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Record W2739890452 · doi:10.1158/1538-7445.am2017-5897

Abstract 5897: Single cell-derived analysis of desmoid tumors for studying tumor-stroma interactions

2017· article· en· W2739890452 on OpenAlexaff
Mushriq Al‐Jazrawe, Steven Xu, Qingxia Wei, Raymond Poon, Benjamin A. Alman

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBiologyMutantWnt signaling pathwayStromaStromal cellPopulationMutationCancer researchAXIN2Cell sortingMolecular biologyCellGeneticsSignal transductionImmunologyGeneImmunohistochemistry

Abstract

fetched live from OpenAlex

Abstract Cancer associated fibroblasts play an important role in the maintenance and remodeling of the tumor microenvironment, providing the appropriate conditions for neoplastic cell growth and invasion. Desmoid tumors (DT), also called aggressive fibromatosis, are rare, locally invasive soft tissue tumors that consist of fibroblastic cells embedded in extracellular matrix. Identification of the stromal cells to study tumor-stroma interactions is difficult due to both populations displaying a fibroblastic phenotype, and no cell marker exists that reliably differentiates between the two populations. Majority of DT arise sporadically due to somatic activating mutations in beta-catenin (CTNNB1), a major effector molecule of canonical Wnt signaling. We established single cell derived colonies from multiple DT samples and characterized the beta-catenin mutation status of each clone by Sanger sequencing. Indeed, we were able to establish both mutant and non-mutant colonies from DT samples. Quantitative PCR for beta-catenin targets AXIN2 and LEF1 confirmed differential activity between the mutant and non-mutant colonies. The specific CTNNB1 codon mutation had no difference on beta-catenin transcriptional activity. We next performed a high throughput surface antigen screen to identify cell markers that can distinguish between the two subpopulations. Our screen found CD142 to be uniquely expressed by the mutant colonies, while the non-mutant colonies uniquely expressed Podoplanin. Quantitative PCR confirmed the differential expression of these markers. Furthermore, the CD142-positive population in heterogeneous DT samples correlated with their mutation frequency. Importantly, CD142-based cell sorting allowed the isolation of the mutant subpopulation even in samples that appeared as wild-type by Sanger sequencing. We also studied the expression of secreted factors in our mutant and non-mutant populations. We observed that CTHRC1, a ligand related to the Wnt/PCP pathway, is highly elevated exclusively in the mutant subpopulations. Recombinant CTHRC1 increased the proliferation rate of DT primary cultures, as measured by BrdU incorporation, while neutralizing antibodies against CTHRC1 decreased cell proliferation. The importance of tumor-stroma interactions cannot be studied without first identifying and characterizing the two populations. This has been especially difficult in soft tissue sarcomas where both the neoplastic and stromal cells exhibit a mesenchymal phenotype. Our study offers a novel method for identifying the mutant and non-mutant subpopulations within desmoid tumors to study how they may interact. Rapidly quantifying tumor composition will also support efforts to understand the natural progression of disease and how it responds to therapy. Citation Format: Mushriq Al-Jazrawe, Steven Xu, Qingxia Wei, Raymond Poon, Benjamin Alman. Single cell-derived analysis of desmoid tumors for studying tumor-stroma interactions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5897. doi:10.1158/1538-7445.AM2017-5897

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.241
GPT teacher head0.482
Teacher spread0.241 · 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 teacher head, 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
Published2017
Admission routes1
Has abstractyes

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