Glutathione S-transferase GSTM1 and GSTT1 genotypes in ovarian cancer: association with p53 expression and survival

Clinical significance and biological mechanisms of glutathione S-transferase mu gene family in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is the most common form of colon cancer. The glutathione S-transferase Mu (GSTM) gene belongs to the GST gene family, which functions in cell metabolism and detoxification. The relationship between GSTM and COAD and the underlying mechanism remain unknown.

Methods

Data extracted from The Cancer Genome Atlas included mRNA expression and clinical information such as gender, age, and tumor stage. Prognostic values of GSTM genes were identified by survival analysis. Function and mechanism of prognostic GSTM genes were identified by gene set enrichment analysis. A nomogram was used to predict the contribution of risk factors to the outcome of COAD patients.

Results

Low expression of GSTM1 and GSTM2 was related to favorable OS (adjusted P = 0.006, adjusted HR = 0.559, 95% CI = 0.367–0.849 and adjusted P = 0.002, adjusted HR = 0.519, 95% CI = 0.342–0.790, respectively) after adjusting for tumor stage. Enrichment analysis also showed that genes involved were related to cell cycle, metabolism, and detoxification processes, as well as the Wnt signaling and NF-κB pathways.

Conclusions

In conclusion, low expression of GSTM1 and GSTM2 were significantly associated with favorable prognosis in COAD. These two genes may serve as potential biomarkers of COAD prognosis.

Genetic variants as ovarian cancer first-line treatment hallmarks: A systematic review and meta-analysis

BACKGROUND

The potential predictive value of genetic polymorphisms in ovarian cancer first-line treatment is inconsistently reported. We aimed to review ovarian cancer pharmacogenetic studies to update and summarize the available data and to provide directions for further research.

METHODS

A systematic review followed by a meta-analysis was conducted on cohort studies assessing the involvement of genetic polymorphisms in ovarian cancer first-line treatment response retrieved through a MEDLINE database search by November 2016. Studies were pooled and summary estimates and 95% confidence intervals (CI) were calculated using random or fixed-effects models as appropriate.

RESULTS

One hundred and forty-two studies gathering 106871 patients were included. Combined data suggested that GSTM1-null genotype patients have a lower risk of death compared to GSTM1-wt carriers, specifically in advanced stages (hazard ratio (HR), 0.68; 95% CI, 0.48-0.97) and when submitted to platinum-based chemotherapy (aHR, 0.61; 95% CI, 0.39-0.94). ERCC1 rs11615 and rs3212886 might have also a significant impact in treatment outcome (aHR, 0.67; 95% CI, 0.51-0.89; aHR, 1.28; 95% CI, 1.01-1.63, respectively). Moreover, ERCC2 rs13181 and rs1799793 showed a distinct ethnic behavior (Asians: aHR, 1.41; 95% CI, 0.80-2.49; aHR, 1.07; 95% CI, 0.62-1.86; Caucasians: aHR, 0.10; 95% CI, 0.01-0.96; aHR, 0.18; 95% CI, 0.05-0.68, respectively).

CONCLUSION(S)

The definition of integrative predictive models should encompass genetic information, especially regarding GSTM1 homozygous deletion. Justifying additional pharmacogenetic investigation are variants in ERCC1 and ERCC2, which highlight the DNA Repair ability to ovarian cancer prognosis. Further knowledge could aid to understand platinum-treatment failure and to tailor chemotherapy strategies.

Identification of multiple DNA copy number alterations including frequent 8p11.22 amplification in conjunctival squamous cell carcinoma

PURPOSE

Little is known about the molecular alterations that drive formation and growth of conjunctival squamous cell carcinoma (cSCC). We therefore sought to identify genetic changes that could be used as diagnostic markers or therapeutic targets.

METHODS

The DNA extracted from 10 snap-frozen cSCC tumor specimens and 2 in situ carcinomas was analyzed using array-based comparative genomic hybridization (aCGH), and further examined with NanoString and quantitative PCR.

RESULTS

The number of regions of DNA loss ranged from 1 to 23 per tumor, whereas gains and amplifications ranged from 1 to 15 per tumor. Most large regions of chromosomal gain and loss were confirmed by NanoString karyotype analysis. The commonest alteration was amplification of 8p11.22 in 9 tumors (75%), and quantitative PCR analysis revealed 100-fold or greater overexpression of ADAM3A mRNA from 8p11.22 locus. In addition, recurring losses were observed at 14q13.2 and 22q11.23, both lost in 5 (42%) of the 12 tumors, and at 12p13.31, lost in 4 (33%) of the 12 samples. Of the eight loci associated with the DNA damage repair syndrome xeroderma pigmentosum, three showed loss of at least one allele in our aCGH analysis, including XPA (9q22.33, one tumor), XPE/DDB2 (11p11.2, one tumor) and XPG/ERCC5 (13q33.1, three tumors).

