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Despite immense interest in the proteome as a source of biomarkers in cancer, mass spectrometry has yet to yield a clinically useful protein biomarker for tumor classification. To explore the potential of a particular class of mass spectrometry-based quantitation approaches, label-free alignment of liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) data sets, for the identification of biomarkers for acute leukemias, we asked whether a label-free alignment algorithm could distinguish known classes of leukemias on the basis of their proteomes. This approach to quantitation involves (1) computational alignment of MS1 peptide peaks across large numbers of samples; (2) measurement of the relative abundance of peptides across samples by integrating the area under the curve of the MS1 peaks; and (3) assignment of peptide IDs to those quantified peptide peaks on the basis of the corresponding MS2 spectra. We extracted proteins from blasts derived from four patients with acute myeloid leukemia (AML, acute leukemia of myeloid lineage) and five patients with acute lymphoid leukemia (ALL, acute leukemia of lymphoid lineage). Mobilized CD34+ cells purified from peripheral blood of six healthy donors and mononuclear cells (MNC) from the peripheral blood of two healthy donors were used as healthy controls. Proteins were analyzed by LC-MS/MS and quantified with a label-free alignment-based algorithm developed in our laboratory. Unsupervised hierarchical clustering of blinded samples separated the samples according to their known biological characteristics, with each sample group forming a discrete cluster. The four proteins best able to distinguish CD34+, AML, and ALL were all either known biomarkers or proteins whose biological functions are consistent with their ability to distinguish these classes. We conclude that alignment-based label-free quantitation of LC-MS/MS data sets can, at least in some cases, robustly distinguish known classes of leukemias, thus opening the possibility that large scale studies using such algorithms can lead to the identification of clinically useful biomarkers.

We compared the gene expression profile of adult acute lymphoblastic leukemia (ALL) to normal hematopoietic and non-ALL samples using oligonucleotide arrays. Connective tissue growth factor (CTGF) was the highest overexpressed gene in B-cell ALL compared with the other groups, and displayed heterogeneous expression, suggesting it might have prognostic relevance. CTGF expression was examined by quantitative reverse transcriptase-polymerase chain reaction (ORT-PCR) on 79 adult ALL specimens. CTGF expression levels were significantly increased in ALL cases with B-lineage (P < .001), unfavorable cytogenetics (P < .001), and blasts expressing CD34 (P < .001). In a multivariate proportional hazards model, higher CTGF expression levels corresponded to worsening of overall survival (OS; hazard ratio 1.36, for each 10-fold increase in expression; P = .019). Further studies are ongoing to confirm the prognostic value of CTGF expression in ALL and to investigate its role in normal and abnormal lymphocyte biology.

Allogeneic transplantation offers a potential cure for patients with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL). We performed a retrospective analysis examining pretransplantation and posttransplantation prognostic factors in 90 patients with Ph+ ALL. The median age of the patients was 33 years, with slightly more than half of the patients (58%) in clinical remission at the time of transplantation. Overall, patients had a nonrelapse mortality rate of 30%, a relapse percentage of 34%, and an estimated 5-year disease-free survival rate of 30%. Pretransplantation risk factors for relapse included the expression of the p190 transcript (relative risk [RR] = 5.1; P =.037), evidence of morphologic disease at the time of transplantation (RR = 3.9; P <.001), and type of donor (RR = 2.5; P =.015), with patients receiving autologous or matched related transplants having the highest risk of relapse. The detection of minimal residual disease by reverse transcription polymerase chain reaction for bcr-abl transcripts was a significant posttransplantation risk factor for relapse (RR = 4.4; P =.001), with posttransplantation patients expressing the p190 transcript having the highest risk of relapse (RR = 8.7; P =.0001). In addition, patients with chronic extensive graft-versus-host disease showed a significantly lower risk of relapse (RR = 0.33; P =.038). Thus, these findings indicate that several pretransplantation and posttransplantation risk factors exist for patients with Ph+ ALL. Together, these factors can be used to improve our risk stratification of patients with Ph+ ALL who undergo transplantation, which will greatly enhance our ability to counsel these patients and potentially lead to the development of more specific treatment plans for them., (Copyright 2003 American Society for Blood and Marrow Transplantation)