Clinical and Paraclinical Considerations Regarding ki67's Role in the Management of Differentiated Thyroid Carcinoma-A Literature Review.

Background and Objectives: The ki67 nuclear protein is a tool for diagnosis and prognosis in oncology that is used to evaluate cell proliferation. Differentiated thyroid carcinoma is usually a slow-growing neoplasm, the most common type being the papillary form. Some clinical and pathological aspects may predict aggressive behaviour. There are reported cases of recurrence without clinico-pathological findings of aggressiveness. To obtain better predictions of the disease outcome in thyroid carcinoma, many immunohistochemical markers have been studied. The aim of this narrative literature review is to identify the benefits that ki67 may add to the management of patients with differentiated thyroid carcinoma, according to the latest evidence. Materials and Methods: We performed a search on the PubMed and Google Scholar databases using controlled vocabulary and keywords to find the most suitable published articles. A total number of sixty-eight items were identified, and five other articles were selected from other sources. After refining the selection, the inclusion criteria and exclusion criteria were applied, and a total number of twenty-nine articles were included in this literature review. Results and Discussion: The studies consist of retrospective studies (89.66%), case reports (6.9%) and literature reviews (3.45%), evaluating the role, implications and other parameters of ki67 as a diagnostic and/or prognostic tool. The statistical correlations between ki67 and other features were systematized as qualitative results of this review in order to improve the treatment strategies presented in the included articles. Conclusions: The included studies present converging data regarding most of the aspects concerning ki67. The ki67 proliferation index is a diagnostic/prognostic tool of interest in differentiated thyroid carcinoma and a good predictor of disease-free survival, disease recurrence and metastatic development. Prospective studies on large cohorts may add value for ki67 as a specific tool in the management strategy of differentiated thyroid carcinoma.

Significance of Staining Intensity in Ki-67 Proliferation Index in Meningiomas, and a Critical Review of the Literature on Proliferation Index Assessment.

OBJECTIVE: Meningioma is the most common primary adult intracranial neoplasm, and proliferation indices (PI) rise with increasing grade from WHO CNS grade 1 to 3. Ki-67 immunohistochemistry (IHC) poses a variety of technical and interpretative challenges. Here, we specifically investigated the staining intensity and its effect on interpretation and final diagnosis. METHODS: 124 high and low-grade meningiomas of various grades were blindly evaluated using different counting strategies (CS) based on the staining intensity of the nuclei as darkest (CS1), darkest+intermediate (CS2), and any staining (CS3) in hot-spots (HS) and in the context of overall proliferative activity (OPA). RESULT: CSs in HS, OPA, and their average results were significantly different between low-grade and high-grade groups. PI obtained using CS3 yielded results that matched best with values expected for the corresponding WHO grade. CS had a profound impact on whether a LG meningioma would be diagnosed as one with a "high proliferation index." CONCLUSION: A large body of work exists on the counting methods, clinically significant cut-off values, and inter- and intra-observer variability for Ki-67 PI interpretation. We show that Ki-67 IHC staining intensity, which to our knowledge has not been previously systematically investigated, can have a significant effect on PI interpretation in settings that influence diagnostic and clinical management decisions.

Clinicopathological characteristics and BRCA1/BRCA2 pathogenic variants of patients with breast cancer.

Although BRCA genes are well-known breast cancer genes, the clinicopathological features of breast cancer patients carrying BRCA1/2 pathogenic variants have not been adequately defined. The goals of this study were to determine the distribution of BRCA1/2 variants in the Turkish population and its correlation with clinicopathological features. Clinical data of 151 women who underwent BRCA1/2 gene testing at Mersin University Medical Faculty Hospital between 2016 and 2019 were retrospectively analyzed. BRCA1/2 variants were detected as pathogenic (n = 11), variants of uncertain significance (n = 5), likely benign (n = 3), and benign (n = 81) in breast cancer cases. The BRCA1/2 pathogenic variant carriers had a higher histological grade, rate of triple- negative type, Ki-67 proliferation index, and rate of no special type carcinoma than the group without mutation (p = 0.03, 0.01, 0.04, and 0.02 respectively). We analyzed the distribution of variants we detected in women living in our region and found that pathogenic variants in patients with breast cancer were associated with high histological grade, triple-negative type, high Ki-67 proliferation index, and histological type. Studies in diverse populations are needed to establish a clinicopathological relationship with variants more easily.

