Proposing Specific Neuronal Epithelial-to-Mesenchymal Transition Genes as an Ancillary Tool for Differential Diagnosis among Pulmonary Neuroendocrine Neoplasms

Pulmonary neuroendocrine neoplasms (PNENs) are currently classified into four major histotypes, including typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). This classification was designed to be applied to surgical specimens mostly anchored in morphological parameters, resulting in considerable overlapping among PNENs, which may result in important challenges for clinicians’ decisions in the case of small biopsies. Since PNENs originate from the neuroectodermic cells, epithelial-to-mesenchymal transition (EMT) gene expression shows promise as biomarkers involved in the genotypic transformation of neuroectodermic cells, including mutation burden with the involvement of chromatin remodeling genes, apoptosis, and mitosis rate, leading to modification in final cellular phenotype. In this situation, additional markers also applicable to biopsy specimens, which correlate PNENs subtypes with systemic treatment response, are much needed, and current potential candidates are neurogenic EMT genes. This study investigated EMT genes expression and its association with PNENs histotypes in tumor tissues from 24 patients with PNENs. PCR Array System for 84 EMT-related genes selected 15 differentially expressed genes among the PNENs, allowing to discriminate TC from AC, LCNEC from AC, and SCLC from AC. Functional enrichment analysis of the EMT genes differentially expressed among PNENs subtypes showed that they are involved in cellular proliferation, extracellular matrix degradation, regulation of cell apoptosis, oncogenesis, and tumor cell invasion. Interestingly, four EMT genes (MAP1B, SNAI2, MMP2, WNT5A) are also involved in neurological diseases, in brain metastasis, and interact with platinum-based chemotherapy and tyrosine–kinase inhibitors. Collectively, these findings emerge as an important ancillary tool to improve the strategies of histologic diagnosis in PNENs and unveil the four EMT genes that can play an important role in driving chemical response in PNENs

CYP1A2*1C, CYP2E1*5B, and GSTM1 polymorphisms are predictors of risk and poor outcome in head and neck squamous cell carcinoma patients

Head and neck squamous cell carcinoma (HNSCC) is associated with environmental factors, especially tobacco and alcohol consumption. Most of the carcinogens present in tobacco smoke are converted into DNA-reactive metabolites by cytochrome P450 (CYPs) enzymes and detoxification of these substances is performed by glutathione S-transferases (GSTs). It has been suggested that genetic alterations, such as polymorphisms, play an important role in tumorigenesis and HNSCC progression. The aim of this study was to investigate CYP1A1, CYP1A2, CYP2E1, GSTM1, and GSTT1 polymorphisms as risk factors in HNSCC and their association with clinicopathologic data. The patients comprised 153 individuals with HNSCC (cases) and 145 with no current or previous diagnosis of cancer (controls). Genotyping of the single nucleotide polymorphisms (SNPs) of the CYP1A1, CYP1A2, and CYP2E1 genes was performed by PCR-RFLP and the GSTM1 and GSTT1 copy number polymorphisms (CNPs) were analyzed by PCR-multiplex. As expected, a significant difference was detected for tobacco and alcohol consumption between cases and controls (P < 0.001). It was observed that the CYP1A2*1D (OR = 16.24) variant and GSTM1 null alleles (OR = 0.02) confer increased risk of HNSCC development (P < 0.001). In addition, head and neck cancer alcohol consumers were more frequently associated with the CYP2E1*5B variant allele than control alcohol users (P < 0.0001, OR = 190.6). The CYP1A2*1C polymorphism was associated with tumor recurrence (log-rank test, P = 0.0161). The CYP2E1*5B and GSTM1 null alleles were significantly associated with advanced clinical stages (T3 + T4; P = 0.022 and P = 0.028, respectively). Overall, the findings suggested that the genetic polymorphisms studied are predictors of risk and are also associated with tumor recurrence, since they are important for determining the parameters associated with tumor progression and poor outcomes in HNSCC. (C) 2009 Elsevier Ltd. All rights reserved.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo[FAPESP 04/00639-2]Fundacao de Amparo a Pesquisa do Estado de Sao Paulo[CEPID/FAPESP 98/14335]National Council for Scientific and Technological Development (CNPq

MicroRNAs Discriminate Familial from Sporadic Non-BRCA1/2 Breast Carcinoma Arising in Patients ≤35 Years

<div><p>The influence of genetic factors may contribute to the poor prognosis of breast cancer (BC) at a very young age. However <i>BRCA1/2</i> mutations could not explain the majority of cases arising in these patients. MicroRNAs (miRs) have been implicated in biological processes associated with BC. Therefore, we investigated differences in miRs expression between tumors from young patients (≤35 years) with sporadic or familial history and non-carriers of <i>BRCA1/2</i> mutations. Thirty-six young Brazilian patients were divided into 2 groups: sporadic (NF-BC) or familial breast cancer (F-BC). Most of the samples were classified as luminal A and B and the frequency of subtypes did not differ between familial or sporadic cases. Using real time qPCR and discriminant function analysis, we identified 9 miRs whose expression levels rather than miR identity can discriminate between both patient groups. Candidate predicted targets were determined by combining results from miRWalk algorithms with mRNA expression profiles (n = 91 differently expressed genes). MiR/mRNA integrated analysis identified 91 candidate genes showing positive or negative correlation to at least 1 of the 9 miRs. Co-expression analysis of these genes with 9 miRs indicated that 49 differentially co-expressed miR-gene interactions changes in F-BC tumors as compared to those of NF-BC tumors. Out of 49, 17 (34.6%) of predicted miR-gene interactions showed an inverse correlation suggesting that miRs act as post-transcriptional regulators, whereas 14 (28.6%) miR-gene pairs tended to be co-expressed in the same direction indicating that the effects exerted by these miRs pointed to a complex level of target regulation. The remaining 18 pairs were not predicted by our criteria suggesting involvement of other regulators. MiR–mRNA co-expression analysis allowed us to identify changes in the miR-mRNA regulation that were able to distinguish tumors from familial and sporadic young BC patients non-carriers of BRCA mutations.</p></div

Co-expression matrixes.