CONCLUSIONS

Conjunctival SCC contains a range of chromosomal alterations potentially important in tumor formation and growth. Amplification of 8p11.22 and overexpression of ADAM3A suggests a potential role for this protease. Our findings also suggest that defects in DNA repair loci are important in sporadic cSCC.

Early detection biomarkers for ovarian cancer

Despite the widespread use of conventional and contemporary methods to detect ovarian cancer development, ovarian cancer remains a common and commonly fatal gynecological malignancy. The identification and validation of early detection biomarkers highly specific to ovarian cancer, which would permit development of minimally invasive screening methods for detecting early onset of the disease, are urgently needed. Current practices for early detection of ovarian cancer include transvaginal ultrasonography, biomarker analysis, or a combination of both. In this paper we review recent research on novel and robust biomarkers for early detection of ovarian cancer and provide specific details on their contributions to tumorigenesis. Promising biomarkers for early detection of ovarian cancer include KLK6/7, GSTT1, PRSS8, FOLR1, ALDH1, and miRNAs.

Translational medicine and reliability of single-nucleotide polymorphism studies: can we believe in SNP reports or not?

BACKGROUND

The number of genetic association studies is increasing exponentially. Nonetheless, genetic association reports are prone to potential biases which may influence the reported outcome.

AIM

We hypothesized that positive outcome for a determined polymorphism might be over-reported across genetic association studies analysing a small number of polymorphisms, when compared to studies analysing the same polymorphism together with a high number of other polymorphisms.

METHODS

We systematically reviewed published reports on the association of glutathione s-transferase (GST) single-nucleotide polymorphisms (SNPs) and cancer outcome.

RESULT

We identified 79 eligible trials. Most of the studies examined the GSTM1, theGSTP1 Ile105Val mutation, and GSTT1polymorphisms (n = 54, 57 and 46, respectively). Studies analysing one to three polymorphisms (n = 39) were significantly more likely to present positive outcomes, compared to studies examining more than 3 polymorphisms (n=40) p = 0.004; this was particularly evident for studies analysing the GSTM1polymorphism (p =0.001). We found no significant associations between journal impact factor, number of citations, and probability of publishing positive studies or studies with 1-3 polymorphisms examined.

CONCLUSIONS

We propose a new subtype of publication bias in genetic association studies. Positive results for genetic association studies analysing a small number of polymorphisms (n = 1-3) should be evaluated extremely cautiously, because a very large number of such studies are inconclusive and statistically under-powered. Indeed, publication of misleading reports may affect harmfully medical decision-making and use of resources, both in clinical and pharmacological development setting.

GSTT1, GSTM1, and GSTP1 polymorphisms and chemotherapy response in locally advanced breast cancer

The glutathione S-transferase (GST) family consists of phase II detoxification enzymes that catalyze the conjugation of toxic substances, such as chemotherapeutic agents, to glutathione. We examined whether GSTT1/GSTT1"null", GSTM1/GSTM1"null" and GSTP1Ile105Ile/GSTP1Ile105Val polymorphisms are associated with different response rates to neoadjuvant chemotherapy in the treatment of stage II and III breast cancer. Forty Brazilian women with invasive ductal adenocarcinoma of the breast submitted to neoadjuvant chemotherapy, using 5-fluorouracil, epirubicin and cyclophosphamide, were genotyped for the GSTT1, GSTM1 and GSTP1 genes. Clinical response was assessed by RECIST criteria. Comparisons were made for the three genes alone and in pairs, as polymorphic and as wild-type combinations and polymorphic/wild-type combinations. We analyzed all possible combinations and their response rate. Patients with the GSTT1/GSTP1105Ile combination were found to have a significantly better response than GSTT1"null"/GSTP1105Val (P = 0.0209) and GSTT1/GSTM1 (P = 0.0376) combinations. Analysis of all possible combinations showed the GSTM1"null" polymorphic genotype to be present in four, and the wild-type GSTP1105Ile in six of the combinations associated with the largest number of responding patients. We found that patients with the GSTT1/GSTP1105Ile wild-type combination had a significantly higher response rate to chemotherapy than patients with the respective polymorphic GSTT1"null"/GSTP1105Val combination or patients with the wild-type GSTT1/GSTM1. The six gene combinations associated with the largest number of responding patients were found to contain the wild-type GSTP1105Ile and the polymorphic-type GSTM1"null". These specific combinations were virtually absent in the combinations with few responding patients.

