Validation of Clinical Treatment Score post-5 years (CTS5) risk stratification in premenopausal breast cancer patients and Ki-67 labelling index.
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SUBMITTER: Lee J
PROVIDER: S-EPMC7546620 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective:To explore the correlation between the spectral computed tomography (CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma. Methods:Spectral CT imaging parameters [iodine concentrations of lesions (ICLs) in the arterial phase (ICLa) and venous phase (ICLv), normalized IC in the aorta (NICa/NICv), slope of the spectral HU curve (?HUa/?HUv) and monochromatic CT number enhancement on 40 keV and 70 keV images (CT40keVa/v, CT70keVa/v)] in 34 lung adenocarcinomas were analyzed, and common molecular markers, including the Ki-67 labeling index, were detected with immunohistochemistry. Different Ki-67 labeling indexes were measured and grouped into four grades according to the number of positive-stained cells (grade 0, ?1%; 1%<grade 1?10%; 10%<grade 2?30%; and grade 3, >30%). One-way analysis of variance (ANOVA) was used to compare the four different grades, and the Bonferroni method was used to correct the P value for multiple comparisons. A Spearman correlation analysis was performed to further research a quantitative correlation between the Ki-67 labeling index and spectral CT imaging parameters. Results:CT40keVa, CT40keVv, CT70keVa and CT70keVv increased as the grade increased, and CT70keVa and CT70keVv were statistically significant (P<0.05). These four parameters and the Ki-67 labeling index showed a moderate positive correlation with lung adenocarcinoma nodules. ICL, NIC and ?HU in the arterial and venous phases were not significantly different among the four grades. Conclusions:The spectral CT imaging parameters CT40keVa, CT40keVv, CT70keVa and CT70keVv gradually increased with Ki-67 expression and showed a moderate positive correlation with lung adenocarcinomas. Therefore, spectral CT imaging parameter-enhanced monochromatic CT numbers at 70 keV may indicate the extent of proliferation of lung adenocarcinomas.
| S-EPMC7072011 | biostudies-literature
Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is an aggressive disease characterized by complex biological features and poor prognosis. A prognostic stratification of PDAC would help to improve patient management. The aim of this study was to analyse the expression of Ki-67 in relation to prognosis in a cohort of patients with PDAC who had surgical treatment.MethodsPatients who had pancreatic resection between August 2010 and October 2014 for PDAC at two Italian centres were reviewed retrospectively. Patients with metastatic or locally advanced disease, those who received neoadjuvant chemotherapy, patients with PDAC arising from intraductal papillary mucinous neoplasm and those with missing data were excluded. Clinical and pathological data were retrieved and analysed. Ki-67 expression was evaluated using immunohistochemistry and patients were stratified into three subgroups. Survival analyses were performed for disease-free (DFS) and disease-specific (DSS) survival outcomes according to Ki-67 expression and tumour grading.ResultsA total of 170 patients met the selection criteria. Ki-67 expression of 10 per cent or less, 11-50 per cent and more than 50 per cent significantly correlated with DFS and DSS outcomes (P = 0·016 and P = 0·002 respectively). Ki-67 index was an independent predictor of poor DFS (hazard ratio (HR) 0·52, 95 per cent c.i. 0·29 to 0·91; P = 0·022) and DSS (HR 0·53, 0·31 to 0·91; P = 0·022). Moreover, Ki-67 index correlated strongly with tumour grade (P < 0·001). Patients with PDAC classified as a G3 tumour with a Ki-67 index above 50 per cent had poor survival outcomes compared with other patients (P < 0·001 for both DFS and DSS).ConclusionKi-67 index could be of use in predicting the survival of patients with PDAC. Further investigation in larger cohorts is needed to validate these results.
