Dataset Information

Characterization of Single-Nucleotide Polymorphisms in the Tumor Necrosis Factor ? Promoter Region and in Lymphotoxin ? in Squamous Intraepithelial Lesions, Precursors of Cervical Cancer.

ABSTRACT: Development of cervical cancer is a long process of abnormal cancerous cell growth in the cervix and is primarily the result of infection with specific high-risk types of human papillomavirus (HPV). The cytokines tumor necrosis factor ? (TNF?) and lymphotoxin ? (LTA) have an important role in all stages of cervical cancer and have the ability to induce the regression or promote the development of human tumors. Biologically important single-nucleotide polymorphisms (SNPs) occur within the TNF? and LTA genes. Therefore, the purpose of this study was to investigate the SNPs in the TNF? promoter region (-163, -238, -244, -308, -376, -857, -863, and -1031) and in the first intron of LTA (+252) in women with precursor lesions of cervical cancer. Overall, we studied 396 women from Mexico City. A total of 191 patients with HPV infection and precursor cervical lesions were subdivided in two groups: those with low-grade squamous intraepithelial lesions (n = 132) and those with high-grade squamous intraepithelial lesions (n = 59). Women (n = 205) negative for HPV and without cervical lesions were also included in the study. DNA was extracted from peripheral white blood cells and from cervical samples, and detection of biallelic polymorphisms of TNF? and LTA was performed using the polymerase chain reaction-sequence-specific oligonucleotide probe and restriction fragment length polymorphism techniques, respectively. We demonstrated that risk is associated with the genotype G/A (odds ratio = 2.48) and that protection is associated with the genotype G/G of SNP TNF? -376 (odds ratio = 0.37).

SUBMITTER: Nieves-Ramirez ME

PROVIDER: S-EPMC3243656 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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Characterization of Single-Nucleotide Polymorphisms in the Tumor Necrosis Factor α Promoter Region and in Lymphotoxin α in Squamous Intraepithelial Lesions, Precursors of Cervical Cancer.

Nieves-Ramirez Miriam Enriqueta ME Partida-Rodriguez Oswaldo O Alegre-Crespo Pedro Eduardo PE Tapia-Lugo Maria Del Carmen Mdel C Perez-Rodriguez Martha Esthela ME

Translational oncology 20111201 6

Development of cervical cancer is a long process of abnormal cancerous cell growth in the cervix and is primarily the result of infection with specific high-risk types of human papillomavirus (HPV). The cytokines tumor necrosis factor α (TNFα) and lymphotoxin α (LTA) have an important role in all stages of cervical cancer and have the ability to induce the regression or promote the development of human tumors. Biologically important single-nucleotide polymorphisms (SNPs) occur within the TNFα an ...[more]

PMID: 22190997

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Project description:It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

Project description:Cervical cancer is an important health concern worldwide and is one of the leading causes of death in Mexican women. Previous studies have shown changes in the female genital tract microbe community related to human papillomavirus (HPV) infection and cervical cancer; yet, this link remains unexplored in many human populations. This study evaluated the vaginal bacterial community among Mexican women with precancerous squamous intraepithelial lesions (SIL). We sequenced the V3 region of the 16S rRNA gene in cervical samples from 228 Mexican women, including 121 participants with SIL, most of which were HPV positive, and 107 healthy women without HPV infection or SIL. The presence of SIL was associated with changes in composition (beta diversity) and with a higher species richness (Chao1). A comparison of HPV-positive women with and without SIL showed that microbiota changes occurred even in the absence of SIL. Multivariate association with linear models (MaAsLin) analysis yielded independent associations between HPV infection and an increase in the relative abundance of Brachybacterium conglomeratum and Brevibacterium aureum as well as a decrease in two Lactobacillus iners operational taxonomic units (OTUs). We also identified a positive independent association between HPV-16, the most common HPV subtype linked to SIL, and Brachybacterium conglomeratum. Our work indicates that HPV infection leading to SIL is primarily associated with shifts in vaginal microbiota composition, some of which may be specific to this human population. IMPORTANCE Human papillomavirus (HPV) plays a critical role in cervical carcinogenesis but is not sufficient for cervical cancer development, indicating the involvement of other factors. The vaginal microbiota is an important factor in controlling infections caused by HPV, and, depending on its composition, it can modulate the microenvironment in vaginal mucosa against viral infections. Ethnic and sociodemographic factors influence differences in vaginal microbiome composition, which underlies the dysbiotic patterns linked to HPV infection and cervical cancer across different populations of women. Here, we provide evidence for associations between vaginal microbiota patterns and HPV infection linked to ethnic and sociodemographic factors. To our knowledge, this is the first report of the species Brevibacterium aureum and Brachybacterium conglomeratum linked to HPV infection or squamous intraepithelial lesions (SIL).

