Search Results
You are looking at 1 - 7 of 7 items for
- Author: S Ross x
- Refine by access: All content x
Search for other papers by Theodora S Ross in
Google Scholar
PubMed
Search for other papers by Igryl S Cordero-Hernandez in
Google Scholar
PubMed
Search for other papers by Alicia C Ross in
Google Scholar
PubMed
Search for other papers by Arvind Dasari in
Google Scholar
PubMed
Search for other papers by Daniel M Halperin in
Google Scholar
PubMed
Search for other papers by Beth Chasen in
Google Scholar
PubMed
Search for other papers by James C Yao in
Google Scholar
PubMed
We observed that some patients with well-differentiated neuroendocrine tumors (NET) who received peptide receptor radionuclide therapy (PRRT) with Lutetium-177 (177Lu) DOTATATE developed rapid disease progression with biopsy-proven histologic transformation to neuroendocrine carcinoma (NEC), an outcome that has not been previously described. Therefore, we conducted a retrospective review of all patients with well-differentiated G1-G2 NET who received at least one cycle of PRRT with (177Lu) DOTATATE at our center from January 2019 to December 2020. Among 152 patients, we identified 7 patients whose NET transformed to NEC. Median time from start of PRRT to transformation was 8.2 months (range: 2.6–14.4 months). All patients whose tumors underwent transformation had pancreatic tail as the primary site and had prior chemotherapy with temozolomide. No differences in the incidence of transformation were observed according to gender, race, original tumor grade, or number of prior therapies. Six patients received treatment with platinum and etoposide after transformation with two patients having partial response as best response. All patients with transformation died from progressive disease with median overall survival (OS) after transformation of 3.3 months (95% CI 2.1–4.4). Molecular testing of transformed NEC identified mutation(s) in TP53 and/or ATM in all cases. Transformation of NET to NEC following PRRT is associated with aggressive course and dismal prognosis. Patients with pancreatic tail as the primary site who had prior therapy with temozolomide may be at a higher risk. Further investigation is necessary to determine the best treatment sequence in this patient population.
Search for other papers by T P Conrads in
Google Scholar
PubMed
Search for other papers by V A Fusaro in
Google Scholar
PubMed
Search for other papers by S Ross in
Google Scholar
PubMed
Search for other papers by D Johann in
Google Scholar
PubMed
Search for other papers by V Rajapakse in
Google Scholar
PubMed
Search for other papers by B A Hitt in
Google Scholar
PubMed
Search for other papers by S M Steinberg in
Google Scholar
PubMed
Search for other papers by E C Kohn in
Google Scholar
PubMed
Search for other papers by D A Fishman in
Google Scholar
PubMed
Search for other papers by G Whitely in
Google Scholar
PubMed
Search for other papers by J C Barrett in
Google Scholar
PubMed
Search for other papers by L A Liotta in
Google Scholar
PubMed
Search for other papers by E F Petricoin 3rd in
Google Scholar
PubMed
Search for other papers by T D Veenstra in
Google Scholar
PubMed
Serum proteomic pattern diagnostics is an emerging paradigm employing low-resolution mass spectrometry (MS) to generate a set of biomarker classifiers. In the present study, we utilized a well-controlled ovarian cancer serum study set to compare the sensitivity and specificity of serum proteomic diagnostic patterns acquired using a high-resolution versus a low-resolution MS platform. In blinded testing sets, the high-resolution mass spectral data contained multiple diagnostic signatures that were superior to the low-resolution spectra in terms of sensitivity and specificity (P<0.00001) throughout the range of modeling conditions. Four mass spectral feature set patterns acquired from data obtained exclusively with the high-resolution mass spectrometer were 100% specific and sensitive in their diagnosis of serum samples as being acquired from either unaffected patients or those suffering from ovarian cancer. Important to the future of proteomic pattern diagnostics is the ability to recognize inferior spectra statistically, so that those resulting from a specific process error are recognized prior to their potentially incorrect (and damaging) diagnosis. To meet this need, we have developed a series of quality-assurance and in-process control procedures to (a) globally evaluate sources of sample variability, (b) identify outlying mass spectra, and (c) develop quality-control release specifications. From these quality-assurance and control (QA/QC) specifications, we identified 32 mass spectra out of the total 248 that showed statistically significant differences from the norm. Hence, 216 of the initial 248 high-resolution mass spectra were determined to be of high quality and were remodeled by pattern-recognition analysis. Again, we obtained four mass spectral feature set patterns that also exhibited 100% sensitivity and specificity in blinded validation tests (68/68 cancer: including 18/18 stage I, and 43/43 healthy). We conclude that (a) the use of high-resolution MS yields superior classification patterns as compared with those obtained with lower resolution instrumentation; (b) although the process error that we discovered did not have a deleterious impact on the present results obtained from proteomic pattern analysis, the major source of spectral variability emanated from mass spectral acquisition, and not bias at the clinical collection site; (c) this variability can be reduced and monitored through the use of QA/QC statistical procedures; (d) multiple and distinct proteomic patterns, comprising low molecular weight biomarkers, detected by high-resolution MS achieve accuracies surpassing individual biomarkers, warranting validation in a large clinical study.
