Optimizing the use of Ki-67 proliferative index as a prognostic biomarker in meningiomas using digital analysis.

OBJECTIVE: Ki-67 immunohistochemistry is widely used as a prognostic marker in meningiomas, but visual estimations tend to be imprecise. Whether the average Ki-67 over an entire slide, a particular block, or areas of high staining (hotspots) is prognostic for recurrence-free survival (RFS) and overall survival (OS) is unknown. This study aimed to generate evidence-based recommendations for the optimal use of Ki-67 immunohistochemistry in the workup of meningiomas. METHODS: All tissue blocks from a retrospective cohort of 221 patients with primary meningioma (141 WHO grade 1, 64 WHO grade 2, 16 WHO grade 3) were immunostained for Ki-67 and scanned using automated digital analysis software. QuPath was used to quantify the average Ki-67 proliferation index per slide as well as the Ki-67 hotspot in a 2.2-mm2 area within each slide. The best block was defined subjectively by a neuropathologist as the most representative tissue block from each case. The pathology report Ki-67 was determined by visual estimation. Age, sex, WHO grade, extent of resection, tumor location, and quantitative Ki-67 labeling were tested to determine risk factors for RFS and OS. RESULTS: Multivariable analyses demonstrated that WHO grade 2 (HR 2.42, p = 0.018), subtotal resection (HR 8.16, p < 0.0001), near-total resection (HR 2.24, p = 0.041), QuPath Ki-67 averaged across all blocks (HR per % increase = 1.72, p = 0.030), and pathology report Ki-67 (HR per % increase = 1.05, p = 0.0026) were associated with shorter RFS. The average Ki-67 in the best block, maximum across all slides, and maximum hotspot in the best block were not associated with RFS. Only male sex was independently associated with shorter OS (HR 8.52, p = 0.0003). The pathology report Ki-67 was, on average, 6.5 times higher than the QuPath average. CONCLUSIONS: These data on Ki-67 in meningiomas indicate the following: 1) visual estimation substantially overestimates Ki-67, 2) digital quantification of average Ki-67 across all tissue blocks provides more prognostic information than small hotspot regions or an entire single block, and 3) Ki-67 is not informative for OS. The results suggest that best practices for incorporating Ki-67 into meningioma prognostication include digital quantification of average Ki-67 over multiple blocks.

Prediction of Oncotype DX Recurrence Score Based on Systematic Evaluation of Ki-67 Scores in Hormone Receptor-Positive Early Breast Cancer.

PURPOSE: Oncotype DX (ODX) predicts the risk of recurrence and benefits of adding chemotherapy for patients with estrogen receptor positive (ER+)/human epidermal growth factor receptor 2 negative (HER2-) early-stage breast cancer. We aimed to develop a simplified scoring system using readily available clinicopathological parameters to predict a high-risk ODX recurrence score (RS) while minimizing reproducibility issues regarding Ki-67 index evaluation methods. METHODS: We enrolled 300 patients with ER+/HER2- early breast cancer, for whom ODX RS data were available in the test set. Using the QuPath image analysis platform, we systematically evaluated the average, hotspot, and hottest spot Ki-67 scores in the test set. Logistic regression analyses were conducted to establish a predictive scoring system for high-risk ODX RS. An independent validation set comprising 117 patients over different periods was established. RESULTS: Factors such as age ≤ 50 years, invasive ductal carcinoma tumor type, histologic grade 2 or 3, tumor necrosis, progesterone receptor negativity, and a high Roche-analyzed Ki-67 score (> 20) were associated with high-risk ODX RS. These variables were incorporated into our scoring system. The area under the curve of the scoring system was 0.8057. When applied to both the test and validation sets with a cutoff value of 3, the sensitivity of our scoring system was 92%. CONCLUSION: We successfully developed a scoring system based on the systematic evaluation of Ki-67 scoring methods. We believe that our user-friendly predictive scoring system for high risk ODX RS could help clinicians in identifying patients who may or may require additional ODX testing.

MRI-based radiomics signatures for preoperative prediction of Ki-67 index in primary central nervous system lymphoma.

