Tumor-biological factors uPA and PAI-1 as stratification criteria of a multicenter adjuvant chemotherapy trial in node-negative breast cancer

In axillary node-negative primary breast cancer, 70% of the patients will be cured by locoregional treatment alone. Therefore, adjuvant systemic therapy is only needed for those 30% of node-negative patients who will relapse after primary therapy and eventually die of metastases. Traditional histomorphological and clinical factors do not provide sufficient information to allow accurate risk group assessment in order to identify node-negative patients who might benefit from adjuvant systemic therapy. In the last decade various groups have reported a strong and statistically independent prognostic impact of the serine protease uPA (urokinase-type plasminogen activator) and its inhibitor PAI-1 (plasminogen activator inhibitor type 1) in node-negative breast cancer patients. Based on these data, a prospective multicenter therapy trial in node-negative breast cancer patients was started in Germany in June 1993, supported by the German Research Association (DFG). Axillary node-negative breast cancer patients with high levels of either or both proteolytic factors in the tumor tissue were randomized to adjuvant CMF chemotherapy versus observation only. Recruitment was continued until the end of 1998, by which time 684 patients had been enrolled. Since then, patients have been followed up in order to assess the value of uPA and PAI-1 determination as an adequate selection criterion for adjuvant chemotherapy in node-negative breast cancer patients. This paper reports on the rationale and design of this prospective multicenter clinical trial, which may have an impact on future policies in prognosis-oriented treatment strategies.     

The favorable prognostic significance of surgery-induced hyperprolactinemia in node-positive breast cancer patients: ten-year disease-free survival results

It has been shown that each manipulation of the mammary region, including breast surgery, may stimulate prolactin secretion. However, it has also been observed that in more than 50% of breast cancer patients surgical removal of the tumor is not followed by enhanced prolactin secretion. This might be indicative of an altered psychoneuroendocrine control of the mammary gland, which could lead to the onset of more biologically aggressive breast cancer. In fact, surgery-induced hyperprolactinemia has been proven to be associated with a better prognosis in terms of survival in node-negative breast cancer patients. The present study was performed to investigate the impact of postoperative hyperprolactinemia on the disease-free survival (DFS) of breast cancer patients with axillary node involvement. The study included 100 consecutive node-positive breast cancer patients who were followed for at least 10 years. Surgery-induced hyperprolactinemia occurred in 45/100 (45%) patients without any significant correlation with the main prognostic variables including number of involved nodes and ER status. The two groups of patients received the same adjuvant therapies. After a median follow-up of 151 months, the recurrence rate in patients with surgery-induced hyperprolactinemia was significantly lower than in patients with no postoperative hyperprolactinemia (23/45 vs 43/55, p<0.01). Moreover, DFS was significantly longer in hyperprolactinemic patients than in patients who had no enhanced secretion of prolactin postoperatively. In agreement with the results described previously in node-negative breast cancer, our study demonstrates the favorable prognostic significance of surgery-induced hyperprolactinemia in terms of DFS duration also in breast cancer patients with axillary node involvement, independent of the other well-known prognostic variables, thereby confirming that the psychoneuroendocrine status of cancer patients may influence the prognosis of their disease.     

Plasma and serum levels of tissue inhibitor of metalloproteinases-1 are associated with prognosis in node-negative breast cancer: a prospective study

The tumor level of TIMP-1 has been suggested as a new prognostic marker in breast cancer. The purpose of this study was to investigate whether TIMP-1 also carries prognostic information when measured in blood as this is a much more preferable material compared with tumor extracts. Using ELISA, TIMP-1 was measured in prospectively collected preoperative plasma and serum samples from 519 patients with primary breast cancer, and the measurements were related to patient outcome. The median age of the patients was 58 years (range, 38-80 years), and the median follow-up time was 1043 days (range, 300-1630 days). Plasma and serum TIMP-1 measurements correlated significantly with each other with a Pearson correlation coefficient of 0.75 (p < 0.0001). For univariate survival analysis, patients were divided into quartiles according to increasing TIMP-1 levels (Q1-Q4). Analysis of all patients showed that high TIMP-1 plasma levels were significantly associated with a shorter disease-free survival. Subgroup analysis showed that plasma TIMP-1 significantly predicted the prognosis of node-negative patients but not of node-positive patients. Importantly plasma TIMP-1 was able to further stratify low risk node-negative patients. High serum TIMP-1 levels were associated with a shorter disease-free survival; however, the association was not statistically significant. In contrast, serum TIMP-1 significantly predicted the prognosis of node-negative and low risk patients. In multivariate survival analysis of node-negative patients including all the classical prognostic parameters, plasma TIMP-1 remained significantly associated with prognosis when comparing Q1 with Q2 and Q4. Serum TIMP-1 remained significant when comparing Q1 with Q4. Taken together, this study is to our knowledge the first large prospective study suggesting that TIMP-1 carries independent prognostic information when measured in blood, especially plasma. This was especially true in the node-negative group of patients and in patients already defined as low risk patients using the currently available prognostic parameters.     

