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Gene expression profiling of the adjacent airway field cancerization in early stage NSCLC

ABSTRACT: Previous work has shown that lung tumors and normal-appearing adjacent lung tissues share specific abnormalities that may be highly pertinent to the pathogenesis of lung cancer. However, the global and molecular adjacent airway field cancerization in non-small cell lung cancer (NSCLC) has not been characterized before. We sought to understand the transcriptomic architecture of the adjacent airway field canerization, in conjunction with tumors, to gain additional insights into the lung cancer biology and oncogenesis. We analyzed the transcriptome, using the Affymetrix Human Gene 1.0 ST platform, of matched NSCLC tumors, multiple normal airway epithelia with differential distance from the tumors as well as uninvolved normal lung tissues. We analyzed the airway field cancerization transcritpome to determine global differentially expressed cancerization profiles in adjacent airways as well as airway profiles that may be modulated by distance from tumors.

ORGANISM(S): Homo sapiens

SUBMITTER: Kadara H

PROVIDER: S-ECPF-GEOD-44077 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

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Project description:To investigate the differentiated whole genome expression profiling of gastric high- and low-grade intraepithelial neoplasia and early-stage adenocarcinoma.Gastric specimens from an upper magnifying chromoendoscopic targeted biopsy were collected from March 2010 to May 2013. Whole genome expression profiling was performed on 19 low-grade intraepithelial neoplasia (LGIN), 20 high-grade intraepithelial neoplasia (HGIN), 19 early-stage adenocarcinoma (EGC), and 19 chronic gastritis tissue samples using Agilent 4 × 44K Whole Human Genome microarrays. Differentially expressed genes between different types of lesions were identified using an unpaired t-test and corrected with the Benjamini and Hochberg false discovery rate algorithm. A gene ontology (GO) enrichment analysis was performed using the GeneSpring software GX 12.6. The differentially expressed gene was verified using a real-time TaqMan® PCR assay with independent tissue samples, including 26 LGIN, 15 HGIN, 14 EGC, and 20 chronic gastritis. The expression of G0S2 were further validated by immunohistochemical staining (IHC) in 24 LGIN, 40 HGIN, 30 EGC and 61 chronic gastritis specimens.The gene expression patterns of LGIN and HGIN tissues were distinct. There were 2521 significantly differentially expressed transcripts in HGIN, with 951 upregulated and 1570 downregulated. A GO enrichment analysis demonstrated that the most striking overexpressed transcripts in HGIN compared with LGIN were in the category of metabolism, defense response, and nuclear factor ?B (NF-?B) cascade. While the vast majority of transcripts had barely altered expression in HGIN and EGC tissues, only 38 transcripts were upregulated in EGC. A GO enrichment analysis revealed that the alterations of the immune response were most prominent in the progression from HGIN to EGC. It is worth noting that, compared with LGIN, 289 transcripts were expressed at higher levels both in HGIN and EGC. A characteristic gene, G0/G1 switch 2 (G0S2) was one of the 289 transcripts and related to metabolism, the immune response, and the NF-?B cascade, and its expression was validated in independent samples through real-time TaqMan® PCR and immunohistochemical staining. In real-time PCR analysis, the expression of G0S2 was elevated both in HGIN and EGC compared with that in LGIN (P < 0.01 and P < 0.001, respectively). In IHC analysis, G0S2 immunoreactivity was detected in the cytoplasmic of neoplastic cells, but was undetectable in chronic gastritis cells. The G0S2 expression in HGIN was higher than that of LGIN (P = 0.012, ? (2) = 6.28) and EGC (P = 0.008, ? (2) = 6.94).A clear biological distinction between gastric high- and low-grade intraepithelial neoplasia was identified, and provides molecular evidence for clinical application.

Project description:Purpose Gene expression profiling assays are frequently used to guide adjuvant chemotherapy decisions in hormone receptor-positive, lymph node-negative breast cancer. We hypothesized that the clinical value of these new tools would be more fully realized when appropriately integrated with high-quality clinicopathologic data. Hence, we developed a model that uses routine pathologic parameters to estimate Oncotype DX recurrence score (ODX RS) and independently tested its ability to predict ODX RS in clinical samples. Patients and Methods We retrospectively reviewed ordered ODX RS and pathology reports from five institutions (n = 1,113) between 2006 and 2013. We used locally performed histopathologic markers (estrogen receptor, progesterone receptor, Ki-67, human epidermal growth factor receptor 2, and Elston grade) to develop models that predict RS-based risk categories. Ordering patterns at one site were evaluated under an integrated decision-making model incorporating clinical treatment guidelines, immunohistochemistry markers, and ODX. Final locked models were independently tested (n = 472). Results Distribution of RS was similar across sites and to reported clinical practice experience and stable over time. Histopathologic markers alone determined risk category with > 95% confidence in > 55% (616 of 1,113) of cases. Application of the integrated decision model to one site indicated that the frequency of testing would not have changed overall, although ordering patterns would have changed substantially with less testing of estimated clinical risk-high or clinical risk-low cases and more testing of clinical risk-intermediate cases. In the validation set, the model correctly predicted risk category in 52.5% (248 of 472). Conclusion The proposed model accurately predicts high- and low-risk RS categories (> 25 or ≤ 25) in a majority of cases. Integrating histopathologic and molecular information into the decision-making process allows refocusing the use of new molecular tools to cases with uncertain risk.

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Gene expression profiling of the adjacent airway field cancerization in early stage NSCLC

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