Improving gene set analysis of microarray data by SAM-GS

Dinu, Irina; Potter, John D.; Mueller, Thomas; Liu, Qi; Adewale, Adeniyi J.; Jhangri, Gian S.; Einecke, G.; Famulski, Konrad S.; Halloran, Philip F.; Yasui, Yutaka

doi:10.1186/1471-2105-8-242

Cited by 230 publications

(242 citation statements)

References 24 publications

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“…A weighted-voting procedure with leave-one-out cross validation was used to identify the optimal gene subset (n = 11) for classifying samples by parity group (GenePattern; ref. 20) and significance analysis of microarray-gene set (SAM-GS) analysis was used for gene set hypothesis testing (21).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, 5 of 28 inflammation-related genes chosen for analysis, or 18%, were differentially regulated between the nulliparous and parous groups. We applied SAM-GS analysis (21) to test the hypothesis that parity status was associated with expression of 28 genes in the inflammation gene set as a group. This analysis, which is similar to a summary t-test approach, yielded a P value of 0.03, indicating that the process of inflammation is differentially regulated between the nulliparous and parous groups.…”

Section: Validation Studiesmentioning

confidence: 99%

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Gene Expression Patterns in the Human Breast after Pregnancy

Asztalos

Gann

Hayes

et al. 2010

Cancer Prevention Research

118

117

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Epidemiologic studies have established that pregnancy has a bidirectional, time-dependent effect on breast cancer risk; a period of elevated risk is followed by a long-term period of protection. The purpose of the present study was to determine whether pregnancy and involution are associated with gene expression changes in the normal breast, and whether such changes are transient or persistent. We examined the expression of a customized gene set in normal breast tissue from nulliparous, recently pregnant (0-2 years since pregnancy), and distantly pregnant (5-10 years since pregnancy) age-matched premenopausal women. This gene set included breast cancer biomarkers and genes related to immune/inflammation, extracellular matrix remodeling, angiogenesis, and hormone signaling. Laser capture microdissection and RNA extraction were done from formalin-fixed paraffin-embedded reduction mammoplasty and benign biopsy specimens and analyzed using real-time PCR arrays containing 59 pathway-specific and 5 housekeeping genes. We report 14 of 64 (22%) of the selected gene set to be differentially regulated (at P < 0.05 level) in nulliparous versus parous breast tissues. Based on gene set analysis, inflammationassociated genes were significantly upregulated as a group in both parous groups compared with nulliparous women (P = 0.03). Moreover, parous subjects had significantly reduced expression of estrogen receptor α (ERα, ESR1), progesterone receptor (PGR), and ERBB2 (Her2/neu) and 2-fold higher estrogen receptor-β (ESR2) expression compared with nulliparous subjects. These initial data, among the first on gene expression in samples of normal human breast, provide intriguing clues about the mechanisms behind the time-dependent effects of pregnancy on breast cancer risk. Cancer Prev Res; 3(3); 301-11. ©2010 AACR.

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Section: Discussionmentioning

confidence: 99%

Section: Validation Studiesmentioning

confidence: 99%

Gene Expression Patterns in the Human Breast after Pregnancy

Asztalos

Gann

Hayes

et al. 2010

Cancer Prevention Research

118

117

View full text Add to dashboard Cite

show abstract

“…8 Four methods were used to compare gene sets and sample groups: GSA 20 : R package GSA; globaltest 21 : R package globaltest; SAM-GS 22 : original R code; and the Tuckey algorithm described in Table 4 of Ref. 23: original R code).…”

Section: Affymetrix Genechip Data Mining-identification Of Biologicalmentioning

confidence: 99%

CD8‐alpha T‐cell infiltration in human papillomavirus‐related oropharyngeal carcinoma correlates with improved patient prognosis

