Abstract 3965: KIFC1 is a therapeutic target in lung cancers with extra centrosomes
Bibliographic record
Abstract
Abstract Introduction: Lung cancer is a deadly malignancy and new treatments targeting mechanisms promoting its growth and progression are needed. Genomic instability (GIN) is a recurrent feature of lung tumours that promotes drug resistance and other cancer hallmarks. One mechanism that enables tumour-promoting GIN is centrosome amplification (CA). Centrosomes are organelles involved in chromosome segregation during cell division and two centrosomes in a bipolar arrangement normally ensure equal division of the genome during mitosis. CA, an abnormal increase in centrosome number, is frequently observed in lung and other cancers despite the fact that it can cause lethal multipolar mitotic spindles that potentiate aneuploidy. To mitigate detrimental consequences of CA, cancer cells can cluster extra centrosomes into pseudo-bipolar mitotic spindles. This process is facilitated by a protein called KIFC1 which is upregulated in a large proportion of lung cancers. However, KIFC1’s potential as a therapeutic target in lung cancers with CA has not been explored. Here we investigate the hypothesis that lung cancers with CA are dependent on KIFC1 and sensitive to its inhibition. Methods: Western blotting for KIFC1 and immunofluorescence (IF) for the centrosomal protein, CEP192, were used to measure basal expression and CA, respectively, across a panel of 21 lung adenocarcinoma (LUAD) and 3 non-malignant (NM) cell lines. KIFC1 loss-of-function (LOF) in H1299 and PC9 (LUAD), and BEAS-2B (NM) was achieved using CRISPR/Cas9 and siRNA. In vitro competition assays were done to assess the relative fitness of mCherry-tagged wild-type and GFP-tagged KIFC1-LOF cells in mixed populations over 3-4 cell passages using flow cytometry. CA was potentiated in cells using low doses of the compound, CFI-400945. Clonogenic survival and IF experiments were also done to determine the consequences of KIFC1 LOF. Results: Our findings suggests that basal KIFC1 expression and CA across 21 LUAD cell lines and 3 NM controls are variable. However, we observed a positive correlation (R2 = 0.52, p = 0.01) between KIFC1 expression and CA in LUAD lines. Competition assays revealed that KIFC1 LOF sensitizes LUAD cells with high KIFC1 expression, but not LUAD with low KIFC1 expression or NM cells, to pharmacologically-induced CA. Complementary siRNA experiments confirmed that KIFC1 LOF impairs the survival of cells with CA. Finally, we found that KIFC1 LOF was associated with an increase in multi-polar spindles. Conclusion: These findings support our hypothesis that LUAD with CA are dependent on KIFC1. We suspect its role in centrosome clustering explains this phenotype. Ongoing work is focused on validating these observations in additional models and clinical tumours to confirm its therapeutic potential in LUAD with CA, since combining KIFC1 inhibition with standard of care therapies that induce CA (eg. cisplatin, radiation) could represent an effective therapeutic strategy. Citation Format: Christopher Z. Zhang, Benson Z. Wu, Yin Fang Wu, Caterina di Ciano-Oliveira, Ju-Yoon Yoon, Tak W. Mak, David W. Cescon, Kelsie L. Thu. KIFC1 is a therapeutic target in lung cancers with extra centrosomes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3965.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".