Search for other papers by W F Symmans in
Google Scholar
PubMed
Search for other papers by D J Fiterman in
Google Scholar
PubMed
Search for other papers by S K Anderson in
Google Scholar
PubMed
Search for other papers by M Ayers in
Google Scholar
PubMed
Search for other papers by R Rouzier in
Google Scholar
PubMed
Search for other papers by V Dunmire in
Google Scholar
PubMed
Search for other papers by J Stec in
Google Scholar
PubMed
Search for other papers by V Valero in
Google Scholar
PubMed
Search for other papers by N Sneige in
Google Scholar
PubMed
Search for other papers by C Albarracin in
Google Scholar
PubMed
Search for other papers by Y Wu in
Google Scholar
PubMed
Search for other papers by J S Ross in
Google Scholar
PubMed
Search for other papers by P Wagner in
Google Scholar
PubMed
Search for other papers by R L Theriault in
Google Scholar
PubMed
Search for other papers by B Arun in
Google Scholar
PubMed
Search for other papers by H Kuerer in
Google Scholar
PubMed
Search for other papers by K R Hess in
Google Scholar
PubMed
Search for other papers by W Zhang in
Google Scholar
PubMed
Search for other papers by G N Hortobagyi in
Google Scholar
PubMed
Search for other papers by L Pusztai in
Google Scholar
PubMed
The pathogenesis of breast cancers that do not express estrogen receptors or Her-2/neu receptors (ER−/HER2− phenotype) is incompletely understood. We had observed markedly elevated gene expression of gamma-aminobutyric acid type A (GABAA) receptor subunit π (GABAπ, GABRP) in some breast cancers with ER−/HER2− phenotype. In this study, transcriptional profiles (TxPs) were obtained from 82 primary invasive breast cancers by oligonucleotide microarrays. Real-time reverse transcription–polymerase chain reaction (RT–PCR) was used to measure GABAπ gene expression in a separate cohort of 121 invasive breast cancers. GABAπ gene expression values from TxP and RT–PCR were standardized and compared with clinicopathologic characteristics in the 203 patients. GABAπ gene expression was increased in 16% of breast cancers (13/82 TxP, 20/ 121 RT–PCR), particularly in breast cancers with ER−/HER2− phenotype (60%), and breast cancers with basal-like genomic profile (60%). The profile of genes coexpressed with GABAπ in these tumors was consistent with an immature cell type. In multivariate linear regression analysis, the level of GABAπ gene expression was associated with ER−/HER2− phenotype (P<0.0001), younger age at diagnosis (P=0.0003), and shorter lifetime duration of breastfeeding (≤ 6 months) in all women (P=0.017) and specifically in parous women (P=0.013). GABAπ gene expression was also associated with combinations of high grade with ER−/HER2− phenotype (P=0.002), and with Hispanic ethnicity (P=0.036). GABAπ gene expression is increased in breast cancers of immature (undifferentiated) cell type and is significantly associated with shorter lifetime history of breastfeeding and with high-grade breast cancer in Hispanic women.
