Reevaluation of negative cervical conizations: Frequency, diagnostic errors, risk factors and management.

OBJECTIVE: Cervical conization is an effective treatment for precancerous lesions. However, in cases where no high-grade lesion is identified in the surgical specimen, managing these patients may be challenging due to the absence of established follow-up protocols for negative conizations. This study aimed to assess the negative conization rates at our institution by histopathological review, identify diagnostic errors, possible risk and recurrence factors and propose follow-up strategies for this group of patients. METHODS: A retrospective study from January-2010 to December-2020 analyzed patients with negative conization including all surgical techniques and procedure indications. Biopsy and cervical conizations slides were reviewed and patients who kept a negative result underwent deeper levels sectioning of the paraffin blocks with immunohistochemical stains application: p16, Ki-67 and geminin. Data were compared with a control group composed by 29 women with CIN3. RESULTS: Out of 1022 conizations, 186 were negative (18.1%), with 151 cases selected for the study after excluding 35 patients. Following pathology review, 4 patients were excluded due to false-positive cervical biopsy results, 16 for false-negative conization results and 9 for hidden dysplasia identified after deeper sectioning. The remaining 122 patients were considered truly negative cones (11.9%) and exhibited IHC staining with p16 positive in 20.4% of cases, low Ki-67 expression, and low geminin score in most cases. Specimens with CIN 1 had higher prevalence of p16 staining, Ki-67 expression and geminin score when compared to absence of neoplasia, nevertheless geminin had no statistical difference. Older age, higher parity and IHC pattern with negative p16, low Ki-67 and geminin expressions were identified as risk factors for negative cones (p<0.05). Only 10 patients recurred for high-grade lesions, with no statistically significant risk factors identified. CONCLUSIONS: The negative conization rate was 11.9%, with diagnostic errors identified across pre-surgical biopsy, cone specimen, and deeper levels. Risk factors included older age, higher parity, low expression of p16, Ki-67 and geminin (p<0.05). Recurrence represented 8.1% of the negative cones, without identification of statistically significant risk factors. Pathological review with deeper level sections and 2-year follow-up are recommended for patients with negative conizations.

3D amide proton transfer-weighted imaging may be useful for diagnosing early-stage breast cancer: a prospective monocentric study.

BACKGROUND: We investigated the value of three-dimensional amide proton transfer-weighted imaging (3D-APTWI) in the diagnosis of early-stage breast cancer (BC) and its correlation with the immunohistochemical characteristics of malignant lesions. METHODS: Seventy-eight women underwent APTWI and dynamic contrast-enhanced (DCE)-MRI. Pathological results were categorized as either benign (n = 43) or malignant (n = 37) lesions. The parameters of APTWI and DCE-MRI were compared between the benign and malignant groups. The diagnostic value of 3D-APTWI was evaluated using the area under the receiver operating characteristic curve (ROC-AUC) to establish a diagnostic threshold. Pearson's correlation was used to analyze the correlation between the magnetization transfer asymmetry (MTRasym) and immunohistochemical characteristics. RESULTS: The MTRasym and time-to-peak of malignancies were significantly lower than those of benign lesions (all p < 0.010). The volume transfer constant, rate constant, and wash-in and wash-out rates of malignancies were all significantly greater than those of benign lesions (all p < 0.010). ROC-AUCs of 3D-APTWI, DCE-MRI, and 3D-APTWI+DCE to differential diagnosis between early-stage BC and benign lesions were 0.816, 0.745, and 0.858, respectively. Only the difference between AUCAPT+DCE and AUCDCE was significant (p < 0.010). When a threshold of MTRasym for malignancy for 2.42%, the sensitivity and specificity of 3D-APTWI for BC diagnosis were 86.5% and 67.6%, respectively; MTRasym was modestly positively correlated with pathological grade (r = 0.476, p = 0.003) and Ki-67 (r = 0.419, p = 0.020). CONCLUSIONS: 3D-APTWI may be used as a supplementary method for patients with contraindications of DCE-MRI. MTRasym can imply the proliferation activities of early-stage BC. RELEVANCE STATEMENT: 3D-APTWI can be an alternative diagnostic method for patients with early-stage BC who are not suitable for contrast injection. KEY POINTS: • 3D-APTWI reflects the changes in the microenvironment of early-stage breast cancer. • Combined 3D-APTWI is superior to DCE-MRI alone for early-stage breast cancer diagnosis. • 3D-APTWI improves the diagnostic accuracy of early-stage breast cancer.

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas.

OBJECTIVES: To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI). MATERIALS AND METHODS: This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared. RESULTS: All ADCs were significantly higher in IDH mutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all). CONCLUSION: Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria. CLINICAL RELEVANCE STATEMENT: Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma. KEY POINTS: • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.