PURPOSE: The aim of this study was to develop and validate radiomics signatures based on MRI for preoperative prediction of Ki-67 proliferative index (PI) expression in primary central nervous system lymphoma (PCNSL). METHODS: A total of 341 patients with PCNSL were retrospectively analyzed, including 286 patients in one center as the training set and 55 patients in another two centers as the external validation set. Radiomics features were extracted and selected from preoperative contrast-enhanced T1-weighted images, fluid attenuation inversion recovery to build radiomics signatures according to the Ki-67 PI. The predictive performances of the radiomics model were evaluated using four classifiers including random forest, K-Nearest Neighbors, Neural Network and Decision Tree. A combined model was built by incorporating radiomics signature, clinical variables and MRI radiological characteristics using multivariate logistic regression analysis, and a nomogram was established to predict the expression of Ki-67 individually. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: Radiomics signatures were independent predictors of the expression level of Ki-67 (OR: 2.523, P < 0.001). RF radiomics models had the highest accuracy (0.934 in the training set and 0.811 in the external validation set) and F1 Score (0.920 in the training set and 0.836 in the external validation set). The clinic-radiologic-radiomics nomogram showed better predictive performance with AUCs of 0.877(95 % CI: 0.837-0.918) in the training set and 0.866(95 % CI: 0.774-0.957) in the external validation set. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. CONCLUSIONS: Nomograms integrating MRI-based radiomics and clinical-radiological characteristics could effectively predict Ki-67 PI in primary PCNSL.

Peer-to-peer validation of Ki-67 scoring in a pathology quality circle as a tool to assess interobserver variability: are we better than we thought?

Ki-67, a nuclear protein expressed in all stages of cellular proliferation, is a valuable tool to assess tumor proliferation and has been linked to more aggressive tumor behavior. However, interlaboratory staining heterogeneity and inter-observer variability challenge its reproducibility. Round Robin tests are a suitable tool to standardize and harmonize immunohistochemical and molecular analyses in histopathology. The study investigates the interrater and interlaboratory reproducibility of Ki-67-scoring using both manual and automated approaches. Unstained TMA slides comprising diverse tumor types (breast cancer, neuroendocrine tumors, lymphomas, and head and neck squamous cell carcinoma) were distributed to six pathology laboratories, each employing their routine staining protocols. Manual and automated scoring methods were applied, and interrater and interlaboratory agreement assessed using intraclass correlation coefficients (ICC). The results highlight good-to-excellent reliability overall, with automated scoring demonstrating higher consistency (ICC 0.955) than manual scoring (ICC 0.871). Results were more variable when looking at the individual entities. Reliability remained good for lymphomas (ICC 0.878) and breast cancer (ICC 0.784) and was poor in well-differentiated neuroendocrine tumors (ICC 0.354). This study clearly advocates standardized practices and training to ensure consistency in Ki-67-assessment, and it demonstrates that this can be achieved in a peer-to-peer approach in local quality-circles.

Subgrading of G2 Pancreatic Neuroendocrine Tumors as 2A (Ki67 3% to < 10%) Versus 2B (10% to ≤ 20%) Identifies Behaviorally Distinct Subsets in Keeping with the Evolving Management Protocols.

BACKGROUND: Grade 1/2 PanNETs are mostly managed similarly, typically without any adjunct treatment with the belief that their overall metastasis rate is low. In oncology literature, Ki67-index of 10% is increasingly being used as the cutoff in stratifying patients to different protocols, although there are no systematic pathology-based studies supporting this approach. METHODS: Ki67-index was correlated with clinicopathologic parameters in 190 resected PanNETs. A validation cohort (n = 145) was separately analyzed. RESULTS: In initial cohort, maximally selected rank statistics method revealed 12% to be the discriminatory cutoff (close to 10% rule of thumb). G2b cases had liver/distant metastasis rate of almost threefold higher than that of G2a and showed significantly higher frequency of all histopathologic signs of aggressiveness (tumor size, perineural/vascular invasion, infiltrative growth pattern, lymph node metastasis). In validation cohort, these figures were as striking. When all cases were analyzed together, compared with G1, the G2b category had nine times higher liver/distant metastasis rate (6.1 vs. 58.5%; p < 0.001) and three times higher lymph node metastasis rate (20.5 vs. 65.1%; p < 0.001). CONCLUSIONS: G2b PanNETs act very similar to G3, supporting management protocols that regard them as potential therapy candidates. Concerning local management, metastatic behavior in G2b cases indicate they may not be as amenable for conservative approaches, such as watchful waiting or enucleation. This substaging should be considered into diagnostic guidelines, and clinical trials need to be devised to determine the more appropriate management protocols for G2b (10% to ≤ 20%) group, which shows liver/distant metastasis in more than half of the cases, which at minimum warrants closer follow-up.

