Gary S. Leiserowitz

The development of retrosynthetic glycan libraries to profile and classify the human serum N-linked glycome.

Annotation of the human serum N‐linked glycome is a formidable challenge but is necessary for disease marker discovery. A new theoretical glycan library was constructed and proposed to provide all possible glycan compositions in serum. It was developed based on established glycobiology and retrosynthetic state‐transition networks. We find that at least 331 compositions are possible in the serum N‐linked glycome. By pairing the theoretical glycan mass library with a high mass accuracy and high‐resolution MS, human serum glycans were effectively profiled. Correct isotopic envelope deconvolution to monoisotopic masses and the high mass accuracy instruments drastically reduced the amount of false composition assignments. The high throughput capacity enabled by this library permitted the rapid glycan profiling of large control populations. With the use of the library, a human serum glycan mass profile was developed from 46 healthy individuals. This paper presents a theoretical N‐linked glycan mass library that was used for accurate high‐throughput human serum glycan profiling. Rapid methods for evaluating a patients glycome are instrumental for studying glycan‐based markers.

Ovarian cancer in younger vs older women: a population-based analysis

To compare the clinico-pathologic prognostic factors and survival of younger vs older women diagnosed with epithelial ovarian cancer. Demographic, clinico-pathologic, treatment, and surgery information were obtained from patients with ovarian cancer from the Surveillance, Epidemiology, and End Results Program from 1988 to 2001 and analysed using Kaplan–Meier estimates. Of 28 165 patients, 400 were <30 years (very young), 11 601 were 30–60 (young), and 16 164 were >60 (older) years of age. Of the very young, young, and older patients, 261 (65.3%), 4664 (40.2%), and 3643 (22.5%) had stage I–II disease, respectively (P<0.001). Across all stages, very young women had a significant survival advantage over the young and older groups with 5-year disease-specific survival estimates at 78.8% vs 58.8 and 35.3%, respectively (P<0.001). This survival difference between the age groups persists even after adjusting for race, stage, grade, and surgical treatment. Reproductive age (16–40 years) women with stage I–II epithelial ovarian cancer who received uterine-sparing procedures had similar survivals compared to those who underwent standard surgery (93.3% vs 91.5%, P=0.26). Younger women with epithelial ovarian cancer have a survival advantage compared to older patients.

Influence of the gynecologic oncologist on the survival of ovarian cancer patients

OBJECTIVE: To estimate the influence of gynecologic oncologists on the treatment and outcome of patients with ovarian cancer. METHODS: Data were obtained from California Cancer Registry from 1994 to 1996. Kaplan-Meier and Cox proportional hazard methods were used for analyses. RESULTS: Of 1,491 patients, the median age was 65 years (range: 13–100). Only 34.1% received care by gynecologic oncologists (group A) while 65.9% were treated by others (group B). Women in group A were more affluent (P<.001), were more educated (P=.036), were classified as white-collar employees (P=.128), and lived in urban regions (P<.001) compared with group B. Patients who saw gynecologic oncologists were more likely to have surgery as their initial treatment (91.9% versus 69.1%; P<.001), present with advanced (stage III-IV) cancers (78.2% versus 70.5%; P<.001), have more grade 3 tumors (61.7% versus 39.9%; P=.048), and receive chemotherapy (90.0% versus 70.1%; P<.001). Women in group B had a fourfold higher risk of having unstaged cancers (8.0% versus 2.1%; P<.001). The 5-year disease-specific survival of group A patients was 38.6% compared with 30.3% in group B (P<.001). On multivariable analysis, early stage, lower grade, and treatment by gynecologic oncologists were independent prognostic factors for improved survival. After adjusting for surgery and chemotherapy, there was no improvement in survival associated with care by gynecologic oncologists (hazard ratio=0.90, 95% confidence interval 0.78–1.03; P=.133). CONCLUSION: In this study of 1,491 women, those who were treated by gynecologic oncologists were more likely to undergo primary staging surgery and receive chemotherapy. Stage, grade of disease, and treatment by gynecologic oncologists were important prognosticators. LEVEL OF EVIDENCE: II

Glycomics analysis of serum: a potential new biomarker for ovarian cancer?

We recently reported the use of matrix-assisted laser desorption ionization (MALDI) Fourier transformation mass spectrometry (FTMS) techniques to identify unique glycan markers in ovarian cancer cell lines which may be biomarkers for diagnosis of ovarian cancer. Glycan markers and CA125 levels are compared in a series of ovarian cancer patients and normal control subjects. Oligosaccharides (OS) were cleaved from the serum glycoproteins and isolated using solid phase extraction. MALDI–FTMS was then used to identify unique mass spectrometry (MS) peaks. Sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve were calculated to measure the test performance of glycan markers. Sixteen unique OS MS signals were identified in ovarian cancer patient sera. Their additive mass/charge intensities were used to determine their presence or absence. The ovarian cancer patients varied in their disease status, with initial cancer stages ranging from IC to IV. Forty-four of 48 patients had detectable OS signals, with CA125 values between 2 and 17,044. Four patients had undetectable signals and their CA125 ranged between 7 and 10. Twenty-three of 24 control subjects had no detectable glycan markers, with CA125 levels between 10 and 64. Sensitivity and specificity values were determined to be 91.6% and 95.8%, respectively. The area under the ROC curve for all 72 samples was 0.954 (95% CI: 0.896, 1.0) using the glycomics assay, which was superior to CA125 in discriminating between cases and controls. This preliminary study suggests that glycomics profiling may be useful for the detection of ovarian cancer

Patterns of Chemotherapy Use for Women With Ovarian Cancer: A Population-Based Study