Prognostic value of tumoral sialyltransferase expression and circulating E-selectin concentrations in node-negative breast cancer patients

AIMS AND BACKGROUND: A crucial step in the metastatic process is the interaction between the endothelial molecule E-selectin and its tumoral ligands sialyl-Lewis- and sialyl-Lewis. Sialyltranferases are involved in the biosynthesis of these ligands. The aim of this study was to assess the prognostic value of tumoral sialyltransferase expression and of circulating soluble E-selectin (sE-selectin) in node-negative breast cancer patients. METHODS: Using a multiplex RT-PCR method, we measured the expression of five sialyltransferases (ST3Gal III, ST6Gal I, ST3Gal IV, ST3Gal I and ST3Gal II) in tumors of 135 surgically treated node-negative breast cancer patients. Circulating sE-selectin concentrations were measured by an ELISA method prior to surgery. We also analyzed tumor size, histoprognostic grading and steroid hormone receptor status. RESULTS: The median follow-up was 7.5 years. Expression of estrogen receptors was associated with a good prognosis for relapse-free survival in univariate analysis. A high ST3Gal III/ST6Gal I ratio and a high sE-selectin concentration were associated with a bad prognosis for relapse-free survival and overall survival in univariate and multivariate analysis. CONCLUSION: In the present study, tumoral sialyltransferase expression and circulating sE-selectin concentrations had prognostic value in patients with node-negative breast cancer. This result provides further evidence for the important role of these agents in the metastatic process.     

Correlations of Differentially Expressed Gap Junction Connexins Cx26, Cx30, Cx32, Cx43 and Cx46 with Breast Cancer Progression and Prognosis

Background and Aims

Connexins and their cell membrane channels contribute to the control of cell proliferation and compartmental functions in breast glands and their deregulation is linked to breast carcinogenesis. Our aim was to correlate connexin expression with tumor progression and prognosis in primary breast cancers.

Materials and Methods

Meta-analysis of connexin isotype expression data of 1809 and 1899 breast cancers from the Affymetrix and Illumina array platforms, respectively, was performed. Expressed connexins were also monitored at the protein level in tissue microarrays of 127 patients equally representing all tumor grades, using immunofluorescence and multilayer, multichannel digital microscopy. Prognostic correlations were plotted in Kaplan-Meier curves and tested using the log-rank test and cox-regression analysis in univariate and multivariate models.

Results

The expression of GJA1/Cx43, GJA3/Cx46 and GJB2/Cx26 and, for the first time, GJA6/Cx30 and GJB1/Cx32 was revealed both in normal human mammary glands and breast carcinomas. Within their subfamilies these connexins can form homo- and heterocellular epithelial channels. In cancer, the array datasets cross-validated each other’s prognostic results. In line with the significant correlations found at mRNA level, elevated Cx43 protein levels were linked with significantly improved breast cancer outcome, offering Cx43 protein detection as an independent prognostic marker stronger than vascular invasion or necrosis. As a contrary, elevated Cx30 mRNA and protein levels were associated with a reduced disease outcome offering Cx30 protein detection as an independent prognostic marker outperforming mitotic index and necrosis. Elevated versus low Cx43 protein levels allowed the stratification of grade 2 tumors into good and poor relapse free survival subgroups, respectively. Also, elevated versus low Cx30 levels stratified grade 3 patients into poor and good overall survival subgroups, respectively.

Conclusion

Differential expression of Cx43 and Cx30 may serve as potential positive and negative prognostic markers, respectively, for a clinically relevant stratification of breast cancers.     