Glutathione S-transferase M1 inhibits dexamethasone-induced apoptosis in association with the suppression of Bim through dual mechanisms in a lymphoblastic leukemia cell line

Glutathione S-transferase mu (GSTM1) is mainly known as a detoxification enzyme but it has also been shown to be a negative regulator of apoptosis-related signaling cascades. Recently GSTM1 has been reported to be a significant risk factor for hematological relapse in childhood acute lymphoblastic leukemia, although the underlying mechanism remains largely unknown. Glucocorticoids play a crucial role in the treatment of childhood acute lymphoblastic leukemia, therefore we hypothesized that GSTM1 plays important roles in glucocorticoid-induced apoptotic pathways. To clarify the relationship between GSTM1 and drug resistance, GSTM1 was transfected into a T-acute lymphoblastic leukemia cell line, CCRF-CEM (CEM), and we established the GSTM1-expressing cell lines CEM/M1-4 and CEM/M1-9. Transduction of GSTM1 into CEM selectively decreased cellular sensitivity to dexamethasone in a manner that was independent of glutathione conjugation, but was due to apoptosis inhibition. Dexamethasone-induced p38-MAPK and Bim activation were concomitantly suppressed. Interestingly, nuclear factor kappa b (NF-kappaB) p50 activity was upregulated in GSTM1-expressing CEM. Inhibition of NF-kappaB by the pharmacological agent BAY11-7082 greatly enhanced the sensitivity of the GSTM1-expressing CEM to dexamethasone and was accompanied by an increase in Bim expression. Thus, we propose that GSTM1, a novel regulator of dexamethasone-induced apoptosis, causes dexamethasone resistance by suppression of Bim through dual mechanisms of both downregulation of p38-MAPK and upregulation of NF-kappaB p50.

Modest effect of p53, EGFR and HER-2/neu on prognosis in epithelial ovarian cancer: a meta-analysis

BACKGROUND

P53, EGFR and HER-2/neu are the most frequently studied molecular biological parameters in epithelial ovarian cancer, but their prognostic impact is still unequivocal. We performed a meta-analysis to more precisely estimate their prognostic significance.

METHODS

Published studies that investigated the association between p53, EGFR and HER-2/neu status and survival were identified. Meta-analysis was performed using a DerSimonian-Laird model. Publication bias was investigated using funnel plots and sources of heterogeneity were identified using meta-regression analysis.

RESULTS

A total of 62 studies were included for p53, 15 for EGFR and 20 for HER-2/neu. P53, EGFR and HER-2/neu status had a modest effect on overall survival (pooled HR 1.47, 95% CI 1.33-1.61 for p53; HR 1.65, 95% CI 1.25-2.19 for EGFR and HR 1.67, 95% CI 1.34-2.08 for HER-2/neu). Meta-regression analysis for p53 showed that FIGO stage distribution influenced study outcome. For EGFR and HER-2/neu, considerable publication bias was present.

CONCLUSIONS

Although p53, EGFR and HER-2/neu status modestly influences survival, these markers are, by themselves, unlikely to be useful as prognostic markers in clinical practice. Our study highlights the need for well-defined, prospective clinical trials and more complete reporting of results of prognostic factor studies.

Associations between p53 overexpression and multiple measures of clinical outcome in high-risk, early stage or suboptimally-resected, advanced stage epithelial ovarian cancers A Gynecologic Oncology Group study

OBJECTIVE

The Gynecologic Oncology Group (GOG) performed a detailed analysis of p53 overexpression in previously-untreated women with invasive early or advanced stage epithelial ovarian cancer (EOC).

METHODS

Women were eligible for the study if they provided a tumor block for translational research and participated in either GOG-157, a randomized phase III trial of three versus (vs.) six cycles of paclitaxel+carboplatin in high-risk, early stage EOC, or GOG-111, a randomized phase III trial of cyclophosphamide+cisplatin vs. paclitaxel+cisplatin in suboptimally-resected, advanced stage EOC. The N-terminal DO-7 p53 antibody was used to examine the expression of the major normal and mutant p53-isoforms. p53 overexpression was defined as >or=10% tumor cells exhibiting nuclear staining.

