Discriminant function based on parameters of hyaluronic acid metabolism and nitric oxide to differentiate metastatic from non-metastatic colorectal cancer patients

Abstract

Colorectal cancer (CRC) is one of the most common causes of cancer-related deaths worldwide. Because there is currently no useful serological marker for metastatic colorectal cancer, the search for simple biomarkers for colorectal cancer diagnosis and prognosis is needed. Hyaluronic acid level was determined by ELISA; in addition to its degrading enzymes, degradation products and nitric oxide were determined by standard techniques in 185 CRC patients with and without metastases. Statistical analyses were performed by logistic regression and receiver-operating characteristic (ROC) curves. The multivariate discriminate analysis (MDA) selects a function based on absolute values of six biochemical markers; score = [-0.62 (numerical constant) + hyaluronic acid (pg/l) × 0.002 + hyaluronidase (mg N-acetyl glucosamine/ml/18 h) × 0.009-β-glucuronidase (μmol/ml/min) × 0.07 + N-acetyl-β-D-glucosaminidase (μmol/ml/min) × 0.019-glucuronic acid (μg/dl) × 0.001 + nitric oxide (μmol/l) × 0.01]. The selected MDA function correctly classified 92% of the metastatic CRC patients at a discriminate cut-off score = 0.24 (i.e., less than 0.24 indicated patients with non-metastatic colon cancer, and greater than 0.24 indicated patients with metastatic colon cancer with high degrees of sensitivity (100%) and specificity (93%)). The positive predictive and negative predictive values were also high (81% and 85%, respectively). Colorectal cancer patients can be simply and efficiently classified into metastatic or non-metastatic using their MDA score.