Blood metabolites can be detected as low-mass ions (LMIs) by mass spectrometry (MS). These LMIs may reflect the pathological changes in metabolism that occur as part of a disease state, such as cancer. We constructed a LMI discriminant equation (LOME) to investigate whether systematic LMI profiling might be applied to cancer screening. LMI information including m/z and mass peak intensity was obtained by five independent MALDI-MS analyses, using 1,127 sera collected from healthy individuals and cancer patients with colorectal cancer (CRC), breast cancer (BRC), gastric cancer (GC) and other types of cancer. Using a two-stage principal component analysis to determine weighting factors for individual LMIs and a two-stage LMI selection procedure, we selected a total of 104 and 23 major LMIs by the LOME algorithms for separating CRC from control and rest of cancer samples, respectively. CRC LOME demonstrated excellent discriminating power in a validation set (sensitivity/specificity: 93.21%/96.47%). Furthermore, in a fecal occult blood test (FOBT) of available validation samples, the discriminating power of CRC LOME was much stronger (sensitivity/specificity: 94.79%/97.96%) than that of the FOBT (sensitivity/specificity: 50.00%/100.0%), which is the standard CRC screening tool. The robust discriminating power of the LOME scheme was reconfirmed in screens for BRC (sensitivity/specificity: 92.45%/96.57%) and GC (sensitivity/specificity: 93.18%/98.85%). Our study demonstrates that LOMEs might be powerful noninvasive diagnostic tools with high sensitivity/specificity in cancer screening. The use of LOMEs could potentially enable screening for multiple diseases (including different types of cancer) from a single sampling of LMI information.
Keywords: MALDI-TOF mass spectrometry; pattern recognition; serum profiling.
© 2013 UICC.