Division of Biomedical Informatics & Personalized Medicine, Department of Medicine, University of Colorado School of Medicine at Colorado Anschutz Medical Campus Aurora, Aurora, Colorado, USA
Search for other papers by Nikita Pozdeyev in
Google Scholar
PubMed
Division of Biomedical Informatics & Personalized Medicine, Department of Medicine, University of Colorado School of Medicine at Colorado Anschutz Medical Campus Aurora, Aurora, Colorado, USA
Search for other papers by Lauren Fishbein in
Google Scholar
PubMed
Search for other papers by Laurie M Gay in
Google Scholar
PubMed
Search for other papers by Ethan S Sokol in
Google Scholar
PubMed
Search for other papers by Ryan Hartmaier in
Google Scholar
PubMed
Departments of Pathology and Urology, Upstate Medical University, Syracuse, New York, USA
Search for other papers by Jeffrey S Ross in
Google Scholar
PubMed
Search for other papers by Sourat Darabi in
Google Scholar
PubMed
Translational Genomics Research Institute, Phoenix, Arizona, USA
Search for other papers by Michael J Demeure in
Google Scholar
PubMed
Search for other papers by Adwitiya Kar in
Google Scholar
PubMed
Search for other papers by Lindsey J Foust in
Google Scholar
PubMed
Search for other papers by Katrina Koc in
Google Scholar
PubMed
Search for other papers by Daniel W Bowles in
Google Scholar
PubMed
Search for other papers by Stephen Leong in
Google Scholar
PubMed
Research Service Veterans Affairs Medical Center, Aurora, Colorado, USA
Search for other papers by Margaret E Wierman in
Google Scholar
PubMed
Research Service Veterans Affairs Medical Center, Aurora, Colorado, USA
Search for other papers by Katja Kiseljak-Vassiliades in
Google Scholar
PubMed
Despite recent advances in elucidating molecular pathways underlying adrenocortical carcinoma (ACC), this orphan malignancy is associated with poor survival. Identification of targetable genomic alterations is critical to improve outcomes. The objective of this study was to characterize the genomic profile of a large cohort of patient ACC samples to identify actionable genomic alterations. Three hundred sixty-four individual patient ACC tumors were analyzed. The median age of the cohort was 52 years and 60.9% (n = 222) were female. ACC samples had common alterations in epigenetic pathways with 38% of tumors carrying alterations in genes involved in histone modification, 21% in telomere lengthening, and 21% in SWI/SNF complex. Tumor suppressor genes and WNT signaling pathway were each mutated in 51% of tumors. Fifty (13.7%) ACC tumors had a genomic alteration in genes involved in the DNA mismatch repair (MMR) pathway with many tumors also displaying an unusually high number of mutations and a corresponding MMR mutation signature. In addition, genomic alterations in several genes not previously associated with ACC were observed, including IL7R, LRP1B, FRS2 mutated in 6, 8 and 4% of tumors, respectively. In total, 58.5% of ACC (n = 213) had at least one potentially actionable genomic alteration in 46 different genes. As more than half of ACC have one or more potentially actionable genomic alterations, this highlights the value of targeted sequencing for this orphan cancer with a poor prognosis. In addition, significant incidence of MMR gene alterations suggests that immunotherapy is a promising therapeutic for a considerable subset of ACC patients.
