Lue Ping Zhao

Gene Expression Profiling Identifies Genes Predictive of Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity. To identify potential biomarkers for the early detection of invasive OSCC, we compared the gene expressions of incident primary OSCC, oral dysplasia, and clinically normal oral tissue from surgical patients without head and neck cancer or preneoplastic oral lesions (controls), using Affymetrix U133 2.0 Plus arrays. We identified 131 differentially expressed probe sets using a training set of 119 OSCC patients and 35 controls. Forward and stepwise logistic regression analyses identified 10 successive combinations of genes which expression differentiated OSCC from controls. The best model included LAMC2, encoding laminin-γ2 chain, and COL4A1, encoding collagen, type IV α1 chain. Subsequent modeling without these two markers showed that COL1A1, encoding collagen, type I α1 chain, and PADI1, encoding peptidyl arginine deiminase, type 1, could also distinguish OSCC from controls. We validated these two models using an internal independent testing set of 48 invasive OSCC and 10 controls and an external testing set of 42 head and neck squamous cell carcinoma cases and 14 controls (GEO GSE6791), with sensitivity and specificity above 95%. These two models were also able to distinguish dysplasia (n = 17) from control (n = 35) tissue. Differential expression of these four genes was confirmed by quantitative reverse transcription-PCR. If confirmed in larger studies, the proposed models may hold promise for monitoring local recurrence at surgical margins and the development of second primary oral cancer in patients with OSCC. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2152–62)

Transcriptional expression profiles of oral squamous cell carcinomas.

Currently, the classification of oral squamous cell carcinoma (OSCC) depends heavily on the clinical and pathologic examination of tissue. This system can lead to the classification of potentially heterogeneous tumors into single groups when they may have different degrees of aggressiveness. No system to date has incorporated genetic changes as a factor by which to classify OSCC tumors.

Comprehensive Analysis of HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 Loci and Squamous Cell Cervical Cancer Risk

Variation in human major histocompatibility genes may influence the risk of squamous cell cervical cancer (SCC) by altering the efficiency of the T-cell-mediated immune response to human papillomavirus (HPV) antigens. We used high-resolution methods to genotype human leukocyte antigen (HLA) class I (A, B, and Cw) and class II (DRB1 and DQB1) loci in 544 women with SCC and 542 controls. Recognizing that HLA molecules are codominantly expressed, we focused on co-occurring alleles. Among 137 allele combinations present at >5% in the case or control groups, 36 were significantly associated with SCC risk. All but one of the 30 combinations that increased risk included DQB1*0301, and 23 included subsets of A*0201-B*4402-Cw*0501-DRB1*0401-DQB1*0301. Another combination, B*4402-DRB1*1101-DQB1*0301, conferred a strong risk of SCC (odds ratio, 10.0; 95% confidence interval, 3.0-33.3). Among the six combinations that conferred a decreased risk of SCC, four included Cw*0701 or DQB1*02. Most multilocus results were similar for SCC that contained HPV16; a notable exception was A*0101-B*0801-Cw*0701-DRB1*0301-DQB1*0201 and its subsets, which were associated with HPV16-positive SCC (odds ratio, 0.5; 95% confidence interval, 0.3-0.9). The main multilocus associations were replicated in studies of cervical adenocarcinoma and vulvar cancer. These data confirm that T helper and cytotoxic T-cell responses are both important cofactors with HPV in cervical cancer etiology and indicate that co-occurring HLA alleles across loci seem to be more important than individual alleles. Thus, certain co-occurring alleles may be markers of disease risk that have clinical value as biomarkers for targeted screening or development of new therapies.

Genomewide Gene Expression Profiles of HPV-Positive and HPV-Negative Oropharyngeal Cancer: Potential Implications for Treatment Choices