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index.

BACKGROUND: The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. PURPOSE: To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. MATERIAL AND METHODS: The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. RESULTS: The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. CONCLUSION: Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

T1 Pre- and Post-contrast Delta Histogram Parameters in Predicting the Grade of Meningioma and Their Relationship to Ki-67 Proliferation Index.

RATIONALE AND OBJECTIVES: To explore the feasibility of delta histogram parameters (including absolute delta histogram parameters (AdHP) and relative delta histogram parameters (RdHP)) in predicting the grade of meningioma and to further investigate whether delta histogram parameters correlate with the Ki-67 proliferation index. METHODS: 92 patients with meningioma who underwent MRI examination (including T1-weighted (T1) and contrast-enhanced T1-weighted images (T1C)) were enrolled in this retrospective study. A total of 46 low-grade cases formed the low-grade group (grade 1, LGM), and a total of 46 high-grade cases formed the high-grade group (38 grade 2, 8 grade 3, HGM). Histogram parameters (HP) of T1 and T1C were extracted. Subsequently, morphological MRI features, AdHP (AdHP=T1CHP-T1HP), and RdHP (RdHP=(T1CHP-T1HP)/T1HP) were recorded and compared, respectively. Binary logistic regression analysis was used to obtain combined performance of the significant parameters. Diagnostic performance was identified by ROC. Spearman's correlation coefficients were taken to assess the relationship between delta histogram parameters and the Ki-67 proliferation index. RESULTS: In morphological MRI features, HGM is more prone to lobulation and necrosis/cystic changes (all p < 0.05). In delta histogram parameters, HGM exhibits higher mean, Perc.01, Perc.25, Perc.50, Perc.75, Perc.99, SD, and variance of AdHP, maximum, mean, Perc.25, Perc.50, Perc.75, and Perc.99 of RdHP, compared to LGM (all p < 0.00357). The optimal predictive performance was obtained by combining morphological MRI features and delta histogram parameters with an AUC of 0.945. Significant correlations were observed between significant delta histogram parameters and the Ki-67 proliferation index (all p < 0.05). CONCLUSION: Delta histogram parameter is a promising potential biomarker, which may be helpful in noninvasive predicting the grade and proliferative activity of meningioma.

Prognostic utility and characteristics of MIB-1 labeling index as a proliferative activity marker in childhood low-grade glioma: a retrospective observational study.

PURPOSE: The prognostic utility of MIB-1 labeling index (LI) in pediatric low-grade glioma (PLGG) has not yet conclusively been described. We assess the correlation of MIB-1 LI and tumor growth velocity (TGV), aiming to contribute to the understanding of clinical implications and the predictive value of MIB-1 LI as an indicator of proliferative activity and progression-free survival (PFS) in PLGG. METHODS: MIB-1 LI of a cohort of 172 nonependymal PLGGs were comprehensively characterized. Correlation to TGV, assessed by sequential MRI-based three-dimensional volumetry, and PFS was analyzed. RESULTS: Mean MIB-1 LI accounted for 2.7% (range: < 1-10) and showed a significant decrease to 1.5% at secondary surgery (p = .0013). A significant difference of MIB-1 LI in different histopathological types and a correlation to tumor volume at diagnosis could be shown. Linear regression analysis showed a correlation between MIB-1 LI and preoperative TGV (R2 = .55, p < .0001), while correlation to TGV remarkably decreased after incomplete resection (R2 = .08, p = .013). Log-rank test showed no association of MIB-1 LI and 5-year PFS after incomplete (MIB-1 LI > 1 vs ≤ 1%: 48 vs 46%, p = .73) and gross-total resection (MIB-1 LI > 1 vs ≤ 1%: 89 vs 95%, p = .75). CONCLUSION: These data confirm a correlation of MIB-1 LI and radiologically detectable TGV in PLGG for the first time. Compared with preoperative TGV, a crucially decreasing correlation of MIB-1 LI and TGV after surgery may result in limited prognostic capability of MIB-1 LI in PLGG.

