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  • 1
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 35, No. 6_suppl ( 2017-02-20), p. 30-30
    Abstract: 30 Background: Endorectal(er) MRI is an emerging tool in assessing intraprostatic tumors. Immunotherapy development in prostate cancer has been limited due to the lack of intermediate (bio)markers of response. Methods: Untreatedpts with high-risk prostate cancer were randomized in a trial (NCT01496131) of standard ADT+Radiation + an immunotherapy targeting MUC1 (tecemotide, aka L-BLP25). Pts had erMRI at baseline and after 2 months of ADT+/- biweekly immunotherapy. Low dose (300 mg/m 2 , maximum 600 mg) cyclophosphamide for regulatory T-cell depletion preceded first immunotherapy. Multiparametric MRI included evaluation of apparent diffusion coefficient (ADC) maps from diffusion-weighted MRI. Monthly peripheral blood assessments utilized flow cytometry to evaluate immune cell subsets. This analysis focuses on the 2 month neoadjuvant period of ADT+/-immunotherapy before radiation. Results: 28 pts (n = 14/arm) with high risk prostate cancer (Gleason 8-10, PSA 〉 20, or stage T3) were enrolled. PSA declined in all pts 2 months after ADT. erMRI findings at 2 months indicated greater improvements in ADC values in pts receiving immunotherapy+ADT vs. ADT alone. Improved ADC on MRI suggests improvements in intratumoral diffusion and has been associated with decreased tumor density. This relative improvement between the groups occurred both per patient (p = 0.16) and per lesion (p = 0.031). Relative to baseline, pts receiving immunotherapy+ADT had increases in CTLA4 + CD8 + T-cells consistent with immune activation (p = 0.0134) and decreases in myeloid derived suppressor cells (MDSCs; p = 0.0353) during the neoadjuvant period corresponding to the erMRI changes. These immune findings were not seen in the ADT alone group. Conclusions: Pts who received immunotherapy+ADT for 2 months had greater improvements in ADC values on erMRI, consistent with decreased tumor density, relative to pts receiving ADT alone. Corresponding increases in activated CD8 + T-cells and decreases in MDSCs were seen in pts receiving vaccine+ADT. These preliminary findings suggest that ADC on MRI may be useful in assessing immunologic impact. Further study is warranted. Clinical trial information: NCT01496131.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2017
    detail.hit.zdb_id: 2005181-5
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  • 2
    In: International Journal of Radiation Oncology*Biology*Physics, Elsevier BV, Vol. 92, No. 5 ( 2015-08), p. 986-992
    Type of Medium: Online Resource
    ISSN: 0360-3016
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 1500486-7
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  • 3
    Online Resource
    Online Resource
    Elsevier BV ; 2023
    In:  International Journal of Radiation Oncology*Biology*Physics Vol. 117, No. 3 ( 2023-11), p. 551-553
    In: International Journal of Radiation Oncology*Biology*Physics, Elsevier BV, Vol. 117, No. 3 ( 2023-11), p. 551-553
    Type of Medium: Online Resource
    ISSN: 0360-3016
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1500486-7
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  • 4
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 16, No. suppl_5 ( 2014-11-01), p. v15-v16
    Type of Medium: Online Resource
    ISSN: 1523-5866 , 1522-8517
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2014
    detail.hit.zdb_id: 2094060-9
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  • 5
    In: Biomarker Research, Springer Science and Business Media LLC, Vol. 1, No. 1 ( 2013-12)
    Abstract: Glioblastoma Multiforme (GBM) is the most common primary malignant tumor of the central nervous system. Standard of care includes maximal resection followed by chemoradiotherapy. Tumors need adequate perfusion and neovascularization to maintain oxygenation and for removal of wastes. Vascular endothelial growth factor (VEGF) is a well characterized pro-angiogenic factor. We hypothesized that the increases in urinary VEGF levels would occur early in the course of tumor recurrence or progression. We examine the feasibility of collecting and analyzing urinary VEGF levels in a prospective, multi-institutional trial (Radiation Therapy Oncology Group, RTOG, 0611) as well as the role of VEGF as a marker of tumor recurrence. Method We evaluated VEGF levels in urine specimens collected post-operatively, at the conclusion of radiation therapy (RT) and one month following RT. Urinary VEGF levels were correlated with tumor progression at one year. VEGF levels were measured by enzyme-linked immunosorbant assay in urine specimens and normalized to urinary creatinine levels. Sample size was determined based on a 50% 1-year recurrence rate. With a sensitivity and specificity of 80%, the expected 95% confidence interval was (0.69, 0.91) with 100 patients. A failure was defined as documented disease progression, recurrence or death before one year. Results 202 patients were enrolled between February-2006 and October-2007. Four patients were ineligible as they did not receive RT. Of the remaining 198 patients, 128 had all three samples collected. In this group, 35 patients (27.3%) did not progress, 89 (69.5%) had progression and 4 (3.1%) died without evidence of progression. Median VEGF levels at baseline were 52.9 pg/mg Cr (range 0.2- 15,034.4); on the last day of RT, 56.6 (range 0–2,377.1); and at one month follow-up, 70.0 (range 0.1-1813.2). In patients without progression at 1-year, both baseline VEGF level and end of RT VEGF level were lower than those of patients who progressed: 40.3 (range 0.2-350.8) vs. 59.7 (range 1.3-15,034.4) and 41.8 (range 0–356.8) vs. 69.7 (range 0–2,377.1), respectively. This did not reach statistical significance. Comparison of the change in VEGF levels between the end of RT and one month following RT, demonstrated no significant difference in the proportions of progressors or non-progressors at 1-year for either the VEGF increased or VEGF decreased groups. Conclusion Urine can be collected and analyzed in a prospective, multi-institutional trial. In this study of patients with GBM a change in urinary VEGF levels between the last day of RT and the one month following RT did not predict for tumor progression by one year.