Immunohistochemical Expression of Ki-67 and p53 and Their Prognostic Role in Ameloblastoma: A Longitudinal Study.

Objectives: Ameloblastoma, comprising approximately 11% of all odontogenic tumors, is a locally aggressive tumor with a high recurrence rate. This study aimed to assess the immunohistochemical expression of Ki-67 and p53 and their association with clinical and pathological factors among patients with ameloblastoma. Methods: Retrospective follow-up data of patients histologically confirmed with ameloblastoma at Makerere College of Health Sciences in Kampala, Uganda from January 2012 to December 2018 were retrieved. Factors associated with Ki-67 and p53 immunohistochemical expression were determined using one-way one-way analysis of variance. Chi-square and Fisher's exact statistical tests were used to assess factors associated with recurrence. A two-tailed p < 0.05 was considered statistically significant. Results: A total of 40 patients confirmed histologically with ameloblastoma were included in the analysis. The majority (62.5%) of cases were of the conventional type of ameloblastoma. The expressions of Ki-67 and p53 were 52.5% and 85.0%, respectively. Recurrence was found in 47.5% of patients and it was associated with conventional histological type (p=0.042), segmental resection (p < 0.001), tumor size (p < 0.001), and high p53 expression (p=0.041). Conclusions: Almost half the cases in this study had recurrence. The immunohistochemical expression of p53 was significantly higher than that of Ki-67.

Amide Proton Transfer-Weighted Imaging in Assessing the Aggressive and Proliferative Potential of Bladder Cancer.

BACKGROUND: Ki-67 and human epidermal growth factor receptor 2 (HER2) are known oncogenes involved in bladder cancer (BCa) patient risk stratification. Preoperative assessment of their expression level can assist in clinical treatment decision-making. Recently, amide proton transfer-weighted (APTw) MRI has shown promising potential in the diagnosis of several malignancies. However, few studies reported the value of APTw imaging in evaluating Ki-67 and HER2 status of BCa. PURPOSE: To investigate the feasibility of APTw MRI in assessing the aggressive and proliferative potential regarding the expression levels of Ki-67 and HER2 in BCa. STUDY TYPE: Retrospective. SUBJECTS: 114 patients (mean age, 64.78 ± 11.93 [SD] years; 97 men) were studied. FIELD STRENGTH/SEQUENCE: APTw MRI acquired by a three-dimensional fast-spin-echo sequence at 3.0 T MRI system. ASSESSMENT: Patient pathologic findings, included histologic grade and the expression status of Ki-67 and HER2, were reviewed by one uropathologist. The APTw values of BCa were independently measured by two radiologists and were compared between high-/low-tumor grade group, high-/low-Ki-67 expression group, and high-/low-HER2 expression group. STATISTICAL TESTS: The interclass correlation coefficient, independent sample t-test, Mann-Whitney U test, Spearman's rank correlation, and receiver operating characteristic curve (ROC) analysis were used. P < 0.05 was considered statistically significant. RESULTS: Significantly higher APTw values were found in high-grade BCa patients (7.72% vs. 4.29%, P < 0.001), high-Ki-67 expression BCa patients (8.40% vs. 3.25%, P < 0.001) and HER2 positive BCa patients (8.24% vs. 5.40%, P = 0.001). APTw values were positively correlated with Ki-67 (r = 0.769) and HER2 (r = 0. 356) expression status. The area under the ROC curve of the APTw values for detecting Ki-67 and HER2 expression status were 0.883 (95% CI: 0.790-0.945) and 0.713 (95% CI: 0.592-0.816), respectively. DATA CONCLUSIONS: APTw MRI is a potential method to assess the biological and proliferation potential of BCa. TECHNICAL EFFICACY: Stage 2.

