| Literature DB >> 21977031 |
Jennifer Sullivan1, Qiaoke Gong, Terry Hyslop, Harish Lavu, Galina Chipitsyna, Charles J Yeo, Hwyda A Arafat.
Abstract
Background/Aims. Pancreatic ductal adenocarcinoma (PDA) has etiological association with chronic inflammation. Elevated circulating levels of inflammatory mediators, such as monocyte chemoattractant protein-1 (MCP-1), are found in obese individuals. We hypothesized that serum MCP-1 levels are elevated in obese PDA patients. Methods. ELISA was used to analyze MCP-1 serum levels in PDA (n = 62) and intraductal papillary mucinous neoplasms (IPMN) (n = 27). Recursive partitioning statistical analysis investigated the relationship between log MCP-1 and clinicopathological parameters. Results. Log MCP-1 values were significantly (P < 0.05) elevated in patients with BMI ≥ 37.5. In patients with BMI < 37.5, average log MCP-1 values were significantly elevated in PDA patients when compared to IPMN patients. Within the IPMN group, higher log MCP-1 levels correlated with increased age. Recursive partitioning analysis of IPMN versus PDA revealed a strategy of predicting characteristics of patients who are more likely to have cancer. This strategy utilizes log MCP-1 as the primary factor and also utilizes smoking status, gender, and age. Conclusion. MCP-1 is a promising biomarker in pancreatic cancer. The potential of using MCP-1 to distinguish PDA from IPMN patients must be studied in larger populations to validate and demonstrate its eventual clinical utility.Entities:
Year: 2011 PMID: 21977031 PMCID: PMC3184439 DOI: 10.1155/2011/518394
Source DB: PubMed Journal: J Oncol ISSN: 1687-8450 Impact factor: 4.375
Clinicopathological characteristics of PDA patients and MCP-1 levels.
| PDA | % | MCP-1 (pg/mL) mean ± SEM |
| Survival at 12 months |
| |
|---|---|---|---|---|---|---|
|
| 64.7 | |||||
| <60 (mean 52.9) | 20 | 211.1 ± 68.37 | 0.12 | 83% | 0.9 | |
| >60 (mean 70.2) | 42 | 232.91 ± 51.69 | 74% | |||
| M | 28 | 45 | 209.1 ± 50.5 | 0.9 | 85% | 0.5 |
| F | 34 | 55 | 239.7 ± 62.9 | 67.9% | ||
|
| ||||||
| Normal weight (<25) | 20 | 32 | 174.3 ± 30.7 | 77.7% | ||
| Overweight (25–29.9) | 28 | 45 | 227.8 ± 55.3 | 0.09 | 75.7% | 0.08 |
| Obese (>30) | 14 | 23 | 277.5 ± 141 | 71.3% | ||
|
| ||||||
| I | 5 | 8 | 69.12 ± 22.04 | 80% | ||
| II | 46 | 74 | 228.43 ± 35.5 | 0.62 | 75% | 0.4 |
| III-IV | 11 | 18 | 104.52 ± 15.6 | 62% | ||
|
| ||||||
| G1 | 8 | 13 | 280.15 ± 119.6 | 83% | ||
| G2 | 37 | 60 | 186.99 ±102.63 | 0.34 | 80% | 0.5 |
| G3-G4 | 17 | 27 | 302.63 ± 38.82 | 65% | ||
|
| ||||||
| N0 | 7 | 11 | 106.08 ± 30.37 | 83% | ||
| N1-N2 | 16 | 26 | 155.04 ± 26.77 | 80% | ||
| N3-N5 | 17 | 27 | 321.82 ± 85.19 | 0.07 | 63% | 0.06 |
| >N6 | 22 | 36 | 241.16 ± 91.066 | 50% |
Clinicopathological characteristics of IPMN patients and MCP-1 levels.
| IPMN | % | MCP-1 (pg/mL) mean ± SEM |
| |
|---|---|---|---|---|
|
| 66.6 | |||
| <60 (mean 53.3) | 9 | 33 | 87.9±17.6 | 0.09 |
| >60 (mean 72.8) | 18 | 67 | 142.7± 17.7 | |
| M | 7 | 26 | 152.9 ± 21.9 | 0.12 |
| F | 20 | 74 | 113.9 ± 14.3 | |
|
| ||||
| Normal weight (<25) | 10 | 37 | 80 ± 14.1 | |
| Overweight (25–29.9) | 10 | 37 | 150 ± 17.7 | 0.34 |
| Obese (>30) | 7 | 26 | 132 ± 30 |
Subgroups of levels of log MCP-1 as defined by recursive partitioning. Data in diagonal cells represents least squares mean of the specified subgroup, while unadjusted P values are provided in the off-diagonal cells.
| BMI < 37.5, diagnosis: benign, age < 55 | CI | BMI < 37.5, diagnosis: benign, age ≥ 55 | CI | BMI < 37.5, diagnosis: cancer | CI | BMI ≥ 37.5, diagnosis: cancer | CI | |
|---|---|---|---|---|---|---|---|---|
| BMI < 37.5, diagnosis: benign, age < 55 | 3.59 | 2.9–4.3 | ||||||
|
| ||||||||
| BMI < 37.5, diagnosis: benign, age ≥ 55 |
| 4.81 | 4.5–5.1 | |||||
|
| ||||||||
| BMI < 37.5, diagnosis: cancer |
|
| 4.94 | 4.8–5.1 | ||||
|
| ||||||||
| BMI ≥ 37.5, diagnosis: cancer |
|
|
| 6.68 | 5.7–7.7 | |||
Figure 1Multivariate logistic regression analysis was used to determine the association of clinical factors and the protein MCP-1 with pancreatic cancer status. An assessment of sensitivity and specificity of this model was completed using receiver-operating characteristic (ROC) methods. Recursive partitioning analysis was used to demonstrate the relationship of log MCP-1 with demographic and clinical characteristics. The lowest levels of log MCP-1 were obtained in benign nonobese patients under the age of 55 years (3.59). Benign nonobese patients aged 55 years and over had average log MCP-1 levels of 4.81, and nonobese cancer patients had log MCP-1 levels of 4.94. Obese patients, regardless of cancer status, had the highest level of log MCP-1 (6.68).
Figure 2Recursive partitioning analysis was used to demonstrate the overall differences between demographic, clinical, and log MCP-1 characteristics of patients with PDA and patients with benign IPMN. Sensitivity and specificity of the resulting algorithm to determine cancer versus benign patients was completed using the standard definitions of these measures. Word at end of node demonstrates that the algorithm predicts either Benign or Cancer for the subgroup and graph then represents how many Benign/Cancer patients are in each subgroup. Standard logistic regression analysis utilizing log MCP-1 could not attain this level of sensitivity and specificity combined, rather it could achieve high values of one of these metrics at the expense of the other.