Gene expression patterns as marker for 5-year postoperative prognosis of primary breast cancers

N6-methyladenosine-regulated ADIRF impairs lung adenocarcinoma metastasis and serves as a potential prognostic biomarker

Aberrant expression of adipogenic regulatory factors (ADIRF) in tumor cells is critical for tumor growth and metastasis. N6-methyladenosine (m6A) modifications have an important role in a variety of biological activities. Our study aimed to investigate the role of ADIRF in adenocarcinoma and to elucidate the regulatory role of m6A signaling on ADIRF. Differential expression of genes in tumor and normal tissues was analyzed using the LUAD dataset (GSE1987). The Kaplan-Meier method and receiver operating characteristic (ROC) curve analysis were performed to evaluate the prognostic and diagnostic value of ADIRF in LUAD. Loss-of-function or gain-of-function experiments were performed to study the effect of ADIRF on LUAD growth in vitro. The molecular mechanism of action of ADIRF in LUAD was confirmed using a dual-luciferase reporter system and MeRIP-qPCR. We identified a loss of ADIRF expression in LUAD tissues and cells. Furthermore, the restoration of ADIRF levels attenuated LUAD cell growth and metastasis in vitro. Mechanistically, an m6A "eraser," α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5), eliminated the ADIRF m6A modification motif and further blocked the binding of the YTH domain-containing 2 (YTHDC2)-binding protein to ADIRF. At the molecular level, ALKBH5 enrichment increased ADIRF mRNA levels and prevented the attenuation of ADIRF mRNA by YTHDC2. The effects of ALKBH5 overexpression could also extend to the inhibition of LUAD cell proliferation and metastasis. This study linked ADIRF with the m6A modifying regulators ALKBH5 and YTHDC2, providing a promising molecular intervention for LUAD and deepening the understanding of LUAD mechanisms.

Adipose most abundant 2 protein is a predictive marker for cisplatin sensitivity in cancers

Cisplatin (CDDP) is one of the chemotherapeutic drugs being used to treat various cancers. Although effective in many cases, as high doses of CDDP cause cytotoxic effects that may worsen patients' condition, therefore, a marker of sensitivity to CDDP is necessary to enhance the safety and efficiency of CDDP administration. This study focused on adipose most abundant 2 (APM2) to examine its potential as a marker of CDDP sensitivity. The relationship of APM2 expression with the mechanisms of CDDP resistance was examined in vitro and in vivo using hepatocellular carcinoma (HCC) cells, tissues and serum of HCC patients (n = 71) treated initially with intrahepatic arterial infusion of CDDP followed by surgical resection. The predictability of serum APM2 for CDDP sensitivity was assessed in additional 54 HCC patients and 14 gastric cancer (GC) patients. APM2 expression in CDDP-resistant HCC was significantly higher both in serum and the tissue. Bioinformatic analyses and histological analyses demonstrated upregulation of ERCC6L (DNA excision repair protein ERCC6-like) by APM2, which accounts for the degree of APM2 expression. The serum APM2 level and chemosensitivity for CDDP were assessed and cut-off value of serum APM2 for predicting the sensitivity to CDDP was determined to be 18.7 µg/mL. The value was assessed in HCC (n = 54) and GC (n = 14) patients for its predictability of CDDP sensitivity, resulted in predictive value of 77.3% and 100%, respectively. Our study demonstrated that APM2 expression is related to CDDP sensitivity and serum APM2 can be an effective biomarker of HCC and GC for determining the sensitivity to CDDP.Trial registration: This study was registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN000028487).

OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma

Esophageal Adenocarcinoma (EAC) is one of the most common gastrointestinal tumors in the world. However, molecular prognostic systems are still lacking for EAC. Hence, we developed an Online consensus Survival analysis web server for Esophageal Adenocarcinoma (OSeac), to centralize published gene expression data and clinical follow up data of EAC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSeac includes 198 EAC cases with gene expression profiling and relevant clinical long-term follow-up data, and employs the Kaplan Meier (KM) survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for EAC patients. Moreover, we have determined the reliability of OSeac by using previously reported prognostic biomarkers such as DKK3, CTO1, and TXNIP. OSeac is free and publicly accessible at http://bioinfo.henu.edu.cn/EAC/EACList.jsp.

Identification of cellular genes showing differential expression associated with hepatitis B virus infection

AIM

To investigate the impact of hepatitis B virus (HBV) infection on cellular gene expression, by conducting both in vitro and in vivo studies.