Can Shockwave Treatment Elicit a Molecular Response to Enhance Clinical Outcomes in Pressure Ulcers? The SHOck Waves in wouNds Project.

Wound healing requires the coordinated interaction of dermis cells, the proper deposition of extracellular matrix, re-epithelialization, and angiogenesis. Extracorporeal shock wave (ESW) is a promising therapeutic modality for chronic wounds. This study determined the biological mechanisms activated under ESW, facilitating the healing of pressure ulcers (PUs). A group of 10 patients with PUs received two sessions of radial ESW (300 + 100 pulses, 2.5 bars, 0.15 mJ/mm2, 5 Hz). Histomorphological and immunocytochemical assessments were performed on tissue sections obtained from the wound edges before the ESW (M0) and after the first (M1) and second (M2) ESW. The proliferation index of keratinocytes and fibroblasts (Ki-67), the micro-vessels' density (CD31), and the number of myofibroblasts (α-SMA) were evaluated. The involvement of the yes-associated protein (YAP1) in sensing mechanical strain, and whether the nuclear localization of YAP1, was shown. The increased proliferative activity of epidermal cells and skin fibroblasts and the increased number of myofibroblasts, often visible as integrated cell bands, were also demonstrated as an effect of wound exposure to an ESW. The results indicate that the major skin cells, keratinocytes, and fibroblasts are mechanosensitive. They intensify proliferation and extracellular matrix remodeling in response to mechanical stress. A significant improvement in clinical wound parameters was also observed.

Immunohistochemical double nuclear staining for cell-specific automated quantification of the proliferation index - A promising diagnostic aid for melanocytic lesions.

AIMS: Pathologists often use immunohistochemical staining of the proliferation marker Ki67 in their diagnostic assessment of melanocytic lesions. However, the interpretation of Ki67 can be challenging. We propose a new workflow to improve the diagnostic utility of the Ki67-index. In this workflow, Ki67 is combined with the melanocytic tumour-cell marker SOX10 in a Ki67/SOX10 double nuclear stain. The Ki67-index is then quantified automatically using digital image analysis (DIA). The aim of this study was to optimise and test three different multiplexing methods for Ki67/SOX10 double nuclear staining. METHODS: Multiplex immunofluorescence (mIF), multiplex immunohistochemistry (mIHC), and multiplexed immunohistochemical consecutive staining on single slide (MICSSS) were optimised for Ki67/SOX10 double nuclear staining. DIA applications were designed for automated quantification of the Ki67-index. The methods were tested on a pilot case-control cohort of benign and malignant melanocytic lesions (n = 23). RESULTS: Using the Ki67/SOX10 double nuclear stain, malignant melanocytic lesions could be completely distinguished from benign lesions by the Ki67-index. The Ki67-index cut-offs were 1.8% (mIF) and 1.5% (mIHC and MICSSS). The AUC of the automatically quantified Ki67-index based on double nuclear staining was 1.0 (95% CI: 1.0;1.0), whereas the AUC of conventional Ki67 single-stains was 0.87 (95% CI: 0.71;1.00). CONCLUSIONS: The novel Ki67/SOX10 double nuclear stain highly improved the diagnostic precision of Ki67 interpretation. Both mIHC and mIF were useful methods for Ki67/SOX10 double nuclear staining, whereas the MICSSS method had challenges in the current setting. The Ki67/SOX10 double nuclear stain shows potential as a valuable diagnostic aid for melanocytic lesions.

Automated AI-based grading of neuroendocrine tumors using Ki-67 proliferation index: comparative evaluation and performance analysis.