    Type of Medium: Online Resource
    ISSN: 2050-7771
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2013
    detail.hit.zdb_id: 2699926-2
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  • 6
    Online Resource
    Online Resource
    SAGE Publications ; 2022
    In:  Health Informatics Journal Vol. 28, No. 4 ( 2022-10), p. 146045822211354-
    In: Health Informatics Journal, SAGE Publications, Vol. 28, No. 4 ( 2022-10), p. 146045822211354-
    Abstract: Gliomas are the most common central nervous system tumors exhibiting poor clinical outcomes. The ability to estimate prognosis is crucial for both patients and providers in order to select the most appropriate treatment. Machine learning (ML) allows for sophisticated approaches to survival prediction using real world clinical parameters needed to achieve superior predictive accuracy. We employed Cox Proportional hazards (CPH) model, Support Vector Machine (SVM) model, Random Forest (RF) model in a large glioma dataset (3462 patients, diagnosed 2000–2018) to explore the most optimal approach to survival prediction. Features employed were age, sex, surgical resection status, tumor histology and tumor site, administration of radiation therapy (RT) and chemotherapy status. Concordance index (c-index) was employed to assess the accuracy of survival time prediction. All three models performed well with prediction accuracy (CI 0.767, 0.771, 0.57 for CPH, SVM, RF models respectively) with the best performance achieved when incorporating RT and chemotherapy administration status which emerged as key predictive features. Within the subset of glioblastoma patients, similar prediction accuracy was achieved. These findings should prompt stricter clinician oversight over registry data accuracy through quality assurance as we move towards meaningful predictive ability using ML approaches in glioma.
    Type of Medium: Online Resource
    ISSN: 1460-4582 , 1741-2811
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2070802-6
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  • 7
    In: Neuro-Oncology Practice, Oxford University Press (OUP), Vol. 5, No. 4 ( 2018-11-02), p. 246-250
    Abstract: Valproic acid (VPA) is an antiepileptic agent with histone deacetylase inhibitor activity shown to enhance overall survival and progression free survival in patients with newly diagnosed glioblastoma (GBM). This reports on the late toxicity of the VPA/radiotherapy (RT)/temozolomide (TMZ) combination in the long-term survivors of a phase 2 study evaluating this regimen. Methods 37 patients with newly diagnosed GBM were initially enrolled on this trial and received combination therapy. VPA/RT/TMZ related late toxicities were evaluated in the 6 patients that lived greater than 3 years using the Cancer Therapy and Evaluation Program Common Toxicity Criteria (CTC) Version 4.0 for toxicity and adverse event reporting as well as the RTOG/EORTC Radiation Morbidity Scoring Scheme. Results The median duration of follow-up for these 6 patients was 69.5m. In this cohort, the median OS was 73.8m (60.8–103.8m) and median PFS was 53.1m (37.3 – 103.8m). The most common late toxicity of VPA in conjunction with RT/TMZ were the CTC classifications of neurological, pain, and blood/ bone marrow toxicity and most were grade 1/2. There were only two grade 3/4 toxicities. Conclusions The addition of VPA to concurrent RT/TMZ in patients with newly diagnosed GBM was well tolerated with little late toxicity. Additionally, VPA may result in improved outcomes as compared to historical data and merits further study.
