Targeting CCL11 in the treatment of ovarian cancer

Nolen, Brian M.; Lokshin, Anna

doi:10.1517/14728220903512983

Cited by 27 publications

(28 citation statements)

References 82 publications

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“…To validate the elevation of CCL11 in clinical GBM tissues, it is necessary to clarify the source of CCL11. There are several studies suggesting that tumor cells themselves could be a possible source [8]. We found that cancer cells themselves could produce CCL11 and overexpress CCR3, indicating the activation of CCL11-CCR3 autocrine signaling in GBM.…”

Section: Discussionmentioning

confidence: 53%

“…These effects are likely the result of multiple signaling pathways regulated by CCL11. Previous studies showed that the binding between CCL11 and CCR3 upregulated the expressions of VEGF, IL-8, PDGF-BB, and FGF [8–10]. In addition, it also induced phosphorylation of ERK1/2, MEK1 and STAT3 [5, 29].…”

Section: Discussionmentioning

confidence: 99%

“…In addition, it also induced phosphorylation of ERK1/2, MEK1 and STAT3 [5, 29]. Accordingly, CCL11 could act as: (1) an inflammatory chemokine contributing to the host response to neoplasia, (2) a proangiogenic factor promoting new vessel formation, (3) a general pro-inflammatory factor in response to tissue stress and/or necrosis, and/or (4) an autocrine growth factor released by cancer cells to promote proliferation, migration, and invasion [5, 8, 30]. …”

Section: Discussionmentioning

confidence: 99%

“…This binding triggers a series of signal transduction events involving transient release of intracellular calcium, cytoskeletal rearrangements, generation of inositol triphosphate, activation of protein kinase C and prolonged receptor internalization into an endocytic compartment [5–7]. In cancer, CCL11 and CCR3 facilitate proliferation, migration, and invasion of cancer cells [5, 8–13]. Indirect evidence also suggests that CCL11 may participate in angiogenesis and metastasis [14].…”

Section: Introductionmentioning

confidence: 99%

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Expression and prognostic significance of CCL11/CCR3 in glioblastoma

Tian

Chen

et al. 2016

Oncotarget

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Glioblastoma (GBM) is the most lethal primary nervous system cancer, but due to its rarity and complexity, its pathogenesis is poorly understood. To identify potential tumorigenic factors in GBM, we screened antibody-based cytokine arrays and found that CCL11 was upregulated. We then demonstrated in vitro that both CCL11 and its receptor, CCR3, were overexpressed and promoted the proliferation, migration and invasion of cancer cells. To examine the clinical significance of CCL11/CCR3, 458 GBM samples were divided into a training cohort with 225 cases and a test cohort containing 233 cases. In the training set, immunohistochemical analysis showed overexpression of CCL11 and CCR3 were correlated with unfavorable overall survival (OS). We further developed a prognostic classifier combining CCL11 and CCR3 expression and Karnofsky performance status (KPS) for predicting one-year survival in GBM patients. Receiver operating characteristic (ROC) analysis demonstrated that this predictor achieved 90.7% sensitivity and 73.4% specificity. These results were validated with the test sample set. Our findings suggest that CCL11-CCR3 binding is involved in the progression of GBM and may prompt a novel therapeutic approach. In addition, CCL11 and CCR3 expression, combined with KPS, may be used as an accurate predictor of one-year survival in GBM patients.

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Section: Discussionmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Expression and prognostic significance of CCL11/CCR3 in glioblastoma

Tian

Chen

et al. 2016

Oncotarget

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“…In addition to its role as a chemo-attractant, CCL11 has been implicated in different eosinophilic inflammatory diseases, such as atopic dermatitis, allergic rhinitis, sinusitis, asthma, ulcerative colitis, and in several other gastrointestinal disorders, as well as in parasitic infections [24][25][26][27][28]. Moreover, the levels of serum or plasma CCL11 as diagnostic or prognostic cancer markers have been described in high-grade renal cell carcinomas, high-risk neuroblastoma, as well as in head and neck small cell carcinomas [29][30][31].…”

Section: Discussionmentioning

confidence: 99%

Serum CCL11 Levels in Benign Prostatic Hyperplasia and Prostate Cancer

Kim

Moon

Park

et al. 2016

Urogenit Tract Infect

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Purpose: CC-chemokine ligand 11 (CCL11; eotaxin-1), an eosinophil chemoattractant chemokine, has been proposed as a serum marker for prostate cancer (PCa) by two research groups. We investigated the usefulness of CCL11 in diagnosing prostatic diseases, such as benign prostatic hyperplasia (BPH) and PCa. Materials and Methods: CCL11 was measured in the sera of 139 men with BPH, 44 men with PCa, and 45 control men attending an outpatient health-screening clinic. A commercial enzyme-linked immunosorbent assay kit was used to measure CCL11. Results: CCL11 concentrations were significantly higher in men with BPH and PCa than in normal men (72.9±3.15 and 80.0±4.91 pg/ml vs. 57.6±8.24). In addition, a receiver operating characteristic (ROC) analysis of serum CCL11 levels showed that the areas under the ROC curves were 0.661 (p=0.001) and 0.654 (p=0.012) for BPH and PCa, respectively, compared with normal men. Conclusions: CCL11 may be helpful in diagnosing prostatic diseases, such as BPH and PCa.

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High‐dimensional feature selection in competing risks modeling: A stable approach using a split‐and‐merge ensemble algorithm

Sun

2022

Biometrical J

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Variable selection is critical in competing risks regression with high‐dimensional data. Although penalized variable selection methods and other machine learning‐based approaches have been developed, many of these methods often suffer from instability in practice. This paper proposes a novel method named Random Approximate Elastic Net (RAEN). Under the proportional subdistribution hazards model, RAEN provides a stable and generalizable solution to the large‐p‐small‐n variable selection problem for competing risks data. Our general framework allows the proposed algorithm to be applicable to other time‐to‐event regression models, including competing risks quantile regression and accelerated failure time models. We show that variable selection and parameter estimation improved markedly using the new computationally intensive algorithm through extensive simulations. A user‐friendly R package RAEN is developed for public use. We also apply our method to a cancer study to identify influential genes associated with the death or progression from bladder cancer.

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Targeting CCL11 in the treatment of ovarian cancer

Abstract: Targeting CCL11 and its receptors through the use of monoclonal antibodies and small-molecule inhibitors may represent a beneficial new avenue of ovarian cancer treatment.

Cited by 27 publications

References 82 publications

Expression and prognostic significance of CCL11/CCR3 in glioblastoma

Expression and prognostic significance of CCL11/CCR3 in glioblastoma

Serum CCL11 Levels in Benign Prostatic Hyperplasia and Prostate Cancer

High‐dimensional feature selection in competing risks modeling: A stable approach using a split‐and‐merge ensemble algorithm

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