cytosis [48,49]. Thrombocytosis has been considered as a negative prognostic marker in several cancers [50,51]. Meanwhile, platelet aggregation and degranulation along with the consequent release of platelet-derived proangiogenic mediators within the microvas- culature of the tumor also could be an important determinant of tumor growth . On the other hand, lymphocytes play a large role in cancer immune-surveillance, which prevent tumor devel- opment . Cancer-related inflammation causes suppression of antitumor immunity by recruitment of regulatory T cells and activation of chemokines resulting in tumor growth and metastasis. In breast cancer and melanoma, tumor-infiltrating lymphocytes have been reported as an important prognostic factor, with higher levels associated with better survival [54,55]. In addition, lymphocytopenia has been reported to be associated with poorer survival outcomes in patients with pancreatic cancer and other gastrointestinal malignancies [56,57]. The association of clinico- pathological factors and PLR was explored in few studies retrieved in our analysis. Kwon et al.  reported that patients with greater PLR showed an increased likelihood of positive lymph node ratio in colorectal cancer. In the study of Asher et al. , PLR could reflect residual disease after surgery and status of clinical stage in ovarian cancer which was consistent with the results of Raungkaewmanee et al. . High PLR was also significantly related to bigger size of the tumor and positive status of lymph nodes metastasis in cervical cancer . Azab et al.  showed that higher PLR quartiles had significantly higher rates of lymph node involvement, higher rates of metastases, higher AJCC staging and lower hemoglobin in breast cancer patients. Interest- ingly, Lee  found that elevated PLR was frequently observed in female gastric cancer patients who did not accept operation previously and adjuvant chemotherapy. These findings suggest that PLR can be a predictor of the state of some tumors. As mentioned above, thrombocytosis and lymphocytopenia both correlate with the degree of host systemic inflammation that PLR might reflect a novel inflammatory marker incorporating the two hematologic factors .
characteristics among the included studies. Heterogeneity is a potential problem that may affect the interpretation of the results of all meta-analyses. Subgroup and meta-regression suggested that cancer type might partially explain the heterogeneity. Of the 26 included studies, only one concerned treatment for ICC. Therefore, the pooled predictive role of high NLR cut-off for survival of ICC patients in subgroup analysis was negative because of the single negative report in the Gomez study. The limited sample size and number of ICC studies induced heterogeneity in this meta-analysis, and larger studies of ICC are required to provide further evidence. In addition, the NLR cut-off value was set differently among studies, which was one of the main sources of heterogeneity. Another weakness of our study was publication bias, Figure 5. Forest plots of the association between the NLR and tumor characteristics. (A) The association between the NLR and vascular invasion. (B) The association between the NLR and an elevated AFP level. Green represents the subgroup pooled effective size, whereas red represents the overall pooled effective size. NLR = neutrophil-to-lymphocyte ratio; AFP = alpha feto-protein; CI = confidence interval; *, the different study by Gomez; **, the different study by Wang.
Two professional reviewers independently extracted relevant data from texts, tables and fig- ures. Any disagreements in data extraction were resolved through discussion among three authors. The following data was collected: author, published year, country of the study partici- pants, number of patients, age distribution, gender distribution, detection method, cutoff valueof ALDH1 expression, rate of high ALDH1 expression, clinicopathological features (T stage, N stage, and tumor differentiation), follow-up time, 5-year OS / DFS rate. Since some publica- tions provided OS/DFS data by Kaplan-Meier curves, but not the rate directly, the software GetData Graph Digitizer 2.25 was used to extract the data.
This meta-analysis was performed using the Review Manager (RevMan) software (version 5.2; Cochrane collaboration, http:ims. cochrane.org/revman/download) and STATA (version 12.0, Stata Corp. College Station, Texas) . Odds ratios (OR), together with 95% confidence intervals (CI), was analyzed to estimate whether and how reduced E-cadherin expression impacts the prognosis of HCCs. Pooled values of ORs and 95% CIs, as the recommended summary statistics for meta-analysis, were calcu- lated using either a fixed-effects or a random-effects model. Heterogeneity among the outcomes of enrolled studies in this meta-analysis was evaluated by using Chi-square based Q statistical test . And I 2 statistic was calculated to quantify the total variation consistent with inter-study heterogeneity, ranging from 0% to 100% Heterogeneity was significant and unacceptable while I 2 statistic was greater than 50%. P,0.05 in Q statistical test was considered statistically significant. Choose fixed-effects models to calculate effect size estimates for those studies lack of heterogeneity with a P value for Q-test higher than 0.10. On the contrary, random-effects models were used when P#0.10. The funnel plots was made by utilizing Egger’s test and Begg’s test to examine the risk of potential publication bias. Then, trim and fill analyses were used to evaluate the stability of our meta-analysis results if the plots were asymmetrical.
