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  1. Article ; Online: Selection of optimal quantile protein biomarkers based on cell-level immunohistochemistry data.

    Yi, Misung / Zhan, Tingting / Peck, Amy R / Hooke, Jeffrey A / Kovatich, Albert J / Shriver, Craig D / Hu, Hai / Sun, Yunguang / Rui, Hallgeir / Chervoneva, Inna

    BMC bioinformatics

    2023  Volume 24, Issue 1, Page(s) 298

    Abstract: Background: Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell ...

    Abstract Background: Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells.
    Results: We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers.
    Conclusion: The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.
    MeSH term(s) Humans ; Female ; Immunohistochemistry ; Ki-67 Antigen ; Biomarkers, Tumor ; Breast Neoplasms ; Algorithms
    Chemical Substances Ki-67 Antigen ; Biomarkers, Tumor
    Language English
    Publishing date 2023-07-22
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-023-05408-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Quantile Index Biomarkers Based on Single-Cell Expression Data.

    Yi, Misung / Zhan, Tingting / Peck, Amy R / Hooke, Jeffrey A / Kovatich, Albert J / Shriver, Craig D / Hu, Hai / Sun, Yunguang / Rui, Hallgeir / Chervoneva, Inna

    Laboratory investigation; a journal of technical methods and pathology

    2023  Volume 103, Issue 8, Page(s) 100158

    Abstract: Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology ... ...

    Abstract Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.
    MeSH term(s) Humans ; Female ; Biomarkers ; Biomarkers, Tumor ; Proteins ; Immunohistochemistry ; Breast Neoplasms/diagnosis
    Chemical Substances Biomarkers ; Biomarkers, Tumor ; Proteins
    Language English
    Publishing date 2023-04-22
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 80178-1
    ISSN 1530-0307 ; 0023-6837
    ISSN (online) 1530-0307
    ISSN 0023-6837
    DOI 10.1016/j.labinv.2023.100158
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  3. Article: Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer.

    Maisel, Brenton A / Yi, Misung / Peck, Amy R / Sun, Yunguang / Hooke, Jeffrey A / Kovatich, Albert J / Shriver, Craig D / Hu, Hai / Nevalainen, Marja T / Tanaka, Takemi / Simone, Nicole / Wang, Li Lily / Rui, Hallgeir / Chervoneva, Inna

    Cancers

    2022  Volume 14, Issue 2

    Abstract: Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. ... ...

    Abstract Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. Histopathological assessments suggest that the density of CD163-positive TAMs within the tumor microenvironment is associated with reduced efficacy of chemotherapy and unfavorable prognosis. However, previous analyses have required research-oriented pathologists to visually enumerate CD163+ TAMs, which is both laborious and subjective and hampers clinical implementation. Objective, operator-independent image analysis methods to quantify TAM-associated information are needed. In addition, since M2-like TAMs exert local effects on cancer cells through direct juxtacrine cell-to-cell interactions, paracrine signaling, and metabolic factors, we hypothesized that spatial metrics of adjacency of M2-like TAMs to breast cancer cells will have further information value. Immunofluorescence histo-cytometry of CD163+ TAMs was performed retrospectively on tumor microarrays of 443 cases of invasive breast cancer from patients who subsequently received adjuvant chemotherapy. An objective and automated algorithm was developed to phenotype CD163+ TAMs and calculate their density within the tumor stroma and derive several spatial metrics of interaction with cancer cells. Shorter progression-free survival was associated with a high density of CD163+ TAMs, shorter median cancer-to-CD163+ nearest neighbor distance, and a high number of either directly
    Language English
    Publishing date 2022-01-08
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers14020308
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  4. Article ; Online: PCA-PAM50 improves consistency between breast cancer intrinsic and clinical subtyping reclassifying a subset of luminal A tumors as luminal B.