Long-term follow-up confirms prognostic impact of PAI-1 and cathepsin D and L in primary breast cancer

After long-term follow-up, the prognostic impact of the following proteolytic factors associated with tumor invasion and metastasis was evaluated in 276 primary breast cancer patients: uPA (urokinase-type plasminogen activator), PAI-1 (uPA inhibitor type 1), and cathepsins B, D and L. The median follow-up of patients still alive at the time of analysis was 109 months. To date 119 patients (43%) have relapsed and 117 (42%) have died. Antigen levels of uPA and PAI-1 were determined by ELISA in detergent extracts; cathepsin B, D, and L content was determined in cytosol fractions of the primary tumor: cathepsin D by ELSA and cathepsin B and L by ELISA. In multivariate analysis (Cox model) for disease-free survival (DFS), lymph node status (p < 0.001; RR = 3.8), cathepsin L (p < 0.001; RR = 2.6) and PAI-1 (p = 0.027; RR = 1.7) were significant factors in all patients. In addition to these factors, grading was significant for overall survival (OS). In another multivariate approach, CART (Classification And Regression Trees) analysis, lymph node status (p < 0.001) turned out to be the strongest discriminator for patients at high risk of relapse. In the node-negative patient subset, PAI-1 was the strongest risk group discriminator (p < 0.001): in this subset, patients with low levels of both PAI-1 and cathepsin D had a very low relapse rate of only 3.2% compared to 39% in the remaining node-negative patients. In node-positive patients cathepsin L gave the best risk group assessment (p = 0.001). In conclusion, tumor-associated PAI-1 and cathepsins D and L provide significant, statistically independent prognostic information for DFS and OS in primary breast cancer, even after a median follow-up period of almost 10 years.     

Coupling proteomics and transcriptomics in the quest of subtype‐specific proteins in breast cancer

Breast‐cancer subtypes present with distinct clinical characteristics. Therefore, characterization of subtype‐specific proteins may augment the development of targeted therapies and prognostic biomarkers. To address this issue, MS‐based secretome analysis of eight breast cancer cell lines, corresponding to the three main breast cancer subtypes was performed. More than 5200 non‐redundant proteins were identified with 23, four, and four proteins identified uniquely in basal, HER2‐neu‐amplified, and luminal breast cancer cells, respectively. An in silico mRNA analysis using publicly available breast cancer tissue microarray data was carried out as a preliminary verification step. In particular, the expression profiles of 15 out of 28 proteins included in the microarray (from a total of 31 in our subtype‐specific signature) showed significant correlation with estrogen receptor (ER) expression. A MS‐based analysis of breast cancer tissues was undertaken to verify the results at the proteome level. Eighteen out of 31 proteins were quantified in the proteomes of ER‐positive and ER‐negative breast cancer tissues. Survival analysis using microarray data was performed to examine the prognostic potential of these selected candidates. Three proteins correlated with ER status at both mRNA and protein levels: ABAT, PDZK1, and PTX3, with the former showing significant prognostic potential.     

Prognostic factors in human primary breast cancer: comparison of c-myc and HER2/neu amplification.

Amplification of oncogenes in primary tumours may have prognostic and/or therapeutic significance for patients with breast cancer. We have studied HER2/neu and c-myc amplification together with steroid receptors in human primary breast tumours and related the outcome with (relapse-free) survival. A strong inverse correlation was found between HER2/neu amplification and the presence of oestrogen and progesterone receptors. Actuarial 5-years survival showed that breast cancer patients with c-myc amplification in their primary tumours experience a shorter relapse-free survival, especially in node-negative and in receptor-positive tumours, whereas HER2/neu amplification may be of prognostic value for overall survival in receptor-negative tumours. Overall, in our hands, c-myc amplification appeared to be a more potent prognosticator than HER2/neu amplification in human primary breast cancer.     

Urokinase-type plasminogen activator: a potent marker of metastatic potential in human cancers

Urokinase-type plasminogen activator (uPA) is a serine protease that is causally involved in cancer progression, especially invasion and metastasis. Multiple studies have shown that breast cancer patients whose primary cancer contains high levels of uPA have a significantly worse outcome than patients with low levels. As a prognostic marker for breast cancer the information supplied by uPA is both independent of traditionally used factors and significant in the important subgroup of axillary-node patients. Paradoxically, high levels of plasminogen activator inhibitor-1 (PAI-1), an endogenous inhibitor of uPA, also predict for aggressive disease. Recently, the prognostic impact of both uPA and PAI-1 in axillary node-negative breast cancer was confirmed using two different Level 1 Evidence studies, i.e. in both a randomized prospective trial and a pooled analysis. Therefore, uPA and PAI-1 appear to have fulfilled all the criteria for the routine assessment of prognosis in newly diagnosed breast cancer patients.     