Bladder Cancer Associated Protein (BLCAP, formerly Bc10), was identified by our laboratory as being down-regulated in bladder cancer with progression. BLCAP is ubiquitously expressed in different tissues, and several studies have found differential expression of BLCAP invarious cancer types, such as cervical and renal cancer, as well as human tongue carcinoma and osteosarcoma. Here we report the first study of the expression patterns of BLCAP in breast tissue. We analyzed by immunohistochemistry tissue sections of normal and malignant specimens collected from 123 clinical high-risk breast cancer patients within the Danish Center for Translational Breast Cancer Research (DCTB) prospective study dataset. The staining pattern, the distribution of the immunostaining, and its intensity were studied in detail. We observed weak immunoreactivity for BLCAP in mammary epithelial cells, almost exclusively localizing to the cytoplasm and found that levels of expression of BLCAP were generally higher in malignant cells as compared to normal cells. Quantitative IHC analysisof BLCAP expression in breast tissues confirmed this differential BLCAP expression in tumor cells, and we could establish, in a 62-patient sample matched cohort, that immunostaining intensity for BLCAP was increased in tumors relative to normal tissue, in more than 45% of the cases examined, indicating that BLCAP may be ofvalue as a marker for breast cancer. We also analyzed BLCAP expression and prognosticvalue using a set of tissue microarrays comprising an independent cohort of 2,197 breast cancer patients for which we had follow-up clinical information.
Notably, various laboratory assays have been used to determine FGFR gene amplification. In situ hybridization techniques are used to measure gene amplification that relies on either fluorescence (FISH) or chromogenic and silver in situ hybridiza- tion (CISH and SISH). However, even using the same measure- ment method (e.g. FISH), different criteria have been used to define FGFR positivity. These differences in methodology can be the cause of the large range and heterogeneity of FGFR1 amplification (from 2.6 to 30.9%). Standardization of the definition of ‘FGFR gene amplification’ is therefore urgently needed. As for other gene amplifications such as HER2 and EGFR, a scoring system is recommended for FGFR gene amplification. Nonetheless, most of the included studies in this meta-analysis used subjective scores without standardization. We believe that publication bias for FGFR1 amplification prevalence is due to the many evaluation standards used. Despite this, the results from subgroup analysis relating to specific methodology (SNP screen, FISH, qPCR, and aCGH) were similar to those of the overall analysis (see Table S2).
However, our study has several limitations, as we could not prevent all potential bias among these studies. Although 21 studies were included in the final analysis, the average sample size was small (mean,98). For articles without HR and 95%CI, we contacted the corresponding author, but received no reply. Consequently, we extrapolated these metrics from the data or curves in these articles indirectly, which could be another potential source of bias. Different methods of examining bFGF expression, primary antibody source and concentration, and threshold cut-off values may introduce more bias as well. IHC is a relatively complicated tech- nique with many steps and is observer-dependent. Moreover, our meta-analysis data did not include information on age, smoking status, tumor size and other factors, which might result in confounding bias. Lastly, we included studies which dichotomized bFGF expression into the high and low expression group. Other studies that included bFGF expression as a continuous variable were excluded because the data was not extractable.