    Raj-Kumar, Praveen-Kumar / Liu, Jianfang / Hooke, Jeffrey A / Kovatich, Albert J / Kvecher, Leonid / Shriver, Craig D / Hu, Hai

    Scientific reports

    2019  Volume 9, Issue 1, Page(s) 7956

    Abstract: The PAM50 classifier is widely used for breast tumor intrinsic subtyping based on gene expression. Clinical subtyping, however, is based on immunohistochemistry assays of 3-4 biomarkers. Subtype calls by these two methods do not completely match even on ... ...

    Abstract The PAM50 classifier is widely used for breast tumor intrinsic subtyping based on gene expression. Clinical subtyping, however, is based on immunohistochemistry assays of 3-4 biomarkers. Subtype calls by these two methods do not completely match even on comparable subtypes. Nevertheless, the estrogen receptor (ER)-balanced subset for gene-centering in PAM50 subtyping, is selected based on clinical ER status. Here we present a new method called Principle Component Analysis-based iterative PAM50 subtyping (PCA-PAM50) to perform intrinsic subtyping in ER status unbalanced cohorts. This method leverages PCA and iterative PAM50 calls to derive the gene expression-based ER status and a subsequent ER-balanced subset for gene centering. Applying PCA-PAM50 to three different breast cancer study cohorts, we observed improved consistency (by 6-9.3%) between intrinsic and clinical subtyping for all three cohorts. Particularly, a more aggressive subset of luminal A (LA) tumors as evidenced by higher MKI67 gene expression and worse patient survival outcomes, were reclassified as luminal B (LB) increasing the LB subtype consistency with IHC by 25-49%. In conclusion, we show that PCA-PAM50 enhances the consistency of breast cancer intrinsic and clinical subtyping by reclassifying an aggressive subset of LA tumors into LB. PCA-PAM50 code is available at ftp://ftp.wriwindber.org/ .
    MeSH term(s) Biomarkers, Tumor/genetics ; Biomarkers, Tumor/metabolism ; Breast Neoplasms/classification ; Breast Neoplasms/diagnosis ; Breast Neoplasms/genetics ; Breast Neoplasms/mortality ; Cohort Studies ; Estrogen Receptor alpha/genetics ; Estrogen Receptor alpha/metabolism ; Female ; Gene Expression ; Gene Expression Profiling ; Humans ; Immunohistochemistry ; Ki-67 Antigen/genetics ; Ki-67 Antigen/metabolism ; Principal Component Analysis ; Prognosis ; Protein Array Analysis ; Receptor, ErbB-2/genetics ; Receptor, ErbB-2/metabolism ; Survival Analysis ; Terminology as Topic
    Chemical Substances Biomarkers, Tumor ; ESR1 protein, human ; Estrogen Receptor alpha ; Ki-67 Antigen ; MKI67 protein, human ; ERBB2 protein, human (EC 2.7.10.1) ; Receptor, ErbB-2 (EC 2.7.10.1)
    Language English
    Publishing date 2019-05-28
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-019-44339-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: High PD-L2 Predicts Early Recurrence of ER-Positive Breast Cancer.

    Chervoneva, Inna / Peck, Amy R / Sun, Yunguang / Yi, Misung / Udhane, Sameer S / Langenheim, John F / Girondo, Melanie A / Jorns, Julie M / Chaudhary, Lubna N / Kamaraju, Sailaja / Bergom, Carmen / Flister, Michael J / Hooke, Jeffrey A / Kovatich, Albert J / Shriver, Craig D / Hu, Hai / Palazzo, Juan P / Bibbo, Marluce / Hyslop, Terry /
    Nevalainen, Marja T / Pestell, Richard G / Fuchs, Serge Y / Mitchell, Edith P / Rui, Hallgeir

    JCO precision oncology

    2023  Volume 7, Page(s) e2100498

    Abstract: Purpose: T-cell-mediated cytotoxicity is suppressed when programmed cell death-1 (PD-1) is bound by PD-1 ligand-1 (PD-L1) or PD-L2. Although PD-1 inhibitors have been approved for triple-negative breast cancer, the lower response rates of 25%-30% in ... ...