<p>Co-expression matrixes of the 91 differentially expressed genes vs 9 differentially expressed miRs for F-BC (A) and NF-BC (B), respectively. The colors represent the co-expression values reaching from 1 to −1 for red and green, respectively. F-BC, familial breast cancer; NF-BC, non-familial breast cancer.</p

Frequency of clinical and histopathological characteristics according to the groups—familial breast cancer (F-BC) and sporadic breast cancer (NF-BC).

<p>Frequency of clinical and histopathological characteristics according to the groups—familial breast cancer (F-BC) and sporadic breast cancer (NF-BC).</p

Cross-validation analysis graphic.

<p>Representative <i>cross-validation analysis</i> graphic of 35 patients from the F-BC and NF-BC groups. Black spots indicate F-BC samples while plus signs indicate NF-BC samples. The line represents the limit discriminant function between groups. F-BC, familial breast cancer; NF-BC, non-familial breast cancer.</p

Target prediction graph.

<p>Graph displaying the number of predicted targets from miRWalk for each miRNA differentially expressed between F-BC and NF-BC groups. F-BC, familial breast cancer; NF-BC, non-familial breast cancer.</p

Illustration of network signatures.

<p>Seventeen miR–mRNA predicted interactions whose co-expression are significantly different between F-BC (A) and NF-BC (B) groups. Color edges represent positive (green) or negative (red) Pearson correlation values. The edge thickness indicates the magnitude of Pearson correlation values. The node size is proportional to the fold change of genes (orange nodes) and of miRs (blue nodes) between F-BC to NF-BC groups. F-BC, familial breast cancer; NF-BC, non-familial breast cancer.</p

Patient and sample characteristics.

<p>POS = positive; NEG: negative; Trip. NEG: triple negative; GN: nuclear grade; GH: histological grade; ER: estrogen receptor; PR: progesterone receptor; HER-2: growth factor receptor type 2; NCCN: <i>National Comprehensive Cancer Network</i>. ER, PR, and Her-2 receptor status was defined according to IHC.TNM =  tumor classification based on stage according to TNM criteria suggested by WHO (World Health Organization): I (T1N0M0); IIA (T0N1M0, T1N1M0, T2N0M0); IIB (T2N1M0,T3N0M0); IIIA (T0N2M0, T1N2M0, T2N2M0, T3N1M0, T3N2M0); IIIB (T4N0M0,T4N1M0, T4N2M0); IV (every T, N, and M1).</p

Comprehensive Analysis of <em>BRCA1</em>, <em>BRCA2</em> and <em>TP53</em> Germline Mutation and Tumor Characterization: A Portrait of Early-Onset Breast Cancer in Brazil

<div><p>Germline mutations in <i>BRCA1</i>, <i>BRCA2</i> and <i>TP53</i> genes have been identified as one of the most important disease-causing issues in young breast cancer patients worldwide. The specific defective biological processes that trigger germline mutation-associated and -negative tumors remain unclear. To delineate an initial portrait of Brazilian early-onset breast cancer, we performed an investigation combining both germline and tumor analysis. Germline screening of the <i>BRCA1, BRCA2</i>, <i>CHEK2</i> (c.1100delC<i>)</i> and <i>TP53</i> genes was performed in 54 unrelated patients <35 y; their tumors were investigated with respect to transcriptional and genomic profiles as well as hormonal receptors and HER2 expression/amplification. Germline mutations were detected in 12 out of 54 patients (22%) [7 in <i>BRCA1</i> (13%), 4 in <i>BRCA2</i> (7%) and one in <i>TP53</i> (2%) gene]. A cancer familial history was present in 31.4% of the unrelated patients, from them 43.7% were carriers for germline mutation (37.5% in <i>BRCA1</i> and in 6.2% in the <i>BRCA2</i> genes). Fifty percent of the unrelated patients with hormone receptor-negative tumors carried <i>BRCA1</i> mutations, percentage increasing to 83% in cases with familial history of cancer. Over-representation of DNA damage-, cellular and cell cycle-related processes was detected in the up-regulated genes of <i>BRCA1/2</i>-associated tumors, whereas cell and embryo development-related processes were over-represented in the up-regulated genes of <i>BRCA1/2</i>-negative tumors, suggesting distinct mechanisms driving the tumorigenesis. An initial portrait of the early-onset breast cancer patients in Brazil was generated pointing out that hormone receptor-negative tumors and positive familial history are two major risk factors for detection of a <i>BRCA1</i> germline mutation. Additionally, the data revealed molecular factors that potentially trigger the tumor development in young patients.</p> </div