PURPOSE To evaluate adherence to published recommendations for chemotherapy for ovarian cancer patients in the general community and to identify factors associated with its use. PATIENTS AND METHODS The study population consisted of 2,150 women residing in Northern California with a first diagnosis of primary epithelial ovarian cancer between January 1994 and December 1996. Patients were identified through the California Cancer Registry and their physicians were surveyed to supplement registry treatment information. RESULTS Almost 89% of women younger than 75 years with International Federation of Gynecology and Obstetrics stage III or IV tumors received chemotherapy, with levels of treatment highest for women diagnosed at stage III. Patients 75 years of age and older were significantly less likely than younger women to receive chemotherapy (58.2% v 86.1%; P =.001) regardless of stage at diagnosis. Approximately 20% of patients younger than 55 years with early-stage (stage IC and II) cancer received no chemotherapy. Treatment in an American College of Surgeons hospital and treatment by a gynecologic oncologist increased the likelihood of receiving chemotherapy. Hospitalization for comorbid illness, race/ethnicity, census-based measures of socioeconomic status, and size or teaching status of hospital were all unrelated to probability of treatment after adjustment for other factors. Reasons reported most frequently by physicians for no treatment were lack of clinical indication and patient refusal. CONCLUSION The results of this study suggest that, despite scientific evidence and published guidelines that advocate chemotherapy for most women with ovarian cancer, some groups of women did not receive optimum treatment.

Human Serum Processing and Analysis Methods for Rapid and Reproducible N-Glycan Mass Profiling

Glycans constitute a new class of compounds for biomarker discovery. Glycosylation is a common post-translational modification and is often associated with transformation to malignancy. To analyze glycans, they are released from proteins, enriched, and measured with mass spectrometry. For biomarker discovery, repeatability at every step of the process is important. Locating and minimizing the process variability is key to establishing a robust platform stable enough for biomarker discovery. Understanding the variability of the measurement devices helps understand the variability associated with the chemical processing. This report explores the potential use of methods expediting the enzymatic release of glycans such as a microwave reactor and automation of the solid-phase extraction with a robotic liquid handler. The study employs matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry but would be suitable with any mass spectrometry method. Methods for system-wide data analysis are examined because proper metrics for evaluating the performance of glycan sample preparation procedures are not well established.

Isomer-specific chromatographic profiling yields highly sensitive and specific potential N-glycan biomarkers for epithelial ovarian cancer

Aberrant glycosylation has been observed for decades in essentially all types of cancer, and is now well established as an indicator of carcinogenesis. Mining the glycome for biomarkers, however, requires analytical methods that can rapidly separate, identify, and quantify isomeric glycans. We have developed a rapid-throughput method for chromatographic glycan profiling using microfluidic chip-based nanoflow liquid chromatography (nano-LC)/mass spectrometry. To demonstrate the utility of this method, we analyzed and compared serum samples from epithelial ovarian cancer cases (n=46) and healthy control individuals (n=48). Over 250 N-linked glycan compound peaks with over 100 distinct N-linked glycan compositions were identified. Statistical testing identified 26 potential glycan biomarkers based on both compositional and structure-specific analyses. Using these results, an optimized model was created incorporating the combined abundances of seven potential glycan biomarkers. The receiver operating characteristic (ROC) curve of this optimized model had an area under the curve (AUC) of 0.96, indicating robust discrimination between cancer cases and healthy controls. Rapid-throughput chromatographic glycan profiling was found to be an effective platform for structure-specific biomarker discovery.

The Glycolyzer: Automated Glycan Annotation Software for High Performance Mass Spectrometry and Its Application to Ovarian Cancer Glycan Biomarker Discovery

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked, and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.

Characteristics of Long-Term Survivors of Epithelial Ovarian Cancer

OBJECTIVE: To identify characteristics associated with long-term survival for patients with epithelial ovarian cancer using the California Cancer Registry. METHODS: A descriptive analysis of survival of all California residents diagnosed with epithelial ovarian cancer between 1994 and 2001 was conducted using patients identified through the cancer registry with follow-up through 2011. Characteristics of the patients who survived more than 10 years (long-term survivors) were compared with three other cohorts: patients who survived less than 2 years, those who survived at least 2 but no more than 5 years, and those who survived at least 5 but no more than 10 years. RESULTS: A total of 3,582 out of 11,541 (31%, confidence interval 30.2–31.8%) of the patients survived more than 10 years. Younger age, early stage, low-grade, and nonserous histology were significant predictors of long-term survival, but long-term survivors also included women with high-risk cancer. CONCLUSION: Long-term survival is not unusual in patients with epithelial ovarian cancer, even in those with high-risk disease. Many of the prognostic factors are well known, but it remains to be determined why some patients with advanced-stage high-grade cancers survive longer than others with the same histology. These findings are important for patient counseling. LEVEL OF EVIDENCE: III

Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data

MOTIVATION The development of better tests to detect cancer in its earliest stages is one of the most sought-after goals in medicine. Especially important are minimally invasive tests that require only blood or urine samples. By profiling oligosaccharides cleaved from glycosylated proteins shed by tumor cells into the blood stream, we hope to determine glycan profiles that will help identify cancer patients using a simple blood test. The data in this article were generated using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI FT-ICR MS). We have developed novel methods for analyzing this type of mass spectrometry data and applied it to eight datasets from three different types of cancer (breast, ovarian and prostate). RESULTS The techniques we have developed appear to be effective in the analysis of MALDI FT-ICR MS data. We found significant differences between control and cancer groups in all eight datasets, including two structurally related compounds that were found to be significantly different between control and cancer groups in all three types of cancer studied.