BRAF V600E mutation mediates invasive and growth features in ameloblastoma.

OBJECTIVES: Ameloblastoma (AM), a locally aggressive tumor with extensive growth capacity, causes significant damage to the jaw and affects facial appearance. Although the high prevalence of BRAF V600E mutation in AM is known, its specific impacts on patients with AM remain unclear. Thus, the present study investigated the role of BRAF V600E mutation, thereby focusing on its impact on AM invasion and growth. MATERIALS AND METHODS: Immunohistochemical analysis was used to compare BRAF V600E, MMP2, MMP9, and Ki-67 expressions in AM (n = 49), normal oral mucosa (NOM) (n = 10), and odontogenic keratocyst (OKC) (n = 15) tissues. AM was further classified according to the presence or absence of BRAF V600E. The relationship between BRAF V600E and invasion as well as growth was evaluated. In addition, correlation analysis was performed using immunohistochemistry and confirmed via double-labeling immunofluorescence. Finally, comparative analyses using mass spectrometry, immunohistochemistry, and immunofluorescence were performed to explore and identify underlying mechanisms. RESULTS: AM exhibited a higher incidence of BRAF V600E mutation than NOM and OKC. BRAF V600E expression was positively correlated with the invasion-associated proteins MMP2 and MMP9 and the growth-related protein Ki-67. Proteomic data revealed that BRAF V600E primarily activates the MAPK signaling pathway in AM, particularly driving the phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2). CONCLUSIONS: In summary, the findings suggested that the BRAF V600E mutation enhances the invasion and growth abilities of AM via the MAPK/ERK signaling pathway. Thus, targeting BRAF V600E or the MAPK/ERK pathway may be a potential AM therapy.

Changes in Invasive Breast Carcinomas after Neoadjuvant Chemotherapy Can Influence Adjuvant Therapeutic Decisions.

PURPOSE: Neoadjuvant chemotherapy (NACT) can change invasive breast carcinomas (IBC) and influence the patients' overall survival time (OS). We aimed to identify IBC changes after NACT and their association with OS. MATERIALS AND METHODS: IBC data in pre- and post-NACT samples of 86 patients were evaluated and associated with OS. RESULTS: Post-NACT tumors changed nuclear pleomorphism score (p=0.025); mitotic count (p=0.002); % of tumor-infiltrating inflammatory cells (p=0.016); presence of in situ carcinoma (p=0.001) and lymphovascular invasion (LVI; p=0.002); expression of estrogen (p=0.003), progesterone receptors (PR; p=0.019), and Ki67 (p=0.003). Immunohistochemical (IHC) profile changed in 26 tumors (30.2%, p=0.050). Higher risk of death was significatively associated with initial tumor histological grade III (hazard ratio [HR], 2.94), high nuclear pleomorphism (HR, 2.53), high Ki67 index (HR, 2.47), post-NACT presence of LVI (HR, 1.90), luminal B-like profile (HR, 2.58), pre- (HR, 2.26) and post-NACT intermediate mitotic count (HR, 2.12), pre- (HR, 4.45) and post-NACT triple-negative IHC profile (HR, 4.52). On the other hand, lower risk of death was significative associated with pre- (HR, 0.35) and post-NACT (HR, 0.39) estrogen receptor-positive, and pre- (HR, 0.37) and post-NACT (HR, 0.57) PR-positive. Changes in IHC profile were associated with longer OS (p=0.050). In multivariate analysis, pre-NACT grade III tumors and pre-NACT and post-NACT triple negative IHC profile proved to be independent factors for shorter OS. CONCLUSION: NACT can change tumor characteristics and biomarkers and impact on OS; therefore, they should be reassessed on residual samples to improve therapeutic decisions.

Characterization of parotid gland tumors: Whole-tumor histogram analysis of diffusion weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion - A pilot study.