Early detection is critical for successfully diagnosing cancer, and timely analysis of diagnostic tests is increasingly important. In the context of neuroendocrine tumors, the Ki-67 proliferation index serves as a fundamental biomarker, aiding pathologists in grading and diagnosing these tumors based on histopathological images. The appropriate treatment plan for the patient is determined based on the tumor grade. An artificial intelligence-based method is proposed to aid pathologists in the automated calculation and grading of the Ki-67 proliferation index. The proposed system first performs preprocessing to enhance image quality. Then, segmentation process is performed using the U-Net architecture, which is a deep learning algorithm, to separate the nuclei from the background. The identified nuclei are then evaluated as Ki-67 positive or negative based on basic color space information and other features. The Ki-67 proliferation index is then calculated, and the neuroendocrine tumor is graded accordingly. The proposed system's performance was evaluated on a dataset obtained from the Department of Pathology at Meram Faculty of Medicine Hospital, Necmettin Erbakan University. The results of the pathologist and the proposed system were compared, and the proposed system was found to have an accuracy of 95% in tumor grading when compared to the pathologist's report.

Use of Novel Open-Source Deep Learning Platform for Quantification of Ki-67 in Neuroendocrine Tumors - Analytical Validation.

Background: Neuroendocrine tumors (NETs) represent a diverse group of neoplasms that arise from neuroendocrine cells, with Ki-67 immunostaining serving as a crucial biomarker for assessing tumor proliferation and prognosis. Accurate and reliable quantification of Ki-67 labeling index is essential for effective clinical management. Methods: We aimed to evaluate the performance of open-source/open-access deep learning cloud-native platform, DeepLIIF (https://deepliif.org), for the quantification of Ki-67 expression in gastrointestinal neuroendocrine tumors and compare it with the manual quantification method. Results: Our results demonstrate that the DeepLIIF quantification of Ki-67 in NETs achieves a high degree of accuracy with an intraclass correlation coefficient (ICC) = 0.885 with 95% CI (0.848-0.916) which indicates good reliability when compared to manual assessments by experienced pathologists. DeepLIIF exhibits excellent intra- and inter-observer agreement and ensures consistency in Ki-67 scoring. Additionally, DeepLIIF significantly reduces analysis time, making it a valuable tool for high-throughput clinical settings. Conclusion: This study showcases the potential of open-source/open-access user-friendly deep learning platforms, such as DeepLIIF, for the quantification of Ki-67 in neuroendocrine tumors. The analytical validation presented here establishes the reliability and robustness of this innovative method, paving the way for its integration into routine clinical practice. Accurate and efficient Ki-67 assessment is paramount for risk stratification and treatment decisions in NETs and AI offers a promising solution for enhancing diagnostic accuracy and patient care in the field of neuroendocrine oncology.

ADC histogram parameters differentiating atypical from transitional meningiomas: correlation with Ki-67 proliferation index.

BACKGROUND: Preoperative differentiation of atypical meningioma (AtM) from transitional meningioma (TrM) is critical to clinical treatment. PURPOSE: To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating AtM from TrM and its correlation with the Ki-67 proliferation index (PI). METHODS: Clinical, imaging, and pathological data of 78 AtM and 80 TrM were retrospectively collected. Regions of interest (ROIs) were delineated on axial ADC images using MaZda software and histogram parameters (mean, variance, skewness, kurtosis, 1st percentile [ADCp1], 10th percentile [ADCp10], 50th percentile [ADCp50], 90th percentile [ADCp90], and 99th percentile [ADCp99]) were generated. The Mann-Whitney U test was used to compare the differences in histogram parameters between the two groups; receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy in differentiating AtM from TrM preoperatively. The correlation between histogram parameters and Ki-67 PI was analyzed. RESULTS: All histogram parameters of AtM were lower than those of TrM, and the variance, skewness, kurtosis, ADCp90, and ADCp99 were significantly different (P < 0.05). Combined ADC histogram parameters (variance, skewness, kurtosis, ADCp90, and ADCp99) achieved the best diagnostic performance for distinguishing AtM from TrM. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.800%, 76.25%, 67.95%, 70.15%, 70.93%, and 73.61%, respectively. All histogram parameters were negatively correlated with Ki-67 PI (r = -0.012 to -0.293). CONCLUSION: ADC histogram analysis is a potential tool for non-invasive differentiation of AtM from TrM preoperatively, and ADC histogram parameters were negatively correlated with the Ki-67 PI.

Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.

