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Record W2478299947 · doi:10.1158/1538-7445.am2016-920

Abstract 920: Migratory cancer side population cells induces stem cell altruism in bone marrow mesenchymal stem cells to resist therapy, and enhance tumorigenic potential of non-tumorigenic cells

2016· article· en· W2478299947 on OpenAlexaff
Joyeeta Talukdar, Rashmi Bhuyan, Jaishree Garhyan, Bidisha Pal, Sora Sandhya, Sukanya Gayan, Anupam Sarma, Reza Bayat‐Mokhtari, Hong Li, Jyotirmoy Phukan, Wael Tasabehji, Seema Bhuyan, Amal Kataki, Rika Tsuchida, Herman Yeger, Debabrata Baishya, Bikul Das

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsStem cellCancer stem cellMesenchymal stem cellCancer researchBiologyPopulationHaematopoiesisBone marrowCell biologyReprogrammingEndothelial stem cellCancer cellImmunologyCancerCellMedicineIn vitroGenetics

Abstract

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Abstract Stem cell may exhibit altruistic behavior that may benefit cancer cells. We recently demonstrated altruistic phenotype in human embryonic stem cells (Das B et al. Stem Cells 2012). The phenotype exhibited reversible induction of high HIF-2alpha and low p53 expression, associated with high glutathione secretion. We speculated that cancer stem cell might induce a similar altruistic phenotype in human bone marrow (BM) derived stem cells (hematopoietic, mesenchymal and endothelial cells). The altruistic reprogrammed BM cells may then facilitate tumor growth, as well as resist the toxicity of oxidative-stress inducing anti-cancer agents. To investigate this possibility, we have obtained conditioned media (CM) from migratory side-population (SPm) and non-SP cells of a diverse panel of tumors including epithelial tumors. The SPm cells exhibit very high tumorigenic capacity (Das B et al, Stem Cell, 2008). The CM was added to in vitro bone marrow (BM) derived CD133+ cells that contain hematopoietic, endothelial, and mesenchymal stem cells. We found that SPm derived CM (henceforth known as SPm-CM) treatment increased the self-renewal capacity of CD271+/CD45- BM-MSCs. Importantly, the reprogrammed CD271+ BM-MSCs (henceforth known as R-MSCs) phenotype exhibited enhanced stemness reprogramming, a cytoprotective mechanism associated with stem cell altruism (Das B et al. Stem Cells, 2012). In contrast, the treatment with CM obtained from non-SP cells did not exhibit R-MSCs. We found that VEGF/VEGR1 autocrine signaling may be involved in R-MSCs mechanism. Importantly, the R-MSCs derived CM reprogrammed non-CSCs to CSCs, and reduced the toxicity of chemotherapy on non-SP cells. In vivo, R-MSCs derived CM, when injected to mice, exhibited mobilization of CD271+ BM-MSCs to circulation. The circulatory CD271+ BM-MSCs exhibited distinct phenotype of R-MSCs including high expression of HIF-2alpha, and VEGFR1. Finally, in human cancer patients, we identified R-MSC phenotype in the peripheral circulation. These studies suggest that cancer stem cells may exploit stem cell altruism to reprogram BM-MSCs for their own benefit. The reprogrammed BM-MSCs gene expression may have the potential as a diagnostic marker for CSC-induced stem cell altruism. Citation Format: Joyeeta Talukdar, Rashmi Bhuyan, Jaishree Garhyan, Bidisha Pal, Sora Sandhya, Sukanya Gayan, Anupam Sarma, Reza Bayat-Mokhtari, Hong Li, Jyotirmoy Phukan, Wael Tasabehji, Seema Bhuyan, Amal Ch Kataki, Rika Tsuchida, Herman Yeger, Debabrata Baishya, Bikul Das. Migratory cancer side population cells induces stem cell altruism in bone marrow mesenchymal stem cells to resist therapy, and enhance tumorigenic potential of non-tumorigenic cells. [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 920.

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 score0.010

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 integrity0.0000.001
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 head0.053
GPT teacher head0.363
Teacher spread0.311 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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