Comparison of Supervised Classification Methods for Protein Profiling in Cancer Diagnosis

A key challenge in clinical proteomics of cancer is the identification of biomarkers that could allow detection, diagnosis and prognosis of the diseases. Recent advances in mass spectrometry and proteomic instrumentations offer unique chance to rapidly identify these markers. These advances pose considerable challenges, similar to those created by microarray-based investigation, for the discovery of pattern of markers from high-dimensional data, specific to each pathologic state (e.g. normal vs cancer). We propose a three-step strategy to select important markers from high-dimensional mass spectrometry data using surface enhanced laser desorption/ionization (SELDI) technology. The first two steps are the selection of the most discriminating biomarkers with a construction of different classifiers. Finally, we compare and validate their performance and robustness using different supervised classification methods such as Support Vector Machine, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Networks, Classification Trees and Boosting Trees. We show that the proposed method is suitable for analysing high-throughput proteomics data and that the combination of logistic regression and Linear Discriminant Analysis outperform other methods tested

Serum Proteomic Profiling of Lung Cancer in High-Risk Groups and Determination of Clinical Outcomes

HypothesisLung cancer remains the leading cause of cancer-related mortality worldwide. Currently known serum markers do not efficiently diagnose lung cancer at early stage.MethodsIn the present study, we developed a serum proteomic fingerprinting approach coupled with a three-step classification method to address two important clinical questions: (i) to determine whether or not proteomic profiling differs between lung cancer and benign lung diseases in a population of smokers and (ii) to assess the prognostic impact of this profiling in lung cancer. Proteomic spectra were obtained from 170 pathologically confirmed lung cancer or smoking patients with benign chronic lung disease serum samples.ResultsAmong the 228 protein peaks differentially expressed in the whole population, 88 differed significantly between lung cancer patients and benign lung disease, with area under the curve diagnostic values ranging from 0.63 to 0.84. Multiprotein classifiers based on differentially expressed peaks allowed the classification of lung cancer and benign disease with an area under the curve ranging from 0.991 to 0.994. Using a cross-validation methodology, diagnostic accuracy was 93.1% (sensitivity 94.3%, specificity 85.9%), and more than 90% of the stage I/II lung cancers were correctly classified. Finally, in the prognosis part of the study, a 4628 Da protein was found to be significantly and independently associated with prognosis in advanced stage non-small cell lung cancer patients (p = 0.0005).ConclusionsThe potential markers that we identified through proteomic fingerprinting could accurately classify lung cancers in a high-risk population and predict survival in a non-small cell lung cancer population

A transcriptomic continuum of differentiation arrest identifies myeloid interface acute leukemias with poor prognosis

Abstract: Classification of acute lymphoblastic and myeloid leukemias (ALL and AML) remains heavily based on phenotypic resemblance to normal hematopoietic precursors. This framework can provide diagnostic challenges for immunophenotypically heterogeneous immature leukemias, and ignores recent advances in understanding of developmental multipotency of diverse normal hematopoietic progenitor populations that are identified by transcriptional signatures. We performed transcriptional analyses of a large series of acute myeloid and lymphoid leukemias and detected significant overlap in gene expression between cases in different diagnostic categories. Bioinformatic classification of leukemias along a continuum of hematopoietic differentiation identified leukemias at the myeloid/T-lymphoid interface, which shared gene expression programs with a series of multi or oligopotent hematopoietic progenitor populations, including the most immature CD34+CD1a−CD7− subset of early thymic precursors. Within these interface acute leukemias (IALs), transcriptional resemblance to early lymphoid progenitor populations and biphenotypic leukemias was more evident in cases originally diagnosed as AML, rather than T-ALL. Further prognostic analyses revealed that expression of IAL transcriptional programs significantly correlated with poor outcome in independent AML patient cohorts. Our results suggest that traditional binary approaches to acute leukemia categorization are reductive, and that identification of IALs could allow better treatment allocation and evaluation of therapeutic options