    Abstract Purpose: T-cell-mediated cytotoxicity is suppressed when programmed cell death-1 (PD-1) is bound by PD-1 ligand-1 (PD-L1) or PD-L2. Although PD-1 inhibitors have been approved for triple-negative breast cancer, the lower response rates of 25%-30% in estrogen receptor-positive (ER+) breast cancer will require markers to identify likely responders. The focus of this study was to evaluate whether PD-L2, which has higher affinity than PD-L1 for PD-1, is a predictor of early recurrence in ER+ breast cancer.
    Methods: PD-L2 protein levels in cancer cells and stromal cells of therapy-naive, localized or locoregional ER+ breast cancers were measured retrospectively by quantitative immunofluorescence histocytometry and correlated with progression-free survival (PFS) in the main study cohort (n = 684) and in an independent validation cohort (n = 273). All patients subsequently received standard-of-care adjuvant therapy without immune checkpoint inhibitors.
    Results: Univariate analysis of the main cohort revealed that high PD-L2 expression in cancer cells was associated with shorter PFS (hazard ratio [HR], 1.8; 95% CI, 1.3 to 2.6;
    Conclusion: Up to one third of treatment-naive ER+ breast tumors expressed high PD-L2 levels, which independently predicted poor clinical outcome, with evidence of further elevated risk of progression in patients who received adjuvant chemotherapy. Collectively, these data warrant studies to gain a deeper understanding of PD-L2 in the progression of ER+ breast cancer and may provide rationale for immune checkpoint blockade for this patient group.
    MeSH term(s) Humans ; B7-H1 Antigen ; Programmed Cell Death 1 Receptor ; Retrospective Studies ; Triple Negative Breast Neoplasms
    Chemical Substances B7-H1 Antigen ; Programmed Cell Death 1 Receptor
    Language English
    Publishing date 2023-01-18
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ISSN 2473-4284
    ISSN (online) 2473-4284
    DOI 10.1200/PO.21.00498
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection.

    Raj-Kumar, Praveen-Kumar / Lin, Xiaoying / Liu, Tao / Sturtz, Lori A / Gritsenko, Marina A / Petyuk, Vladislav A / Sagendorf, Tyler J / Deyarmin, Brenda / Liu, Jianfang / Praveen-Kumar, Anupama / Wang, Guisong / McDermott, Jason E / Shukla, Anil K / Moore, Ronald J / Monroe, Matthew E / Webb-Robertson, Bobbie-Jo M / Hooke, Jeffrey A / Fantacone-Campbell, Leigh / Mostoller, Brad /
    Kvecher, Leonid / Kane, Jennifer / Melley, Jennifer / Somiari, Stella / Soon-Shiong, Patrick / Smith, Richard D / Mural, Richard J / Rodland, Karin D / Shriver, Craig D / Kovatich, Albert J / Hu, Hai

    Breast cancer research : BCR

    2024  Volume 26, Issue 1, Page(s) 76

    Abstract: Background: Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as ...

    Abstract Background: Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors.
    Methods: We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers.
    Results: We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors.
    Conclusions: This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.
    MeSH term(s) Humans ; Female ; Breast Neoplasms/genetics ; Breast Neoplasms/pathology ; Breast Neoplasms/metabolism ; Breast Neoplasms/mortality ; Biomarkers, Tumor/genetics ; Proteogenomics/methods ; Mutation ; Laser Capture Microdissection ; Middle Aged ; Retrospective Studies ; Aged ; Adult ; Proteomics/methods ; Prognosis
    Language English
    Publishing date 2024-05-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 2015059-3
    ISSN 1465-542X ; 1465-5411
    ISSN (online) 1465-542X
    ISSN 1465-5411
    DOI 10.1186/s13058-024-01835-4
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5494: Show issues Location:
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  7. Article ; Online: Malignant cell-specific pro-tumorigenic role of type I interferon receptor in breast cancers.