Prognostic and Clinical Significance of PD-L1, EGFR and Androgen Receptor (AR) Expression in Triple-Negative Breast Cancer (TNBC) Patients.

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and is associated with high recurrence rates, a high incidence of distant metastases and poor overall survival. The aim of this study was to investigate the role of PD-L1, EGFR and AR expression in TNBC promotion and progression. To that end, we analyzed the immunohistochemical expression of these genes in 125 TNBC patients and their relation to clinicopathological parameters and survival. An elevated expression of PD-L1 was significantly correlated with higher tumor and nuclear grade, while a low expression was correlated with loco-regional recurrence without any influence on survival. Contrary to this, the expression of AR showed a positive impact on the DFI and a negative association with tumor grade. Furthermore, PD-L1 and AR demonstrated simultaneous expression, and further co-expression analysis revealed that a positive expression of PD-L1/AR notably correlates with tumor and nuclear grade and has a significant impact on a longer DFI and OS, while a negative PD-L1/AR expression is significantly associated with metastases. Therefore, our results suggest that positive PD-L1/AR expression is beneficial for TNBC patients. In addition, an elevated expression of EGFR contributes to metastases and a worse DFI and OS. In conclusion, we think that low PD-L1/low AR/high EGFR expression followed by high Ki67 expression constitutes a 'high risk' profile of TNBC.

Findings and Challenges in Replacing Traditional Uterine Cervical Cancer Diagnosis with Molecular Tools in Private Gynecological Practice in Mexico.

We have been encouraging practicing gynecologists to adopt molecular diagnostics tests, PCR, and cancer biomarkers, as alternatives enabled by these platforms, to traditional Papanicolaou and colposcopy tests, respectively. An aliquot of liquid-based cytology was used for the molecular test [high-risk HPV types, (HR HPV)], another for the PAP test, and one more for p16/Ki67 dual-stain cytology. A total of 4499 laboratory samples were evaluated, and we found that 25.1% of low-grade samples and 47.9% of high-grade samples after PAP testing had a negative HR HPV-PCR result. In those cases, reported as Pap-negative, 22.1% had a positive HR HPV-PCR result. Dual staining with p16/Ki67 biomarkers in samples was positive for HR HPV, and 31.7% were also positive for these markers. Out of the PCR results that were positive for any of these HR HPV subtypes, n 68.3%, we did not find evidence for the presence of cancerous cells, highlighting the importance of performing dual staining with p16/Ki67 after PCR to avoid unnecessary colposcopies. The encountered challenges are a deep-rooted social reluctance in Mexico to abandon traditional Pap smears and the opinion of many specialists. Therefore, we still believe that colposcopy continues to be a preferred procedure over the dual-staining protocol.

Multiparametric MRI-based radiomics approach with deep transfer learning for preoperative prediction of Ki-67 status in sinonasal squamous cell carcinoma.

Purpose: Based on comparison of different machine learning (ML) models, we developed the model that integrates traditional hand-crafted (HC) features and ResNet50 network-based deep transfer learning (DTL) features from multiparametric MRI to predict Ki-67 status in sinonasal squamous cell carcinoma (SNSCC). Methods: Two hundred thirty-one SNSCC patients were retrospectively reviewed [training cohort (n = 185), test cohort (n = 46)]. Pathological grade, clinical, and MRI characteristics were analyzed to choose the independent predictor. HC and DTL radiomics features were extracted from fat-saturated T2-weighted imaging, contrast-enhanced T1-weighted imaging, and apparent diffusion coefficient map. Then, HC and DTL features were fused to formulate the deep learning-based radiomics (DLR) features. After feature selection and radiomics signature (RS) building, we compared the predictive ability of RS-HC, RS-DTL, and RS-DLR. Results: No independent predictors were found based on pathological, clinical, and MRI characteristics. After feature selection, 42 HC and 10 DTL radiomics features were retained. The support vector machine (SVM), LightGBM, and ExtraTrees (ET) were the best classifier for RS-HC, RS-DTL, and RS-DLR. In the training cohort, the predictive ability of RS-DLR was significantly better than those of RS-DTL and RS-HC (p< 0.050); in the test set, the area under curve (AUC) of RS-DLR (AUC = 0.817) was also the highest, but there was no significant difference of the performance between DLR-RS and HC-RS. Conclusions: Both the HC and DLR model showed favorable predictive efficacy for Ki-67 expression in patients with SNSCC. Especially, the RS-DLR model represented an opportunity to advance the prediction ability.

