Abstract 2104: <i>In vitro</i> drug effects on cancer cell morphology and functional state revealed by multiparameter imaging mass cytometry
Bibliographic record
Abstract
Abstract Results of in vitro drug testing are correlated with clinical response to chemotherapy: Accuracy to predict clinical drug resistance was found to be as high as 90%. The benefit of using in vitro models lies in the ability to probe cellular response in a controlled closed system, where effects of drug concentrations, treatment duration, drug efflux kinetics and multidrug combinations can be assessed by a variety of cell biology techniques. Cisplatin is a widely used chemotherapy drug that targets genomic DNA of the cells, forming both interstrand and intrastrand cross-links that lead to cell death. One limitation of its clinical use is in predicting the development of resistance and severe side effects in patients. Mechanisms of resistance such as reduced drug accumulation, increased detoxification through cisplatin binding to cellular thiols, reduced DNA platination, and increased DNA repair have been reported, however (tamoxifen enhancement of cisplatin). In vitro models of different cancer types (SKOV3, HeLa, A431, MCF-7) were used to study the effects of cisplatin on cell morphology and phenotypic and functional characteristics with a large panel of metal-tagged antibodies and Imaging Mass Cytometry (IMC) at the single-cell level (1). Proteins involved in DNA damage repair (γH2AX, PP2A, pHistone H3), apoptosis (CD98, caspase-3, cleaved PARP), cell proliferation (cyclin B1, Ki-67), metastasis (vimentin, β-catenin, VEGF, CD63, CD9), substrate adhesion (CD29, CD49e, CD49b, CD51, CD54, CD47, CD61), organelle morphology (CD107a, Mito, histone H3), and signaling pathways (STAT3, pERK1/2, pS6), as well as surface receptors (EGFR, HER2, BRCA, MUC1, CD44, EpCAM, CD142, CD59, beta-catenin) and structural markers (CK5, CK8/18, β-actin, β-tubulin), were identified simultaneously in each individual cell with specific metal-conjugated antibodies. S-phase cells were visualized by detection of 127I in 5-iodo-2′-deoxyuridine (IdU) added to culture media. Presence of cisplatin in cell nuclei and cytoplasm was registered by IMC of platinum stable isotopes. Combination therapy of cisplatin and paclitaxel is a standard chemotherapeutic regimen to treat recurrent or metastatic cervical cancer. Cell lines from various tumors may develop resistance to cisplatin. Reduced cisplatin uptake has been observed in cervical cancer cells with cisplatin resistance. The cisplatin-resistant HeLa cells and A431 (A431/Pt) cells show 50% and 77% reduction in cisplatin uptake, respectively, compared with the parental cell lines. Human ovarian cancers (in vitro model SKOV3), for which cisplatin is a mainstay of treatment, develop drug resistance and pose an important clinical challenge. (1) Chang, Q et al. Nature Scientific Reports 6 (2016): 36641 Citation Format: Olga Ornatsky, Alexandre Bouzekri, Bedilu Allo, Jessica Watson. In vitro drug effects on cancer cell morphology and functional state revealed by multiparameter imaging mass cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2104. doi:10.1158/1538-7445.AM2017-2104
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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".