Yingye Zheng

A multicenter, double-blinded validation study of methylation biomarkers for progression prediction in Barrett’s esophagus

Esophageal adenocarcinoma risk in Barretts esophagus (BE) is increased 30- to 125-fold versus the general population. Among all BE patients, however, neoplastic progression occurs only once per 200 patient-years. Molecular biomarkers are therefore needed to risk-stratify patients for more efficient surveillance endoscopy and to improve the early detection of progression. We therefore performed a retrospective, multicenter, double-blinded validation study of eight BE progression prediction methylation biomarkers. Progression or nonprogression were determined at 2 years (tier 1) and 4 years (tier 2). Methylation was assayed in 145 nonprogressors and 50 progressors using real-time quantitative methylation-specific PCR. Progressors were significantly older than nonprogressors (70.6 versus 62.5 years; P < 0.001). We evaluated a linear combination of the eight markers, using coefficients from a multivariate logistic regression analysis. Areas under the ROC curve (AUC) were high in the 2-year, 4-year, and combined data models (0.843, 0.829, and 0.840; P < 0.001, <0.001, and <0.001, respectively). In addition, even after rigorous overfitting correction, the incremental AUCs contributed by panels based on the 8 markers plus age versus age alone were substantial (Delta-AUC = 0.152, 0.114, and 0.118, respectively) in all 3 models. A methylation biomarker-based panel to predict neoplastic progression in BE has potential clinical value in improving both the efficiency of surveillance endoscopy and the early detection of neoplasia.

Estrogen plus progestin use, microsatellite instability, and the risk of colorectal cancer in women

Current users of postmenopausal hormones (PMH) have approximately 30% to 40% lower risk of colorectal cancer (CRC), although associations with specific types of hormones have been inconsistent. Further, it is not clear whether some tumor types have a different risk. We conducted a case-control study to examine the relationship between PMH and CRC. Cases (n = 1,004), ages 50 to 74 years, were identified from the Surveillance Epidemiology and End Results registry in Washington from 1998 to 2002; controls (n = 1,062) were randomly selected from population lists. Case tissue samples were obtained for microsatellite instability (MSI) analyses. Interviews collected risk-factor data for CRC, including detailed information on PMH. Multivariable logistic regression models estimated odds ratios (OR) and 95% confidence intervals (95% CI). Current use of any PMH was associated with a 20% reduction in CRC risk (95% CI 0.6-0.9). This reduction in risk was limited to women who had taken estrogen plus progestin (EP) preparations only (OR = 0.6, 95% CI 0.5-0.9); there was no association with estrogen-only (E alone) use (OR = 0.9, 95% CI 0.7-1.1). For women with MSI-low or MSI-stable tumors, there was a statistically significant 40% reduction in CRC risk associated with EP use (95% CI 0.4-0.9); there was no clear association with MSI-high tumors. EP use was associated with a decreased risk of CRC; however, there seemed to be no association with E alone data that are consistent with the recent Womens Health Initiative findings. Progestin may enhance the estrogenic effect of conjugated estrogen so the combination may be more biologically active in the colon than E alone.

Integrated Proteomic Profiling of Cell Line Conditioned Media and Pancreatic Juice for the Identification of Pancreatic Cancer Biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.

Prediction of ovarian cancer prognosis and response to chemotherapy by a serum-based multiparametric biomarker panel