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project.

BACKGROUND: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. PATIENTS AND METHODS: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. RESULTS: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. CONCLUSIONS: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.

Nomogram for the preoperative prediction of Ki-67 expression and prognosis in stage IA lung adenocarcinoma based on clinical and multi-slice spiral computed tomography features.

OBJECTIVE: This study developed and validated a nomogram utilizing clinical and multi-slice spiral computed tomography (MSCT) features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma. Additionally, we assessed the predictive accuracy of Ki-67 expression levels, as determined by our model, in estimating the prognosis of stage IA lung adenocarcinoma. MATERIALS AND METHODS: We retrospectively analyzed data from 395 patients with pathologically confirmed stage IA lung adenocarcinoma. A total of 322 patients were divided into training and internal validation groups at a 6:4 ratio, whereas the remaining 73 patients composed the external validation group. According to the pathological results, the patients were classified into high and low Ki-67 labeling index (LI) groups. Clinical and CT features were subjected to statistical analysis. The training group was used to construct a predictive model through logistic regression and to formulate a nomogram. The nomogram's predictive ability and goodness-of-fit were assessed. Internal and external validations were performed, and clinical utility was evaluated. Finally, the recurrence-free survival (RFS) rates were compared. RESULTS: In the training group, sex, age, tumor density type, tumor-lung interface, lobulation, spiculation, pleural indentation, and maximum nodule diameter differed significantly between patients with high and low Ki-67 LI. Multivariate logistic regression analysis revealed that sex, tumor density, and maximum nodule diameter were significantly associated with high Ki-67 expression in stage IA lung adenocarcinoma. The calibration curves closely resembled the standard curves, indicating the excellent discrimination and accuracy of the model. Decision curve analysis revealed favorable clinical utility. Patients with a nomogram-predicted high Ki-67 LI exhibited worse RFS. CONCLUSION: The nomogram utilizing clinical and CT features for the preoperative prediction of Ki-67 expression in stage IA lung adenocarcinoma demonstrated excellent performance, clinical utility, and prognostic significance, suggesting that this nomogram is a noninvasive personalized approach for the preoperative prediction of Ki-67 expression.

Immunoreactivity of LMO7 and other molecular markers as potential prognostic factors in oropharyngeal squamous cell carcinoma.

BACKGROUND: Despite the better prognosis associated with human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC), some patients experience relapse and succumb to the disease; thus, there is a need for biomarkers identifying these patients for intensified treatment. Leucine-rich repeats and immunoglobulin-like domain (LRIG) protein 1 is a negative regulator of receptor tyrosine kinase signaling and a positive prognostic factor in OPSCC. Studies indicate that LRIG1 interacts with the LIM domain 7 protein (LMO7), a stabilizer of adherence junctions. Its role in OPSCC has not been studied before. METHODS: A total of 145 patients diagnosed with OPSCC were enrolled. Immunohistochemical LMO7 expression and staining intensity were evaluated in the tumors and correlated with known clinical and pathological prognostic factors, such as HPV status and LRIG1, CD44, Ki67, and p53 expression. RESULTS: Our results show that high LMO7 expression is associated with significantly longer overall survival (OS) (p = 0.044). LMO7 was a positive prognostic factor for OS in univariate analysis (HR 0.515, 95% CI: 0.267-0.994, p = 0.048) but not in multivariate analysis. The LMO7 expression correlated with LRIG1 expression (p = 0.048), consistent with previous findings. Interestingly, strong LRIG1 staining intensity was an independent negative prognostic factor in the HPV-driven group of tumors (HR 2.847, 95% Cl: 1.036-7.825, p = 0.043). CONCLUSIONS: We show for the first time that high LMO7 expression is a positive prognostic factor in OPSCC, and we propose that LMO7 should be further explored as a biomarker. In contrast to previous reports, LRIG1 expression was shown to be an independent negative prognostic factor in HPV-driven OPSCC.