PURPOSE: To investigate the diagnostic performance of histogram features of diffusion parameters in characterizating parotid gland tumors. METHOD: From December 2018 to January 2023, patients who underwent diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) were consecutively enrolled in this retrospective study. The histogram features of diffusion parameters, including apparent diffusion coefficient (ADC), diffusion coefficient (Dk), diffusion kurtosis (K), pure diffusion coefficient (D), pseudo-diffusion coefficient (DP), and perfusion fraction (FP) were analyzed. The Mann-Whitney U test was used for comparison between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs). Receiver operating characteristic curve and logistic regression analysis were used to identify the differential diagnostic performance. The Spearman's correlation coefficient was used to analyze the correlation between diffusion parameters and Ki-67 labeling index. RESULTS: For diffusion MRI, twenty-three histogram features of diffusion parameters showed significant differences between BPGTs and MPGTs (all P < 0.05). Compared with the DWI model, the IVIM model and combined model had better diagnostic specificity (58 %, 94 %, and 88 %, respectively; both corrected P < 0.001) and accuracy (64 %, 89 %, and 86 %, respectively; both corrected P = 0.006). The combined model was superior to the single DWI model with improved IDI (IDI improvement 0.25). Significant correlations were found between Ki-67 and ADCmean, Dkmean, Kmean, and Dmean (r = -0.57 to 0.53; all P < 0.05). CONCLUSIONS: Whole-tumor histogram analysis of IVIM and combined diffusion model could further improve the diagnostic performance for differentiating BPGTs from MPGTs.

Cervical Intraepithelial Neoplasia grade 2 biopsy: Do p16INK4a and Ki-67 biomarkers contribute to the decision to treat? A cross-sectional study

ABSTRACT BACKGROUND: Managing cervical intraepithelial neoplasia grade 2 (CIN2) is challenging, considering the CIN2 regression rate, perinatal risks associated with excisional procedures, and insufficient well-established risk factors to predict progression. OBJECTIVES: To determine the ability of p16INK4a and Ki-67 staining in biopsies diagnosed with CIN2 to identify patients with higher-grade lesions (CIN3 or carcinoma). DESIGN AND SETTING: Cross-sectional study conducted at a referral center for treating uterine cervical lesions. METHODS: In 79 women, we analyzed the correlation of p16INK4a and Ki-67 expression in CIN2 biopsies with the presence of a higher-grade lesions, as determined via histopathology in surgical specimens from treated women or via two colposcopies and two cytological tests during follow-up for untreated women with at least a 6-month interval. The expression of these two biomarkers was verified by at least two independent pathologists and quantified using digital algorithms. RESULTS: Thirteen (16.8%) women with CIN2 biopsy exhibited higher-grade lesions on the surgical excision specimen or during follow-up. p16INK4a expression positively and negatively predicted the presence of higher-grade lesions in 17.19% and 86.67% patients, respectively. Ki-67 expression positively and negatively predicted the presence of higher-grade lesions in 40% and 88.24% patients, respectively. CONCLUSIONS: Negative p16INK4a and Ki67 immunohistochemical staining can assure absence of a higher-grade lesion in more than 85% of patients with CIN2 biopsies and can be used to prevent overtreatment of these patients. Positive IHC staining for p16INK4a and Ki-67 did not predict CIN3 in patients with CIN2 biopsies.

Focal reactive nodular gliosis: an extremely rare retinal astrocytic tumor.

Focal reactive nodular gliosis (FRNG) is an extremely rare benign retinal reactive astrocytic tumor that results from the proliferation of well-differentiated glial cells secondary to a variety of retinal conditions. We describe a case of this tumor in a 64-year-old male in association with a chorioretinal scar he has had since childhood. The symptom was sudden painful vision loss. In the clinical examination, iris rubeosis, posterior synechiae, cataract, vitreous haze and a suspected fundus mass were showed. B-scan ultrasonography demonstrated a retinal mass consistent with choroidal melanoma. The magnetic resonance imaging (MRI) showed a well-circumscribed mass with T1 hyperintensity and T2 hypointensity. Enucleation was performed and histopathologic and immunohistochemical studies confirmed the diagnosis of FRNG.

Ki-67 index after neoadjuvant endocrine therapy as a prognostic biomarker in patients with ER-positive/HER2-negative early breast cancer: a systematic review and meta-analysis.

BACKGROUND: Neoadjuvant treatment discriminates responders, but pathologic complete response is uncommon in oestrogen receptor (ER)-positive/HER2-negative early breast cancer. We aimed to assess the prognostic value of Ki-67 index after neoadjuvant endocrine therapy (NET). METHODS: We conducted a systematic literature search of PubMed, Embase, CENTRAL, and conference proceedings up to 22nd August 2023 to identify studies reporting the association of Ki-67 index after NET with recurrence-free survival (RFS) and/or overall survival (OS) in women with ER-positive/HER2-negative early breast cancer. We combined RFS and OS hazard ratios (HRs) with 95% confidence intervals (CIs). RESULTS: Twelve studies including 7897 patients were analysed. Most studies were clinical trials (n = 7547) including only postmenopausal women (n = 3953) treated with aromatase inhibitor (n = 3359). Three studies evaluated Ki-67 in a preplanned core biopsy at 2-4 weeks of NET (n = 3348), while nine evaluated Ki-67 in the surgical specimen (n = 4549) after 2-24 weeks of NET. Median follow-up ranged between 37 and 95 months for RFS and 62-84 months for OS. High Ki-67 index after NET was significantly associated with worse RFS (HR 2.48, 95% CI 1.86-3.30) and OS (HR 2.66, 95% CI 1.65-4.28). A sensitivity analysis including three studies that measured Ki-67 in a preplanned core biopsy showed similar association with RFS (HR 2.41, 95% CI 1.77-3.30). CONCLUSIONS: High Ki-67 after NET is associated with worse survival outcomes, even after a short course of NET, emphasising the prognostic value of this biomarker in women with ER-positive/HER2-negative early breast cancer.

