in gene expression between the cells derived from primary and metastatic sites in each patient as well as between normoxia and hypoxia. This analysis revealed significant changes in gene expression between the described conditions. Interestingly, beta defensin 2 was one of the genes that came up as overexpressed in metastasis as well as in cells cultured in hypoxia. Beta defensins are small cationic peptides that belong to the innate immune system and exhibit anti-microbial and anti-viral activities. Few studies reported their abnormal expression patterns in various cancers including HNSCC. While various novel anti-cancer therapies are currently being developed, early diagnosis remains one of the biggest challenges in cancer research. A discovery of soluble serum factors that can reliably detect the presence of primary or metastatic disease would serve as an extremely valuable tool in defining diagnosis and prognosis, predicting the response to treatment, and monitoring disease progression. We hypothesized the beta defensin 2 can serve as a serum biomarker of hypoxia and metastasis in HNSCC patients. Utilizing a commercial ELISA kit developed to detect and quantify levels of beta-defensin in human sera, we demonstrated that media collected from cell lines derived from metastases contained higher levels of beta-defensin compared to the cell lines derived from the primary tumors. Moreover, sera from HNSCC patients showed higher levels of beta defensin compared to the normal controls. As a next step we tested sera samples from 40 HNSCC patients out of which 20 had lymph node metastasis and 20 did not. While these data are still under analysis, preliminary results suggest that higher concentrations of beta-defensin correlate with the presence of lymph node metastasis in HNSCC patients. Utilizing 2 large chemical libraries that together contain about 4000 FDA approved drugs we performed high through put screening of the HNSCC lines described above in order to discover new drugs targeting head and neck cancer including drugs that target selectively metastatic cells compared to their primary tumor counterparts. Interestingly, many of the metastasis-specific drugs were antibiotics. Together with the findings described above, this data clearly suggests a connection between patient microbiome and the metastatic process in HNSCC. Citation Format: Maria Kondratyev, Aleksandra Pesic, Anna Dvorkin-Sheva, Marianne Koritzinsky, Bradly G. Wouters. The potential role of microbiome in metastatic HNSCC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 978.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".