Fe3O4 and Fe3O4core Aushell-based Hyperthermia Reduces Expression of Proliferation Markers Ki-67, TOP2A and TPX2 in a Human Breast Cancer Cell Line.

BACKGROUND/AIM: Hyperthermia represents an adjuvant local anticancer strategy which relies on the increase of temperature beyond the physiological level. In this study, we investigated the anticancer potential of Fe3O4 and Fe3O4core Aushell nanoparticles as hyperthermic agents in terms of cytotoxicity and studied the expression of cellular markers of proliferation (changes in mRNA levels via real-time polymerase chain reaction). MATERIALS AND METHODS: The human breast cancer cell line SK-BR-1 was incubated with either Fe3O4 or Fe3O4core Aushell nanoparticles stabilized with tryptophan, prior to hyperthermia treatment. The normal HEK293 cell line was used as a control. Toxicity was determined using the 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium assay to estimate possible toxic effects of the tested nanoparticles. After RNA extraction and cDNA synthesis, mRNA expression of three indicators of proliferation, namely marker of proliferation Ki-67, DNA topoisomerase II alpha (TOP2A) and TPX2 microtubule nucleation factor (TPX2), was investigated. RESULTS: At each concentration tested, Fe3O4core Aushell nanoparticles showed greater toxicity compared to Fe3O4, while SK-BR-3 cells were more susceptible to their cytotoxic effects compared to the HEK293 cell line. The expression of Ki-67, TOP2A and TPX2 was reduced in SK-BR-3 cells by both Fe3O4 or Fe3O4core Aushell nanoparticles compared to untreated cells, while the only observed change in HEK293 cells was the up-regulation of TOP2A. CONCLUSION: Both Fe3O4core Aushell and Fe3O4 NPs exhibit increased cytotoxicity to the cancer cell line tested (SK-BR-3) compared to HEK293 cells. The down-regulation in SK-BR-3 cells of the three proliferative markers studied, Ki-67, TOP2A and TPX2, after incubation with NPs suggests that cells that survived thermal destruction were not actively proliferating.

Evaluation of Microvascular Density in Glioblastomas in Relation to p53 and Ki67 Immunoexpression.

Glioblastoma is the most aggressive tumor in the central nervous system, with a survival rate of less than 15 months despite multimodal therapy. Tumor recurrence frequently occurs after removal. Tumoral angiogenesis, the formation of neovessels, has a positive impact on tumor progression and invasion, although there are controversial results in the specialized literature regarding its impact on survival. This study aims to correlate the immunoexpression of angiogenesis markers (CD34, CD105) with the proliferation index Ki67 and p53 in primary and secondary glioblastomas. This retrospective study included 54 patients diagnosed with glioblastoma at the Pathology Department of County Emergency Clinical Hospital Târgu Mureș. Microvascular density was determined using CD34 and CD105 antibodies, and the results were correlated with the immunoexpression of p53, IDH1, ATRX and Ki67. The number of neoformed blood vessels varied among cases, characterized by different shapes and calibers, with endothelial cells showing modified morphology and moderate to marked pleomorphism. Neovessels with a glomeruloid aspect, associated with intense positivity for CD34 or CD105 in endothelial cells, were observed, characteristic of glioblastomas. Mean microvascular density values were higher for the CD34 marker in all cases, though there were no statistically significant differences compared to CD105. Mutant IDH1 and ATRX glioblastomas, wild-type p53 glioblastomas, and those with a Ki67 index above 20% showed a more abundant microvascular density, with statistical correlations not reaching significance. This study highlighted a variety of percentage intervals of microvascular density in primary and secondary glioblastomas using immunohistochemical markers CD34 and CD105, respectively, with no statistically significant correlation between evaluated microvascular density and p53 or Ki67.

Immunohistochemical Analysis of Dentigerous Cysts and Odontogenic Keratocysts Associated with Impacted Third Molars-A Systematic Review.