Increased expression of mdig predicts poorer survival of the breast cancer patients

Breast cancer is the most common cancer and the second leading cause of cancer death among women of all races and Hispanic origin populations in the United States. In the present study, we reported that the survival time of the breast cancer patients is influenced by the expression level of mdig, a previously identified lung cancer-associated oncogene encoding a JmjC-domain protein. By checking the expression levels of mRNA and protein of mdig through both RT-PCR and immunohistochemistry in samples from 204 patients, we noticed that about 30% of breast cancer samples showed increased expression of mdig. Correlation of the mdig expression levels with the survival time of the breast cancer patients indicated a clear inverse relationship between mdig expression and patient survival, including poorer overall survival, distant metastasis free survival, relapse free survival, and post-progression survival. Taken together, these data suggest that an increased expression of mdig is an important prognostic factor for poorer survival time of the breast cancer patients.     

表面增强激光解吸电离飞行时间质谱技术筛查肺癌血清特异性蛋白质及其临床意义

目的:探讨用表面增强激光解吸电离飞行时间质谱(SELDI-TOF-MS)技术筛查肺癌血清特异性蛋白质的临床意义。方法:应用SELDI-TOF-MS对35例正常对照组、43例治疗前肺癌病人的血清样品进行蛋白质指纹图谱测定,用BioMarker Wizard 3．01及BioMarker Parrern System 5．01分析软件对测得的数据进行处理及建立诊断模型。结果:共检测到251个蛋白质峰,筛选出差异蛋白质峰11个,以质荷比(m/z)分别为M2799_26,M3227_41,M5739_70和M8164_30的4个蛋白质峰为依据组合构建分类决策树模型,分出5个终节点。决策树模型的原始判别总准确率为91．0%(71/78),敏感性为88．4%(38/43),特异性为94．3%(33/35);交叉验证总准确率为85．9%(67/78),敏感性为88．4%(38/43),特异性为82．9%(29/35)。结论:SELDI-TOF-MS在肺癌血清特异性蛋白质的筛选及诊断模型的建立有一定的临床意义。     

Plasminogen activator inhibitor-1 (PAI-1) gene 4G/5G promoter polymorphism is not associated with breast cancer

The antigen content of plasminogen activator inhibitor-1 (PAI-1) in primary breast cancer tissue extracts may be of strong prognostic value: high levels of PAI-1 in tumors predict poor prognosis for patients. The gene encoding PAI-1 is highly polymorphic and an insertion (5G)/deletion (4G) polymorphism in the PAI-1 gene promoter (the 4G/5G polymorphism), may have functional significance in PAI-1 expression. In the present work the distribution of genotypes and frequency of alleles of the 4G/5G polymorphism in subjects with breast cancer were investigated. Tumor tissues were obtained from 100 postmenopausal women with node-negative and node-positive ductal breast carcinoma with uniform tumor size. Blood samples from age matched healthy women served as control. The 4G/5G polymorphism was determined by PCR amplification using the allele specific primers. The distribution of the genotypes of the 4G/5G polymorphism in both control and patients did not differ significantly (P > 0.05) from those predicted by the Hardy-Weinberg distribution. There were no differences in the genotype distributions and allele frequencies between node-positive and node-negative patients. The 4G/5G polymorphism may not be linked with elevated level of PAI-1 observed in breast cancer and therefore may not be associated with appearance and/or progression of breast cancer.     

A prognostic eight-lncRNA expression signature in predicting recurrence of ER-positive breast cancer receiving endocrine therapy

Long noncoding RNAs (lncRNAs) have the main role in the tumorigenesis of breast cancer. In the present study, lncRNA expression profiling was collected to identify a lncRNA expression signature from the Gene Expression Omnibus database. An eight-lncRNA signature was established to predict the survival of patients with estrogen receptor (ER)-positive breast cancer receiving endocrine therapy. Patients were separated into a low-risk group and a high-risk group based on this signature. Patients in high-risk group have worse survival compared to those in low-risk group using Kaplan–Meier curve analysis with log-rank test. Receiver operating characteristic analysis suggested good diagnostic efficiency of the eight-lncRNA signature. When adjusting the clinical features, including age, grade, lymph node status, and tumor size, this signature was independently associated with the relapse-free survival. The prognostic value of the lncRNA prognostic model was then validated in validation sets. When validated in a cohort of patients treated with neoadjuvant chemotherapy and endocrine therapy, this signature demonstrated good performance as well. Besides, we have built a nomogram that integrated the conventional clinicopathological features and the eight-lncRNA-based signature. To sum up, our results indicated that the eight-lncRNA prognostic model was a reliable tool to group patients at high and low risk of disease relapse. This signature may have possible implication in prognostic evaluations of patients with ER-positive breast cancer receiving endocrine therapy.     