OBJECTIVE To study the difference in gene expression between human papillomavirus (HPV)-positive and HPV-negative oral cavity and oropharyngeal squamous cell carcinoma (OSCC). DESIGN We used Affymetrix U133 plus 2.0 arrays to examine gene expression profiles of OSCC and normal oral tissue. The HPV DNA was detected using polymerase chain reaction followed by the Roche LINEAR ARRAY HPV Genotyping Test, and the differentially expressed genes were analyzed to examine their potential biological roles using the Ingenuity Pathway Analysis Software, version 5.0. SETTING Three medical centers affiliated with the University of Washington. PATIENTS A total of 119 patients with primary OSCC and 35 patients without cancer, all of whom were treated at the setting institutions, provided tissues samples for the study. RESULTS Human papillomavirus DNA was found in 41 of 119 tumors (34.5%) and 2 of 35 normal tissue samples (5.7%); 39 of the 43 HPV specimens were HPV-16. A higher prevalence of HPV DNA was found in oropharyngeal cancer (23 of 31) than in oral cavity cancer (18 of 88). We found no significant difference in gene expression between HPV-positive and HPV-negative oral cavity cancer but found 446 probe sets (347 known genes) differentially expressed in HPV-positive oropharyngeal cancer than in HPV-negative oropharyngeal cancer. The most prominent functions of these genes are DNA replication, DNA repair, and cell cycling. Some genes differentially expressed between HPV-positive and HPV-negative oropharyngeal cancer (eg, TYMS, STMN1, CCND1, and RBBP4) are involved in chemotherapy or radiation sensitivity. CONCLUSION These results suggest that differences in the biology of HPV-positive and HPV-negative oropharyngeal cancer may have implications for the management of patients with these different tumors.

A Genetic Expression Profile Associated with Oral Cancer Identifies a Group of Patients at High Risk of Poor Survival

Purpose: To determine if gene expression signature of invasive oral squamous cell carcinoma (OSCC) can subclassify OSCC based on survival. Experimental Design: We analyzed the expression of 131 genes in 119 OSCC, 35 normal, and 17 dysplastic mucosa to identify cluster-defined subgroups. Multivariate Cox regression was used to estimate the association between gene expression and survival. By stepwise Cox regression, the top predictive models of OSCC-specific survival were determined and compared by receiver operating characteristic analysis. Results: The 3-year overall mean ± SE survival for a cluster of 45 OSCC patients was 38.7 ± 0.09% compared with 69.1 ± 0.08% for the remaining patients. Multivariate analysis adjusted for age, sex, and stage showed that the 45 OSCC patient cluster had worse overall and OSCC-specific survival (hazard ratio, 3.31; 95% confidence interval, 1.66-6.58 and hazard ratio, 5.43; 95% confidence interval, 2.32-12.73, respectively). Stepwise Cox regression on the 131 probe sets revealed that a model with a term for LAMC2 (laminin γ2) gene expression best identified patients with worst OSCC-specific survival. We fit a Cox model with a term for a principal component analysis-derived risk score marker and two other models that combined stage with either LAMC2 or PCA. The area under the curve for models combining stage with either LAMC2 or PCA was 0.80 or 0.82, respectively, compared with 0.70 for stage alone (P = 0.013 and 0.008, respectively). Conclusions: Gene expression and stage combined predict survival of OSCC patients better than stage alone.

Population–based family study designs: An interdisciplinary research framework for genetic epidemiology

Most complex traits such as cancer and coronary heart diseases are attributed either to heritable factors or to environmental factors or to both. Dissecting the genetic and environmental etiology of complex traits thus requires an interdisciplinary research strategy. Genetic studies generally involve families and investigate familial aggregations of traits, segregation of major disease genes, and locations of disease genes on the human genome, the latter of which can be identified via linkage analysis. Epidemiologic studies often use population‐based case‐control studies to establish the role of specific environmental factors. Integrating both objectives, genetic epidemiology is to assess the associations of environmental factors with disease status, to quantify the aggregation of cases within families, to characterize putative disease genes via segregation analysis, and to localize disease genes via linkage analysis with genetic markers. To accomplish these objectives through designed studies, we propose a class of population‐based family study designs, which are formed by choosing among sampling designs at three stages. The objectives of sampling at these three stages are 1) combined aggregation and association analysis, 2) combined segregation, aggregation, and association analysis, and 3) combined linkage, segregation, aggregation, and association analysis. These designs form an interdisciplinary research framework for genetic epidemiology. Our preliminary exploration of this framework and related analytic methods indicates that population‐based family study designs retain the efficiency of linkage analysis for localizing disease genes without losing the property of being population‐based, and they will therefore allow an assessment of a joint contribution of genetic and environmental factors to complex traits. Genet. Epidemiol. 14:365–388,1997.

Defining genetic risk for graft-versus-host disease and mortality following allogeneic hematopoietic stem cell transplantation.