METHODS

Knockdown of HBV was targeted by stable expression of short hairpin RNA (shRNA) in huH-1 cells. Cellular gene expression was compared using a human 30K cDNA microarray in the cells and quantified by real-time reverse transcription-polymerase chain reaction (RT-PCR) (qRT-PCR) in the cells, hepatocellular carcinoma (HCC) and surrounding non-cancerous liver tissues (SL).

RESULTS

The expressions of HBsAg and HBx protein were markedly suppressed in the cells and in HBx transgenic mouse liver, respectively, after introduction of shRNA. Of the 30K genes studied, 135 and 103 genes were identified as being down- and up-regulated, respectively, by at least twofold in the knockdown cells. Functional annotation revealed that 85 and 62 genes were classified into four up-regulated and five down-regulated functional categories, respectively. When gene expression levels were compared between HCC and SL, eight candidate genes that were confirmed to be up- or down-regulated in the knockdown cells by both microarray and qRT-PCR analyses were not expressed as expected from HBV reduction in HCC, but had similar expression patterns in HBV- and hepatitis C virus-associated cases. In contrast, among the eight genes, only APM2 was constantly repressed in HBV non-associated tissues irrespective of HCC or SL.

CONCLUSION

The signature of cellular gene expression should provide new information regarding the pathophysiological mechanisms of persistent hepatitis and hepatocarcinogenesis that are associated with HBV infection.

APM2 is a novel mediator of cisplatin resistance in a variety of cancer cell types regardless of p53 or MMR status

Cisplatin is one of the most widely used chemotherapeutics in the world today. Unfortunately, chemoresistance often develops hindering the effectiveness of the drug. Mismatch-repair (MMR) and p53 have previously been shown to be important determinants of cisplatin resistance and can contribute to cisplatin resistance clinically. Here, we have used cDNA microarray to identify several genes as up or downregulated in a previously described, cisplatin resistant, clone of the HCT116 cell line (HCT116-K). On follow-up, one gene, APM2, was found to promote cisplatin resistance when overexpressed in sensitive HCT116 clones. Furthermore, silencing APM2 in a panel of cell lines encompassing all combinations of p53 status and MMR proficiency (HCT116-K, HCT116, SW620, MCF7, PC-3 and OV2008) resulted in sensitization regardless of these 2 factors. In addition, silencing APM2 stably using shRNA also resulted in the sensitization of cells to cisplatin. More importantly, cisplatin inhibited the growth of APM2 silenced tumor xenografts (HCT116-K or OV2008 cells) significantly better than it inhibited the growth of xenografts carrying nontargeting control shRNAs. These findings represent a novel strategy that could be exploited to overcome cisplatin resistance in patients regardless of p53 status or ability to perform MMR.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

Background

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated.

Methods

46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material.

Results

A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively).

Conclusion

The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved.

Trial registration

The research on these tumours was approved by the Medical Faculty Research Ethics Committee (Medicinska fakultetens forskningsetikkommitté, Göteborg, Sweden (S164-02)).

Consensus genes of the literature to predict breast cancer recurrence

BACKGROUND

Extensive efforts have been undertaken to discover genes relevant for breast cancer prognosis. Yet, in current opinion, with little overlap in findings. We aimed to reanalyze molecular prediction of breast cancer recurrence.

METHODS

From 44 published gene lists relevant for breast cancer prognosis, we extracted 374 genes, which, besides other quality criteria, are recorded at least twice. From eight published microarray datasets, a single dataset of 1,067 breast cancer patients was created, using transformation to 'probability of expression' scale. For recurrence analysis, the Cox proportional hazards model was applied.

RESULTS

The 374 genes, termed '374 Gene Set', are highly enriched in cell cycle genes. The '374 Gene Set' is significantly associated with breast cancer recurrence (p = 2 x 10(-12), log-rank test) in the meta set of 1,067 patients, showing an estimated Hazard Ratio of recurrence for the 'poor' prognosis group compared to the 'good' prognosis group of 2.03 (95% confidence interval, 1.66-2.48). Notably, the '374 Gene Set' is significantly associated with recurrence in untreated patients. In multivariate analysis, including the standard histopathological parameters, only tumor size and the '374 Gene Set' remain independent predictors of recurrence. External validation further confirmed the prognostic relevance of the gene set (253 patients, p = 0.001, log-rank test).

CONCLUSIONS

The '374 Gene Set' comprises a molecular basis of metastatic breast cancer progression. Starting from this gene set it might be possible to construct a clinically relevant classifier, which then again needs to be validated.