Use of a Novel Deep Learning Open-Source Model for Quantification of Ki-67 in Breast Cancer Patients in Pakistan: A Comparative Study between the Manual and Automated Methods.

Introduction: Breast cancer is the most common cancer in women; its early detection plays a crucial role in improving patient outcomes. Ki-67 is a biomarker commonly used for evaluating the proliferation of cancer cells in breast cancer patients. The quantification of Ki-67 has traditionally been performed by pathologists through a manual examination of tissue samples, which can be time-consuming and subject to inter- and intra-observer variability. In this study, we used a novel deep learning model to quantify Ki-67 in breast cancer in digital images prepared by a microscope-attached camera. Objective: To compare the automated detection of Ki-67 with the manual eyeball/hotspot method. Place and duration of study: This descriptive, cross-sectional study was conducted at the Jinnah Sindh Medical University. Glass slides of diagnosed cases of breast cancer were obtained from the Aga Khan University Hospital after receiving ethical approval. The duration of the study was one month. Methodology: We prepared 140 digital images stained with the Ki-67 antibody using a microscope-attached camera at 10×. An expert pathologist (P1) evaluated the Ki-67 index of the hotspot fields using the eyeball method. The images were uploaded to the DeepLiif software to detect the exact percentage of Ki-67 positive cells. SPSS version 24 was used for data analysis. Diagnostic accuracy was also calculated by other pathologists (P2, P3) and by AI using a Ki-67 cut-off score of 20 and taking P1 as the gold standard. Results: The manual and automated scoring methods showed a strong positive correlation as the kappa coefficient was significant. The p value was <0.001. The highest diagnostic accuracy, i.e., 95%, taking P1 as gold standard, was found for AI, compared to pathologists P2 and P3. Conclusions: Use of quantification-based deep learning models can make the work of pathologists easier and more reproducible. Our study is one of the earliest studies in this field. More studies with larger sample sizes are needed in future to develop a cohort.

Near-infrared photoimmunotherapy in the models of hepatocellular carcinomas using cetuximab-IR700.

Epidermal growth factor receptor (EGFR) has emerged as an important therapeutic target in many cancers, and overexpression of EGFR is frequently observed in hepatocellular carcinomas (HCCs). Near-infrared photoimmunotherapy (NIR-PIT) is a new anticancer treatment that selectively damages the cell membrane of cancer cells after NIR light-induced photochemical reaction of IR700, which is bound to a targeting antibody on the cell membrane. NIR-PIT using cetuximab-IR700 has already been approved in Japan, is under review by the US Food and Drug Administration (FDA) for advanced head and neck cancers, and its safety has been established. However, EGFR has not been investigated as a target in NIR-PIT in HCCs. Here, we investigate the application of NIR-PIT using cetuximab-IR700 to HCCs using xenograft mouse models of EGFR-expressing HCC cell lines, Hep3B, HuH-7, and SNU-449. In vitro NIR-PIT using EGFR-targeted cetuximab-IR700 killed cells in a NIR light dose-dependent manner. In vivo NIR-PIT resulted in a delayed growth compared with untreated controls. In addition, in vivo NIR-PIT in both models showed histological signs of cancer cell damage, such as cytoplasmic vacuolation and nuclear dysmorphism. A significant decrease in Ki-67 positivity was also observed after NIR-PIT, indicating decreased cancer cell proliferation. This study suggests that NIR-PIT using cetuximab-IR700 has potential for the treatment of EGFR-expressing HCCs.

Intratumoral and peritumoral radiomics model based on abdominal ultrasound for predicting Ki-67 expression in patients with hepatocellular cancer.