AIMS: The International Medullary Thyroid Carcinoma Grading System, introduced in 2022, mandates evaluation of the Ki67 proliferation index to assign a histological grade for medullary thyroid carcinoma. However, manual counting remains a tedious and time-consuming task. METHODS AND RESULTS: We aimed to evaluate the performance of three other counting techniques for the Ki67 index, eyeballing by a trained experienced investigator, a machine learning-based deep learning algorithm (DeepLIIF) and an image analysis software with internal thresholding compared to the gold standard manual counting in a large cohort of 260 primarily resected medullary thyroid carcinoma. The Ki67 proliferation index generated by all three methods correlate near-perfectly with the manual Ki67 index, with kappa values ranging from 0.884 to 0.979 and interclass correlation coefficients ranging from 0.969 to 0.983. Discrepant Ki67 results were only observed in cases with borderline manual Ki67 readings, ranging from 3 to 7%. Medullary thyroid carcinomas with a high Ki67 index (≥ 5%) determined using any of the four methods were associated with significantly decreased disease-specific survival and distant metastasis-free survival. CONCLUSIONS: We herein validate a machine learning-based deep-learning platform and an image analysis software with internal thresholding to generate accurate automatic Ki67 proliferation indices in medullary thyroid carcinoma. Manual Ki67 count remains useful when facing a tumour with a borderline Ki67 proliferation index of 3-7%. In daily practice, validation of alternative evaluation methods for the Ki67 index in MTC is required prior to implementation.

Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomes.

OBJECTIVE: The clinical behavior of meningiomas is not entirely captured by its designated WHO grade, therefore other factors must be elucidated that portend increased tumor aggressiveness and associated risk of recurrence. In this study, the authors identify multiparametric MRI radiomic signatures of meningiomas using Ki-67 as a prognostic marker of clinical outcomes independent of WHO grade. METHODS: A retrospective analysis was conducted of all resected meningiomas between 2012 and 2018. Preoperative MR images were used for high-throughput radiomic feature extraction and subsequently used to develop a machine learning algorithm to stratify meningiomas based on Ki-67 indices < 5% and ≥ 5%, independent of WHO grade. Progression-free survival (PFS) was assessed based on machine learning prediction of Ki-67 strata and compared with outcomes based on histopathological Ki-67. RESULTS: Three hundred forty-three meningiomas were included: 291 with WHO grade I, 43 with grade II, and 9 with grade III. The overall rate of recurrence was 19.8% (15.1% in grade I, 44.2% in grade II, and 77.8% in grade III) over a median follow-up of 28.5 months. Grade II and III tumors had higher Ki-67 indices than grade I tumors, albeit tumor and peritumoral edema volumes had considerable variation independent of meningioma WHO grade. Forty-six high-performing radiomic features (1 morphological, 7 intensity-based, and 38 textural) were identified and used to build a support vector machine model to stratify tumors based on a Ki-67 cutoff of 5%, with resultant areas under the curve of 0.83 (95% CI 0.78-0.89) and 0.84 (95% CI 0.75-0.94) achieved for the discovery (n = 257) and validation (n = 86) data sets, respectively. Comparison of histopathological Ki-67 versus machine learning-predicted Ki-67 showed excellent performance (overall accuracy > 80%), with classification of grade I meningiomas exhibiting the greatest accuracy. Prediction of Ki-67 by machine learning classifier revealed shorter PFS for meningiomas with Ki-67 indices ≥ 5% compared with tumors with Ki-67 < 5% (p < 0.0001, log-rank test), which corroborates divergent patient outcomes observed using histopathological Ki-67. CONCLUSIONS: The Ki-67 proliferation index may serve as a surrogate marker of increased meningioma aggressiveness independent of WHO grade. Machine learning using radiomic feature analysis may be used for the preoperative prediction of meningioma Ki-67, which provides enhanced analytical insights to help improve diagnostic classification and guide patient-specific treatment strategies.

Calcium-Sensing Receptor Expression in Breast Cancer.

