Preoperative Monocyte-to-Lymphocyte Ratio in Peripheral Blood Predicts Stages,Metastasis, and Histological Grades in Patients with Ovarian Cancer

PURPOSE: The monocyte-to-lymphocyte ratio (MLR) has been shown to be associated with the prognosis of various solid tumors. This study sought to evaluate the important value of the MLR in ovarian cancer patients. METHODS: A total of 133 ovarian cancer patients and 43 normal controls were retrospectively reviewed. The patients'' demographics were analyzed along with clinical and pathologic data. The counts of peripheral neutrophils, lymphocytes, monocytes, and platelets were collected and used to calculate the MLR, neutrophil-to-lymphocyte ratio (NLR). and platelet-to-lymphocyte ratio (PLR). The optimal cutoff value of the MLR was determined by using receiver operating characteristic curve analysis. We compared the MLR, NLR, and PLR between ovarian cancer and normal control patients and among patients with different stages and different grades, as well as between patients with lymph node metastasis and non–lymph node metastasis. We then investigated the value of the MLR in predicting the stage, grade, and lymph node positivity by using logistic regression. The impact of the MLR on overall survival (OS) was calculated by Kaplan-Meier method and compared by log-rank test. RESULTS: Statistically significant differences in the MLR were observed between ovarian cancer patients and normal controls. However, no difference was found for the NLR and PLR. Highly significant differences in the MLR were found among patients with different stages (stage I-II and stage III-IV), grades (G1 and >G1), and lymph node metastasis status. The MLR was a significant and independent risk factor for lymph node metastasis, as determined by logistic regression. The optimal cutoff value of the MLR was 0.23. We also classified the data according to tumor markers (CA125, CA199, HE4, AFP, and CEA) and conventional coagulation parameters (International Normalized Ratio [INR] and fibrinogen). Highly significant differences in CA125, CA199, HE4, INR, fibrinogen levels, and lactate dehydrogenase were found between the low-MLR group (MLR ≤ 0.23) and the high-MLR group (MLR > 0.23). Correspondingly, dramatic differences were observed between the two groups in OS. CONCLUSION: Our results show that the peripheral blood MLR before surgery could be a significant predictor of advanced stages, advanced pathologic grades, and positive lymphatic metastasis in ovarian cancer patients.     

An Epigenetic Signature in Peripheral Blood Associated with the Haplotype on 17q21.31, a Risk Factor for Neurodegenerative Tauopathy

Little is known about how changes in DNA methylation mediate risk for human diseases including dementia. Analysis of genome-wide methylation patterns in patients with two forms of tau-related dementia – progressive supranuclear palsy (PSP) and frontotemporal dementia (FTD) – revealed significant differentially methylated probes (DMPs) in patients versus unaffected controls. Remarkably, DMPs in PSP were clustered within the 17q21.31 region, previously known to harbor the major genetic risk factor for PSP. We identified and replicated a dose-dependent effect of the risk-associated H1 haplotype on methylation levels within the region in blood and brain. These data reveal that the H1 haplotype increases risk for tauopathy via differential methylation at that locus, indicating a mediating role for methylation in dementia pathophysiology.     

Gene Expression Signature of Normal Cell-of-Origin Predicts Ovarian Tumor Outcomes

The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.     

An Elevated Peripheral Blood Lymphocyte-to-Monocyte Ratio Predicts Favorable Response and Prognosis in Locally Advanced Breast Cancer following Neoadjuvant Chemotherapy

Purpose

Neoadjuvant chemotherapy (NCT) is a standard treatment option for locally advanced breast cancer. However, the lack of an efficient method to predict treatment response and patient prognosis hampers the clinical evaluation of patient eligibility for NCT. An elevated lymphocyte-to-monocyte ratio (LMR) has been reported to be associated with a favorable prognosis for certain hematologic malignancies and for nasopharyngeal carcinoma; however, this association has not been investigated in breast cancer. The purpose of this study was to evaluate whether pre-NCT LMR analysis could predict the prognosis of patients with locally advanced breast cancer.

Methods

A retrospective cohort of 542 locally advanced breast cancer patients (T3/T4 and/or N2/N3 disease) receiving NCT followed by radical surgery was recruited between May 2002 and August 2011 at the Fudan University Shanghai Cancer Center. Counts for pre-NCT peripheral absolute lymphocytes and monocytes were obtained and used to calculate the LMR.

Results

Univariate and multivariate analysis revealed that higher LMR levels (≥4.25) were significantly associated with favorable DFS (P = 0.009 and P = 0.011, respectively). Additionally, univariate analysis revealed that a higher lymphocyte count (≥1.5×10⁹/L) showed borderline significance for improved DFS (P = 0.054), while a lower monocyte count (<0.4×10⁹/L) was associated with a significantly better DFS (P = 0.010).