    Odnokoz, Olena / Yu, Pengfei / Peck, Amy R / Sun, Yunguang / Kovatich, Albert J / Hooke, Jeffrey A / Hu, Hai / Mitchell, Edith P / Rui, Hallgeir / Fuchs, Serge Y

    Cancer biology & therapy

    2020  Volume 21, Issue 7, Page(s) 629–636

    Abstract: Within the microenvironment of solid tumors, stress associated with deficit of nutrients and oxygen as well as tumor-derived factors triggers the phosphorylation-dependent degradation of the IFNAR1 chain of type I interferon (IFN1) receptor and ensuing ... ...

    Abstract Within the microenvironment of solid tumors, stress associated with deficit of nutrients and oxygen as well as tumor-derived factors triggers the phosphorylation-dependent degradation of the IFNAR1 chain of type I interferon (IFN1) receptor and ensuing suppression of the IFN1 pathway. Here we sought to examine the importance of these events in malignant mammary cells. Expression of non-degradable IFNAR1
    MeSH term(s) Animals ; Breast Neoplasms/genetics ; Breast Neoplasms/pathology ; Cell Line, Tumor ; Cell Proliferation ; Female ; Humans ; Interferon Type I/metabolism ; Mice ; Signal Transduction ; Tumor Microenvironment
    Chemical Substances Interferon Type I
    Language English
    Publishing date 2020-05-07
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2146305-0
    ISSN 1555-8576 ; 1538-4047
    ISSN (online) 1555-8576
    ISSN 1538-4047
    DOI 10.1080/15384047.2020.1750297
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  8. Article ; Online: Development and validation of prognostic gene signature for basal-like breast cancer and high-grade serous ovarian cancer.

    Zhang, Yi / Liu, Jianfang / Raj-Kumar, Praveen-Kumar / Sturtz, Lori A / Praveen-Kumar, Anupama / Yang, Howard H / Lee, Maxwell P / Fantacone-Campbell, J Leigh / Hooke, Jeffrey A / Kovatich, Albert J / Shriver, Craig D / Hu, Hai

    Breast cancer research and treatment

    2020  Volume 184, Issue 3, Page(s) 689–698

    Abstract: Purpose: Molecular similarities have been reported between basal-like breast cancer (BLBC) and high-grade serous ovarian cancer (HGSOC). To date, there have been no prognostic biomarkers that can provide risk stratification and inform treatment ... ...

    Abstract Purpose: Molecular similarities have been reported between basal-like breast cancer (BLBC) and high-grade serous ovarian cancer (HGSOC). To date, there have been no prognostic biomarkers that can provide risk stratification and inform treatment decisions for both BLBC and HGSOC. In this study, we developed a molecular signature for risk stratification in BLBC and further validated this signature in HGSOC.
    Methods: RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA) project for 190 BLBC and 314 HGSOC patients. Analyses of differentially expressed genes between recurrent vs. non-recurrent cases were performed using different bioinformatics methods. Gene Signature was established using weighted linear combination of gene expression levels. Their prognostic performance was evaluated using survival analysis based on progression-free interval (PFI) and disease-free interval (DFI).
    Results: 63 genes were differentially expressed between 18 recurrent and 40 non-recurrent BLBC patients by two different methods. The recurrence index (RI) calculated from this 63-gene signature significantly stratified BLBC patients into two risk groups with 38 and 152 patients in the low-risk (RI-Low) and high-risk (RI-High) groups, respectively (p = 0.0004 and 0.0023 for PFI and DFI, respectively). Similar performance was obtained in the HGSOC cohort (p = 0.0131 and 0.004 for PFI and DFI, respectively). Multivariate Cox regression adjusting for age, grade, and stage showed that the 63-gene signature remained statistically significant in stratifying HGSOC patients (p = 0.0005).
    Conclusion: A gene signature was identified to predict recurrence in BLBC and HGSOC patients. With further validation, this signature may provide an additional prognostic tool for clinicians to better manage BLBC, many of which are triple-negative and HGSOC patients who are currently difficult to treat.
    MeSH term(s) Biomarkers, Tumor/genetics ; Breast Neoplasms/genetics ; Cystadenocarcinoma, Serous/genetics ; Female ; Humans ; Neoplasm Recurrence, Local/genetics ; Ovarian Neoplasms/genetics ; Prognosis
    Chemical Substances Biomarkers, Tumor
    Language English
    Publishing date 2020-09-02
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 604563-7
    ISSN 1573-7217 ; 0167-6806
    ISSN (online) 1573-7217
    ISSN 0167-6806
    DOI 10.1007/s10549-020-05884-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Comparative analysis of differentially abundant proteins quantified by LC-MS/MS between flash frozen and laser microdissected OCT-embedded breast tumor samples.