Background: Hepatocellular cancer (HCC) is one of the most common tumors worldwide, and Ki-67 is highly important in the assessment of HCC. Our study aimed to evaluate the value of ultrasound radiomics based on intratumoral and peritumoral tissues in predicting Ki-67 expression levels in patients with HCC. Methods: We conducted a retrospective analysis of ultrasonic and clinical data from 118 patients diagnosed with HCC through histopathological examination of surgical specimens in our hospital between September 2019 and January 2023. Radiomics features were extracted from ultrasound images of both intratumoral and peritumoral regions. To select the optimal features, we utilized the t-test and the least absolute shrinkage and selection operator (LASSO). We compared the area under the curve (AUC) values to determine the most effective modeling method. Subsequently, we developed four models: the intratumoral model, the peritumoral model, combined model #1, and combined model #2. Results: Of the 118 patients, 64 were confirmed to have high Ki-67 expression while 54 were confirmed to have low Ki-67 expression. The AUC of the intratumoral model was 0.796 (0.649-0.942), and the AUC of the peritumoral model was 0.772 (0.619-0.926). Furthermore, combined model#1 yielded an AUC of 0.870 (0.751-0.989), and the AUC of combined model#2 was 0.762 (0.605-0.918). Among these models, combined model#1 showed the best performance in terms of AUC, accuracy, F1-score, and decision curve analysis (DCA). Conclusion: We presented an ultrasound radiomics model that utilizes both intratumoral and peritumoral tissue information to accurately predict Ki-67 expression in HCC patients. We believe that incorporating both regions in a proper manner can enhance the diagnostic performance of the prediction model. Nevertheless, it is not sufficient to include both regions in the region of interest (ROI) without careful consideration.

The assessment of Ki-67 for prognosis of gastroenteropancreatic neuroendocrine neoplasm patients: a systematic review and meta-analysis.

Background: Neuroendocrine neoplasm (NEN) is a group of rare tumors. Among which, gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) is the most common group. The World Health Organization (WHO) classified these tumors into three different grades (G1, G2, and G3) based on Ki-67 and mitotic rate, and updated the classification in 2019. Several previous studies proved that Ki-67 was related to tumor prognosis, but others still reported that Ki-67 had no predictive value for tumor prognosis. There are different conclusions between studies regarding the correlation between Ki-67 and tumor prognosis, and there is a lack of studies about this correlation of GEP-NENs. Further analysis is still needed to evaluate the prognostic value of Ki-67 in GEP-NENs, to provide reference for clinical decisions. Methods: A total of 303 studies were retrieved that included Ki-67, GEP-NENs, prognosis, survival, and other subject terms and keywords. We excluded studies that did not show complete Ki-67 index, number of patients and 5-year survival data available for meta-analysis, non-cohort studies, articles published before 2000 or not published in English. Fifteen studies were finally included to assess the value of Ki-67 in the prognosis of patients with GEP-NENs using a random-effects model. Results: The cumulative 5-year survival rate for GEP-NEN G1 (Ki-67 ≤2%), G2 (Ki-67 2-20%) and G3 (Ki-67 >20%) was 86%, 65%, 25% respectively. The 5-year survival rate of GEP-NEN G1 (Ki-67 <3%, first revised in WHO classification 2017, redefined WHO classification 2019) and G1 (Ki-67 ≤2%, WHO classification 2010) was 97% and 84% respectively. Conclusions: The overall prognosis of GEP-NENs patients showed a decreasing trend with the increase of Ki-67, which confirmed the significance of Ki-67 index as a prognostic marker for the prognosis of GEP-NENs. Increasing the cut-off value of Ki-67 index for G1 grade from ≤2% to <3% according to WHO classification 2019 did not significantly decrease the 5-year survival rate.

Prediction of high Ki-67 proliferation index of gastrointestinal stromal tumors based on CT at non-contrast-enhanced and different contrast-enhanced phases.

OBJECTIVES: To evaluate and analyze radiomics models based on non-contrast-enhanced computed tomography (CT) and different phases of contrast-enhanced CT in predicting Ki-67 proliferation index (PI) among patients with pathologically confirmed gastrointestinal stromal tumors (GISTs). METHODS: A total of 383 patients with pathologically proven GIST were divided into a training set (n = 218, vendor 1) and 2 validation sets (n = 96, vendor 2; n = 69, vendors 3-5). Radiomics features extracted from the most recent non-contrast-enhanced and three contrast-enhanced CT scan prior to pathological examination. Random forest models were trained for each phase to predict tumors with high Ki-67 proliferation index (Ki-67>10%) and were evaluated using the area under the receiver operating characteristic curve (AUC) and other metrics on the validation sets. RESULTS: Out of 107 radiomics features extracted from each phase of CT images, four were selected for analysis. The model trained using the non-contrast-enhanced phase achieved an AUC of 0.792 in the training set and 0.822 and 0.711 in the two validation sets, similar to models trained on different contrast-enhanced phases (p > 0.05). Several relevant features, including NGTDM Busyness and tumor size, remained predictive in non-contrast-enhanced and different contrast-enhanced images. CONCLUSION: The results of this study indicate that a radiomics model based on non-contrast-enhanced CT matches that of models based on different phases of contrast-enhanced CT in predicting the Ki-67 PI of GIST. GIST may exhibit similar radiological patterns irrespective of the use of contrast agent, and such radiomics features may help quantify these patterns to predict Ki-67 PI of GISTs. CLINICAL RELEVANCE STATEMENT: GIST may exhibit similar radiomics patterns irrespective of contrast agent; thus, radiomics models based on non-contrast-enhanced CT could be an alternative for risk stratification in GIST patients with contraindication to contrast agent. KEY POINTS: • Performance of radiomics models in predicting Ki-67 proliferation based on different CT phases is evaluated. • Non-contrast-enhanced CT-based radiomics models performed similarly to contrast-enhanced CT in risk stratification in GIST patients. • NGTDM Busyness remains stable to contrast agents in GISTs in radiomics models.