OBJECTIVE: This systematic review investigates the diagnostic, prognostic, and therapeutic implications of immunohistochemical markers in dentigerous cysts (DCs) and odontogenic keratocysts (OKCs) associated with impacted third molars. MATERIALS AND METHODS: A comprehensive search strategy was employed across major databases including MEDLINE/PubMed, EMBASE, and Web of Science, from the inception of the databases to March 2024. Keywords and Medical Subject Heading (MeSH) terms such as "dentigerous cysts", "odontogenic keratocysts", "immunohistochemistry", "Ki-67", and "p53" were used. The PRISMA 2020 guidelines were followed to ensure methodological rigor. Inclusion criteria encompassed studies on humans and animals providing definitive diagnoses or specific signs and symptoms related to DCs and OKCs, with results on protein expression derived from immunohistochemistry, immune antibody, proteomics, or protein expression methods. RESULTS: Of the 159 studies initially identified, 138 met the inclusion criteria. Our analysis highlighted significantly higher expressions of Ki-67 (22.1% ± 4.7 vs. 10.5% ± 3.2, p < 0.001), p53 (15.3% ± 3.6 vs. 5.2% ± 1.9, p < 0.001), and Bcl-2 (18.4% ± 3.2 vs. 8.7% ± 2.4, p < 0.001) in OKCs compared to DCs, indicating a higher proliferative index, increased cellular stress, and enhanced anti-apoptotic mechanisms in OKCs. Additionally, PCNA levels were higher in OKCs (25.6% ± 4.5 vs. 12.3% ± 3.1, p < 0.001). Genetic mutations, particularly in the PTCH1 gene, were frequently observed in OKCs, underscoring their aggressive behavior and potential malignancy. CONCLUSIONS: The findings emphasize the significant role of immunohistochemical markers in distinguishing between DCs and OKCs, with elevated levels of Ki-67, p53, Bcl-2, and PCNA in OKCs suggesting a higher potential for growth and recurrence. Genetic insights, including PTCH1 mutations, further support the need for personalized treatment approaches. These markers enhance diagnostic accuracy and inform targeted therapeutic strategies, potentially transforming patient management in oral and maxillofacial surgery.

Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm.

Finding appropriate image analysis techniques for a particular purpose can be difficult. In the context of the analysis of immunocytochemistry images, where the key information lies in the number of nuclei containing co-localised fluorescent signals from a marker of interest, researchers often opt to use manual counting techniques because of the paucity of available tools. Here, we present the development and validation of the Fluorescence Imaging of Nuclear Staining (FINS) algorithm for the quantification of fluorescent signals from immunocytochemically stained cells. The FINS algorithm is based on a variational segmentation of the nuclear stain channel and an iterative thresholding procedure to count co-localised fluorescent signals from nuclear proteins in other channels. We present experimental results comparing the FINS algorithm to the manual counts of seven researchers across a dataset of three human primary cell types which are immunocytochemically stained for a nuclear marker (DAPI), a biomarker of cellular proliferation (Ki67), and a biomarker of DNA damage (γH2AX). The quantitative performance of the algorithm is analysed in terms of consistency with the manual count data and acquisition time. The FINS algorithm produces data consistent with that achieved by manual counting but improves the process by reducing subjectivity and time. The algorithm is simple to use, based on software that is omnipresent in academia, and allows data review with its simple, intuitive user interface. We hope that, as the FINS tool is open-source and is custom-built for this specific application, it will streamline the analysis of immunocytochemical images.

CENPF May Act as a Novel Marker and Highlight the Influence of Pericyte in Infantile Hemangioma.

Infantile hemangioma (IH), a benign microvascular tumor, is marked by early and extensive proliferation of immature hemangioma endothelial cells (Hem-ECs) that naturally regress through differentiation into fibroblasts or adipocytes. However, a challenge persists, as the unique biological behavior of IH remains elusive, despite its general sensitivity to propranolol treatment. Recent evidence suggests that abnormal volume proliferation in IH is primarily attributed to the accumulation of hemangioma pericytes (Hem-Pericytes), in addition to Hem-ECs. Centromere protein F (CENPF) is involved in regulating mitotic processes and has been associated with malignant tumor cell proliferation. It is a key player in maintaining genomic stability during cell division. Our findings revealed specific expression of CENPF in Hem-Pericytes, with a proliferation index (PI) approximately half that of Ki67 (3.28 vs 6.97%) during the proliferative phase of IH. This index decreased rapidly in the involuting phase (P < .05), suggesting that the contribution of pericytes to IH development was comparable to that of Hem-ECs. Tumor expansion and shrinkage may be due to the proliferation, reduction, and differentiation of Hem-Pericytes. In conclusion, we speculate CENPF as a novel marker for clinical pathological diagnosis and a potential therapeutic target, fostering advancements in drug development.

