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- Friboulet, Luc, et al.
(författare)
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Molecular Characteristics of ERCC1-Negative versus ERCC1-Positive Tumors in Resected NSCLC
- 2011
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Ingår i: Clinical Cancer Research. - 1078-0432 .- 1557-3265. ; 17:17, s. 5562-5572
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Excision repair cross-complementation group 1 (ERCC1) is a protein involved in repair of DNA platinum adducts and stalled DNA replication forks. We and others have previously shown the influence of ERCC1 expression upon survival rates and benefit of cisplatin-based chemotherapy in patients with resected non-small-cell lung cancer (NSCLC). However, little is known about the molecular characteristics of ERCC1-positive and ERCC1-negative tumors. Experimental Design: We took advantage of a cohort of 91 patients with resected NSCLC, for which we had matched frozen and paraffin-embedded samples to explore the comparative molecular portraits of ERCC1-positive and ERCC1-negative tumors of NSCLC. We carried out a global molecular analysis including assessment of ERCC1 expression levels by using both immunohistochemistry (IHC) and quantitative reverse transcriptase PCR (qRT-PCR), genomic instability, global gene and miRNA expression, and sequencing of selected key genes involved in lung carcinogenesis. Results: ERCC1 protein and mRNA expression were significantly correlated. However, we observed several cases with clear discrepancies. We noted that ERCC1-negative tumors had a higher rate of genomic abnormalities versus ERCC1-positive tumors. ERCC1-positive tumors seemed to share a common DNA damage response (DDR) phenotype with the overexpression of seven genes linked to DDR. The miRNA expression analysis identified miR-375 as significantly underexpressed in ERCC1-positive tumors. Conclusions: Our data show inconsistencies in ERCC1 expression between IHC and qRT-PCR readouts. Furthermore, ERCC1 status is not linked to specific mutational patterns or frequencies. Finally, ERCC1negative tumors have a high rate of genomic aberrations that could consequently influence prognosis in patients with resected NSCLC. Clin Cancer Res; 17(17); 5562-72.
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| 2. |
- Kroeze, Leonie I., et al.
(författare)
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Evaluation of a Hybrid Capture-Based Pan-Cancer Panel for Analysis of Treatment Stratifying Oncogenic Aberrations and Processes
- 2020
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Ingår i: Journal of Molecular Diagnostics. - : Elsevier. - 1525-1578 .- 1943-7811. ; 22:6, s. 757-769
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Tidskriftsartikel (refereegranskat)abstract
- Stratification of patients for targeted and immune-based therapies requires extensive genomic profiling that enables sensitive detection of clinically relevant variants and interrogation of biomarkers, such as tumor mutational burden (TMB) and microsatellite instability (MSI). Detection of single and multiple nucleotide variants, copy number variants, MSI, and TMB was evaluated using a commercially available next-generation sequencing panel containing 523 cancer-related genes (1.94 megabases). Analysis of formalin-fixed, paraffin-embedded tissue sections and cytologic material from 45 tumor samples showed that all previously known MSI-positive samples (n = 7), amplifications (n = 9), and pathogenic variants (n = 59) could be detected. TMB and MSI scores showed high intralaboratory and interlaboratory reproducibility (eight samples tested in 11 laboratories). For reliable TMB analysis, 20 ng DNA was shown to be sufficient, even for relatively poor-quality samples. A minimum of 20% neoplastic cells was required to minimize variations in TMB values induced by chromosomal instability or tumor heterogeneity. Subsequent analysis of 58 consecutive lung cancer samples in a diagnostic setting was successful and revealed sufficient somatic mutations to generate mutational signatures in 14 cases. In conclusion, the 523-gene assay can be applied for evaluation of multiple DNA-based biomarkers relevant for treatment selection.
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| 3. |
- Lazar, Vladimir, et al.
(författare)
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Integrated molecular portrait of non-small cell lung cancers
- 2013
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Ingår i: BMC Medical Genomics. - : Springer Science and Business Media LLC. - 1755-8794. ; 6:1, s. 53-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods: Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results: At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of similar to 800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions: Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.
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