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Dataset results
14 results for “Ki-67”
Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and aspirates from patients with myeloid malignancies.
<p>This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferation and anti-apoptosis in hematopoietic cells. This dataset includes analysis of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell population in non-malignant BM, and the BM disorders myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. As gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 50 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research about the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations based on cell biological characteristics were identified, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells to identify minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.</p>
Ki-67 and Bcl-2 data by flow cytometry in non-malignant bone marrow aspirates and patients with myeloid malignancies
<p>This Data in Brief article displays a flow cytometric assay that was used for the acquisition and analyses of proliferative and anti-apoptotic activity in hematopoietic cells. This dataset includes analyses of the Ki-67 positive fraction (Ki-67 proliferation index) and Bcl-2 positive fraction (Bcl-2 anti-apoptotic index) of the different myeloid bone marrow (BM) cell populations in non-malignant BM, and in BM disorders, i.e. myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). The present dataset comprises 1) the percentage of the CD34 positive blast cells, erythroid cells, myeloid cells and monocytic cells, and 2) the determined Ki-67 positive fraction and Bcl-2 positive fraction of these cell populations in tabular form. This allows the comparison and reproduction of the data when these analyses are repeated in a different setting. Because gating the Ki-67 positive and Bcl-2 positive cells is a critical step in this assay, different gating approaches were compared to determine the most sensitive and specific approach. BM cells from aspirates of 50 non-malignant, 25 MDS and 27 AML cases were stained with 7 different antibody panels and subjected to flow cytometry for determination of the Ki-67 positive cells and Bcl-2 positive cells of the different myeloid cell populations. The Ki-67 or Bcl-2 positive cells were then divided by the total number of cells of the respective cell population to generate the Ki-67 positive fraction (Ki-67 proliferation index) or the Bcl-2 positive fraction (Bcl-2 anti-apoptotic index). The presented data may facilitate the establishment and standardization of flow cytometric analyses of the Ki-67 proliferation index and Bcl-2 anti-apoptotic index of the different myeloid cell populations in non-malignant BM as well as MDS and AML patients in other laboratories. Directions for proper gating of the Ki-67 positive and Bcl-2 positive fraction are crucial for achieving standardization among different laboratories. In addition, the data and the presented assay allows application of Ki-67 and Bcl-2 in a research and clinical setting and this approach can serve as the basis for optimization of the gating strategy and subsequent investigation of other cell biological processes besides proliferation and anti-apoptosis. These data can also promote future research into the role of these parameters in diagnosis of myeloid malignancies, prognosis of myeloid malignancies and therapeutic resistance against anti-cancer therapies in these malignancies. As specific populations were identified based on cell biological characteristics, these data can be useful for evaluating gating algorithms in flow cytometry in general by confirming the outcome (e.g. MDS or AML diagnosis) with the respective proliferation and anti-apoptotic profile of these malignancies. The Ki-67 proliferation index and Bcl-2 anti-apoptotic index may potentially be used for classification of MDS and AML based on supervised machine learning algorithms, while unsupervised machine learning can be deployed at the level of single cells to potentially distinguish non-malignant from malignant cells in the identification of minimal residual disease. Therefore, the present dataset may be of interest for internist-hematologists, immunologists with affinity for hemato-oncology, clinical chemists with sub-specialization of hematology and researchers in the field of hemato-oncology.</p>
TEMCAP in Grade 3 and Low Ki-67 Gastroenteropancreatic Neuroendocrine Tumors
ClinicalTrials.gov study NCT03079440. IPD Sharing: NO. Countries: 1. Publications: 5.
Over-expression of Ki-67 as a predictor of lymph node metastasis in penile cancer patients
<p>In this study, we will look at the association of Ki-67 with lymph node metastasis in patients with penile cancer.</p>
Could Ki-67 be Used as a Diagnostic or Prognostic Marker in Hemato-oncological Diagnostics?
ClinicalTrials.gov study NCT04517175. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.
p16 and Ki-67 Stainings and Natural Killer (NK) Cells in CIN-II Management
ClinicalTrials.gov study NCT02522585. IPD Sharing: Not stated. Countries: 0. Publications: 6.
Ki-67 promotes carcinogenesis by enabling global transcriptional programmes
GEO Series GSE163114. Homo sapiens; Mus musculus. 52 samples. Type: Expression profiling by high throughput sequencing; Expression profiling by array; Genome binding/occupancy profiling by high throughput sequencing.
Lactate Levels Correlates With Ki-67 in Brain Tumor Surgery
ClinicalTrials.gov study NCT03531307. IPD Sharing: NO. Countries: 1. Publications: 0.
SUV on 68Ga-DOTATATE PET/CT and Ki-67 Index in Neuro-Endocrine Tumors
ClinicalTrials.gov study NCT02840149. IPD Sharing: NO. Countries: 1. Publications: 0.
Multigene Risk Score Combined With Ki-67 Dynamic Assessment in Stratified Neoadjuvant Endocrine Therapy Treatment With or Without CDK4/6 Inhibitors in HR+/HER2- Breast Cancer
ClinicalTrials.gov study NCT06650748. IPD Sharing: NO. Countries: 1. Publications: 0.
Analysis of adrenocortical tumors identify IGF2 and Ki-67 as useful in differentiating carcinomas from adenomas
GEO Series GSE12368. Homo sapiens. 34 samples. Type: Expression profiling by array.
Identification and Semi-Quantification of Ki-67 Protein Expression Status
ClinicalTrials.gov study NCT02654457. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Raw RNA-seq data from control and Ki-67-depleted HCT116 human colon cancer cells
GEO Series GSE159160. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Human HeLa cells: Control shRNA vs Ki-67 shRNA, in vitro and xenografts
GEO Series GSE162365. Homo sapiens. 12 samples. Type: Expression profiling by array.
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