The calcium-sensing receptor (CaSR) plays a crucial role in maintaining the balance of calcium in the body. Altered signaling through the CaSR has been linked to the development of various tumors, such as colorectal and breast tumors. This retrospective study enrolled 79 patients who underwent surgical removal of invasive breast carcinoma of no special type (NST) to explore the expression of the CaSR in breast cancer. The patients were categorized based on age, tumor size, hormone receptor status, HER2 status, Ki-67 proliferation index, tumor grade, and TNM staging. Immunohistochemistry was conducted on core needle biopsy samples to assess CaSR expression. The results revealed a positive correlation between CaSR expression and tumor size, regardless of the tumor surrogate subtype (p = 0.001). The expression of ER exhibited a negative correlation with CaSR expression (p = 0.033). In contrast, a positive correlation was observed between CaSR expression and the presence of HER2 receptors (p = 0.002). Increased CaSR expression was significantly associated with lymph node involvement and the presence of distant metastasis (p = 0.001 and p = 0.038, respectively). CaSR values were significantly higher in the patients with increased Ki-67 (p = 0.042). Collectively, higher CaSR expression in breast cancer could suggest a poor prognosis and treatment outcome regardless of the breast cancer subtype.

Apparent diffusion coefficient values effectively predict cell proliferation and determine oligodendroglioma grade.

This study aims to evaluate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) values in differentiating oligodendroglioma of various grades and explore the correlation between ADC and Ki-67. The preoperative MRI data of 99 patients with World Health Organization (WHO) grades 2 (n = 42) and 3 (n = 57) oligodendroglioma confirmed by surgery and pathology were retrospectively analyzed. Conventional MRI features, ADCmean, ADCmin, and normalized ADC (nADC) were compared between the two groups. A receiver operating characteristic curve was used to evaluate each parameter's diagnostic efficacy in differentiating the two tumor types. Each tumor's Ki-67 proliferation index was also measured to explore its relationship with the ADC value. Compared with WHO2 grade tumors, WHO3 grade tumors had a larger maximum diameter and more significant cystic degeneration/necrosis, edema, and moderate/severe enhancement (all P < 0.05). The ADCmin, ADCmean, and nADC values of the WHO3 and WHO2 grade tumors were significantly different, and the ADCmin value most accurately distinguished the two tumor types, yielding an area under the curve value of 0.980. When 0.96 × 10-3 mm2/s was used as the differential diagnosis threshold, the sensitivity, specificity, and accuracy of the two groups were 100%, 93.00%, and 96.96%, respectively. The ADCmin (r = -0.596), ADCmean (r = - 0.590), nADC (r = - 0.577), and Ki-67 proliferation index values had significantly negative correlations (all P < 0.05). Conventional MRI features and ADC values are beneficial in the noninvasive prediction of the WHO grade and tumor proliferation rate of oligodendroglioma.

Baseline tumor growth rate highlights the heterogeneity of well differentiated gastroenteropancreatic neuroendocrine tumors and predicts for increases in Ki67 index over time.

Refined risk stratification for gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has the potential to improve comparisons of study populations across clinical trials and facilitate drug development. Tumor growth rate (TGR) is a radiological metric with demonstrated prognostic value in well differentiated grade 1 and 2 (G1-2) GEP-NETs, but little is known about TGR in G3 NETs. In this retrospective study of 48 patients with advanced G1-3 GEP-NET, we calculated baseline TGR (TGR0 ) from radiological images of metastases acquired prior to first-line therapy and evaluated its association with disease characteristics and outcomes. The median pretreatment Ki67 proliferation index for G1-3 tumors combined was 5% (range = 0.1%-52%) and median TGR0 was 4.8%/month (m) (range = 0%-45.9%/m). TGR0 correlated with pretreatment Ki67 across G1-3 pooled and within G3 GEP-NET. Patients with higher TGR0 (>11.7%/m) tumors, which were primarily G3 pancreatic NETs, exhibited decreased time to first therapy (median, 2.2 vs. 5.3 months; p = .03) and shorter overall survival (median, 4.1 years vs. not reached; p = .003). Independent of therapies given, higher TGR0 GEP-NETs experienced a greater incidence of Ki67 increase (100 vs. 50%; p = .02) and greater magnitude of Ki67 change (median, 14.0 vs. 0.1%; p = .04) upon serial biopsy. Importantly, TGR0 , but not grade, predicted for future Ki67 increase in this series. Given the heterogeneity of well differentiated GEP-NETs, future clinical trials may benefit from stratification for TGR0 , particularly in G1-2 tumors, in which TGR0 does not correlate with Ki67. TGR0 has the potential to noninvasively identify patients with previously undiagnosed grade progression and those in whom more or less frequent monitoring may be appropriate. Additional research is needed to determine the prognostic and predictive value of TGR0 in larger and more homogeneously treated cohorts, and to ascertain if post-treatment TGR has value in previously treated patients starting a new line of therapy.