Prognostic Biomarkers of Cell Proliferation in Colorectal Cancer (CRC): From Immunohistochemistry to Molecular Biology Techniques.

Colorectal cancer (CRC) is one of the most common and severe malignancies worldwide. Recent advances in diagnostic methods allow for more accurate identification and detection of several molecular biomarkers associated with this cancer. Nonetheless, non-invasive and effective prognostic and predictive testing in CRC patients remains challenging. Classical prognostic genetic markers comprise mutations in several genes (e.g., APC, KRAS/BRAF, TGF-ß, and TP53). Furthermore, CIN and MSI serve as chromosomal markers, while epigenetic markers include CIMP and many other candidates such as SERP, p14, p16, LINE-1, and RASSF1A. The number of proliferation-related long non-coding RNAs (e.g., SNHG1, SNHG6, MALAT-1, CRNDE) and microRNAs (e.g., miR-20a, miR-21, miR-143, miR-145, miR-181a/b) that could serve as potential CRC markers has also steadily increased in recent years. Among the immunohistochemical (IHC) proliferative markers, the prognostic value regarding the patients' overall survival (OS) or disease-free survival (DFS) has been confirmed for thymidylate synthase (TS), cyclin B1, cyclin D1, proliferating cell nuclear antigen (PCNA), and Ki-67. In most cases, the overexpression of these markers in tissues was related to worse OS and DFS. However, slowly proliferating cells should also be considered in CRC therapy (especially radiotherapy) as they could represent a reservoir from which cells are recruited to replenish the rapidly proliferating population in response to cell-damaging factors. Considering the above, the aim of this article is to review the most common proliferative markers assessed using various methods including IHC and selected molecular biology techniques (e.g., qRT-PCR, in situ hybridization, RNA/DNA sequencing, next-generation sequencing) as prognostic and predictive markers in CRC.

Prognostic Value Of Basal Markers (Epidermal Growth Factor Receptor "EGFR" And Cytokeratin 5/6) Expression In Triple-Negative Invasive Breast Cancer.

Objectives: The To distinguish between basal and non-basal subtypes of triple-negative breast cancers based on epidermal growth factor receptor and cytokeratin 5/6, and to establish the association of the diagnosis with clinicopathological parameters and survival rates. Method: The retrospective study was conducted at the Clinical Oncology and Nuclear Medicine Department of Kafrelsheikh University Hospital and Tanta University Hospital, Egypt, and comprised medical records from January 2014 to December 2018 related to cases with histopathologically proven triple-negative breast cancer who had been treated and followed up for at least 5 years. The cases had been evaluated using immunohistochemistry for epidermal growth factor receptor and Cytokeratin 5/6 expression. Data related to prognostic factors, overallsurvival and disease free survival was retrieved. Data was analysed using SPSS 21. RESULTS: There were 100 patients with median age 50 years (inter-quartile range: 35-55.25 years; range: 22-69 years). There were 58(58%) pre-menopausal subjects, 15(15%) had positive family history, and 68(68%) had tumour size T2. Basal markers were noted in 74(74%) patients. Basal subtype was significantly more common in patients aged <50 years at diagnosis, premenopausal women, patients with positive nodal status, those with grade III tumours, and patients with Ki67 proliferation marker >20% (p<0.05). Tumour size, histological subtypes and lympho-vascular invasion were not significantly different between the groups (p>0.05). The basal subtype had worse disease-free survival and overall survival rates (p<0.05). CONCLUSIONS: Triple-negative breast cancer patients who expressed epidermal growth factor receptor and/or cytokeratin 5/6 were found to have poor findings, with worse disease-free survival and overall survival.

