MétaCan
Menu
Back to cohort
Record W2561944026 · doi:10.1158/1538-7445.am2015-2377

Abstract 2377: Bone-derived osteopontin mediates the migration and stem-like properties of breast cancer cells

2015· article· en· W2561944026 on OpenAlexaff
Graciella M. Pio

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicBone and Dental Protein Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsOsteopontinCancer stem cellCD44Breast cancerCancer researchCancerBone marrowCancer cellPopulationBone metastasisTumor microenvironmentStem cellMetastasisPathologyMedicineBiologyImmunologyInternal medicineCellCell biology

Abstract

fetched live from OpenAlex

Abstract Metastatic breast cancer has an affinity for certain organs and tissues, a phenomenon termed organ tropism. Of particular interest is breast cancer's preference for bone, since this is the most common site of metastasis in breast cancer patients. In addition, research suggests that breast cancer cells that do metastasize may have stem-like properties, including the ability to self-renew and differentiate into a heterogeneous tumor. These cells can be identified by their high aldehyde dehydrogenase activity (ALDH) and/or CD44+CD24- phenotype. However, it is unclear whether properties of the organ microenvironment or the stem-like cancer cells (or both) facilitate metastatic organ tropism. In the current study, we tested the hypothesis that bone marrow-conditioned media (an ex vivo representation of the bone microenvironment) contains specific soluble factors that enhance the growth and migration of whole population and ALDHhiCD44+CD24- breast cancer cells. Bone marrow-conditioned media (BMCM) generated from the bones of athymic nude mice was analyzed for the presence and identity of soluble factors using protein arrays. Osteopontin (OPN) was detected in the BMCM in significant amounts by the protein array and confirmed by ELISA. OPN was then depleted from the BMCM using immunoprecipitation and migration of MDA-MB-231 and SUM-159 breast cancer cells to the BMCM was assessed. Results indicate that bone-derived OPN significantly enhances MDA-MB-231 and SUM-159 breast cancer cell migration (P<0.05). Additionally, bone-derived OPN enhances the migration of ALDHhiCD44+CD24- MDA-MB-231 breast cancer stem cells relative to their ALDHlowCD44-CD24+ counterparts (P<0.05). The effect of bone-derived OPN on the tumorsphere forming abilities of whole population and ALDHhiCD44+CD24- MDA-MB-231 was also assessed; bone-derived OPN significantly enhances the tumorsphere forming abilities of whole population and stem-like MDA-MB-231 breast cancer cells (P<0.05). The interaction between bone-derived OPN and its cell surface receptors CD44 and αvβ5 in breast cancer cell migration to BMCM was also investigated using blocking antibodies. We observed that both whole population MDA-MB-231 and SUM-159 breast cancer cells interact with bone-derived OPN via CD44 and αvβ5 (P<0.05). Ongoing studies are investigating the activation of OPN-mediated signaling pathways in breast cancer cells as well as the role of CD44 and other cell surface integrins in the tumorsphere forming abilities of breast cancer cells. Overall, elucidation of the interactions between bone-derived OPN and breast cancer cells could contribute to future development of novel therapeutics that interrupt these interactions in the bone marrow niche, thereby improving breast cancer patient prognosis. Citation Format: Graciella M. Pio. Bone-derived osteopontin mediates the migration and stem-like properties of breast cancer cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2377. doi:10.1158/1538-7445.AM2015-2377

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 score0.003
Threshold uncertainty score0.011

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)0.0030.001

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 head0.119
GPT teacher head0.364
Teacher spread0.244 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicBone and Dental Protein StudiesFrench-language works237,207