Identification of DNA methylation changes associated with human gastric cancer

Background

Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.

Methods

Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.

Results

We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.

Conclusions

Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.     

Progesterone Receptor Status and Ki-67 Index May Predict Early Relapse in Luminal B/HER2 Negative Breast Cancer Patients: A Retrospective Study

Purpose

Few studies has documented early relapse in luminal B/HER2-negative breast cancer. We examined prognostic factors for early relapse among these patients to improve treatment decision-making.

Patients and Methods

A total 398 patients with luminal B/HER2-negative breast cancer were included. Kaplan-Meier curves were applied to estimate disease-free survival and Cox regression to identify prognostic factors.

Results

Progesterone receptor (PR) negative expression was associated with higher tumor grade (p<.001) and higher Ki-67 index (p = .010). PR-negative patients received more chemotherapy than the PR-positive group (p = .009). After a median follow-up of 28 months, 17 patients (4.3%) had early relapses and 8 patients (2.0%) died of breast cancer. The 2-year disease-free survival was 97.7% in the PR-positive and 90.4% in the PR-negative groups (Log-rank p = .002). Also, patients with a high Ki-67 index (defined as >30%) had a reduced disease-free survival (DFS) when compared with low Ki-67 index group (≤30%) (98.0% vs 92.4%, respectively, Log-rank p = .013). In multivariate analysis, PR negativity was significantly associated with a reduced DFS (HR = 3.91, 95% CI 1.29–11.88, p = .016).

Conclusion

In this study, PR negativity was a prognostic factor for early relapse in luminal B/HER2-negative breast cancer, while a high Ki-67 index suggested a higher risk of early relapse.     

Analysis of DNA and morphometry in breast carcinoma

Feulgen-stained imprints and smears from 730 cases of invasive breast cancer were investigated using an image analysis system. From each tumor sample 100 cells were randomly scanned and several DNA and morphometrical parameters evaluated. Their prognostic value for a prediction of distant metastases within 5 years was investigated with the multivariate Cox regression analysis, which was performed for all consecutive cases, as well as for node-negative and node-positive patients separately. The multivariate analyses showed a strong prognostic value of the anisonucleosis (variation of nuclear radius) and the DNA histogram type in addition to the nodal status, the tumor size (pT), and the histological tumor grade. However, performing this analysis for both node-positive patients and for those without lymph node metastases demonstrated a different prognostic meaning of the variables. The combination of each of the group-specific variables led to a prognostic factor, which allowed an assignment of patients to several subgroups with significantly different risk for distant metastases. Thus, both a low-risk group of node-negative patients with a 5-year distant recurrence rate of only 5.8%, and a higher risk group of node-negative patients with a recurrence rate of 38.6% could be identified. Among the node-positive patients, a low-risk group with a distant recurrence rate of 8.6%, and also a high risk group with 69% distant recurrence, could be identified.     

Prognostic and predictive value of the urokinase-type plasminogen activator (uPA) and its inhibitors PAI-1 and PAI-2 in operable breast cancer

The present study on the prognostic and predictive value of serine proteases was conducted in 460 early breast cancer patients mostly treated with some kind of adjuvant systemic therapy: 156 received chemotherapy, 141 hormone therapy and 111 a combination of both. Already in univariate analysis PAI-1 was the only proteolytic factor with a significant impact on DFS, which was retained in multivariate analysis (p = 0.020); PAI-2 showed borderline significance in univariate analysis (p = 0.0503) and uPA did not present as a significant prognostic factor for DFS in our patient series. In a separate univariate analysis of DFS on patient subgroups defined by adjuvant systemic therapy, a higher risk of relapse associated with higher uPA and PAI-1 levels was found in the subgroup of patients who did not receive any treatment; this difference did not reach the level of significance, probably due to the small number (n = 52) of patients in this group (HR 1.37; p = 0.71 and HR 2.14; p = 0.321, respectively). A higher risk of relapse was also found in the subgroup of patients treated with adjuvant chemotherapy (HR 1.44; p = 0.381 and HR 2.48; p = 0.003, respectively). In contrast, the bad prognostic impact of high uPA and PAI-1 levels was lost in the subgroup of patients treated with adjuvant hormone therapy (HR 0.79; p = 0.693 and HR 0.26; p = 0.204, respectively). The same observations were made for the uPA/PAI-1 combination. Our study confirmed the prognostic value of serine proteases in early breast cancer. In addition, it pointed to a possible predictive value of these tumor markers for response to adjuvant hormone therapy with tamoxifen, which should be confirmed in further studies.     