    Type of Medium: Online Resource
    ISSN: 2054-2577 , 2054-2585
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2018
    detail.hit.zdb_id: 2768945-1
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  • 8
    In: Cancers, MDPI AG, Vol. 14, No. 12 ( 2022-06-12), p. 2897-
    Abstract: Recent technological developments have led to an increase in the size and types of data in the medical field derived from multiple platforms such as proteomic, genomic, imaging, and clinical data. Many machine learning models have been developed to support precision/personalized medicine initiatives such as computer-aided detection, diagnosis, prognosis, and treatment planning by using large-scale medical data. Bias and class imbalance represent two of the most pressing challenges for machine learning-based problems, particularly in medical (e.g., oncologic) data sets, due to the limitations in patient numbers, cost, privacy, and security of data sharing, and the complexity of generated data. Depending on the data set and the research question, the methods applied to address class imbalance problems can provide more effective, successful, and meaningful results. This review discusses the essential strategies for addressing and mitigating the class imbalance problems for different medical data types in the oncologic domain.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 9
    In: Biomolecules, MDPI AG, Vol. 13, No. 10 ( 2023-10-10), p. 1499-
    Abstract: Background: Glioblastoma (GBM) is the most common brain tumor with an overall survival (OS) of less than 30% at two years. Valproic acid (VPA) demonstrated survival benefits documented in retrospective and prospective trials, when used in combination with chemo-radiotherapy (CRT). Purpose: The primary goal of this study was to examine if the differential alteration in proteomic expression pre vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA as compared to standard-of-care CRT. The second goal was to explore the associations between the proteomic alterations in response to VPA/RT/TMZ correlated to patient outcomes. The third goal was to use the proteomic profile to determine the mechanism of action of VPA in this setting. Materials and Methods: Serum obtained pre- and post-CRT was analyzed using an aptamer-based SOMAScan® proteomic assay. Twenty-nine patients received CRT plus VPA, and 53 patients received CRT alone. Clinical data were obtained via a database and chart review. Tests for differences in protein expression changes between radiation therapy (RT) with or without VPA were conducted for individual proteins using two-sided t-tests, considering p-values of 〈 0.05 as significant. Adjustment for age, sex, and other clinical covariates and hierarchical clustering of significant differentially expressed proteins was carried out, and Gene Set Enrichment analyses were performed using the Hallmark gene sets. Univariate Cox proportional hazards models were used to test the individual protein expression changes for an association with survival. The lasso Cox regression method and 10-fold cross-validation were employed to test the combinations of expression changes of proteins that could predict survival. Predictiveness curves were plotted for significant proteins for VPA response (p-value 〈 0.005) to show the survival probability vs. the protein expression percentiles. Results: A total of 123 proteins were identified pre- vs. post-CRT that were differentially expressed between the cohorts who received CRT plus VPA and those who received CRT alone. Clinical factors did not confound the results, and distinct proteomic clustering in the VPA-treated population was identified. Time-dependent ROC curves for OS and PFS for landmark times of 20 months and 6 months, respectively, revealed AUC of 0.637, 0.756, 0.762 for OS and 0.559, 0.723, 0.776 for PFS for protein expression, clinical factors, and the combination of protein expression and clinical factors, respectively, indicating that the proteome can provide additional survival risk discrimination to that already provided by the standard clinical factors with a greater impact on PFS. Several proteins of interest were identified. Alterations in GALNT14 (increased) and CCL17 (decreased) (p = 0.001 and 0.002, respectively, FDR 0.104 for both) were associated with an improvement in both OS and PFS. The pre-CRT protein expression revealed 429 proteins predictive for OS and 223 for PFS (p 〈 0.05), of which 107 overlapped between OS and PFS. However, FDR-adjusted p values were high, with OS (0.987) and PFS (0.794). The protein PLCD3 had the lowest p-value (p = 0.004 and 0.0004 for OS and PFS, respectively), and its elevation prior to CRT predicted superior OS and PFS with VPA administration. Cancer hallmark genesets associated with proteomic alteration observed with the administration of VPA aligned with known signal transduction pathways of this agent in malignancy and non-malignancy settings, and GBM signaling, and included epithelial–mesenchymal transition, hedgehog signaling, Il6/JAK/STAT3, coagulation, NOTCH, apical junction, xenobiotic metabolism, and complement signaling. Conclusions: Differential alteration in proteomic expression pre- vs. post-completion of concurrent chemoirradiation (CRT) is present with the addition of VPA. Using pre- vs. post-data, prognostic proteins emerged in the analysis. Using pre-CRT data, potentially predictive proteins were identified. The protein signals and hallmark gene sets associated with the alteration in the proteome identified between patients who received VPA and those who did not, align with known biological mechanisms of action of VPA and may allow for the identification of novel biomarkers associated with outcomes that can help advance the study of VPA in future prospective trials.
    Type of Medium: Online Resource
    ISSN: 2218-273X
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2701262-1
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  • 10
    In: Radiation Oncology, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2017-12)
    Type of Medium: Online Resource
    ISSN: 1748-717X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2224965-5
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