A tumor-restricted glycoform of podocalyxin is a highly selective marker of immunologically cold high-grade serous ovarian carcinoma
Bibliographic record
Abstract
Introduction Targeted-immunotherapies such as antibody-drug conjugates (ADC), chimeric antigen receptor (CAR) T cells or bispecific T-cell engagers (eg, BiTE ® ) all aim to improve cancer treatment by directly targeting cancer cells while sparing healthy tissues. Success of these therapies requires tumor antigens that are abundantly expressed and, ideally, tumor specific. The CD34-related stem cell sialomucin, podocalyxin (PODXL), is a promising target as it is overexpressed on a variety of tumor types and its expression is consistently linked to poor prognosis. However, PODXL is also expressed in healthy tissues including kidney podocytes and endothelia. To circumvent this potential pitfall, we developed an antibody, named PODO447, that selectively targets a tumor-associated glycoform of PODXL. This tumor glycoepitope is expressed by 65% of high-grade serous ovarian carcinoma (HGSOC) tumors. Methods In this study we characterize these PODO447-expressing tumors as a distinct subset of HGSOC using four different patient cohorts that include pre-chemotherapy, post-neoadjuvant chemotherapy (NACT) and relapsing tumors as well as tumors from various peritoneal locations. Results We find that the PODO447 epitope expression is similar across tumor locations and negligibly impacted by chemotherapy. Invariably, tumors with high levels of the PODO447 epitope lack infiltrating CD8 + T cells and CD20 + B cells/plasma cells, an immune phenotype consistently associated with poor outcome. Discussion We conclude that the PODO447 glycoepitope is an excellent biomarker of immune “cold” tumors and a candidate for the development of targeted-therapies for these hard-to-treat cancers.
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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 | 0.001 |
| 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".