Abstract 4006: MicroRNA footprints of circulating tumor cells in patients with non-small cell lung cancer
Bibliographic record
Abstract
Abstract Purpose: MicroRNAs (miRNAs) are being investigated as stable, non-invasive, circulating biomarkers for detecting human disease, including cancer. We sought to determine whether select, circulating miRNAs can define a “footprint” for circulating tumor cells (CTCs) in the blood of lung cancer patients. Methods: We analyzed plasma from patients with non-small cell lung cancer (NSCLC) for nine candidate miRNAs using Taqman™ qRT-PCR primers in duplicate and normalized by spiked-in synthetic cel-miR-39. We then associated miRNA expression levels with CTCs using a morphometric assay that is independent of Epithelial Cell Adhesion Molecule (EpCAM) and designed for the ultra-sensitive detection of individual CTCs and tumor cell clusters. We chose candidate plasma miRNA markers based on criteria including low or absent expression in other blood components, epithelial-specific expression, and/or significance in the literature. This included miRs -21, -135b, -141, -200a/b/c, -205, -210 and -429. We analyzed Pearson and Spearman rank correlations and associations by group using ANOVA with Bonferonni adjustments for multiple comparisons. Lastly, we integrated patients' clinical and tumors' imaging data for modeling using multiple logistic regression to assess how miRNAs associated with CTCs. Results: We evaluated 68 patients with predominantly stage I disease (75%) and adenocarcinoma histology (69%). Median CTC/mL was 4.2 (Interquartile Range [IQR] 0-19), 49% (33/68) of patients had more than 5 CTCs/mL and 51% (35/68) of these patients also had tumor clusters present. MiRNAs were only weakly correlated with absolute CTC/mL levels in the circulation but at a threshold of 5 CTCs/mL there was a strong relationship with miR-141 (p-value = 0.0004, adj p-value = 0.004). Several miRNAs were associated with the presence of tumor clusters, including miR-205 (p-value = 0.007; adj p-value = 0.06) and miR-429 (p-value = 0.006, adj p-value = 0.05). A logistic model integrating clinical, imaging and miRNA features selected several miRNAs preferentially to predict the presence of tumor clusters (miR-21, miR-200b, miR-205, and miR-429). Conclusion: Circulating oncomiRs may indirectly associate with CTCs and tumor clusters in patients with NSCLC. Our “footprint” is concordant with one previous investigation in metastatic breast cancer showing common results for miR-141 and the miR-200-429 cluster. Further investigations examining miRNAs expressed directly in CTCs would be useful to determine the origin of circulating cancer-associated miRNAs. Citation Format: Viswam S. Nair, Maria Giraldez, Madelyn Luttgen, Khun Visith Keu, Minal Vasanawala, George Horng, Mehran Jamali, Anand Kolatkar, Ware Kuschner, Peter Kuhn, Sanjiv Sam Gambhir, Muneesh Tewari. MicroRNA footprints of circulating tumor cells in patients with non-small cell lung cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4006. doi:10.1158/1538-7445.AM2014-4006
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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 | 0.001 |
| 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) | 0.002 | 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".