    Sturtz, Lori A / Wang, Guisong / Shah, Punit / Searfoss, Richard / Raj-Kumar, Praveen-Kumar / Hooke, Jeffrey A / Fantacone-Campbell, J Leigh / Deyarmin, Brenda / Cutler, Mary Lou / Sarangarajan, Rangaprasad / Narain, Niven R / Hu, Hai / Kiebish, Michael A / Kovatich, Albert J / Shriver, Craig D

    Clinical proteomics

    2020  Volume 17, Issue 1, Page(s) 40

    Abstract: Background: Proteomic studies are typically conducted using flash-frozen (FF) samples utilizing tandem mass spectrometry (MS). However, FF specimens are comprised of multiple cell types, making it difficult to ascertain the proteomic profiles of ... ...

    Abstract Background: Proteomic studies are typically conducted using flash-frozen (FF) samples utilizing tandem mass spectrometry (MS). However, FF specimens are comprised of multiple cell types, making it difficult to ascertain the proteomic profiles of specific cells. Conversely, OCT-embedded (Optimal Cutting Temperature compound) specimens can undergo laser microdissection (LMD) to capture and study specific cell types separately from the cell mixture. In the current study, we compared proteomic data obtained from FF and OCT samples to determine if samples that are stored and processed differently produce comparable results.
    Methods: Proteins were extracted from FF and OCT-embedded invasive breast tumors from 5 female patients. FF specimens were lysed via homogenization (FF/HOM) while OCT-embedded specimens underwent LMD to collect only tumor cells (OCT/LMD-T) or both tumor and stromal cells (OCT/LMD-TS) followed by incubation at 37 °C. Proteins were extracted using the illustra triplePrep kit and then trypsin-digested, TMT-labeled, and processed by two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS). Proteins were identified and quantified with Proteome Discoverer v1.4 and comparative analyses performed to identify proteins that were significantly differentially expressed amongst the different processing methods.
    Results: Among the 4,950 proteins consistently quantified across all samples, 216 and 171 proteins were significantly differentially expressed (adjusted p-value < 0.05; |log
    Conclusions: The proteomic profiles of the OCT/LMD-TS samples were more similar to those from OCT/LMD-T samples than FF/HOM samples, suggesting a strong influence from the sample processing methods. These results indicate that in LC-MS/MS proteomic studies, FF/HOM samples exhibit different protein expression profiles from OCT/LMD samples and thus, results from these two different methods cannot be directly compared.
    Language English
    Publishing date 2020-11-07
    Publishing country England
    Document type Journal Article
    ZDB-ID 2205154-5
    ISSN 1542-6416
    ISSN 1542-6416
    DOI 10.1186/s12014-020-09300-y
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  10. Article: p53 Immunohistochemistry for Distinguishing Reactive Mesothelium from Low Grade Ovarian Carcinoma

    Pindzola, Ander / Kovatich, Albert J. / Bibbo, Marluce

    Acta Cytologica

    2011  Volume 44, Issue 1, Page(s) 31–36

    Institution From the Divisions of Immunohistochemistry and Cytopathology, Department of Pathology, Cell Biology and Anatomy, Jefferson Medical, College, Thomas Jefferson University, Philadelphia, Pennsylvania, U.S.A
    Language English
    Publishing date 2011-04-15
    Publisher S. Karger AG
    Publishing place Basel, Switzerland
    Document type Article
    Note Original Articles
    ZDB-ID 80003-x
    ISSN 1938-2650 ; 0001-5547
    ISSN (online) 1938-2650
    ISSN 0001-5547
    DOI 10.1159/000326221
    Database Karger publisher's database

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