Abstract A010: A patient first approach using CRISPR-directed gene editing as an augmentative therapy for the treatment of pancreatic ductile adenocarcinoma
Bibliographic record
Abstract
Abstract At the Gene Editing Institute, we are advancing a novel strategy for the treatment of pancreatic ductile adenocarcinoma by employing CRISPR-directed gene editing to disable the functions of key genes that block effective drug application including chemotherapy, radiation and immunotherapy. No matter how careful one is at designing a specific drug against a specific protein, ultimately, the tumor cell develops a workaround. A paradigm shift is required to truly overcome this formidable barrier. We’ve accomplished this by leveraging the effectiveness of standard care and augmenting it, thereby reducing patient suffering, increasing treatment tolerance and, most importantly, improving outcomes. With an enthusiastic response for this concept from the FDA- INTERFACT meeting, we have demonstrated that a carefully selected CRISPR/Cas complex disables the NRF2 gene in the tumor cell and significantly reduces the dose of chemotherapy required to halt pancreatic tumor cell growth, and consequently promoting cell death. The efficiency of gene editing approaches 70 % routinely, which destroys the function of NRF2 and enables additional killing of residual tumor cells by chemotherapeutic agents. As a consequence of CRISPR/Cas activity, we effectively reduce the amount of chemotherapy needed to kill tumor cells by over 20-fold. This level of reduction should enable patients to complete their treatment regimens more successfully, at lower dosages and with far fewer adverse side effects. In addition to reduced suffering, this will invariably prolong survival as we are augmenting already proven treatments. This approach is agnostic to the haplotype of the tumor cell and does not rely on specific biomarker composition; radically expanding the patient population that would be suitable for this type of treatment. We will discuss the impact of CRISPR/Cas-gene editing to disable specific genes, including NRF2 and mutant KRAS, to enable current therapies to work at greater efficacy and at lower dosages. Citation Format: London P McGill, Kelly H Banas, Gregory Tiesi, Eric B Kmiec. A patient first approach using CRISPR-directed gene editing as an augmentative therapy for the treatment of pancreatic ductile adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A010.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".