Currently, there are no effective biomarkers for ovarian cancer prognosis or prediction of therapeutic response. The objective of this study was to examine a panel of 10 serum biochemical parameters for their ability to predict response to chemotherapy, progression and survival of ovarian cancer patients. Sera from ovarian cancer patients were collected prior and during chemotherapy and were analysed by enzyme-linked immunosorbent assay for CA125, kallikreins 5, 6, 7, 8, 10 and 11, B7-H4, regenerating protein IV and Spondin-2. The odds ratio and hazard ratio and their 95% confidence interval (95% CI) were calculated. Time-dependent receiver-operating characteristic (ROC) curves were utilised to evaluate the prognostic performance of the biomarkers. The levels of several markers at baseline (c0), or after the first chemotherapy cycle (rc1), predicted chemotherapy response and overall or progression-free survival in univariate analysis. A multiparametric model (c0 of CA125, KLK5, KLK7 and rc1 of CA125) provided predictive accuracy with area under the ROC curve (AUC) of 0.82 (0.62 after correction for overfitting). Another marker combination (c0 of KLK7, KLK10, B7-H4, Spondin-2) was useful in predicting short-term (1-year) survival with an AUC of 0.89 (0.74 after correction for overfitting). All markers examined, except KLK7 and regenerating protein IV, were powerful predictors of time to progression (TTP) among chemotherapy responders. Individual and panels of biomarkers from the kallikrein family (and other families) can predict response to chemotherapy, overall survival, short-term (1-year) survival, progression-free survival and TTP of ovarian cancer patients treated with chemotherapy.

DNA Methylation Profiles of Lymphoid and Hematopoietic Malignancies

Purpose: Aberrant methylation of the 5′ gene promoter regions is an epigenetic phenomenon that is the major mechanism for silencing of tumor suppressor genes in many cancer types. The aims of our study were (a) to compare the methylation profiles of the major forms of hematological malignancies and (b) to determine the methylation profile of monoclonal gammopathy of undetermined significance (MGUS) and compare it with that of multiple myeloma (MM). Experimental Design: We compared the aberrant promoter methylation profile of 14 known or suspected tumor suppressor genes in leukemias (n = 48), lymphomas (n = 42), and MMs (n = 40). We also examined the methylation profile of MGUS (n = 20), a premalignant plasma cell dyscrasia. The genes studied represent five of the six “hallmarks of cancer.” Results: Peripheral blood lymphocytes (n = 14) from healthy volunteers were negative for methylation of all genes, and methylation percentages in 41 nonmalignant tissues (peripheral blood mononuclear cells, bone marrows, and lymph nodes) from hematological patients were low (0–9%) for all 14 genes, confirming that methylation was tumor specific. Ten of the genes were methylated at frequencies of 29–68% in one or more tumor types, and the methylation indices (an indicator of overall methylation) varied from 0.25 to 0.34. With two exceptions, the methylation patterns of leukemias and lymphomas were similar. However, the pattern of MMs varied from the other tumor types for six genes. In general, the methylation pattern of MGUS was similar to that of MM, although the methylation frequencies were lower (the methylation index of MGUS was 0.15, and that of MM was 0.3). However, the methylation frequencies of six genes were significantly higher in MGUS than in control tissues. The relatively high frequencies of methylation in MGUS are consistent with it being a premalignant condition. Conclusions: The three major forms of lymphoid/hematopoietic malignancies show overlapping but individual patterns of methylation.

Presence of Simian Virus 40 DNA Sequences in Human Lymphoid and Hematopoietic Malignancies and Their Relationship to Aberrant Promoter Methylation of Multiple Genes

The simian polyoma virus SV40 has been detected in specific human tumors including non-Hodgkin’s lymphomas, although a causative role for the virus has not been convincingly demonstrated. Aberrant methylation of CpG islands in promoter regions is a frequent method of silencing tumor suppressor genes (TSGs) in cancers and may be induced by oncogenic viruses. We investigated the relationship between the presence of SV40 or EBV DNA sequences and the methylation profiles for 10 TSGs in 90 cases of non-Hodgkin’s lymphomas/leukemias and 56 control tissues. SV40 sequences were present in 33/90 (37%) non-Hodgkin’s lymphomas/leukemias, and EBV was present in 11/42 (26%) of non-Hodgkin’s lymphomas. We found a highly significant correlation between the presence of SV40 and methylation of seven genes (P values, 0.006 to <0.0001). In lymphomas, there was no relationship between EBV and methylation. Oncogenic viruses and methylation were rarely present in control tissues. We investigated methylation of the same 10 TSGs in peripheral blood mononuclear cells (PBMC) from a healthy volunteer infected with EBV or EBV and SV40. Promoter methylation of CDH1 and CDH13 were noted in dual SV40- and EBV-infected PBMC, and these two genes were also highly significantly correlated to the presence of SV40 sequences in tumors. SV40 infection also resulted in appearance of the lymphoma/leukemia-specific marker, methylated SHP1. Methylation was completely absent in uninfected and EBV-infected PBMC. Our results demonstrate that the presence of SV40 in hematological malignancies is associated with promoter methylation of TSGs and that in all probability, the virus plays a role in tumor pathogenesis.