Jung

Guihard²,

Krugell³

et al. 2012

Intl Journal of Cancer

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Patients with human papillomavirus (HPV)-related oropharyngeal tumors display improved prognosis. The biological basis of this tumor phenotype is poorly understood. We investigated whether increased lymphocyte infiltrate in HPV-positive oropharyngeal squamous cell carcinomas could account for better prognosis. We previously identified, in an Affymetrix GeneChip analysis of 83 HPV-unrelated and 11 HPV-related squamous cell carcinoma of the oropharynx, several candidate genes, including CD8a and CD3f. Their expression was validated in this study by qRT-PCR on an independent clinical series of 144 oropharyngeal tumors. Immunohistochemical staining of tumor specimens was performed to evaluate infiltration of tumor stroma by CD81 and CD41 lymphocytes. The prognostic value of CD8a and CD3f expression levels was measured by Kaplan-Meier and Cox regression model analyses. Immune response-related signaling pathways were found to be deregulated in HPV-positive oropharyngeal tumors. Expression of CD8a, CD3f, granzyme K, CD28 and integrin aL RNAs was upregulated in HPV-positive lesions when compared with HPV-unrelated tumors (p < 0.05). Stroma of HPV-positive tumors was frequently and strongly infiltrated by CD8a-and CD3f-positive T cells. CD8a RNA expression correlated with both improved global (Kaplan-Meier; p 5 0.005; Cox regression: p 5 0.003) and disease-free (Cox regression: p 5 0.04) survival. CD3f RNA expression correlated with improved overall survival (Cox regression: p 5 0.024). These results suggest that an increased cytotoxic T-cell-based antitumor immune response is involved in improved prognosis of patients with HPV-positive tumors.The presence of human papillomaviruses (HPVs; mainly HPV type 16) correlates with the onset and development of about 25% of head and neck squamous cell carcinomas (HNSCC). 1 HPV-positive cancers of the head and neck arise mainly in the oropharynx and define a subgroup of radioand chemosensitive tumors with distinct clinical, pathological and molecular features and improved prognosis with respect to their HPV-negative counterparts. [2][3][4][5] The majority of HPVrelated oropharyngeal squamous cell carcinomas (OSCC) express wild-type TP53, 6,7 which might be involved in the improved response of tumors to treatment. Despite thorough analysis of gene expression profiles of HPV-positive OSCC by several groups, [8][9][10][11] no novel prognostic or predictive biomarker has been identified, and the molecular mechanisms that underlie improved prognosis of HPV-related OSCC are poorly understood.The immune response has an important impact in many HPV-associated tumors and can have either favorable or unfavorable consequences. 12 The importance of the immune response in HPV-related OSCC is less well established. An increased T-cell response against HPV E7 epitopes has been detected in the blood of patients with HPV-positive HNSCC. 13-15 A more recent study has shown that T cells that proliferate and synthesize inflammatory cytokines upon HPV16 E6 and E7 oncoprotein recognition can be isolate...

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“…6 The IGA method requires an initial calculation of differentially expressed genes that is influenced by the statistical methods and their thresholds. Since the emergence of gene set enrichment analysis (GSEA), an increasing number of GSA approaches based on various statistical methods have been rapidly developed, such as GSEA, 7,8 globaltest, 9 SAM-GS, 10 GlobalANCOVA, 11 ADGO 12,13 and Bayesian network-based pathway analysis. 14 Tian et al 15 classified two types of null hypotheses that test whether a gene set displays a coordinated association with a phenotype of interest.…”

Section: Introductionmentioning

confidence: 99%

DBGSA: a novel method of distance-based gene set analysis

Wang

et al. 2012

J Hum Genet

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When compared with single gene functional analysis, gene set analysis (GSA) can extract more information from gene expression profiles. Currently, several gene set methods have been proposed, but most of the methods cannot detect gene sets with a large number of minor-effect genes. Here, we propose a novel distance-based gene set analysis method. The distance between two groups of genes with different phenotypes based on gene expression should be larger if a certain gene set is significantly associated with the given phenotype. We calculated the distance between two groups with different phenotypes, estimated the significant P-values using two permutation methods and performed multiple hypothesis testing adjustments. This method was performed on one simulated data set and three real data sets. After a comparison and literature verification, we determined that the gene resampling-based permutation method is more suitable for GSA, and the centroid statistical and average linkage statistical distance methods are efficient, especially in detecting gene sets containing more minor-effect genes. We believe that this distance-based method will assist us in finding functional gene sets that are significantly related to a complex trait. Additionally, we have prepared a simple and publically available Perl and R package

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Improving gene set analysis of microarray data by SAM-GS

Cited by 230 publications

References 24 publications

Gene Expression Patterns in the Human Breast after Pregnancy

Gene Expression Patterns in the Human Breast after Pregnancy

CD8‐alpha T‐cell infiltration in human papillomavirus‐related oropharyngeal carcinoma correlates with improved patient prognosis

DBGSA: a novel method of distance-based gene set analysis

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