We started summarizing the effect of BRAF-V600E mutation on patient survival separately based on study design RCT versus cohort and cancer type. We evaluated the publication bias using funnel plot analysis. We also assessed the heterogeneity of the studies using chi-square test of heterogeneity and I 2 measure of inconsistency. Significant heterogeneity was defined as a Chi- square test P valueof ,0.10 or as an I 2 measure .50%. Estimated hazard ratio (HR) was calculated using odds ratio and confidence interval in studies where HR was not available. In the absence of heterogeneity HRs and CIs were calculated according to a fixed model  which assumes that results across studies differ only by sampling error. In those studies where only the survival curve was available with no other detailed information, survival rates were extracted over multiple time periods in order to reconstruct HR and its variance with the assumption that patient censor rate was constant during study follow-up. This method has been described
Subgroup analysis is a method for exploring the sources of heterogeneity and for increasing the reliability of an article. Tumor stage is an important factor that affects the prognosis of NSCLC . While the patients in the included studies were of different disease stages, Zhu et al. studied only stage IB NSCLC patients , and Li et al. did not report the disease stage of the pa- tients they enrolled . Therefore, we performed subgroup analysis according to stage, and found that TIMP-2 expression was a statistically significant favorable factor in patients with stage I-IV NSCLC. From this, we may assume that high TIMP-2 expression is not only related to out- come in early-stage NSCLC, but also the late stages. The methods used to measure TIMP-2 ex- pression varied between the studies, which may have reduced the reliability of our result. We selected the most commonly applied method, i.e., IHC, for the subgroup analysis and found that the conclusion that high TIMP-2 expression is associated with good prognosis in NSCLC re- mained the same if only IHC was used to assess TIMP-2 expression levels. The percentage of high TIMP-2 expression of patients in the included studies ranged 31–67.3%. The reasons for this may be the differing states of illness, definitions of positive expression, and race or sex com- position of the sampled populations in the included studies. Therefore, we selected studies where the percentage of high TIMP-2 expression was <50% for subgroup analysis to determine the strength of the previous conclusion. This subgroup analysis also suggested that high TIMP-2 ex- pression in NSCLC patients was a significant predictor of good survival. Thus, we believe that TIMP-2 may be a relatively stable indicator of favorable prognosis in NSCLC.
All of the above findings should be verified in a larger group of patients using the other potential markers (e.g., PCNA, FGFR3, AKT1). Extensive study allow definitively determine the diagnostic and prognostic markers with the highest informative value suitable not only for urinary bladder cancer, but also for other malignancies (Cariaga-Martinez et al., 2013; Ziaran et al., 2013).
Furthermore, we found that high EZH2 expression was more closely associated with poor OS in Asian patients than in Western populations, in which EZH2 had no significant predictive value for DFS. However, there were only two studies of DFS in Western patients, resulting in a loss of comparative strength for the pooled data, and inevitably introducing considerable bias. The results based on higher-quality reports revealed that high EZH2 expression was signifi- cantly associated with OS, but not with DFS or RFS. Moreover, sample size was found to be a significant source of heterogeneity, and HRs were smaller in large studies than in small studies. Therefore, we might have overestimated the significance of EZH2 in predicting cancer survival, as a consequence of the disproportionate contribution of results from low-quality or relatively small studies. Similarly, our analysisof EZH2’s associations with MFS, PFS, CSS, and DSS were based on only two or three studies, with inevitable publication bias. Accordingly, no firm con- clusions can be drawn at present.
Esophageal squamous cell carcinoma (ESCC) is one of the most malignant gastrointestinal cancers and occurs at a high frequency rate in China and other Asian countries. Recently, several molecular markers were identified for pre- dicting ESCC. Notwithstanding, additional prognostic markers, with a clear understanding of their underlying roles, are still required. Through bioinformatics, a graph-clustering method by DPClus was used to detect co-expressed modules. The aim was to identify a set of discriminating genes that could be used for predicting ESCC through graph-clustering and GO-term analysis. The results showed that CXCL12, CYP2C9, TGM3, MAL, S100A9, EMP-1 and SPRR3 were highly associated with ESCC development. In our study, all their predicted roles were in line with previous reports, whereby the assumption that a combination ofmeta-analysis, graph-clustering and GO-term analy- sis is effective for both identifying differentially expressed genes, and reflecting on their functions in ESCC.