Clinico-Pathological Features and Immunohistochemical Comparison of p16, p53, and Ki-67 Expression in Muscle-Invasive and Non-Muscle-Invasive Conventional Urothelial Bladder Carcinoma.

INTRODUCTION: The identification of bladder detrusor muscle invasion in urothelial cancer is essential for prognosis and management. We studied the clinical, histological, and immunohistochemical expression of p16, p53, and Ki-67 in urothelial detrusor muscle-invasive bladder cancer (MIBC) and urothelial non-detrusor muscle-invasive bladder cancer (NMIBC) in Egyptian patients. METHODS: Sixty-two bladder urothelial cancer cases obtained through TURBT were included and divided into two groups: (MIBC, stage T2) and NMIBC (T1). Tissue blocks were recut and re-examined microscopically; then, the immunostaining of p16, p53, and Ki-67 was performed to compare both groups and evaluate the 13% cut-off for Ki-67, 20% for p53, and p16 intensity in various conditions aided by telepathology technology. RESULTS AND CONCLUSION: Hematuria was the main clinical first presentation, with no significant difference between either group. The mean age was 61.6 years, with male predominance (52 males and 10 females). The absence of papillary histological pattern was associated with a higher stage, including detrusor muscle invasion (p = 0.000). The overall average percent of p53 immunostaining was 12.9%, revealing no significant difference between MIBC and NMIBC when a cut-off of 20% was implicated. The Ki-67 expression was correlated with higher grade and muscle invasion; however, no association was found with the other two markers' expression. The negative immunostaining of p16 was associated with low grade and NMIBC in the case of the preservation of the papillary pattern. We recommend further studies on the cut-off of widely used markers and more immunohistochemical and genetic studies on the p16(INK4A), taking into consideration the histological pattern of conventional carcinomas.

Prediction of Ki-67 expression in gastrointestinal stromal tumors using radiomics of plain and multiphase contrast-enhanced CT.

OBJECTIVE: To study the value of radiomics models based on plain and multiphase contrast-enhanced CT to predict Ki-67 expression in gastrointestinal stromal tumors (GISTs). METHODS: A total of 215 patients with GISTs were retrospectively analyzed, including 150 patients in one hospital as the training set and 65 patients in another hospital as the external verification set. The tumor at the largest level of CT images was delineated as the region of interest (ROI). The maximum diameter of the ROI was defined as the tumor size. A total of 851 radiomics features were extracted from each ROI by 3D Slicer Radiomics. After dimensionality reduction, three machine learning classification algorithms including logistic regression (LR), random forest (RF), and support vector machine (SVM) were used for Ki-67 expression prediction. Using a multivariable logistic model, a nomogram was established to predict the expression of Ki-67 individually. RESULTS: Delong tests showed that the SVM models had the highest accuracy in the arterial phase (Z value 0.217-1.139) and venous phase (Z value 0.022-1.396). For the plain phase, LR and SVM models had the highest accuracy (Z value 0.874-1.824, 1.139-1.763). For the delayed phase, LR models had the highest accuracy (Z value 0.056-1.824). For the combined phase, RF models had the highest accuracy (Z value 0.232-1.978). There was no significant difference among the above models for KI-67 expression prediction (Z value 0.022-1.978). A nomogram was developed with a C-index of 0.913 (95% CI, 0.878 to 0.956). CONCLUSIONS: Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. CLINICAL RELEVANCE STATEMENT: CT radiomics could accurately predict the expression of Ki-67 in GIST, which has a great clinical value in reflecting the proliferative activity of tumor cells and helping determine whether a patient is suitable for adjuvant therapy with imatinib. KEY POINTS: • Radiomics of both plain and enhanced CT images could accurately predict the expression of Ki-67 in GIST. • For patients who were not suitable to use contrast agents, plain scan could be used as an alternative. • A radiomics nomogram was developed to allow personalized preoperative evaluation with high accuracy.

