Biochip-Based Detection of KRAS Mutation in Non-Small Cell Lung Cancer

This study is aimed at evaluating the potential of a biochip assay to sensitively detect KRAS mutation in DNA from non-small cell lung cancer (NSCLC) tissue samples. The assay covers 10 mutations in codons 12 and 13 of the KRAS gene, and is based on mutant-enriched PCR followed by reverse-hybridization of biotinylated amplification products to an array of sequence-specific probes immobilized on the tip of a rectangular plastic stick (biochip). Biochip hybridization identified 17 (21%) samples to carry a KRAS mutation of which 16 (33%) were adenocarcinomas and 1 (3%) was a squamous cell carcinoma. All mutations were confirmed by DNA sequencing. Using 10 ng of starting DNA, the biochip assay demonstrated a detection limit of 1% mutant sequence in a background of wild-type DNA. Our results suggest that the biochip assay is a sensitive alternative to protocols currently in use for KRAS mutation testing on limited quantity samples

SOCS2 is part of a highly prognostic 4-gene signature in AML and promotes disease aggressiveness

Acute myeloid leukemia (AML) is a heterogeneous disease with respect to its genetic and molecular basis and to patients´ outcome. Clinical, cytogenetic, and mutational data are used to classify patients into risk groups with different survival, however, within-group heterogeneity is still an issue. Here, we used a robust likelihood-based survival modeling approach and publicly available gene expression data to identify a minimal number of genes whose combined expression values were prognostic of overall survival. The resulting gene expression signature (4-GES) consisted of 4 genes (SOCS2, IL2RA, NPDC1, PHGDH), predicted patient survival as an independent prognostic parameter in several cohorts of AML patients (total, 1272 patients), and further refined prognostication based on the European Leukemia Net classification. An oncogenic role of the top scoring gene in this signature, SOCS2, was investigated using MLL-AF9 and Flt3-ITD/NPM1c driven mouse models of AML. SOCS2 promoted leukemogenesis as well as the abundance, quiescence, and activity of AML stem cells. Overall, the 4-GES represents a highly discriminating prognostic parameter in AML, whose clinical applicability is greatly enhanced by its small number of genes. The newly established role of SOCS2 in leukemia aggressiveness and stemness raises the possibility that the signature might even be exploitable therapeutically

SOCS2 is part of a highly prognostic 4-gene signature in AML and promotes disease aggressiveness.

Acute myeloid leukemia (AML) is a heterogeneous disease with respect to its genetic and molecular basis and to patients´ outcome. Clinical, cytogenetic, and mutational data are used to classify patients into risk groups with different survival, however, within-group heterogeneity is still an issue. Here, we used a robust likelihood-based survival modeling approach and publicly available gene expression data to identify a minimal number of genes whose combined expression values were prognostic of overall survival. The resulting gene expression signature (4-GES) consisted of 4 genes (SOCS2, IL2RA, NPDC1, PHGDH), predicted patient survival as an independent prognostic parameter in several cohorts of AML patients (total, 1272 patients), and further refined prognostication based on the European Leukemia Net classification. An oncogenic role of the top scoring gene in this signature, SOCS2, was investigated using MLL-AF9 and Flt3-ITD/NPM1c driven mouse models of AML. SOCS2 promoted leukemogenesis as well as the abundance, quiescence, and activity of AML stem cells. Overall, the 4-GES represents a highly discriminating prognostic parameter in AML, whose clinical applicability is greatly enhanced by its small number of genes. The newly established role of SOCS2 in leukemia aggressiveness and stemness raises the possibility that the signature might even be exploitable therapeutically

Molecular pathogenesis of lung cancer and potential translational applications

Molecular studies of lung cancer using individual genes and global approaches of gene analysis have shown several observations that are ready to be translated into clinically useful information to provide new methods of diagnosis, risk assessment, prevention, and treatment. Clinically evident lung cancers have acquired 20 or more clonal genetic alterations, and tumor acquired promoter hypermethylation is a frequent epigenetic mechanism of inactivation of gene expression in lung cancer giving at least another 10-20 lesions. Furthermore, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) have acquired different genetic and epigenetic lesions. Alterations in 3p tumor suppression genes (TSGs) appear especially early, including those of RASSF1A and SEMA3B at 3p21.3, followed by changes in 9p (p16), 8p, and then multiple other sites. Changes consistent with oxidative damage leading to mitotic recombination are frequently seen. Smoking-damaged, histologically normal epithelium as well as epithelium with preneoplastic/preinvasive changes have thousands of clonal patches containing genetic alterations. Finally, correcting even single genetic abnormalities can reverse the malignant phenotype