Plasma Choline Metabolites and Colorectal Cancer Risk in the Women's Health Initiative Observational Study

Few studies have examined associations between plasma choline metabolites and risk of colorectal cancer. Therefore, we investigated associations between plasma biomarkers of choline metabolism [choline, betaine, dimethylglycine, and trimethylamine N-oxide (TMAO)] and colorectal cancer risk among postmenopausal women in a case-control study nested within the Womens Health Initiative Observational Study. We selected 835 matched case-control pairs, and cases were further stratified by tumor site (proximal, distal, or rectal) and stage (local/regional or metastatic). Colorectal cancer was assessed by self-report and confirmed by medical records over the mean of 5.2 years of follow-up. Baseline plasma choline metabolites were measured by LC/MS-MS. In multivariable-adjusted conditional logistic regression models, plasma choline tended to be positively associated with rectal cancer risk [OR (95% confidence interval, CI)(highest vs. lowest quartile) = 2.44 (0.93-6.40); P trend = 0.08], whereas plasma betaine was inversely associated with colorectal cancer overall [0.68 (0.47-0.99); P trend = 0.01] and with local/regional tumors [0.64 (0.42-0.99); P trend = 0.009]. Notably, the plasma betaine:choline ratio was inversely associated with colorectal cancer overall [0.56 (0.39-0.82); P trend = 0.004] as well as with proximal [0.66 (0.41-1.06); P trend = 0.049], rectal [0.27 (0.10-0.78); P trend = 0.02], and local/regional [0.50 (0.33-0.76); P trend = 0.001] tumors. Finally, plasma TMAO, an oxidative derivative of choline produced by intestinal bacteria, was positively associated with rectal cancer [3.38 (1.25-9.16); P trend = 0.02] and with overall colorectal cancer risk among women with lower (vs. higher) plasma vitamin B12 levels (P interaction = 0.003). Collectively, these data suggest that alterations in choline metabolism, which may arise early in disease development, may be associated with higher risk of colorectal cancer. The positive association between plasma TMAO and colorectal cancer risk is consistent with an involvement of the gut microbiome in colorectal cancer pathogenesis.

Biomarkers of inflammation are associated with colorectal cancer risk in women but are not suitable as early detection markers.

Initial studies have investigated the association between inflammation and colorectal cancer (CRC) using C‐reactive protein (CRP) as a proinflammatory biomarker and have noted inconsistent results among women. We here report the findings from a large prospective study with repeat measurements of CRP, as well as serum amyloid A (SAA), an additional biomarker of inflammation, and risk of CRC. In the Womens Health Initiative Observational Study, we examined associations of CRP and SAA with CRC using repeat assessments (baseline and 3‐year follow‐up) among 953 matched case–control pairs for CRP and 966 pairs for SAA. Multivariate‐adjusted conditional‐logistic regression models were used with two‐sided tests of significance. Receiver operating characteristic (ROC) curve analysis assessed their utility as early detection markers. Colon cancer risk (odds ratio [OR] and 95% confidence intervals) among women in the highest quintiles of CRP or SAA compared to those in the lowest quintiles was ORcolon/CRP = 1.37 (0.95–1.97, p‐trend = 0.04) and ORcolon/SAA = 1.26 (0.88–1.80, p‐trend = 0.10), respectively. Women with elevated concentrations of both CRP and SAA had an increased risk of ORcolon = 1.50 (1.12–2.00, p‐value = 0.006) compared to those with low concentrations. No positive associations were observed with rectal cancer and weaker associations for CRC overall. Temporal changes in biomarkers more than 3 years did not predict risk. The area under the 6‐month ROC curve for CRP+SAA was 0.62 (95% confidence interval = 0.55–0.68). Elevated inflammatory biomarkers are associated with an increased risk of CRC, mainly colon cancer. Nevertheless, changes in the biomarkers over time do not suggest that they merit consideration as early detection markers for CRC.