A transcriptomic continuum of differentiation arrest identifies myeloid interface acute leukemias with poor prognosis

Abstract: Classification of acute lymphoblastic and myeloid leukemias (ALL and AML) remains heavily based on phenotypic resemblance to normal hematopoietic precursors. This framework can provide diagnostic challenges for immunophenotypically heterogeneous immature leukemias, and ignores recent advances in understanding of developmental multipotency of diverse normal hematopoietic progenitor populations that are identified by transcriptional signatures. We performed transcriptional analyses of a large series of acute myeloid and lymphoid leukemias and detected significant overlap in gene expression between cases in different diagnostic categories. Bioinformatic classification of leukemias along a continuum of hematopoietic differentiation identified leukemias at the myeloid/T-lymphoid interface, which shared gene expression programs with a series of multi or oligopotent hematopoietic progenitor populations, including the most immature CD34+CD1a−CD7− subset of early thymic precursors. Within these interface acute leukemias (IALs), transcriptional resemblance to early lymphoid progenitor populations and biphenotypic leukemias was more evident in cases originally diagnosed as AML, rather than T-ALL. Further prognostic analyses revealed that expression of IAL transcriptional programs significantly correlated with poor outcome in independent AML patient cohorts. Our results suggest that traditional binary approaches to acute leukemia categorization are reductive, and that identification of IALs could allow better treatment allocation and evaluation of therapeutic options

Chemotherapy or allogeneic transplantation in high-risk Philadelphia chromosome–negative adult lymphoblastic leukemia

The need for allogeneic hematopoietic stem cell transplantation (allo-HSCT) in adults with Philadelphia chromosome–negative (Ph−) acute lymphoblastic leukemia (ALL) with high-risk (HR) features and adequate measurable residual disease (MRD) clearance remains unclear. The aim of the ALL-HR-11 trial was to evaluate the outcomes of HR Ph− adult ALL patients following chemotherapy or allo-HSCT administered based on end-induction and consolidation MRD levels. Patients aged 15 to 60 years with HR-ALL in complete response (CR) and MRD levels (centrally assessed by 8-color flow cytometry) <0.1% after induction and <0.01% after early consolidation were assigned to receive delayed consolidation and maintenance therapy up to 2 years in CR. The remaining patients were allocated to allo-HSCT. CR was attained in 315/348 patients (91%), with MRD <0.1% after induction in 220/289 patients (76%). By intention-to-treat, 218 patients were assigned to chemotherapy and 106 to allo-HSCT. The 5-year (±95% confidence interval) cumulative incidence of relapse (CIR), overall survival (OS), and event-free survival probabilities for the whole series were 43% ± 7%, 49% ± 7%, and 40% ± 6%, respectively, with CIR and OS rates of 45% ± 8% and 59% ± 9% for patients assigned to chemotherapy and of 40% ± 12% and 38% ± 11% for those assigned to allo-HSCT, respectively. Our results show that avoiding allo-HSCT does not hamper the outcomes of HR Ph− adult ALL patients up to 60 years with adequate MRD response after induction and consolidation. Better postremission alternative therapies are especially needed for patients with poor MRD clearance

RUNX1-dependent RAG1 deposition instigates human TCR-δ locus rearrangement

V(D)J recombination of TCR loci is regulated by chromatin accessibility to RAG1/2 proteins, rendering RAG1/2 targeting a potentially important regulator of lymphoid differentiation. We show that within the human TCR-α/δ locus

Rôle des récepteurs cytokiniques et de leur signalisation dans l'hématopoièse normale et pathologique (application aux leucémies aiguës lymphoblastiques et aux mastocytoses)

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

Recherche de marqueurs sériques des cancers bronchiques par approche protéomique

MONTPELLIER-BU Médecine UPM (341722108) / SudocPARIS-BIUM (751062103) / SudocMONTPELLIER-BU Médecine (341722104) / SudocSudocFranceF