corresponding study arms. The meta-regression analysis found that some of the pooled HRs were influenced by study characteristics (uni- vs. multivariate analysis, NOS score and eligible cases), as shown in Table 2. Subgroup analyses based on these study characteristics were per- formed to eliminate the between-studies heterogeneity and to evaluate the HRs ofvarious sub- groups (all HRs >1, P < 0.05, Table 2). Second, the prognostic effects of the MAPF status were repeatedly confirmed through subgroup analyses and validated in “trim and fill” analyses, yet some potential confounders might have weakened the HR estimate. We cannot completely exclede the presence of prognosis-related confounding factors in the estimated HR. Although the subgroup analyses based on multivariate-adjusted HRs were performed to minimize poten- tial confounders, the prognosticvalueof MAPF persisted with respect to OS (CEA: HR 1.95, 95% CI 1.53–2.50; CEA/CK20: 11.98, 95% CI 3.07–46.66; cytology negative status: HR 1.92, 95% CI 1.17–3.15; curative treatment: HR 2.94, 95% CI 1.27–6.85), DFS (CEA/CK20: HR 4.31, 95% CI 1.49–12.48; cytology negative status: HR 3.49, 95% CI 1.14–10.69;) and PRF (CEA: HR 2.60, 95% CI 1.77–3.83; CEA/CK20: HR 3.67, 95% 1.69–7.96; cytology negative status: HR 1.75, 95% CI 1.08–2.84; curative treatment: HR 3.44, 95% CI 2.01–5.87)(Table 2 and Figs 4 and 5).
epithelium through progesterone. During endometriosis, only the PgRA isoform is expressed and the absence of PgRB is suggested due to the inappropriate cycling of the endometrial gland ; however PgRA expression in normal cycling is predominant during the proliferative phase, which shifts towards PgRB expression during the early secretary phase . The upregulation and proliferative nature of the PgRB isoform in the carriers of the +331A allele may result in different types of cancer . With respect to this biological postulation, the +331G/A PgR may modulate cancer risk. However, the association of this polymorphism with overall cancer risk was mild (OR = 1.063, p = 0.048). It is important to note that expression of the PgR is associated with better disease-free survival . An alteration in the ratio of the expression of the PgR isoforms precedes changes that may lead to endometrial carcinoma . The increase in PgRB expression due to polymorphism in promoter leads to changes in the isoform ratio and is associated with an increased risk of developing endome- trial cancer . Additionally, a case-control study of endome- trial cancer with the +331G/A PgR polymorphism and PgR expression predicted that the recurrence risk and clinical response to progesterone therapy was six times more likely in women with PR(+) than with PR(2) tumors. Progesterone therapy is effective against the developed endometrial cancer, which is dependent on oestrogen-mediated proliferation. Also, PR(+) endometrial cancer was an independent prognostic factor in disease-free survival . The finding that PgRB could contribute to cell proliferation may provide clinical implications for hormonal management of endometrial and mammalian epithelium by rectifying relative expression of the PgRA: PgRB isoform, which is essential for appropriate reproductive tissue responses. Isoform-specific modulators like progestin, which could differentiate between PgRA and PgRB isoform, may also be of clinical value.
In face of the epidemiology of chest pain in the ED, the evaluation of these patients is a major challenge, both from the point of view of diagnosis and the optimization of time (to start treatment or discharge) and in the correct direction of resources. The use of serum biomarkers does not allow a rapid exclusion of myocardial ischemia, resulting in early discharge from the ED. Thus, there are limited tools available for fast triage of patients with chest pain. It is with this idea that the four clinical trials randomized 12-15 investigated the
AKT has been found to play a role in the survival of cancer cells in breast, prostate, ovary, and brain tissue [25-28]. It was also identified as a constitutively active kinase that promotes survival of NSCLC cell . Recently, a clinical study of p-AKT expression in tissue from patients with bronchial epithelial dysplasia and malignancy corroborates this hypothesis. They observed strong p-AKT staining in 12 of 44 normal bronchial biopsy specimens, 4 of 9 reactive specimens, 22 of 25 dysplastic specimens, and 25 of 76 NSCLC specimens. Tsao et al.  considered that AKT activation may be more strongly associated with the early stages of malignant transformation than with progression to frank neoplasia .
