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Record W2040449973 · doi:10.1158/1538-7445.am10-1422

Abstract 1422: Cancer-associated fibroblasts influence the sensitivity of pancreatic cancer cells to gemcitabine in pancreatic ductal adenocarcinoma

2010· article· en· W2040449973 on OpenAlexaff
Shannon M. Valdez, Karam S. Takhar, Dorothy Leung, Allen Delaney, May Q. Wong, Karen K. Cham, David Owen, Stephen W. Chung, Charles H. Scudamore, Donald T. Yapp, Sylvia S. W. Ng

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of British ColumbiaCanada's Michael Smith Genome Sciences CentreBC Cancer Agency
Fundersnot available
KeywordsGemcitabinePancreatic cancerCancer researchCancerCancer-Associated FibroblastsMedicineCA19-9OncologyAdenocarcinomaInternal medicineCancer cell

Abstract

fetched live from OpenAlex

Abstract Introduction: Pancreatic ductal adenocarcinoma is chemo- and radio-resistant, and has the worst survival rates of all cancers. Gemcitabine improves quality of life, but only provides modest survival benefits. Notably, pancreatic cancer is characterized by a strong “reactive” stroma in association with extensive fibroblast proliferation. Our hypothesis is that the large population of cancer-associated fibroblasts (CAFs) in pancreatic tumors produces a plethora of growth factors and cytokines which in turn, influence the sensitivity of pancreatic cancer cells to gemcitabine. Methods: Fourteen primary pancreatic cancer-associated fibroblast (CAF) lines were established in culture using freshly resected pancreatic tumor tissues from 14 different patients. To assess whether these CAFs influence chemosensitivity, MiaPaCa-2 pancreatic cancer cells were injected alone or co-injected with one of the CAF lines CAF11 subcutaneously into SCID mice. When tumors reached ∼200 mm3, mice bearing MiaPaCa-2 tumors or MiaPaCa-2+CAF11 tumors were treated with the vehicle control (0.9% saline) or gemcitabine (120 mg/kg, q7d, i.p.). Tumor volume was measured weekly. Concurrently, Affymetrix U133 plus 2.0 arrays were used to determine the differentially expressed genes in pancreatic CAFs vs. normal fibroblasts. The genes were then analyzed with Ingenuity Systems to identify network and canonical pathways that are altered in CAFs, and which may mediate chemosensitivity. Selected genes were further validated by RT-PCR, western blotting, or ELISA. Results: Gemcitabine was found to suppress the growth of MiaPaCa-2 tumors but not that of MiaPaCa-2+CAF11 tumors, suggesting that the presence of CAF11 renders MiaPaCa-2 cells more resistant to the drug. Affymetrix results showed that 1704 probe sets representing 1183 unique genes were differentially expressed by 2-fold or greater (P<0.05) in primary pancreatic CAFs, of which 382 gene were upregulated and 801 genes were downregulated. Thirty-four of these genes were mapped to the highest ranking network whose molecular functions include “cell cycle, cancer”. IL-6 was the most highly upregulated gene (8.3-fold; P=2.20e-05) in this network. Furthermore, 19 and 11 other genes were mapped to two significant canonical pathways, “hepatic fibrosis/hepatic stellate cell activation” and “IL-6 signaling”, respectively. IL-6 was the central component of both canonical pathways. RT-PCR and ELISA data confirmed the increased expression of IL-6 and other soluble factors in CAFs. Conclusion: Primary pancreatic CAFs secrete elevated levels of various growth factors and cytokines such as IL-6, which may promote survival of pancreatic cancer cells and reduce their sensitivity to gemcitabine. These soluble factors are potential therapeutic targets in pancreatic cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1422.

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 score0.009

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)0.0030.000

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 head0.047
GPT teacher head0.396
Teacher spread0.350 · 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
Published2010
Admission routes1
Has abstractyes

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