RESULTS

p53 was overexpressed in 51% (73/143) and 66% (90/136) of cases in the GOG-157 and GOG-111 cohorts, respectively. In the GOG-157 cohort, p53 overexpression was not associated with any clinical characteristics or overall survival (OS) but was associated with worse progression-free survival (PFS) (logrank test: p=0.013; unadjusted Cox modeling: p=0.015). In the GOG-111 cohort, p53 overexpression was associated with GOG performance status (p=0.018) and grade (p=0.003), but not with age, stage, cell type or with tumor response and disease status after primary chemotherapy, PFS or OS. Adjusted Cox regression modeling demonstrated that p53 overexpression was not an independent prognostic factor for PFS or OS in either cohort.

CONCLUSIONS

p53 overexpression assessed by DO-7 immunostaining is common in early and advanced stage EOC, but has limited prognostic value in women treated with surgical staging and platinum-based combination chemotherapy.

Genetic polymorphism and function of glutathione S-transferases in tumor drug resistance

The human glutathione S-transferase, GSTs, possess both enzymatic and non-enzymatic functions and are involved in many important cellular processes, such as, phase II metabolism, stress response, cell proliferation, apoptosis, oncogenesis, tumor progression and drug resistance. The non-enzymatic functions of GSTs involve their interactions with cellular proteins, such as, JNK, TRAF, ASK, PKC, and TGM2, during which, either the interacting protein partner undergoes functional alteration or the GST protein itself is post-translationally modified and/or functionally altered. The majority of GST genes harbor polymorphisms that influence their transcription and/or function of their encoded proteins. This overview focuses on recent insights into the biology and pharmacogenetics of GSTs as a determinant of cancer drug resistance and response of cancer patients to therapy.

Role of glutathione-S-transferase and codon 72 of P53 genotypes in epithelial ovarian cancer patients

PURPOSE

A series of polymorphisms in germ-line DNA have been investigated in an effort to delineate polygenic models of cancer susceptibility and prognosis. As low-penetrance susceptibility genes may combine additively or multiplicatively and contribute to cancer incidence and to the response to chemotherapy, we studied GSTT1, GSTM1, GSTO2, GSTP1 and codon 72 of p53 genotype profiles in ovarian cancer patients.

METHODS

We compared 69 ovarian cancer patients with 222 control healthy women paired for ethnic and life-style characteristics. Outcome was evaluated in 29 stage III and IV patients submitted to a platinum-based chemotherapy followed-up for 6-29 months (17 +/- 9 months).

RESULTS

GSTT1, GSTM1, GSTO2 and GSTP1 genes presented a similar genotype distribution, but codon 72 of p53 gene wild-type variant was less frequent in ovarian cancer patients than in controls (chi(2); P = 0.0004).

CONCLUSIONS

We were unable to demonstrate any association between the GST genotypes studied and the risk of ovarian cancer but the inheritance of a heterozygous Arg/Pro genotype of p53 increased the risk of ovarian cancer more than 2.5 times (OR = 2.571; 95% CI = 1.453-4.550). There was no association of the studied genes to any clinical or pathological feature of the patients or to their response to chemotherapy.

Glutathione S-transferase polymorphisms: cancer incidence and therapy

The super family of glutathione S-transferases (GSTs) is composed of multiple isozymes with significant evidence of functional polymorphic variation. Over the last three decades, data from cancer studies have linked aberrant expression of GST isozymes with the development and expression of resistance to a variety of chemicals, including cancer drugs. This review addresses how differences in the human GST isozyme expression patterns influence cancer susceptibility, prognosis and treatment. In addition to the well-characterized catalytic activity, recent evidence has shown that certain GST isozymes can regulate mitogen-activated protein kinases or can facilitate the addition of glutathione to cysteine residues in target proteins (S-glutathionylation). These multiple functionalities have contributed to the recent efforts to target GSTs with novel small molecule therapeutics. Presently, at least two drugs are in late-stage clinical testing. The evolving functions of GST and their divergent expression patterns in individuals make them an attractive target for drug discovery.

Glutathione S-transferase polymorphisms and ovarian cancer treatment and survival

OBJECTIVE

Members of the glutathione S-transferase (GST) family have been shown to have functional polymorphisms that may affect drug metabolism and influence the effects of chemotherapy and survival from cancer. GSTM1, GSTT1, and GSTP1 genotypes were evaluated for their role in ovarian cancer treatment and survival.