Diagnostic work-up and advancement in the diagnosis of gastroenteropancreatic neuroendocrine neoplasms.

Neuroendocrine neoplasms (NENs) are a heterogeneous group of neoplasms ranging from well-differentiated, slowly growing tumors to poorly differentiated carcinomas. These tumors are generally characterized by indolent course and quite often absence of specific symptoms, thus eluding diagnosis until at an advanced stage. This underscores the importance of establishing a prompt and accurate diagnosis. The gold-standard remains histopathology. This should contain neuroendocrine-specific markers, such as chromogranin A; and also, an estimate of the proliferation by Ki-67 (or MIB-1), which is pivotal for treatment selection and prognostication. Initial work-up involves assessment of serum Chromogranin A and in selected patients gut peptide hormones. More recently, the measurement of multiple NEN-related transcripts, or the detection of circulating tumor cells enhanced our current diagnostic armamentarium and appears to supersede historical serum markers, such as Chromogranin A. Standard imaging procedures include cross-sectional imaging, either computed tomography or magnetic resonance, and are combined with somatostatin receptor scintigraphy. In particular, the advent of 111In-DTPA-octreotide and more recently PET/CT and 68Ga-DOTA-Octreotate scans revolutionized the diagnostic landscape of NENs. Likewise, FDG PET represents an invaluable asset in the management of high-grade neuroendocrine carcinomas. Lastly, endoscopy, either conventional, or more advanced modalities such as endoscopic ultrasound, capsule endoscopy and enteroscopy, are essential for the diagnosis and staging of gastroenteropancreatic neuroendocrine neoplasms and are routinely integrated in clinical practice. The complexity and variability of NENs necessitate the deep understanding of the current diagnostic strategies, which in turn assists in offering optimal patient-tailored treatment. The current review article presents the diagnostic work-up of GEP-NENs and all the recent advances in the field.

Expression of substance P, neurokinin 1 receptor, Ki-67 and pyruvate kinase M2 in hormone receptor negative breast cancer and evaluation of impact on overall survival.

BACKGROUND: Chronic inflammation is a hallmark of cancer, and it can be stimulated by many factors. Substance P (SP), through binding to neurokinin 1 receptor (NK1R), and pyruvate kinase M2 (PKM2) play critical roles in cancer development and progression via modulating the tumor microenvironment. This study aimed to investigate the prognostic significance of SP and PKM2 in combination with NK1R and Ki-67 in hormone receptor negative (HR-ve) breast cancer. METHODS: Immunohistochemical expression levels of SP, NK1R, PKM2, and Ki-67 were measured in 144 paraffin-embedded breast cancer tissues (77 h -ve and 67 h + ve). SP, NK1R, and PKM2 were scored semiquantitatively, while Ki-67 was obtained by the percentage of total number of tumor cells with nuclear staining. The optimal cutoff value for SP, NK1R, PKM2, and Ki-67 were assessed by Cutoff Finder. RESULTS: High SP expression in HR -ve breast cancer was associated with TNM stage (p = 0.020), pT stage (p = 0.035), pN stage (p = 0.002), axillary lymph node metastasis (p = 0.003), and NK1R expression level (p = 0.010). In HR + ve breast cancer, SP expression was associated with HER2 status (p = 0.001) and PKM2 expression level (p = 0.012). Regarding PKM2 expression level, it significantly associated with HER2 status (p = 0.001) and history of DCIS (p = 0.046) in HR-ve tumors, and with HER2 status (p < 0.001) and SP expression level (p = 0.012) in HR + ve tumors. Survival analysis revealed that high SP level negatively impacted overall survival in HR-ve tumors that had low NK1R level (p = 0.021). Moreover, high SP negatively impacted overall survival in HR-ve tumors that had low Ki-67 level (p = 0.005). High PKM2 negatively impacted overall survival in HR-ve cases with low SP (p = 0.047). CONCLUSION: Combined expression levels of SP with NK1R or Ki-67, and PKM2 with SP could be used to predict survival in breast cancer patients with HR-ve tumors. Our findings suggest a role of SP/NK1R pathway and PKM2 in HR-ve breast cancer pathogenesis which should be further investigated to unveil the underlying molecular mechanisms.