Conclusions

An elevated pre-NCT peripheral LMR level was a significantly favorable factor for locally advanced breast cancer patient prognosis. This easily obtained variable may serve as a valuable marker to predict the outcomes of locally advanced breast cancer.     

An Elevated Peripheral Blood Monocyte-to-Lymphocyte Ratio Predicts Poor Prognosis in Patients with Primary Pulmonary Lymphoepithelioma-Like Carcinoma

Primary pulmonary lymphoepithelioma-like carcinoma (LELC) is a rare type of non-small cell lung cancer. In this study, we retrospectively reviewed the data from 74 consecutive patients with pulmonary LELC and investigated the prognostic value of pretreatment monocyte-to-lymphocyte ratio (MLR). The cut-off value determined by ROC curve for MLR was 0.262. According to this cut-off value, 36 (48.6%) patients had lower MLR value (<0.262) at diagnosis. There was no significant correlation between MLR level and gender, age, smoking history, stage, and lactate dehydrogenase (LDH) level. The 2-year, 5-year, and 10-year OS rate were 86%, 72%, and 61%, respectively; the 2-year, 5-year, and 10-year PFS rate were 71%, 63%, and 49%, respectively. In univariate analysis, advanced stage, elevated LDH level, and higher MLR value (> = 0.262) were significantly associated with poor OS and PFS. In a multivariate Cox regression model that included stage, LDH and MLR level, all of these three factors were found to be independent prognostic factors for both PFS and OS. In patients who received radical surgery, MLR level remained significantly correlated with OS and PFS. In conclusion, we firstly demonstrated that pretreatment MLR can be used as a useful independent prognostic marker in patients with pulmonary LELC, and might guide us to optimize the treatment strategies. However, due to the relatively rarity of this disease and the limitation of a retrospective study, further prospective studies performed in multicenter are necessary to validate the prognostic value of MLR in pulmonary LELC.     

Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell population and difficult to isolate experimentally. Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer. The purpose of this study was the genomic identification and characterization of a subtype of ovarian cancer that has stem cell-like gene expression. Using human and mouse gene signatures of embryonic, adult, or cancer stem cells, we performed an unsupervised bipartition class discovery on expression profiles from 145 serous ovarian tumors to identify a stem-like and more differentiated subgroup. Subtypes were reproducible and were further characterized in four independent, heterogeneous ovarian cancer datasets. We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival. Conversely, the differentiated tumors share properties with Type I, including lower grade and mixed histological subtypes. The stem cell-like signature was prognostic within high-stage serous ovarian cancer, classifying a small subset of high-stage tumors with better prognosis, in the differentiated subtype. In multivariate models that adjusted for common clinical factors (including grade, stage, age), the subtype classification was still a significant predictor of relapse. The prognostic stem-like gene signature yields new insights into prognostic differences in ovarian cancer, provides a genomic context for defining Type I/II subtypes, and potential gene targets which following further validation may be valuable in the clinical management or treatment of ovarian cancer.     

The Cold-Inducible RNA-Binding Protein (CIRP) Level in Peripheral Blood Predicts Sepsis Outcome

Objectives

Sepsis is a lethal and complex clinical syndrome caused by infection or suspected infection. Cold-inducible RNA-binding protein (CIRP) is a widely distributed cold-shock protein that plays a proinflammatory role in sepsis and that may induce organ damage. However, clinical studies regarding the use of CIRP for the prognostic evaluation of sepsis are lacking. The purpose of this research was to investigate the prognostic significance of peripheral blood concentrations of CIRP in sepsis. Sepsis was assessed using several common measures, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score; the Sepsis-related Organ Failure Assessment (SOFA) score; the lactate, serum creatinine, and procalcitonin (PCT) levels; the white blood cell (WBC) count; and the neutrophil ratio (N%).

Design

Sixty-nine adult patients with sepsis were enrolled in this study. According to the mortality data from the hospital, 38 patients were survivors, and 31 were nonsurvivors. The plasma levels of the biomarkers were measured and the APACHE II and SOFA scores were calculated within 24 hours of patient enrollment into our study. The CIRP level was measured via ELISA.

Results

The plasma level of CIRP was significantly higher in the nonsurvivors than in the survivors (median (IQR) 4.99 (2.37–30.17) ng/mL and 1.68 (1.41–13.90) ng/mL, respectively; p = 0.013). The correlations of the CIRP level with the APACHE II score (r = 0.248, p = 0.040, n = 69), the SOFA score (r = 0.323, p = 0.007, n = 69), the serum creatinine level (r = 0.316, p = 0.008, n = 69), and the PCT level (r = 0.282, p = 0.019, n = 69) were significant. Receiver operator characteristic (ROC) curve analysis showed that the area under the ROC curve (AUC) for the CIRP level was 0.674 (p = 0.013). According to Cox proportional hazards models, the CIRP level independently predicts sepsis mortality. When the CIRP level in the peripheral blood increased by 10 ng/mL, the mortality risk increased by 1.05-fold (p = 0.012). Thus, the CIRP level reflects the degree of renal injury but does not predict the severity of sepsis or organ damage.