A Multiparametric Panel for Ovarian Cancer Diagnosis, Prognosis, and Response to Chemotherapy

Purpose: Our goal was to examine a panel of 11 biochemical variables, measured in cytosolic extracts of ovarian tissues (normal, benign, and malignant) by quantitative ELISAs for their ability to diagnose, prognose, and predict response to chemotherapy of ovarian cancer patients. Experimental Design: Eleven proteins were measured (9 kallikreins, B7-H4, and CA125) in cytosolic extracts of 259 ovarian tumor tissues, 50 tissues from benign conditions, 35 normal tissues, and 44 tissues from nonovarian tumors that metastasized to the ovary. Odds ratios and hazard ratios and their 95% confidence interval were calculated. Time-dependent receiver operating characteristic curves for censored survival data were used to evaluate the performance of the biomarkers. Resampling was used to validate the performance. Results: Most biomarkers effectively separated cancer from noncancer groups. A composite marker provided an area under the curve of 0.97 (95% confidence interval, 0.95-0.99) for discriminating normal and cancer groups. Univariately, hK5 and hK6 were positively associated with progression. After adjusting for clinical variables in multivariate analysis, both hK10 and hK11 significantly predicted time to progression. Increasing levels of hK13 were associated with chemotherapy response, and the predictive power of hK13 to chemotherapy response was improved by a panel of five biomarkers. Conclusions: The evidence shows that a group of kallikreins and multiparametric combinations with other biomarkers and clinical variables can significantly assist with ovarian cancer classification, prognosis, and response to platinum-based chemotherapy. In particular, we developed a multiparametric strategy for predicting ovarian cancer response to chemotherapy, comprising several biomarkers and clinical features.

Activated leukocyte cell adhesion molecule: a novel biomarker for breast cancer.

Activated leukocyte cell adhesion molecule (ALCAM) has been implicated in tumorigenesis. Our goal was to examine the levels of ALCAM, in addition to the classical breast cancer tumor markers carbohydrate antigen 15‐3 (CA15‐3) and carcinoembryonic antigen (CEA), in serum by quantitative enzyme‐linked immunosorbent assay for diagnosis in breast cancer patients. The 3 proteins were measured in serum of 100 healthy women, 50 healthy men and 150 breast carcinoma patients. The diagnostic sensitivity and specificity of the tests were calculated and the association of serum marker concentrations with various clinicopathologic variables was examined using nonparametric Kruskal‐Wallis tests. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the biomarkers. ALCAM, with area under the curve (AUC) of 0.78 [95% CI: 0.73, 0.84] outperformed CA15‐3 (AUC = 0.70 [95% CI: 0.64, 0.76]) and CEA (AUC= 0.63 [95% CI: 0.56, 0.70]). The incremental values of AUC for ALCAM over that for CA15‐3 were statistically significant (Delong test, p < 0.05). Combining CA15‐3 and ALCAM yielded a ROC curve with an AUC of 0.81 (95% CI [0.75, 0.87]). Serum ALCAM appears to be a new biomarker for breast cancer and may have value for disease diagnosis.