The value of the malignant subregion-based texture analysis in predicting the Ki-67 status in breast cancer.

Objective: To evaluate the value of the malignant subregion-based texture analysis in predicting Ki-67 status in breast cancer. Materials and methods: The dynamic contrast-enhanced magnetic resonance imaging data of 119 histopathologically confirmed breast cancer patients (81 patients with high Ki-67 expression status) from January 2018 to February 2023 in our hospital were retrospectively collected. According to the enhancement curve of each voxel within the tumor, three subregions were divided: washout subregion, plateau subregion, and persistent subregion. The washout subregion and the plateau subregion were merged as the malignant subregion. The texture features of the malignant subregion were extracted using Pyradiomics software for texture analysis. The differences in texture features were compared between the low and high Ki-67 expression cohorts and then the receiver operating characteristic (ROC) curve analysis to evaluate the predictive performance of texture features on Ki-67 expression. Finally, a support vector machine (SVM) classifier was constructed based on differential features to predict the expression level of Ki-67, the performance of the classifier was evaluated using ROC analysis and confirmed using 10-fold cross-validation. Results: Through comparative analysis, 51 features exhibited significant differences between the low and high Ki-67 expression cohorts. Following feature reduction, 5 features were selected to build the SVM classifier, which achieved an area under the ROC curve (AUC) of 0.77 (0.68-0.87) for predicting the Ki-67 expression status. The accuracy, sensitivity, and specificity were 0.76, 0.80, and 0.68, respectively. The average AUC from the 10-fold cross-validation was 0.72 ± 0.14. Conclusion: The texture features of the malignant subregion in breast cancer were potential biomarkers for predicting Ki-67 expression level in breast cancer, which might be used to precisely diagnose and guide the treatment of breast cancer.

Noninvasive assessment of Ki-67 labeling index in glioma patients based on multi-parameters derived from advanced MR imaging.

Purpose: To investigate the predictive value of multi-parameters derived from advanced MR imaging for Ki-67 labeling index (LI) in glioma patients. Materials and Methods: One hundred and nine patients with histologically confirmed gliomas were evaluated retrospectively. These patients underwent advanced MR imaging, including dynamic susceptibility-weighted contrast enhanced MR imaging (DSC), MR spectroscopy imaging (MRS), diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), before treatment. Twenty-one parameters were extracted, including the maximum, minimum and mean values of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), relative apparent diffusion coefficient (rADC), relative fractional anisotropy (rFA) and relative mean diffusivity (rMD) respectively, and ration of choline (Cho)/creatine (Cr), Cho/N-acetylaspartate (NAA) and NAA/Cr. Stepwise multivariate regression was performed to build multivariate models to predict Ki-67 LI. Pearson correlation analysis was used to investigate the correlation between imaging parameters and the grade of glioma. One-way analysis of variance (ANOVA) was used to explore the differences of the imaging parameters among the gliomas of grade II, III, and IV. Results: The multivariate regression showed that the model of five parameters, including rCBVmax (RC=0.282), rCBFmax (RC=0.151), rADCmin (RC= -0.14), rFAmax (RC=0.325) and Cho/Cr ratio (RC=0.157) predicted the Ki-67 LI with a root mean square (RMS) error of 0. 0679 (R2 = 0.8025).The regression check of this model showed that there were no multicollinearity problem (variance inflation factor: rCBVmax, 3.22; rCBFmax, 3.14; rADCmin, 1.96; rFAmax, 2.51; Cho/Cr ratio, 1.64), and the functional form of this model was appropriate (F test: p=0.682). The results of Pearson correlation analysis showed that the rCBVmax, rCBFmax, rFAmax, the ratio of Cho/Cr and Cho/NAA were positively correlated with Ki-67 LI and the grade of glioma, while the rADCmin and rMDmin were negatively correlated with Ki-67 LI and the grade of glioma. Conclusion: Combining multiple parameters derived from DSC, DTI, DWI and MRS can precisely predict the Ki-67 LI in glioma patients.