Inmunolocalización de citoqueratina 14, 19 y Ki-67 en el epitelio de pacientes con agrandamiento gingival

R E S U M E N En pacientes con ortodoncia aparecen eventos patológicos no deseados como agrandamiento gingival inducido por tratamiento de ortodoncia (AGTO) o hipertrofia gingival. El objetivo del estudio es identificar la distribución inmunohistoquímica de citoqueratina CK-14, CK-19 y Ki-67 en epitelio gingival de pacientes con AGTO. Se seleccionaron I3 pacientes divididos en: grupo control (n=6), conformado por individuos periodontalmente sanos no portadores de aparatología ortodóntica y grupo test (n=7), integrado por pacientes con AGTO. Los marcadores CK-14, CK-19 y Ki-67 fueron identificados mediante inmunohistoquímica con anticuerpos monoclonales y observados en un microscopio óptico Leica DM 500. En los pacientes del grupo test el tejido epitelial se mostró hipertrófico con pérdida en la continuidad de la membrana basal. La CK-14 y CK-19 fue positiva en el epitelio de todos los sujetos evaluados, con una expresión positiva de alta intensidad en células de la lámina basal del grupo test. El promedio de células positivas para Ki-67 en el grupo test fue de 56%. En conclusión, la CK-14, CK-19 y Ki-67 son marcadores con elevada inmunoreactividad en tejido gingival de pacientes con AGTO portadores de ortodoncia.

During orthodontic treatment, unwanted pathological events such as gingival overgrowth induced by orthodontic treatment or gingival hypertrophy may appear The objective of this study is to identify immunohistochemical distribution of cytokeratin CK-14, CK-19 and Ki-67 in the gingival epithelium of patients with gingival overgrowth induced by orthodontic treatment. Thirteen patients were selected divided into: control group (n = 6), conformed of periodontally healthy individuals without orthodontic appliances and the test group (n = 7), conformed of patients with gingival overgrowth induced by orthodontic treatment. The biomarkers CK-14, CK-19 and Ki-67 were identified by immunohistochemistry with monoclonal antibodies and observed in a Leica DM 500 optical microscope. Hypertrophic epithelial tissue with loss of continuity of the basement membrane was found in the test group patients. CK-14 and CK-19 were positive in the epithelial tissue of all the subjects evaluated, with a high intensity positive expression in the cells of the basal lamina of the test group. The average number of cells positive for Ki-67 in test group was 56%. In conclusion, CK-14, CK-19 and Ki-67 are biomarkers with high immunoreactivity in the gingival tissue of patients with gingival overgrowth induced by orthodontic treatment.

Durante o tratamento ortodôntico, eventos patológicos indesejados como o crescimento gengival induzido pelo tratamento ortodôntico (CGTO) ou hipertrofia gengival podem aparecer: O objetivo deste estudo é identificar a distribuição imuno-histoquímica das citoqueratinas CK -14, CK-19 e Ki-67 no epitélio gengival de pacientes com CGTO. Foram selecionados 13 pacientes divididos em: grupo controle (n=6), conformado por indivíduos periodontalmente saudáveis sem aparelhos ortodônticos e o grupo teste (n=7), conformado por pacientes com CGTO. Os biomarcadores CK-14, CK-19 e Ki-67 foram identificados por imuno-histoquímica com anticorpos monoclonais e observados em microscópio óptico Leica DM 500. Tecido epitelial hipertrófico com perda de continuidade da membrana basal foi encontrado nos pacientes do grupo teste. CK-14 e CK-19 foram positivos no tecido epitelial de todos os sujeitos avaliados, com expressão positiva de alta intensidade nas células da lâmina basal do grupo teste. O número médio de células positivas para Ki-67 no grupo teste foi de 56%. Em conclusão, CK-14, CK-19 e Ki-67 são biomarcadores com alta imunorreatividade no tecido gengival de pacientes com CGTO.

Prediction of Oncotype DX Recurrence Score Using Clinicopathological Variables in Estrogen Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer.

PURPOSE: Oncotype DX (ODX) is a well-validated multigene assay that is increasingly used in Korean clinical practice. This study aimed to develop a clinicopathological prediction (CPP) model for the ODX recurrence scores (RSs). METHODS: A total of 297 patients (study group, n = 175; external validation group, n = 122) with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative, T1-3N0-1M0 breast cancer, and available ODX test results were included in the study. Risk categorization as determined by ODX RSs concurred with the TAILORx study (low-risk, RS ≤ 25; high-risk, RS > 25). Univariate and multivariate logistic regression analyses were used to assess the relationships between clinicopathological variables and risk stratified by the ODX RSs. A CPP model was constructed based on regression coefficients (ß values) for clinicopathological variables significant by multivariate regression analysis. RESULTS: Progesterone receptor (PR) negativity, high Ki-67 index, and nuclear grade (NG) 3 independently predicted high-risk RS, and these variables were used to construct the CPP model. The C-index, which represented the discriminatory ability of our CPP model for predicting a high-risk RS, was 0.915 (95% confidence interval [CI], 0.859-0.971). When the CPP model was applied to the external validation group, the C-index was 0.926 (95% CI, 0.873-0.978). CONCLUSION: Our CPP model based on PR, Ki-67 index, and NG could aid in the selection of patients with breast cancer requiring an ODX test.