Metallothionein expression in feline injection site fibrosarcomas.

BACKGROUND: Feline injection site fibrosarcoma is an aggressive and infiltrative tumour arising in the background of chronic inflammation. The aim of this study was to evaluate the expression of metallothionein (I-II) in feline injection site fibrosarcomas and to assess its possible relationships with Ki67 index, inflammation score and tumour grade. The study included 40 feline fibrosarcomas, located in the common injection sites (i.e., interscapular area, thigh, flank), constituting archival diagnostic specimens collected between 2019-2020. Tumours were graded histologically according to the newly proposed soft-tissue sarcoma grading system in cats. Immunohistochemistry was performed to evaluate the expression of Ki67 and metallothionein in tumour cells. RESULTS: The cytoplasmic and sometimes nuclear expression of metallothionein was observed in all tumours grade I, 66.67% of tumours grade II and 55% of tumours grade III. The expression of metallothionein was negatively correlated with tumour grade and inflammation score, while the Ki67 index was positively correlated with tumour grade, inflammation score and necrosis score. CONCLUSION: The downregulation of MT expression in feline injection site fibrosarcomas seems to be connected with an increase in the inflammatory infiltration, hence tumour progression. This is the first study describing metallothionein expression in feline injection site fibrosarcomas.

Microstructural parameters from DW-MRI for tumour characterization and local recurrence prediction in particle therapy of skull-base chordoma.

BACKGROUND: Quantitative imaging such as Diffusion-Weighted MRI (DW-MRI) can be exploited to non-invasively derive patient-specific tumor microstructure information for tumor characterization and local recurrence risk prediction in radiotherapy. PURPOSE: To characterize tumor microstructure according to proliferative capacity and predict local recurrence through microstructural markers derived from pre-treatment conventional DW-MRI, in skull-base chordoma (SBC) patients treated with proton (PT) and carbon ion (CIRT) radiotherapy. METHODS: Forty-eight patients affected by SBC, who underwent conventional DW-MRI before treatment and were enrolled for CIRT (n = 25) or PT (n = 23), were retrospectively selected. Clinically verified local recurrence information (LR) and histological information (Ki-67, proliferation index) were collected. Apparent diffusion coefficient (ADC) maps were calculated from pre-treatment DW-MRI and, from these, a set of microstructural parameters (cellular radius R, volume fraction vf, diffusion D) were derived by applying a fine-tuning procedure to a framework employing Monte Carlo simulations on synthetic cell substrates. In addition, apparent cellularity (ρapp ) was estimated from vf and R for an easier clinical interpretation. Histogram-based metrics (mean, median, variance, entropy) from estimated parameters were considered to investigate differences (Mann-Whitney U-test, α = 0.05) in estimated tumor microstructure in SBCs characterized by low or high cell proliferation (Ki-67). Recurrence-free survival analyses were also performed to assess the ability of the microstructural parameters to stratify patients according to the risk of local recurrence (Kaplan-Meier curves, log-rank test α = 0.05). RESULTS: Refined microstructural markers revealed optimal capabilities in discriminating patients according to cell proliferation, achieving best results with mean values (p-values were 0.0383, 0.0284, 0.0284, 0.0468, and 0.0088 for ADC, R, vf, D, and ρapp, respectively). Recurrence-free survival analyses showed significant differences between populations at high and low risk of local recurrence as stratified by entropy values of estimated microstructural parameters (p = 0.0110). CONCLUSION: Patient-specific microstructural information was non-invasively derived providing potentially useful tools for SBC treatment personalization and optimization in particle therapy.