Multiplex determination of serological signatures in the sera of colorectal cancer patients using hydrogel biochips.

Colorectal cancer (CRC) is the third most common malignancy in industrialized countries. Despite the advances in diagnostics and development of new drugs, the 5-year survival remains only 60-65%. Our approach to early diagnostics of CRC is based on the determination of serological signatures with an array of hemispherical hydrogel cells containing immobilized proteins and oligosaccharides (glycochip). The compounds immobilized on the glycochip include tumor-associated glycans (SiaTn, Tn, TF, Le(C) , Le(Y) , SiaLe(A) , and Manß1-4GlcNAcß) and antibodies against human immunoglobulins IgG, IgA, and IgM. The glycochip detects antibodies against tumor-associated glycans in patients' sera. The simultaneous measurement of the levels of immunoglobulins enhances the diagnostic impact of the signatures. In this work, we found previously unreported increase in antibodies against oligosaccharide Manß1-4GlcNAcß in patients with CRC. In parallel with these experiments, we determined the levels of oncomarkers carcinoembryonic antigen (CEA), cancer antigen (CA) 19-9, CA 125, CA 15-3, human chorionic gonadotropin (HCG), and alpha-fetoprotein (AFP) using another gel-based biochip with immobilized antibodies (oncochip) developed earlier in our laboratory. In total, 69 samples from healthy donors, 33 from patients with colorectal carcinoma, and 27 from patients with inflammatory bowel diseases were studied. The use of combined signatures of antiglycan antibodies and oncomarkers provides much better predictive value than the conventional measurement of oncomarkers CEA and CA 19-9. Positive predictive value of CRC diagnoses using together glycochip and oncochip reached 95% with the sensitivity and specificity 88% and 98%, respectively. Thus, the combination of antibody profiling with detection of conventional oncomarkers proved to be a promising tool in diagnostics of CRC.

Clinical screening of gene rearrangements in childhood leukemia by using a multiplex polymerase chain reaction-microarray approach.

PURPOSE: Currently, many forms of leukemia are considered potentially curable, with prognosis and clinical outcome strongly dependent on the underlying molecular pathophysiology. A substantial number of leukemia patients harbor nonrandom karyotypic abnormalities that define subgroups with unique biological and clinical features. For detection of these types of gene rearrangements, a combination of multiplex RT-PCR with hybridization on oligonucleotide gel array was presented previously, which identified five chromosomal translocations with fusion variants. In the present study, additional clinically relevant translocations were included in our analysis using a second generation of microarrays. We also expanded significantly on the clinical correlation of our findings. EXPERIMENTAL DESIGN: An oligonucleotide microarray was designed for hybridization with products of a multiplex RT-PCR to identify the following translocations: t(9;22)p190, t(4;11), t(12;21), t(1;19), typical for acute lymphoblastic leukemia; t(9;22)p210 for chronic myeloid leukemia; and t(8;21), t(15;17), inv16, typical for acute myeloblastic leukemia. RESULTS: To demonstrate the potential clinical application of the method, 247 cases of childhood leukemia were screened, and the above-mentioned gene rearrangements were found in 30% of cases. The sensitivity and specificity of the assay is comparable with the RT-PCR technique, so that it can be used to follow minimal residual disease. The feasibility of an additional refinement of the method, on-chip-multiplex PCR, has been successfully demonstrated by identifying a common translocation, t(9;22), in chronic myeloid leukemia. CONCLUSIONS: Our data suggest that the microarray-based assay can be an effective and reliable tool in the clinical screening of leukemia patients for the presence of specific gene rearrangements with important diagnostic and prognostic implications. The method is amenable for automation and high-throughput analysis.