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1.  Proteomic classification of acute leukemias by alignment-based quantitation of LC-MS/MS data sets 
Journal of proteome research  2012;11(10):5005-5010.
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.
PMCID: PMC3564549  PMID: 22900933
2.  Allogeneic Hematopoietic Cell Transplantation for Chronic Myelomonocytic Leukemia: Relapse-Free Survival is Determined by Karyotype and Comorbidities 
Hematopoietic cell transplantation (HCT) offers potentially curative therapy for Chronic Myelomonocytic Leukemia (CMML). We evaluated HCT outcomes in 85 patients with CMML, 1.0–69.1 (median 51.7) years of age, with follow-up extending to 19 years. CMML was considered de novo in 71 and secondary in 14 patients. Conditioning regimens were of various intensities. Thirty-eight patients had related (34 HLA identical), and 47 (39 HLA matched) unrelated donors. The source of stem cells was marrow in 32 and peripheral blood progenitor cells in 53 patients. Acute GVHD grades II–IV occurred in 72% and chronic GVHD in 26% of patients. Relapse incidence was 27% at 10 years. Relapse correlated with increasing scores by the MD Anderson prognostic score (p=0.01). The major causes of death were relapse and infections ±GVHD. Progression-free survival was 38% at 10 years. Mortality was negatively correlated with pre-HCT hematocrit (p=0.007), and increased with high-risk cytogenetics (p=0.02), higher HCT Comorbidity Index (p=0.0008), and increased age (p=.02). WHO classification did not statistically significantly affect outcome. Thus, a proportion of patients with CMML have lasting remissions following allogeneic HCT and appear to be cured of their disease.
PMCID: PMC3100432  PMID: 20932924
CMML; Cytogenetics; Co-morbidity; Hematopoietic cell transplantation
3.  Analysis of Tp53 Codon 72 Polymorphisms, Tp53 Mutations, and HPV Infection in Cutaneous Squamous Cell Carcinomas 
PLoS ONE  2012;7(4):e34422.
Non-melanoma skin cancers are one of the most common human malignancies accounting for 2–3% of tumors in the US and represent a significant health burden. Epidemiology studies have implicated Tp53 mutations triggered by UV exposure, and human papilloma virus (HPV) infection to be significant causes of non-melanoma skin cancer. However, the relationship between Tp53 and cutaneous HPV infection is not well understood in skin cancers. In this study we assessed the association of HPV infection and Tp53 polymorphisms and mutations in lesional specimens with squamous cell carcinomas.
We studied 55 cases of histologically confirmed cutaneous squamous cell carcinoma and 41 controls for the presence of HPV infection and Tp53 genotype (mutations and polymorphism).
We found an increased number of Tp53 mutations in the squamous cell carcinoma samples compared with perilesional or control samples. There was increased frequency of homozygous Tp53-72R polymorphism in cases with squamous cell carcinomas, while the Tp53-72P allele (Tp53-72R/P and Tp53-72P/P) was more frequent in normal control samples. Carcinoma samples positive for HPV showed a decreased frequency of Tp53 mutations compared to those without HPV infection. In addition, carcinoma samples with a Tp53-72P allele showed an increased incidence of Tp53 mutations in comparison carcinomas samples homozygous for Tp53-72R.
These studies suggest there are two separate pathways (HPV infection and Tp53 mutation) leading to cutaneous squamous cell carcinomas stratified by the Tp53 codon-72 polymorphism. The presence of a Tp53-72P allele is protective against cutaneous squamous cell carcinoma, and carcinoma specimens with Tp53-72P are more likely to have Tp53 mutations. In contrast Tp53-72R is a significant risk factor for cutaneous squamous cell carcinoma and is frequently associated with HPV infection instead of Tp53 mutations. Heterozygosity for Tp53-72R/P is protective against squamous cell carcinomas, possibly reflecting a requirement for both HPV infection and Tp53 mutations.
PMCID: PMC3335843  PMID: 22545084
4.  Too Much Cleavage of Cyclin E Promotes Breast Tumorigenesis 
PLoS Genetics  2012;8(3):e1002623.
PMCID: PMC3315477  PMID: 22479209

Results 1-4 (4)