Conclusion

An elevated plasma concentration of CIRP was significantly associated with poor prognosis among patients with sepsis. Therefore, CIRP is a potential predictor of sepsis prognosis.     

癌症中的表观遗传变化

DNA与组蛋白上的共价标记如何参与癌细胞的产生与扩散,这项研究同时带来了新的治疗策略。     

A Seven-microRNA Expression Signature Predicts Survival in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth common cancer. The differential expression of microRNAs (miRNAs) has been associated with the prognosis of various cancers. However, limited information is available regarding genome-wide miRNA expression profiles in HCC to generate a tumor-specific miRNA signature of prognostic values. In this study, the miRNA profiles in 327 HCC patients, including 327 tumor and 43 adjacent non-tumor tissues, from The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) were analyzed. The associations of the differentially expressed miRNAs with patient survival and other clinical characteristics were examined with t-test and Cox proportional regression model. Finally, a tumor-specific miRNA signature was generated and examined with Kaplan–Meier survival, univariate\multivariate Cox regression analyses and KEGG pathway analysis. Results showed that a total of 207 miRNAs were found differentially expressed between tumor and adjacent non-tumor HCC tissues. 78 of them were also discriminatively expressed with gender, race, tumor grade and AJCC tumor stage. Seven miRNAs were significantly associated with survival (P value <0.001). Among the seven significant miRNAs, six (hsa-mir-326, hsa-mir-3677, hsa-mir-511-1, hsa-mir-511-2, hsa-mir-9-1, and hsa-mir-9-2) were negatively associated with overall survival (OS), while the remaining one (hsa-mir-30d) was positively correlated. A tumor-specific 7-miRNAs signature was generated and validated as an independent prognostic predictor. Collectively, we have identified and validated an independent prognostic model based on the expression of seven miRNAs, which can be used to assess patients’ survival. Additional work is needed to translate our model into clinical practice.     

A Ten-MicroRNA Signature Identified from a Genome-Wide MicroRNA Expression Profiling in Human Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.     

Ovarian Function,Not Age,Predicts the Benefit from Ovarian Suppression or Ablation for Premenopausal Women with Breast Cancer

The role of adjuvant ovarian suppression or ablation (OS/OA) in premenopausal women with hormone receptor-positive breast cancer remains controversial. The purpose of our study was to examine which patients might benefit from the addition of OS/OA to tamoxifen. We analyzed the data of 2065 premenopausal patients with hormone receptor-positive invasive ductal carcinomas who were treated at Sun Yat-Sen University Cancer Center from 2000 to 2008. The five-year disease-free survival rate (DFSR) and overall survival rate (OSR) were compared by menstrual status and treatment. Compared with patients older than forty years of age, patients younger than forty years old had significant lower DFSRs and OSRs. The addition of OS/OA to tamoxifen increased the DFSR and OSR of patients with normal menstrual cycles after chemotherapy, regardless of their age at diagnosis. Patients with normal menstrual cycles after chemotherapy are the main beneficiaries of an adjuvant OS/OA.     

A Long Noncoding RNA Signature That Predicts Pathological Complete Remission Rate Sensitively in Neoadjuvant Treatment of Breast Cancer

BACKGROUND: Mounting evidence suggests that long noncoding RNAs (lncRNAs) are closely related to pathological complete response (pCR) in neoadjuvant treatment of breast cancer. Here, we construct lncRNA associated models to predict pCR rate. METHODS: LncRNA expression profiles of breast cancer patients treated with neoadjuvant chemotherapy (NAC) were obtained from Gene Expression Omnibus by repurposing existing microarray data. The prediction model was firstly built by analyzing the correlation between pCR and lncRNA expression in the discovery dataset GSE 25066 (n = 488). Another three independent datasets, GSE20194 (n = 278), GSE20271 (n = 178), and GSE22093 (n = 97), were integrated as the validation cohort to assess the prediction efficiency. RESULTS: A novel lncRNA signature (LRS) consisting of 36 lncRNAs was identified. Based on this LRS, patients with NAC treatment were divided into two groups: LRS-high group and LRS-low group, with positive correlation of pCR rate in the discovery dataset. In the validation cohort, univariate and multivariate analyses both demonstrated that high LRS was associated with higher pCR rate. Subgroup analysis confirmed that this model performed well in luminal B [odds ratio (OR) = 5.4; 95% confidence interval (CI) = 2.7-10.8; P = 1.47e-06], HER2-enriched (OR = 2.5; 95% CI = 1.1-5.7; P = .029), and basal-like (OR = 5.5; 95% CI = 2.3-16.2; P = 5.32e-04) subtypes. Compared with other preexisting prediction models, LRS demonstrated better performance with higher area under the curve. Functional annotation analysis suggested that lncRNAs in this signature were mainly involved in cancer proliferation process. CONCLUSION: Our findings indicated that our lncRNA signature was sensitive to predict pCR rate in the neoadjuvant treatment of breast cancer, which deserves further evaluation.     

