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Record W2953413417 · doi:10.5430/jst.v9n2p22

Differential expression of efferocytosis and phagocytosis associated genes in tumor associated macrophages exposed to African American patient derived prostate cancer microenvironment

2019· article· en· W2953413417 on OpenAlexvenueno aff
Christopher Krauss, Myla Worthington, Narendra Banerjee, Ray Shawn Walker, Sasha Hodges, Lin Chen, Kuldeep Rawat, Santanu Dasgupta, Somiranjan Ghosh, Santosh K. Mandal

Bibliographic record

VenueJournal of Solid Tumors · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of General Medical SciencesUniversity of Texas Health Science Center at San AntonioNational Institutes of HealthNational Science Foundation
KeywordsBiologyPhagocytosisCarcinogenesisMicroarray analysis techniquesTumor microenvironmentCancer researchEfferocytosisCancer cellCancerGene expressionMicroarrayMacrophageCell biologyGeneImmune systemImmunologyGenetics

Abstract

fetched live from OpenAlex

Macrophages are the first line of defense in the cellular environment in response to any antigenic or foreign invasion. Since cancer cells express antigenic molecules and create a tumor microenvironment quite different from the normal cellular environment, macrophages will attack this cancer cells as foreign Invaders. However, the cancer cells adept their ability to suppress macrophage activity by secreting compounds/proteins through unknown mechanisms and train these macrophages to aid in tumorigenesis. These macrophages are commonly known as tumor associated macrophages (TAM). In this study, our goal was to find out key regulatory molecules involved in this conversion of cancer-fighting macrophages to cancer friendly macrophages. We used African American(AA) patient derived established human prostate cancer cells along with the human derived macrophages followed by Affymetrix cDNA microarray analysis. Microarray analysis of the PCa cell exposed macrophages revealed appreciable decrease in mRNA expression of several genes associated with phagocytosis process. Aberrant expression of several noncoding RNAs that control the expression of such phagocytosis associated molecules were also evident. Increased expression of oncogenic miR such as, miR-148, 615, 515, 130, 139 and markedly decreased expression of tumor suppressive miR's MiR-3130, let7c,101,103, 383 were noted. Further, TARGET SCAN analysis demonstrated these differential expression of non-coding RNA's causing down regulation of phagocytosis promoting genes elf5A, Meg3, Tubb5, Sparcl-1, Uch-1, Bsg(CD147), Ube2v, GULP, Stabilin 1 and Pamr1. There is an increase of RAP1GAP gene that causes concomitant decrease in the expression of tubulin genes that promote cytoskeletal assembly in forming phagosomes. In addition Ingenuity pathway analysis of the gene expression data also showed upregulation of antiphagocytic genes IL-10, CD 16, IL-18 and MMP-9. Some core canonical pathways showing physiology of cellular signaling obtained by data analyzed by the Ingenuity software is confirmed a very complex mechanism still to be deciphered involved in the biology of TAM formation by which the rogue cancer cells tame their enemies, the macrophages and actually make them their helper cells to survive and propagate in the tumor microenvironment and thus prepare for epithelial mesenchymal transition for future metastasis and cancer stem cell formation and progression.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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