An Antibody–Drug Conjugate Directed against Lymphocyte Antigen 6 Complex, Locus E (LY6E) Provides Robust Tumor Killing in a Wide Range of Solid Tumor Malignancies
Bibliographic record
Abstract
PURPOSE: Chemotherapies are limited by a narrow therapeutic index resulting in suboptimal exposure of the tumor to the drug and acquired tumor resistance. One approach to overcome this is through antibody-drug conjugates (ADC) that facilitate greater potency via target-specific delivery of highly potent cytotoxic agents. EXPERIMENTAL DESIGN: In this study, we used a bioinformatics approach to identify the lymphocyte antigen 6 complex locus E (LY6E), an IFN-inducible glycosylphosphatidylinositol (GPI)-linked cell membrane protein as a promising ADC target. We developed a monoclonal anti-LY6E antibody and characterized in situ LY6E expression in over 750 cancer specimens and normal tissues. Target-dependent anti-LY6E ADC killing was investigated both in vitro and in vivo using patient-derived xenograft models. RESULTS: Using in silico approaches, we found that LY6E was significantly overexpressed and amplified in a wide array of different human solid tumors. IHC analysis revealed high LY6E protein expression in a number of tumor types, such as breast, lung, gastric, ovarian, pancreatic, kidney and head/neck carcinomas. Characterization of the endocytic pathways for LY6E revealed that the LY6E-specific antibody is internalized into cells leading to lysosomal accumulation. Consistent with this, a LY6E-specific ADC inhibited in vitro cell proliferation and produced durable tumor regression in vivo in clinically relevant LY6E-expressing xenograft models. CONCLUSIONS: Our results identify LY6E as a highly promising molecular ADC target for a variety of solid tumor types with current unmet medical need.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".