| S-EPMC6773637 | biostudies-literature
Project description:Ki-67 serves as a prominent cancer marker. We describe how expression of the MKI67 gene coding for Ki-67 is controlled during the cell cycle. MKI67 mRNA and Ki-67 protein are maximally expressed in G2 phase and mitosis. Expression is dependent on two CHR elements and one CDE site in the MKI67 promoter. DREAM transcriptional repressor complexes bind to both CHR sites and downregulate the expression in G0/G1 cells. Upregulation of MKI67 transcription coincides with binding of B-MYB-MuvB and FOXM1-MuvB complexes from S phase into G2/M. Importantly, binding of B-MYB to the two CHR elements correlates with loss of CHR-dependent MKI67 promoter activation in B-MYB-knockdown experiments. In knockout cell models, we find that DREAM/MuvB-dependent transcriptional control cooperates with the RB Retinoblastoma tumor suppressor. Furthermore, the p53 tumor suppressor indirectly downregulates transcription of the MKI67 gene. This repression by p53 requires p21/CDKN1A. These results are consistent with a model in which DREAM, B-MYB-MuvB, and FOXM1-MuvB together with RB cooperate in cell cycle-dependent transcription and in transcriptional repression following p53 activation. In conclusion, we present mechanisms how MKI67 gene expression followed by Ki-67 protein synthesis is controlled during the cell cycle and upon induction of DNA damage, as well as upon p53 activation.
| S-EPMC8629999 | biostudies-literature
Project description:The clinical evolution of solitary fibrous tumors (SFTs) is often uncertain and several risk stratification systems (RSS) have been proposed. The Demicco et al. RSS is the most frequently implemented. In this study we aim to validate two alternative RSS (Sugita et al. and G-Score) using results for the Demicco RSS from a previous study of 97 SFTs. In addition, we aim to determine whether reclassified cases had any distinctive molecular features. As the Sugita et al. system substitutes mitotic count with Ki-67 index we also investigated whether Ki-67 results for tissue microarrays are comparable to those obtained using whole tissue sections. In the present study we detected that many cases classified by Demicco RSS as low-risk were reclassified as intermediate risk using the new system (G-score RSS). Kaplan-Meier survival plots for G-Score RSS showed that the low-risk and intermediate-risk SFTs had a similar evolution that contrasted with the more aggressive high-risk group. Moreover, the similar evolution in both low and intermediate-risk groups occurred despite the G-score system being stricter in classifying low-risk tumors. We observed that Sugita RSS does not provide any better risk stratification in comparison with the Demicco RSS, and testing both RSS in our series produced similar Kaplan-Meier survival data. We found some discordant results when comparing whole sections and the corresponding tissue microarrays samples, finding the hotspot areas easier to locate in whole sections. Forty-one SFTs with initial low-risk assigned by the Demicco RSS were reclassified as intermediate-risk by G-score finding both TP53 and HTER mutations in four cases, only HTER mutation in 11 cases, and only TP53 mutation in 2 cases. All six cases of SFT classified as high-risk by both the Demicco and G-score RSS suffered recurrence/metastasis, and half showed both TP53 and HTER mutations. Five SFTs were categorized as low-risk by both Demicco and G-score, of which 4 cases revealed HTER mutation. Regarding the outcome of these 5 patients, two were lost to follow-up, and one of the remaining three patients suffered recurrence. We believe that although the presence of both TP53 and HTER mutations may confer or be related to poor evolution, the isolated presence of HTER mutation alone would not necessarily be related to poor outcome. The G-score RSS more accurately identified low-risk patients than the other two risk models evaluated in the present series. Late recurrence/metastasis may occasionally be observed even in low-risk SFTs categorized by stricter classification systems such as the G-score RSS. These findings support the possibility that additional, as yet unknown factors may influence the clinical evolution of SFTs. In conclusion, given the possibility of late recurrence, long-term follow-up is recommended for all SFT patients, even in cases classified as low risk by the stricter G-score system. An integration of clinical, radiological, pathological, and molecular findings may improve SFT risk stratification and better predict patient outcome.