Dissimilarity in gene expression profiles of lung adenocarcinoma in Japanese men and women

BACKGROUND

Although clinical differences in lung cancer between men and women have been noted, few studies have examined the sex dissimilarity using gene expression analysis.

OBJECTIVE

The purpose of this study was to determine the different molecular carcinogenic mechanisms involved in lung cancers in Japanese men and women.

METHODS

Patients who received surgery for stage I lung adenocarcinoma were included. RNA was extracted from cancerous and normal tissue, and gene expression was then examined with oligonucleotide microarray analysis. A quantitative polymerase chain reaction assay was performed.

RESULTS

In a microarray analysis of tissue from 13 men and 6 women, 12 genes were under-expressed and 24 genes were overexpressed in lung adenocarcinoma in women compared with men. Genes related to cell cycle were present in underexpressed genes, and genes related to apoptosis, ubiquitination, and metabolism were observed in overexpressed genes. Of interest among the selected genes were WAP four-disulfide core domain 2 (WFDC2) and major histocompatibility complex, class II, DM alpha (HLA-DMA); these genes were classified into 2 groups by hierarchical clustering analysis. Expression of WFDC2 in nonsmokers was significantly higher than that in smokers (P=0.023). However, there was no significant difference in HLA-DMA expression between smokers and nonsmokers.

CONCLUSION

Thirty-six genes that characterize lung adenocarcinoma by sex were selected. This information may contribute to the development of novel diagnostic techniques and treatment modalities that consider sex differences in lung adenocarcinoma.

Genetic Prognostic Index Influences Patient Outcome for Node-Positive Breast Cancer

PURPOSE

To establish a novel genetic prognostic index among node-positive breast cancer patients.

METHODS

Using a cDNA microarray, the gene expression profiles of 20 primary breast cancers that had metastasis to four or more axillary lymph nodes were examined. Ten patients survived disease-free for more than 5 years (5S), while ten patients died of breast cancer within 5 years of surgery (5D).

RESULTS

A set of genes characterizing each group was identified. Sixteen genes were underexpressed in 5D compared to 5S, and 15 genes were underexpressed in 5S in comparison to 5D. The prognostic index (PI) was established, which could predict the postoperative outcome with five genes that were commonly underexpressed in the 5D group; these genes encoded granulin (GRN), heat shock 90 kDa protein 1 beta (HSPCB), large tumor suppressor homolog 1 (LATS1), valosin-containing protein (VCP), and LIM-and-SH3 protein1 (LASP1).

CONCLUSION

These five genes might play an important role in deciding the behavior of node-positive breast cancer. The PI system could thus predict the prognosis of node-positive breast cancer, and might therefore be able to provide valuable information for the prognosis of breast cancer patients.

A clinical prognostic prediction of lymph node-negative breast cancer by gene expression profiles

PURPOSE

To set up a method by use of gene expression data to predict the prognosis of breast cancer patients on the basis of genes as few as possible, but maintaining the accuracy of prediction, we reanalyze the data from van't Veer et al. (Nature 415:530-536, 2002) and van de Vijver et al. (N Engl J Med 347:1999-2009, 2002).

METHODS

A three-step method based on re-sampling strategy is employed to select the prognostic genes. And based on these genes, a predictive approach is established. Validation sets are used to testify the predictive power of the prognostic genes.

RESULTS

We have discovered 13 genes as the most informative ones to predict the clinical outcomes of breast cancer patients with lymph node-negative. The validation results show the robust performances of these genes. And the results of further analysis illustrate the significant association of the prediction to the time of metastases and overall survival.

CONCLUSION

Our predictive approach is useful in prognosis prediction for breast cancer patients with lymph node-negative. The gene markers provide valuable information for the progression of breast cancer and suggest potential target genes for treating the cancer.

Genomics in breast cancer—therapeutic implications

The introduction of DNA microarray techniques has had dramatic implications on cancer research, allowing researchers to analyze expression of multiple genes in concert and relate the findings to clinical parameters. The main discoveries in breast cancer, as well as in other malignancies, have so far been with respect to two key issues. First, individual tumors arising from the same organ may be grouped into distinct classes based on their gene expression profiles, independent of stage and grade. Second, the biologic relevance of such classification is corroborated by significant prognostic impact. We review how the use of microarray technologies can provide unique possibilities to explore the mechanisms of tumor behavior in vivo that will allow evaluation of prognosis and, potentially, drug resistance. However, in spite of recent advances, we are not yet at a stage where the use of these techniques should be implemented for routine clinical use, whether to define prognostic factors or to predict sensitivity to therapy.