METHODS

DNA was extracted from tumor tissues of 215 patients diagnosed with primary epithelial ovarian cancer. GSTM1 and GSTT1 genotypes were determined by multiplex PCR; GSTP1 genotypes were assessed with PCR-RFLP. Associations between GST polymorphisms and risk of ovarian cancer progression or death were analyzed using Cox proportional hazards regression; subgroups of patients receiving different chemotherapeutics were also evaluated.

RESULTS

GST polymorphisms were not found to be associated with patient or tumor characteristics or response to treatment. However, GSTM1 null patients were less likely to have disease progression (HR: 0.65, 95% CI: 0.43-0.99) or to die (HR: 0.68, 95% CI: 0.45-1.03) compared to patients with GSTM1. Patients with GSTM1 null and GSTP1 ile/val or val/val (reduced function) had a further reduction in risk of disease progression compared to patients with GSTM1 or GSTP1 ile/ile (HR: 0.42, 95% CI: 0.24-0.75). A similar association was also suggested for overall survival (HR: 0.61, 95% CI: 0.36-1.05). Subgroup analyses indicated that the effects of GST on survival were more pronounced among patients treated with specific chemotherapeutics.

CONCLUSION

These findings support the idea that reduced GST function may improve ovarian cancer survival after post-operative chemotherapy; evaluation of GST functional polymorphisms may help to predict ovarian cancer prognosis.

The use of cytogenetics in understanding ovarian cancer

The future of cancer research is no longer limited to epidemiological data and clinical management, but rather encompasses a new dimension of understanding, that involves genetics of the tumors themselves. This has been exemplified most prominently in hematological tumors where alterations at the DNA level have been found to play key roles in the pathophysiology, diagnosis, monitoring and prognosis of these tumors. It has been shown over the last 20 years that recurrent chromosomal rearrangements are strongly associated with the activation of oncogenes, acquisition of drug resistance and loss of tumor suppressor gene function. Chromosomal alterations have also been shown to characterize many solid tumors, including epithelial ovarian cancer [Cancer Res. 62 (2002) 3466; Cancer 91 (2001) 534; Genes Chromosomes Cancer 25 (1999) 290]. Despite these findings, however, there are currently few examples of specific cytogenetic studies that have contributed to the clinical management of solid tumors such as ovarian cancer. The limiting factor to date is the resolution of available techniques. With time, as the technology improves, so will our ability to focus on specific findings that may be applicable to future clinical management. The intention of this report is to familiarize the reader with the evolution of cytogenetic and molecular cytogenetic techniques used in the study of ovarian cancer, the early formulations from these studies and their use in answering specific clinical questions such as association with pathologic subtype, the relevance of drug resistance, the impact of BRCA mutations, and finally to guide the reader into the future of this ever growing field.

Association between glutathione-S-transferase GSTP1 genotypes, GSTP1 over-expression, and outcome in epithelial ovarian cancer

Ovarian cancer accounts for the majority of deaths from gynaecological malignancy, and polymorphisms in genes encoding the glutathione-S-transferase (GST) GSTP1 detoxifying enzymes may lead to variation in detoxification of carcinogens. We describe a study involving 81 women with invasive epithelial ovarian cancer. A number of important clinical variables and outcome data were obtained. GSTP1 genotyping was undertaken using PCR-based techniques, and GSTP1 expression was quantified using immunohistochemistry (IHC). A Cox's proportional hazard regression model was used to analyze the effects on outcome. We also independently examined 11 women with borderline or low malignant potential (LMP) tumors using IHC only. The mean age of the women was 61.5 years +/- 12 (1 SD) (range 36-88 years), the median overall survival was 26 months, and median progression free interval (PFI) 21 months. There was a significant association between GSTP1 (Val(104)/Val(104)) genotypes, and reduced survival (P = 0.05) and the GTP1 (Ile(104)/Val(104)) genotype appeared to have the best outcome (HR = 0.34, P = 0.045, 95% CI = 0.12-0.98). There was no significant association between the GSTP1 genotypes and any clinico-pathological parameters; there were also no associations between GSTP1 genotypes and response to postoperative chemotherapy. Specific nuclear GSTP1 over-expression was associated with less residual disease (P = 0.05); specific cytoplasmic GSTP1 over-expression with more favourable performance status (P = 0.014)). We found that 10/11 (91%) of the LMP (borderline) tumors over-expressed nuclear GSTP1 compared to only 52% of the invasive tumors (chi(2) ((1)) = 5.95, P = 0.015). There was no significant association between the level of GSTP1 expression and response to postoperative chemotherapy. The overall level of GSTP1 expression and the subcellular localization of GSTP1 expression were not associated with either survival or PFI. There was a significant association between the GSTP1 (Ile(104)/Ile(104)) genotypes and increased overall GSTP1 expression (P = 0.049), and the GSTP1 (Ile(104)/Val(104)) genotypes and reduced overall GSTP1 expression (P = 0.046). We speculate that GSTP1 Ile(104)/Val(104) genotypes are associated with improved outcome because the protein/enzyme, which is expressed, may provide a better balance between the effects of detoxification of carcinogens and the effects of metabolism of chemotherapy agents. In addition, over-expression of nuclear GSTP1 appears to be associated with more favorable ovarian tumor characteristics. In our preliminary study, we also reported a relationship between overall GSTP1 expression and certain GSTP1 genotypes. As far as we are aware, this is the first time that a relationship between the GSTP1 genotypes, GSTP1 expression and outcome has been described in ovarian cancer. Whether the genotype directly determines GSTP1 expression is at present unclear and the precise mechanism of this interaction is unknown.