| S-EPMC9820154 | biostudies-literature
Project description:BackgroundRho GTPase-activating protein 10 (ARHGAP10), which catalyzes the conversion of active Rho GTPase to the inactive form, is downregulated in some cancers. However, little is known about ARHGAP10 in breast cancer.MethodsThe transcriptional expression level of ARHGAP10 in breast cancer was analyzed with the data downloaded from The Cancer Genome Atlas (TCGA) and Oncomine, then verified by reverse-transcription quantitative polymerase chain reaction (RT-qPCR) in 30 pairs of breast cancer tissues and the corresponding adjacent normal tissues. ARHGAP10 protein expression was examined by immunohistochemistry (IHC) in 190 breast cancer and 30 corresponding adjacent normal breast tissue samples. The associations between ARHGAP10 expression and clinicopathological characteristics of patients were analyzed, and Kaplan-Meier Plotter was used to assess the relationship between ARHGAP10 and relapse-free survival (RFS). Different expression levels of ARHGAP10 in response to chemotherapy agents were determined by GEO2R online tool. The potential biological functions of ARHGAP10 were analyzed by Gene Set Enrichment Analysis (GSEA) using data downloaded from TCGA.ResultsARHGAP10 mRNA and protein expression was lower in breast cancer tissues than in adjacent normal tissues. Low expression of ARHGAP10 was associated with advanced clinical TNM (cTNM) stage (p b = 0.001) and high Ki-67 index (p = 0.015). Low expression of ARHGAP10 indicated worse RFS (p = 0.0015) and a poor response to chemotherapy (p = 0.006). GSEA results showed that ARHGAP10 was involved in signaling pathways including protein export, nucleotide excision repair, base excision repair, focal adhesion, JAK-STAT pathway and the actin cytoskeleton.
| S-EPMC6679923 | biostudies-literature
Project description:BackgroundTo determine whether preoperative computed tomography (CT) features can be used for the prediction of gastrointestinal stromal tumors (GISTs) with a high Ki-67 proliferation index (Ki-67 PI).MethodsA total of 198 patients with surgically and pathologically proven GISTs were retrospectively included. All GISTs were divided into a low Ki-67 PI group (<10%) and a high Ki-67 PI group (≥10%). All imaging features were blindly interpreted by two radiologists. Receiver operating characteristic (ROC) curve analyses were conducted to evaluate the predictive performance of the imaging features.ResultsImaging features were found to be significantly different between the low and the high Ki-67 PI groups (P<0.05). Wall thickness of necrosis showed the highest predictive ability, with an area under the curve (AUC) of 0.838 [95% confidence interval (CI): 0.627-0.957], followed by necrosis, necrosis degree, hyperenhancement of the overlying mucosa (HYOM), and long diameter (LD) (AUC >0.7, P<0.05). HYOM was the strongest predictive feature for the high Ki-67 PI GISTs group, with an odds ratio (OR) value of 30.037 (95% CI: 5.707-158.106).ConclusionsImaging features, including the presence of necrosis, high necrosis degree, thick wall of necrosis, and HYOM were significant predictive indicators for the high Ki-67 PI GISTs group.
| S-EPMC8576677 | biostudies-literature
Project description:The current World Health Organization (WHO) classification of human gliomas is mainly based on morphology. However, it has limitations in prognostic prediction. We examined whether combining isocitrate dehydrogenase (IDH) 1/2 mutation status with the Ki-67 labeling index would improve the definition of prognostically distinct entities. We investigated the correlation of Ki-67 expression with IDH1/2 mutation status and their impact on clinical outcome in 703 gliomas. Low Ki-67 expression closely overlapped with IDH1/2 mutation in our cohort (P < 0.0001). Patients with IDH1/2 mutation survived significantly longer than patients with wild-type IDH1/2 did (P < 0.0001); higher Ki-67 expression was associated with shorter progression-free survival and overall survival (OS) (P < 0.0001). IDH1/2 combined with Ki-67 was used to re-classify glioma patients into five groups. IDH1/2 mutant patients with low and moderate Ki-67 expression (Group1) had the best prognosis, whereas patients with wild-type IDH1/2 and high Ki-67 expression (Group5) had the worst prognosis (Median OS = 1527 vs. 355 days, P < 0.0001). To summarize, our new classification model distinguishes biologically distinct subgroups and provides prognostic information regardless of the conventional WHO grade. Classification based on IDH1/2 mutation status and Ki-67 expression level could be more convenient for clinical application and guide personalized treatment in malignant gliomas.