Expression of the hypoxia-inducible monocarboxylate transporter MCT4 is increased in triple negative breast cancer and correlates independently with clinical outcome

Background

¹⁸Fluor-deoxy-glucose PET-scanning of glycolytic metabolism is being used for staging in many tumors however its impact on prognosis has never been studied in breast cancer.

Methods

Glycolytic and hypoxic markers: glucose transporter (GLUT1), carbonic anhydrase IX (CAIX), monocarboxylate transporter 1 and 4 (MCT1, 4), MCT accessory protein basigin and lactate-dehydrogenase A (LDH-A) were assessed by immunohistochemistry in two cohorts of breast cancer comprising 643 node-negative and 127 triple negative breast cancers (TNBC) respectively.

Results

In the 643 node-negative breast tumor cohort with a median follow-up of 124 months, TNBC were the most glycolytic (≈70%), followed by Her-2 (≈50%) and RH-positive cancers (≈30%). Tumoral MCT4 staining (without stromal staining) was a strong independent prognostic factor for metastasis-free survival (HR = 0.47, P = 0.02) and overall-survival (HR = 0.38, P = 0.002). These results were confirmed in the independent cohort of 127 cancer patients.

Conclusion

Glycolytic markers are expressed in all breast tumors with highest expression occurring in TNBC. MCT4, the hypoxia-inducible lactate/H⁺ symporter demonstrated the strongest deleterious impact on survival. We propose that MCT4 serves as a new prognostic factor in node-negative breast cancer and can perhaps act soon as a theranostic factor considering the current pharmacological development of MCT4 inhibitors.     

Diagnostic application of serum proteomic patterns in gastric cancer patients by ProteinChip surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is one of thecurrently used techniques to identify biomarkers for cancers. This study was planned to establish a system to accurately distinguish gastric cancer patients by using SELDI-TOF-MS. A total of 100 serum samples obtained from 60 individuals with gastric cancer and 40 healthy individuals were screened. Protein expression profiles were expressed on CM10 ProteinChip arrays and analyzed. Peak intensities were analyzed with the Biomarker Wizard software to identify peaks showing significantly different intensities between normal and cancer groups. Classification analysis and construction of decision trees were done with the Biomarker Pattern software 5.0. Seventeen protein peaks showed significant differences between the two groups. The decision tree which gave the highest discrimination included four peaks at mass 5,919, 8,583, 10,286, and 13,758 as splitters. The sensitivity and specificity for classification of the decision tree were 96.7% (58/60) and 97.5% (39/40), respectively. When the protein biomarker pattern was tested on a blinded test set, it yielded a sensitivity of 93.3% (28/30) and a specificity of 90% (18/20). These results suggest that serum protein profiling by the SELDI system may distinguish gastric cancer patients from healthy controls with relatively high sensitivity and specificity.     

Identifying gene expression changes in breast cancer that distinguish early and late relapse among uncured patients

MOTIVATION: In recent years, microarray technology has revealed many tumor-expressed genes prognostic of clinical outcomes in early-stage breast cancer patients. However, in the presence of cured patients, evaluating gene effect on time to relapse is quite complex since it may affect either the probability of never experiencing a relapse (cure effect) or the time to relapse among the uncured patients (disease progression effect) or both. In this context, we propose a simple and an efficient method for identifying gene expression changes that characterize early and late recurrence for uncured patients. RESULTS: Simulation results show the good performance of the proposed statistic for detecting a disease progression effect. In a study of early-stage breast cancer, our results show that the proposed statistic provides a more powerful basis for gene selection than the classical Cox model-based statistic. From a biological perspective, many of the genes identified here as associated with the speed of disease recurrence have known roles in tumorigenesis.