Purpose of reviewThis review explores what is known about the genetics of hematopoietic stem cell transplantation (HCT) and how genetic polymorphism affects risk of graft-versus-host disease (GVHD) and mortality. Recent findingsGenetic variation found across the human genome can impact HCT outcome by causing genetic disparity between patient and donor and modifying gene function. Single nucleotide polymorphism (SNP) and structural variation can result in mismatching for cellular peptides known as histocompatibility antigens. At least 25–30 polymorphic genes are known to encode functional histocompatibility antigens in mismatched individuals, but their individual contribution to clinical GVHD is unclear. HCT outcome may also be affected by polymorphism in donor or recipient. Association studies have implicated several genes associated with GVHD and mortality, however results have been inconsistent most likely due to limited sample size, and differences in racial diversity and clinical covariates. New technologies using DNA arrays genotyping for a million or more SNPs promise genome-wide discovery of HCT-associated genes, however adequate statistical power requires study populations of several thousand patient–donor pairs. SummaryAvailable data offers strong preliminary support for the impact that genetic variation has on risk of GVHD and mortality following HCT. Definitive results however await future genome-wide studies of large multicenter HCT cohorts.

Tumor-specific genetic expression profile of metastatic oral squamous cell carcinoma †

Metastasis is the most important predictor of survival in patients with oral squamous cell carcinoma (OSCC). We tested the hypothesis that there is a genetic expression profile associated with OSCC metastasis.

Polymorphisms in Nucleotide Excision Repair Genes and Endometrial Cancer Risk

Background: Exposure to estrogens increases the risk of endometrial cancer. Certain estrogen metabolites can form bulky DNA adducts, which are removed via nucleotide excision repair (NER), and the ability to carry out this repair might be related to endometrial cancer risk. Methods: We examined 64 tag and functional single-nucleotide polymorphisms (SNPs) in the NER genes ERCC1, ERCC2 (XPD), ERCC3 (XPB), ERCC4 (XPF), ERCC5 (XPG), LIG1, XPA, and XPC in a population-based case–control study in Washington state, with 783 endometrial cancer cases and 795 controls. Results: The presence of ERCC5 rs4150386 C, LIG1 rs3730865 C, XPA rs2808667 T, or XPC rs3731127 T alleles was associated with risk of endometrial cancer, with respective age-, county-, and reference year–adjusted per-allele ORs and 95% CIs of 0.68 (0.53–0.87, P = 0.002), 1.46 (1.02–2.10, P = 0.04), 0.71 (0.52–0.97, P = 0.03), and 1.57 (1.13–2.17, P = 0.007), respectively. Conclusions: Certain ERCC5, LIG1, XPA, and XPC genotypes might influence endometrial cancer risk. Impact: Because of multiple redundancies in DNA repair pathways (and therefore a low prior probability) and the large number of associations examined, false-positive findings are likely. Further characterization of the relation between variation in NER genes and endometrial cancer risk is warranted. Cancer Epidemiol Biomarkers Prev; 20(9); 1873–82. ©2011 AACR.

Genetic variation in CXCL12 and risk of cervical carcinoma: a population-based case-control study.

CXCL12 provides a chemotactic signal‐directing leucocyte migration and regulates metastatic behaviour of tumour cells. We conducted a population‐based case–control study to test the hypothesis that common genetic variation in CXCL12 individual single nucleotide polymorphism (SNP) alleles and haplotypes] is associated with the risk of cervical carcinoma. Cases (n = 917) were residents of western Washington State diagnosed with invasive squamous cell cervical carcinoma (SCC), invasive adenocarcinoma or adenosquamous carcinoma, or adenocarcinoma in situ of the cervix. Control participants (n = 849) were identified from the source population by random digit telephone dialling and frequency matched to cases on county and age. Nine CXCL12 tagSNPs chosen from the SeattleSNPs database were genotyped. The minor allele of intronic SNP rs266085 was inversely associated with cervical cancer under a recessive genetic effects model (OR = 0.74, 95% CI: 0.56–0.98). Among the ten common haplotypes inferred from the nine tagSNPs, one haplotype defined by minor alleles at 5′‐flanking SNP rs17885289 and rs266085, and common alleles at the other seven SNPs occurred among 7.8% of cases and 10.6% of controls (dominant model OR = 0.72, 95% CI: 0.56–0.93; recessive model OR = 0.35, 95% CI: 0.12–0.97; and log‐additive model OR = 0.72, 95% CI: 0.57–0.90). A stepwise procedure identified rs17885289, rs266085 and 3′‐untranslated region (UTR) SNP rs266093 as the most parsimonious subset of SNPs necessary to define the haplotype inversely associated with cervical cancer risk in our study. A 3′‐UTR SNP, rs1801157, previously found to be related to HIV pathogenesis, was not associated with cervical cancer risk. Further population‐based studies are warranted to confirm these associations between genetic variation in CXCL12 and cervical cancer risk.