Project description:BackgroundThe complete response rate of cervical high-grade squamous intraepithelial lesion (cHSIL) patients to imiquimod immunotherapy is approximately 60%. Consequently, many patients are exposed to unnecessary adverse effects of imiquimod. On the other hand, conventional surgical large loop excision therapy is associated with increased risk of premature births in subsequent pregnancies. An in-depth analysis of the cHSIL immune microenvironment was performed in order to identify and develop a predictive biomarker for response to imiquimod, to maximize therapy efficacy and to avoid adverse effects in patients unlikely to respond.MethodsBiopsies of 35 cHSIL patients, before and 10 weeks on imiquimod treatment, were analyzed by two multispectral seven-color immunofluorescence panels for T cell and myeloid cell composition in relation to treatment response. Based on these results a simplified immunohistochemical detection protocol was developed. Samples were scanned with the Vectra multispectral imaging system and cells were automatically identified using machine learning.ResultsThe immune microenvironment of complete responders (CR) is characterized by a strong and coordinated infiltration by T helper cells (activated PD1+/type 1 Tbet+), M1-like macrophages (CD68+CD163-) and dendritic cells (CD11c+) prior to imiquimod. The lesions of non-responders (NRs) displayed a high infiltration by CD3+FOXP3+ regulatory T cells. At 10 weeks on imiquimod, a strong influx of intraepithelial and stromal CD4+ T cells was observed in CR but not NR patients. A steep decrease in macrophages occurred both in CR and NR patients, leveling the pre-existing differences in myeloid cell composition between the two groups. Based on the pre-existing immune composition differences, the sum of intraepithelial CD4 T cell, macrophage and dendritic cell counts was used to develop a quantitative simplified one color immunohistochemical biomarker, the CHSIL immune biomarker for imiquimod (CIBI), which can be automatically and unbiasedly quantified and has an excellent predictive capacity (receiver operating characteristic area under the curve 0.95, p<0.0001).ConclusionThe capacity of cHSIL patients to respond to imiquimod is associated with a pre-existing coordinated local immune process, fostering an imiquimod-mediated increase in local T cell infiltration. The CIBI immunohistochemical biomarker has strong potential to select cHSIL patients with a high likelihood to experience a complete response to imiquimod immunotherapy.

Project description:Background Deep learning has presented considerable potential and is gaining more importance in computer assisted diagnosis. As the gold standard for pathologically diagnosing cervical intraepithelial lesions and invasive cervical cancer, colposcopy-guided biopsy faces challenges in improving accuracy and efficiency worldwide, especially in developing countries. To ease the heavy burden of cervical cancer screening, it is urgent to establish a scientific, accurate and efficient method for assisting diagnosis and biopsy. Methods The data were collected to establish three deep-learning-based models. For every case, one saline image, one acetic image, one iodine image and the corresponding clinical information, including age, the results of human papillomavirus testing and cytology, type of transformation zone, and pathologic diagnosis, were collected. The dataset was proportionally divided into three subsets including the training set, the test set and the validation set, at a ratio of 8:1:1. The validation set was used to evaluate model performance. After model establishment, an independent dataset of high-definition images was collected to further evaluate the model performance. In addition, the comparison of diagnostic accuracy between colposcopists and models weas performed. Results The sensitivity, specificity and accuracy of the classification model to differentiate negative cases from positive cases were 85.38%, 82.62% and 84.10% respectively, with an AUC of 0.93. The recall and DICE of the segmentation model to segment suspicious lesions in acetic images were 84.73% and 61.64%, with an average accuracy of 95.59%. Furthermore, 84.67% of high-grade lesions were detected by the acetic detection model. Compared to colposcopists, the diagnostic system performed better in ordinary colposcopy images but slightly unsatisfactory in high-definition images. Implications The deep learning-based diagnostic system could help assist colposcopy diagnosis and biopsy for HSILs.

Dataset Information

Characterization of Single-Nucleotide Polymorphisms in the Tumor Necrosis Factor ? Promoter Region and in Lymphotoxin ? in Squamous Intraepithelial Lesions, Precursors of Cervical Cancer.

Publications

Characterization of Single-Nucleotide Polymorphisms in the Tumor Necrosis Factor α Promoter Region and in Lymphotoxin α in Squamous Intraepithelial Lesions, Precursors of Cervical Cancer.

Similar Datasets

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