Search for other papers by Charles E Massie in
Google Scholar
PubMed
Search for other papers by Inmaculada Spiteri in
Google Scholar
PubMed
Search for other papers by Helen Ross-Adams in
Google Scholar
PubMed
Search for other papers by Hayley Luxton in
Google Scholar
PubMed
Search for other papers by Jonathan Kay in
Google Scholar
PubMed
Search for other papers by Hayley C Whitaker in
Google Scholar
PubMed
Search for other papers by Mark J Dunning in
Google Scholar
PubMed
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Search for other papers by Alastair D Lamb in
Google Scholar
PubMed
Search for other papers by Antonio Ramos-Montoya in
Google Scholar
PubMed
Search for other papers by Daniel S Brewer in
Google Scholar
PubMed
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Search for other papers by Colin S Cooper in
Google Scholar
PubMed
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Search for other papers by Rosalind Eeles in
Google Scholar
PubMed
Search for other papers by UK Prostate ICGC Group in
Google Scholar
PubMed
Search for other papers by Anne Y Warren in
Google Scholar
PubMed
Search for other papers by Simon Tavaré in
Google Scholar
PubMed
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Cancer Research UK Cambridge Institute, Division of Genetics and Epidemiology, Department of Biological Sciences and School of Medicine, Royal Marsden NHS Foundation Trust, Departments of Pathology, Urology, Surgical Oncology, University of Cambridge, Cambridge, CB2 0RE, UK
Search for other papers by David E Neal in
Google Scholar
PubMed
Search for other papers by Andy G Lynch in
Google Scholar
PubMed
Prostate cancer is the most common cancer in men, resulting in over 10 000 deaths/year in the UK. Sequencing and copy number analysis of primary tumours has revealed heterogeneity within tumours and an absence of recurrent founder mutations, consistent with non-genetic disease initiating events. Using methylation profiling in a series of multi-focal prostate tumours, we identify promoter methylation of the transcription factor HES5 as an early event in prostate tumourigenesis. We confirm that this epigenetic alteration occurs in 86–97% of cases in two independent prostate cancer cohorts (n=49 and n=39 tumour–normal pairs). Treatment of prostate cancer cells with the demethylating agent 5-aza-2′-deoxycytidine increased HES5 expression and downregulated its transcriptional target HES6, consistent with functional silencing of the HES5 gene in prostate cancer. Finally, we identify and test a transcriptional module involving the AR, ERG, HES1 and HES6 and propose a model for the impact of HES5 silencing on tumourigenesis as a starting point for future functional studies.
Search for other papers by F M Brouwers in
Google Scholar
PubMed
Search for other papers by E F Petricoin III in
Google Scholar
PubMed
Search for other papers by L Ksinantova in
Google Scholar
PubMed
Search for other papers by J Breza in
Google Scholar
PubMed
Search for other papers by V Rajapakse in
Google Scholar
PubMed
Search for other papers by S Ross in
Google Scholar
PubMed
Search for other papers by D Johann in
Google Scholar
PubMed
Search for other papers by M Mannelli in
Google Scholar
PubMed
Search for other papers by B L Shulkin in
Google Scholar
PubMed
Search for other papers by R Kvetnansky in
Google Scholar
PubMed
Search for other papers by G Eisenhofer in
Google Scholar
PubMed
Search for other papers by M M Walther in
Google Scholar
PubMed
Search for other papers by B A Hitt in
Google Scholar
PubMed
Search for other papers by T P Conrads in
Google Scholar
PubMed
Search for other papers by T D Veenstra in
Google Scholar
PubMed
Search for other papers by D P Mannion in
Google Scholar
PubMed
Search for other papers by M R Wall in
Google Scholar
PubMed
Search for other papers by G M Wolfe in
Google Scholar
PubMed
Search for other papers by V A Fusaro in
Google Scholar
PubMed
Search for other papers by L A Liotta in
Google Scholar
PubMed
Search for other papers by K Pacak in
Google Scholar
PubMed
Metastatic lesions occur in up to 36% of patients with pheochromocytoma. Currently there is no way to reliably detect or predict which patients are at risk for metastatic pheochromocytoma. Thus, the discovery of biomarkers that could distinguish patients with benign disease from those with metastatic disease would be of great clinical value. Using surface-enhanced laser desorption ionization protein chips combined with high-resolution mass spectrometry, we tested the hypothesis that pheochromocytoma pathologic states can be reflected as biomarker information within the low molecular weight (LMW) region of the serum proteome. LMW protein profiles were generated from the serum of 67 pheochromocytoma patients from four institutions and analyzed by two different bioinformatics approaches employing pattern recognition algorithms to determine if the LMW component of the circulatory proteome contains potentially useful discriminatory information. Both approaches were able to identify combinations of LMW molecules which could distinguish all metastatic from all benign pheochromocytomas in a separate blinded validation set.
In conclusion, for this study set low molecular mass biomarker information correlated with pheochromocytoma pathologic state using blinded validation. If confirmed in larger validation studies, efforts to identify the underlying diagnostic molecules by sequencing would be warranted. In the future, measurement of these biomarkers could be potentially used to improve the ability to identify patients with metastatic disease.
