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Record W2483975375 · doi:10.1158/1538-7445.am2016-3798

Abstract 3798: A glycan-binding malaria protein provides therapeutic access to cisplatin-resistant bladder cancer

2016· article· en· W2483975375 on OpenAlexaff
Htoo Zarni Oo, Roland Seiler, Sherry S. Lee, Davide Tortora, Gunjan Kumar, Chris Wang, Thomas Mandel Clausen, Mette Ø. Agerbæk, Jamie R. Rich, John S. Babcook, Peter C. Black, Ali Salanti, Mads Daugaard

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsCentre for Drug Research and DevelopmentUniversity of British Columbia
Fundersnot available
KeywordsCisplatinBladder cancerGemcitabineChemotherapyMedicineCancer researchCancerCystectomyOncologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

Abstract Bladder cancer is a disease of compelling morbidity and mortality mainly due to its high recurrence rate. Cisplatin-based chemotherapy is an integral part of muscle invasive bladder cancer (MIBC) treatment. Although responses are common, a significant number of patients develop resistance to cisplatin and second line treatment options are not well established. No improvement of the MIBC treatment strategy has been achieved in the past two decades and therefore; new approaches to systemic therapy are urgently needed. The Plasmodium falciparum host-cell anchor protein VAR2CSA has been evolutionarily optimized to bind distinctly modified chondroitin sulfate (CS) glycosaminoglycan (GAG) chains expressed exclusively in the mammalian placenta. This is the underlying key event behind pregnancy-associated malaria outbreaks in endemic regions of the world. We have recently discovered that placental-type CS chains are re-expressed in the malignant compartment as a secondary oncofetal CS (ofCS) modification (Salanti et al. 2015, Cancer Cell). In the present study, we have analyzed the expression and role of ofCS in cisplatin-resistant bladder cancer and evaluated the potential of a VAR2-drug conjugate (VDC) to target cisplatin-resistant tumors. Using recombinant VAR2CSA protein (rVAR2) as an ofCS detection reagent, we analyzed a tissue microarray of 52 chemotherapy-naïve MIBC samples, with 36 matched post-chemotherapy cystectomy specimens from patients receiving neoadjuvant gemcitabine/cisplatin. In chemoresistant tumor specimens, of-CS expression was significantly upregulated in residual patient tumors after neoadjuvant chemotherapy (p = 0.001) and it was associated with advanced tumor stage (ypT3/4, p = 0.005) and poor overall survival (p = 0.04). Microarray analysis of primary human bladder tumors and subsequent in situ proximity ligation assay validation identified S100A9 and CD44 as the major ofCS-modified proteoglycans in chemoresistant bladder cancer. Binding of rVAR2 to ofCS chains on bladder cancer cells facilitated rapid internalization of the protein. Moreover, a rVAR2-drug conjugate (VDC) efficiently killed all bladder cancer cells in the low nanomolar IC50 concentration range in vitro and retarded growth of chemoresistant orthotopic MIBC xenografts in vivo. In summary, we demonstrate how a glycan-binding malaria protein can be utilized to gain therapeutic access to cisplatin-resistant bladder cancer. Thus, we provide a method to target cancer-specific glycan modifications for therapeutic intervention as a second line treatment in MIBC, not responding to cisplatin. Citation Format: HTOO ZARNI OO, Roland Seiler, Sherry S. Lee, Davide Tortora, Gunjan Kumar, Chris Wang, Thomas M. Clausen, Mette Ø. Agerbæk, Jamie R. Rich, John S. Babcook, Peter C. Black, Ali Salanti, Mads Daugaard. A glycan-binding malaria protein provides therapeutic access to cisplatin-resistant bladder cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3798.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.149
GPT teacher head0.450
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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