A Thirteen-Gene Expression Signature Predicts Survival of Patients with Pancreatic Cancer and Identifies New Genes of Interest

Background

Currently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions.

Methods and Findings

Affymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.

Conclusions

We identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.     

An Eight-Gene Blood Expression Profile Predicts the Response to Infliximab in Rheumatoid Arthritis

Background

TNF alpha blockade agents like infliximab are actually the treatment of choice for those rheumatoid arthritis (RA) patients who fail standard therapy. However, a considerable percentage of anti-TNF alpha treated patients do not show a significant clinical response. Given that new therapies for treatment of RA have been recently approved, there is a pressing need to find a system that reliably predicts treatment response. We hypothesized that the analysis of whole blood gene expression profiles of RA patients could be used to build a robust predictor to infliximab therapy.

Methods and Findings

We performed microarray gene expression analysis on whole blood RNA samples from RA patients starting infliximab therapy (n = 44). The clinical response to infliximab was determined at week 14 using the EULAR criteria. Blood cell populations were determined using flow cytometry at baseline, week 2 and week 14 of treatment. Using complete cross-validation and repeated random sampling we identified a robust 8-gene predictor model (96.6% Leave One Out prediction accuracy, P = 0.0001). Applying this model to an independent validation set of RA patients, we estimated an 85.7% prediction accuracy (75–100%, 95% CI). In parallel, we also observed a significantly higher number of CD4+CD25+ cells (i.e. regulatory T cells) in the responder group compared to the non responder group at baseline (P = 0.0009).

Conclusions

The present 8-gene model obtained from whole blood expression efficiently predicts response to infliximab in RA patients. The application of the present system in the clinical setting could assist the clinician in the selection of the optimal treatment strategy in RA.     

Functional Folate Receptor Alpha Is Elevated in the Blood of Ovarian Cancer Patients

Background

Despite low incidence, ovarian cancer is the fifth leading cause of cancer deaths and it has the highest mortality rate of all gynecologic malignancies among US women. The mortality rate would be reduced with an early detection marker. The folate receptor alpha (FRα) is one logical choice for a biomarker because of its prevalent overexpression in ovarian cancer and its exclusive expression in only a few normal tissues. In prior work, it was observed that patients with ovarian cancer had elevated serum levels of a protein that bound to a FRα-specific monoclonal antibody relative to healthy individuals. However, it was not shown that the protein detected was intact functional FRα. In the current study, the goal was to determine whether ovarian cancer patients (n = 30) had elevated serum levels of a fully functional intact FRα compared to matched healthy controls (n = 30).

Methodology/Principal Findings

FRα levels in serum were analyzed by two methods, immunoblotting analysis and a radiolabeled folic acid-based microfiltration binding assay. Using the immunoassay, we observed that levels of FRα were higher in serum of ovarian cancer patients as compared to controls. Similar results were also observed using the microfiltration binding assay, which showed that the circulating FRα is functional. Importantly, we also found that the levels of FRα were comparable between early and advanced stage patients.

Conclusions

Our results demonstrate that ovarian cancer patients have elevated levels of functional intact FRα. These findings support the potential use of circulating FRα as a biomarker of early ovarian cancer.     

Met Kinetic Signature Derived from the Response to HGF/SF in a Cellular Model Predicts Breast Cancer Patient Survival

To determine the signaling pathways leading from Met activation to metastasis and poor prognosis, we measured the kinetic gene alterations in breast cancer cell lines in response to HGF/SF. Using a network inference tool we analyzed the putative protein-protein interaction pathways leading from Met to these genes and studied their specificity to Met and prognostic potential. We identified a Met kinetic signature consisting of 131 genes. The signature correlates with Met activation and with response to anti-Met therapy (p<0.005) in in-vitro models. It also identifies breast cancer patients who are at high risk to develop an aggressive disease in six large published breast cancer patient cohorts (p<0.01, N>1000). Moreover, we have identified novel putative Met pathways, which correlate with Met activity and patient prognosis. This signature may facilitate personalized therapy by identifying patients who will respond to anti-Met therapy. Moreover, this novel approach may be applied for other tyrosine kinases and other malignancies.