Systemic Inflammation and Activation of Haemostasis Predict Poor Prognosis and Response to Chemotherapy in Patients with Advanced Lung Cancer

Systemic inflammation and activation of haemostasis are common in patients with lung cancer. Both conditions support tumour growth and metastasis. Therefore, inflammatory and haemostatic biomarkers might be useful for prediction of survival and therapy response. Patients with unresectable/metastatic lung cancer initiating 1st-line chemotherapy (n = 277, 83% non-small cell lung cancer) were followed in a prospective observational cohort study. A comprehensive panel of haemostatic biomarkers (D-dimer, prothrombin fragment 1+2, soluble P-selectin, fibrinogen, coagulation factor VIII, peak thrombin generation), blood count parameters (haemoglobin, leucocytes, thrombocytes) and inflammatory markers (neutrophil-lymphocyte ratio, lymphocyte-monocyte ratio, platelet-lymphocyte ratio, C-reactive protein) were measured at baseline. We assessed the association of biomarkers with mortality, progression-free-survival (PFS) and disease-control-rate (DCR). A biomarker-based prognostic model was derived. Selected inflammatory and haemostatic biomarkers were strong and independent predictors of mortality and therapy response. The strongest predictors (D-dimer, LMR, CRP) were incorporated in a unified biomarker-based prognostic model (1-year overall-survival (OS) by risk-quartiles: 79%, 69%, 51%, 24%; 2-year-OS: 53%, 36%, 23%, 8%; log-rank p < 0.001). The biomarker-based model further predicted shorter PFS and lower DCR. In conclusion, inflammatory and haemostatic biomarkers predict poor prognosis and treatment-response in patients with advanced lung cancer. A biomarker-based prognostic score efficiently predicts mortality and disease progression beyond clinical characteristics

Aberrant promoter methylation of multiple genes in non-small cell lung cancers

Aberrant methylation of CpG islands acquired in tumor cells in promoter regions is one method for loss of gene function. We determined the frequency of aberrant promoter methylation (referred to as methylation) of the genes retinoic acid receptor β-2 (RARβ), tissue inhibitor of metalloproteinase 3 (TIMP-3), p16, O-methylguanine-DNA-methyltransferase (MGMT), death-associated protein kinase (DAPK), E-cadherin (ECAD), p14, and glutathione S-transferase P1 (GSTP1) in 107 resected primary non-small cell lung cancers (NSCLCs) and in 104 corresponding nonmalignant lung tissues by methylation-specific PCR. Methylation in the tumor samples was detected in 40% for RARβ, 26% for TIMP-3, 25% for p16, 21% for MGMT, 19% for DAPK, 18% for ECAD, 8% for p14, and 7% for GSTP1, whereas it was not seen in the vast majority of the corresponding nonmalignant tissues. Moreover, p16 methylation was correlated with loss of p16 expression by immunohistochemistry. A total of 82% of the NSCLCs had methylation of at least one of these genes; 37% of the NSCLCs had one gene methylated, 22% of the NSCLCs had two genes methylated, 13% of the NSCLCs had three genes methylated, 8% of the NSCLCs had four genes methylated, and 2% of the NSCLCs had five genes methylated. Methylation of these genes was correlated with some clinicopathological characteristics of the patients. In comparing the methylation patterns of tumors and nonmalignant lung tissues from the same patients, there were many discordancies where the genes methylated in nonmalignant tissues were not methylated in the corresponding tumors. This suggests that the methylation was occurring as a preneoplastic change. We conclude that these findings confirm in a large sample that methylation is a frequent event in NSCLC, can also occur in smoking-damaged nonmalignant lung tissues, and may be the most common mechanism to inactivate cancer-related genes in NSCLC