Cancer drugs, genetic variation and the glutathione-S-transferase gene family

The glutathione-S-transferase (GST) super family comprises multiple isozymes (Alpha, Mu, Pi, Omega, Theta, and Zeta) with compelling evidence of functional polymorphic variation. Over the last two decades, a significant body of data has accumulated linking aberrant expression of GST isozymes with the development and expression of resistance to cancer drugs. Clinical correlation studies show that genetic differences within the human GST isozymes may play a role in cancer susceptibility and treatment. The initial confusion was presented by the fact that not all drugs used to select for resistance were substrates for thioether bond catalysis by GSTs. However, recent evidence that certain GST isozymes possess the capacity to regulate mitogen activated protein kinases presents an alternative explanation. This dual functionality has contributed to the recent efforts to target GSTs with novel small molecule therapeutics. While the ultimate success of these attempts remains to be shown, at least one drug is in late-stage clinical testing. In addition, the concept of designing new drugs that might interfere with protein:protein interactions between GSTs and regulatory kinases provides a novel approach to identify new targets in the search for cancer therapeutics.

Glutathione S-transferase polymorphisms and risk of ovarian cancer: a HuGE review

Glutathione S-transferases (GSTs) catalyze the conjugation of glutathione to numerous potentially genotoxic compounds. The GSTM1 gene codes for the enzyme glutathione S-transferase-mu, the GSTT1 gene codes for the enzyme glutathione S-transferase-theta, and the GSTP1 gene codes for the enzyme glutathione S-transferase-pi. GSTM1 is polymorphically expressed, and three alleles have been identified (GSTM1-0, GSTM1a, and GSTM1b). Two functionally different genotypes at the GSTT1 locus have been described. Individuals with homozygous deletions of GSTM or GSTT have reduced or no glutathione S-transferase activity and therefore may be unable to eliminate electrophilic carcinogens as efficiently. However, results of epidemiologic studies do not confirm associations between GSTM1, GSTT1, and GSTP1 and epithelial ovarian cancer.

Molecular characteristics of non-small cell lung cancer

We used hierarchical clustering to examine gene expression profiles generated by serial analysis of gene expression (SAGE) in a total of nine normal lung epithelial cells and non-small cell lung cancers. Separation of normal and tumor, as well as histopathological subtypes, was evident by using the 3,921 most abundant transcript tags. This distinction remained when only 115 highly differentially expressed tags were used. Furthermore, these 115 transcript tags clustered into groups suggestive of the unique biological and pathological features of the different tissues examined. Adenocarcinomas were characterized by high-level expression of small airway-associated or immunologically related proteins, whereas squamous cell carcinomas overexpressed genes involved in cellular detoxification or antioxidation. The messages of two p53-regulated genes, p21(WAF1/CIP1) and 14-3-3final sigma, were consistently underexpressed in the adenocarcinomas, suggesting that the p53 pathway itself might be compromised in this cancer type. Gene expression patterns observed by SAGE were consistent with results obtained by quantitative real-time PCR or cDNA array analyses by using a total of 43 lung tumor and normal samples. Thus, although derived from only a few tissue libraries, gene expression profiles obtained by using SAGE most likely represent an unbiased yet distinctive molecular signature for the most common forms of human lung cancer.