Astrocyte elevated gene-1 (AEG-1), also known as metadherin (MTDH)  or LYsine-RIch CEACAM1 coisolated (LYRIC) , was first identified in 2002 as a novel protein induced in primary human fetal astrocytes infected by human immunodeficiency virus 1 (HIV)-1 and tumor necrosis factor-α (TNF-α) . The AEG-1 gene is an oncogene, which is located at chromosome 8q22 , and it is observed that elevated expression of AEG-1 promoted tumor proliferation, progression or metastasis in multiple carcinomas such as EC , HCC , neu- roblastoma , breast cancer , prostate cancer  and malignant glioma . In addition, AEG-1 could activate multiple molecular mechanisms to exert its functions, including nuclear factor κ-B (NF-κB) , phosphatidylinositol 3-kinase (PI3K)/Akt and c-Myc [13, 14], Wnt/ b-catenin , extracellular signal-regulated kinase (ERK) , activator protein 1 (AP-1)  and non-thyroidal illness syndrome (NTIS) . Also, it was reported that AEG-1 could increase the expression of angiopoietin-1, matrix metalloprotease-2 (MMP2), hypoxia-induc- ible factor 1-α (HIF-α) and Tie2, which are essential in angiogenesis .
Three study were excluded from this meta-analysis because PD-L1 expression were detected using DNA microarray[30, 31] or fluorescent RNAscope paired-primer assay. Clearly, comparing IHC-based protein expression with microarray-based gene-expression levels can lead to quite distinct conclusions. For example, DNA microarray-based measurements quan- tify expression levels in tumor cells, non-tumor cells, and infiltrating immune cells, while our present study focused on the expression of PD-L1 in tumor cells. Sabatier et al and Schalper et al concluded that PD-L1 upregulation was associated with better survival in patients with breast cancer especially basal-like breast cancer (express genes characteristic of the outer or basally located epithelial layer of the mammary gland)[31 – 33], while Bertucci et al considered PD-L1 overexpression in inflammatory breast cancer orrelated with better response to chemo- therapy. The differences in results between these studies may be mainly due to differences in the detection method used and the subtype of breast cancer.
Medical subheading (Mesh) terms relating to NLR (e.g. ‘‘neutrophil-to-lymphocyte ratio’’ or ‘‘neutrophil lymphocyte ratio’’) combined with words related to urinary cancers (e.g. ‘‘renal cancer’’, ‘‘bladder cancer’’, ‘‘prostate cancer’’, ‘‘urothelial cancer’’ or ‘‘transitional cell carcinoma’’) and terms to prognosis (e.g. ‘‘outcome’’, ‘‘prognosis’’, ‘‘prognostic’’ or ‘‘survival’’) were searched on PubMed and the last search was updated on November 17, 2013. The references of articles and reviews were also explored to retrieve potentially additional studies. Studies were eligible if they met the following criteria: (a) patients with urinary cancersin the studies were histopathologically confirmed; (b) investigated the association of pre-treatment NLR with overall survival (OS), recurrence-free survival (RFS) or cancer-specific survival (CSS); (c) full text articles in English. Exclusion criteria were as follows: (a) letters, reviews, expert opinions, case reports or laboratory studies; (b) studies had overlapping or duplicate data; (c) lack of key information for further analysis.
Cluster of differentiation 11b (CD11b) is a kind of cell surface receptor that are selectively expressed on leukocytes, which is also named as integrin alpha M (ITGAM), complement com- ponent 3 receptor alpha chain (CR3a), macrophage-1 antigen alpha subunit or macrophage receptor 1 alpha subunit (MAC1a). In GENE database of national center for biotechnology information (NCBI), this protein is also named as systemic lupus erythematosus type 6 (SLEB6) or MO1A[11, 12,13]. It is one protein subunit that forms the heterodimeric integrin alpha-M beta-2 molecule with cluster of differentiation 18 (CD18), also named as macro- phage-1 antigen or macrophage-1 antigen (Mac-1), complement receptor 3 (CR3)or MO1[11, 12,13]. This protein can participate in cell activation, chemotaxis, cytotoxicity, phagocytosis and regulates interaction of leukemic cells with microenvironment through binding to its ligands, such as inactivated complement component 3b (iC3b), intercellular adhesion molecule (ICAM), fibrinogen, beta-glukanes, coagulation factor X etc.[14–19]. Recently, CD11b is also defined as a marker for myeloid-derived suppressor cells, which is reported to be harnessed by malignant cells to restrain antitumor immunity and to promote malignant expansion or refrac- toriness to treatment [20–22]. So it is presumable that CD11b may participate in the regulation of biology of malignant AML cells and its expression level may affect the prognosis of AML patients.