| S-EPMC4745793 | biostudies-literature
Project description:Ki-67 is one of the most famous marker proteins used by histologists to identify proliferating cells. Indeed, over 30 000 articles referring to Ki-67 are listed on PubMed. Here, we review some of the current literature regarding the protein. Despite its clinical importance, our knowledge of the molecular biology and biochemistry of Ki-67 is far from complete, and its exact molecular function(s) remain enigmatic. Furthermore, reports describing Ki-67 function are often contradictory, and it has only recently become clear that this proliferation marker is itself dispensable for cell proliferation. We discuss the unusual organization of the protein and its mRNA and how they relate to various models for its function. In particular, we focus on ways in which the intrinsically disordered structure of Ki-67 might aid in the assembly of the still-mysterious mitotic chromosome periphery compartment by controlling liquid-liquid phase separation of nucleolar proteins and RNAs.
| S-EPMC8354752 | biostudies-literature
Project description:ObjectiveTo build highly predictive performance models for glioma stratification with radiomics features from non-invasive MRI.MethodsT2-weighted fluid-attenuated inversion recovery (T2-FLAIR) imaging, diffusion-weighted MRI and diffusion kurtosis imaging were retrospectively collected for 139 glioma cases (2 with grade I, 67 with grade II, 36 with grade III and 34 with grade IV disease). Multi-parameter maps, including the apparent diffusion coefficient (ADC), mean diffusion coefficient (Dmean), fractional anisotropy (FA), and mean kurtosis (MK), were co-registered to T2-FLAIR, and 431 radiomics features for each were extracted within manually segmented tumour regions. Partial correlation analysis revealed correlations between radiomics features and glioma stratification factors (tumour grades and Ki-67 LI). Predictive models were built with adjusted-imbalanced logistic regression.ResultsMK radiomics features were more closely correlated with glioma stratification than other modalities analysed. The maximum R in MK was 0.52 for tumour grade and 0.56 for Ki-67 index (compared with 0.36 and 0.34 in FA, and 0.43 and 0.37 in ADC, and 0.48 and 0.42 in T2-FLAIR). The best predictive models for grade II vs. III, grade II vs. IV, low-grade vs. high-grade gliomas and positive vs. highly positive Ki-67 LI were obtained by combining multi-parameter MR radiomics features with AUCs of 0.858, 0.966, 0.853 and 0.870, respectively. However, for grade III vs. IV gliomas, the model obtained from MK radiomics features achieved the highest AUC (0.947), with excellent sensitivity and specificity.ConclusionCompared with the other modalities, MK showed closer correlations with tumour grade and Ki-67 LI. Combined radiomics models integrating multi-parameter MRI allow for the generation of highly predictive models for glioma stratification.
| S-EPMC8430185 | biostudies-literature
Project description:BackgroundThe Ki-67 index is an indicator of proliferation and aggressive behavior in pituitary adenomas (PAs). This study aims to develop and validate a predictive nomogram for forecasting Ki-67 index levels preoperatively in PAs.MethodsA total of 439 patients with PAs underwent PA resection at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020; they were enrolled in this retrospective study and were classified randomly into a training cohort (n = 300) and a validation cohort (n = 139). A range of clinical, radiological, and laboratory characteristics were collected. The Ki-67 index was classified into the low Ki-67 index (<3%) and the high Ki-67 index (≥3%). Least absolute shrinkage and selection operator algorithm and uni- and multivariate logistic regression analyses were applied to identify independent risk factors associated with Ki-67. A nomogram was constructed to visualize these risk factors. The receiver operation characteristic curve and calibration curve were computed to evaluate the predictive performance of the nomogram model.ResultsAge, primary-recurrence subtype, maximum dimension, and prolactin were included in the nomogram model. The areas under the curve (AUCs) of the nomogram model were 0.694 in the training cohort and 0.658 in the validation cohort. A well-fitted calibration curve was also generated for the nomogram model. A subgroup analysis revealed stable predictive performance for the nomogram model. A correlation analysis revealed that age (R = -0.23; p < 0.01), maximum dimension (R = 0.17; p < 0.01), and prolactin (R = 0.16; p < 0.01) were all significantly correlated with the Ki-67 index level.ConclusionsAge, primary-recurrence subtype, maximum dimension, and prolactin are independent predictors for the Ki-67 index level. The current study provides a novel and feasible nomogram, which can further assist neurosurgeons to develop better, more individualized treatment strategies for patients with PAs by predicting the Ki-67 index level preoperatively.
| S-EPMC8200848 | biostudies-literature